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Posts Tagged ‘Cancer Genomics’

War on Cancer Needs to Refocus to Stay Ahead of Disease Says Cancer Expert


War on Cancer Needs to Refocus to Stay Ahead of Disease Says Cancer Expert

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

Is one of the world’s most prominent cancer researchers throwing in the towel on the War On Cancer? Not throwing in the towel, just reminding us that cancer is more complex than just a genetic disease, and in the process, giving kudos to those researchers who focus on non-genetic aspects of the disease (see Dr. Larry Bernstein’s article Is the Warburg Effect the Cause or the Effect of Cancer: A 21st Century View?).

 

National Public Radio (NPR) has been conducting an interview series with MIT cancer biology pioneer, founding member of the Whitehead Institute for Biomedical Research, and National Academy of Science member and National Medal of Science awardee Robert A. Weinberg, Ph.D., who co-discovered one of the first human oncogenes (Ras)[1], isolation of first tumor suppressor (Rb)[2], and first (with Dr. Bill Hahn) proved that cells could become tumorigenic after discrete genetic lesions[3].   In the latest NPR piece, Why The War On Cancer Hasn’t Been Won (seen on NPR’s blog by Richard Harris), Dr. Weinberg discusses a comment in an essay he wrote in the journal Cell[4], basically that, in recent years, cancer research may have focused too much on the genetic basis of cancer at the expense of multifaceted etiology of cancer, including the roles of metabolism, immunity, and physiology. Cancer is the second most cause of medically related deaths in the developed world. However, concerted efforts among most developed nations to eradicate the disease, such as increased government funding for cancer research and a mandated ‘war on cancer’ in the mid 70’s has translated into remarkable improvements in diagnosis, early detection, and cancer survival rates for many individual cancer. For example, survival rate for breast and colon cancer have improved dramatically over the last 40 years. In the UK, overall median survival times have improved from one year in 1972 to 5.8 years for patients diagnosed in 2007. In the US, the overall 5 year survival improved from 50% for all adult cancers and 62% for childhood cancer in 1972 to 68% and childhood cancer rate improved to 82% in 2007. However, for some cancers, including lung, brain, pancreatic and ovarian cancer, there has been little improvement in survival rates since the “war on cancer” has started.

(Other NPR interviews with Dr. Weinberg include How Does Cancer Spread Through The Body?)

As Weinberg said, in the 1950s, medical researchers saw cancer as “an extremely complicated process that needed to be described in hundreds, if not thousands of different ways,”. Then scientists tried to find a unifying principle, first focusing on viruses as the cause of cancer (for example rous sarcoma virus and read Dr. Gallo’s book on his early research on cancer, virology, and HIV in Virus Hunting: AIDS, Cancer & the Human Retrovirus: A Story of Scientific Discovery).

However (as the blog article goes on) “that idea was replaced by the notion that cancer is all about wayward genes.”

“The thought, at least in the early 1980s, was that were a small number of these mutant, cancer-causing oncogenes, and therefore that one could understand a whole disparate group of cancers simply by studying these mutant genes that seemed to be present in many of them,” Weinberg says. “And this gave the notion, the illusion over the ensuing years, that we would be able to understand the laws of cancer formation the way we understand, with some simplicity, the laws of physics, for example.”

According to Weinberg, this gene-directed unifying theory has given way as recent evidences point back once again to a multi-faceted view of cancer etiology.

But this is not a revolutionary or conflicting idea for Dr. Weinberg, being a recipient of the 2007 Otto Warburg Medal and focusing his latest research on complex systems such as angiogenesis, cell migration, and epithelial-stromal interactions.

In fact, it was both Dr. Weinberg and Dr. Bill Hanahan who formulated eight governing principles or Hallmarks of cancer:

  1. Maintaining Proliferative Signals
  2. Avoiding Immune Destruction
  3. Evading Growth Suppressors
  4. Resisting Cell Death
  5. Becoming Immortal
  6. Angiogenesis
  7. Deregulating Cellular Energy
  8. Activating Invasion and Metastasis

Taken together, these hallmarks represent the common features that tumors have, and may involve genetic or non-genetic (epigenetic) lesions … a multi-modal view of cancer that spans over time and across disciplines. As reviewed by both Dr. Larry Bernstein and me in the e-book Volume One: Cancer Biology and Genomics for Disease Diagnosis, each scientific discipline, whether the pharmacologist, toxicologist, virologist, molecular biologist, physiologist, or cell biologist has contributed greatly to our total understanding of this disease, each from their own unique perspective based on their discipline. This leads to a “multi-modal” view on cancer etiology and diagnosis, treatment. Many of the improvements in survival rates are a direct result of the massive increase in the knowledge of tumor biology obtained through ardent basic research. Breakthrough discoveries regarding oncogenes, cancer cell signaling, survival, and regulated death mechanisms, tumor immunology, genetics and molecular biology, biomarker research, and now nanotechnology and imaging, have directly led to the advances we now we in early detection, chemotherapy, personalized medicine, as well as new therapeutic modalities such as cancer vaccines and immunotherapies and combination chemotherapies. Molecular and personalized therapies such as trastuzumab and aromatase inhibitors for breast cancer, imatnib for CML and GIST related tumors, bevacizumab for advanced colorectal cancer have been a direct result of molecular discoveries into the nature of cancer. This then leads to an interesting question (one to be tackled in another post):

Would shifting focus less on cancer genome and back to cancer biology limit the progress we’ve made in personalized medicine?

 

In a 2012 post Genomics And Targets For The Treatment Of Cancer: Is Our New World Turning Into “Pharmageddon” Or Are We On The Threshold Of Great Discoveries? Dr. Leonard Lichtenfield, MD, Deputy Chief Medical Officer for the ACS, comments on issues regarding the changes which genomics and personalized strategy has on oncology drug development. As he notes, in the past, chemotherapy development was sort of ‘hit or miss’ and the dream and promise of genomics suggested an era of targeted therapy, where drug development was more ‘rational’ and targets were easily identifiable.

To quote his post

That was the dream, and there have been some successes–even apparent cures or long term control–with the used of targeted medicines with biologic drugs such as Gleevec®, Herceptin® and Avastin®. But I think it is fair to say that the progress and the impact hasn’t been quite what we thought it would be. Cancer has proven a wily foe, and every time we get answers to questions what we usually get are more questions that need more answers. The complexity of the cancer cell is enormous, and its adaptability and the genetic heterogeneity of even primary cancers (as recently reported in a research paper in the New England Journal of Medicine) has been surprising, if not (realistically) unexpected.

                                                                               ”

Indeed the complexity of a given patient’s cancer (especially solid tumors) with regard to its genetic and mutation landscape (heterogeneity) [please see post with interview with Dr. Swanton on tumor heterogeneity] has been at the forefront of many clinicians minds [see comments within the related post as well as notes from recent personalized medicine conferences which were covered live on this site including the PMWC15 and Harvard Personalized Medicine conference this past fall].

In addition, Dr. Lichtenfeld makes some interesting observations including:

  • A “pharmageddon” where drug development risks/costs exceed the reward so drug developers keep their ‘wallets shut’. For example even for targeted therapies it takes $12 billion US to develop a drug versus $2 billion years ago
  • Drugs are still drugs and failure in clinical trials is still a huge risk
  • “Eroom’s Law” (like “Moore’s Law” but opposite effect) – increasing costs with decreasing success
  • Limited market for drugs targeted to a select mutant; what he called “slice and dice”

The pros and cons of focusing solely on targeted therapeutic drug development versus using a systems biology approach was discussed at the 2013 Institute of Medicine’s national Cancer Policy Summit.

  • Andrea Califano, PhD – Precision Medicine predictions based on statistical associations where systems biology predictions based on a physical regulatory model
  • Spyro Mousses, PhD – open biomedical knowledge and private patient data should be combined to form systems oncology clearinghouse to form evolving network, linking drugs, genomic data, and evolving multiscalar models
  • Razelle Kurzrock, MD – What if every patient with metastatic disease is genomically unique? Problem with model of smaller trials (so-called N=1 studies) of genetically similar disease: drugs may not be easily acquired or re-purposed, and greater regulatory burdens

So, discoveries of oncogenes, tumor suppressors, mutant variants, high-end sequencing, and the genomics and bioinformatic era may have led to advent of targeted chemotherapies with genetically well-defined patient populations, a different focus in chemotherapy development

… but as long as we have the conversation open I have no fear of myopia within the field, and multiple viewpoints on origins and therapeutic strategies will continue to develop for years to come.

References

  1. Parada LF, Tabin CJ, Shih C, Weinberg RA: Human EJ bladder carcinoma oncogene is homologue of Harvey sarcoma virus ras gene. Nature 1982, 297(5866):474-478.
  2. Friend SH, Bernards R, Rogelj S, Weinberg RA, Rapaport JM, Albert DM, Dryja TP: A human DNA segment with properties of the gene that predisposes to retinoblastoma and osteosarcoma. Nature 1986, 323(6089):643-646.
  3. Hahn WC, Counter CM, Lundberg AS, Beijersbergen RL, Brooks MW, Weinberg RA: Creation of human tumour cells with defined genetic elements. Nature 1999, 400(6743):464-468.
  4. Weinberg RA: Coming full circle-from endless complexity to simplicity and back again. Cell 2014, 157(1):267-271.

 

Other posts on this site on The War on Cancer and Origins of Cancer include:

 

2013 Perspective on “War on Cancer” on December 23, 1971

Is the Warburg Effect the Cause or the Effect of Cancer: A 21st Century View?

World facing cancer ‘tidal wave’, warns WHO

2013 American Cancer Research Association Award for Outstanding Achievement in Chemistry in Cancer Research: Professor Alexander Levitzki

Genomics and Metabolomics Advances in Cancer

The Changing Economics of Cancer Medicine: Causes for the Vanishing of Independent Oncology Groups in the US

Cancer Research Pioneer, after 71 years of Immunology Lab Research, Herman Eisen, MD, MIT Professor Emeritus of Biology, dies at 96

My Cancer Genome from Vanderbilt University: Matching Tumor Mutations to Therapies & Clinical Trials

Articles on Cancer-Related Topic in http://pharmaceuticalintelligence.com Scientific Journal

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

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

Introduction – The Evolution of Cancer Therapy and Cancer Research: How We Got Here?

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10:15AM 11/13/2014 – 10th Annual Personalized Medicine Conference at the Harvard Medical School, Boston

REAL TIME Coverage of this Conference by Dr. Aviva Lev-Ari, PhD, RN – Director and Founder of LEADERS in PHARMACEUTICAL BUSINESS INTELLIGENCE, Boston http://pharmaceuticalintelligence.com

10:15 a.m. Panel Discussion — IT/Big Data

IT/Big Data

The human genome is composed of 6 billion nucleotides (using the genetic alphabet of T, C, G and A). As the cost of sequencing the human genome is decreasing at a rapid rate, it might not be too far into the future that every human being will be sequenced at least once in their lifetime. The sequence data together with the clinical data are going to be used more and more frequently to make clinical decisions. If that is true, we need to have secure methods of storing, retrieving and analyzing all of these data.  Some people argue that this is a tsunami of data that we are not ready to handle. The panel will discuss the types and volumes of data that are being generated and how to deal with it.

IT/Big Data

   Moderator:

Amy Abernethy, M.D.
Chief Medical Officer, Flatiron

Role of Informatics, SW and HW in PM. Big data and Healthcare

How Lab and Clinics can be connected. Oncologist, Hematologist use labs in clinical setting, Role of IT and Technology in the environment of the Clinicians

Compare Stanford Medical Center and Harvard Medical Center and Duke Medical Center — THREE different models in Healthcare data management

Create novel solutions: Capture the voice of the patient for integration of component: Volume, Veracity, Value

Decisions need to be made in short time frame, documentation added after the fact

No system can be perfect in all aspects

Understanding clinical record for conversion into data bases – keeping quality of data collected

Key Topics

Panelists:

Stephen Eck, M.D., Ph.D.
Vice President, Global Head of Oncology Medical Sciences,
Astellas, Inc.

Small data expert, great advantage to small data. Populations data allows for longitudinal studies,

Big Mac Big Data – Big is Good — Is data been collected suitable for what is it used, is it robust, limitations, of what the data analysis mean

Data analysis in Chemical Libraries – now annotated

Diversity data in NOTED by MDs, nuances are very great, Using Medical Records for building Billing Systems

Cases when the data needed is not known or not available — use data that is available — limits the scope of what Valuable solution can be arrived at

In Clinical Trial: needs of researchers, billing clinicians — in one system

Translation of data on disease to data object

Signal to Noise Problem — Thus Big data provided validity and power

 

J. Michael Gaziano, M.D., M.P.H., F.R.C.P.
Scientific Director, Massachusetts Veterans Epidemiology Research
and Information Center (MAVERIC), VA Boston Healthcare System;
Chief Division of Aging, Brigham and Women’s Hospital;
Professor of Medicine, Harvard Medical School

at BWH since 1987 at 75% – push forward the Genomics Agenda, VA system 25% – VA is horizontally data integrated embed research and knowledge — baseline questionnaire 200,000 phenotypes – questionnaire and Genomics data to be integrated, Data hierarchical way to be curated, Simple phenotypes, validate phenotypes, Probability to have susceptibility for actual disease, Genomics Medicine will benefit Clinicians

Data must be of visible quality, collect data via Telephone VA – on Med compliance study, on Ability to tolerate medication

–>>Annotation assisted in building a tool for Neurologist on Alzheimer’s Disease (AlzSWAN knowledge base) (see also Genotator , a Disease-Agnostic Tool for Annotation)

–>>Curation of data is very different than statistical analysis of Clinical Trial Data

–>>Integration of data at VA and at BWH are tow different models of SUCCESSFUL data integration models, accessing the data is also using a different model

–>>Data extraction from the Big data — an issue

–>>Where the answers are in the data, build algorithms that will pick up causes of disease: Alzheimer’s – very difficult to do

–>>system around all stakeholders: investment in connectivity, moving data, individual silo, HR, FIN, Clinical Research

–>>Biobank data and data quality

 

Krishna Yeshwant, M.D.
General Partner, Google Ventures;
Physician, Brigham and Women’s Hospital

Computer Scientist and Medical Student. Were the technology is going?

Messy situation, interaction IT and HC, Boston and Silicon Valley are focusing on Consumers, Google Engineers interested in developing Medical and HC applications — HUGE interest. Application or Wearable – new companies in this space, from Computer Science world to Medicine – Enterprise level – EMR or Consumer level – Wearable — both areas are very active in Silicon Valley

IT stuff in the hospital HARDER that IT in any other environment, great progress in last 5 years, security of data, privacy. Sequencing data cost of big data management with highest security

Constrained data vs non-constrained data

Opportunities for Government cooperation as a Lead needed for standardization of data objects

 

Questions from the Podium:

  • Where is the Truth: do we have all the tools or we don’t for Genomic data usage
  • Question on Interoperability
  • Big Valuable data — vs Big data
  • quality, uniform, large cohort, comprehensive Cancer Centers
  • Volume of data can compensate quality of data
  • Data from Imaging – Quality and interpretation – THREE radiologist will read cancer screening

 

 

 

– See more at: http://personalizedmedicine.partners.org/Education/Personalized-Medicine-Conference/Program.aspx#sthash.qGbGZXXf.dpuf

 

@HarvardPMConf

#PMConf

@SachsAssociates

@Duke_Medicine

@AstellasUS

@GoogleVentures

@harvardmed

@BrighamWomens

@kyeshwant

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4:00PM 11/12/2014 – 10th Annual Personalized Medicine Conference at the Harvard Medical School, Boston

REAL TIME Coverage of this Conference by Dr. Aviva Lev-Ari, PhD, RN – Director and Founder of LEADERS in PHARMACEUTICAL BUSINESS INTELLIGENCE, Boston http://pharmaceuticalintelligence.com

4:00 p.m. Panel Discussion Novel Approaches to Personalized Medicine

Novel Approaches to Personalized Medicine

Genetic and genomic knowledge is helping the development of new drugs, therapies and prognostic tests. As a result, there are new approaches, new partnerships and new business models that are emerging. In some cases, diseases that were considered incurable not too long ago are now being tackled with highly targeted therapies. In other cases the uncertainties associated with assessing potential aggressiveness of disease are being eliminated. This panel will provide examples of new business paradigms that are emerging from the application of personalized medicine.

Novel Approaches to Personalized Medicine

Moderator:

Meghan FitzGerald, Ph.D. @cardinalhealth
President, Cardinal Health Specialty Solutions

Chief Genome Officer – next steps in companies, Genomics Index will replace the Biotech Index

Most Interesting person in Genomics: Marc Levin,

Panelists:

2. Chris Garabedian @Sarepta
President and CEO, Sarepta

  • Applications of genomics to Infectious diseases, therapeutics – design of drugs, Duchenne Muscular Dystrophy (DMD)
  • technology safe working, one drug very effective, 60 alternative drugs, not enough patients to power clinical trials

 

4. Shawn Marcell
President & CEO, Metamark Genetics

  • Prostatic Cancer – Use of genomics tools to diagnose and treat Prostate cancer
  • US market is the best for Genomics innovations because venture capital Market is mature, FDA is negotiable, CMP well established
  • Business model: platform, good test big market, commercialize, clinical data — PM has a different Business model: Delivery of Test results need to be different
  • IPO 2016

 

1. Scott Schell, M.D., Ph.D. – surgical oncology @KEWGroup
President and CEO, KEW Group

  • Large scale platform, strategic partnerships with Oncology Practices,
  • Immuno oncologists, repository of data
  • 80% of cancers are treated in the community 20% at Academic centers. Integration of knowledge, patients wish to stay in the community
  • phase I approval at record high levels

3. Gabriel Bien-Willner, M.D., Ph.D. @MolecularHealth
Medical Director, MolecularHealth, Inc.

  • Diagnostics Tools in Analytics. Clinicians do not have the training in Genomics – position firm to create Lab reports and consulting MDs using Analytics for Clinicians

 

 

– See more at: http://personalizedmedicine.partners.org/Education/Personalized-Medicine-Conference/Program.aspx#sthash.qGbGZXXf.dpuf

@HarvardPMConf

#PMConf

@SachsAssociates

@cardinalhealth

@Sarepta

@KEWGroup

@MolecularHealth

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9:20AM 11/12/2014 – 10th Annual Personalized Medicine Conference at the Harvard Medical School, Boston

REAL TIME Coverage of this Conference by Dr. Aviva Lev-Ari, PhD, RN – Director and Founder of LEADERS in PHARMACEUTICAL BUSINESS INTELLIGENCE, Boston http://pharmaceuticalintelligence.com

9:20 a.m. Panel Discussion – Genomic Technologies

Genomic Technologies

The greatest impetus for personalized medicine is the initial sequencing of the human genome at the beginning of this Century. As we began to recognize the importance of genetic factors in human health and disease, efforts to understand genetic variation and its impact on health have accelerated. It was estimated that it cost more than two billion dollars to sequence the first human genome and reduction in the cost of sequence became an imperative to apply this technology to many facets of risk assessment, diagnosis, prognosis and therapeutic intervention. This panel will take a brief historical look back at how the technologies have evolved over the last 15 years and what the future holds and how these technologies are being applied to patient care.

Genomic Technologies

Opening Speaker and Moderator:

George Church, Ph.D.
Professor of Genetics, Harvard Medical School; Director, Personal Genomics

Genomic Technologies and Sequencing

  • highly predictive, preventative
  • non predictive

Shareable Human Genomes Omics Standards

$800 Human Genome Sequence – Moore’s Law does not account for the rapid decrease in cost of Genome Sequencing

Genome Technologies and Applications

  • Genia nanopore – battery operated device
  • RNA & protein traffic
  • Molecular Stratification Methods – more than one read, sequence ties
  • Brain Atlas  – transcriptome of mouse brains
  • Multigenics – 700 genes: hGH therapies

Therapies

  • vaccine
  • hygiene
  • age

~1970 Gene Therapy in Clinical Trials

Is Omic technologies — a Commodity?

  • Some practices will have protocols
  • other will never become a commodity

 

Panelists:

Sam Hanash, M.D., Ph.D. @MDAndersonNews

Director, Red & Charline McCombs Institute for Early Detection & Treatment of Cancer MD Anderson Cancer Center

Heterogeneity among Cancer cells. Data analysis and interpretation is very difficult, back up technology

Proteins and Peptides before analysis with spectrometry:

  • PM  – Immunotherapy approaches need be combined with other techniques
  • How modification in protein type affects disease
  • amplification of an aberrant protein – when that happens cancer developed. Modeling on a CHip of peptide synthesizer

Mark Stevenson @servingscience

Executive Vice President and President, Life Sciences Solutions
Thermo Fisher Scientific

Issues of a Diagnostics Developer:

  • FDA regulation, need to test on several tissues
  • computational environment
  • PCR, qPCR – cost effective
  • BGI – competitiveness

Robert Green, MD @BrighamWomens

Partners, Health Care Personalized Medicine — >>Disclosure: Illumina and three Pharmas

Innovative Clinical Trial: Alzheimer’s Disease, integration of sequencing with drug development

  • Population based screening with diagnosis
  • Cancer predisposition: Cost, Value, BRCA
  • epigenomics technologies to be integrated
  • Real-time diagnostics
  • Screening makes assumption on Predisposition
  • Public Health view: Phenotypes in the Framingham Studies: 64% pathogenic genes were prevalent – complication based in sequencing.

Questions from the Podium:

  • Variants analysis
  • Metastasis different than solid tumor itself – Genomics will not answer issues related to tumor in special tissues variability

 

 

 

 

– See more at: http://personalizedmedicine.partners.org/Education/Personalized-Medicine-Conference/Program.aspx#sthash.qGbGZXXf.dpuf

@HarvardPMConf

#PMConf

@SachsAssociates

 

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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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