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Prologue to Cancer – e-book Volume One – Where are we in this journey?

Prologue to Cancer – e-book Volume One – Where are we in this journey?

Author and Curator: Larry H. Bernstein, MD, FCAP

Article ID #128: Prologue to Cancer – e-book Volume One – Where are we in this journey? Published on 4/13/2014

WordCloud Image Produced by Adam Tubman

Consulting Reviewer and Contributor:  Jose Eduardo de Salles Roselino, MD

 

LH Bernstein

LH Bernstein

Jose Eduardo de Salles Roselino

LES Roselino

 

 

This is a preface to the fourth in the ebook series of Leaders in Pharmaceutical Intelligence, a collaboration of experienced doctorate medical and pharmaceutical professionals.  The topic is of great current interest, and it entails a significant part of current medical expenditure by a group of neoplastic diseases that may develop at different periods in life, and have come to supercede infections or even eventuate in infectious disease as an end of life event.  The articles presented are a collection of the most up-to-date accounts of the state of a now rapidly emerging field of medical research that has benefitted enormously by progress in immunodiagnostics,  radiodiagnostics, imaging, predictive analytics, genomic and proteomic discovery subsequent to the completion of the Human Genome Project, advances in analytic methods in qPCR, gene sequencing, genome mapping, signaling pathways, exome identification, identification of therapeutic targets in inhibitors, activators, initiators in the progression of cell metabolism, carcinogenesis, cell movement, and metastatic potential.  This story is very complicated because we are engaged in trying to evoke from what we would like to be similar clinical events, dissimilar events in their expression and classification, whether they are within the same or different anatomic class.  Thus, we are faced with constructing an objective evidence-based understanding requiring integration of several disciplinary approaches to see a clear picture.  The failure to do so creates a high risk of failure in biopharmaceutical development.

The chapters that follow cover novel and important research and development in cancer related research, development, diagnostics and treatment, and in balance, present a substantial part of the tumor landscape, with some exceptions.  Will there ever be a unifying concept, as might be hoped for? I certainly can’t see any such prediction on the horizon.  Part of the problem is that disease classification is a human construct to guide us, and so are treatments that have existed and are reexamined for over 2,000 years.  In that time, we have changed, our afflictions have been modified, and our environment has changed with respect to the microorganisms within and around us, viruses, the soil, and radiation exposure, and the impacts of war and starvation, and access to food.  The outline has been given.  Organic and inorganic chemistry combined with physics has given us a new enterprise in biosynthetics that is and will change our world.  But let us keep in mind that this is a human construct, just as drug target development is such a construct, workable with limitations.

What Molecular Biology Gained from Physics

We need greater clarity and completeness in defining the carcinogenetic process.  It is the beginning, but not the end.  But we must first examine the evolution of the scientific structure that leads to our present understanding. This was preceded by the studies of anatomy, physiology, and embryology that had to occur as a first step, which was followed by the researches into bacteriology, fungi, sea urchins and the evolutionary creatures that could be studied having more primary development in scale.  They are still major objects of study, with the expectation that we can derive lessons about comparative mechanisms that have been passed on through the ages and have common features with man.  This became the serious intent of molecular biology, the discipline that turned to find an explanation for genetics, and to carry out controlled experiments modelled on the discipline that already had enormous success in physics, mathematics, and chemistry. In 1900, when Max Planck hypothesized that the frequency of light emitted by the black body depended on the frequency of the oscillator that emitted it, it had important ramifications for chemistry and biology (See Appendix II and Footnote 1, Planck equation, energy and oscillation).  The leading idea is to search below the large-scale observations of classical biology.

The central dogma of molecular biology where genetic material is transcribed into RNA and then translated into protein, provides a starting point, but the construct is undergoing revision in light of emerging novel roles for RNA and signaling pathways.   The term, coined by Warren Weaver (director of Natural Sciences for the Rockefeller Foundation), who observed an emergence of significant change given recent advances in fields such as X-ray crystallography. Molecular biology also plays important role in understanding formations, actions, regulations of various parts of cellswhich can be used efficiently for targeting new drugs, diagnosis of disease, physiology of the Cell. The Nobel Prize in Physiology or Medicine in 1969 was shared by Max Delbrück, Alfred D. Hershey, Salvador E. Luria, whose work with viral replication gave impetus to the field.  Delbruck was a physicist who trained in Copenhagen under Bohr, and specifically committed himself to a rigor in biology, as was in physics.

Dorothy Hodgkin protein crystallography

Dorothy Hodgkin protein crystallography

Rosalind Franlin crystallographer double helix

Rosalind Franlin
crystallographer
double helix

 Max Delbruck         molecular biology

Max Delbruck        
molecular biology

Max Planck

Max Planck Quantum Physics

 

 

 

We then stepped back from classical (descriptive) physiology, with the endless complexity, to molecular biology.  This led us to the genetic code, with a double helix model.  It has recently been found insufficiently explanatory, with the recent construction of triplex and quadruplex models. They have a potential to account for unaccounted for building blocks, such as inosine, and we don’t know whether more than one model holds validity under different conditions .  The other major field of development has been simply unaccounted for in the study of proteomics, especially in protein-protein interactions, and in the energetics of protein conformation, first called to our attention by the work of Jacob, Monod, and Changeux (See Footnote 2).  Proteins are not just rigid structures stamped out by the monotonously simple DNA to RNA to protein concept.  Nothing is ever quite so simple. Just as there are epigenetic events, there are posttranslational events, and yet more.

JPChangeux-150x170

JP Changeux

 

 

 

 

 

 

 

 

The Emergence of Molecular Biology

I now return the discussion to the topic of medicine, the emergence of molecular biology and the need for convergence with biochemistry in the mid-20th century. Jose Eduardo de Salles Roselino recalls “I was previously allowed to make of the conformational energy as made by R Marcus in his Nobel lecture revised (J. of Electroanalytical  Chemistry 438:(1997) p251-259. (See Footnote 1) His description of the energetic coordinates of a landscape of a chemical reaction is only a two-dimensional cut of what in fact is a volcano crater (in three dimensions) (each one varies but the sum of the two is constant. Solvational+vibrational=100% in ordinate) nuclear coordinates in abcissa. In case we could represent it by research methods that allow us to discriminate in one by one degree of different pairs of energy, we would most likely have 360 other similar representations of the same phenomenon. The real representation would take into account all those 360 representations together. In case our methodology was not that fine, for instance it discriminates only differences of minimal 10 degrees in 360 possible, will have 36 partial representations of something that to be perfectly represented will require all 36 being taken together. Can you reconcile it with ATGC?  Yet, when complete genome sequences were presented they were described as though we will know everything about this living being. The most important problems in biology will be viewed by limited vision always and the awareness of this limited is something we should acknowledge and teach it. Therefore, our knowledge is made up of partial representations. If we had the entire genome data for the most intricate biological problems, they are still not amenable to this level of reductionism. But going from general views of signals andsymptoms we could get to the most detailed molecular view and in this case genome provides an anchor.”

“Warburg Effect” describes the preference of glycolysis and lactic acid fermentation rather than oxidative phosphorylation for energy production in cancer cells. Mitochondrial metabolism is an important and necessary component in the functioning and maintenance of the cell, and accumulating evidence suggests that dysfunction of mitochondrial metabolism plays a role in cancer. Progress has demonstrated the mechanisms of the mitochondrial metabolism-to-glycolysis switch in cancer development and how to target this metabolic switch.

 

 

Glycolysis

glycolysis

 

Otto Heinrich Warburg (1883- )

Otto Warburg

435px-Louis_Pasteur,_foto_av_Félix_Nadar_Crisco_edit

Louis Pasteur

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The expression “Pasteur effect” was coined by Warburg when inspired by Pasteur’s findings in yeast cells, when he investigated this metabolic observation (Pasteur effect) in cancer cells. In yeast cells, Pasteur had found that the velocity of sugar used was greatly reduced in presence of oxygen. Not to be confused, in the “Crabtree effect”, the velocity of sugar metabolism was greatly increased, a reversal, when yeast cells were transferred from the aerobic to an anaerobic condition. Thus, the velocity of sugar metabolism of yeast cells was shown to be under metabolic regulatory control in response to change in environmental oxygen conditions in growth. Warburg had to verify whether cancer cells and tissue related normal mammalian cells also have a similar control mechanism. He found that this control was also found in normal cells studied, but was absent in cancer cells. Strikingly, cancer cells continue to have higher anaerobic gycolysis despite the presence of oxygen in their culture media (See Footnote 3).

Taking this a step further, food is digested and supplied to cells In vertebrates mainly in the form of glucose, which is metabolized producing Adenosine Triphosphate (ATP) by two pathways. Glycolysis, occurs via anaerobic metabolism in the cytoplasm, and is of major significance for making ATP quickly, but in a minuscule amount (2 molecules).  In the presence of oxygen, the breakdown process continues in the mitochondria via the Krebs’s cycle coupled with oxidative phosphorylation, which is more efficient for ATP production (36 molecules). Cancer cells seem to depend on glycolysis. In the 1920s, Otto Warburg first proposed that cancer cells show increased levels of glucose consumption and lactate fermentation even in the presence of ample oxygen (known as “Warburg Effect”). Based on this theory, oxidative phosphorylation switches to glycolysis which promotes the proliferation of cancer cells. Many studies have demonstrated glycolysis as the main metabolic pathway in cancer cells.

Albert Szent Gyogy (Warburg’s student) and Otto Meyerhof both studied striated skeletal muscle metabolism invertebrates, and they found those changes observed in yeast by Pasteur. The description of the anaerobic pathway was largely credited to Emden and Meyerhof. Whenever there is increase in muscle work, energy need is above what can be provided by blood supply, the cell metabolism changes from aerobic (where  Acetyl CoA  provides the chemical energy for aerobic production of ATP) to anaerobic metabolism of glucose. In this condition, glucose is obtained directly from its muscle glycogen stores (not from hepatic glycogenolysis).  This is the sole source of chemical energy that is independent of oxygen supplied to the cell. It is a physiological change on muscle metabolism that favors autonomy. It does not depend upon the blood oxygen for aerobic metabolim or blood sources of carbon metabolites borne out from adipose tissue (free fatty acids) or muscle proteins (branched chain amino acids), or vascular delivery of glucose. On that condition, the muscle can perform contraction by its internal source of ATP and uses conversion of pyruvate to lactate in order to regenerate much-needed NAD (by hydride transfer from pyruvate) as a replacement for this mitochondrial function. This regulatory change, keeps glycolysis going at fast rate in order to meet ATP needs of the cell under low yield condition (only two or three ATP for each glucose converted into two lactate molecules). Therefore, it cannot last for long periods of time. This regulatory metabolic change is made in seconds, minutes and therefore happens with the proteins that are already presented in the cell. It does not requires the effect of transcription factors and/or changes in gene expression (See Footnote 1, 2).

In other types mammalian cells, like those from the lens of the eye (86% gycolysis + pentose shunt),  and red blood cells (RBC)[both lacking mitochondria], and also in the deep medullary layer of the kidneys, for lack of mitochondria in the first two cases and normally reduced blood perfusion in the third – A condition required for the counter current mechanism and our ability to concentrate urine also have, permanent higher anaerobic metabolism. In the case of RBC, it includes the ability to produce in a shunt of glycolytic pathway 2,3 diphospho- glycerate that is required to place the hemogloblin macromolecule in an unstable equilibrium between its two forms (R and T – Here presented as simplified accordingly to the model of Monod, Wyman and Changeux. The final model would be even much complex (see for instance, H-W and K review Nature 2007 vol 450: p 964-972 )

Any tissue under a condition of ischemia that is required for some medical procedures (open heart surgery, organ transplants, etc) displays this fast regulatory mechanism (See Footnote 1, 2). A display of these regulatory metabolic changes can be seen in: Cardioplegia: the protection of the myocardium during open heart surgery: a review. D. J. Hearse J. Physiol., Paris, 1980, 76, 751-756 (Fig 1).  The following points are made:

1-       It is a fast regulatory response. Therefore, no genetic mechanism can be taken into account.

2-       It moves from a reversible to an irreversible condition, while the cells are still alive. Death can be seen at the bottom end of the arrow. Therefore, it cannot be reconciled with some of the molecular biology assumptions:

A-       The gene and genes reside inside the heart muscle cells but, in order to preserve intact, the source of coded genetic information that the cell reads and transcribes, DNA must be kept to a minimal of chemical reactivity.

B-       In case sequence determines conformation, activity and function , elevated potassium blood levels could not cause cardiac arrest.

In comparison with those conditions here presented, cancer cells keep the two metabolic options for glucose metabolism at the same time. These cells can use glucose that our body provides to them or adopt temporarily, an independent metabolic form without the usual normal requirement of oxygen (one or another form for ATP generation).  ATP generation is here, an over-simplification of the metabolic status since the carbon flow for building blocks must also be considered and in this case oxidative metabolism of glucose in cancer cells may be viewed as a rich source of organic molecules or building blocks that dividing cells always need.

JES Roselino has conjectured that “most of the Krebs cycle reaction works as ideal reversible thermodynamic systems that can supply any organic molecule that by its absence could prevent cell duplication.” In the vision of Warburg, cancer cells have a defect in Pasteur-effect metabolic control. In case it was functioning normally, it will indicate which metabolic form of glucose metabolism is adequate for each condition. What more? Cancer cells lack differentiated cell function. Any role for transcription factors must be considered as the role of factors that led to the stable phenotypic change of cancer cells. The failure of Pasteur effect must be searched for among the fast regulatory mechanisms that aren’t dependent on gene expression (See Footnote 3).

Extending the thoughts of JES Roselino (Hepatology 1992;16: 1055-1060), reduced blood flow caused by increased hydrostatic pressure in extrahepatic cholestasis decreases mitochondrial function (quoted in Hepatology) and as part of Pasteur effect normal response, increased glycolysis in partial and/or functional anaerobiosis and therefore blocks the gluconeogenic activity of hepatocytes that requires inhibited glycolysis. In this case, a clear energetic link can be perceived between the reduced energetic supply and the ability to perform differentiated hepatic function (gluconeogenesis). In cancer cells, the action of transcription factors that can be viewed as different ensembles of kaleidoscopic pieces (with changing activities as cell conditions change) are clearly linked to the new stable phenotype. In relation to extrahepatic cholestasis mentioned above it must be reckoned that in case a persistent chronic condition is studied a secondary cirrhosis is installed as an example of persistent stable condition, difficult to be reversed and without the requirement for a genetic mutation. (See Footnote 4).

 The Rejection of Complexity

Most of our reasoning about genes was derived from scientific work in microorganisms. These works have provided great advances in biochemistry.

250px-DNA_labeled DNA diagram showing base pairing

double helix

 

hgp_hubris_220x288_72 genome cartoon

Dna triplex pic

Triple helix

 

formation of a triplex DNA structure

formation of triple helix

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1-      The “Gelehrter idea”: No matter what you are doing you will always be better off, in case you have a gene (In chapter 7 Principles of Medical Genetics Gelehrter and Collins Williams & Wilkins 1990).

2-      The idea that everything could be found following one gene one enzyme relationship that works fine for our understanding of the metabolism, in all biological problems.

3-      The idea that everything that explains biochemistry in microorganisms explains also for every living being (J Nirenberg).

4-      The idea that biochemistry may not require that time should be also taken into account. Time must be considered only for genetic and biological evolution studies (S Luria. In Life- The unfinished experiment 1977 C Scribner´s sons NY).

5-      Finally, the idea that everything in biology, could be found in the genome. Since all information in biology goes from DNA through RNA to proteins. Alternatively, are in the DNA, in case the strict line that includes RNA is not included.

This last point can be accepted in case it is considered that ALL GENETIC information is in our DNA. Genetics as part of life and not as its total expression.

For example, when our body is informed that the ambient temperature is too low or alternatively is too high, our body is receiving an information that arrives from our environment. This external information will affect our proteins and eventually, in case of longer periods in a new condition will cause adaptive response that may include conformational changes in transcription factors (proteins) that will also, produce new readings on the DNA. However, it is an information that moves from outside, to proteins and not from DNA to proteins. The last pathway, when transcription factors change its conformation and change DNA reading will follow the dogmatic view as an adaptive response (See Footnotes 1-3).

However, in case, time is taken into account, the first reactions against cold or warmer temperatures will be the ones that happen through change in protein conformation, activities and function before any change in gene expression can be noticed at protein level. These fast changes, in seconds, minutes cannot be explained by changes in gene expression and are strongly linked to what is needed for the maintenance of life.

“It is possible”, says Roselino, “desirable, to explain all these fast biochemical responses to changes in a living being condition as the sound foundation of medical practices without a single mention to DNA. In case a failure in any mechanism necessary to life is found to be genetic in its origin, the genome in context with with this huge set of transcription factors must be taken into account. This is the biochemical line of reasoning that I have learned with Houssay and Leloir. It would be an honor to see it restored in modern terms.”

More on the Mechanism of Metabolic Control

It was important that genomics would play such a large role in medical research for the last 70 years. There is also good reason to rethink the objections of the Nobelists James Watson and Randy Schekman in the past year, whatever discomfort it brings.  Molecular biology has become a tautology, and as a result deranged scientific rigor inside biology.

Crick & Watson with their DNA model, 1953

Eatson and Crick

Randy-Schekman Berkeley

Randy-Schekman Berkeley

 

 

According to JES Roselino, “consider that glycolysis is oscillatory thanks to the kinetic behavior of Phosphofructokinase. Further, by its effect upon Pyruvate kinase through Fructose 1,6 diphosphate oscillatory levels, the inhibition of gluconeogenesis is also oscillatory. When the carbon flow through glycolysis is led to a maximal level gluconeogenesis will be almost completely blocked. The reversal of the Pyruvate kinase step in liver requires two enzymes (Pyruvate carboxylase (maintenance of oxaloacetic levels) + phosphoenolpyruvate carboxykinase (E.C. 4.1.1.32)) and energy requiring reactions that most likely could not as an ensemble, have a fast enough response against pyruvate kinase short period of inhibition during high frequency oscillatory periods of glycolytic flow. Only when glycolysis oscillates at low frequency the opposite reaction could enable gluconeogenic carbon flow.”

In case it can be shown in a rather convincing way, the same reasoning could be applied to understand how simple replicative signals inducing Go to G1 transition in cells, could easily overcome more complex signals required for cell differentiation and differentiated function.

Perhaps the problem of overextension of the equivalence of the DNA and what happens to the organism is also related to the initial reliance on a single cell model to relieve the complexity (which isn’t fully the case).

For instance, consider this fragment:
“Until only recently it was assumed that all proteins take on a clearly defined three-dimensional structure – i.e. they fold in order to be able to assume these functions.”
Cold Spring Harbour Symp. Quant. Biol. 1973  p 187-193 J.C Seidel and J Gergely – Investigation of conformational changes in Spin-Labeled Myosin Model for muscle contraction:
Huxley, A. F. 1971 Proc. Roy. Soc (London) (B) 178:1
Huxley, A.F and R. M. Simmons,1971. Nature 233:633
J.C Haselgrove X ray Evidence for a conformational Change in the Actin-containing filaments…Cold Spring Harbour Symp Quant Biol.1972 v 37: p 341-352

Only a very small sample indicating otherwise. Proteins were held as interacting macromolecules, changing their conformation in regulatory response to changes in the microenvironment (See Footnote 2). DNA was the opposite, non-interacting macromolecules to be as stable as a library must be.

The dogma held that the property of proteins could be read in DNA alone. Consequenly, the few examples quoted above, must be ignored and all people must believe that DNA alone, without environmental factors roles, controls protein amino acid sequence (OK), conformation (not true), activity (not true) and function (not true).

It appeared naively to be correct from the dogma to conclude from interpreting your genome: You have a 50% increased risk of developing the following disease (deterministic statement).  The correct form must be: You belong to a population that has a 50% increase in the risk of….followed by –  what you must do to avoid increase in your personal risk and the care you should take in case you want to have longer healthy life.  Thus, genetics and non-genetic diseases were treated as the same and medical foundations were reinforced by magical considerations (dogmas) in a very profitable way for those involved besides the patient.

 Footnotes:

  1. There is a link of electricity with ions in biology and the oscillatory behavior of some electrical discharges.  In addition, the oscillatory form of electrical discharged may have allowed Planck to relate high energy content with higher frequencies and conversely, low energy content in low frequency oscillatory events.  One may think of high density as an indication of great amount of matter inside a volume in space.  This helps the understanding of Planck’s idea as a high-density-energy in time for a high frequency phenomenon.
  1. Take into account a protein that may have its conformation restricted by an S-S bridge. This protein also, may move to another more flexible conformation in case it is in HS HS condition when the S-S bridge is broken. Consider also that, it takes some time for a protein to move from one conformation for instance, the restricted conformation (S-S) to other conformations. Also, it takes a few seconds or minutes to return to the S-S conformation (This is the Daniel Koshland´s concept of induced fit and relaxation time used by him in order to explain allosteric behavior of monomeric proteins- Monod, Wyman and Changeux requires tetramer or at least, dimer proteins).
  1. In case you have glycolysis oscillating in a frequency much higher than the relaxation time you could lead to the prevalence of high NADH effect leading to high HS /HS condition and at low glycolytic frequency, you could have predominance of S-S condition affecting protein conformation. In case you have predominance of NAD effect upon protein S-S you would get the opposite results.  The enormous effort to display the effect of citrate and over Phosphofructokinase conformation was made by others. Take into account that ATP action as an inhibitor in this case, is a rather unusual one. It is a substrate of the reaction, and together with its action as activator  F1,6 P (or its equivalent F2,6 P) is also unusual. However, it explains oscillatory behaviour of glycolysis. (Goldhammer , A.R, and Paradies: PFK structure and function, Curr. Top Cell Reg 1979; 15:109-141).
  1. The results presented in our Hepatology work must be viewed in the following way: In case the hepatic (oxygenated) blood flow is preserved, the bile secretory cells of liver receive well-oxygenated blood flow (the arterial branches bath secretory cells while the branches originated from portal vein irrigate the hepatocytes.  During extra hepatic cholestasis the low pressure, portal blood flow is reduced and the hepatocytes do not receive enough oxygen required to produce ATP that gluconeogenesis demands. Hepatic artery do not replace this flow since, its branches only join portal blood fluxes after the previous artery pressure  is reduced to a low pressure venous blood – at the point where the formation of hepatic vein is. Otherwise, the flow in the portal vein would be reversed or, from liver to the intestine. It is of no help to take into account possible valves for this reasoning since minimal arterial pressure is well above maximal venous pressure and this difference would keep this valve in permanent close condition. In low portal blood flow condition, the hepatocyte increases pyruvate kinase activity and with increased pyruvate kinase activity Gluconeogenesis is forbidden (See Walsh & Cooper revision quoted in the Hepatology as ref 23). For the hemodynamic considerations, role of artery and veins in hepatic portal system see references 44 and 45 Rappaport and Schneiderman and Rappapaport.

 

 Appendix I.

metabolic pathways

metabolic pathways

Signals Upstream and Targets Downstream of Lin28 in the Lin28 Pathway

Signals Upstream and Targets Downstream of Lin28 in the Lin28 Pathway

 

 

 

 

 

 

 

 

1.  Functional Proteomics Adds to Our Understanding

Ben Schuler’s research group from the Institute of Biochemistry of the University of Zurich has now established that an increase in temperature leads to folded proteins collapsing and becoming smaller. Other environmental factors can trigger the same effect. The crowded environments inside cells lead to the proteins shrinking. As these proteins interact with other molecules in the body and bring other proteins together, understanding of these processes is essential “as they play a major role in many processes in our body, for instance in the onset of cancer”, comments study coordinator Ben Schuler.

Measurements using the “molecular ruler”

“The fact that unfolded proteins shrink at higher temperatures is an indication that cell water does indeed play an important role as to the spatial organisation eventually adopted by the molecules”, comments Schuler with regard to the impact of temperature on protein structure. For their studies the biophysicists use what is known as single-molecule spectroscopy. Small colour probes in the protein enable the observation of changes with an accuracy of more than one millionth of a millimetre. With this “molecular yardstick” it is possible to measure how molecular forces impact protein structure.

With computer simulations the researchers have mimicked the behaviour of disordered proteins. They want to use them in future for more accurate predictions of their properties and functions.

Correcting test tube results

That’s why it’s important, according to Schuler, to monitor the proteins not only in the test tube but also in the organism. “This takes into account the fact that it is very crowded on the molecular level in our body as enormous numbers of biomolecules are crammed into a very small space in our cells”, says Schuler. The biochemists have mimicked this “molecular crowding” and observed that in this environment disordered proteins shrink, too.

Given these results many experiments may have to be revisited as the spatial organisation of the molecules in the organism could differ considerably from that in the test tube according to the biochemist from the University of Zurich. “We have, therefore, developed a theoretical analytical method to predict the effects of molecular crowding.” In a next step the researchers plan to apply these findings to measurements taken directly in living cells.

Explore further: Designer proteins provide new information about the body’s signal processesMore information: Andrea Soranno, Iwo Koenig, Madeleine B. Borgia, Hagen Hofmann, Franziska Zosel, Daniel Nettels, and Benjamin Schuler. Single-molecule spectroscopy reveals polymer effects of disordered proteins in crowded environments. PNAS, March 2014. DOI: 10.1073/pnas.1322611111

 

Effects of Hypoxia on Metabolic Flux

  1. Glucose-6-phosphate dehydrogenase regulation in the hepatopancreas of the anoxia-tolerantmarinemollusc, Littorina littorea

JL Lama , RAV Bell and KB Storey

Glucose-6-phosphate dehydrogenase (G6PDH) gates flux through the pentose phosphate pathway and is key to cellular antioxidant defense due to its role in producing NADPH. Good antioxidant defenses are crucial for anoxia-tolerant organisms that experience wide variations in oxygen availability. The marine mollusc, Littorina littorea, is an intertidal snail that experiences daily bouts of anoxia/hypoxia with the tide cycle and shows multiple metabolic and enzymatic adaptations that support anaerobiosis. This study investigated the kinetic, physical and regulatory properties of G6PDH from hepatopancreas of L. littorea to determine if the enzyme is differentially regulated in response to anoxia, thereby providing altered pentose phosphate pathway functionality under oxygen stress conditions.

Several kinetic properties of G6PDH differed significantly between aerobic and 24 h anoxic conditions; compared with the aerobic state, anoxic G6PDH (assayed at pH 8) showed a 38% decrease in K G6P and enhanced inhibition by urea, whereas in pH 6 assays Km NADP and maximal activity changed significantly.

All these data indicated that the aerobic and anoxic forms of G6PDH were the high and low phosphate forms, respectively, and that phosphorylation state was modulated in response to selected endogenous protein kinases (PKA or PKG) and protein phosphatases (PP1 or PP2C). Anoxia-induced changes in the phosphorylation state of G6PDH may facilitate sustained or increased production of NADPH to enhance antioxidant defense during long term anaerobiosis and/or during the transition back to aerobic conditions when the reintroduction of oxygen causes a rapid increase in oxidative stress.

Lama et al.  Peer J 2013.   http://dx.doi.org/10.7717/peerj.21

 

  1. Structural Basis for Isoform-Selective Inhibition in Nitric Oxide Synthase

    TL. Poulos and H Li

In the cardiovascular system, the important signaling molecule nitric oxide synthase (NOS) converts L-arginine into L-citrulline and releases nitric oxide (NO). NO produced by endothelial NOS (eNOS) relaxes smooth muscle which controls vascular tone and blood pressure. Neuronal NOS (nNOS) produces NO in the brain, where it influences a variety of neural functions such as neural transmitter release. NO can also support the immune system, serving as a cytotoxic agent during infections. Even with all of these important functions, NO is a free radical and, when overproduced, it can cause tissue damage. This mechanism can operate in many neurodegenerative diseases, and as a result the development of drugs targeting nNOS is a desirable therapeutic goal.

However, the active sites of all three human isoforms are very similar, and designing inhibitors specific for nNOS is a challenging problem. It is critically important, for example, not to inhibit eNOS owing to its central role in controlling blood pressure. In this Account, we summarize our efforts in collaboration with Rick Silverman at Northwestern University to develop drug candidates that specifically target NOS using crystallography, computational chemistry, and organic synthesis. As a result, we have developed aminopyridine compounds that are 3800-fold more selective for nNOS than eNOS, some of which show excellent neuroprotective effects in animal models. Our group has solved approximately 130 NOS-inhibitor crystal structures which have provided the structural basis for our design efforts. Initial crystal structures of nNOS and eNOS bound to selective dipeptide inhibitors showed that a single amino acid difference (Asp in nNOS and Asn in eNOS) results in much tighter binding to nNOS. The NOS active site is open and rigid, which produces few large structural changes when inhibitors bind. However, we have found that relatively small changes in the active site and inhibitor chirality can account for large differences in isoform-selectivity. For example, we expected that the aminopyridine group on our inhibitors would form a hydrogen bond with a conserved Glu inside the NOS active site. Instead, in one group of inhibitors, the aminopyridine group extends outside of the active site where it interacts with a heme propionate. For this orientation to occur, a conserved Tyr side chain must swing out of the way. This unanticipated observation taught us about the importance of inhibitor chirality and active site dynamics. We also successfully used computational methods to gain insights into the contribution of the state of protonation of the inhibitors to their selectivity. Employing the lessons learned from the aminopyridine inhibitors, the Silverman lab designed and synthesized symmetric double-headed inhibitors with an aminopyridine at each end, taking advantage of their ability to make contacts both inside and outside of the active site. Crystal structures provided yet another unexpected surprise. Two of the double-headed inhibitor molecules bound to each enzyme subunit, and one molecule participated in the generation of a novel Zn site that required some side chains to adopt alternate conformations. Therefore, in addition to achieving our specific goal, the development of nNOS selective compounds, we have learned how subtle differences in and structure can control proteinligand interactions and often in unexpected ways.

 

300px-Nitric_Oxide_Synthase

Nitric oxide synthase

arginine-NO-citulline cycle

arginine-NO-citulline cycle

active site of eNOS (PDB_1P6L) and nNOS (PDB_1P6H).

active site of eNOS (PDB_1P6L) and nNOS (PDB_1P6H).

 

 

NO - muscle, vasculature, mitochondria

NO – muscle, vasculature, mitochondria

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure:  (A) Structure of one of the early dipeptide lead compounds, 1, that exhibits excellentisoform selectivity. (B, C) show the crystal structures of the dipeptide inhibitor 1 in the active site of eNOS (PDB: 1P6L) and nNOS (PDB: 1P6H). In nNOS, the inhibitor “curls” which enables the inhibitor R-amino group to interact with both Glu592 and Asp597. In eNOS, Asn368 is the homologue to nNOS Asp597.

Accounts in Chem Res 2013; 46(2): 390-98.

  1. Jamming a Protein Signal

Interfering with a single cancer-promoting protein and its receptor can open this resistance mechanism by initiating autophagy of the affected cells,  according to researchers at The University of Texas MD Anderson Cancer Center  in the journal Cell Reports.  According to Dr. Anil Sood and Yunfei Wen, lead and first authors, blocking  prolactin, a potent growth factor for ovarian cancer, sets off downstream events that result in cell by autophagy, the process  recycles damaged organelles and proteins for new use by the cell through the phagolysozome. This in turn, provides a clinical rationale for blocking prolactin and its receptor to initiate sustained autophagy as an alternative strategy for treating cancers.

Steep reductions in tumor weight

Prolactin (PRL) is a hormone previously implicated in ovarian, endometrial and other cancer development andprogression. When PRL binds to its cell membrane receptor, PRLR, activation of cancer-promoting cell signaling pathways follows.  A variant of normal prolactin called G129R blocks the reaction between prolactin and its receptor. Sood and colleagues treated mice that had two different lines of human ovarian cancer, both expressing the prolactin receptor, with G129R. Tumor weights fell by 50 percent for mice with either type of ovarian cancer after 28 days of treatment with G129R, and adding the taxane-based chemotherapy agent paclitaxel cut tumor weight by 90 percent. They surmise that higher doses of G129R may result in even greater therapeutic benefit.

 

3D experiments show death by autophagy

 

[video width=”1280″ height=”720″ mp4=”http://pharmaceuticalintelligence.com/wp-content/uploads/2014/04/1741-7007-11-65-s1-macromolecular-juggling-by-ubiquitylation-enzymes1.mp4″][/video]

 

Next the team used the prolactin-mimicking peptide to treat cultures of cancer spheroids which sharply reduced their numbers, and blocked the activation of JAK2 and STAT signaling pathways.

Protein analysis of the treated spheroids showed increased presence of autophagy factors and genomic analysis revealed increased expression of a number of genes involved in autophagy progression and cell death.  Then a series of experiments using fluorescence and electron microscopy showed that the cytosol of treated cells had large numbers of cavities caused by autophagy.

The team also connected the G129R-induced autophagy to the activity of PEA-15, a known cancer inhibitor. Analysis of tumor samples from 32 ovarian cancer patients showed that tumors express higher levels of the prolactin receptor and lower levels of phosphorylated PEA-15 than normal ovarian tissue. However, patients with low levels of the prolactin receptor and higher PEA-15 had longer overall survival than those with high PRLR and low PEA-15.

Source: MD Anderson Cancer Center

 

  1. Chemists’ Work with Small Peptide Chains of Enzymes

Korendovych and his team designed seven simple peptides, each containing seven amino acids. They then allowed the molecules of each peptide to self-assemble, or spontaneously clump together, to form amyloids. (Zinc, a metal with catalytic properties, was introduced to speed up the reaction.) What they found was that four of the seven peptides catalyzed the hydrolysis of molecules known as esters, compounds that react with water to produce water and acids—a feat not uncommon among certain enzymes.

“It was the first time that a peptide this small self-assembled to produce an enzyme-like catalyst,” says Korendovych. “Each enzyme has to be an exact fit for its respective substrate,” he says, referring to the molecule with which an enzyme reacts. “Even after millions of years, nature is still testing all the possible combinations of enzymes to determine which ones can catalyze metabolic reactions. Our results make an argument for the design of self-assembling nanostructured catalysts.”

Source: Syracuse University

Here are three articles emphasizing the value of combinatorial analysis, which can be formed from genomic, clinical, and proteomic data sets.

 

  1. Comparative analysis of differential network modularity in tissue specific normal and cancer protein interaction networks

    F Islam , M Hoque , RS Banik , S Roy , SS Sumi, et al.

As most biological networks show modular properties, the analysis of differential modularity between normal and cancer protein interaction networks can be a good way to understand cancer more significantly. Two aspects of biological network modularity e.g. detection of molecular complexes (potential modules or clusters) and identification of crucial nodes forming the overlapping modules have been considered in this regard.

The computational analysis of previously published protein interaction networks (PINs) has been conducted to identify the molecular complexes and crucial nodes of the networks. Protein molecules involved in ten major cancer signal transduction pathways were used to construct the networks based on expression data of five tissues e.g. bone, breast, colon, kidney and liver in both normal and cancer conditions.

Cancer PINs show higher level of clustering (formation of molecular complexes) than the normal ones. In contrast, lower level modular overlapping is found in cancer PINs than the normal ones. Thus a proposition can be made regarding the formation of some giant nodes in the cancer networks with very high degree and resulting in reduced overlapping among the network modules though the predicted molecular complex numbers are higher in cancer conditions.

Islam et al. Journal of Clinical Bioinformatics 2013, 3:19-32

  1. A new 12-gene diagnostic biomarker signature of melanoma revealed by integrated microarray analysis

    Wanting Liu , Yonghong Peng and Desmond J. Tobin
    PeerJ 1:e49;        http://dx.doi.org/10.7717/peerj.49

Here we present an integrated microarray analysis framework, based on a genome-wide relative significance (GWRS) and genome-wide global significance (GWGS) model. When applied to five microarray datasets on melanoma published between 2000 and 2011, this method revealed a new signature of 200 genes. When these were linked to so-called ‘melanoma driver’ genes involved in MAPK, Ca2+, and WNT signaling pathways we were able to produce a new 12-gene diagnostic biomarker signature for melanoma (i.e., EGFR, FGFR2, FGFR3, IL8, PTPRF, TNC, CXCL13, COL11A1, CHP2, SHC4, PPP2R2C, andWNT4).We have begun to experimentally validate a subset of these genes involved inMAPK signaling at the protein level, including CXCL13, COL11A1, PTPRF and SHC4 and found these to be overexpressed inmetastatic and primarymelanoma cells in vitro and in situ compared to melanocytes cultured from healthy skin epidermis and normal healthy human skin.

 

catalytic amyloid forming particle

catalytic amyloid forming particle

 

 

 

 

 

 

 

        8.    PanelomiX: A threshold-based algorithm to create panels of biomarkers

X Robin , N Turck , A Hainard , N Tiberti, et al.
               Translational Proteomics 2013.    http://dx.doi.org/10.1016/j.trprot.2013.04.003

The PanelomiX toolbox combines biomarkers and evaluates the performance of panels to classify patients better than singlemarkers or other classifiers. The ICBTalgorithm proved to be an efficient classifier, the results of which can easily be interpreted.

Here are two current examples of the immense role played by signaling pathways in carcinogenic mechanisms and in treatment targeting, which is also confounded by acquired resistance.

 

  1. Triple-Negative Breast Cancer

  1. epidermal growth factor receptor (EGFR or ErbB1) and
  2. high activity of the phosphatidylinositol 3-kinase (PI3K)–Akt pathway

are both targeted in triple-negative breast cancer (TNBC).

  • activation of another EGFR family member [human epidermal growth factor receptor 3 (HER3) (or ErbB3)] may limit the antitumor effects of these drugs.

This study found that TNBC cell lines cultured with the EGFR or HER3 ligand EGF or heregulin, respectively, and treated with either an Akt inhibitor (GDC-0068) or a PI3K inhibitor (GDC-0941) had increased abundance and phosphorylation of HER3.

The phosphorylation of HER3 and EGFR in response to these treatments

  1. was reduced by the addition of a dual EGFR and HER3 inhibitor (MEHD7945A).
  2. MEHD7945A also decreased the phosphorylation (and activation) of EGFR and HER3 and
  3. the phosphorylation of downstream targets that occurred in response to the combination of EGFR ligands and PI3K-Akt pathway inhibitors.

In culture, inhibition of the PI3K-Akt pathway combined with either MEHD7945A or knockdown of HER3

  1. decreased cell proliferation compared with inhibition of the PI3K-Akt pathway alone.
  2. Combining either GDC-0068 or GDC-0941 with MEHD7945A inhibited the growth of xenografts derived from TNBC cell lines or from TNBC patient tumors, and
  3. this combination treatment was also more effective than combining either GDC-0068 or GDC-0941 with cetuximab, an EGFR-targeted antibody.
  4. After therapy with EGFR-targeted antibodies, some patients had residual tumors with increased HER3 abundance and EGFR/HER3 dimerization (an activating interaction).

Thus, we propose that concomitant blockade of EGFR, HER3, and the PI3K-Akt pathway in TNBC should be investigated in the clinical setting.

Reference: Antagonism of EGFR and HER3 Enhances the Response to Inhibitors of the PI3K-Akt Pathway in Triple-Negative Breast Cancer. JJ Tao, P Castel, N Radosevic-Robin, M Elkabets, et al.  Sci. Signal., 25 March 2014;
7(318), p. ra29   http://dx.doi.org/10.1126/scisignal.2005125

 

                  10.   Metastasis in RAS Mutant or Inhibitor-Resistant Melanoma Cells

The protein kinase BRAF is mutated in about 40% of melanomas, and BRAF inhibitors improve progression-free and overall survival in these patients. However, after a relatively short period of disease control, most patients develop resistance because of reactivation of the RAF–ERK (extracellular signal–regulated kinase) pathway, mediated in many cases by mutations in RAS. We found that BRAF inhibition induces invasion and metastasis in RAS mutant melanoma cells through a mechanism mediated by the reactivation of the MEK (mitogen-activated protein kinase kinase)–ERK pathway.

Reference: BRAF Inhibitors Induce Metastasis in RAS Mutant or Inhibitor-Resistant Melanoma Cells by Reactivating MEK and ERK Signaling. B Sanchez-Laorden, A Viros, MR Girotti, M Pedersen, G Saturno, et al., Sci. Signal., 25 March 2014;  7(318), p. ra30  http://dx.doi.org/10.1126/scisignal.2004815

Appendix II.

The world of physics in the twentieth century saw the end of determinism established by Newton. This is characterized by discrete laws that describe natural observations. These are in gravity and in eletricity. In an early phase of investigation, an era of galvanic or voltaic electricity represented a revolutionary break from the historical focus on frictional electricity. Alessandro Voltadiscovered that chemical reactions could be used to create positively charged anodes and negatively charged cathodes.  In 1790, Prof. Luigi Alyisio Galvani of Bologna, while conducting experiments on “animal electricity“, noticed the twitching of a frog’s legs in the presence of an electric machine. He observed that a frog’s muscle, suspended on an iron balustrade by a copper hook passing through its dorsal column, underwent lively convulsions without any extraneous cause, the electric machine being at this time absent.  Volta communicated a description of his pile to the Royal Society of London and shortly thereafter Nicholson and Cavendish (1780) produced the decomposition of water by means of the electric current, using Volta’s pile as the source of electromotive force.

Siméon Denis Poisson attacked the difficult problem of induced magnetization, and his results provided  a first approximation. His innovation required the application of mathematics to physics.  His memoirs on the theory of electricity and magnetism created a new branch of mathematical physics.  The discovery of electromagnetic induction was made almost simultaneously and independently by Michael Faraday and Joseph Henry. Michael Faraday, the successor of Humphry Davy, began his epoch-making research relating to electric and electromagnetic induction in 1831. In his investigations of the peculiar manner in which iron filings arrange themselves on a cardboard or glass in proximity to the poles of a magnet, Faraday conceived the idea of magnetic “lines of force” extending from pole to pole of the magnet and along which the filings tend to place themselves. On the discovery being made that magnetic effects accompany the passage of an electric current in a wire, it was also assumed that similar magnetic lines of force whirled around the wire. He also posited that iron, nickel, cobalt, manganese, chromium, etc., are paramagnetic (attracted by magnetism), whilst other substances, such as bismuth, phosphorus, antimony, zinc, etc., are repelled by magnetism or are diamagnetic.

Around the mid-19th century, Fleeming Jenkin‘s work on ‘ Electricity and Magnetism ‘ and Clerk Maxwell’s ‘ Treatise on Electricity and Magnetism ‘ were published. About 1850 Kirchhoff published his laws relating to branched or divided circuits. He also showed mathematically that according to the then prevailing electrodynamic theory, electricity would be propagated along a perfectly conducting wire with the velocity of light. Herman Helmholtz investigated the effects of induction on the strength of a current and deduced mathematical equations, which experiment confirmed. In 1853 Sir William Thomson (later Lord Kelvin) predicted as a result of mathematical calculations the oscillatory nature of the electric discharge of a condenser circuit.  Joseph Henry, in 1842 discerned  the oscillatory nature of the Leyden jardischarge.

In 1864 James Clerk Maxwell announced his electromagnetic theory of light, which was perhaps the greatest single step in the world’s knowledge of electricity. Maxwell had studied and commented on the field of electricity and magnetism as early as 1855/6 when On Faraday’s lines of force was read to the Cambridge Philosophical Society. The paper presented a simplified model of Faraday’s work, and how the two phenomena were related. He reduced all of the current knowledge into a linked set of differential equations with 20 equations in 20 variables. This work was later published as On Physical Lines of Force in1861. In order to determine the force which is acting on any part of the machine we must find its momentum, and then calculate the rate at which this momentum is being changed. This rate of change will give us the force. The method of calculation which it is necessary to employ was first given by Lagrange, and afterwards developed, with some modifications, by Hamilton’s equations. Now Maxwell logically showed how these methods of calculation could be applied to the electro-magnetic field. The energy of a dynamical systemis partly kinetic, partly potential. Maxwell supposes that the magnetic energy of the field is kinetic energy, the electric energy potential.  Around 1862, while lecturing at King’s College, Maxwell calculated that the speed of propagation of an electromagnetic field is approximately that of the speed of light.   Maxwell’s electromagnetic theory of light obviously involved the existence of electric waves in free space, and his followers set themselves the task of experimentally demonstrating the truth of the theory. By 1871, he presented the Remarks on the mathematical classification of physical quantities.

A Wave-Particle Dilemma at the Century End

In 1896 J.J. Thomson performed experiments indicating that cathode rays really were particles, found an accurate value for their charge-to-mass ratio e/m, and found that e/m was independent of cathode material. He made good estimates of both the charge e and the mass m, finding that cathode ray particles, which he called “corpuscles”, had perhaps one thousandth of the mass of the least massive ion known (hydrogen). He further showed that the negatively charged particles produced by radioactive materials, by heated materials, and by illuminated materials, were universal.  In the late 19th century, the Michelson–Morley experiment was performed by Albert Michelson and Edward Morley at what is now Case Western Reserve University. It is generally considered to be the evidence against the theory of a luminiferous aether. The experiment has also been referred to as “the kicking-off point for the theoretical aspects of the Second Scientific Revolution.” Primarily for this work, Albert Michelson was awarded theNobel Prize in 1907.

Wave–particle duality is a theory that proposes that all matter exhibits the properties of not only particles, which have mass, but also waves, which transfer energy. A central concept of quantum mechanics, this duality addresses the inability of classical concepts like “particle” and “wave” to fully describe the behavior of quantum-scale objects. Standard interpretations of quantum mechanics explain this paradox as a fundamental property of the universe, while alternative interpretations explain the duality as an emergent, second-order consequence of various limitations of the observer. This treatment focuses on explaining the behavior from the perspective of the widely used Copenhagen interpretation, in which wave–particle duality serves as one aspect of the concept of complementarity, that one can view phenomena in one way or in another, but not both simultaneously.  Through the work of Max PlanckAlbert EinsteinLouis de BroglieArthur Compton, Niels Bohr, and many others, current scientific theory holds that all particles also have a wave nature (and vice versa).

Beginning in 1670 and progressing over three decades, Isaac Newton argued that the perfectly straight lines of reflection demonstrated light’s particle nature, but Newton’s contemporaries Robert Hooke and Christiaan Huygens—and later Augustin-Jean Fresnel—mathematically refined the wave viewpoint, showing that if light traveled at different speeds in different, refraction could be easily explained. The resulting Huygens–Fresnel principle was supported by Thomas Young‘s discovery of double-slit interference, the beginning of the end for the particle light camp.  The final blow against corpuscular theory came when James Clerk Maxwell discovered that he could combine four simple equations, along with a slight modification to describe self-propagating waves of oscillating electric and magnetic fields. When the propagation speed of these electromagnetic waves was calculated, the speed of light fell out. While the 19th century had seen the success of the wave theory at describing light, it had also witnessed the rise of the atomic theory at describing matter.

Matter and Light

In 1789, Antoine Lavoisier secured chemistry by introducing rigor and precision into his laboratory techniques. By discovering diatomic gases, Avogadro completed the basic atomic theory, allowing the correct molecular formulae of most known compounds—as well as the correct weights of atoms—to be deduced and categorized in a consistent manner. The final stroke in classical atomic theory came when Dimitri Mendeleev saw an order in recurring chemical properties, and created a table presenting the elements in unprecedented order and symmetry.   Chemistry was now an atomic science.

Black-body radiation, the emission of electromagnetic energy due to an object’s heat, could not be explained from classical arguments alone. The equipartition theorem of classical mechanics, the basis of all classical thermodynamic theories, stated that an object’s energy is partitioned equally among the object’s vibrational modes. This worked well when describing thermal objects, whose vibrational modes were defined as the speeds of their constituent atoms, and the speed distribution derived from egalitarian partitioning of these vibrational modes closely matched experimental results. Speeds much higher than the average speed were suppressed by the fact that kinetic energy is quadratic—doubling the speed requires four times the energy—thus the number of atoms occupying high energy modes (high speeds) quickly drops off. Since light was known to be waves of electromagnetism, physicists hoped to describe this emission via classical laws. This became known as the black body problem. The Rayleigh–Jeans law which, while correctly predicting the intensity of long wavelength emissions, predicted infinite total energy as the intensity diverges to infinity for short wavelengths.

The solution arrived in 1900 when Max Planck hypothesized that the frequency of light emitted by the black body depended on the frequency of the oscillator that emitted it, and the energy of these oscillators increased linearly with frequency (according to his constant h, where E = hν). By demanding that high-frequency light must be emitted by an oscillator of equal frequency, and further requiring that this oscillator occupy higher energy than one of a lesser frequency, Planck avoided any catastrophe; giving an equal partition to high-frequency oscillators produced successively fewer oscillators and less emitted light. And as in the Maxwell–Boltzmann distribution, the low-frequency, low-energy oscillators were suppressed by the onslaught of thermal jiggling from higher energy oscillators, which necessarily increased their energy and frequency. Planck had intentionally created an atomic theory of the black body, but had unintentionally generated an atomic theory of light, where the black body never generates quanta of light at a given frequency with energy less than .

In 1905 Albert Einstein took Planck’s black body model in itself and saw a wonderful solution to another outstanding problem of the day: the photoelectric effect, the phenomenon where electrons are emitted from atoms when they absorb energy from light.   Only by increasing the frequency of the light, and thus increasing the energy of the photons, can one eject electrons with higher energy. Thus, using Planck’s constant h to determine the energy of the photons based upon their frequency, the energy of ejected electrons should also increase linearly with frequency; the gradient of the line being Planck’s constant. These results were not confirmed until 1915, when Robert Andrews Millikan, produced experimental results in perfect accord with Einstein’s predictions. While  the energy of ejected electrons reflected Planck’s constant, the existence of photons was not explicitly proven until the discovery of the photon antibunching effect  When Einstein received his Nobel Prizein 1921, it was  for the photoelectric effect, the suggestion of quantized light. Einstein’s “light quanta” represented the quintessential example of wave–particle duality. Electromagnetic radiation propagates following  linear wave equations, but can only be emitted or absorbed as discrete elements, thus acting as a wave and a particle simultaneously.

Radioactivity Changes the Scientific Landscape

The turn of the century also features radioactivity, which later came to the forefront of the activities of World War II, the Manhattan Project, the discovery of the chain reaction, and later – Hiroshima and Nagasaki.

Marie Curie

Marie Curie

 

 

 

Marie Skłodowska-Curie was a Polish and naturalized-French physicist and chemist who conducted pioneering research on radioactivity. She was the first woman to win a Nobel Prize, the only woman to win in two fields, and the only person to win in multiple sciences. She was also the first woman to become a professor at the University of Paris, and in 1995 became the first woman to be entombed on her own merits in the Panthéon in Paris. She shared the 1903 Nobel Prize in Physics with her husband Pierre Curie and with physicist Henri Becquerel. She won the 1911 Nobel Prize in Chemistry.  Her achievements included a theory of radioactivity (a term that she coined, techniques for isolating radioactive isotopes, and the discovery of polonium and radium. She named the first chemical element that she discovered – polonium, which she first isolated in 1898 – after her native country. Under her direction, the world’s first studies were conducted into the treatment of neoplasms using radioactive isotopes. She founded the Curie Institutes in Paris and in Warsaw, which remain major centres of medical research today. During World War I, she established the first military field radiological centres.  Curie died in 1934 due to aplastic anemia brought on by exposure to radiation – mainly, it seems, during her World War I service in mobile X-ray units created by her.

 

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Epilogue: Envisioning New Insights in Cancer Translational Biology

Author and Curator: Larry H Bernstein, MD, FCAP

 

The foregoing  summary leads to a beginning as it is a conclusion.  It concludes a body of work in the e-book series,

Series C: e-Books on Cancer & Oncology

Series C Content Consultant: Larry H. Bernstein, MD, FCAP

 

VOLUME ONE 

Cancer Biology and Genomics for Disease Diagnosis

2014

Stephen J. Williams, PhD, Senior Editor

sjwilliamspa@comcast.net

Tilda Barliya, PhD, Editor

tildabarliya@gmail.com

Ritu Saxena, PhD, Editor

ritu.uab@gmail.com

Leaders in Pharmaceutical Business Intelligence 

that has been presented by the cancer team of professional experts, e-Book concept was conceived by Aviva Lev-Ari, PhD, RN, e-Series Editor-in-Chief and Founder of Leaders in Pharmaceutical Business Intelligence 

and the Open Access Online Scientific Journal

http://pharmaceuticalintelligence.com

Stephen J. Williams, PhD, Senior Editor, and other notable contributors in  various aspects of cancer research in the emerging fields of targeted  pharmacology,  nanotechnology, cancer imaging, molecular pathology, transcriptional and regulatory ‘OMICS’, metabolism, medical and allied health related sciences, synthetic biology, pharmaceutical discovery, and translational medicine.

This  volume and its content have been conceived and organized to capture the organized events that emerge in embryological development, leading to the major organ systems that we recognize anatomically and physiologically as an integrated being.  We capture the dynamic interactions between the systems under stress  that are elicited by cytokine-driven hormonal responses, long thought to be circulatory and multisystem, that affect the major compartments of  fat and lean body mass, and are as much the drivers of metabolic pathway changes that emerge as epigenetics, without disregarding primary genetic diseases.

The greatest difficulty in organizing such a work is in whether it is to be merely a compilation of cancer expression organized by organ systems, or whether it is to capture developing concepts of underlying stem cell expressed changes that were once referred to as “dedifferentiation”.  In proceeding through the stages of neoplastic transformation, there occur adaptive local changes in cellular utilization of anabolic and catabolic pathways, and a retention or partial retention of functional specificities.

This  effectively results in the same cancer types not all fitting into the same “shoe”. There is a sequential loss of identity associated with cell migration, cell-cell interactions with underlying stroma, and metastasis., but cells may still retain identifying “signatures” in microRNA combinatorial patterns.  The story is still incomplete, with gaps in our knowledge that challenge the imagination.

What we have laid out is a map with substructural ordered concepts forming subsets within the structural maps.  There are the traditional energy pathways with terms aerobic and anaerobic glycolysis, gluconeogenesis, triose phosphate branch chains, pentose shunt, and TCA cycle vs the Lynen cycle, the Cori cycle, glycogenolysis, lipid peroxidation, oxidative stress, autosomy and mitosomy, and genetic transcription, cell degradation and repair, muscle contraction, nerve transmission, and their involved anatomic structures (cytoskeleton, cytoplasm, mitochondria, liposomes and phagosomes, contractile apparatus, synapse.

Then there is beneath this macro-domain the order of signaling pathways that regulate these domains and through mechanisms of cellular regulatory control have pleiotropic inhibitory or activation effects, that are driven by extracellular and intracellular energy modulating conditions through three recognized structures: the mitochondrial inner membrane, the intercellular matrix, and the ion-channels.

What remains to be done?

  1. There is still to be elucidated the differences in patterns within cancer types the distinct phenotypic and genotypic features  that mitigate anaplastic behavior. One leg of this problem lies in the density of mitochondria, that varies between organ types, but might vary also within cell type of a common function.  Another leg of this problem has also appeared to lie in the cell death mechanism that relates to the proeosomal activity acting on both the ribosome and mitochondrion in a coordinated manner.  This is an unsolved mystery of molecular biology.

 

  1. Then there is a need to elucidate the major differences between tumors of endocrine, sexual, and structural organs, which are distinguished by primarily a synthetic or primarily a catabolic function, and organs that are neither primarily one or the other.  For example, tumors of the thyroid and paratnhyroids, islet cells of pancreas, adrenal cortex, and pituitary glands have the longest 5 year survivals.  They and the sexual organs are in the visceral compartment.  The rest of the visceral compartment would be the liver, pancreas, salivary glands, gastrointestinal tract, and lungs (which are embryologically an outpouching of the gastrointestinal tract), kidneys and lower urinary tract.  Cancers of these organs have a much less favorable survival (brain, breast and prostate, lymphatic, blood forming organ, skin).  The case  is intermediate for breast and prostate between the endocrine organs and GI tract, based on natural history, irrespective of the available treatments.  Just consider the dilemma over what we do about screening for prostate cancer in men over the age of 60 years age who have a 70 percent incident silent carcinoma of the prostate that could be associated with unrelated cause of death.  The very rapid turnover of the gastric and colonic GI epithelium, and of the  subepithelial  B cell mucosal lymphocytic structures  is associated  with a greater aggressiveness of the tumor.

 

  1. However, we  have to reconsider the observation by NO Kaplan than the synthetic and catabolic functions are highlighted by differences in the expressions of the balance of  the two major pyridine nucleotides – DPN (NAD) and TPN (NADP) – which also might be related to the density of mitochondria  which is associated with both NADP and synthetic activity, and  with efficient aerobic function.  These are in an equilibrium through the “transhydrogenase reaction” co-discovered by Kaplan, in Fritz Lipmann’s laboratory. There does  arise a conundrum involving the regulation of mitochondria in these high turnover epithelial tissues  that rely on aerobic energy, and generate ATP through TPN linked activity, when they undergo carcinogenesis. The cells  replicate and they become utilizers of glycolysis, while at the same time, the cell death pathway is quiescent. The result becomes the introduction of peripheral muscle and liver synthesized protein cannabolization (cancer cachexia) to provide glucose  from proteolytic amino acid sources.

 

  1. There is also the structural compartment of the lean body mass. This is the heart, skeletal  structures (includes smooth muscle of GI tract, uterus, urinary bladder, brain, bone, bone marrow).  The contractile component is associated with sarcomas.  What is most striking is that the heart, skeletal muscle, and inflammatory cells are highly catabolic, not anabolic.  NO Kaplan referred tp them as DPN (NAD) tissues. This compartment requires high oxygen supply, and has a high mechanical function. But again, we return to the original observations of enrgy requirements at rest being different than at high demand.  At work, skeletal muscle generates lactic acid, but the heart can use lactic acid as fuel,.

 

  1. The liver is supplied by both the portal vein and the hepatic artery, so it is not prone to local ischemic injury (Zahn infarct). It is exceptional in that it carries out synthesis of all the circulating transport proteins, has a major function in lipid synthesis and in glycogenesis and glycogenolysis, with the added role of drug detoxification through the P450 system.  It is not only the largest organ (except for brain), but is highly active both anabolically and catabolically (by ubiquitilation).
  2. The expected cellular turnover rates for these tissues and their balance of catabolic and anabolic function would have to be taken into account to account for the occurrence and the activities of oncogenesis. This is by no means a static picture, but a dynamic organism constantly in flux imposed by internal and external challenges.  It is also important to note the the organs have a concentration of mitochondria, associated with energy synthetic and catabolic requirements provided by oxygen supply and the electron transport mechanism for oxidative phosphorylation.  For example, tissues that are primarily synthetic do not have intermitent states of resting and high demand, as seen in skeletal muscle, or perhaps myocardium (which is syncytial and uses lactic acid generated from skeletal muscle when there is high demand).
  3. The existence of  lncDNA has been discovered only as a result of the human genome project (HGP). This was previously known only as “dark DNA”.  It has become clear that lncDNA has an important role in cellular regulatory activities centered in the chromatin modeling.  Moreover, just as proteins exhibit functionality in their folding, related to tertiary structure and highly influenced by location of –S-S- bridges and amino acid residue distances (allosteric effects), there is a less studied effect as the chromatin becomes more compressed within the nucleus, that should have a bearing on cellular expression.

According to Jose Eduardo de Salles Roselino , when the Na/Glucose transport system (for a review Silvermann, M. in Annu. Rev. Biochem.60: 757-794(1991)) was  found in kidneys as well as in key absorptive cells of digestive tract, it should be stressed its functional relationship with “internal milieu” and real meaning, homeostasis. It is easy to understand how the major topic was presented as how to prevent diarrheal deaths in infants, while detected in early stages. However, from a biochemical point of view, as presented in Schrödinger´s What is life?, (biochemistry offering a molecular view for two legs of biology, physiology and genetics). Why should it be driven to the sole target of understanding genetics? Why the understanding of physiology in molecular terms should be so neglected?

From a biochemical point of view, here in a single protein. It is found the transport of the cation most directly related to water maintenance, the internal solvent that bath our cells and the hydrocarbon whose concentration is kept under homeostatic control on that solvent. Completely at variance with what is presented in microorganisms as previously mentioned in Moyed and Umbarger revision (Ann. Rev42: 444(1962)) that does not regulates the environment where they live and appears to influence it only as an incidental result of their metabolism.

In case any attempt is made in order to explain why the best leg that supports scientific reasoning from biology for medical purposes was led to atrophy, several possibilities can be raised. However, none of them could be placed strictly in scientific terms. Factors that bare little relationship with scientific progress in general terms must also be taken into account.

One simple possibility of explanation can be found in one review (G. Scatchard – Solutions of Electrolytes Ann. Rev. Physical Chemistry 14: 161-176 (1963)).  A simple reading of it and the sophisticated differences among researchers will discourage one hundred per cent of biologists to keep in touch with this line of research. Biochemists may keep on reading.  However, consider that first: Complexity is not amenable to reductionist vision in all cases. Second, as coupling between scalar flows such as chemical reactions and vector flows such as diffusion flows, heat flows, and electrical current can occur only in anisotropic system…let them with their problems of solvents, ions and etc. and let our biochemical reactions on another basket. At the interface, for instance, at membrane level, we will agree that ATP is converted to ADP because it is far from equilibrium and the continuous replenishment of ATP that maintain relatively constant ATP levels inside the cell and this requires some non-stationary flow.

Our major point must be to understand that our biological limits are far clearer present in our limited ability to regulate the information stored in the DNA than in the amount of information we have in the DNA as the master regulator of the cells.

The amazing revelation that Masahiro Chiga   (discovery of liver adenylate kinase  distinct from that of muscle) taught  me (LHB) is – draw 2 circles  that intersect, one of which represents what we know, the other – what we don’t know.  We don’t teach how much we don’t know!  Even today, as much as 40 years ago, there is a lot we need to get on top of this.

 

The observation is rather similar to the presentations I  (Jose Eduardo de Salles Rosalino) was previously allowed to make of the conformational energy as made by R Marcus in his Nobel lecture revised (J. of  Electroanalytical Chemistry 438:(1997) p251-259. His description of the energetic coordinates of a landscape of a chemical reaction is only a two-dimensional cut of what in fact is a volcano crater (in three dimensions) ( each one varie but the sum of the two is constant. Solvational+vibrational=100% in ordinate) nuclear coordinates in abcissa. In case we could represent it by research methods that allow us to discriminate in one by one degree of different pairs of energy, we would most likely have 360 other similar representations of the same phenomenon. The real representation would take into account all those 360 representation together. In case our methodology was not that fine, for instance it discriminate only differences of minimal 10 degrees in 360 possible, will have 36 partial representations of something that to be perfectly represented will require all 36 being taken together. Can you reconcile it with ATGC? Yet, when complete genome sequences were presented they were described as we will know everything about this living being. The most important problems in biology will be viewed by limited vision always and the awareness of this limited is something we should acknowledge and teach it. Therefore, our knowledge is made up of partial representations.

 

Even though we may have complete genome data for the most intricate biological problems, they are not so amenable to this level of reductionism. However, from general views of signals and symptoms we could get to the most detailed molecular view and in this case the genome provides an anchor. This is somehow, what Houssay was saying to me and to Leloir when he pointed out that only in very rare occasions biological phenomena could be described in three terms: Pacco, the dog and the anesthetic (previous e-mail). The non-coding region, to me will be important guiding places for protein interactions.

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Larry H. Bernstein, MD, FCAP, reviewer and curator

http://pharmaceuticalintelligence.com/2013-12-09/larryhbern/VEGF-activation-and-signaling,-lysine-methylation,-and-activation-of-receptor-tyrosine-kinase

Lysine Methylation Promotes VEGFR-2 Activation and Angiogenesis

 Edward J. Hartsough1*, Rosana D. Meyer1*, Vipul Chitalia2, Yan Jiang3, Victor E. Marquez4, Irina V. Zhdanova5, Janice Weinberg6, Catherine E. Costello3, and Nader Rahimi1{dagger}
 1 Departments of Pathology and Ophthalmology, School of Medicine, Boston University Medical Campus, Boston, MA 02118, USA.
2 Harvard-MIT Division of Health Science and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
3 Department of Biochemistry and Center for Biomedical Mass Spectrometry, School of Medicine, Boston University Medical Campus, Boston, MA 02118, USA.
4 Chemical Biology Laboratory, National Cancer Institute at Frederick, Frederick, MD 21702, USA.
5 Department of Anatomy and Neurobiology, Boston University Medical Campus, Boston, MA 02118, USA.
6 School of Public Health, Boston University Medical Campus, Boston, MA 02118, USA.
Activation of vascular endothelial growth factor receptor-2 (VEGFR-2), an endothelial cell receptor tyrosine kinase,
  • promotes tumor angiogenesis and ocular neovascularization.
We report the methylation of VEGFR-2 at multiple Lys and Arg residues, including Lys1041,
  • a residue that is proximal to the activation loop of the kinase domain.
Methylation of VEGFR-2 was
  • independent of ligand binding and
  • was not regulated by ligand stimulation.
Methylation of Lys1041 enhanced tyrosine phosphorylation and kinase activity in response to ligands. Additionally, interfering with the methylation of VEGFR-2 by pharmacological inhibition or by site-directed mutagenesis revealed that
  • methylation of Lys1041 was required for VEGFR-2–mediated angiogenesis
    • in zebrafish and
    • tumor growth in mice.
We propose that methylation of Lys1041 promotes the activation of VEGFR-2 and that
  • similar posttranslational modification could also regulate the activity of other receptor tyrosine kinases.
{dagger} Corresponding author. E-mail: nrahimi@bu.edu
Citation: E. J. Hartsough, R. D. Meyer, V. Chitalia, Y. Jiang, V. E. Marquez, I. V. Zhdanova, J. Weinberg, C. E. Costello, N. Rahimi, Lysine Methylation Promotes VEGFR-2 Activation and Angiogenesis. Sci. Signal. 6, ra104 (2013).

Phosphoproteomic Analysis Implicates the mTORC2-FoxO1 Axis in VEGF Signaling and Feedback Activation of Receptor Tyrosine Kinases

Guanglei Zhuang, Kebing Yu, Zhaoshi Jiang, Alicia Chung, Jenny Yao, Connie Ha, Karen Toy, Robert Soriano, Benjamin Haley, Elizabeth Blackwood, Deepak Sampath, Carlos Bais, Jennie R. Lill, and Napoleone Ferrara (16 April 2013){dagger}
Sci. Signal. 16 April 2013;  6 (271), ra25.    http://dx.doi.org/10.1126/scisignal.2003572
Genentech Inc., 1 DNA Way, South San Francisco, CA 94080, USA.
* These authors contributed equally to this work.{dagger}
{dagger} Present address: Department of Pathology and Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093, USA.
The vascular endothelial growth factor (VEGF) signaling pathway plays a pivotal role in normal development and
  • also represents a major therapeutic target for tumors and intraocular neovascular disorders.
The VEGF receptor tyrosine kinases promote angiogenesis by phosphorylating downstream proteins in endothelial cells. We applied a large-scale proteomic approach to define
  1. the VEGF-regulated phosphoproteome and
  2. its temporal dynamics in human umbilical vein endothelial cells and then
  3. used siRNA (small interfering RNA) screens to investigate the function of a subset of these phosphorylated proteins in VEGF responses.
The PI3K (phosphatidylinositol 3-kinase)–mTORC2 (mammalian target of rapamycin complex 2) axis emerged as central
  1. in activating VEGF-regulated phosphorylation and
  2. increasing endothelial cell viability
    • by suppressing the activity of the transcription factor FoxO1 (forkhead box protein O1),
    • an effect that limited cellular apoptosis and feedback activation of receptor tyrosine kinases.
This FoxO1-mediated feedback loop not only reduced the effectiveness of mTOR inhibitors at decreasing protein phosphorylation and cell survival
  • but also rendered cells more susceptible to PI3K inhibition.
Collectively, our study provides a global and dynamic view of VEGF-regulated phosphorylation events and
  • implicates the mTORC2-FoxO1 axis in VEGF receptor signaling and
  • reprogramming of receptor tyrosine kinases in human endothelial cells.
{ddagger} Corresponding author. E-mail: nferrara@ucsd.edu
Citation: G. Zhuang, K. Yu, Z. Jiang, A. Chung, J. Yao, C. Ha, K. Toy, R. Soriano, B. Haley, E. Blackwood, D. Sampath, C. Bais, J. R. Lill, N. Ferrara, Phosphoproteomic Analysis Implicates the mTORC2-FoxO1 Axis in VEGF Signaling and Feedback Activation of Receptor Tyrosine Kinases. Sci. Signal. 6, ra25 (2013).

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Life Sciences Circle Event: Next omics – Personalized Medicine beyond Genomics, December 11, 2013 5:30-8:30PM, The Broad Institute, Cambridge

Reporter: Aviva Lev-Ari, PhD, RN

December 11, 2013: 5:30pm – 8:30pm

 Over the past decade, the genomics revolution has led to the creation of numerous groundbreaking personalized therapies as well as multiple diagnostic and therapeutic targets.  But what will the next field of biology be similar to that which created the genomics revolution? Join us to learn from thought leaders of several Cambridge-based “’omics” companies and institutions as they discuss their role in improving therapeutic effectiveness, realizing potential reductions in adverse effects,  and the related promises of cost-effectiveness and efficiencies associated with these advances.  We will gain insight from viewing the unique application of epigenetics, metabolomics, microbiomics, proteomics and more from these players to address our individual targeted medical needs and challenges.  What are the challenges of commercializing new technologies and new areas of basic biological research?   Will the next group of ‘omics contribute to the future of personalized therapies and ultimately improve healthcare outcomes and cost-effectiveness in our complex, expensive healthcare system?
Register

Panelists:

Clary Clish, PhD, Director of Metabolite Profiling, Broad Institute

Bernat Olle, PhD, Principal, PureTech

Robert Copeland, PhD, Executive Vice President and Chief Scientific Officer, Epizyme, Inc.

Edward Driggers, PhD, Senior Director, Cell Metabolism, Agios Pharmaceuticals, Inc.

http://www.mitforumcambridge.org/events/life-sciences-circle-event-next-omics-personalized-medicine-beyond-genomics/

 

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Landscape of Cardiac Biomarkers for Improved Clinical Utilization

Curator and Author: Larry H Bernstein, MD, FCAP

Curation

This reviewer has been engaged in the development, the application, and the validation of cardiac biomarkers for over 30 years. There has been a nonlinear introduction of new biomarkers in that period, with an explosion of methods discovery and large studies to validate them in concert with clinical trials. The improvement of interventional methods, imaging methods, and the unraveling of patient characteristics associated with emerging cardiovascular disease is both cause for alarm (technology costs) and for raised expectations for both prevention, risk reduction, and treatment. What is strikingly missing is the kind of data analyses on the population database that could alleviate the burden of physician overload. It is an urgent requirement for the EHR, and it needs to be put in place to facilitate patient care.

Introduction

This is a journey through the current status of biochemical markers in cardiac evaluation. 

In the traditional use of cardiac biomarkers, the is a timed blood sampling from the decubital fossa. This was the case with alanine aminotransferase (AST, then SGOT), creatine kinase (CK) or its isoenzyme MB, and lactic dehydrogenase (or the isoenzyme-1). The time of sampling was based on time to appearance from time of damage, and the release of the biomarker is a stochastic process. The earliest studies of CK-MB appearance, peak height, and disappearance was by Burton Sobel and associates related to measuring the extent of damage, and determined that reperfusion had an effect. A significant reason for using a combination of CK-MB and LD-1 was that a patient who is a late arrival might have a CK-MB on the decline (peak at 18 h) while the LD-1 is rising (peak at 48 h).

The introduction of the troponins was accompanied by a serial 4 h measurement, usually for 4 draws (0, 4, 8, 12 h). The computational power of laboratory information systems was limited until recently, so it is somewhat surprising, given what we have seen – in addition to published work in the 1980’s – that this capability is not in use today, when regression and nonparametric classification algorithms are now so advanced that would enable much improved and effective communication to the physician needing the information.

J Adan, LH Bernstein, J Babb. Can peak CK-MB segregate patients with acute myocardial infarction into different outcome classes? Clin Chem 1985; 31(2):996-997. ICID: 844986.

RA Rudolph, LH Bernstein, J Babb. Information induction for predicting acute myocardial infarction. Clin Chem 1988; 34(10):2031-2038. ICID: 825568.

LH Bernstein, IJ Good, GI Holtzman, ML Deaton, J Babb. Diagnosis of acute myocardial infarction from two measurements of creatine kinase isoenzyme MB with use of nonparametric probability estimation. Clin Chem 1989; 35(3):444-447. ICID: 825570.

L H Bernstein, A Qamar, C McPherson, S Zarich, R Rudolph. Diagnosis of myocardial infarction: integration of serum markers and clinical descriptors using information theory. Clin Chem 1999; 72(1):5-13. ICID: 825618

Vermunt, J.K. & Magidson, J. (2000a). “Latent Class Cluster Analysis”, chapter 3 in J.A. Hagenaars and A.L. McCutcheon (eds.), Advances in Latent Class AnalysisCambridge University Press.

Vermunt, J.K. & Magidson, J. (2000b). Latent GOLD 2.0 User’s Guide. Belmont, MA: Statistical Innovations Inc.

LH Bernstein, A Qamar, C McPherson, S Zarich. Evaluating a new graphical ordinal logit method (GOLDminer) in the diagnosis of myocardial infarction utilizing clinical features and laboratory data. Yale J Biol Med. 1999; 72(4):259-268. ICID: 825617.

L Bernstein, K Bradley, S Zarich. GOLDmineR: improving models for classifying patients with chest pain.
Yale J Biol Med. 2002; 75(4):183-198. ICID: 825624

SA Haq, M Tavakol, LH Bernstein, J Kneifati-Hayek, M Schlefer, et al. The ACC/ESC Recommendation for 99th Percentile of the Reference NormalTroponin I Overestimates the Risk of an Acute Myocardial Infarction: a novel enhancement in the diagnostic performance of troponins. “6th Scientific Forum on Quality of Care and Outcomes Research in Cardiovascular Disease and Stroke.” Circulation 2005; 111(20):e313-313. ICID: 939931.

LH Bernstein, MY Zions, SA Haq, S Zarich, J Rucinski, B Seamonds, …., John F Heitner. Effect of renal function loss on NT-proBNP level variations. Clin Biochem 2009; 42(10-11):1091-1098. ICID: 937529

SA Haq, M Tavakol, S Silber, L Bernstein, J Kneifati-Hayek, et al. Enhancing the diagnostic performance of troponins in the acute care setting. J Emerg Med 2008; ICID: 937619

Gil David, LarryH Bernstein, Ronald Coifman. Generating Evidence Based Interpretation of Hematology Screens via Anomaly Characterization. OCCJ 2011; 4(1):10-16. ICID: 939928

The use and limitations of high-sensitivity cardiac troponin and natriuretic peptide concentrations in at risk populations

Background: High-sensitivity cardiac troponin (hs-cTn) assays are now available that can detect measurable troponin in significantly more individuals in the general population than conventional assays. The clinical use of these hs-cTn assays depends on the development of proper reference values. However, even with a univariate biomarker for risk and/or severity of ischemic heart disease, a single reference value for the cardiac biomarker does not discriminate the probabilities between 2 or 3 different cardiac disorders, or identify any combination of these, such as, heart failure or renal disease > stage 2 and acute coronary syndrome. True, the physician has a knowledge of the history and presentation as a guide. Do we know how adequate the information is in a patient who has an atypical presentation? Again, the same problem arises with the use of the natriuretic peptides, but the value of these tests is improved over the previous generation tests. Let us parse through the components of this diagnostic problem, which is critical for reaching the best decisions under the circumstances.

Issue 1. The use of the clinical information, such as, patient age, gender, past medical history, known medical illness, CHEST PAIN, ECG, medications, are the basis of longstanding clinical practice. These may be sufficient in a patient who presents with acute coronary syndrome and a Q-wave not previously seen, or with ST-elevation, ST-depression, T-wave inversion, or rhythm abnormality. Many patients don’t present that way.

Issue 2. The use of a single ‘decision-value’ for critical situations decribed, leaves us with a yes-no answer. If you use a receiver-operator characteristic curve, all of the patients used to construct the sensitivity/specificity analysis have to be decisively known for identification. Otherwise, one might just take the median of a very large population, and the median represents the best value for a data set that is not normal distribution. However, the ROC method may inform about an acute event, if that is the purpose, but with a single value for a single variable, it can’t identify a likelihood of an event in the next six months.

Issue 3. There are several quantitative biomarkers that are considerably better than were available 15 years prior to this discussion. These can be used alone, but preferably in combination for diagnostic evaluation, for predictiong prognosis, and for therapeutic decision-making. What is now available was unimagined 20 years ago, both in test selection and in treatment selection.

Cardiac troponin assays were recently reviewed in Clin Chem by Fred Apple and Amy Seenger. (The State of Cardiac Troponin Assays: Looking Bright and Moving in the Right Direction).

Cardiac troponin assays have evolved substantially over 20 years, owing to the efforts of manufacturers to make them more precise and sensitive. These enhancements have led to high-sensitivity cardiac troponin assays, which ideally would give measureable values above the limit of detection (LoD) for 100% of healthy individuals and demonstrate an imprecision (CV) of ≤10% at the 99th percentile.

As laboratorians, we wish to comment on the recently published “ACCF 2012 Expert Consensus Document on Practical Clinical Considerations in the Implementation of Troponin Elevations”. Our purpose is to address 8 analytical issues that we believe have the potential to cause confusion and that therefore deserve clarification.

Since the initial publications by the National Academy of Clinical Biochemistry (NACB) in 1999 and by the European Society of Cardiology/American College of Cardiology in 2000, when both organizations endorsed cardiac troponin I (cTnI) or cTnT as the preferred biomarker for the detection of myocardial infaction, numerous other organizations have followed suit and promoted the sole use of cardiac troponin in this clinical application. The American College of Cardiology Foundation (ACCF) 2012 Expert Consensus Document summarizes the recently published 2012 Third Universal Definition of Myocardial Infarction by the Global Task Force, thus providing some practical recommendations on the use and interpretation of cardiac troponin in clinical practice.

This commentator has already expressed the view that there is no ‘silver bullet’, and the potential for confusion is not yet going to be resolved. The potential for greater accuracy in diagnosis is bolstered by currently available imaging.

Current strength of cardiac biomarker opportunities:

A recent study measured hs-tnI in 1716 (93%) of the community-based study cohort and 499 (88%) of the healthy reference cohort. Parameters that significantly contributed to higher hs-cTnI concentrations in the healthy reference cohort included age, male sex, systolic blood pressure, and left ventricular mass. Glomerular filtration rate and body mass index were not independently associated with hs-cTnI in the healthy reference cohort. Individuals with diastolic and systolic dysfunction, hypertension, and coronary artery disease (but not impaired renal function) had significantly higher hs-cTnI values than the healthy reference cohort.

The authors concluded that hs-cTnI assay with the aid of echocardiographic imaging in a large, well-characterized community-based cohort demonstrated hs-cTnI to be remarkably sensitive in the general population, and there are important sex and age differences among healthy reference individuals. Even though the results have important implications for defining hs-cTnI reference values and identifying disease, the reference value is not presented, and the question remains about how many subjects in the 88% (499) healthy reference consort had elevated systolic blood pressure or left ventricular hypertrophy (LVH) measured by imaging. Furthermore, while impaired renal function dropped out as an independent predictor of associated hs-cTnI, one would expect it to have a strong association with LVH.

Defining High-Sensitivity Cardiac Troponin Concentrations in the Community.
PM McKie, DM Heublein, CG. Scott, ML Gantzer, …and AS Jaffe.
Depart Med & Lab Med and Pathology, Mayo Clinic and Foundation, Rochester, MN; Siemens Diagnostics, Newark, DE. Clin Chem 2013.

hsTnI with NSTEMI

Another study looks at the prognostic performance of hs-TnI assay with non-STEMI. High-sensitivity assays for cardiac troponin enable more precise measurement of very low concentrations and improved diagnostic accuracy. However, the prognostic value of these measurements, particularly at low concentrations, is less well defined. (This is the sensitivity vs specificity dilemma raised with regard to the impoved hs-cTn assays.) But the value of low measured values is a matter for prognostic evaluation, based on the hypothesis that any cTnI that is measured in serum is leaked from cardiomyocytes. This assay evaluation used the Abbott ARCHITECT. The data were 4695 patients with non–ST-segment elevation acute coronary syndromes (NSTE-ACS) from the EARLY-ACS (Early Glycoprotein IIb/IIIa Inhibition in NSTE-ACS) and SEPIA-ACS1-TIMI 42 (Otamixaban for the Treatment of Patients with NSTE-ACS–Thrombolysis in Myocardial Infarction 42) trials. The primary endpoint was cardiovascular death or new myocardial infarction (MI) at 30 days. Baseline cardiac troponin was categorized at the 99th percentile reference limit (26 ng/L for hs-cTnI; 10 ng/L for cTnT) and at sex-specific 99th percentiles for hs-cTnI.

All patients at baseline had detectable hs-cTnI compared with 94.5% with detectable cTnT. With adjustment for all other elements of the TIMI risk score, patients with hs-cTnI ≥99th percentile had a 3.7-fold higher adjusted risk of cardiovascular death or MI at 30 days relative to patients with hs-cTnI <99th percentile (9.7% vs 3.0%; odds ratio, 3.7; 95% CI, 2.3–5.7; P < 0.001). Similarly, when stratified by categories of hs-cTnI, very low concentrations demonstrated a graded association with cardiovascular death or MI (P-trend < 0.001). Thus, Application of this hs-cTnI assay identified a clinically relevant higher risk of recurrent events among patients with NSTE-ACS, even at very low troponin concentrations.

Prognostic Performance of a High-Sensitivity Cardiac Troponin I Assay in Patients with Non–ST-Elevation Acute Coronary Syndrome. EA Bohula May, MP Bonaca, P Jarolim, EM Antman, …and DA Morrow. Clin Chem 2013.

Combination test with cTnI and a troponin

The next study looks at the value of a combination of cTnT and N-Terminal pro-B-type-natriuretic-peptide (NT proBNP) to predict heart failure risk. Recall that NT proBNP has been a stabd-alone biomarker for CHF. The study was done with the consideration that heart failure (HF) is projected to have the largest increases in incidence over the coming decades. Therefore, would cardiac troponin T (cTnT) measured with a high-sensitivity assay and N-terminal pro-B–type natriuretic peptide (NT-proBNP), biomarkers strongly associated with incident HF, improve HF risk prediction in the Atherosclerosis Risk in Communities (ARIC) study?

Using sex-specific models, we added cTnT and NT-proBNP to age and race (“laboratory report” model) and to the ARIC HF model (includes age, race, systolic blood pressure, antihypertensive medication use, current/former smoking, diabetes, body mass index, prevalent coronary heart disease, and heart rate) in 9868 participants without prevalent HF; area under the receiver operating characteristic curve (AUC), integrated discrimination improvement, net reclassification improvement (NRI), and model fit were described.

Over a mean follow-up of 10.4 years, 970 participants developed incident HF. Adding cTnT and NT-proBNP to the ARIC HF model significantly improved all statistical parameters (AUCs increased by 0.040 and 0.057; the continuous NRIs were 50.7% and 54.7% in women and men, respectively). Interestingly, the simpler laboratory report model was statistically no different than the ARIC HF model.

Troponin T and N-Terminal Pro-B–Type Natriuretic Peptide: A Biomarker Approach to Predict Heart Failure Risk: The Atherosclerosis Risk in Communities Study. V Nambi, X Liu, LE Chambless, JA de Lemos, SS Virani, et al.
Clin Chem 2013.

BCM Researchers Discover Simpler, Improved Biomarkers to Predict Heart Failure As Accurate As Complex Models     Posted by: Anna Ishibashi Sep 17, 2013

Biomarkers for heart failure Researchers at the Baylor College of Medicine and the Michael E. DeBakey Veterans Affairs hospital discovered two improved biomarkers in the bloodstream that predict who is at higher risk of having heart failure in 10 years. The study was published in the journal Clinical Chemistry.

In the Atherosclerosis Risk in Communities (ARIC) clinical study, researchers measured the blood concentration of troponin T and N-terminal-pro-B-type natriuretic peptide (NT-proBNP) in the models, while also collecting age and race data. The important point taken from the study was that researchers did not find any difference in the accuracy of heart failure risk prediction statistically between this simpler test and the traditional, more complex one, which includes information of age, race, systolic blood pressure, antihypertensive medication use, smoking status, diabetes, body-mass index, prevalent coronary heart disease and heart rate.

Troponin T is an indicator of damaged heart muscle and can be detected in low levels even in individuals with no symptoms through this simpler, improved testing method. Similarly, NT-proBNP is a by-product of brain natriuretic peptide (BNP), which is a small neuropeptide hormone that has been shown to be effective in diagnosing congestive heart failure.

The critical issues that we must now address is what lifestyle and drug therapies can prevent the development of heart failures for individuals who are at high risk – according to Dr. Christie Ballantyne, professor of medicine and section chief of cardiology and cardiovascular research at BCM and the Houston Methodist Center for Cardiovascular Disease Prevention.

Although chest pain is widely considered a key symptom in the diagnosis of myocardial infarction (MI), not all patients with MI present with chest pain. This study was done the frequency with which patients with MI present without chest pain and to examine their subsequent management and outcome. A total of 434,877 patients with confirmed MI enrolled June 1994 to March 1998 in the National Registry of Myocardial Infarction, which includes 1674 hospitals in the United States. Outcome measures were prevalence of presentation without chest pain; clinical characteristics, treatment, and mortality among MI patients without chest pain vs those with chest pain.

Of all patients diagnosed as having MI, 142,445 (33%) did not have chest pain on presentation to the hospital. This group of MI patients was, on average, 7 years older than those with chest pain (74.2 vs 66.9 years), with a higher proportion of women (49.0% vs 38.0%) and patients with diabetes mellitus (32.6% vs 25.4%) or prior heart failure (26.4% vs 12.3%). Also, MI patients without chest pain had a longer delay before hospital presentation (mean, 7.9 vs 5.3 hours), were less likely to be diagnosed as having confirmed MI at the time of admission (22.2% vs 50.3%), and were less likely to receive thrombolysis or primary angioplasty (25.3% vs 74.0%), aspirin (60.4% vs 84.5%), β-blockers (28.0% vs 48.0%), or heparin (53.4% vs 83.2%). Myocardial infarction patients without chest pain had a 23.3% in-hospital mortality rate compared with 9.3% among patients with chest pain (adjusted odds ratio for mortality, 2.21 [95% confidence interval, 2.17-2.26]).

We tested the hypotheses that MI patients without chest pain compared with those with chest pain would present later for medical attention, would be less likely to be diagnosed as having acute MI on initial evaluation, and would receive fewer appropriate medical treatments within the first 24 hours. We also evaluated the association between the presence of atypical presenting symptoms and hospital mortality related to MI.

Our results suggest that patients without chest pain on presentation represent a large segment of the MI population and are at increased risk for delays in seeking medical attention, less aggressive treatments, and in-hospital mortality.

Prevalence, Clinical Characteristics, and Mortality Among Patients With Myocardial Infarction Presenting Without Chest Pain. JG Canto, MG Shlipak, WJ Rogers, JA Malmgren, PD Frederick, et al. JAMA 2013; 283(24):3223-3229. http://dx.doi.org/10.1001/jama.283.24.3223

cTnT degraded forms in circulation

This recent study questions whether degraded cTnT forms circulate in the patient’s blood. Separation of cTnT forms by gel filtration chromatography (GFC) was performed in sera from 13 AMI patients to examine cTnT degradation. The GFC eluates were subjected to Western blot analysis with the original antibodies from the Roche immunoassay used to mimic the clinical cTnT assay. GFC analysis of AMI patients’ sera revealed 2 cTnT peaks with retention volumes of 5 and 21 mL. Western blot analysis identified these peaks as cTnT fragments of 29 and 14–18 kDa, respectively. Furthermore, the performance of direct Western blots on standardized serum samples demonstrated a time-dependent degradation pattern of cTnT, with fragments ranging between 14 and 40 kDa. Intact cTnT (40 kDa) was present in only 3 patients within the first 8 h after hospital admission.

Time-Dependent Degradation Pattern of Cardiac Troponin T Following Myocardial Infarction. EPM Cardinaels, AMA Mingels T van Rooij, PO Collinson, FW Prinzen and MP van Dieijen-Visser. Clin Chem 2013.

Older patients with higher cTNI

One of the problems of interpretation of cTnI is the age relationship to the 99th percentile of the elderly. cTnI was measured using a high-sensitivity assay (Abbott Diagnostics) in 814 community-dwelling individuals at both 70 and 75 years of age. The cTnI 99th percentiles were determined separately using nonparametric methods in the total sample, in men and women, and in individuals with and without CVD.

The cTnI 99th percentile at baseline was 55.2 ng/L for the total cohort. Higher 99th percentiles were noted in men (69.3 ng/L) and individuals with CVD (74.5 ng/L). The cTnI 99th percentile in individuals free from CVD at baseline (n = 498) increased by 51% from 38.4 to 58.0 ng/L during the 5-year observation period. Relative increases ranging from 44% to 83% were noted across all subgroups. Male sex [odds ratio, 5.3 (95% CI, 1.5–18.3)], log-transformed N-terminal pro-B-type natriuretic peptide [odds ratio, 1.9 (95% CI, 1.2–3.0)], and left-ventricular mass index [odds ratio, 1.3 (95% CI, 1.1–1.5)] predicted increases in cTnI concentrations from below the 99th percentile (i.e., 38.4 ng/L) at baseline to concentrations above the 99th percentile at the age of 75 years.

cTnI concentration and its 99th percentile threshold depend strongly on the characteristics of the population being assessed. Among elderly community dwellers, higher concentrations were seen in men and individuals with prevalent CVD. Aging contributes to increasing concentrations, given the pronounced changes seen with increasing age across all subgroups. These findings should be taken into consideration when applying cTnI decision thresholds in clinical settings.

KM Eggers, Lars Lind, Per Venge and Bertil Lindahl. Factors Influencing the 99th Percentile of Cardiac Troponin I Evaluated in Community-Dwelling Individuals at 70 and 75 Years of Age/. Clin Chem 2013.

Background: Atrial natriuretic peptide (ANP) has antihypertrophic and antifibrotic properties that are relevant to AF substrates. The −G664C and rs5065 ANP single nucleotide polymorphisms (SNP) have been described in association with clinical phenotypes, including hypertension and left ventricular hypertrophy. A recent study assessed the association of early AF and rs5065 SNPs in low-risk subjects. In a Caucasian population with moderate-to-high cardiovascular risk profile and structural AF, we conducted a case-control study to assess whether the ANP −G664C and rs5065 SNP associate with nonfamilial structural AF.
Methods: 168 patients with nonfamilial structural AF and 168 age- and sex-matched controls were recruited. The rs5065 and −G664C ANP SNPs were genotyped.
Results: The study population had a moderate-to-high cardiovascular risk profile with 86% having hypertension, 23% diabetes, 26% previous myocardial infarction, and 23% left ventricular systolic dysfunction. Patients with AF had greater left atrial diameter (44 ± 7 vs. 39 ± 5 mm; P , 0.001) and higher plasma NTproANP levels (6240 ± 5317 vs. 3649 ± 2946 pmol/mL; P , 0.01). Odds ratios (ORs) for rs5065 and −G664C gene variants were 1.1 (95% confidence interval [CI], 0.7–1.8; P = 0.71) and 1.2 (95% CI, 0.3–3.2; P = 0.79), respectively, indicating no association with AF. There were no differences in baseline clinical characteristics among carriers and noncarriers of the −664C and rs5065 minor allele variants.
Conclusions: We report lack of association between the rs5065 and −G664C ANP gene SNPs and AF in a Caucasian population of patients with structural AF. Further studies will clarify whether these or other ANP gene variants affect the risk of different subphenotypes of AF driven by distinct pathophysiological mechanisms.

P Francia, A Ricotta, A Frattari, R Stanzione, A Modestino, et al.
Atrial Natriuretic Peptide Single Nucleotide Polymorphisms in Patients with Nonfamilial Structural Atrial Fibrillation.
Clinical Medicine Insights: Cardiology 2013:7 153–159   http://dx.doi.org/10.4137/CMC.S12239  http://www.la-press.com/atrial-natriuretic-peptide-single-nucleotide-polymorphisms-in-patients-article-a3882

Cystatin C and eGFR predict AMI or CVD mortality

BACKGROUND: The estimated glomerular filtration rate (eGFR) independently predicts cardiovascular death or myocardial infarction (MI) and can be estimated by creatinine and cystatin C concentrations. We evaluated 2 different cystatin C assays, alone or combined with creatinine, in patients with acute coronary syndrome.
METHODS: We analyzed plasma cystatin C, measured with assays from Gentian and Roche, and serum creatinine in 16 279 patients from the PLATelet Inhibition and Patient Outcomes (PLATO) trial. We evaluated Pearson correlation and agreement (Bland–Altman) between methods, as well as prognostic value in relation to cardiovascular death or MI during 1 year of follow up by multivariable logistic regression analysis including clinical variables, biomarkers, c-statistics, and relative integrated discrimination improvement (IDI).
RESULTS: Median cystatin C concentrations (interquartile intervals) were 0.83 (0.68–1.01) mg/L (Gentian) and 0.94 (0.80–1.14) mg/L (Roche). Overall correlation was 0.86 (95% CI 0.85–0.86). The level of agreement was within 0.39 mg/L (2 SD) (n = 16 279).
The areas under the curve (AUCs) in the multivariable risk prediction model with cystatin C (Gentian, Roche) or Chronic Kidney Disease Epidemiology Collaboration eGFR (CKD-EPI) added were 0.6914, 0.6913, and 0.6932. Corresponding relative IDI values were 2.96%, 3.86%, and 4.68% (n = 13 050). Addition of eGFR by the combined creatinine–cystatin C equation yielded AUCs of 0.6923 (Gentian) and 0.6924 (Roche) with relative IDI values of 3.54% and 3.24%.
CONCLUSIONS: Despite differences in cystatin C concentrations, overall correlation between the Gentian and Roche assays was good, while agreement was moderate. The combined creatinine–cystatin C equation did not outperform risk prediction by CKD-EPI.
A Åkerblom, L Wallentin, A Larsson, A Siegbahn, et al.
Cystatin C– and Creatinine-Based Estimates of Renal Function and Their Value for Risk Prediction in Patients with Acute Coronary Syndrome: Results from the PLATelet Inhibition and Patient Outcomes (PLATO) Study.
 

T2Dm has many subphenotypes in the prediabetic phase

For decades, glucose, hemoglobin A1c, insulin, and C peptide have been the laboratory tests of choice to detect and monitor diabetes. However, these tests do not identify individuals at risk for developing type 2 diabetes (T2Dm) (so-called prediabetic individuals and the subphenotypes therein), which would be a prerequisite for individualized prevention. Nor are these parameters suitable to identify T2Dm subphenotypes, a prerequisite for individualized therapeutic interventions. The oral glucose tolerance test (oGTT) is still the only means for the early and reliable identification of people in the prediabetic phase with impaired glucose tolerance (IGT). This procedure, however, is very time-consuming and expensive and is unsuitable as a screening method in a doctor′s office. Hence, there is an urgent need for innovative laboratory tests to simplify the early detection of alterations in glucose metabolism.
The search for diabetic risk genes was the first and most intensively pursued approach for individualized diabetes prevention and treatment. Over the last 20 years cohorts of tens of thousands of people have been analyzed, and more than 70 susceptibility loci associated with T2Dm and related metabolic traits have been identified. But despite extensive replication, no susceptibility loci or combinations of loci have proven suitable for diagnostic purposes.
Why did the genomic studies fail? One reason might be that T2Dm is a polygenetic disease, but there is another more important reason. The large diabetes cohorts investigated in these studies were very heterogeneous, consisting of poorly characterized individuals who were usually selected because they had an increase in blood glucose. Subsequently it has become clear that many different subphenotypes already exist in the prediabetic phase.
Metabolomics represents a new potential approach to move the diagnosis of diabetes beyond the application of the classical diabetic laboratory tests.
Rainer Lehmann. Diabetes Subphenotypes and Metabolomics: The Key to Discovering Laboratory Markers for Personalized Medicine?
 

Ca2+/calmodulin-dependent protein kinase II (CaMKII) has recently emerged as a ROS activated proarrhythmic signal

Background—Atrial fibrillation is a growing public health problem without adequate therapies. Angiotensin II (Ang II) and reactive oxygen species (ROS) are validated risk factors for atrial fibrillation (AF) in patients, but the molecular pathway(s) connecting ROS and AF is unknown. The Ca2+/calmodulin-dependent protein kinase II (CaMKII) has recently emerged as a ROS activated proarrhythmic signal, so we hypothesized that oxidized CaMKII􀄯(ox-CaMKII) could contribute to AF.
Methods and Results—We found ox-CaMKII was increased in atria from AF patients compared to patients in sinus rhythm and from mice infused with Ang II compared with saline. Ang II treated mice had increased susceptibility to AF compared to saline treated WT mice, establishing Ang II as a risk factor for AF in mice. Knock in mice lacking critical oxidation sites in CaMKII􀄯 (MM-VV) and mice with myocardial-restricted transgenic over-expression of methionine sulfoxide reductase A (MsrA TG), an enzyme that reduces ox-CaMKII, were resistant to AF induction after Ang II infusion.
 
RyR and Ca+ release from SR
 
ANS-   autonomic innervation of heart
 
 
mongillo_fig1  regulation of cardiac Ca++ cycling by ANS
 
jce561317.fig3    cardiac contraction
 
 
 
 
serum levels of MAA differentiated stable CAD from MI. For IgM antibodies to MAA, results were consistent with IgGantibodies to MAA
 
 
 
Conclusions—Our studies suggest that CaMKII is a molecular signal that couples increased ROS with AF and that therapeutic strategies to decrease ox-CaMKII may prevent or reduce AF.
Key words: atrial fibrillation, calcium/calmodulin-dependent protein kinase II, angiotensin II, reactive oxygen species, arrhythmia (mechanisms)
A Purohit, AG Rokita, X Guan, B Chen, et al.  Oxidized CaMKII Triggers Atrial Fibrillation.  Circulation. Sep 12, 2013;
 

Microparticles (MP)s give clues about vascular endothelial injury

BACKGROUND: Endothelial dysfunction is an early event in the development and progression of a wide range of cardiovascular diseases. Various human studies have identified that measures of endothelial dysfunction may offer prognostic information with respect to vascular events. Microparticles (MPs) are a heterogeneous population of small membrane fragments shed from various cell types. The endothelium is one of the primary targets of circulating MPs, and MPs isolated from blood have been considered biomarkers of vascular injury and inflammation.
CONTENT: This review summarizes current knowledge of the potential functional role of circulating MPs in promoting endothelial dysfunction. Cells exposed to different stimuli such as shear stress, physiological agonists, proapoptotic stimulation, or damage release MPs, which contribute to endothelial dysfunction and the development of cardiovascular diseases. Numerous studies indicate that MPs may trigger endothelial dysfunction by disrupting production of nitric oxide release from vascular endothelial cells and subsequently modifying vascular tone. Circulating MPs affect both proinflammatory and proatherosclerotic processes in endothelial cells. In addition, MPs can promote coagulation and inflammation or alter angiogenesis and apoptosis in endothelial cells.
SUMMARY: MPs play an important role in promoting endothelial dysfunction and may prove to be true biomarkers of disease state and progression.
Fina Lovren and Subodh Verma.  Evolving Role of Microparticles in the Pathophysiology of Endothelial Dysfunction.
 
Outcomes of STEMI and NSTEMI different predicted by NPs after MI
Patients with increased blood concentrations of natriuretic peptides (NPs) have poor cardiovascular outcomes after myocardial infarction (MI). Data from 41 683 patients with non–ST-segment elevation MI (NSTEMI) and 27 860 patients with ST-segment elevation MI (STEMI) at 309 US hospitals were collected as part of the ACTION Registry®–GWTG™ (Acute Coronary Treatment and Intervention Outcomes Network Registry–Get with the Guidelines) (AR-G) between July 2008 and September 2009.

B-type natriuretic peptide (BNP) or N-terminal pro-BNP (NT-proBNP) was measured in 19 528 (47%) of NSTEMI and 9220 (33%) of STEMI patients. Patients in whom NPs were measured were older and had more comorbidities, including prior heart failure or MI. There was a stepwise increase in the risk of in-hospital mortality with increasing BNP quartiles for both NSTEMI (1.3% vs 3.2% vs 5.8% vs 11.1%) and STEMI (1.9% vs 3.9% vs 8.2% vs 17.9%). The addition of BNP to the AR-G clinical model improved the C statistic from 0.796 to 0.807 (P < 0.001) for NSTEMI and from 0.848 to 0.855 (P = 0.003) for STEMI. The relationship between NPs and mortality was similar in patients without a history of heart failure or cardiogenic shock on presentation and in patients with preserved left ventricular function.

NPs are measured in almost 50% of patients in the US admitted with MI and appear to be used in patients with more comorbidities. Higher NP concentrations were strongly and independently associated with in-hospital mortality in the almost 30 000 patients in whom NPs were assessed, including patients without heart failure.

BM Scirica, MB Kadakia, JA de Lemos, MT Roe, DA Morrow, et al. Association between Natriuretic Peptides and Mortality among Patients Admitted with Myocardial Infarction: A Report from the ACTION Registry®–GWTG™.

Predictive value of processed forms of BNP in circulation

B-type natriuretic peptide (BNP) is secreted in response to pathologic stress from the heart. Its use as a biomarker of heart failure is well known; however, its diagnostic potential in ischemic heart disease is less explored. Recently, it has been reported that processed forms of BNP exist in the circulation. We characterized processed forms of BNP by a newly developed mass spectrometry–based detection method combined with immunocapture using commercial anti-BNP antibodies.

Measurements of processed forms of BNP by this assay were found to be strongly associated with presence of restenosis. Reduced concentrations of the amino-terminal processed peptide BNP(5–32) relative to BNP(3–32) [as the index parameter BNP(5–32)/BNP(3–32) ratio] were seen in patients with restenosis [median (interquartile range) 1.19 (1.11–1.34), n = 22] vs without restenosis [1.43 (1.22–1.61), n = 83; P < 0.001] in a cross-sectional study of 105 patients undergoing follow-up coronary angiography. A sensitivity of 100% to rule out the presence of restenosis was attained at a ratio of 1.52. Processed forms of BNP may serve as viable potential biomarkers to rule out restenosis.

H Fujimoto, T Suzuki, K Aizawa, D Sawaki, J Ishida, et al. Processed B-Type Natriuretic Peptide Is a Biomarker of Postinterventional Restenosis in Ischemic Heart Disease. Clin Chem 2013.

Circulating proteins from patients requiring revascularization

More than a million diagnostic cardiac catheterizations are performed annually in the US for evaluation of coronary artery anatomy and the presence of atherosclerosis. Nearly half of these patients have no significant coronary lesions or do not require mechanical or surgical revascularization. Consequently, the ability to rule out clinically significant coronary artery disease (CAD) using low cost, low risk tests of serum biomarkers in even a small percentage of patients with normal coronary arteries could be highly beneficial. METHODS: Serum from 359 symptomatic subjects referred for catheterization was interrogated for proteins involved in atherogenesis, atherosclerosis, and plaque vulnerability. Coronary angiography classified 150 patients without flow-limiting CAD who did not require percutaneous intervention (PCI) while 209 required coronary revascularization (stents, angioplasty, or coronary artery bypass graft surgery). Continuous variables were compared across the two patient groups for each analyte including calculation of false discovery rate (FDR [less than or equal to]1%) and Q value (P value for statistical significance adjusted to [less than or equal to]0.01).

Significant differences were detected in circulating proteins from patients requiring revascularization including increased apolipoprotein B100 (APO-B100), C-reactive protein (CRP), fibrinogen, vascular cell adhesion molecule 1 (VCAM-1), myeloperoxidase (MPO), resistin, osteopontin, interleukin (IL)-1beta, IL-6, IL-10 and N-terminal fragment protein precursor brain natriuretic peptide (NT-pBNP) and decreased apolipoprotein A1 (APO-A1). Biomarker classification signatures comprising up to 5 analytes were identified using a tunable scoring function trained against 239 samples and validated with 120 additional samples. A total of 14 overlapping signatures classified patients without significant coronary disease (38% to 59% specificity) while maintaining 95% sensitivity for patients requiring revascularization. Osteopontin (14 times) and resistin (10 times) were most frequently represented among these diagnostic signatures. The most efficacious protein signature in validation studies comprised osteopontin (OPN), resistin, matrix metalloproteinase 7 (MMP7) and interferon gamma (IFNgamma) as a four-marker panel while the addition of either CRP or adiponectin (ACRP-30) yielded comparable results in five protein signatures.

Proteins in the serum of CAD patients predominantly reflected

  1. a positive acute phase, inflammatory response and

  2. alterations in lipid metabolism, transport, peroxidation and accumulation.

    There were surprisingly few indicators of growth factor activation or extracellular matrix remodeling in the serum of CAD patients except for elevated OPN. These data suggest that many symptomatic patients without significant CAD could be identified by a targeted multiplex serum protein test without cardiac catheterization thereby eliminating exposure to ionizing radiation and decreasing the economic burden of angiographic testing for these patients.

WA Laframboise, R Dhir, LA Kelly, P Petrosko, JM Krill-Burger, et al. Serum protein profiles predict coronary artery disease in symptomatic patients referred for coronary angiography.
BMC Medicine (impact factor: 6.03). 12/2012; 10(1):157. http://dx.doi.org/10.1186/1741-7015-10-157

miRNAs in CAD

MicroRNAs are small RNAs that control gene expression. Besides their cell intrinsic function, recent studies reported that microRNAs are released by cultured cells and can be detected in the blood. To address the regulation of circulating microRNAs in patients with stable coronary artery disease. To determine the regulation of microRNAs, we performed a microRNA profile using RNA isolated from n=8 healthy volunteers and n=8 patients with stable coronary artery disease that received state-of-the-art pharmacological treatment. Interestingly, most of the highly expressed microRNAs that were lower in the blood of patients with coronary artery disease are known to be expressed in endothelial cells (eg, miR-126 and members of the miR-17 approximately 92 cluster). To prospectively confirm these data, we detected selected microRNAs in plasma of 36 patients with coronary artery disease and 17 healthy volunteers by quantitative PCR. Consistent with the data obtained by the profile, circulating levels of miR-126, miR-17, miR-92a, and the inflammation-associated miR-155 were significantly reduced in patients with coronary artery disease compared with healthy controls. Likewise, the smooth muscle-enriched miR-145 was significantly reduced. In contrast, cardiac muscle-enriched microRNAs (miR-133a, miR-208a) tend to be higher in patients with coronary artery disease. These results were validated in a second cohort of 31 patients with documented coronary artery disease and 14 controls. Circulating levels of vascular and inflammation-associated microRNAs are significantly downregulated in patients with coronary artery disease.

S Fichtlscherer, S De Rosa, H Fox, T Schwietz, A Fischer, et al. Circulating microRNAs in patients with coronary artery disease. Circulation Research 09/2010; 107(5):677-84.

Imaging modalities compared

This review compares the noninvasive anatomical imaging modalities of coronary artery calcium scoring and coronary CT angiography to the functional assessment modality of MPI in the diagnosis and prognostication of significant CAD in symptomatic patients. A large number of studies investigating this subject are analyzed with a critical look on the evidence, underlying the strengths and limitations. Although the overall findings of the presented studies are favoring the use of CT-based anatomical imaging modalities over MPI in the diagnosis and prognosticating of CAD, the lack of a high number of large- scale, multicenter randomized controlled studies limits the generalizability of this early evidence. Further studies comparing the short- and long-term clinical outcomes and cost-effectiveness of these tests are required to determine their optimal role in the management of symptomatic patients with suspected CAD.

Y Hacioglu, M Gupta, Matthew J Budoff. Noninvasive anatomical coronary artery imaging versus myocardial perfusion imaging: which confers superior diagnostic and prognostic information?
Journal of computer assisted tomography 34(5):637-44.

Three Dimensional In-Room Imaging (3DCA) in PCI

Introduction: Coronary angiography is a two-dimensional (2D) imaging modality and thus is limited in its ability to represent complex three-dimensional (3D) vascular anatomy. Lesion length, bifurcation angles/lesions, and tortuosity are often inadequately assessed using 2D angiography due to vessel overlap and foreshortening. 3D Rotational Angiography (3DRA) with subsequent reconstruction generates models of the coronary vasculature from which lesion length measurements and Optimal View Maps (OVM) defining the amount of vessel foreshortening for each gantry angle can be derived. This study sought to determine if 3DRA-assisted percutaneous coronary interventions resulted in improved procedural results by minimizing foreshortening and optimizing stent selection.
 Rotational angiographic acquisitions were performed and a 3D model was generated from two images greater than 30° apart. An optimal view map identifying the least amount of vessel foreshortening and overlap was derived from the 3D model.
The clinical validation of in-room image-processing tools such as 3DCA and optimal view maps is important since FDA approval of these tools does not require the presentation of any data on clinical experience and impact on clinical outcomes. While the technology of 3DRA and optimal view calculations has been well validated by the work of Chen and colleagues, this study is important in demonstrating how clinical care may be impacted [4,5,7]. This study was biased toward minimizing the impact of these tools on clinical decision-making since the study site, cardiologists, and staff have extensive experience in rotational angiography, 3-D modeling and reconstruction, and the impact of foreshortening on the assessment of lesion length and choice of stent size.
3DRA assistance significantly reduced target vessel foreshortening when compared to operator’s choice of working view for PCI (2.99% ± 2.96 vs. 9.48% ± 7.56, p=0.0001). The operators concluded that 3DRA recommended better optimal view selection for PCI in 14 of 26 (54%) total cases. In 9 (35%) of 26 cases 3DRA assistance facilitated stent positioning. 3DRA based imaging prompted stent length changes in 4/26 patients (15%).
MH. Eng, PA Hudson, AJ Klein, SYJ Chen, … , JA Garcia. Impact of Three Dimensional In-Room Imaging (3DCA) in the Facilitation of Percutaneous Coronary Interventions. J Cardio Vasc Med 2013; 1: 1-5.

 

Related References from PharmaceuticalIntelligence.com:

Genomics & Genetics of Cardiovascular Disease Diagnoses: A Literature Survey of AHA’s Circulation Cardiovascular Genetics, 3/2010 – 3/2013
Curators: Aviva Lev-Ari, PhD, RN and Larry H. Bernstein, MD, FCAP
http://pharmaceuticalintelligence.com/2013/03/07/genomics-genet…cs-32010-32013/
http://wp.me/p2kEDv-2Jp

Prognostic Marker Importance of Troponin I in Acute Decompensated Heart Failure (ADHF)
Larry H Bernstein and  Aviva Lev-Ari
http://pharmaceuticalintelligence.com/2013/06/30/troponin-i-in-…-heart-failure
http://wp.me/p2kEDv-41S

A Changing expectation from cardiac biomarkers.
Larry H Bernstein
http://pharmaceuticalintelligence.com/2012/12/25/assessing-card…ith-biomarkers/
http://wp.me/p2kEDv-1DN

Dealing with the Use of the High Sensitivity Troponin (hs cTn) Assays
Larry H Bernstein and Aviva Lev-Ari
http://pharmaceuticalintelligence.com/2013/05/18/dealing-with-t…-hs-ctn-assays/
http://pharmaceuticalintelligence.com/wp-admin/post.php?post=13255
http://wp.me/p2kEDv-3rN

For Disruption of Calcium Homeostasis in Cardiomyocyte Cells, see

Part VI: Calcium Cycling (ATPase Pump) in Cardiac Gene Therapy: Inhalable Gene Therapy for Pulmonary Arterial Hypertension and Percutaneous Intra-coronary Artery Infusion for Heart Failure: Contributions by Roger J. Hajjar, MD

Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/08/01/calcium-molecule-in-cardiac-gene-therapy-inhalable-gene-therapy-for-pulmonary-arterial-hypertension-and-percutaneous-intra-coronary-artery-infusion-for-heart-failure-contributions-by-roger-j-hajjar/

Part VII: Cardiac Contractility & Myocardium Performance: Ventricular Arrhythmias and Non-ischemic Heart Failure – Therapeutic Implications for Cardiomyocyte Ryanopathy (Calcium Release-related Contractile Dysfunction) and Catecholamine Responses

Justin Pearlman, MD, PhD, FACC, Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/08/28/cardiac-contractility-myocardium-performance-ventricular-arrhythmias-and-non-ischemic-heart-failure-therapeutic-implications-for-cardiomyocyte-ryanopathy-calcium-release-related-contractile/

Part VIII: Disruption of Calcium Homeostasis: Cardiomyocytes and Vascular Smooth Muscle Cells: The Cardiac and Cardiovascular Calcium Signaling Mechanism

Justin Pearlman, MD, PhD, FACC, Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/2013/09/12/disruption-of-calcium-homeostasis-cardiomyocytes-and-vascular-smooth-muscle-cells-the-cardiac-and-cardiovascular-calcium-signaling-mechanism/

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Issues in Personalized Medicine: Discussions of Intratumor Heterogeneity from the Oncology Pharma forum on LinkedIn

Curator and Writer: Stephen J. Williams, Ph.D.

Article ID #77: Issues in Personalized Medicine: Discussions of Intratumor Heterogeneity from the Oncology Pharma forum on LinkedIn. Published on 9/4/2013

WordCloud Image Produced by Adam Tubman

In an earlier post entitled “Issues in Personalized Medicine in Cancer: Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing” the heterogenic nature of solid tumors was discussed.  There resulted an excellent discussion in the Oncology Pharma forum on LinkedIn so I curated the comments (below article) to foster further discussion. To summarize the original post, this was a discussion of Dr. Charles Swanton’s paper[1] in which he and colleagues had noticed that individual biopsies from primary renal tumors displayed a variety of mutations of the same and different tumor suppressor genes (TSG), thereby not only revealing the heterogeneity of individual tumors but also how tumors can evolve.  Thus it was suggested that individual cells of a primary tumor can represent individual clones, each evolving on a distinct pathway to tumorigenicity and metastasis as each clone would have accumulated different passenger mutations.  It is these passenger mutations which have been posited to be responsible for a tumor’s continued growth (as discussed in the following post Rewriting the Mathematics of Tumor Growth; Teams Use Math Models to Sort Drivers from Passengers).  Indeed, as Dr. Swanton mentioned in the posting that it is very likely a solid tumor contains discrete clones with different driver and passenger mutations and possibly different mutated TSG but also this intra-tumor heterogeneity would have great implications for personalized chemotherapeutic strategies, not only against the primary tumor but against resistant outgrowth clones, and to the metastatic disease, as Swanton and colleagues had found that the metastatic disease displayed tremendously increased genomic instability than the underlying primary disease.

Therefore it may behoove the clinical oncologist to view solid tumors as a collection of multiple clones, each having their own mutagenic spectrum and tumorigenic phenotype.  Each of these clones may acquire further mutations which provide growth advantage over other clones in the early primary tumor.  In addition, branched evolution of a clone most likely depends more on genomic instability and epigenetic factors than on solely somatic mutation.

This is echoed in a  report in Carcinogenesis back in 2005[3] Lorena Losi, Benedicte Baisse, Hanifa Bouzourene and Jean Benhatter had shown some similar results in colorectal cancer as their abstract described:

“In primary colorectal cancers (CRCs), intratumoral genetic heterogeneity was more often observed in early than in advanced stages, at 90 and 67%, respectively. All but one of the advanced CRCs were composed of one predominant clone and other minor clones, whereas no predominant clone has been identified in half of the early cancers. A reduction of the intratumoral genetic heterogeneity for point mutations and a relative stability of the heterogeneity for allelic losses indicate that, during the progression of CRC, clonal selection and chromosome instability continue, while an increase cannot be proven.”

Therefore if a tumor had evolved in time closer to the initial driver mutation multiple therapies may be warranted while tumors which had not yet evolved much from their driver mutation may be tackled with an agent directed against that driver, hence the branched evolution as shown in the following diagram:

branced chain evolution cancer

Cancer Sequencing

Unravels clonal evolution.

From Carlos Caldas. (2012).

Nature Biotechnology V.30

pp 405-410.[2] used with

permission.

 

 

 

 

 

 

 

An article written by Drs. Andrei Krivtsov and Scott Armstron entitled “Can One Cell Influence Cancer Heterogeneity”[4] commented on a study by Friedman-Morvinski[5] in Inder Verma’s laboratory discussed how genetic lesions can revert differentiated neorons and glial cells to an undifferentiated state [an important phenotype in development of glioblastoma multiforme].

In particular it is discussed that epigenetic state of the transformed cell may contribute to the heterogeneity of the resultant tumor.  Indeed many investigators (initially discovered and proposed by Dr. Beatrice Mintz of the Institute for Cancer Research, later to be named the Fox Chase Cancer Center) show the cellular microenvironment influences transformation and tumor development[6-8].

Briefly the Friedman-Morvinski study used intra-cerebral ventricular (ICV) injection of lentivirus to introduce oncogenes within the CNS and produced tumors of multiple cell origins including neuronal and glial cell origin (neuroblastoma and glioma).  The important takeaway was differentiated somatic cells which acquire genetic lesions can transform to form multiple tumor types.  As the authors state, “cellular differentiation and specialization are accompanied by gradual changes in epigenetic programs” and that “the cell of origin may influence the epigenetic state of the tumor”.   In essence this means that the success of therapy may depend on the cellular state (whether stem cell, progenitor cell, or differentiated specialized cell) at time of transformation.  In other words tumors arising from cells with an epigenetic state seen in stem cells would be more resistant to therapy unless given an epigenetic therapy, such as azacytididne, retinoic acid or HDAC inhibitors.

 

So as the Oncology Pharma forum on LinkedIn was such an excellent discussion I would like to post the comments for curation purposes and foster further discussion.  I would like to thank everyone’s great comments below.  I would especially like to thank Dr. Emanuel Petricoin from George Mason and Dr. David Anderson for supplying extra papers which will be the subject of a future post. I had curated each comment with inserted LIVE LINKS to make it easier to refer to a paper and/or company mentioned in the comment.

The comments seemed to center on three main themes:

  1. 1.      Clinicians pondering the benefit to mutational spectrum analysis to determine personalized therapy and develop biomarkers of early disease
  2. 2.      A shift in the clinicians paradigm of cancer development, diagnoses, and treatment from strictly histologic evaluation to a genetic and altered cellular pathway view
  3. 3.      Use of proteomics, microarray and epigenetics as an alternative to mutational analysis to determine aberrant cellular networks in various stages of tumor development

 

Victor Levenson • Thanks for posting this! To be honest, I am puzzled by the insistence on sequencing as a tool for tumor analysis – we know that expression patterns rather than mutations in a limited number of genes determine tumor physiology (or, even more, physiology of any tissue). Since the AACR-2012 we know that different tumors have similar or even identical mutations, so >functional< rather than >structural< differences are important. Frankly, I’d be much more excited learning about expression pattern heterogeneity in tumors.Granted that is much more challenging than NGS sequencing, but the value of the data would be incomparable, especially in its application to biomarker development.

Stephen J. Williams, Ph.D. • Dear Dr. Levenson, thanks for your comments. I agree with you and in no way am insisting on the releiance of sequencing mutations in cancer as the sole means for determining therapy. It is extremely true that tumors will show tremendous heterogeneity of mRNA expression. There are a number of studies (one which I will post on pharmaceuticalintelligence.com) that individual tumor cells will have differing expression patterns based on the levels of regional hypoxia within the tumor as well as other microenvironmental factors. I do have two posts on pharmaceuticalintelligence.com on this matter, curating various programs around the world which are using microarray expression analysis of tumors to determine personalized strategies. I believe the reliance on mutational analysis is based on the drugs that have been developed (such as Gleevec and crizotinib) which are based on mutant forms of BCR-Abl and ALK, respectively. However (as per two posts I did based on Mike Martin on our site “Mathematical Models of Driver and Passenger mutations) where he discusses how certain driver mutations will get the senescent cell over the hump to get to fully transformed and contribute to a certain level of growth while subsequent passengers are responsible for the sustained survival and expansion of the tumor.

Victor Levenson • Dr. Williams, thanks for the comments. Driving a senescent cell into proliferative stage is a tremendous change, which >may< begin with a mutation, but involves dramatic restructuring of transcription patterns that will drive the process. Hypoxia will definitely contribute to variations in the patterns, although will probably not be the main driver of the process. As to whether a mutation or a change in transcription pattern initiate the process, I am not sure we will ever be able to determine <grin>.

Vanisree Staniforth • Thanks for posting! Certainly a thought provoking article with regard to the future of personalized cancer therapies.

 

Dr. Raj Batra • If we follow Dr Levenson’s proposed conceptual approach (which we also published in 2009 and 2010), we are MUCH more likely to significantly impact tumor morbidity and mortality.

Stephen J. Williams, Ph.D. • Thanks Vanisiree and Dr. Batra for your comments. Hopefully we will see, from the future cancer statistics, how personlized therapy have improved outcomes for the solid tumors, like the hematologic cancers. 26 days ago

Emanuel Petricoin • The issue about intra and inter tumor heterogeneity is very important however since it is unknown which mutations are true drivers, an explanation of the results found in these studies simply could be the variances are all in the inconsequential mutations and the commonality is the driver mutations. Moreover, at the end of the day, its not the mRNA expression that we really care about but the functional protein signaling -phosphoprotein driven signaling architecture, that we care about since these are the drug targets directly.

Mohammad Azhar Aziz,PhD • This article addresses the potential complexity of dealing with cancer which is apparently increasing proportionally with the amount of data generated. Intratumor heterogeneity will remain there and even multiple biopsies that are randomly chosen will offer no conclusive solution.Mutations,expression profiles and functional protein signaling (as discussed above) alone can not provide any breakthrough. It will be a composite picture of all these and many other components (e.g. microenvironment, alternative splicing, epigenetics,non-coding RNAs etc.) that will hold the promises in the future. We have made phenomenal advances in understanding each of these aspects separately but definitely lack the tools to integrate all these. Developing tools to integrate all these data may provide some breakthrough in understanding and thus treating cancer.

Emanuel Petricoin • I agree Mohammad in a systems biology approach however the current compendium of drugs largely are kinase inhibitors or enzymatic inhibitors. Since most studies have shown little correlation between gene mutation and protein levels and phosphoprotein levels, for example, it is no wonder why the recent spate of failed trials (e.g. stratification by PIK3CA mutation or PTEN mutation for AKT-mTOR inhibitors) should come as any shock. We will be publishing work using protein pathway activation mapping coupled to laser dissection of a number of intra and inter tumoral analysis that indicates that the signaling architecture appears much more stable.

Stephen J. Williams, Ph.D. • Thank you Dr. Pettricoin for your comments. I eagerly await the publication of your results concerning proteomic evaluation of multiple biopsies of a tumor. I am very interested that you found limited intratuoral heterogeneity of signaling pathways given the diversity of intratumoral microenvironmental stresses (changes in regional hypoxia, blood flow, and populations of cancer stem cells). I agree with you and Mohammed that proteomic profiling will be imperative in determining personalized approaches for targeted therapy. Dr. Swanton had informed me that they had used IHC to determine if mTOR signaling had correlated with the mutational spectrum they had seen. In addition he had mentioned that there was enhanced genomic instability in the metastatic disease relative to the primary tumor and it would be very interesting to see how signaling pathways change in cohorts of matched metastatic and primary tumors. A few years ago we were looking at genes which were completely lost upon transformation of ovarian epithelial cells and worked up one of those genes (CRBP1) in cohorts of human ovarian cancer samples, using expression analysis in conjunction with laser capture microdissection and backed up by IHC analysis, and found that the expression pattern of CRBP1 was uniform in a tumor, either there was a complete loss in all cells in a tumor of CRBP1 or all the cells expressed the protein. Therefore I am curious if intratumor heterogeneity is dependent on the cell lineage and evolution of the transformed cell into a full tumor or a function of a discrete population of stem cells with varied genomic instability. Your results might suggest a more clonal evolution rather than a branched evolution which was found in this paper.
It is interesting that you mention the tough trials with the PTEN/PI3K/AKT axis of inhibitors. In high grade serous ovarian cancer we were never able to find any PI3K, PTEN, nor AKT mutations yet PI3K activity is usually overactive. If feel both your and Mohammed’s assessment that a systems biology approach instead of just relying on DNA mutational analysis will be more important in the future. In addition, there is nice work from Dr. Jefferey Peterson at Fox Chase and the development of a database of kinase inhibitors and activity effects on the kinome, showing the vast amount of crosstalk between once thought linear enzyme systems. If TKI’s will be the brunt of pharma’s development I feel they need to quickly develop as many TKI’s as they can now before we get to a clinical problem (resistance and lack of available therapeutics).

Emanuel Petricoin • Thanks Steven- yes, we are working with Charlie Swanton and Marco on the renal sets- our other studies are from breast and colon cancers. I think one of the things we do that really no one else is doing, unfortunately, is to laser capture microdissect the tumor cells from these specimens so that we have a more pure and accurate view of the signaling architecture. One confounder from the proteomic stand-point is the fact that pre-analytical variables such as post-excision delay times where the tissue is a hypoxic wound and signaling changes fluctuating as the tissue reacts to the ex-vivo condition can really effect things. When we look at tissue sets where the tissue is biopsied and immediately frozen we really dont see big differences in the signaling – the within tumor architecture is much more similar then between. We use the reverse phase array technology we invented to provide quantitative analysis on hundreds of phosphoproteins at once – so a nice view of the functional protein activation network. Your results of CRBP1 in ovarian tumors and the IHC data are very interesting. We will see how this all plays out. Of course once other confounder with the mutational data is that we really dont know what are the drivers and what are the passengers…
Yes I know Jeff Peterson’s work- its fantastic. In the end the hope I think- and in my personal opinion- will be rationally combined therapeutics based on the signaling architecture of each individual patient.

Incidentally, we just published a paper that you may be interested in from a “systems biology” standpoint-

SYSTEMS ANALYSIS OF THE NCI-60 CANCER CELL LINES BY ALIGNMENT OF PROTEIN PATHWAY ACTIVATION MODULES WITH “-OMIC” DATA FIELDS AND THERAPEUTIC RESPONSE SIGNATURES.

Federici G, Gao X, Slawek J, Arodz T, Shitaye A, Wulfkuhle JD, De Maria R, Liotta LA, Petricoin EF 3rd. Mol Cancer Res. 2013 May

also- we published a paper that speaks directly to your point where we compared the signaling network activation of patient-matched primary colorectal cancers and synchronous liver mets. indeed there is huge systemic differences in the liver metastasis compared to the primary. there is no doubt in my mind that we will need to biopsy the metastasis to know how to treat. Looking at the primary tumor as a guide for therapy is a fools errand. here is the paper reference:

Protein pathway activation mapping of colorectal metastatic progression reveals metastasis-specific network alterations.

Silvestri A, Calvert V, Belluco C, Lipsky M, De Maria R, Deng J, Colombatti A, De Marchi F, Nitti D, Mammano E, Liotta L, Petricoin E, Pierobon M.

Clin Exp Metastasis. 2013 Mar;30(3):309-16. doi: 10.1007/s10585-012-9538-5. Epub 2012 Sep 29.

Center for Applied Proteomics and Molecular Medicine, George Mason University, 10900 University Blvd., Manassas, VA, 20110, USA.

Abstract

The mechanism by which tissue microecology influences invasion and metastasis is largely unknown. Recent studies have indicated differences in the molecular architecture of the metastatic lesion compared to the primary tumor, however, systemic analysis of the alterations within the activated protein signaling network has not been described. Using laser capture microdissection, protein microarray technology, and a unique specimen collection of 34 matched primary colorectal cancers (CRC) and synchronous hepatic metastasis, the quantitative measurement of the total and activated/phosphorylated levels of 86 key signaling proteins was performed. Activation of the EGFR-PDGFR-cKIT network, in addition to PI3K/AKT pathway, was found uniquely activated in the hepatic metastatic lesions compared to the matched primary tumors. If validated in larger study sets, these findings may have potential clinical relevance since many of these activated signaling proteins are current targets for molecularly targeted therapeutics. Thus, these findings could lead to liver metastasis specific molecular therapies for CRC.

Adrian Anghel • I think both patterns (protein phosphorylation and mRNA) should be important in this complicated equation of heterogeneity. Let’s not forget the so-called functional miRNA-mRNA regulatory modules (FMRMs). Also I think we have different patterns of this heterogeneity for different evolutive stages of the tumour.

 

Alvin L. Beers, Jr., M.D. • This is a great study, but bad news for attempting to tailor treatment based on molecular markers. Dr. Swanton’s comment: “herterogeneity is likely to complicate matters” is an understatement. Intratumoral heterogeneity, branched, instead of linear, evolution of mutational events portends a nightmare in trying to predict location and volume of biopsies. I am reminded of a series of articles in Nature 491 (22 November 2012) “Physical Scientists take on Cancer”. There is a great comment by Jennie Dusheck: “Cancer researchers now recognize that taming wild cancer cells – populations of cells that evolve, cooperate, and roam freely through the body-demand a wider-angle view than molecular biology has been able to offer. Cross-disciplinary collaborations can approach cancer a greater spatial and temporal scales, using mathematical methods more typical of engineering, physics, ecology and evolutionary biology. The sense of failure so evident five years ago is giving way to the excitement of a productive intellectual partnership.” I’m not certain how well the “productive partnership” is going, but this Swanton study confirms the limitations of molecular biology.

Stephen J. Williams, Ph.D. • Thanks Dr. Beers for adding in your comment and adding in Jennie’s comment. Certainly it is something to be aware of if a cancer center’s strategy is to rely solely on gene arrays to genotype tumors. I think Dr. Pettricoin’s work on using proteomics might give some resolution to the matter however, in communicating with Dr. Swanton, I did not get the feeling of an “all hope is lost” but just that, in the case of solid tumors like renal, that careful monitoring of tumors after treatment may be warranted and, more interestingly, from a scientific standpoint, is the genetic complexity surrounding the origin of the disease, and not simple mutational spectrum of a single clone.

Burke Lillian • This is clinically a very important issue. Right now, sequencing or massive approaches such as pan-phosphorylation studies are helpful because, although we know many of the drivers, these studies are actually identifying new genes or new pathways that are activated. After a few (or several years), we truly will know which genes are typically activated and there will be panels to look for these.

Emanuel Petricoin • yes, I agree. In fact, the company that I co-founded, Theranostics Health, Inc– is launching a CLIA based protein pathway activation mapping test at ASCO that measures actionable drug targets (e.g. phospho HER2, EGFR, HER3, AKT, ERK, JAK, STAT, p70S6) and total HER2, EGFR, HER3 and PTEN. So these tests are coming even now.

 

Alvin L. Beers, Jr., M.D. • I do not think that “all hope is lost” nor did I have the impression that Dr. Swanton feels that way with regards to molecular profiling of cancer. I certainly applaud further research into the molecular aspects of cancer biology. But I do not believe that this will be sufficient. Integrating physicial sciences into cancer biology makes perfect sense toward better understanding of this complex disease.

Eleni Papadopoulos-Bergquist • I have enjoyed reading these comments and different ideas regarding genetic testing and profiling. As a nurse and researcher at heart, this is information that will make a huge impact on drug protocols, therefore allowing the best and most specific treatment to each individual rather than having a standard treatment protocol. Even with the scientific complexity of specifying genotypes of particular cancers, there is still the question of each individuals body responding to treatment. I’d love to have some dialogue regarding immune response.

Bradford Graves • I too have enjoyed reading this discussion. I am not a clinician but as a drug discovery researcher I have been struck by some parallels to the concept of virus fitness in virology – particularly as applied to HIV. Drug discovery cannot wait for the final answers to the many important questions being addressed in the discussion initiated by Dr. Williams. The best we can do is to pursue a broad range of therapeutics that will give the clinicians the armament they will need to either cure a given cancer or to at least turn it into a chronic as opposed to an acute disease. There has been a measure of success in the HIV field and it seems like it will be achievable for cancer. Obviously, to the extent that the labels of driver and passenger mutations can be correctly applied will help to prioritize the targets we address.

David W. Anderson • I would suggest that you look at the following publications:

Horn and Pao, (2009) JCO 26: 4232-4234.

Bunn and Doebele (2011) JCO:29:1-3

Boguski et al. (2009) Customized care 2020: how medical sequencing and network biology will enable personalized medicine. F1000 Bio Report 1:7.

Jones, S et al. (2010). Evolution of an adenocarcinoma in response to selection by targeted kinase inhibitors. Genome Biology. 11:R82. Marco Marra’s group in Toronto.

Also look at how companies and organizations like Foundation Medicine, Caris, Clarient, and CollabRx who are using genomics and sequencing on a large scale to address cancer from a personalized/individual approach.

Cancer is/will be a chronic disease requiring individualized/combinatorial therapies in many cases.

Alvin L. Beers, Jr., M.D. • David. These are excellent articles by Paul Bunn and Mark Boguski regarding integrating molecular markers into diagnostic evaluation, and I’ve seen other papers of similiar elk, and likely there will be more to come. Particularly in NSC lung cancer, the SOC is to use these markers up front. Diagnosis based on histology alone can no longer be recommended. The challenge for the future is how to integrate other aspects of cell biology with these markers. It remains daunting that not only do we see heterogeneity in molecular within tumors at a particularly point in time, but that there is often an evolution of markers over time, ie, a “plasticity” of markers, whether treatment is given or not. We know that targeted agents, TKI’s, enzyme inhibitors are not curative, but do give an improvement in PFS. A great deal of this resistance has to do with this “moving target” aspect of cancer cell biology..

 

References:

1.         Gerlinger M, Rowan AJ, Horswell S, Larkin J, Endesfelder D, Gronroos E, Martinez P, Matthews N, Stewart A, Tarpey P et al: Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. The New England journal of medicine 2012, 366(10):883-892.

2.         Caldas C: Cancer sequencing unravels clonal evolution. Nature biotechnology 2012, 30(5):408-410.

3.         Losi L, Baisse B, Bouzourene H, Benhattar J: Evolution of intratumoral genetic heterogeneity during colorectal cancer progression. Carcinogenesis 2005, 26(5):916-922.

4.         Krivtsov AV, Armstrong SA: Cancer. Can one cell influence cancer heterogeneity? Science 2012, 338(6110):1035-1036.

5.         Friedmann-Morvinski D, Bushong EA, Ke E, Soda Y, Marumoto T, Singer O, Ellisman MH, Verma IM: Dedifferentiation of neurons and astrocytes by oncogenes can induce gliomas in mice. Science 2012, 338(6110):1080-1084.

6.         Mintz B, Cronmiller C: Normal blood cells of anemic genotype in teratocarcinoma-derived mosaic mice. Proceedings of the National Academy of Sciences of the United States of America 1978, 75(12):6247-6251.

7.         Watanabe T, Dewey MJ, Mintz B: Teratocarcinoma cells as vehicles for introducing specific mutant mitochondrial genes into mice. Proceedings of the National Academy of Sciences of the United States of America 1978, 75(10):5113-5117.

8.         Mintz B, Cronmiller C, Custer RP: Somatic cell origin of teratocarcinomas. Proceedings of the National Academy of Sciences of the United States of America 1978, 75(6):2834-2838.

 

 

Other articles on this site on “PERSONALIZED MEDICINE” and “CANCER” and “OMICS” include:

Personalized medicine-based diagnostic test for NSCLC

Personalized medicine and Colon cancer

Helping Physicians identify Gene-Drug Interactions for Treatment Decisions: New ‘CLIPMERGE’ program – Personalized Medicine @ The Mount Sinai Medical Center

Systems Diagnostics – Real Personalized Medicine: David de Graaf, PhD, CEO, Selventa Inc.

Issues in Personalized Medicine in Cancer: Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

Personalized Medicine: Clinical Aspiration of Microarrays

Understanding the Role of Personalized Medicine

Directions for Genomics in Personalized Medicine

Paradigm Shift in Human Genomics – Predictive Biomarkers and Personalized Medicine – Part 1

Rewriting the Mathematics of Tumor Growth; Teams Use Math Models to Sort Drivers from Passengers

Diagnosing Diseases & Gene Therapy: Precision Genome Editing and Cost-effective microRNA Profiling

Breast Cancer: Genomic profiling to predict Survival: Combination of Histopathology and Gene Expression Analysis

Proteomics and Biomarker Discovery

 

 Also please see our upcoming e-book “Genomics Orientations for Individualized Medicine” in our Medical E-book Series at http://pharmaceuticalintelligence.com/biomed-e-books/genomics-orientations-for-personalized-medicine/volume-one-genomics-orientations-for-personalized-medicine/

 

 

 

 

 

 

 

 

 

 

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New scheme to routinely test patients for inherited cancer genes

Reporter, Curator: Stephen J. Williams, Ph.D.

KJ Monohan reports in The Family History of Bowel Cancer Clinic blog, a report from the Cancer Research UK about a new program being initiated by a team consisting of The Institute of Cancer Research, The Royal Marsden, Illumina Inc and the Wellcome Trust Centre for Human Genetics to screen ovarian and breast cancer patients for genes known to increase cancer risk.

The program Mainstreaming Cancer Genetics Programme will evaluate 97 known cancer predisposition genes in breast and ovarian cancer patients (using the TruSight Cancer Panel; see below for description and link).

A link to the full story can be found here:

New scheme to routinely test patients for inherited cancer genes.

The program will complement Cancer Research UK’s own stratified medicine program, which aims to identify driver mutations (mutations in genes {usually tumor suppressor genes} which drive (responsible for) the initiation and growth of a patient’s tumor. For descriptions of driver mutations of tumors please see some articles posted on this site such as:

Rewriting the Mathematics of Tumor Growth; Teams Use Math Models to Sort Drivers from Passengers

Winning Over Cancer Progression: New Oncology Drugs to Suppress Passengers Mutations vs. Driver Mutations

Writer’s commentary: As I had commented on this posting, 10% of breast and ovarian cancers are considered hereditary, meaning germline mutations exist in cancer risk genes (notably BRCA1/2 for breast /ovarian) and the offspring who inherit these mutant genes from carriers have a greatly enhanced risk to develop cancer in their lifetime. Although not in the scope of this post, I will curate, in a future post, research on the identity and relative risk for various gene mutations for breast/ovarian cancer risk.

TruSight Cancer Panel

A description of Illumina’s TruSight Cancer Panel is given below:

Targeting genes previously linked to a predisposition towards cancer.

  • Developed in collaboration with Professor Nazneen Rahman and team at the Institute of Cancer Research (ICR), London
  • Targets 94 known genes and 284 SNPs associated with a predisposition towards cancer

TruSight Cancer includes genes associated with both common (e.g., breast, colorectal) and rare cancers. In addition, the set includes 284 SNPs found to correlate with cancer through genome-wide association studies (GWAS). Content selection was based on expert curation of the scientific literature and other high-quality resources.

The TruSight Cancer sequencing panel provides custom oligos targeting identified regions of interest. Sufficient product is supplied for four enrichment reactions. TruSight Cancer is compatible with TruSight Rapid Capture and is supported on the MiSeq, NextSeq, and HiSeq sequencing systems.

The authors note that in the US and UK, genetic testing is performed at a genetics clinic, at the request of physicians and/or the individual. With the new program the patient’s cancer doctor can manage the genetic testing, giving the oncologist access to critical genetic information which can help in treatment options and family risk assessments.

Some cancer centers already have integrated a genetic counseling department among their services. These departments also act as Family Risk Assessment Programs. A few family risk assessment programs which deal with breast/ovarian cancer are given below:

Fox Chase Cancer Center Risk Assessment Program

The Mariann and Robert MacDonald Women’s Cancer Risk Evaluation Center at Penn Medicine

Massachusetts General Hospital Breast and Ovarian Cancer Genetics and Risk Assessment Program

Breast & Ovarian Risk Evaluation Program at University of Michigan

The Breast & Ovarian Cancer Prevention Program at Seattle Cancer Care Alliance

Dana-Farber Cancer Institute’s Center for Cancer Genetics and Prevention

Cancer Risk Program are offered through the UCSF Medical Center

These are only a few cancer centers in the US which provide comprehensive counseling and testing.

Other posts on this site about Cancer Risk and Genetic Testing include:

Testing for Multiple Genetic Mutations via NGS for Patients: Very Strong Family History of Breast & Ovarian Cancer, Diagnosed at Young Ages, & Negative on BRCA Test

(discussions on Angela Jolie’s experiences and issues through genetic testing and decision)

Host – Tumor Interactions during Cancer Therapy – Dr. Yuval Shaked’s Lab @Technion

(discussion by assistant professor on new paradigms in cancer treatment, detection)

Foundation Medicine reported 4,702 Clinical Tests in Q1, 715 were the FoundationOne Heme Cancer Test, average Reimbursement of $3,400 per Test

(report on success and use of Foundation Medicine’s cancer genetic testing kit)

Efficacy of Ovariectomy in Presence of BRCA1 vs BRCA2 and the Risk for Ovarian Cancer

Cancer Biomarkers for Companion Diagnostics

(Scientists from around the world gathered to share some of their newest biomarker research at the “Oncology Biomarkers Conference”)

Invitae been Sued for BRCA1/2 Patent Violation by Myriad Genetics

(legal problems may hinder the availability of BRCA1/2 testing)

Ethical Concerns in Personalized Medicine: BRCA1/2 Testing in Minors and Communication of Breast Cancer Risk

(discussion about issues mothers have informing their daughters about test results)

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Advances in Separations Technology for the “OMICs” and Clarification of Therapeutic Targets

Advances in Separations Technology for the “OMICs” and Clarification of Therapeutic Targets

Curator, Reporter, EAW:  Larry H Bernstein, MD, FCAP

 

This discussion is a continuation of an earlier piece on the technologic framework for , proteomics, nutrigenomics, and translational medicine. The last decade has seen the emergence of a genomic science that is changing the trajectory of biological sciences and medicine. It has not resolved all of our problems by any means, but it has begun to redraw the map, which began with the elucidation of major metabolic pathways in the first half of the 20th century, was then captured by the transformation of genetics with the discovery of the “Watson-Crick Model”, and then later was recharged with the discovery of the Toll-like receptor and the drawing of “signaling pathways”. What we have seen in an unraveling of protein-genome interactions, small peptide regulators, and dynamic changes in pathway dominance, bloackage, and reentry, depending on genetic, dietary, and environmental conditions, mostly expressed in what we refer to as “oxidative stress”.

Unraveling the multitude of nutrigenomic, proteomic, and metabolomic patterns that arise from the ingestion of foods or their bioactive food components will not be simple but is likely to provide insights into a tailored approach to diet and health. The use of new and innovative technologies, such as microarrays, RNA interference, and nanotechnologies, will provide needed insights into molecular targets for specific bioactive food components and how they harmonize to influence individual phenotypes. A challenging aspect of omic technologies is the refined analysis of quantitative dynamics in biological systems.

In recent years, nutrition research has moved from classical epidemiology and physiology to molecular biology and genetics. The new era of nutrition research translates empirical knowledge to evidence-based molecular science. Following this trend, Nutrigenomics has emerged as a novel and multidisciplinary research field in nutritional science that aims to elucidate how diet can influence human health. It is already well known that bioactive food compounds can interact with genes affecting transcription factors, protein expression and metabolite production. The study of these complex interactions requires the development of advanced analytical approaches combined with bioinformatics.
The Institute of Medicine recently convened a workshop to review the state of the various domains of nutritional genomics research and policy and to provide guidance for further development and translation of this knowledge into nutrition practice and policy. Nutritional genomics holds the promise to revolutionize both clinical and public health nutrition practice and facilitate the establishment of

  1.  genome-informed nutrient and food-based dietary guidelines for disease prevention and healthful aging,
  2.  individualized medical nutrition therapy for disease management, and
  3.  better targeted public health nutrition interventions (including micronutrient fortification and supplementation) that maximize benefit and minimize adverse outcomes within genetically diverse human populations.

For metabolomics, gas and liquid chromatography coupled to mass spectrometry are well suited for coping with high sample numbers in reliable measurement times with respect to both technical accuracy and the identification and quantitation of small-molecular-weight metabolites. This potential is a prerequisite for the analysis of dynamic systems. Thus, metabolomics is a key technology for systems biology.
The bioavailability of bioactive food constituents as well as dose-effect correlations are key information to understand the impact of food on defined health outcomes. Both strongly depend on appropriate analytical tools to identify and quantify minute amounts of individual compounds in highly complex matrices–food or biological fluids–and to monitor molecular changes in the body in a highly specific and sensitive manner. Based on these requirements, mass spectrometry has become the analytical method of choice with broad applications throughout all areas of nutrition research.

Dynamic Construct of the –Omics

Metabolomics is a term that encompasses several types of analyses, including

  1. metabolic fingerprinting, which measures a subset of the whole profile with little differentiation or quantitation of metabolites;
  2. metabolic profiling, the quantitative study of a group of metabolites, known or unknown, within or associated with a particular metabolic pathway; and
  3. target isotope-based analysis, which focuses on a particular segment of the metabolome by analyzing only a few selected metabolites that comprise a specific biochemical pathway.

Any unifying concept of the metabolome was incomplete or debatable in the first 30 years of the 20th century. It was only known that insulin is anabolic and that insulin deficiency (or resistance) would have consequences in the point of entry into the citric acid cycle, which generates 28-32 ATPs. In fat catabolism, triglycerides are hydrolyzed to break them into fatty acids and glycerol. In the liver the glycerol can be converted into glucose via dihydroxyacetone phosphate and glyceraldehyde-3-phosphate by way of gluconeogenesis. In the case of this cycle there is a tie in with both catabolism and anabolism.

See Aerobic glucose and acetate metabolism. (from dos Santos MM, et al. EUKARYOTIC CELL 2003; 2:599–608)

For bypass of the Pyruvate Kinase reaction of Glycolysis, cleavage of 2 ~P bonds is required. The free energy change associated with cleavage of one ~P bond of ATP is insufficient to drive synthesis of phosphoenolpyruvate (PEP), since PEP has a higher negative DG of phosphate hydrolysis than ATP.
The two enzymes that catalyze the reactions for bypass of the Pyruvate Kinase reaction are the following:

  • Pyruvate Carboxylase (Gluconeogenesis) catalyzes pyruvate + HCO3- + ATP — oxaloacetate + ADP + Pi
  • PEP Carboxykinase (Gluconeogenesis) catalyzes: oxaloacetate + GTP —- phosphoenolpyruvate + GDP + CO2

Many high throughput methods have been employed to get some insight into the whole process and several examples of successful research. Proteomics and metabolomics need to encompass large numbers of experiments and linked data. Due to the nature of the proteins, as well as due to the properties of various metabolites, experimental approaches require the use of comprehensive high throughput methods and a sufficiency of analysed tissue or body fluids.

Ovesná J, Slabý O, Toussaint O, Kodícek M, et al. High throughput ‘omics’ approaches to assess the effects of phytochemicals in human health studies. Br J Nutr. 2008;99 E Suppl 1:ES127-34.

An important and revolutionary aspect of  ‘The 2010 Project’ is that it implicitly endorses the allocation of resources to attempts to assign function to genes that have no known function. This represents a significant departure from the common practice of defining and justifying a scientific goal based on the biological phenomena. The rationale for endorsing this radical change is that for the first time it is feasible to envision a whole-systems approach to gene and protein function. I shall not discuss the emerging field of bioinformatics that makes this possible.
In this review, the end-of-the line “detector will be considered having been covered. The entire focus proceeds to a discussion of separation methods. Separation methods have always been tricky, time consuming, and a multiple step process that depended on using anionic and cationic resins as intermediate steps in bulk separation, and then molecular size separation.  Therapeutic Targets will be identified as they are seen.

Affinity Chromatography
The rapid development of biotechnology and biomedicine requires more reliable and efficient separation technologies for the isolation and purification of biopolymers such as therapeutic proteins, antibodies, enzymes and nucleic acids. In particular, monoclonal antibodies are centrally important as therapeutics for the treatment of cancer and other diseases, leading to recombinant monoclonal antibodies that dominate today’s biopharmaceutical pipeline. The large-scale production of therapeutic biopolymers requires

  • a manufacturing process that delivers reliability and in high-yield, as well as
  • an effective purification process affording extremely pure products.

Because of its high selectivity, affinity chromatography has been used extensively to isolate a variety of biopolymers. The retention of solutes is based on specific, reversible interactions found in biological systems, such as the binding of an enzyme with an inhibitor or an antibody with an antigen. These interactions are exploited in affinity chromatography by immobilizing an affinity ligand onto a support, and using this as a stationary phase.
Non-porous particles having an average diameter of 2.1 mm were prepared by co-polymerization of styrene, methyl methacrylate and glycidyl methacrylate, which was abbreviated as P(S–MMA–GMA). The particles were mechanically stable due to the presence of benzene rings in the backbone of polymer chains, and could withstand high pressures when a column packed with these particles was operated in the HPLC mode.

The polymer particles were advantaged by immobilization of ligands via the epoxy groups on the particle surface that were introduced by one of the monomers, glycidyl methacrylate. As a model system, Cibacron Blue 3G-A was covalently immobilized onto the non-porous copolymer beads. The dye-immobilized P(S–MMA–GMA) particles were slurry packed into a 1.0 cm30.46 cm I.D. column. This affinity column was effective for the separation of turkey egg white lysozyme from a protein mixture. The bound lysozyme could be eluted to yield a sharp peak by using a phosphate buffer containing 1 M NaCl. For a sample containing up to 8 mg of lysozyme, the retained portion of proteins could be completely eluted without any slit peak. Due to the use of a shorter column, the analysis time was shorter in comparison with other affinity systems reported in the literature. The retention time could be reduced significantly by increasing the flow-rate, while the capacity factor remained at the same level.
CH Chen, WC Lee. Affinity chromatography of proteins on non-porous copolymerized particles of styrene, methyl methacrylate and glycidyl methacrylate. Journal of Chromatography A 2001; 921: 31–37.

Affinity separation membranes, consisting of electrospun nanofibers, have been developed recently. Affinity ligands are attached to the surface of the constituent fibers, offering a potential solution to some of the problems of traditional, column-based, affinity chromatography. Electrospun fibers are good candidates for use in affinity separation because of their

  • unique characteristics of high surface area to volume ratio, resulting in
  • high ligand loading, and
  • their large porosity, resulting in
  • high throughput operation.

A number of polymers have been used for electrospun fiber mesh-based affinity membrane separations including poly (ether-urethane-urea), cellulose, poly(ethylene terephthalate, polysulphone, and polyacrlonitrile. Typically, very thin electrospun fiber meshes are produced by electrostatically collecting negatively charged fibers on a collector electrode. These very thin 2D electrospun fiber mesh mats provide excellent solution permeability as compared to 3D column packed with affinity beads.
M Miyauchi, J Miao, TJ Simmons, JS Dordick and RJ Linhardt. Flexible Electrospun Cellulose Fibers as an Affinity Packing Material for the Separation of Bovine Serum Albumin. J Chromatograph Separat Techniq 2011; 2:2 http://dx.doi.org/10.4172/2157-7064.1000110

Dye Affinity Chromatography
Biomimetic Dyes
Affinity adsorbents based on immobilized triazine dyes offer important advantages circumventing many of the problems associated with biological ligands. The main drawback of dyes is their moderate selectivity for proteins. Rational attempts to tackle this problem are realized through the biomimetic dye concept according to which new dyes, the biomimetic dyes, are designed to mimic natural ligands. Biomimetic dyes are expected to exhibit increased affinity and purifying ability for the targeted proteins.

Biocomputing offers a powerful approach to biomimetic ligand design. The successful exploitation of contemporary computational techniques in molecular design requires the knowledge of the three-dimensional structure of the target protein, or at least, the amino acid sequence of the target protein and the three-dimensional structure of a highly homologous protein. From such information one can then design, on a graphics workstation,

  • the model of the protein and also
  • a number of suitable synthetic ligands which mimic natural biological ligands of the protein.

There are several examples of enzyme purifications

  • trypsin
  • urokinase
  • kallikrein
  • alkaline phosphatase
  • malate dehydrogenase
  • formate dehydrogenase
  • oxaloacetate decarboxylase
  • lactate dehydrogenase

where synthetic biomimetic dyes have been used successfully as affinity chromatography tools.
YD Clonis, NE Labrou, VPh Kotsira, C Mazitsos, et al. Biomimetic dyes as affinity chromatography tools in enzyme purification. Journal of Chromatography A 2000; 891: 33–44.

Interactions between Cibacron Blue F3GA (CB F3GA), as a model of triazine dye, and 2-hydroxypropyl-b-cyclodextrin (HP-b-CD), as a model of cyclodextrin, were investigated by monitoring the spectral shift that accompanies the binding phenomena. Matrix analysis of the difference spectral titration of CB F3GA with HP-b-CD revealed only two absorbing species, indicating a host–guest ratio of 1:1. The dissociation constant for this HP-b-CD–CB F3GA complex, K , was found d to be 0.43 mM. The data for HP-b-CD forming inclusion complexes with CB F3GA were used to develop the concept of competitive elution by inclusion complexes in dye-affinity chromatography.
When this concept was applied to the elution of L-lactate dehydrogenase from a CB F3GA affinity matrix, it was shown to be an effective elution strategy. It provided a 15-fold purification factor with 89% recovery and sharp elution profile (0.8 column volumes for 80% recovery), which is as good as that obtained by specific elution with NADH (16-fold, 78% recovery and 1.8 column volumes). In addition, the new elution strategy showed a better purification factor and sharper elution profile than traditional non-specific.
JA Lopez-Mas, SA Streitenberger, F Garcıa-Carmona, AA Sanchez-Ferrer. Cyclodextrin biospecific-like displacement in dye-affinity chromatography. Journal of Chromatography A 2001; 911: 47–53.

Affinity chromatography uses biospecific binding usually between an antibody and an antigen, an enzyme and a substrate or other pairs of key-lock type of matching molecules. Due to its high selectivity, it is able to purify proteins and other macromolecules from very dilute solutions. In this work, a general rate model for affinity chromatography was used for scale-up studies. Parameters for the model were estimated from existing correlations, or from experimental results obtained on a small column with the same packing material. As anexample, Affi-Gel with 4.5mol cm−3 Cibacron Blue F-3GA as immobilized ligands covalently attached to cross-linked 6% agarose was used for column packing. Cibacron Blue F-3GA was also used as a soluble ligand in the elution stage. Satisfactory scale-up predictions were obtained for a 98.2 ml column and a 501 ml column based on a few experimental data obtained on a 7.85 ml small column.
T. Gu, K.-H. Hsu and M.-J. Syu, “Scale-Up of Affinity Chromatography for Purification of Enzymes and Other Proteins.” Enzyme and Microbial Technology 2003; 33:433-437.

Affinity Column with AAAA as a Model Sense Ligand
The degeneracy of antisense peptides was studied by high-performance affinity chromatography. A model sense peptide (AAAA) and its antisense peptides (CGGG, GGGG, RGGG, SGGG) were designed and synthesized according to the degeneracy of genetic codes. An affinity column with AAAA as the ligand was prepared. The affinity chromatographic behaviors of antisense peptides on the column were evaluated. The results indicated that model antisense peptides have clear retention on the immobilized AAAA affinity column. RGGG showed the strongest affinity interaction.
R Zhao, X Yu, H Liu, L Zhai, S Xiong, et al. Study on the degeneracy of antisense peptides using affinity chromatography. Journal of Chromatography A 2001; 913: 421–428.

Frontal AC for Biomolecular Interactions
Frontal affinity chromatography is a method for quantitative analysis of biomolecular interactions. We reinforced it by incorporating various merits of a contemporary liquid chromatography system. As a model study, the interaction between an immobilized Caenorhabditis elegans galectin (LEC-6) and fluorescently labeled oligosaccharides (pyridylaminated sugars) was analyzed. LEC-6 was coupled to N-hydroxysuccinimide-activated Sepharose 4 Fast Flow (100 mm diameter), and packed into a miniature column (e.g., 1034.0 mm, 0.126 ml). The volume of the elution front (V) determined graphically for each sample was compared with that obtained in the presence of an excess amount of hapten saccharide, lactose (V ); and the dissociation constant, K , was calculated according to the literature. This system also proved to be useful for an inverse confirmation; that is, application of galectins to an immobilized glycan column (in the present case, asialofetuin was immobilized on Sepharose 4 Fast Flow), and the elution profiles were monitored by fluorescence based on tryptophan. The newly constructed system proved to be extremely versatile. It enabled rapid (analysis time 12 min/ cycle) and sensitive (20 nM for pyridylaminated derivatives, and 1 mg/ml for protein) analyses of lectin–carbohydrate interactions.
J Hirabayashi, Y Arata, K Kasai. Reinforcement of frontal affinity chromatography for effective analysis of lectin–oligosaccharide interactions. Journal of Chromatography A 2000; 890:261–271.

Immobilized Metal Ion Affinity
New immobilized metal ion affinity chromatography (IMAC) matrices containing a high concentration of metal–chelate moieties and completely coated with inert flexible and hydrophilic dextrans are here proposed to improve the purification of polyhistidine (poly-His) tagged proteins. The purification of an interesting recombinant multimeric enzyme (a thermoresistant b-galactosidase from Thermus sp. strain T2) has been used to check the performance of these new chromatographic media.

IMAC supports with a high concentration (and surface density) of metal chelate groups promote a rapid adsorption of poly-His tagged proteins during IMAC. However, these supports also favor the promotion of undesirable multi-punctual adsorptions and problems may arise for the simple and effective purification of poly-His tagged proteins. For example, desorption of the pure enzyme from the support may become quite difficult (e.g., it is not fully desorbed from the support even using 200 mM of imidazole).

The coating of these IMAC supports with dextrans greatly reduces these undesired multi-point adsorptions. However, this dextran coating of chromatographic matrices seems to allow the formation of strong one-point adsorptions that involve small areas of the protein and support surface, but the dextran coating seems to have dramatic effects for the prevention of weak or strong multipoint interactions that should involve a high geometrical congruence between the enzyme and the support surface.
C Mateo , G Fernandez-Lorente , BCC Pessela , A Vian, et al. Affinity chromatography of polyhistidine tagged enzymes. New dextran-coated immobilized metal ion affinity chromatography matrices for prevention of undesired multipoint adsorptions. Journal of Chromatography A 2001; 915:97–106.
The underlying principle of immobilized metal ion affinity chromatography (IMAC) of proteins is the coordination between the electron donor groupings on a protein surface (histidine, tryptophan, cysteine) and chelated (iminodiacetate; IDA) transition metal ions [IDA-M(II)].  This principle of immobilized metal ion affinity (IMA) has been presented by now in some detail. The practice of IMAC in the purification of proteins has had its empirical phase. There is now a need, from the body of data, to establish somewhat more detailed ground rules that would allow for the use of IMAC in a more predictive manner.
Immobilized metal ion affinity chromatography (IMAC) has been explored as a probe into the topography of histidyl residues of a protein molecule. An evaluation of the chromatographic behavior of selected model proteins-

  • thioredoxin
  • ubiquitin
  • calmodulin
  • lysozyme
  • cytochrome c
  • myoglobin

on immobilized transition metal ions

  • Co2+
  • Ni2+
  • Cu2+
  • Zn2

-allows establishment of the following facets of the histidyl side chain distribution:

  1. either interior or surface;
  2. when localized on the surface, accessible or unaccessible for coordination;
  3. single or multiple;
  4. When multiple, either distant or vicinal.

Moreover, proteins displaying single histidyl side chains on their surfaces may, in some instances, be resolved by IMAC; apparently, the microenvironments of histidyl residues are sufficiently diverse to result in different affinities for the immobilized metal ions. IMAC, previously introduced as an approach to the fractionation of proteins, has become also, upon closer examination, a facile probe into the topography of histidyl residues.
This is possible because of the inherent versatility of IMAC; an appropriate metal ion (M2+) can be selected to suit the analytical purpose and a particular chromatographic protocol can be applied (isocratic pH, falling pH, and imidazole elution). We now report that IMAC may be exploited as an analytical tool in addition to its use as a protein purification technique. IMAC can be used to ascertain several facets of the status of a histidyl residue(s) in a protein molecule:

  1. localization (interior vs. surface)
  2. coordination potential as defined by the steric accessibility and the state of protonation
  3. single vs. multiple
  4. surface density.

ES Hemdan, YJ Zhao, E Sulkowski, J Porath. Surface topography of histidine residues: A facile probe by immobilized metal ion affinity chromatography. Proc. Natl. Acad. Sci. USA 1989; 86: 1811-1815. Biochemistry.

A novel, two-step preparative technique is described for the purification of authentic recombinant human prolactin (rhPRL) secreted into the periplasm of transformed Escherichia coli cells. The first step is based on immobilized metal ion affinity chromatography of periplasmic extract, using Ni(II) as a relatively specific ligand for hPRL in this system. It gives superior resolution and yield than established ion-exchange chromatography. Size-exclusion chromatography is used for further purification to .99.5% purity. The methodology is reproducible, leading to 77% recovery. Identity and purity of the rhPRL were demonstrated using sodium dodecylsulphate–polyacrylamide electrophoresis, isoelectric focusing, mass spectrometry (matrix-assisted laser desorption ionization time-of-flight), radioimmunoassay, RP-HPLC and high-performance size-exclusion chromatography. In the Nb2 bioassay, the hormone showed a bioactivity of 40.9 IU/mg.

EKM Ueda, PW Gout, L Morgantia. Ni(II)-based immobilized metal ion affinity chromatography of recombinant human prolactin from periplasmic Escherichia coli extracts. Journal of Chromatography A 2001; 922:165–175.

Adenosine Affinity Ligand for Glutamine Synthase
Glutamine synthetase has been purified from both procaryotic and eucaryotic sources using various types of affinity chromatography. For example, ADP-agarose has been used to purify glutamine synthetase from photosynthetic bacteria, while the related “Blue” chromatography media (e.g. Affigel Blue) have been used to purify glutamine synthetases from a variety of sources. In addition, 2’,5’-ADPSepharose 4B has been used to purify glutamine synthetase from procaryotes, plants and insects. However, this latter affinity ligand resembles NADP more than ADP, particularly with respect to the position of the phosphate moieties. This is reflected in the more general use of this affinity ligand in the purification of NADPH-dependent enzymes.
In the present report, we characterize the ability of glutamine synthetase to be purified by three different adenosine-affinity ligands: 5’-ADP-agarose (an ADP analogue), 2’,5’-ADP-Sepharose 4B (an NADP analogue) and 3’,5’-ADP-agarose (a cyclic AMP analogue). We report conditions for the successful purification of insect flight muscle glutamine synthetase using each of these three different affinity ligands.
The enzyme bound most strongly to the

  1. ADP analogue (S-ADP-agarose),
  2. followed by the NADPH analogue (2’,5’-ADP-Sepharose 4B), and least strongly to
  3. the cyclic AMP analogue (3’J’-ADP-agarose).

In all cases, binding was strongest in the presence of Mn2+ when compared to Mg”. These results suggest that the binding of glutamine synthetase to adenosine-affinity media is related to the participation of Mn. ADP in the y-glutamyl transferase reaction that is catalyzed by glutamine synthetase.
M Dowton, IR Kennedy. Purification of glutamine synthetase by adenosine-affinity chromatography. Journal of Chromatography A 1994; 664: 280-283

Aptamer Based Stationary Phase
An anti-adenosine aptamer was evaluated as a stationary phase in packed capillary liquid chromatography. Using an 21 aqueous mobile phase containing 20 mM Mg , adenosine was strongly retained on the column.  A gradient of increasing 21 Ni (to 18 mM), which is presumed to complex with nitrogen atoms in adenosine involved in binding to the aptamer, eluted adenosine in a narrow zone. The adenosine assay, which required no sample preparation, was used on microdialysis samples. Total analysis times were short so samples could be injected every 5 min.
Q Deng, CJ Watson, RT Kennedy. Aptamer affinity chromatography for rapid assay of adenosine in microdialysis samples collected in vivo. Journal of Chromatography A 2003; 1005:123–130.

We will realize the full power of proteomics only when we can measure and compare the proteomes of many individuals to identify biomarkers of human health and disease and track the blood-based proteome of an individual over time. Because the human proteome contains an estimated 20,000 proteins – plus splicing and post-translational variants – that span a concentration range of ,12 logs, identifying and quantifying valid biomarkers is a great technical challenge.
Proteomic measurements demand

  • extreme sensitivity
  • specificity
  • dynamic range
  • accurate quantification.

We describe a new class of DNA-based aptamers enabled by a versatile chemistry technology that endows nucleotides with protein-like functional groups. These modifications greatly expand the repertoire of targets accessible to aptamers.
The resulting technology provides efficient, large-scale selection of exquisite protein-binding reagents selected specifically for use in highly multiplexed proteomics arrays.
Aptamers are a class of nucleic acid-based molecules discovered twenty years ago, and have since been employed in diverse applications including

  • therapeutics
  • catalysis
  • proteomics

Aptamers are short single-stranded oligonucleotides, which fold into diverse and intricate molecular structures that bind with high affinity and specificity to

  • proteins
  • peptides
  • small molecules.

Aptamers are selected in vitro from enormously large libraries of randomized sequences by the process of Systematic Evolution of Ligands by EXponential enrichment (SELEX). A SELEX library with 40 random sequence positions has 440 (,1024) possible combinations and a typical selection screens 1014–1015 unique molecules. This is on the order of 105 times larger than standard peptide or protein combinatorial molecular libraries.

The interrogation of proteomes (‘‘proteomics’’) in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 mL of serum or plasma).

Our current assay measures 813 proteins with low limits of detection (1 pM median), 7 logs of overall dynamic range (,100 fM–1 mM), and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray.

Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and
unique nucleotide sequences recognizable by specific hybridization probes.

This is a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine.
L Gold, D Ayers, J Bertino, Christopher Bock, et al. Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery. PlosONE 2010; 5 (12): e15004

Biomarker Discovery, Diagnostics, and Therapeutics
Progression from health to disease is accompanied by complex changes in protein expression in both the circulation and affected tissues. Large-scale comparative interrogation of the human proteome can offer insights into disease biology as well as lead to

  • the discovery of new biomarkers for diagnostics
  • new targets for therapeutics
  • can identify patients most likely to benefit from treatment.

Although genomic studies provide an increasingly sharper understanding of basic biological and pathobiological processes, they ultimately only offer a prediction of relative disease risk, whereas proteins offer an immediate assessment of “real-time” health and disease status.
We have recently developed a new proteomic technology, based on modified aptamers, for biomarker discovery that is capable of simultaneously measuring more than a thousand proteins from small volumes of biological samples such as plasma, tissues, or cells. Our technology is enabled by SOMAmers (Slow Off-rate Modified Aptamers), a new class of protein binding reagents that contain chemically modified nucleotides that greatly expand the physicochemical diversity of nucleic acid-based ligands. Such modifications introduce functional groups that are absent in natural nucleic acids but are often found in protein-protein, small molecule-protein, and antibody-antigen interactions. The use of these modifications expands the range of possible targets for SELEX (Systematic Evolution of Ligands by EXponential Enrichment), results in improved binding properties, and facilitates selection of SOMAmers with slow dissociation rates. Our assay works by transforming protein concentrations in a mixture into a corresponding DNA signature, which is then quantified on current commercial DNA microarray platforms. In essence, we take advantage of the dual nature of SOMAmers as

  • both folded binding entities with defined shapes and
  • unique nucleic acid sequences recognizable by specific hybridization probes.

Mehan MR, Ostroff R, Wilcox SK, Steele F, et al. Highly multiplexed proteomic platform for biomarker discovery, diagnostics, and therapeutics. Adv Exp Med Biol. 2013; 734:283-300.

Aptamers and Smart Drug delivery Targeting
In this review, the strategies for using functional nucleic acids in creating smart drug delivery devices will be explained, as their has been very recent progress in controlled drug release based on molecular gating achieved with aptamers. Aptamers are functional nucleic acid sequences which can bind specific targets.
An artificial combinatorial methodology can identify aptamer sequences for any target molecule, from ions to whole cells. Drug delivery systems seek to increase efficacy and reduce side-effects by concentrating the therapeutic agents at specific disease sites in the body. This is generally achieved by specific targeting of inactivated drug molecules.
Aptamers which can bind to various cancer cell types selectively and with high affinity have been exploited in a variety of drug delivery systems for therapeutic purposes. Recent progress in selection of cell-specific aptamers has provided new opportunities in targeted drug delivery. Especially functionalization of nanoparticles with such aptamers has drawn major attention in the biosensor and biomedical areas.

Nucleic acids are recognized as attractive building materials in nanomachines because of their unique molecular recognition properties and structural features. An active controlled delivery of drugs once targeted to a disease site is a major research challenge. Stimuli-responsive gating is one way of achieving controlled release of nanoparticle cargoes. Recent reports incorporate the structural properties of aptamers in controlled release systems of drug delivering nanoparticles.

Nanoparticle-encapsulated drug delivery aims to deliver the active therapeutic ingredients to the disease site in stable compartments in order to reduce premature release. This ensures that the effects of drug are maximized and the side effects are reduced. An encapsulated nanoparticle system requires a specific targeting mechanism and at the same time the retention of drugs inside the container should be high. The balance between specificity of targeting and the extent of premature leakage determines the success of a given delivery system.

Nanotechnology research approaches in drug delivery include a wide variety of nanomaterials ranging from soft hydrogels to solid polymeric particles. Large surface area, high drug loading efficiency and potential combination with other organic/inorganic materials are the main properties of hollow nanostructures that are attractive for biomedical applications.

Packaging of small-molecule drugs

  • improves their availability
  • compatibility
  • reduces toxicity

Controlling the drug release profile is the main challenge in drug delivery development when the drug is to be successfully targeted to a specific site. Stimuli-responsive materials have been created by using biological, physical and chemical properties of materials for heat-activated, light-activated or pH-activated delivery. Nucleic acids are utilized to construct rationally designed nanostructures at molecular levels for nanotechnology applications. Integration of the properties of nucleic acids can offer many opportunities for drug delivery systems, including stimuli-responsive nanogates for nanocarriers and molecular sensors. Favorable drug release kinetics can be achieved at the target sites by aptamer-based capping systems.

VC Ozalp, F Eyidogan and HA Oktem. Aptamer-Gated Nanoparticles for Smart Drug Delivery.
Pharmaceuticals 2011, 4, 1137-1157; doi:10.3390/ph4081137. ISSN 1424-8247. http://www.mdpi.com/journal/pharmaceuticals

Activity Based Profiling
Powerful strategies for the gel-free analysis of proteomes have emerged, including isotope-coded affinity tagging (ICAT) for quantitative proteomics and multidimensional protein identification technology (MudPIT) for comprehensive proteomics, both of which utilize liquid chromatography (LC) and MS for protein separation and detection, respectively.
Nonetheless, these methods, like 2DE-MS, still focus on measuring changes in protein abundance and, therefore, provide only an indirect estimate of dynamics in protein function. Indeed, several important forms of post-translational regulation, including protein–protein and protein–small-molecule interactions, may elude detection by abundance-based proteomic methods.
To facilitate the analysis of protein function, several proteomic methods have been introduced to characterize the activity of proteins on a global scale. These include large-scale yeast two-hybrid screens and epitope tagging immunoprecipitation experiments, which aim to construct comprehensive maps of protein–protein interactions, and protein microarrays, which aim to provide an assay platform for the rapid assessment of protein activities. A chemical proteomic strategy referred to as activity-based protein profiling (ABPP) has emerged that utilizes active site-directed probes to profile the functional state of enzyme families directly in complex proteomes.

Recent advances in genomic and proteomic technologies have begun to address the challenge of assigning molecular and cellular functions to the numerous protein products encoded by prokaryotic and eukaryotic genomes. In particular, chemical strategies for proteome analysis have emerged that enable profiling of protein activity on a global scale. Herein, we highlight these chemical proteomic methods and their application to the discovery and characterization of disease-related enzyme activities.

N Jessani and BF Cravatt. The development and application of methods for activity-based protein profiling. Current Opinion in Chemical Biology 2004; 8:54–59. In Proteomics and genomics, M Snyder and J Yates III, eds. 2003 Elsevier Ltd. DOI: 10.1016/ j.cbpa.2003.11.004

Cells with fundamental metabolic alterations commonly arise during tumorigenesis, and it is these types of changes that help to establish a biochemical foundation for disease progression and malignancy. A seminal example of this was discovered in the 1920s when Otto Warburg found that cancer cells consume higher levels of glucose and secrete most of the glucose carbon as lactate rather than oxidizing it completely.
Since then, studies by multiple groups have uncovered a diverse array of metabolic changes in cancer, including
alterations in

  1. glycolytic pathways
  2. the citric acid cycle
  3. glutaminolysis
  4. lipogenesis
  5. lipolysis
  6. proteolysis

These in turn modulate the levels of cellular building blocks

  1. lipids, nucleic acids and amino acids,
  2. cellular energetics,
  3. oncogenic signaling molecules
  4. the extracellular environment to confer protumorigenic and malignant properties.

Despite these advances, our current understanding of cancer metabolism is far from complete and would probably benefit from experimental strategies that are capable of profiling enzymatic pathways on a global scale. To this end, conventional genomic and proteomic methods, which comparatively quantify the expression levels of transcripts and proteins, respectively, have yielded many useful insights. These platforms are, however, limited in their capacity to identify changes in protein activity that are caused by posttranslational mechanisms.

Annotating biochemical pathways in cancer is further complicated by the potential for enzymes to carry out distinct metabolic activities in tumor cells that might not be mirrored in normal physiology. In addition, a substantial proportion of the human proteome remains functionally uncharacterized, and it is likely that at least some of these poorly understood proteins also have roles in tumorigenesis. These challenges require new proteomic technologies that can accelerate the assignment of protein function in complex biological systems, such as cancer cells and tumors.

Metabolomics has emerged as a powerful approach for investigating enzyme function in living systems. Metabolomic experiments in the context of enzyme studies typically start with

  1. the extraction of metabolites from control and enzyme-disrupted biological systems,
  2. followed by metabolite detection and comparative data analysis.

For example, lipophilic metabolites can be enriched from cells or tissues by organic extraction.
Mass spectrometry (MS) has become a primary analytical method for surveying metabolites in complex biological samples, with upfront separation accomplished by liquid chromatography (LC–MS) or gas chromatography (GC–MS). MS experiments can be carried out using

  • targeted or untargeted approaches,
  • depending on whether the objective is
  • to profile and quantitate known metabolites or
  • to broadly scan for metabolites across a large mass range, respectively.

As metabolomic experiments generate a large amount of data, powerful software tools are needed for identification and quantitation of ions in LC–MS data sets (see the figure; the mass to charge ratio (m/z) is indicated). One such program is XCMS95, which

  • aligns,
  • quantifies and
  • statistically ranks ions that are altered between two sets of metabolomic data.

This program can be used to rapidly identify metabolomic signatures of various disease states or to assess metabolic networks that are regulated by an enzyme using pharmacological or genetic tools that modulate enzyme function. Additional databases assist in metabolite structural characterization, such as HMDB96,97, METLIN98,99 and LIPID MAPS100.
In this Review, we discuss one such proteomic platform, termed activity based protein profiling (ABPP), and its implementation in the discovery and functional characterization of deregulated enzymatic pathways in cancer. We discuss the evidence that, when coupled with other large scale profiling methods, such as metabolomics and proteomics, ABPP can provide a compelling, systems level understanding of biochemical networks that are important for the development and progression of cancer.

Large-scale profiling methods have uncovered numerous gene and protein expression changes that correlate with tumorigenesis. However, determining the relevance of these expression changes and which biochemical pathways they affect has been hindered by our incomplete understanding of the proteome and its myriad functions and modes of regulation. Activity-based profiling platforms enable both the discovery of cancer-relevant enzymes and selective pharmacological probes to perturb and characterize these proteins in tumour cells. When integrated with other large-scale profiling methods, activity-based proteomics can provide insight into the metabolic and signaling pathways that support cancer pathogenesis and illuminate new strategies for disease diagnosis and treatment.

Representative activity-based probes and their application to cancer research

  • enzyme class applications in cancer
  • Serine hydrolases increased KIAA1363 and MAGL
  • aggressive human cancer lines
  • uPA and tPA serine protease aggressive cancers
  • RBBP9 activity in pancreatic carcinoma
  • Metalloproteinases neprilysin activity in melanoma cell lines
  • Cysteine proteases cathepsin cysteine protease in pancreatic islet tumours
  • Kinases Inhibitor selectivity profiling of kinase inhibitors
  • Caspases visualization of apoptosis in colon tumour-bearing mice treated with Apomab
  • Deubiquitylases Identified increased carboxy-terminal hydrolase UCHL3 and UCH37 activity in HPV cervical carcinomas
  • Cytochrome P450s Identified the aromatase inhibitor anastrazole as an inducer of CYP1A2

Serine hydrolases KIaa1363 and MaGL regulate lipid metabolic pathways that support cancer pathogenesis. Activity-based protein profiling (ABPP) identified

  • KIAA1363 and
  • monoacylglycerol (MAG) lipase (MAGL)

as being increased in aggressive human cancer cells from multiple tumour types. Pharmacological and/or RNA interference ablation of KIAA1363 and MAGL coupled with metabolomic analysis revealed specific roles for KIAA1363 and MAGL in cancer metabolism. Disruption of KIAA1363 by the small-molecule inhibitor AS115 lowered monoalkylglycerol ether (MAGE), alkyl lysophosphatidic acid (alkyl LPA) and alkyl lysophosphatidyl choline (alkyl LPC) levels in cancer cells. Disruption of MAGL by the small-molecule inhibitor JZL184 raised MAG levels and reduced free fatty acid, lysophosphatidic acid (LPA) and prostaglandin E2 (PGE2) levels in cancer cells. Disruption of KIAA1363 and MAGL leads to impairments in cancer cell aggressiveness and tumour growth, PAF, platelet-activating factor.

At a glance

• Activity-based protein profiling (ABPP) facilitates the discovery of deregulated enzymes in cancer.
• Competitive ABPP yields selective inhibitors for functional characterization of cancer enzymes.
• ABPP can be integrated with metabolomics to map deregulated enzymatic pathways in cancer.
• ABPP can be integrated with other proteomic methods to map proteolytic pathways in cancer.
• ABPP probes can be used to image tumour development in living animals.

DK Nomura, MM Dix and BF Cravatt. Activity-based protein profiling for biochemical pathway discovery in cancer. Nature Reviews. Cancer. 2010; 10: 630-638.

New methods are thus needed to accelerate the assignment of biochemical, cellular and physiological functions to these poorly annotated genes and proteins. Here we propose that the emerging chemical proteomic technology, ABPP, is distinctly suited to address this problem.

Activity-based protein profiling (ABPP), the use of active site-directed chemical probes to monitor enzyme function in complex biological systems, is emerging as a powerful post-genomic technology. ABPP probes have been developed for several enzyme classes and have been used to inventory enzyme activities en masse for a range of (patho)physiological processes.

ABPP uses active site–directed, small molecule–based covalent probes to report on the functional state of enzyme activities directly in native biological systems. ABPP probes are designed or selected to target a subset of the proteome based on shared principles of binding and/or reactivity and have been successfully developed for many enzyme classes, including

  • serine
  • cysteine,
  • aspartyl
  • metallo hydrolases
  • kinases
  • glycosidases
  • histone deacetylases and
  • oxidoreductases.

These probes have been shown to selectively label active enzymes but not their inactive precursor (zymogen) or inhibitor-bound forms, thus allowing researchers to capture functional information that is beyond the scope of standard proteomic methods.
By presenting specific examples, we show here that ABPP provides researchers with a distinctive set of chemical tools to embark on the assignment of functions to many of the uncharacterized enzymes that populate eukaryotic and prokaryotic proteomes.

Reactive group                                                 Enzyme                                                       Enzyme class

Benzophenone                                                  Presenilins                            Aspartyl protease (γ-secretase )

Bromoethyl                                           HSPC263 (OTU domain)              Deubiquitinating enzyme (DUB)

Vinyl-methylester                             UL from HSV-1                                 Deubiquitinating enzyme (DUB)

Aryl 2-deoxy-2-fluoro                    glycoside Cfx from C. fimi            Glycosidase (β-1-4-glycanase)
Fluorophosphonate                                    SAE                                             Serine hydrolase

Examples of enzymes assigned to specific mechanistic classes by ABPP

ABPP can also be implemented as a direct assay for inhibitor discovery, allowing researchers to develop potent and selective pharmacological probes for uncharacterized enzymes.

Examples of enzymes assigned to specific mechanistic classes by ABPP.

  • Probe Leu-Asp-αCA probe selectively labeled Upβ
  • Substrate the endogenous Upβ substrate, N-carbamoyl-β-alanine
  • Substrate mimicry of an ABPP probe.

Multidimensional profiling strategy for the annotation of the cancer-related enzyme KIAA1363. ABPP using fluorophosphonate probes identified KIAA1363 as a highly elevated enzyme activity in aggressive cancer cells. Competitive ABPP was then used to develop a selective KIAA1363 inhibitor (AS115). Metabolomic analysis of cancer cells treated with AS115 determined a role for this enzyme in the regulation of MAGE lipids in cancer cells. Biochemical studies confirmed that KIAA1363 acts as 2-acetyl MAGE hydrolase in a metabolic network that bridges the platelet activating factor and lysophosphatidic acid classes of signaling lipids.
Assignment of enzyme mechanism by ABPP

There are multiple levels of annotation for enzymes. The most basic level is assignment to a specific mechanistic class based on the general chemical reaction catalyzed by the enzyme (for example, hydrolase, kinase, oxidoreductase and others). Additional annotation involves determining the endogenous substrates and products for the enzyme. Finally, complete annotation requires an understanding of how the specific chemical transformation(s) catalyzed by an enzyme integrate into larger metabolic and signaling pathways to influence cell physiology and behavior.

Many of the predicted enzymes uncovered by genome sequencing projects can be assigned to a mechanistic class or ascribed a putative biochemical function based on sequence homology to well-characterized enzymes. But some enzymes have insufficient sequence relatedness for class assignment or have a function different from that predicted by sequence comparisons. ABPP has facilitated class annotation for several such uncharacterized enzymes.

KT Barglow & BF Cravatt. Activity-based protein profiling for the functional annotation of enzymes. Nature Methods 2007; 4(10): 822- 827. DOI:10.1038/NMETH1092

A principal goal of modern biomedical research is to discover, assemble, and experimentally manipulate molecular pathways in cells and organisms to reveal new disease mechanisms.

Toward this end, complete genome sequences for numerous bacteria and higher organisms, including humans, have laid the fundamental groundwork for understanding the molecular basis of life in its many forms. However, the information content of DNA sequences is limited and, on its own, cannot describe most physiological and pathological processes.

Unlike oligonucleotides, proteins are a very diverse group of biomolecules that display a wide range of chemical and biophysical features, including

  • membrane-binding,
  • hetero/homo-oligomerization, and
  • posttranslational modification.

The biochemical complexity intrinsic to protein science intimates that several complementary analytical strategies will be needed to achieve the ultimate goal of proteomics – a comprehensive characterization of the expression, modification state, interaction map, and activity of all proteins in cells and tissues.

A powerful LC-MS strategy for proteomics involves the use of isotope-coded affinity tags (ICAT). This approach enables the comparison of protein expression in proteomes by treating samples with isotopically distinct forms of a chemical labeling reagent. ICAT methods provide superior resolving power compared to gel-based methods and improve access to membrane-associated proteins. More recently, isotope-free MS methods for quantitative proteomics have emerged.

Reverse protein microarrays have also been described in which proteomes themselves are arrayed and the antibodies used for detection in a format analogous to Western blotting. In addition to increasing the throughput of proteomic experiments by integrating the protein separation and detection steps, microarrays consume much less material than conventional proteomic methods. Still, the general application of microarrays for proteomics is currently limited by the availability of high-quality capture reagents (e.g., antibodies, aptamers, etc).

These approaches, by measuring protein abundance provide, like genomics, only an indirect assessment of protein activity and may fail to detect important posttranslational events that regulate protein function, such as protein–protein or protein–small-molecule interactions. To address these limitations, complementary strategies for the functional analysis of proteins have been introduced. Prominent among these functional proteomic efforts is the use of chemistry for the design of active site-directed probes that measure enzyme activity in samples of high biological complexity.

Many post-translational modes of enzyme regulation share a common mechanistic foundation – they perturb the active site such that catalytic power and/or substrate recognition is impaired. Accordingly, it was hypothesized that chemical probes capable of reporting on the integrity of enzyme active sites directly in cells and tissues might serve as effective functional proteomic tools. These activity based protein profiling (ABPP) probes consist of at least two general elements:

  1. a reactive group for binding and covalently modifying the active sites of many members of a given enzyme class or classes
  2. a reporter tag for the detection, enrichment, and identification of probe-labeled proteins

ABPP probes have been successfully developed for more than a dozen enzyme classes, including

  • all major classes of proteases
  • kinases
  • phosphatases
  • glycosidases
  • GSTs
  • oxidoreductases.

Post-translational regulation of enzyme activity. Many enzymes are produced as inactive precursors, or zymogens, which require proteolytic processing for activation. Enzyme activity can be further regulated by interactions with endogenous protein inhibitors.
The field of proteomics aims to develop and apply technologies for the characterization of protein function on a global scale. Toward this end, synthetic chemistry has played a major role by providing new reagents to profile segments of the proteome based on activity rather than abundance. Small molecule probes for activity-based protein profiling have been created for more than a dozen enzyme classes and used to discover several enzyme activities elevated in disease states. These innovations have inspired complementary advancements in analytical chemistry, where new platforms have been introduced to augment the information content achievable in chemical proteomics experiments. Here, we will review these analytical platforms and discuss how they have exploited the versatility of chemical probes to gain unprecedented insights into the function of proteins in biological samples of high complexity.

Advanced analytical platforms utilize a range of separation and detection strategies, including LC-MS, CELIF, and antibody microarrays, to achieve an unprecedented breadth and depth of proteome coverage in ABPP investigations. The complementary strengths and weaknesses of each of these methods suggest that the selection of an appropriate analytical platform should be guided by the specific experimental question being addressed.
SA Sieber and BF Cravatt. Analytical platforms for activity-based protein profiling – exploiting the versatility of chemistry for functional proteomics. Chem. Commun. 2006, 2311–2319. http://www.rsc.org/chemcomm

Diagnostic Therapeutics in Activity Based Probes
Activity-based chemical proteomics-an emerging field involving a combination of organic synthesis, biochemistry, cell biology, biophysics and bioinformatics-allows the detection, visualisation and activity quantification of whole families or selected sub-sets of proteases based upon their substrate specificity. This approach can be applied for drug target/lead identification and validation, the fundamentals of drug discovery. The activity-based probes discussed in this review contain three key features;

  1. a ‘warhead’ (binds irreversibly but selectively to the active site),
  2. a ‘tag’ (allowing enzyme ‘handling’, with a combination of fluorescent, affinity and/or radio labels),
  3. a linker region between warhead and tag.

From the design and synthesis of the linker arise some of the latest developments discussed here; not only can the physical properties (e.g., solubility, localisation) of the probe be tuned, but the inclusion of a cleavable moiety allows selective removal of tagged enzyme from affinity beads etc.
Heal WP, Wickramasinghe SR, Tate EW. Activity based chemical proteomics: profiling proteases as drug targets. Curr Drug Discov Technol 2008; 5(3):200-12. PMID: 18690889

The genomic revolution has created a wealth of information regarding the fundamental genetic code that defines the inner workings of a cell. However, it has become clear that analyzing genome sequences alone will not lead to new therapies to fight human disease. Rather, an understanding of protein function within the context of complex cellular networks will be required to facilitate the discovery of novel drug targets and, subsequently, new therapies directed against them. The past ten years has seen a dramatic increase in technologies that allow large-scale, systems-based methods for analysis of global biological processes and disease states.

In the field of proteomics, several well-established methods persist as a means to resolve and analyze complex mixtures of proteins derived from cells and tissues. However, the resolving power of these methods is often challenged by the diverse and dynamic nature of the proteome. The field of activity-based proteomics, or chemical proteomics, has been established in an attempt to focus proteomic efforts on subsets of physiologically important protein targets. This new approach to proteomics is centered around the use of small molecules termed activity-based probes (ABPs) as a means to tag, enrich, and isolate, distinct sets of proteins based on their enzymatic activity.
Berger AB, Vitorino PM, Bogyo M. Activity-based protein profiling: applications to biomarker discovery, in vivo imaging and drug discovery. Am J Pharmacogenomics. 2004;4(6):371-81.

Recent advances in global genomic and proteomic methods have led to a greater understanding of how genes and proteins function in complex networks within a cell. One of the major limitations in these methodologies is their inability to provide information on the dynamic, post-translational regulation of enzymatic proteins. In particular proteases are often synthesized as inactive zymogens that need to be activated in order to carry out specific biological processes. Thus, methods that allow direct monitoring of protease activity in the context of a living cell or whole animal will be required to begin to understand the systems-wide functional roles of proteases. In this review, we discuss the development and applications of activity based probes (ABPs) to study proteases and their role in pathological processes. Specifically we focus on application of this technique for biomarker discovery, in vivo imaging and drug screening.

Fonović M, Bogyo M. Activity based probes for proteases: applications to biomarker discovery, molecular imaging and drug screening. Curr Pharm Des. 2007;13(3):253-61.

Proteases, in particular, are known for their multilayered post-translational activity regulation that can lead to a significant difference between protease abundance levels and their enzyme activity. To address these issues, the field of activity-based proteomics has been established in order to characterize protein activity and monitor the functional regulation of enzymes in complex proteomes.

Fonović M, Bogyo M. Activity-based probes as a tool for functional proteomic analysis of proteases. Expert Rev Proteomics. 2008; 5(5):721-30. PMID: 18937562. PMCID: PMC2997944

As a result of the recent enormous technological progress, experimental structure determination has become an integral part of the development of drugs against disease-related target proteins. The post-translational modification of proteins is an important regulatory process in living organisms; one such example is lytic processing by peptidases. Many different peptidases represent disease targets and are being used in structure-based drug design approaches. The development of drugs such as aliskiren and tipranavir, which inhibit renin and HIV protease, respectively, testifies to the success of this approach.

Mittl PR, Grütter MG. Opportunities for structure-based design of protease-directed drugs.
Curr Opin Struct Biol 2006; 16(6):769-75. Epub 2006 Nov 16. PMID: 17112720

Presenilin is the catalytic component of γ-secretase, a complex aspartyl protease and a founding member of intramembrane-cleaving proteases. γ-Secretase is involved in the pathogenesis of Alzheimer’s disease and a top target for therapeutic intervention. However, the protease complex processes a variety of transmembrane substrates, including the Notch receptor, raising concerns about toxicity. Nevertheless, γ-secretase inhibitors and modulators have been identified that allow Notch processing and signaling to continue, and promising compounds are entering clinical trials.

Molecular and biochemical studies offer a model for how this protease hydrolyzes transmembrane domains in the confines of the lipid bilayer. Progress has also been made toward structure elucidation of presenilin and the γ-secretase complex by electron microscopy as well as by studying cysteine-mutant presenilins. The signal peptide peptidase (SPP) family of proteases are distantly related to presenilins. However, the SPPs work as single polypeptides without the need for cofactors and otherwise appear to be simple model systems for presenilin in the γ-secretase complex.

Critical clues to the identity of γ-secretase included:
(1) Genes encoding the multi-pass membrane proteins presenilin-1 and presenilin-2 are, like APP, associated with familial, early-onset Alzheimer’s disease. The disease-causing missense mutations were found to alter how γ-secretase cuts APP, leading to increased proportions of longer, more aggregation-prone forms of Aβ.
(2) Knockout of presenilin genes eliminates γ-secretase cleavage of APP.
(3) Peptidomimetics that inhibit γ-secretase contain moieties typically found in aspartyl protease inhibitors.
These findings led to the identification of two conserved transmembrane aspartates in the multi-pass presenilins that are critical for γ-secretase cleavage of APP, evidence that presenilins are aspartyl proteases.
Presenilin is endoproteolytically cleaved into two polypeptides, an N-terminal fragment (NTF) and a C-terminal fragment (CTF), the formation of which is

  • regulated
  • metabolically stable
  • part of a high-molecular weight complex

suggesting that the NTF-CTF heterodimer is the biologically active form. NTF and CTF each contribute one of the essential and conserved aspartates, and transition-state analogue inhibitors of γ-secretase, compounds designed to interact with the active site of the protease, bind directly to presenilin NTF and CTF.
Presenilins are also required for Notch signaling (Levitan and Greenwald, 1995), a pathway essential for cell differentiation during development and beyond.

The highly conserved role of γ-secretase in Notch signalling and its importance in development led to genetic screens in Caenorhabditis elegans that identified three other integral membrane proteins besides presenilin that modify Notch signaling.
Designed inhibitors have proven to be useful tools in understanding the mechanism of γ-secretase and substrate recognition – affinity labelling with transition-state analogue inhibitors showed binding at the interface between the presenilin NTF and CTF subunits, consistent with the active site residing at this interface, with each presenilin subunit contributing one of the essential aspartates.
The concept of presenilin as the catalytic component for γ-secretase was considerably strengthened when

  1. signal peptide peptidase (SPP) was found to be a similar intramembrane aspartyl protease
  2. SPP is exploited by the hepatitis C virus for the maturation of its core protein, suggesting that this protease may be a suitable target for antiviral therapy
  3. SPP was identified by affinity labeling with a peptidomimetic inhibitor, and the protein sequence displayed similarities with presenilin.
  4. SPP contains two conserved aspartates, each predicted to lie in the middle of a transmembrane domain, and the aspartate-containing sequences resemble those found in presenilins.
  5. SPP appears to be less complicated than γ-secretase.

Expression of human SPP in yeast reconstituted the protease activity, suggesting that the protein has activity on its own and does not require other mammalian protein cofactors.

Aspartyl I-CLiPs are found in all forms of life and play essential roles in biology and disease. How these enzymes carry out hydrolysis in the membrane is a fascinating question that is not entirely resolved, but evidence suggests an initial substrate docking site and a lateral gate into a pore where water and the active site aspartates reside. Designed inhibitors have been critical in elucidating these mechanisms, but inhibitors targeting γ-secretase for the treatment of Alzheimer’s disease must avoid interfering with Notch signaling.

MS Wolfe. Structure, Mechanism and Inhibition of γ-Secretase and Presenilin-Like Proteases.
Biol Chem. 2010 August; 391(8): 839–847. doi: 10.1515/BC.2010.086. PMCID: PMC2997569. NIHMSID: NIHMS254540
Study Suggests Expanding the Genetic Alphabet May Be Easier than Previously Thought
Genomics Monday, June 4, 2012
A new study led by scientists at The Scripps Research Institute suggests that the replication process for DNA—the genetic instructions for living organisms that is composed of four bases (C, G, A and T)—is more open to unnatural letters than had previously been thought.

An expanded “DNA alphabet” could carry more information than natural DNA, potentially coding for a much wider range of molecules and enabling a variety of powerful applications, from precise molecular probes and nanomachines to useful new life forms.
The new study, which appears in the June 3, 2012 issue of Nature Chemical Biology, solves the mystery of how a previously identified pair of artificial DNA bases can go through the DNA replication process almost as efficiently as the four natural bases.
“We now know that the efficient replication of our unnatural base pair isn’t a fluke, and also that the replication process is more flexible than had been assumed,” said Floyd E. Romesberg, principal developer of the new DNA bases.

Adding to the DNA Alphabet
Romesberg and his lab have been trying to find a way to extend the DNA alphabet since the late 1990s. In 2008, they developed the efficiently replicating bases NaM and 5SICS, which come together as a complementary base pair within the DNA helix, much as, in normal DNA, the base adenine (A) pairs with thymine (T), and cytosine (C) pairs with guanine (G).

The following year, Romesberg and colleagues showed that NaM and 5SICS could be efficiently transcribed into RNA. But these bases’ lack the ability to form the hydrogen bonds that join natural base pairs in DNA. Such bonds had been thought to be an absolute requirement for successful DNA replication‑—a process in which a large enzyme, DNA polymerase, moves along a single, unwrapped DNA strand and stitches together the opposing strand, one complementary base at a time.

An early structural study of a very similar base pair in double-helix DNA added to Romesberg’s concerns. The data strongly suggested that NaM and 5SICS do not even approximate the edge-to-edge geometry of natural base pairs—termed the Watson-Crick geometry, after the co-discoverers of the DNA double-helix. Instead, they join in a looser, overlapping, “intercalated” fashion. “Their pairing resembles a ‘mispair,’ such as two identical bases together, which normally wouldn’t be recognized as a valid base pair by the DNA polymerase.” Yet in test after test, the NaM-5SICS pair was efficiently replicable.

Edge to Edge
The NaM-5SICS pair maintain an abnormal, intercalated structure within double-helix DNA—but remarkably adopt the normal, edge-to-edge, “Watson-Crick” positioning when gripped by the polymerase during the crucial moments of DNA replication. “The DNA polymerase apparently induces this unnatural base pair to form a structure that’s virtually indistinguishable from that of a natural base pair.” NaM and 5SICS, lacking hydrogen bonds, are held together in the DNA double-helix by “hydrophobic” forces, which cause certain molecular structures to be repelled by water molecules, and thus to cling together in a watery medium. “It’s very possible that these hydrophobic forces have characteristics that enable the flexibility and thus the replicability of the NaM-5SICS base pair.”

An Arbitrary Choice?
The finding suggests that NaM-5SICS and potentially other, hydrophobically bound base pairs could some day be used to extend the DNA alphabet. It also hints that Evolution’s choice of the existing four-letter DNA alphabet—on this planet—may have been somewhat arbitrary. “It seems that life could have been based on many other genetic systems.” Source: The Scripps Research Institute

DNA damage response (DDR) network

Eukaryotic cells have evolved an intricate system to resolve DNA damage to prevent its transmission to daughter cells. This system, collectively known as the DNA damage response (DDR) network, includes many proteins that detect DNA damage, promote repair, and coordinate progression through the cell cycle. Because defects in this network can lead to cancer, this network constitutes a barrier against tumorigenesis. The modular BRCA1 carboxyl-terminal (BRCT) domain is frequently present in proteins involved in the DDR, can exist either as an individual domain or as tandem domains (tBRCT), and can bind phosphorylated peptides. We performed a systematic analysis of protein-protein interactions involving tBRCT in the DDR.

We identified 23 proteins containing conserved BRCT domains and generated a human protein-protein interaction network for seven proteins with tBRCT. This study also revealed previously unknown components in DNA damage signaling, such as COMMD1 and the target of rapamycin complex mTORC2. Additionally, integration of tBRCT domain interactions with DDR phosphoprotein studies and analysis of kinase-substrate interactions revealed signaling subnetworks that may aid in understanding the involvement of tBRCT in disease and DNA repair.

NT Woods, RD Mesquita, M Sweet, MA. Carvalho, et al. Charting the Landscape of Tandem BRCT Domain–Mediated Protein Interactions. Sci. Signal 2012; 5(242): rs6. DOI: 10.1126/ scisignal.2002255.

Mitochondrial ROS production

Mitochondria have various essential functions in metabolism and in determining cell fate during apoptosis. In addition, mitochondria are also important nodes in a number of signaling pathways. For example, mitochondria can modulate signals transmitted by second messengers such as calcium. Because mitochondria are also major sources of reactive oxygen species (ROS), they can contribute to redox signaling—for example, by the production of ROS such as hydrogen peroxide that can reversibly modify cysteine residues and thus the activity of target proteins. Mitochondrial ROS production is thought to play a role in hypoxia signaling by stabilizing the oxygen-sensitive transcription factor hypoxia-inducible factor–1α. New evidence has extended the mechanism of mitochondrial redox signaling in cellular responses to hypoxia in interesting and unexpected ways. Hypoxia altered the microtubule-dependent transport of mitochondria so that the organelles accumulated in the perinuclear region, where they increased the intranuclear concentration of ROS. The increased ROS in turn enhanced the expression of hypoxia-sensitive genes such as VEGF (vascular endothelial growth factor) not by reversibly oxidizing a protein, but by oxidizing DNA sequences in the hypoxia response element of the VEGF promoter. This paper and other recent work suggest a new twist on mitochondrial signaling: that the redistribution of mitochondria within the cell can be a component of regulatory pathways.

M. P. Murphy. Modulating Mitochondrial Intracellular Location as a Redox Signal. Sci Signal 2012; 5(242): p re39. DOI: 10.1126/scisignal.2002858

A challenge in the treatment of lung cancer is the lack of early diagnostics. Here, we describe the application of monoclonal antibody proteomics for discovery of a panel of biomarkers for early detection (stage I) of non-small cell lung cancer (NSCLC). We produced large monoclonal antibody libraries directed against the natural form of protein antigens present in the plasma of NSCLC patients. Plasma biomarkers associated with the presence of lung cancer were detected via high throughput ELISA. Differential profiling of plasma proteomes of four clinical cohorts, totaling 301 patients with lung cancer and 235 healthy controls, identified 13 lung cancer-associated (p < 0.05) monoclonal antibodies. The monoclonal antibodies recognize five different cognate proteins identified using immunoprecipitation followed by mass spectrometry. Four of the five antigens were present in non-small cell lung cancer cells in situ.

Guergova-Kuras M, Kurucz I, Hempel W, et al. Discovery of lung cancer biomarkers by profiling the plasma proteome with monoclonal antibody libraries. Mol Cell Proteomics. 2011 (12): M111.010298. Epub 2011 Sep 26.

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SDS-PAGE with Taq DNA Polymerase. SDS-PAGE is ...

SDS-PAGE with Taq DNA Polymerase. SDS-PAGE is an useful technique to separate proteins according to their electrophoretic mobility. (Photo credit: Wikipedia)

Proteomics and Biomarker Discovery

Reporter: Larry H. Bernstein, MD, FCAP

 

 

Advanced Proteomic Technologies for Cancer Biomarker Discovery

Sze Chuen Cesar Wong; Charles Ming Lok Chan; Brigette Buig Yue Ma; Money Yan Yee Lam; Gigi Ching Gee Choi; Thomas Chi Chuen Au; Andrew Sai Kit Chan; Anthony Tak Cheung Chan

Published: 06/10/2009

This report is extracted from the article above with editing and shortening as much as possible for the reader, and updated from LCGCNA Aug 12,  2012; 8
www.chromatographyonline.com

Part I

Abstract

This review will focus on four state-of-the-art proteomic technologies, namely 2D difference gel electrophoresis, MALDI imaging mass spectrometry, electron transfer dissociation mass spectrometry and reverse-phase protein array. The major advancements these techniques have brought about biomarker discovery will be presented in this review. The wide dynamic range of protein abundance, standardization of protocols and validation of cancer biomarkers, and a 5-year view of potential solutions to such problems is discussed.

English: Public domain image from cancer.gov h...

English: Public domain image from cancer.gov http://visualsonline.cancer.gov/details.cf?imageid=3483. TECAN Genesis 2000 robot preparing Ciphergen SELDI-TOF protein chips for proteomic  analysis. (Photo credit: Wikipedia)

Introduction

A common method used for isolating and identifying cancer biomarkers involves the use of serum or tissue protein identification. Unfortunately, currently used tumor markers have low sensitivities and specificities.[2] Therefore, the development of novel tumor markers might be helpful in improving cancer diagnosis, prognosis and treatment.

The rapid development of proteomic technologies during the past 10 years has brought about a massive increase in the discovery of novel cancer biomarkers. Such biomarkers may have broad applications, such as for the detection of the presence of a disease, monitoring of disease clearance and/or progression, monitoring of treatment response and demonstration of drug targeting of a particular pathway and/or target. In general, proteomic approaches begin with the collection of biological specimens representing two different physiological conditions, cancer patients and reference subjects. Proteins or peptides are extracted and separated, and the protein or peptide profiles are compared against each other in order to detect differentially expressed proteins. Commonly, quantitative proteomics is mainly performed by protein separation using either 2DE- or liquid chromatography (LC)-based methods coupled with protein identification using mass spectrometry (MS). Limitations include inability to obtain protein profiles directly from tissue sections for correlation with tissue morphology, limited ability to analyze post-translational modifications (PTMs) and low capacity for high-throughput validation of identified markers. Progress in proteomic technologies has led to the development of 2D DIGE, MALDI imaging MS (IMS), electron transfer dissociation (ETD) MS, and reverse-phase protein array (RPA).

2D Difference Gel Electrophoresis

The 2DE method has been one of the mainstream technologies used for proteomic investigations.[3,4] In this method, proteins are separated in the first dimension according to charge by isoelectric focusing, followed by separation in the second dimension according to molecular weight, using polyacrylamide gel electrophoresis. The gels are then stained to visualize separated protein spots,[5] separating up to 1000 protein spots in a single experiment and  protein spots are then excised and identified using mass spectrometry (MS).[6,7]

We previously used a 2DE approach to compare the proteomic profiles to identify differentially expressed proteins that may be involved in the development of nasopharyngeal cancer, [8]   as well as proteins that were responsive to treatment with the chemotherapeutic agent 5-fluorouracil (5FU) in the colorectal cancer SW480 cell line. Briefly, cell lysates from SW480 cells that were either treated with 5FU or were controls were separated using 2DE. After staining and analysis of the gels, differentially expressed protein spots were excised and identified using MS. The upregulation of heat-shock protein (Hsp)-27 and peroxiredoxin 6 and the downregulation of Hsp-70 were successfully validated by immunohistochemical (IHC) staining of SW480 cells.[9]

The 2D DIGE method improved the 2DE technique. Figure 1 shows how two different protein samples (e.g., control and disease) and, optionally, one reference sample (e.g., control and disease pooled together) are labeled with one of three spectrally different fluorophores: cyanine (Cy)2, 3 or 5. They have the same charge, similar molecular weight and distinct fluorescent properties, allowing their discrimination during fluorometric scanning.[10-12]  The minimal dye causes minimal change in the electrophoretic mobility pattern of the protein, whereas the saturation dye labels all available cysteine residues but causes a shift in electrophoretic mobility labeled proteins.[13]  The same pooled reference sample used for all gels within an experiment is an internal reference for normalization and spot matching.[12] The gel is scanned at three different wavelengths yielding images for each of the different samples, and variation between gels is minimized and difficulties are reduced in correctly matching of protein spots across different gels.[10,11]  Significant advantages of the DIGE technology includes a dynamic range of over four orders of magnitude and full compatibility with MS.  However, careful validations of identified markers using alternative techniques are still needed.

In a study that compared three commonly used DIGE analysis software packages, Kang et al. concluded that although the three softwares performed satisfactorily with minimal user intervention, significant improvements in the accuracy of analysis could be achieved .[14] Moreover, it was suggested that results concerning the magnitude of differential expression between protein spots after statistical analysis by such softwares must be examined with care.[14]

Figure 1.  Procedures for performing a 2D DIGE experiment. CY: Cyanine; DIGE: Differential in gel electrophoresis.

The choice of appropriate statistical methods for the analysis of DIGE data has to be considered. Statistical methodological error can be addressed by the use of statistical methods that apply a false-discovery rate (FDR) for the determination of significance. In this method, q-values are calculated for all protein spots. The q-value of each spot corresponds to the expected proportion of false-positives incurred by a change in expression level of that protein spot found to be significant.

Despite the ease of use and enabling the researcher to select an appropriate FDR according to study requirements, this approach was found to be only applicable to DIGE experiments using a two-dye labeling scheme, as a three-dye labeling approach violated the assumption of data independence required for statistical analysis.[16] Other statistical tests that have been applied for the analysis of DIGE results include significance analysis of microarrays,[7] principal components analysis[17,18] and partial least squares discriminant analysis.[18,19] Detailed discussions of the different statistical approaches applicable to proteomic research are beyond the scope of this review and readers may refer to[18,20] for further reading.

Using 2D DIGE, Yu et al. successfully identified biomarkers that were associated with pancreatic cancer.[21] In the study, 24 upregulated and 17 downregulated proteins were identified by MS. Among those proteins, upregulation of apolipoprotein E, α-1-antichymotrypsin and inter-α-trypsin inhibitor were confirmed by western blot analysis. Furthermore, the association of those three proteins with pancreatic cancer was successfully validated in another series of 20 serum samples from pancreatic cancer patients. Using a similar approach, Huang et al. identified and confirmed the upregulation of transferrin in the sera of patients with breast cancer.[22] When Sun et al. compared the proteomic profiles between malignant and adjacent benign tissue samples from patients with hepatocellular carcinoma, they proved 2D DIGE is not limited to serum or plasma samples.[23] In their study, overexpression of Hsp70/Hsp90-organizing protein and heterogenous nuclear ribonucleoproteins C1 and C2 were identified by 2D DIGE coupled with MS analysis, and the findings were successfully validated by both western blotting and IHC staining. Next, Kondo et al. applied 2D DIGE to laser-microdissected cells from fresh patient tissues.[13] Using this protocol, a 1-mm area of an 8-12-µm-thick tissue section was shown to be sufficient. These examples demonstrate the high sensitivity and broad applicability of 2D DIGE for proteomic investigations using various types of patient samples and provide evidence that 2D DIGE is a powerful technique for biomarker discovery.

MALDI Imaging Mass Spectrometry

A deeper understanding of the complex biochemical processes occurring within tumor cells and tissues requires a knowledge of the spatial and temporal expression of individual proteins. Currently, such information is mainly obtained by IHC staining for specific proteins in patient tissues.[8,24,25] Nevertheless, IHC has limited use in high-throughput proteomic biomarker discovery because only a few proteins can be immunostained simultaneously. MALDI IMS allows researchers to analyze proteomic expression profiles directly from patient tissue sections.[26-28] The protocol begins with mounting a tissue section onto a sample plate (Figure 2). MALDI matrix is then applied onto the tissue sample, which is analyzed by MALDI MS in order to obtain mass spectra from predefined locations across the entire patient tissue section. The mass spectrum from each location is a complete proteomic profile for that particular area. All acquired mass spectra from the entire tissue are then compiled to create a 2D map for that tissue sample. This map could then be compared with those from other tissue samples to identify changes in protein or peptide expression or comparisons of the maps from different areas within the same tissue section could be performed. This technology  importantly allows the high-throughput discovery of novel protein markers. In addition, correlations between protein expression and tissue histology can also be studied easily.

Most studies using MALDI IMS have been performed on frozen tissue sections ranging from 5 to 20 µm in thickness.[26,27,29] After sectioning, a MALDI matrix is applied either by automated spraying or spotting. The matrix of choice is usually α-cyano-4-hydroxy-cinnamic acid for peptides and sinapinic acid (3,5-dimethoxy-4-hydroxycinnamic acid) for proteins.

Figure 2.  Procedures for MALDI imaging. IMS: Imaging mass spectrometry; MS: Mass spectrometry.

Spotting allows the precise application of matrix to areas of interest and minimizes the diffusion of analyte material across the sample, although the imaging resolution achieved by spotting is lower (~150 µm). A laser beam is then fired towards the area of interest on the tissue section to generate protein ions for analysis by a mass analyzer.[29] Among the different mass analyzers, TOF analyzers are the most commonly used owing to their high sensitivity, broad mass range and suitability for detection of ions generated by MALDI. Use of other mass analyzers such as TOF-TOF, quadrupole TOF (QTOF), ion traps (ITs) and Fourier transform-ion cyclotron resonance (FT-ICR) have also been reported in other studies.[30-33]

After obtaining the mass spectra, statistical analysis needs to be performed to identify statistically significant features that could have potential use as biomarkers. But before such analyses can be applied, there has to be background-noise subtraction, spectral normalization and spectral alignment.[34,35,34] Statistical methods used to identify significant differences in peak intensity are symbolic discriminant analysis and principal component analysis. Symbolic discriminant analysis determines discriminatory features and builds functions based on such features for distinguishing samples according to their classification.[36,37] Using this approach, Lemaire et al. found a putative proteomic biomarker from ovarian cancer tissues by MALDI IMS that was later identified to be the Reg-α protein, a member of the proteasome activator 11S.[37] This result was later successfully validated by western blot (protein expression found in 88.8% carcinoma cases vs 18.7% benign disease) and IHC (protein expression found in 63.6% carcinoma tissues vs 16.6% benign tissues).[37] On the other hand, principal component analysis reduces data complexity by transforming data based on peak intensities to information based on data variance, termed ‘principal components’, resulting in a list of significant peaks (principal components) ordered by decreasing variance.[35,38,39] Neither symbolic discriminant analysis or principal component analysis is capable of performing unsupervised classification. This aim requires the use of other methods such as hierarchical clustering.[39,40] In this method identified peaks are clustered as nodes in a pair-wise manner according to similarity until a dendogram is obtained, providing information as to the degree of association of all peak masses in a hierarchical fashion. Peaks that are capable of differentiating between different histological/pathological features could then be chosen for further validation of their value as tumor markers.[39]

In MALDI IMS, protein identification cannot be performed with confidence solely on the molecular weight. However, Groseclose et al. have developed a method using in situ digestion of proteins directly on tissue section.[41] They first used MALDI IMS to obtain a map of the protein and peptide spectra, then spotted a consecutive section of the same tissue sample with trypsin for protein digestion, and then spotted matrix solution onto the digested spots and the resulting peptides are identified directly from the tissue by MS/MS. This modification increases the confidence in protein identification. The time required for MALDI IMS analysis per tissue section is as follows: tissue sectioning, mounting and matrix application: 4-8 h; MALDI image acquisition: 1-2 days; spectral analysis: 1-2 h.[33,39]

Recently, in situ enzymatic digestion has been successfully applied for improving the retrieval of peptides directly from formalin-fixed, paraffin-embedded FFPE tissue samples.[27] Such development has greatly facilitated the application of MALDI IMS in FFPE tissues.[26,42] In fact, Stauber et al. identified the downregulation of ubiquitin, transelongation factor 1, hexokinase and neurofilament M from FFPE brain tissues of rat models of Parkinson disease using this modified technique.[42] The success of performing proteomic profiling using MALDI IMS directly on FFPE tissues opens up great possibility for using archival patient materials in high-throughput biomarker discovery. Novel cancer biomarkers identified using MALDI IMS still require validation by other techniques such as IHC.

Electron Transfer Dissociation MS

Post-translational modifications play important roles in the structure and function of proteins such as protein folding, protein localization, regulation of protein activity and mediation of protein-protein interaction. Two common forms of PTM that have been implicated in cancer development are phosphorylation and glycosylation. Previously, phosphoproteomic studies have led to the identification of novel tyrosine kinase substrates in breast cancer,[43] discovery of novel therapeutic targets for brain cancer[44] and increased understanding of signaling pathways involved in lung cancer formation.[45,46] Conversely, the identification of abnormally glycosylated proteins, such as mucins, has provided novel biomarkers and therapeutic targets for ovarian cancer.[47]

The study of PTM begins with digesting the target protein using enzymes such as trypsin,   introducing the fragments into MS for determination of the sites and types of modification and, at the same time, identification of the protein. The analysis is conventionally carried out using collision-induced dissociation (CID) MS, where peptides are collided with a neutral gas for cleavage of peptide bonds to produce b- and y-type ions (Figure 3). A complete series of peptides differing in length by one amino acid is produced, leading to identification of the protein by peptide-sequence determination. However, for phosphopeptides, the presence of phosphate groups would compete with the peptide backbone as the preferred cleavage site. The end result is a reduced set of peptide fragments, which hinders protein identification, and the exact location of the phosphate group on the peptide cannot be determined accurately when there are more than one possible phosphorylation sites.[48,49]

Figure 3.  Peptide bond-cleavage site for a-, b-, c-, x-, y– and z-type ions.

Electron transfer dissociation is a recently developed dissociation technique for the analysis of peptides by MS, utilizing radiofrequency quadrupole ion traps such as 2D linear IT, spherical IT and Orbitrap™ (Thermo Fisher Scientific Inc., MA, USA) mass analyzers.[48,49] In this technology, peptides are fragmented by transfer of electrons from anions to induce cleavage of Cα-N bonds along the peptide backbone, hence producing c- and z-type ions (Figure 3). In contrast to CID, ETD preserves the localization of labile PTM and also provides peptide-sequence information.[48] But ETD fails to fragment peptide bonds adjacent to proline, which are readily cleaved by CID.[50] A study that compared the performance of CID with that of ETD found that only 12% of the identified peptides were commonly detected between the two techniques. A study reported that CID successfully identified more peptides with charge states of +2 and below, whereas ETD was found to be better at identifying peptide ions with charge states of greater than +2.[51] Therefore, it is suggested that CID and ETD should be used together to complement each other.[52]  Han et al. successfully differentiated the isobaric amino acids isoleucine and leucine from one another by performing CID on the resulting z-ions after ETD. The presence of isoleucine residue was then confirmed by the detection of a specific 29-Da loss from the peptide.[53]  A clear advantage of using ETD for the analysis of phosphopeptides is a near complete series of c- and z-ions without loss of phosphoric acid,[48] greatly facilitating the determination of the phosphorylation sites and the identification of phosphopeptides. Recently, an analysis of yeast phosphoproteome using ETD successfully identified 1252 phosphorylation sites on 629 proteins, whose expression levels ranged from less than 50 to 1,200,000 copies per cell.[54] In another study using ETD, a total of 1435 phosphorylation sites were identified from human embryonic kidney 293T cells, of which 1141 (80%) were previously unidentified. Finally, a study by Molina et al. successfully identified 80% of the known phosphorylation sites in more than 1000 yeast phosphopeptides in one single study using a combination of ETD and CID.[55] In addition, ETD could be applied to investigate other forms of PTM, such as N-linked glycosylations.[56,57] N-linked glycans contain a common core with branched structures. These can be processed by stepwise addition or removal of monosaccharide residues linked by glycosidic bonds, producing highly varied forms of N-linked glycan structures.[58-60] A weakness of analyzing glycopeptides using CID is that cleavage of glycosidic bonds occurs with little peptide backbone fragmentation, so that only the glycan structure is available.[61]  Hogan et al. used CID and ETD together to overcome this problem determining the glycan structure and glycosylation site.[61] ICID was initially used for cleavage of glycosidic bonds that allowed the entire glycan structure to be inferred from the CID spectrum alone. ETD was later performed to dissociate the same peptide that resulted in a contiguous series of fragment ions with no loss of glycan molecules, allowing the identification of both the site of glycosylation and the identity of the glycoprotein.[61] Readers are strongly encouraged to refer to[49] and.[62] In a comprehensive comparison of CID versus ETD for the identification of peptides without PTMs, CID was found to identify 50% more peptides than ETD (3518 by CID vs 2235 by ETD), but ETD provided somewhat better sequence coverage (67% for CID vs 82% for ETD). It turns out that ETD produced more uniformly fragmented ions with intensities that were five- to ten-times lower than those produced by CID.[55] Finally, the best sequence coverage of up to 92% was achieved when consecutive CID and ETD were performed.[55]

This increase in sequence coverage using the combined approach is needed for studies requiring de novo peptide identifications. As such, this strategy is particularly suited for studies involved in the discovery, identification and characterization of novel peptides or proteins and their PTMs for biomarker use. A prerequisite of this technique is that the biological samples under investigation must undergo some form of fractionation before they are amenable to analysis by ETD or CID. This is achieved by the use of LC techniques, such as reverse-phase, strong cation exchange or strong anion exchange chromatography, and serves to reduce the complexity and wide dynamic range of protein-expression levels commonly found in biological specimens. Given the important roles of PTM in the function and activity of proteins, this technology paves the way for exploring the intricate cellular activities within a cancer cell.

References

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Advanced Proteomic Technologies for Cancer Biomarker Discovery

Part II

Reverse-phase Protein Array

One of the goals of proteomics is to identify protein changes associated with the development of diseases such as cancer.  Even with the rapid development of proteomic technologies during the past few years, analysis of patient samples is still a challenge. Difficulties arise from the fact that[63,64]:

  • Proteomic patterns differ among cell types;
  • Protein expression changes occur over time;
  • Proteins have a broad dynamic range of expression levels spanning several orders of magnitude;
  • Proteins can be present in multiple forms, such as polymorphisms and splice variants;
  • Traditional proteomic methods require relatively large amounts of protein
  • Many proteomic technologies cannot be used to study protein-protein interactions.

The principle of RPA is simple and involves the spotting of patient samples in an array format onto a nitrocellulose support (Figure 4). Hundreds of patient specimens can be spotted onto an array, allowing a comparison of a large number of samples at once.[65] Each array is incubated with one particular antibody, and signal intensity proportional to the amount of analyte in the sample spot is generated.[66] Signal detection is commonly performed by fluorescence, chemiluminescence or colorimetric methods. The results are quantified by scanning and analyzed by softwares such as P-SCAN and ProteinScan, which can be downloaded from[84] for free.[67,68]

Figure 4.  Principle of reverse-phase protein array.

Main advantages of RPA technology include[69-71]:

  • Various types of biological samples can be used;
  • The possibility of investigating PTMs;
  • Protein-protein interactions can be studied;
  • Labeling of patient samples with fluorescent dyes (e.g., 2D DIGE) or mass tags (e.g., isotope-coded affinity tag [ICAT]) are not required;
  • Any samples spotted as a dilution allows quantifying in the linear range of detection;
  • Quantitative measurement of any protein is possible compared to reference standards of known amounts on the same array.

It has been shown that RPA is extremely sensitive as it is capable of detecting up to zeptomole (1 x 10-21 mole) levels of target proteins with less than 10% variance. The analysis of few cell signaling events is known.[65,70,71] The assay sensitivity depends on antibody affinity, which depends upon antigen-antibody pairs.[68] Of course, only known proteins with available antibodies can be identified. Therefore, this method is more suitable for biomarker screening or validation than discovery of novel proteins. To assist researchers in selecting suitable antibodies, two open antibody databases show their western blot results using cell lysates.[72,73,85,86]

One application of RPA is to investigate the signaling pathways in human cancers. Zha et al. compared the survival signaling events between Bcl 2-positive and -negative lymphomas and found that survival signals, independent of Bcl 2 expression, were detected in follicular lymphoma and confirmed by validation with IHC.[71] In another study, patient-specific signaling pathways have been identified in breast cancers using RPA. Bayesian clustering of a set of 54 subjects successfully separated normal subjects from cancer patients based on an epithelial signaling signature. Principal component analysis was capable of distinguishing normal from cancer patient samples by using a signature composed of a panel of kinase substrates.[69] Differences in cell signaling between patient-matched primary and metastatic lesions have also been found using RPA. In the study, six patient-matched primary ovarian tumors probed with antibodies against signaling proteins, and the signaling profiles differed significantly between primary and metastatic tumors and upregulation of phosphor c-kit was capable of distinguishing five of the six metastatic tumors from the primary lesions.[70] These findings suggest that treatment strategies may need to target signaling events among disseminated tumor cells.

Reverse-phase protein array has also been used to validate mathematical models of cellular pathways. The p53-Mdm2 feedback loop is one of the most well-studied cellular-feedback mechanisms.[74] Normally, p53 activates transcription and expression of Mdm2, which, in turn, suppresses p53 activity. This negative-feedback loop ensures the low-level expression of p53 under normal conditions. Mathematical models have previously been used to investigate this negative-feedback loop.[67] Ramalingam et al. has shown, by using RPA, that part of the mechanism of the p53-Mdm2 feedback loop can be explained by current mathematical models.[75]

Another important application of RPA is for the identification of cancer specific antigens.  Using this method serum from 14 lung cancer patients, colon cancer patients and normal subjects were incubated and eight fractions of the cell lysate were recognized by the sera from four patients, while none of the sera from normal individuals was positive.[76] This study demonstrates the diagnostic potential of identifying cancer antigens that induce immune response in cancer patients by using RPA.

Expert Commentary and Five-year View

The development of 2D DIGE in the past few years has provided researchers with a more accurate method for relative quantification of proteins substantially reducing the number of replicates required for 2D gels and increased its applicability for high-throughput biomarker discovery. MALDI MS has immensely facilitated the direct discovery of biomarkers from patient tissue. Even though archival patient tissue samples are a potential source of materials for tumor marker research, high-throughput techniques for biomarker discovery using such samples has been problematic. With the development of MALDI IMS, investigators can now perform studies that aim to discover novel biomarkers directly from tissue sections and are able to correlate their expression with the histopathological changes of tumors. Previously, investigation into the sites of protein PTM has been difficult since MS-dissociation techniques, such as CID, would lead to preferential loss of PTM, but the use of ETD as a complementary peptide ion-dissociation method has allowed researchers to investigate the precise location and structure of the PTM, and to identify peptide sequence with higher confidence.

The rapid technological improvements in proteomic technologies will identify potential biomarkers for clinical use. Independent validation studies using clinical specimens must be performed before such markers can be applied clinically,. In this regard, RPA has added a potential for high-throughput screening or validation of newly found markers. Using this technique, it will be possible for researchers to quantitatively measure and validate novel markers on hundreds of patient samples simultaneously.

A big problem for proteomic researchers iincludes the abundance of proteins in biological samples. This could be partially solved by depletion of abundant proteins or by fractionation of protein samples according to characteristics. It is envisaged that, in the future, proteomic technologies will be developed to a stage that is capable of analyzing complex protein mixtures without preparatory fractionation. Such progress has recently been achieved in LC-MS, where the use of a high-field, asymmetric waveform, ion-mobility spectrometry device as an interface to an IT MS resulted in a more than fivefold increase in dynamic range without increasing the length of the LC-MS analysis.[77]

Another area that needs improvement is the standardization of protocols for patient-sample collection because results were found to be inconsistent among various studies using MS.[78] It is also considered that part of the reason for this inconsistency is due to the differences in sample-collection or sample-handling procedures.[78,79] The Human Proteome Organization previously published its findings on pre-analytical factors that affect plasma proteomic patterns and provides suggestions for sample handling.[80,81] In addition to the pre-analytical stages, it is imperative to stress that consistent and strict adherence to predefined procedures or standards, from sample collection, sample processing, experimentation, data analysis through to result validation, are of utmost importance to minimize variations and achieve consistent and reproducible results.

Any newly identified potential biomarker must also be validated using an independent cohort of patients in order to establish its clinical value, but the translation of results from the laboratory to the clinic has been slow. Consequently, it has been suggested that quantitative MS could be used for the detection of proteins.[82] The increasing availability of MS facilities to researchers worldwide will facilitate the detection, measurement and validation of protein biomarkers using quantitative MS techniques. Even after validation of such results in the laboratory, diagnostic tests will need to be developed for the marker and large-scale clinical trials would also have to be performed to confirm the results.  All these efforts require cooperation of personnel from various disciplines, such as scientists, medical professionals, pharmaceutical companies and governments. Finally, it is hoped that, through improved understanding of the protein expression as cancer progresses will lead to the discovery and development of useful cancer biomarkers for patient diagnosis, prognosis, monitoring and treatment.

Key Issues

  • 2DE coupled with mass spectrometry has been the main workhorse for the proteomic discovery of novel biomarkers in the past 10 years, and the development of 2D difference gel electrophoresis has substantially improved the quantification accuracy of 2DE.
  • MALDI imaging mass spectrometry has allowed the identification of novel proteomic features directly from patient tissue section for correlation with histopathological changes.
  • Electron transfer dissociation mass spectrometry has opened up the possibility of identifying the structure and localization of the post-translational modification and the peptide/protein.
  • Reverse-phase protein array is a powerful tool for the high-throughput validation of novel biomarkers across hundreds of patient samples simultaneously.

References

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67. Ramalingam S, Honkanen P, Young L et al. Quantitative assessment of the p53-Mdm2 feedback loop using protein lysate microarrays. Cancer Res. 67(13),6247-6252 (2007).

68. Nishizuka S, Ramalingam S, Spurrier B et al. Quantitative protein network monitoring in response to DNA damage. J. Proteome Res. 7(2),803-808 (2008).

69. Petricoin EF 3rd, Bichsel VE, Calvert VS et al. Mapping molecular networks using proteomics: a vision for patient-tailored combination therapy. J. Clin. Oncol. 23(15),3614-3621 (2005).

70. Sheehan KM, Calvert VS, Kay EW et al. Use of reverse-phase protein microarrays and reference standard development for molecular network analysis of metastatic ovarian carcinoma. Mol. Cell Proteomics 4(4),346-355 (2005).

71. Zha H, Raffled M, Charboneau L et al. Similarities of prosurvival signals in Bcl 2-positive and Bcl 2-negative follicular lymphomas identified by reverse phase protein microarray. Lab. Invest. 84(2),235-244 (2004).

72. Major SM, Nishizuka S, Morita D et al. AbMiner: a bioinformatic resource on available monoclonal antibodies and corresponding gene identifiers for genomic, proteomic, and immunologic studies. BMC Bioinformatics 7,192 (2006).

73. Spurrier B, Washburn FL, Asin S, Ramalingam S, Nishizuka S. Antibody screening database for protein kinetic modeling. Proteomics 7(18),3259-3263 (2007).

74. Ciliberto A, Novak B, Tyson JJ. Steady states and oscillations in the p53/Mdm2 network. Cell Cycle 4(3),488-493 (2005).

75. Ma L, Wagner J, Rice JJ, Hu W, Levine AJ, Stolovitzky GA. A plausible model for the digital response of p53 to DNA damage. Proc. Natl Acad. Sci. USA 102(40),14266-14271 (2005).

76. Madoz-Gurpide J, Kuick R, Wang H, Misek DE, Hanash SM. Integral protein microarrays for the identification of lung cancer antigens in sera that induce a humoral immune response. Mol. Cell. Proteomics 7(2),268-281 (2007).

77. Canterbury JD, Yi X, Hoopmann MR, MacCoss MJ. Assessing the dynamic range and peak capacity of nanoflow LC-FAIMS-MS on an ion trap mass spectrometer for proteomics. Anal. Chem. 80(18),6888-6897 (2008).

78. Coombes KR, Morris JS, Hu J, Edmonson SR, Baggerly KA. Serum proteomics – a young technology begins to mature. Nat. Biotechnol. 23(3),291-292 (2005).

78. Hortin GL. Can mass spectrometric protein profiling meet desired standards of clinical laboratory practice? Clin. Chem. 51(1),3-5 (2005).

79. Omenn GS, States DJ, Adamski M et al. Overview of the HUPO plasma proteome project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database. Proteomics 5(13),3226-3245 (2005).

80. Rai AJ, Gelfrand CA, Haywood BC et al. HUPO plasma proteome project specimen collection and handling: towards the standardization of parameters for plasma proteome samples. Proteomics 5(13),3262-3277 (2005).

• Concise report on several pre-analytical factors that impact the results of plasma proteomic profiling.

81. Mann M. Can proteomics retire the western blot? J. Proteome Res. 7(8),3065 (2008).

Update from LC/GC North America.

Solutions for Separation Scientists. Aug 2012; 30(8).

30 years of LCGC

www.chromatographyonline.com

The key advances in separation science is covered in five areas of the discipline:

  1. sample preparation
  2. gas chromatography(GC) columns
  3. GC instrumentation
  4. liquid cheomatography (LC) columns
  5. LC instrumentation

In the first, there is automated sample preparation in kit form (QuEChERS). A short list of automated sample preparation techniques includes: supercritical fluid extraction (SFE), microwave extraction, automated solvent extraction (ASE), and solid phase extraction (SPE). A panel of experts views the bast basic method of extraction is SPE, and one uses solid phase microextraction with direct immersion and static headspace extraction, along with liquid-liquid extraction.[2] In GC incremental improvements have been made with ionic liquids, multidimentional GC, and fast GC. LC has advanced dramatically with ultra-high pressure LC and superficially porous particles. LC-MS has become standard equipment routinely used in many labs.[1]

Biomarkers have to be detected in a background of 104-106 other components of comparable concentration that also partition with the stationary phase. The partition coefficients of many species are similar, or identical to the biomarker target. The issue is how to select and resolve fewer than 100 biomarkers from a milieu of 1 million components in a complex mixture. The novel idea is to target structure instead of general properties of molecules.[3] How might this work?  A single substrate, metabolite, hormone, or toxin is identified in milliseconds by specific protein receptors. The combinatorial chemistry community has shown that synthetic polynucleotides (aptamers) can be found and amplified that have selectivities approaching antibodies.This is a method well know for years as affinity chromatography. A distinct problem has been the natural process of post translational modification (PTMs), which may create isoforms by addition of a single phosphate ester to be found in the proverbial soup.

1. Bush L. Separation Science: Past, Present and Future. LCGC NA 2012; 30(8):620.

2.McNally ME. Analysis of the State of the Art: Sample Preparation. LCGC NA 2012; 30(8):648-651.

2. Regnier FE. Plates vs Selectivity: An Emerging Issue with Complex Samples.  LCGC NA 2012; 30(8):622.

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A Protease for ‘Middle-down’ Proteomics

Author and Reporter: Ritu Saxena, Ph.D.

Neil Kelleher and his research team at Northwestern University have developed a method for enzymatic proteolysis large peptides for mass spectrometry–based proteomics using a protease OmpT. The method was published in a recent issue of the journal Nature. http://www.ncbi.nlm.nih.gov/pubmed/22706673

Proteomics is defined as the study of the structure and function of proteins. Proteomic technologies will play an important role in drug discovery, diagnostics and molecular medicine because is the link between genes, proteins and disease. As researchers study defective proteins that cause particular diseases, their findings will help develop new drugs that either alter the shape of a defective protein or mimic a missing one. http://www.ama-assn.org/ama/pub/physician-resources/medical-science/genetics-molecular-medicine/current-topics/proteomics.page Proteomics, although refers to the study of the structure and function of proteins, it is often specifically used for protein purification and mass spectrometry.

‘Bottom-up’ and ‘Top-down’ are the two main strategies for proteomic studies using mass spectrometry. In Bottom-up proteomics referred to as the more common method, proteins are broken down into smaller pieces through enzymatic digestion followed by characterization into amino acid sequences and post translational modifications prior to analysis by mass spectrometry. By identifying and sequencing these smaller pieces, researchers can then determine the identity of the protein they make up. In Top-down proteomics, on the other hand, the process of proteolysis is skipped and it focuses on complete characterization of intact proteins and their post-translational modifications (PTMs).

“Although both the top-down and bottom-up approaches continue to mature, they each have limitations. The tryptic peptides used in the bottom-up approach are the primary unit of measurement, but their relatively small size (typically ~8–25 residues long) leads to problems such as sample complex­ity, difficulties in assigning peptides to specific gene products rather than protein groups, and loss of single and combinato­rial PTM information. The top-down approach handles these issues by characterizing intact proteins, but its success declines in the high-mass region. Therefore, a hybrid approach based on 2–20 kDa peptides could unite positive aspects of both bottom-up and top-down proteomics” says Kelleher et al in the research article.

The hybrid approach, referred to as ‘middle-down’ proteomics would enable the analysis of complex mixtures pre-sorted by protein size. Previously research efforts ‘middle-down’ proteomics included exploring the restricted proteolysis with enzyme alternatives to Trypsin and chemical methods (such as microwave-assisted acid hydrolysis), However, these methods generated peptides that were marginally longer than those produced by trypsin digestion. For the current study, Kelleher adds “We established an OmpT-based middle-down platform to analyze complex mixtures pre-sorted by protein size. After inte­grating the data from the middle-down workflow that was applied to ~20–100-kDa proteins fractionated from the HeLa cell proteome, we identified 3,697 unique peptides (average size: 6.3 kDa) from 1,038 unique proteins (26% average sequence coverage) at an esti­mated 1% false discovery rate”.

OmpT, a protease derived from Escherichia coli K12 outer membrane belongs to the novel omptin protease family10 and is known to cleave between two consecutive basic amino acid residues (Lys/Arg-Lys/Arg). The authors developed OmpT into an efficient rea­gent to generate >2-kDa peptides for middle-down proteomics, thus, utilizing OmpT to achieve robust, yet restricted, proteolysis of a complex genome. http://www.ncbi.nlm.nih.gov/pubmed/22706673

Researcher Kelleher and his team have been in news earlier for their work on ‘top-down’ proteomics when his team developed a new method that could separate and identify thousands of protein molecules quickly. In the first large-scale demonstration of the top-down method, the researchers were able to identify more than 3,000 protein forms created from 1,043 genes from human HeLa cells. The study was published in last year in the October issue of the journal Nature. http://www.ncbi.nlm.nih.gov/pubmed?term=22037311

Thus, Kelleher and his group was able to demonstrate that OmpT-based proteomic approach has a robust and restricted proteolysis capacity making it an attractive option for mass-spectrometry-based analysis of primary structure of protein.

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