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Zebrafish—Susceptible to Cancer

Posted in CANCER BIOLOGY & Innovations in Cancer Therapy, Cell Biology, Signaling & Cell Circuits, Genome Biology, Genomic Testing: Methodology for Diagnosis, Molecular Genetics & Pharmaceutical, Pharmaceutical Industry Competitive Intelligence, Technology Transfer: Biotech and Pharmaceutical, tagged Biology, Cancer - General, Developmental biology, genetics, PubMed, research, University of Brescia, Zebrafish on April 2, 2013| Leave a Comment »

Zebrafish—Susceptible to Cancer

Reporter: Larry H Bernstein, MD, FCAP

Word Cloud By Danielle Smolyar

Models of Transparency

Researchers are taking advantage of small, transparent zebrafish embryos and larvae—and a special strain of see-through adults—to understand the development and spread of cancer.

By Joan K. Heath, David Langenau, Kirsten C. Sadler, and Richard White | April 1, 2013

http://www.the-scientist.com/images/April2013/zebrafish.jpg

LOOKING INSIDE DISEASE: The wild-type zebrafish larva on the left is stained for the two neuronal proteins (green) and membrane-trafficking proteins expressed near synapses (blue). On the right, the neurons of a transgenic zebrafish larva produce the dementia-associated Tau protein (red), a disease-specific form of which is stained in blue. Tubulin is stained in green.

COURTESY OF DOMINIK PAQUET, THE ROCKEFELLER UNIVERSITY, NEW YORK, USA

From frogs to dogs and people, cancer wreaks havoc across the animal kingdom—and fish are no exception. Coral trout, for example, develop melanoma from overexposure to sun, just as humans do. Rainbow trout develop liver cancer in response to environmental toxins. And zebrafish—small, striped fish indigenous to the rivers of India and a widely used model organism—are susceptible to both malignant and benign tumors of the brain, nervous system, blood, liver, pancreas, skin, muscle, and intestine.

Importantly, tumors that arise in the same organs in humans and fish look and behave alike, and the cancers often share common genetic underpinnings. As a result, most researchers believe that the basic mechanisms underlying tumor formation are conserved across species, allowing them to study the formation, expansion, and spread of tumors in animal models with the hope of eventually finding new insights into cancer in people.

Zebrafish are an increasingly popular choice among cancer biologists. Between 1995 and 2012, there was a 10-fold increase in the number of yearly PubMed citations of cancer studies in the species, with more than 200 research papers published last year.  Although dwarfed by cancer studies using human tissue and mouse models, the optical transparency of zebrafish embryos and larvae—and now, adult fish of a recently created strain—allows researchers to track tumors in a way that is not possible in other vertebrate models. Furthermore, their small size—embryos are small enough to be reared in 96-well plates—make them a more practical laboratory system than other cancer models. Indeed, researchers are now using these fish to identify druggable oncogenic drivers of specific tumor types, to tease apart the complex network of cancer genes that cooperate in tumor formation and progression, to probe the interplay between the genes that govern embryonic development and those that cause cancer, and to uncover how tumors metastasize and kill their host. The zebrafish model offers a major opportunity to discover important pathways underlying cancer and to identify novel therapies in high-throughput drug screens in a way that mice never could.

The zebrafish toolbox

Zebrafish (Danio rerio) have fast made their way from pet stores and home aquaria into research laboratories worldwide. Their weekly matings produce 100 to 200 embryos that rapidly and synchronously march through embryonic development, so that within 5 days of fertilization, they are mature, feeding larvae. Zebrafish are small and inexpensive to maintain in high numbers, facilitating large-scale experimentation and cheap in vivo drug screens. Famously, the fish are transparent during early larval stages, allowing investigators to directly observe internal development and making the fish a favorite of developmental biologists since the 1960s. But in recent years, the utility of zebrafish has been proven beyond developmental fields, and they are now being found in more and more laboratories studying behavior, diabetes, heart disease, regeneration, stem cell biology—and cancer.

Critically, zebrafish can be used to identify the important pathways and processes that cause cancer in people. Common organ systems and cell types are shared between human and zebrafish, and whether induced by transgenesis or carcinogens, cancers arising from the blood (leukemia and lymphoma), pigmented cells of the skin (melanoma), and the cells that line the bile ducts (cholangiocarcinoma) have microscopic features that are essentially indistinguishable between humans and zebrafish.

The zebrafish model offers a major opportunity to discover important pathways underlying cancer and to identify novel therapies in high-throughput drug screens, in a way that mice never could.

Comparing gene-expression profiles of tumors across various species provides a powerful mechanism for identifying genes that likely represent core functions of cancer. For example, microarray gene-expression analyses have compared the gene signatures of fish hepatocellular carcinoma to that of human liver, gastric, prostate, and lung tumors. Remarkably, this analysis revealed that fish and human liver tumors are more similar to each other than either tumor type is to human tumors derived from different tissues. Moreover, comparative studies can often be used to pinpoint pathways that are active in human disease. This is illustrated by work on a zebrafish model of rhabdomyosarcoma (RMS), a cancer of skeletal muscle, which revealed a gene signature that is also commonly found in human RMS, highlighting the importance of the RAS signaling pathway in the genesis of human RMS.1

A window into cancer

In 2003, the laboratory of A. Thomas Look at Children’s Hospital Boston was the first to realize the long-held dream of following the behavior of cancer cells as they initiate tumor growth and invade structures within live animals. Specifically, the researchers engineered leukemia-afflicted T cells to express green fluorescent protein (GFP) and visualized cancer onset within the zebrafish thymus.2 Moreover, these GFP-positive tumor cells were transplantable into recipient fish, a hallmark of the malignant cell type. Following up on this work, several researchers have now begun transplanting fluorescently labeled human cancer cells into zebrafish larvae to visualize tumor growth and spread in a manner not achievable in more common mouse xenograft models.

Capitalizing on the lack of an acquired immune system during larval stages and the ability to rear zebrafish at temperatures that mimic the human core temperature, Stefania Nicoli of the University of Brescia in Italy and colleagues implanted human cancer cells expressing high levels of vascular endothelial growth factor (VEGF) into zebrafish larvae with GFP-labeled blood vessels.3 VEGF is a factor commonly produced by growing cancers and is responsible for coaxing blood vessels to invade the developing tumor. Nicoli’s work allowed the direct visualization of vasculature remodeling and new vessel formation—and showed that it could be blocked by the addition of VEGF-inhibitory drugs to the water in which the larvae lived. Using similar approaches, many laboratories have successfully engrafted human cancer cells from a range of tumor types into zebrafish embryos.

Researchers have also used zebrafish to visualize the role of tumor heterogeneity within cancer over time. Work from one of our labs (David Langenau’s) has utilized a model of RAS-induced RMS to fluorescently label tumor cells based on differentiation status. This allowed the team to watch the never-before-visualized birth of cancer—the acquisition of invasive properties by normal muscle stem cells and the breakdown of normal muscle architecture, clearing the way for continued tumor expansion. The researchers also characterized two molecularly distinct cell populations, one that is responsible for tumor growth and another that drives cancer spread or metastasis. (See photos below—Imaging Blood Cancers; Solid Tumor Development.)

http://www.the-scientist.com/images/April2013/zebrafish_new.jpg

SEE-THROUGH SUBJECTS: Zebrafish embryos (bottom right), shown here at 28 hours, are naturally transparent, as are zebrafish larvae (bottom left) until around 3 weeks of age. A new strain of zebrafish, called casper, maintains its transparency into adulthood (top right), allowing researchers to observe cancer formation in adult fish. A wall of tanks (top left) at the Zebrafish Resource Center, Karlsruhe Institute of Technology.

CLOCKWISE FROM TOP: © MARTIN LOBER; COURTESY OF RICHARD WHITE; COURTESY OF GRAHAM SCOTT; COURTESY OF KIRSTEN EDEPLI

T-cell leukemia and RMS are pediatric diseases, favoring cancer development in early larval stages of these zebrafish models. However, cancer is predominantly a disease that affects adults, and zebrafish lose their transparency at around 3 weeks of age. To visualize tumor formation in older zebrafish, one of us (Richard White) and Len Zon of Children’s Hospital Boston have developed a strain of zebrafish called casper, which lacks pigment and is optically clear into adulthood.4 (See photo here.) Using these animals, investigators have implanted pigmented melanomas and witnessed local spread and metastasis over time. First described in 2008, casper is now the zebrafish strain of choice for imaging studies in the field.

Zebrafish have truly proven to be ideal organisms for visualizing cancer; there is no other animal system that allows researchers to literally watch tumors grow and spread. Because we can follow cells as they escape from the primary tumor, migrate, and form metastases in a variety of organs, zebrafish provide an unsurpassed model to describe the distinct steps of cancer progression, and researchers using this model are already contributing much to our understanding of cancer.

 Screening for drugs

In terms of drug discovery, zebrafish have emerged as the only vertebrate organism amenable to high-throughput and high-content chemical screening in vivo. The small size of freshly hatched zebrafish embryos means that up to 20 embryos can be dispensed into the individual wells of a 96-well plate, thereby providing a platform for the robotic delivery and testing of hundreds or thousands of compounds in living animals. Because of the parallels between embryonic development and cancer, compounds producing changes in the growth or proliferation of developing organs may also be relevant to cancer. However, to more directly search for small molecules capable of putting the brakes on cancerous growth, researchers are turning to several established tumor-prone zebrafish lines.

One prominent success from such endeavors is the identification of a drug to treat melanoma. Like human melanoma skin lesions, zebrafish melanomas exhibit a gene-expression signature characteristic of the embryonic neural crest, a multipotent group of stem cells that give rise to dozens of cell types, including pigmented skin cells called melanocytes. The genes in this signature, including sox10 and mitf, were hypothesized to be important for melanoma growth, so in 2011 White and Zon performed an in vivo screen to identify small molecules that suppressed the expression of these neural crest genes in developing embryos.5 After screening 2,000 molecules, they identified leflunomide, an approved treatment for rheumatoid arthritis. Importantly, leflunomide was then found to inhibit the growth of both zebrafish and human melanoma xenografts in vivo, and the drug moved from discovery to Phase 1/2 trials in only 4 years, demonstrating just how quickly discoveries in zebrafish can have clinical impact. Similar efforts to discover novel modulators of leukemia growth have recently been reported to work in both fish and humans, suggesting that this approach will be broadly applicable to a wide range of solid and liquid tumors.

Probing the cancer genome

The genesis of cancer generally depends on the inactivation of one or more tumor suppressor genes in conjunction with signaling from oncogenes. Indeed, rapid advances in sequencing technologies and efforts such as The Cancer Genome Atlas (TCGA) have revealed surprisingly few “driver” mutations capable of causing cancer alone. Instead, TCGA and other sequencing studies have identified vast genetic heterogeneity both across and within tumor types, with mutations extending well beyond genes likely to represent classical oncogenes or tumor suppressor genes. How these mutations influence tumor growth remains a major unanswered question in cancer biology.

http://www.the-scientist.com/images/April2013/fish.jpg

IMAGING BLOOD CANCERS: Developing T lymphocytes in the thymus of a transgenic zebrafish (top right) express green fluorescent protein (GFP). A transgenic zebrafish (bottom right) that coexpresses the Myc oncogene with GFP shows signs of prominent leukemia, which has spread well beyond the boundaries of the thymus (T).

COURTESY OF DAVID LANGENAU

Enter zebrafish, and a range of high-throughput reverse-genetic techniques for cancer gene discovery. By transiently overexpressing each of 30 candidate genes in zebrafish larvae, for example, Craig Ceol and Yariv Houvras in Zon’s group identified a single cooperating oncogene, SETDB1, as a new player in melanoma.6 In this study, the researchers created and analyzed more than 3,000 transgenic animals. Because they used a transposon-based transgenic approach that leads to high-level, uniform expression, they could directly assess how the injected genes affected tumor onset without going through the lengthy process of germline transgenics, a major bottleneck in mouse genetics. This rapid screening approach is a prime example of how the mountains of data generated by TCGA can be quickly assessed for biological function, and zebrafish are the only in vivo whole-animal vertebrate system that enables researchers to rapidly sift through these data to understand which mutations drive cancer.

Other new approaches are advancing loss-of-function analyses. Until recently, such studies relied on TiLLING (targeting induced local lesions in genomes), in which a chemical carcinogen, ethylnitrosourea (ENU), introduces point mutations throughout the genome and high-throughput methods then look for mutations in genes of interest. This method yielded several valuable strains of tumor-prone zebrafish harboring clinically relevant mutations in the well-known tumor-suppressor genes p53, apc, and pten, and these have been pivotal to the development of multiple zebrafish cancer models. However, the unbiased nature of ENU mutagenesis makes TiLLING a labor-intensive and impractical business in most laboratory settings. Instead, precision editing of the genome has emerged as the method of choice for the systematic creation of knockout and mutant animals. Specifically, homology-based editing, using TALENs (transcription activator–like effector nucleases) and, more recently, CRISPR (clustered regularly interspaced short palindromic repeats)/Cas systems, has revolutionized the field.7,8 Using relatively simple procedures, virtually any gene can now be mutated in zebrafish, allowing for very large-scale, in vivo assessments of novel cancer genes and the analysis of interacting mutations—one of the greatest challenges facing the cancer field in the coming decade.

http://www.the-scientist.com/images/April2013/fish-magnified.jpg

SOLID TUMOR DEVELOPMENT: A transgenic zebrafish (bottom left) with fluorescent-labeled RAS-induced rhabdomyosacoma. Green fluorescent protein is expressed in the tumor-propagating cells, which drive continued tumor growth. Red fluorescent protein is localized to the nucleus and expressed in myoblast-like cells, while blue fluorescent protein is confined to terminally differentiated cancer cells that express myosin (magnified image, bottom right). Live-cell imaging permits dynamic visualization of the birth of cancer and the functional consequences of tumor cell heterogeneity within established tumors.

COURTESY OF DAVID LANGENAU

To complement approaches that directly inactivate genes within the genome, strategies to achieve interference RNA-mediated gene silencing in zebrafish have come of age as well. Expression of short hairpin RNAs, for example, have produced stable and tissue-specific knockdown in cancer-related genes such as chordin and wnt5b.9,10 Because of the ease of manipulating the genome as well as the large number of well-characterized zebrafish gene promoters, such strategies immediately afford the opportunity to knockdown known gene functions in a tissue-specific fashion, and it is likely that temporal control will be readily achievable as well.

In all, combining the descriptive data from TCGA with zebrafish transgenesis, high-throughput overexpression and knockout techniques, and unbiased genetic screens offers an unprecedented opportunity to functionally probe the cancer genome.

The future of the field

Given its power for imaging, transplantation, small-molecule screens, and high-throughput transgenesis, the zebrafish model should become a major platform for deeply interrogating cancer biology in vivo over the next decade. One major area where zebrafish are particularly valuable is in teasing apart the extreme complexity of cancer. Because combinations of genetic pathways can be assessed simultaneously, potentially dozens of genomic alterations found in human cancer could be tested for their effects in the fish, allowing us to sort biologically meaningful alterations from neutral ones. These techniques will also allow us to understand how numerous small changes, which on their own have little phenotypic effect, can combine to cause cancer.

The success of the field will depend upon improved funding for zebrafish cancer research, however. Currently, only a small fraction of National Institutes of Health RO1 grants for cancer research are awarded for zebrafish studies, with the vast majority going to work in mice, humans, and human cells. Consortium efforts analogous to the Mouse Model Consortium will be necessary to develop more faithful zebrafish models of human cancer, which can then be used as the basis for further screens. Whereas mouse models of cancer have delivered great insights into the biological mechanisms underlying human malignancy, we view zebrafish models as a springboard for the rapid launch of unbiased genetic and chemical screens.

With any cancer model, bridging the gap between the animals and human patients is the ultimate proof of its utility. For the zebrafish, this can occur not only through bringing drugs to the clinic, but also in the development of novel biomarkers and early detection methods. The next 10 years will be an exciting time, and we have great confidence that the zebrafish will contribute major discoveries to the treatment of human cancers.

Joan K. Heath is an associate professor in the ACRF Chemical Biology Division at the Walter and Eliza Hall Institute of Medical Research and the Department of Medical Biology at the University of  Melbourne, Australia, where her laboratory is studying the genetic regulation of  intestinal organogenesis and colorectal cancer.

David Langenau, an assistant professor of pathology at Harvard Medical School, studies the mechanisms that drive pediatric cancer relapse within the Molecular Pathology Unit and the Cancer Center at Massachusetts General Hospital.

Kirsten C. Sadler is an assistant professor in the Division of Liver Diseases/Department of Medicine and in Developmental and Regenerative Biology at the Icahn School of Medicine at Mount Sinai in New York City, where she studies the mechanisms of liver development, regeneration, and cancer.

Richard White is an assistant professor at the Memorial Sloan-Kettering Cancer Center and Weill Cornell Medical College in New York City. His laboratory studies the evolutionary mechanisms by which tumors develop the capacity for metastasis.

References

D.M. Langenau et al., “Effects of RAS on the genesis of embryonal rhabdomyosarcoma,” Genes Dev, 21:1382-95, 2007.

D.M. Langenau et al., “Myc-induced T cell leukemia in transgenic zebrafish,” Science, 299:887-90, 2003.

S. Nicoli et al., “Mammalian tumor xenografts induce neovascularization in zebrafish embryos,” Cancer Res, 67:2927-31, 2007.

R.M. White et al., “Transparent adult zebrafish as a tool for in vivo transplantation analysis,” Cell Stem Cell, 2:183-89, 2008.

R.M. White et al., “DHODH modulates transcriptional elongation in the neural crest and melanoma,” Nature, 471:518-22, 2011.

C.J. Ceol et al., “The histone methyltransferase SETDB1 is recurrently amplified in melanoma and accelerates its onset,” Nature, 471:513-17, 2011.

V.M. Bedell et al., “In vivo genome editing using a high-efficiency TALEN system,” Nature, 491:114-18, 2012.

W.Y. Hwang et al., “Efficient genome editing in zebrafish using a CRISPR-Cas system,” Nat Biotechnol, doi: 10.1038/nbt.2501, 2013.

M. Dong et al., “Heritable and lineage-specific gene knockdown in zebrafish embryo,” PLOS ONE, 4:e6125, 2009.

G. De Rienzo et al., “Efficient shRNA-mediated inhibition of gene expression in zebrafish,” Zebrafish, 9:97-107, 2012.

Tags

zebrafish, model organisms, cancer therapetics, cancer research, cancer genomics, cancer gene expression, cancer and animal models

Danio rerio, better known as the zebrafish (Photo credit: Wikipedia)

Zebrafish embryo development (Photo credit: Carl Zeiss Microscopy)

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• An activity map of the whole zebrafish brain | Mo Costandi (guardian.co.uk)
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English: zebrafish (Danio rerio) ovary oocyte maturation (Photo credit: Wikipedia)

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AMPK Is a Negative Regulator of the Warburg Effect and Suppresses Tumor Growth In Vivo

Posted in Biological Networks, Gene Regulation and Evolution, BioSimilars, CANCER BIOLOGY & Innovations in Cancer Therapy, Cell Biology, Signaling & Cell Circuits, Chemical Biology and its relations to Metabolic Disease, Chemical Genetics, Disease Biology, Small Molecules in Development of Therapeutic Drugs, Genome Biology, Health Economics and Outcomes Research, Metabolomics, Molecular Genetics & Pharmaceutical, Nutrigenomics, Personalized and Precision Medicine & Genomic Research, tagged Allosteric regulation, AMP-activated protein kinase, AMPK, Aviva Lev-Ari, Biology, Cancer - General, Cell Biology, cell proliferation, cellular metabolism, cellular stress, Chemotherapy, DNA, gene expression, genetics, health, medicine, Metabolism, mutation, Myc, redox, research, RNA, Stem cell, tumor response, tumor suppressor, Warburg, Warburg Effect on March 12, 2013| 5 Comments »

AMPK Is a Negative Regulator of the Warburg Effect and Suppresses Tumor Growth In Vivo

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

Word Cloud by Daniel Menzin

There has been a causal link between alterations in cellular metabolism and the cancer phenotype.  Reorganization of cellular metabolism, marked by a shift from oxidative phosphorylation to aerobic glycolysis for cellular energy requirements (Warburg effect), is considered a hallmark of the transformed cell.  In addition, if tumors are to survive and grow, cancer cells need to adapt to environments high in metabolic stress and to avoid programmed cell death (apoptosis). Recently, a link between cancer growth and metabolism has been supported by the discovery that the LKB1/AMPK signaling pathway as a tumor suppressor axis[1].

LKB1/AMPK/mTOR Signaling Pathway

The Liver Kinase B1 (LKB1)/AMPK  AMP-activated protein kinase/mammalian Target of Rapamycin Complex 1 (mTORC1) signaling pathway links cellular metabolism and energy status to pathways involved in cell growth, proliferation, adaption to energy stress, and autophagy.  LKB1 is a master control for 14 other kinases including AMPK, a serine-threonine kinase which senses cellular AMP/ATP ratios.  In response to cellular starvation, AMPK is allosterically activated by AMP, leading to activation of ATP-generating pathways like fatty acid oxidation and blocking anabolic pathways, like lipid and cholesterol synthesis (which consume ATP).  In addition, AMPK regulates cell growth, proliferation, and autophagy by regulating the mTOR pathway.  AMPK activates the tuberous sclerosis complex 1/2, which ultimately inhibits mTORC1 activity and inhibits protein translation.  This mTOR activity is dis-regulated in many cancers.

LKB1/AMPK in Cancer

• Somatic mutations of the STK11 gene encoding LKB1 are detected in lung and cervical cancers
• Therefore LKB1 may be a strong tumor suppressor
• Pharmacologic activation of LKB1/AMPK with metformin can suppress cancer cell growth

In a recent Cell Metabolism paper[2], Brandon Faubert and colleagues describe how AMPK activity reduces aerobic glycolysis and tumor proliferation while loss of AMPK activity promotes tumor proliferation by shifting cells to aerobic glycolysis and increasing anabolic pathways in a HIF1-dependent manner.

The paper’s major findings were as follows:

• Loss of AMPKα1 cooperates with the Myc oncogene to accelerate lymphomagenesis
• AMPKα dysfunction enhances aerobic glycolysis (Warburg effect)
• Inhibiting HIF-1α reverses the metabolic effects of AMPKα loss
• HIF-1α mediates the growth advantage of tumors with reduced AMPK signaling

Summary

AMPK is a metabolic sensor that helps maintain cellular energy homeostasis. Despite evidence linking AMPK with tumor suppressor functions, the role of AMPK in tumorigenesis and tumor metabolism is unknown. Here we show that AMPK negatively regulates aerobic glycolysis (the Warburg effect) in cancer cells and suppresses tumor growth in vivo. Genetic ablation of the α1 catalytic subunit of AMPK accelerates Myc-induced lymphomagenesis. Inactivation of AMPKα in both transformed and nontransformed cells promotes a metabolic shift to aerobic glycolysis, increased allocation of glucose carbon into lipids, and biomass accumulation. These metabolic effects require normoxic stabilization of the hypoxia-inducible factor-1α (HIF-1α), as silencing HIF-1α reverses the shift to aerobic glycolysis and the biosynthetic and proliferative advantages conferred by reduced AMPKα signaling. Together our findings suggest that AMPK activity opposes tumor development and that its loss fosters tumor progression in part by regulating cellular metabolic pathways that support cell growth and proliferation.

Below is the graphical abstract of this paper.

(Photo credit reference(2; Faubert et. al) permission from Elsevier)

However, this regulation of tumor promotion by AMPK may be more complicated and dependent on the cellular environment.

Nissam Hay from the University of Illinois College of Medicine, Chicago, Illinois, USA and his co-workers Sang-Min Jeon and Navdeep Chandel were investigating the mechanism through which LKB1/AMPK regulate the balance between cancer cell growth and apoptosis under energy stress[3]. In their system, the loss of function of either of these proteins makes cells more sensitive to apoptosis in low glucose environments, and cells deficient in either AMPK or LKB1 were shown to be resistant to oncogenic transformation.  Whereas previous studies showed (as above) AMPK opposes tumor proliferation in a HIF1-dependent manner, their results showed AMPK could promote tumor cell survival during periods of low glucose or altered redox status.

The researchers incubated LKB1-deficient cancer cells in the presence of either glucose or one of the non-metabolizable glucose analogues 2-deoxyglucose (2DG) and 5-thioglucose (5TG), and found that 2DG, but not 5TG, induced the activation of AMPK and protected the cells from apoptosis, even in cells that were deficient in LKB1.

The authors demonstrated that glucose deprivation depleted NADPH levels, increased H₂O₂ levels and increased cell death, and that this was accelerated in cells deficient in the enzyme glucose-6-phosphate dehydrogenase. Anti-oxidants were also found to inhibit cell death in cells deficient in either AMPK or LKB1.

Knockdown or knockout of either LKB1 or AMPK in cancer cells significantly increased levels of H₂O₂ but not of peroxide (O₂^–) during glucose depletion. The glucose analogue 2DG was able to activate AMPK and maintain high levels of NADPH and low levels of H₂O₂ in these cells.

The nucleotide coenzyme NADPH is generated in the pentose phosphate pathway and mitochondrial metabolism, and consumed in H₂O₂ elimination and fatty acid synthesis. If glucose is limited mitochondrial metabolism becomes the major source of NADPH, supported by fatty acid oxidation. AMPK is known to be a regulator of fatty acid metabolism through inhibition of two acetyl-CoA carboxylases, ACC1 and ACC2.

Short interfering RNAs (siRNAs) to knock down levels of both ACC1 and ACC2 in A549 cancer cells and found that only ACC2 knockdown significantly increased peroxide accumulation and apoptosis, while over-expression of mutant ACC1 and ACC2 in LKB1-proficient cells increased H₂O₂ and apoptosis.

Therefore, it was concluded AMPK acts to promote early tumor growth and prevent apoptosis in conditions of energy stress through inhibiting acetyl-CoA carboxylase activity, thus maintaining NADPH levels and preventing the build-up of peroxide in glucose-deficient conditions.

This may appear to be conflicting with the previous report in this post however, it is possible that these reports reflect differences in the way cells respond to various cellular stresses, be it hypoxia, glucose deprivation, or changes in redox status.  Therefore a complex situation may arise:

• AMPK promotes tumor progression under glucose starvation
• AMPK can oppose tumor proliferation under a normoxic, HIF1-dependent manner
• Could AMPK regulation be different in cancer stem cells vs. non-stem cell?

References:

1.            Green AS, Chapuis N, Lacombe C, Mayeux P, Bouscary D, Tamburini J: LKB1/AMPK/mTOR signaling pathway in hematological malignancies: from metabolism to cancer cell biology. Cell Cycle 2011, 10(13):2115-2120.

2.            Faubert B, Boily G, Izreig S, Griss T, Samborska B, Dong Z, Dupuy F, Chambers C, Fuerth BJ, Viollet B et al: AMPK is a negative regulator of the Warburg effect and suppresses tumor growth in vivo. Cell metabolism 2013, 17(1):113-124.

3.            Jeon SM, Chandel NS, Hay N: AMPK regulates NADPH homeostasis to promote tumour cell survival during energy stress. Nature 2012, 485(7400):661-665.

 Other posts on this site related to Warburg Effect and Cancer include:

Otto Warburg, A Giant of Modern Cellular Biology

Is the Warburg Effect the cause or the effect of cancer: A 21st Century View?

Breast Cancer and Mitochondrial Mutations

AKT signaling variable effects

Bibliographies on Genomics by Subject Matter

Volume One: Genomics Orientations for Individualized Medicine

The Initiation and Growth of Molecular Biology and Genomics – Part I

Ubiquitin-Proteosome pathway, Autophagy, the Mitochondrion, Proteolysis and Cell Apoptosis: Part III

Novel Cancer Hypothesis Suggests Antioxidants Are Harmful

Mitochondrial Damage and Repair under Oxidative Stress

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Imaging-biomarkers is Imaging-based tissue characterization

Posted in Advanced Drug Manufacturing Technology, Bio Instrumentation in Experimental Life Sciences Research, Biomarkers & Medical Diagnostics, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Prevention: Research & Programs, Computational Biology/Systems and Bioinformatics, Disease Biology, Small Molecules in Development of Therapeutic Drugs, Drug Delivery Platform Technology, Ecosystems & Industrial Concentration in the Medical Device Sector, FDA Regulatory Affairs, FDA, CE Mark & Global Regulatory Affairs: process management and strategic planning - GCP, GLP, ISO 14155, Genomic Testing: Methodology for Diagnosis, Health Economics and Outcomes Research, HealthCare IT, Imaging-based Cancer Patient Management, International Global Work in Pharmaceutical, Medical Devices R&D and Inventions, Medical Devices R&D Investment, Medical Imaging Technology, Image Processing/Computing, MRI, CT, Nuclear Medicine, Ultra Sound, Personalized and Precision Medicine & Genomic Research, Pharmaceutical R&D Investment, Pharmacotherapy and Cell Activity, Population Health Management, Genetics & Pharmaceutical, Regulated Clinical Trials: Design, Methods, Components and IRB related issues, Technology Transfer: Biotech and Pharmaceutical, tagged bio-markers, biomarkers, Cancer - General, cancer management, imaging-bio-markers, MRI, MRI sequence, research, tissue characterisation on March 10, 2013| 3 Comments »

Imaging-biomarkers is Imaging-based tissue characterization

Author – Writer: Dror Nir, PhD

• 

For everyone who is skeptical about the future role of imaging-based tissue chracterisation in the management of cancer, the following “Statement paper” ESR statement on the stepwise development of imaging biomarkers published online: 9 February 2013, by the European Society of Radiology (ESR), should provide substantial reassurance that this kind of technology will become a must! In support of this claim I quote the following information:

“The European Society of Radiology and its related European Institute for Biomedical Imaging Research (EIBIR) should have a relevant role in coordinating future developments of biomarkers and in the assessment and validation of imaging biomarkers as surrogate end points.

Acknowledgements

This paper was kindly prepared by the ESR Subcommittee on Imaging Biomarkers (Chairperson: Bernard Van Beers. Research Committee Chairperson: Luis Martí-Bonmatí. Members: Marco Essig, Thomas Helbich, Celso Matos, Wiro Niessen, Anwar Padhani, Harriet C. Thoeny, Siegfried Trattnig, Jean-Paul Vallée. Co-opted members: Peter Brader, Nicolas Grenier) on behalf of the European Society of Radiology (ESR) and with the help of Sabrina Doblas, INSERM U773, Paris, France.

It was approved by the ESR Executive Council in December 2012..”

According to ESR: “There is increasing interest in developing the quantitative imaging of biomarkers in personalised medicine”. In this perspective, “Biomarkers” are tissue properties that can be quantitatively and reproducibly measured by imaging devices. One example for a major unmet need, which I found to be most interesting is the imaging-based detection of tumor invasiveness.

Quoting from the paper: ” Biomarkers are defined as “characteristics that are objectively measured and evaluated as indicators of normal biological processes, pathological processes, or pharmaceutical responses to a therapeutic intervention” [1]. Broadly, biomarkers fall into two categories: bio-specimen biomarkers, including molecular biomarkers and genetic biomarkers, and bio-signal biomarkers or imaging biomarkers. Bio-specimen biomarkers are obtained by removing a sample from a patient. Examples of these molecular biomarkers are genes and proteins detected from fluids or tissue samples. Bio-signal biomarkers remove no material from the patient, but rather detect and analyse an electromagnetic, photonic or acoustic signal emitted by the patient [2]. These imaging biomarkers have the advantage of being non-invasive, spatially resolved and repeatable [3]. They are of particular interest if they can overcome the limitations of the established histological “gold standards”. Indeed, invasive reference examinations, such as biopsy, can be inconclusive, are non-representative of the whole tissue (which is a tremendous limitation when assessing malignant tumours, which are known to be heterogeneous) and possess non-negligible levels of mortality and morbidity.

Genetic biomarkers indicate whether a disease may occur, but they are usually inefficient to assess the presence and stage of a disease. Similar to molecular biomarkers, imaging biomarkers can be used for early detection of diseases, staging and grading, and predicting or assessing the response to treatment [3]. Accordingly, because of their relative lower cost compared with imaging, molecular biomarkers may be more appropriate for disease screening and early detection than imaging biomarkers. With their high sensitivity, molecular biomarkers could also detect subclinical stages of disease before any morphological or functional change is detectable on imaging. In contrast, imaging biomarkers are often more useful than molecular biomarkers for disease staging, and also grading and for assessing tumour response, because localised information is crucial.”

The main messages ESR wishes to deliver in this paper are that:

• Using imaging-biomarkers to streamline drug discovery and disease progression will drive a huge advancement in healthcare.

• The clinical qualification and validation of imaging biomarkers technology pose challenges, mainly in establishing the accuracy and reproducibility of such techniques. In that respect, agreements on standards and evaluation methods (e.g. clinical studies design) is imperative.

• There should be high motivation to pursue the development of imaging-biomarkers as the “clinical value of new biomarkers is of the highest priority in terms of patient management, assessing risk factors and disease prognosis.”

The paper deals to a great extent with the requirements on accuracy, reproducibility, standardization and quality control from the process of developing imaging-biomarkers:

“Accuracy: Before being routinely used in the clinic, imaging biomarkers must be validated. Determining the accuracy implies calculating the sensitivity and specificity of the biomarker when compared with a biological process, such as tumour necrosis, which can be assessed at histopathological examination… [6–9]  [10, 11]

Reproducibility: Repeatability (measurements at short intervals on the same subjects using the same equipment in the same centres) and reproducibility (measurements at short intervals on the same subjects using different facilities in the same and different centres) studies must be conducted for image acquisition and image analysis…. Reproducibility studies are now very often included in scientific papers, as advised by the “standards for reporting of diagnostic accuracy” (STARD) criteria and should ideally include Bland-Altman plots and results of coefficients of repeatability [16, 17].

Standardisation: Standardisation relates to the establishment of norms or requirements about technical aspects. In the development of imaging biomarkers, two main aspects should be considered: Standardisation of image acquisition and Standardisation of image analysis…  [18] [19–21]  [22] [27, 28] [31–33]

Quality control: Adequate phantoms could be used to validate, on a day-to-day basis, that the biomarker stays robust and to avoid any drift in the machine, acquisition or processing protocol….  [34] [30, 35] [36] [37] [23].”

The proposed development workflow:

“Similar to new drugs, the development of biomarkers has to pass along a pipeline going from discovery, through verification in different laboratories, validation and qualification before they can be used in clinical routine. Validation includes the determination of the accuracy and the precision (reproducibility) of the biomarker and standardisation concerns both acquisition and analysis. Qualification, defined as a “graded, fit-for-purpose evidentiary process linking a biomarker with biological processes and clinical end-points”, is a validation process in large cohorts of patients involving multiple centres, similar to phase III clinical trials, to obtain regulatory approval as surrogate endpoints [4]. A more extensive path to biomarker development has been reported [5]. The first step is the proof of concept, which defines any specific change relevant to the disease that can be studied using the available imaging and computational techniques. The relationship between this change and the presence, grading and response to treatment of the disease constitutes the proof of mechanism. The images needed to extract the biomarker must be appropriate (in terms of resolution, signal and contrast behaviour). Preparation of images relates to improving the data before the analysis (such as segmentation, filtering, interpolation or registration). The analysis and modelling of the signal by computational numerical adjustment of a mathematical model allow extracting the needed information (such as structural, physical, chemical, biological and functional properties). After this voxel-by-voxel computation, the spatial distribution of the biomarker can be depicted by parametric images, defined as derived secondary images which pixels represent the distribution values of a given parameter. Multivariate parametric images obtained by statistical modelling of the relevant parameters allow the reduction of data and a clear definition of the defined disease target. The abnormal values should be defined and measured through histogram analysis. A pilot test on a small sample of subjects, with and without the disease, has to be performed to validate the process—also called proof of principle—and to evaluate the influence of potential variations related to age, sex or any other source of biases. Finally, proofs of efficacy and effectiveness on larger and well-defined series of patients will show the ability of a biomarker to measure the clinical endpoint (Fig. 1).”

Steps for the development of imaging biomarkers (adapted from [5])

The authors admit that the requirement posed on development of imaging-biomarkers represents a huge challenge and they try to offer ideas, mainly taken from the “MRI experience” to overcome certain hurdles. There is one important point on which they do not discuss: the definition of appropriate reference test. It is my own experience, based on many study protocols I developed in the past decade, that without reaching an agreement on that point, the development of imaging-biomarkers will just move in circles. Note, that today’s most “acceptable” reference test is histopathology, which everyone admits (as well mentioned in this paper); suffers many limitations. When it comes to validating imaging-biomarkers, the need to accurately match imaging products with histopathology is an additional major hurdle.

This is why, I see as a necessary step, to develop “real-time” imaging based tissue characterization combined with in-situ imaging-based histology.

 

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Virtual Biopsy – is it possible?

Posted in Bio Instrumentation in Experimental Life Sciences Research, Biomarkers & Medical Diagnostics, CANCER BIOLOGY & Innovations in Cancer Therapy, Chemical Biology and its relations to Metabolic Disease, Ecosystems & Industrial Concentration in the Medical Device Sector, Health Economics and Outcomes Research, Imaging-based Cancer Patient Management, Medical Devices R&D and Inventions, Medical Devices R&D Investment, Medical Imaging Technology, Image Processing/Computing, MRI, CT, Nuclear Medicine, Ultra Sound, Personalized and Precision Medicine & Genomic Research, Regulated Clinical Trials: Design, Methods, Components and IRB related issues, Statistical Methods for Research Evaluation, Technology Transfer: Biotech and Pharmaceutical, tagged Biology, biopsy, Cancer - General, coherence tomography, health, medicine, OCT, optical coherence, optical coherence tomography, research, resolution reconstruction, virtual biopsy on March 3, 2013| 7 Comments »

Virtual Biopsy – is it possible?

Author and Curator: Dror Nir, PhD

• 

In a remark made to my last post: New envelopment in measuring mechanical properties of tissue, Dr. Aviva Lev-Ari, PhD, RN, Director and Founder of our Open Access Online Scientific Journal:  Leaders of Pharmaceutical Business Intelligence, asked whether OCT can be used for the purpose of performing biopsy. My answer to her question was “YES”. I thought that it will be worthwhile explaining why I am so “optimistic” about this:

A conventional biopsy is a process where a tissue sample is being cut out of the body and after being subjected to all kind of chemical processes a thin-film of tissue is trimmed and read under the microscope by a trained pathologist. Can imaging provide histological assessment of “thin-film” of tissue without cutting it out of the body? The answer would be positive if the imaging will result with high resolution reconstruction of a tissue sample identical in quality to a “live-sample” that is put under the microscope.

I was happy to find support to my optimism regarding the feasibility of constructing such device in the following article: Virtual skin biopsy by optical coherence tomography: the first quantitative imaging biomarker for scleroderma published on February 20^th 2013 in Ann Rheum Dis doi:10.1136/annrheumdis-2012-202682

 This article reports an original, first study to perform histological comparison and explore Optical coherence tomography (“OCT”) as a potential imaging technique for the clinical assessment of patients presenting with systemic sclerosis (“SSc”). In their study the investigators used a device emitting low-intensity infrared laser beam, capable of producing high-contrast images of skin up to 2 mm deep with resolutions of 4–10 μm.

[START ORIGINAL PAPER]

ABSTRACT

Background

Skin involvement is of major prognostic value in systemic sclerosis (SSc) and often the primary outcome in clinical trials. Nevertheless, an objective, validated biomarker of skin fibrosis is lacking. Optical coherence tomography (OCT) is an imaging technology providing high-contrast images with 4 μm resolution, comparable with microscopy (‘virtual biopsy’). The present study evaluated OCT to detect and quantify skin fibrosis in SSc.

Methods

We performed 458 OCT scans of hands and forearms on 21 SSc patients and 22 healthy controls. We compared the findings with histology from three skin biopsies and by correlation with clinical assessment of the skin. We calculated the optical density (OD) of the OCT images employing Matlab software and performed statistical analysis of the results, including intraobserver/ interobserver reliability, employing SPSS software.

 Results

Comparison of OCT images with skin histology indicated a progressive loss of visualisation of the dermal–epidermal junction associated with dermal fibrosis. Furthermore, SSc affected skin showed a consistent decrease of OD in the papillary dermis, progressively worse in patients with worse modified Rodnan skin score (p<0.0001). Additionally, clinically unaffected skin was also distinguishable from healthy skin for its specific pattern of OD decrease in the reticular dermis (p<0.001). The technique showed an excellent intraobserver and interobserver reliability (intraclass correlation coefficient >0.8).

Conclusions

OCT of the skin could offer a feasible and reliable quantitative outcome measure in SSc. Studies determining OCT sensitivity to change over time and its role in defining skin vasculopathy may pave the way to defining OCT as a valuable imaging biomarker in SSc.

Virtual skin biopsy by OCT

The OCT images acquisition allowed the reconstruction of a virtual skin biopsy measuring 4×0.4×2 mm. The main structure of the healthy skin was easily recognisable by OCT (figure 1).

Virtual biopsy of forearm skin by optical coherence tomography. Representative 3D reconstruction from the tomography of healthy and systemic sclerosis (SSc) (site modified Rodnan skin score=3) skin scans. The keratin of the skin appears as a white line on the surface (k). The epidermis (ED) is quite visible in the healthy skin by the contrast with the increased optical density of the papillary dermis (PD). The dermal– epidermal junction (DEJ) is quite visible in the healthy skin between the ED and PD. On the contrary, neither clear distinction of ED and PD or DEJ is appreciable in the SSc skin. The vessels (*) are numerous and very well recognisable in healthy skin, whereas they appear less numerous and less distinct in the OCT image of SSc skin. Total depth of 3D reconstruction=1.2 mm. Scale bars are calculated by ImageJ.

Some quantitative results  – in images:

Validation of optical coherence tomography (OCT) images by histology. (A and B) H&E staining (A) and corresponding OCT scan (B) from a healthy control (HC). The green line is the mean A-scan of the entire OCT image (100 scans) overlaid by matching the scale bars of OCT and histology. The green arrow indicates the nadir of the valley in the mean A-scan, which corresponds to the dermal–epidermal junction clearly visible on both images. The green arrowhead indicates the second peak of the mean OCT A-Scan which corresponds by the overlay to the most superficial region of the papillary dermis. (C and D) H&E staining (C) and corresponding OCT scan (D) from a systemic sclerosis (SSc) patient (site modified Rodnan skin score =3). The red line is the mean A-scan of the OCT image, overlaid by matching the scale bars in the two panels. The red arrow indicates the nadir in the valley of the mean A-scan, which in this case does not correspond to the dermal–epidermal junction. The red arrowhead corresponds to the second peak in mean A-Scan. (E) Overlay of HC and SSc. Scale bar=240 μm.

Optical coherence tomography (OCT) of affected and not affected skin in plaque morphea. (A) OCT of not affected skin. Vertical scale represents depth in micrometre from the surface. The dermal–epidermal junction (DEJ) level is indicated by the white dotted line. Mean A-scan curve is overlaid and displayed in green. (B) OCT of affected skin in morphea patient. Mean A-scan curve is overlaid and displayed in red. Note the poorly visible DEJ and the valley of the curve below the DEJ (arrowhead). (C) Overlay of mean A-scan curves from the analysis of affected and unaffected skin in a morphea patient. Note that in the curves overlay graph both the difference depth of the first valley is clearly appreciable (arrowheads). Similarly the second mean A-scan peak (arrow) is subtle in the affected skin, similar to scleroderma affected skin.

DISCUSSION

The current gold standard for semiquantitative assessment of skin fibrosis, the mRSS, suffers from several shortcomings ranging from the subjectivity of skin palpation assessments and the high level of skill required from the clinical investigator. Even more importantly, a meta-analysis of three independent studies determined an overall within patient interobserver SD of five units independently of the mean skin score,[6 21] which represents an SE ranging from 20% to 26%. A primary outcome measure with 25% of SE entails the recruitment of a large number of patients to attain statistical validity in minimally significant changes, a task often difficult to accomplish given the comparatively low incidence of SSc.

A robust imaging biomarker for the assessment of skin fibrosis in SSc has not previously been reported. Herein we report the first study aimed to validate OCT for the quantitative assessment of skin involvement in SSc.

To date, the limited data on surrogate outcome measures for skin involvement are largely composed of histopathological or molecular changes in affected skin.[22 23] Despite conceptually very valuable, these studies, involving skin biopsies, are invasive and limited because of a site bias, referring to only one precise body area. Moreover, they are difficult to repeat in longitudinal manner and showed no sensitivity to change over time.[24] In this study, we evaluated OCT skin scanning as a reliable and quanti­tative tool that could be used as a surrogate marker of skin fibrosis. The technique requires minimal operator training, less than 10s per site examined, and offers the great advantage of saving image files for further or centralised operator independ­ent analysis. This latter is a particularly useful tool limiting the ‘hands on’ time in the clinic office and allowing a centralised, blinded assessment of results in clinical trials.

We observed an excellent correlation of OCT mean A-Scan curves and mRSS score at the site of analysis. More importantly, the corroboration of our OCT findings with pathological changes at the DEJ provides a robust construct validity for the technique. Of interest, we found that the changes of the OD of the dermis in SSc are similar to the ones observed in a case of plaque morphea, corroborating even further the potential value of OCT in measuring skin fibrosis.

Additional Comment

HFUS (High Frequensy Ultrasound) has been recently suggested to offer a quantitative assessment of skin thickness in SSc by several studies.8–10 In contrast with ultrasound, OCT does not require any use of gels, is able to give a higher resolution images and the analysis algo­rithm is automatic, not involving any operator interpretation. Nevertheless, since the penetration of OCT is limited to the first millimetre of skin, OCT and HFUS may be explored as comple­mentary imaging biomarkers in SSc.

REFERENCES

1     Jimenez SA, Derk CT. Following the molecular pathways toward an understanding
of the pathogenesis of systemic sclerosis. Ann Intern Med 2004;140:37–50.

2     Varga J, Abraham D. Systemic sclerosis: a prototypic multisystem fibrotic disorder.
J Clin Invest 2007;117:557–67.

3     Gabrielli A, Avvedimento EV, Krieg T. Scleroderma. N Engl J Med
2009;360:1989–2003.

4     Clements PJ, Hurwitz EL, Wong WK, et al. Skin thickness score as a predictor and
correlate of outcome in systemic sclerosis: high-dose versus low-dose penicillamine trial. Arthritis Rheum 2000;43:2445–54.

5     Steen VD, Medsger TA Jr. Improvement in skin thickening in systemic sclerosis
associated with improved survival. Arthritis Rheum 2001;44:2828–35.

6     Pope JE, Baron M, Bellamy N, et al. Variability of skin scores and clinical
measurements in scleroderma. J Rheumatol 1995;22:1271–6.

Clements PJ, Lachenbruch PA, Seibold JR, et al. Skin thickness score in systemic

sclerosis: an assessment of interobserver variability in 3 independent studies. J Rheumatol 1993;20:1892–6.

   8     Akesson A, Hesselstrand R, Scheja A, et al. Longitudinal development of skin
involvement and reliability of high frequency ultrasound in systemic sclerosis. Ann Rheum Dis 2004;63:791–6.

   9     Moore TL, Lunt M, McManus B, et al. L. Seventeen-point dermal ultrasound scoring
system—a reliable measure of skin thickness in patients with systemic sclerosis. Rheumatology (Oxford) 2003;42:1559–63.

10     Kaloudi O, Bandinelli F, Filippucci E, et al. High frequency ultrasound

measurement of digital dermal thickness in systemic sclerosis. Ann Rheum Dis 2010;69:1140–3.

11     Aden N, Shiwen X, Aden D, et al. Proteomic analysis of scleroderma lesional skin
reveals activated wound healing phenotype of epidermal cell layer. Rheumatology (Oxford) 2008;47:1754–60.

12     Aden N, Nuttall A, Shiwen X, et al. Epithelial Cells Promote Fibroblast Activation via
IL-1alpha in Systemic Sclerosis. J Invest Dermatol 2010;130:2191–200.

13     Gambichler T, Jaedicke V, Terras S. Optical coherence tomography in dermatology:
technical and clinical aspects. Arch Dermatol Res 2011;303:457–73.

14     Marschall S, Sander B, Mogensen M, et al. Optical coherence tomography-current
technology and applications in clinical and biomedical research. Anal Bioanal Chem 2011;400:2699–720.

15     Coleman AJ, Richardson TJ, Orchard G, et al. Histological correlates of optical
coherence tomography in non-melanoma skin cancer. Skin Res Technol 2013;19: e10–9.

16     Preliminary criteria for the classification of systemic sclerosis (scleroderma).
Subcommittee for scleroderma criteria of the American Rheumatism Association Diagnostic and Therapeutic Criteria Committee. Arthritis Rheum 1980;23:581–90.

17     Collins TJ. ImageJ for microscopy. Biotechniques 2007;43:25–30.

18     Clendenon JL, Phillips CL, Sandoval RM, et al. Voxx: a PC-based, near real-time

volume rendering system for biological microscopy. Am J Physiol Cell Physiol 2002;282:C213–18.

19     Bland JM, Altman DG. Statistical methods for assessing agreement between two
methods of clinical measurement. Lancet 1986;1:307–10.

20     LeRoy EC, Black C, Fleischmajer R, et al. Scleroderma (systemic sclerosis):
classification, subsets and pathogenesis. J Rheumatol 1988;15:202–5.

21     Merkel PA, Silliman NP, Clements PJ, et al. Patterns and predictors of change in
outcome measures in clinical trials in scleroderma: an individual patient meta-analysis of 629 subjects with diffuse cutaneous systemic sclerosis. Arthritis Rheum 2012;64:3420–9.

22     Farina G, Lafyatis D, Lemaire R, et al. A four-gene biomarker predicts skin disease
in patients with diffuse cutaneous systemic sclerosis. Arthritis Rheum 2010;62:580–8.

23     Milano A, Pendergrass SA, Sargent JL, et al. Molecular subsets in the gene
expression signatures of scleroderma skin. PLoS One 2008;3:e2696.

  24   Pendergrass SA, Lemaire R, Francis IP, et al. Intrinsic gene expression subsets of

diffuse cutaneou

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New development in measuring mechanical properties of tissue

Posted in Health Economics and Outcomes Research, Imaging-based Cancer Patient Management, Medical Devices R&D and Inventions, Medical Devices R&D Investment, Medical Imaging Technology, Image Processing/Computing, MRI, CT, Nuclear Medicine, Ultra Sound, Personalized and Precision Medicine & Genomic Research, Population Health Management, Genetics & Pharmaceutical, Regulated Clinical Trials: Design, Methods, Components and IRB related issues, Technology Transfer: Biotech and Pharmaceutical, tagged Cancer - General, Clinical trial, elastography, health, Magnetic resonance imaging, magnetic resonance imaging mri, OCT, research, science, tissue, tissue differentiation on February 22, 2013| Leave a Comment »

New development in measuring mechanical properties of tissue

Author – Writer: Dror Nir, PhD

• 

Measuring the effects induced onto imaging by the mechanical properties of tissue is a common approach to differentiate tissue abnormalities. In previous posts I discussed the applicability of imaging applications that visualize variations in tissue stiffness; e.g. ultrasound-elastography and MRI-elastography as aid in the diagnosis workflow of cancer. Today, I would like to report on a recent publication made in SPIE Newsroom describing an optical-imaging system to measure tissue stiffness at high resolution. I think that such emerging technologies should be followed up as they bear promise to bridge deficiencies of the traditional modalities currently in use.

Reporting on: Optical elastography probes mechanical properties of tissue at high resolution

By: David Sampson, Kelsey Kennedy, Robert McLaughlin and Brendan Kennedy

Information published at: SPIE Newsroom – Biomedical Optics & Medical Imaging

Probing the micro-mechanical properties of tissue using optical imaging might offer new surgical tools that enable improved differentiation of tissue pathologies, such as cancer or atherosclerosis.

11 January 2013, SPIE Newsroom. DOI: 10.1117/2.1201212.004605

Elastography is an emerging branch of medical imaging that uses mechanical contrast to better characterize tissue pathology than can be achieved with structural imaging alone. It achieves this by imaging a tissue’s response to mechanical loading. Although commercial products based on ultrasonography and magnetic resonance imaging (MRI) have been available for several years, these new modalities offer superior tissue differentiation deep in the human body. However, elastography is limited by its low resolution compared with the length scales relevant to many diseases. Increasing the resolution with optical techniques might offer new opportunities for elastography in medical imaging and surgical guidance.

An elastography system requires a means of loading the tissue to cause deformation and an imaging system with sufficient sensitivity and range to capture this deformation. Implicit in these requirements is access to the tissue of interest. Optical elastography has previously been largely based on schemes that suit small tissue samples rather than intact tissue in living humans. Additionally, such schemes have not had the sensitivity or range to produce high-fidelity images of mechanical properties. We have addressed both these issues in our recent work, developing the means to access tissues in vivo and improve the sensitivity and range of optical elastography using phase-sensitive optical coherence tomography as the underlying modality. The use of optical coherence tomography to perform elastography has come to be referred to as optical coherence elastography.¹

To make optical coherence elastography on human subjects feasible, we designed an annular piezoelectric loading transducer (see Figure 1), through which we could simultaneously image, enabling the first in vivo dynamic optical coherence elastography on human subjects.² We were subsequently able to extend this to three dimensions (see Figure 2), in collaboration with Stephen Boppart’s group at the University of Illinois at Urbana-Champaign.³ This extension took advantage of the high speed of spectral-domain optical coherence tomography, and the maturity of phase-sensitive detection techniques originally developed for Doppler flowmetry and microangiography.

 

Figure 1. Schematic (left) and photograph (right) of the annular load transducer and imaging optics for in vivo optical coherence elastography.

 

Figure 2. 2D images of in vivo human skin selected from 3D stacks. (a) Optical coherence tomography image and (b) the same image overlaid by the 2D dynamic elastogram recorded at 125Hz load frequency, highlighting the greater strain in the epidermis. Reprinted in modified form with permission.³

For general access to tissues in the body, optical coherence elastography faces two basic limitations. The free-space probe requires miniaturization for versatile access to tissue in confined or convoluted geometries. We addressed this in studies of the elastic properties of human airways using catheter-based anatomical optical coherence tomography.⁴

 

Figure 3. (a) Schematic diagram of needle optical coherence elastography. The phase difference Δφ=φ₁– φ₂ determines the displacement, d, when scaled by the wavelength, λ, and refractive index, n. (b) Needle and pig trachea. (c) Local displacement versus distance, with tissue boundaries indicated by red stars. (d) Representative histology. Reprinted in modified form with permission.⁶

More fundamentally, optical coherence tomography can only penetrate, at best, 1–2mm into most tissues, limiting it to superficial applications. To address this issue, we combined optical coherence elastography with needle probes, an active research area in our group (see Figure 3).⁵ We conveniently use the needle probe itself to deform the tissue during insertion.⁶ The deformation ahead of the needle tip depends on the mechanical properties of the tissue encountered, as well as on the nearby tissue environment, particularly on any interfaces ahead of it. We measure the local sub-micrometer displacement of the tissue between two positions of the moving needle probe. We plot this displacement versus distance ahead of the probe: see Figure 3(c). The slope of the displacement at location z is a measure of the local strain. A change in slope signifies a change in tissue stiffness; the steeper the slope, the softer the tissue (other things being equal). Figure 3 highlights this effect in a layered sample of pig trachea. The positions of the changes in slope correlate well with the tissue interfaces shown in the accompanying histology: see Figure 3(d).

The other key area of improvement we have focused on is lowering the optical coherence elastography noise floor by increasing the detection sensitivity, which is vital to make clinical imaging practical. We firstly showed that Gaussian-smoothed, weighted-least squares strain estimation improved the sensitivity of estimates by up to 12dB over conventional finite-difference methods.⁷ Next, we showed that performance could be further improved at low optical coherence tomo- graphy signal-to-noise ratios (and, therefore, at greater depths in tissue) by employing a 2D Fourier transform technique.⁸Combined with other system refinements, these improvements have enabled us to reach a displacement sensitivity of 300pm for typical optical coherence tomography signal-to-noise ratios in tissue, with room for improvement.

The Young’s modulus of soft tissue varies from kPa to tens of MPa, whereas the scattering coefficient of such tissues—which is largely responsible for determining the contrast of optical coherence tomography—is typically in the range 2–20mm⁻¹. This apparent native advantage in mechanical over optical contrast (see the example in Figure 4), combined with the maturation of optical coherence elastography methods, bodes well for the future. In our group, we are pursuing tumor-margin identification using elastography; others have begun to consider corneal elastography,^{9, 10} and still others are examining shear wave schemes with the aim of probing Young’s modulus much deeper in tissues.^11,12

 

Figure 4. Optical coherence tomography (a) and optical coherence elastography (b) images of the same phantom with two inclusions visible, showing enhanced mechanical over scattering contrast.

Optical elastography currently sits at a similar stage of development as ultrasound elastography did in 1999. Based on a similar trajectory, this field will rapidly expand over the next decade. Our recent results point to the first convincing applications of optical elastography being just around the corner.

We acknowledge funding for this work from Perpetual Trustees, the Raine Medical Research Foundation, the Cancer Council of Western Australia, the Australian Research Council, the National Health and Medical Research Council (Australia), and the National Breast Cancer Foundation (Australia).

---

David Sampson

Optical+Biomedical Engineering Laboratory
School of Electrical, Electronic and Computer Engineering

and
Centre for Microscopy, Characterisation and Analysis
The University of Western Australia

 

Perth, Australia

Kelsey Kennedy, Robert McLaughlin, Brendan Kennedy

Optical+Biomedical Engineering Laboratory
School of Electrical, Electronic and Computer Engineering
The University of Western Australia

Perth, Australia

---

References:

1. J. Schmitt, OCT elastography: imaging microscopic deformation and strain of tissue, Opt. Express 3(6), p. 199-211, 1998.doi:10.1364/OE.3.000199

2. B. F. Kennedy, T. R. Hillman, R. A. McLaughlin, B. C. Quirk, D. D. Sampson, In vivo dynamic optical coherence elastography using a ring actuator, Opt. Express 17(24), p. 21762-21772, 2009.doi:10.1364/OE.17.021762

3. B. F. Kennedy, X. Liang, S. G. Adie, D. K. Gerstmann, B. C. Quirk, S. A. Boppart, D. D. Sampson, In vivo three-dimensional optical coherence elastography, Opt. Express 19(7), p. 6623-6634, 2011.doi:10.1364/OE.19.006623

4. J. P. Williamson, R. A. McLaughlin, W. J. Noffsingerl, A. L. James, V. A. Baker, A. Curatolo, J. J. Armstrong, Elastic properties of the central airways in obstructive lung diseases measured using anatomical optical coherence tomography, Am. J. Resp. Crit. Care 183(5), p. 612-619, 2011.doi:10.1164/rccm.201002-0178OC

5. R. A. McLaughlin, B. C. Quirk, A. Curatolo, R. W. Kirk, L. Scolaro, D. Lorenser, P. D. Robbins, B. A. Wood, C. M. Saunders, D. D. Sampson, Imaging of breast cancer with optical coherence tomography needle probes: Feasibility and initial results, IEEE J. Sel. Topics Quantum Electron. 18(3), p. 1184-1191, 2012. doi:10.1109/JSTQE.2011.2166757

6. K. M. Kennedy, B. F. Kennedy, R. A. McLaughlin, D. D. Sampson, Needle optical coherence elastography for tissue boundary detection, Opt. Lett. 37(12), p. 2310-2312, 2012. doi:10.1364/OL.37.002310

7. B. F. Kennedy, S. H. Koh, R. A. McLaughlin, K. M. Kennedy, P. R. T. Munro, D. D. Sampson, Strain estimation in phase-sensitive optical coherence elastography, Biomed. Opt. Express 3(8), p. 1865-1879, 2012.doi:10.1364/BOE.3.001865

8. B. F. Kennedy, M. Wojtkowski, M. Szkulmowski, K. M. Kennedy, K. Karnowski, D. D. Sampson, Improved measurement of vibration amplitude in dynamic optical coherence elastography, Biomed. Opt. Express 3(12), p. 3138-3152, 2012. doi:10.1364/BOE.3.003138

9. R. K. Manapuram, S. R. Aglyamov, F. M. Monediado, M. Mashiatulla, J. Li, S. Y. Emelianov, K. V. Larin, In vivo estimation of elastic wave parameters using phase-stabilized swept source optical coherence elastography, J. Biomed. Opt. 17(10), p. 100501, 2012.doi:10.1117/1.JBO.17.10.100501

10. W. Qi, R. Chen, L. Chou, G. Liu, J. Zhang, Q. Zhou, Z. Chen, Phase-resolved acoustic radiation force optical coherence elastography, J. Biomed. Opt. 17(11), p. 110505, 2012. doi:10.1117/1.JBO.17.11.110505

11. C. Li, G. Guan, S. Li, Z. Huang, R. K. Wang, Evaluating elastic properties of heterogeneous soft tissue by surface acoustic waves detected by phase-sensitive optical coherence tomography, J. Biomed. Opt. 17(5), p. 057002, 2012. doi:10.1117/1.JBO.17.5.057002

12. M. Razani, A. Mariampillai, C. Sun, T. W. H. Luk, V. X. D. Yang, M. C. Kolios, Feasibility of optical coherence elastography measurements of shear wave propagation in homogeneous tissue equivalent phantoms,Biomed. Opt. Express 3(5), p. 972-980, 2012. doi:10.1364/BOE.3.00097

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State of the art in oncologic imaging of Colorectal cancers.

Posted in Bio Instrumentation in Experimental Life Sciences Research, Biomarkers & Medical Diagnostics, CANCER BIOLOGY & Innovations in Cancer Therapy, Chemical Biology and its relations to Metabolic Disease, Health Economics and Outcomes Research, Imaging-based Cancer Patient Management, Liver & Digestive Diseases Research, Medical Devices R&D and Inventions, Medical Devices R&D Investment, Medical Imaging Technology, Image Processing/Computing, MRI, CT, Nuclear Medicine, Ultra Sound, Personalized and Precision Medicine & Genomic Research, Regulated Clinical Trials: Design, Methods, Components and IRB related issues, Statistical Methods for Research Evaluation, tagged American Cancer Society, Cancer - General, Clinical trial, colorectal cancers, health, liver metastasis, medicine, Personalized medicine, research, science on February 2, 2013| 2 Comments »

State of the art in oncologic imaging of Colorectal cancers.

Author-Writer: Dror Nir, PhD

Word Cloud By Danielle Smolyar

This is the fourth post in a series in which I will address the state of the art in oncologic imaging based on a review paper; Advances in oncologic imaging^†‡ that provides updates on the latest approaches to imaging of 5 common cancers: breast, lung, prostate, colorectal cancers, and lymphoma. This paper is published at CA Cancer J Clin 2012. © 2012 American Cancer Society.

The paper gives a fair description of the use of imaging in interventional oncology based on literature review of more than 200 peer-reviewed publications. In this post I summaries the chapter on colorectal cancer imaging. It reviews current and developing radiologic practices in CRC with respect to screening, preoperative evaluation, surveillance, and post-treatment re-staging.

Colorectal cancer (CRC) is an example to successful imaging-based screening evident by noticeable reduction in mortality rates. The 5-year survival rate of CRC patients diagnosed at an early stage is 90%.1 121 According to this review; “(CRC) is the third most common cancer worldwide and the second most frequent cause of cancer death in the United States. The American Cancer Society estimates that 143,460 new cases of CRC will be diagnosed and 51,690 deaths from CRC will occur in the United States in 2012.120 Because of screening and removal of premalignant polyps, incidence rates have declined over the last 3 decades.”

The authors found out that the increased use of CT in CRC screening has the potential of reducing its costs and associated tisks 122 In addition, use of DW-MRI enabled better outcomes of CRC liver metastasis treatment as it enables tailored localized treatment of such lesions.123 124 Finally, the authors found that: “MRI for staging of rectal cancer has become standard practice and, in some instances, is performed in lieu of surgeon-performed endorectal US (ERUS), providing the radiologist with an even greater role in the management of patients with CRC.125 “

 Screening

“CRC is a largely preventable disease, as the progression of the adenoma-carcinoma sequence of mutations is slow and leaves ample time to intervene. Nonetheless, approximately 41% of the population (in the USA) eligible for screening remains unscreened. 126 Most screening is performed using non-imaging tests”

Any of these screening strategies will reduce mortality from CRC.126, 127 

Among imaging tests used for screening, barium enema has seen a continual decline in usage, at least in part due to the landmark study showing that this test detected only 39% of polyps identified at colonoscopy, including only 48% of those > 1 cm in size.131 The recent (and largest, with > 2500 patients) multicenter CT colonography (CTC, also known as virtual colonoscopy) screening study, performed by the American College of Radiology Imaging Network, found that CTC had sensitivity of 90% and similar specificity for polyps > 9 mm, and the number of centers using CTC has increased.122 Widespread deployment of CTC remains hindered, in part, by the 2009 decision of the Center for Medicare and Medicaid Service (CMS) to deny reimbursement based on 1) potential radiation risk, 2) impact of detection of extracolonic findings, and 3) efficacy in the 65 years and older age group of concern to CMS. Data from studies reported after this decision put CTC in a good position to be reconsidered for reimbursement. The median estimated effective dose is currently 5 to 6 mSv, a dose far less than that received from a standard CT exam and even comparable to or lower than that received from a barium enema examination. In fact, the radiation dose from CTC is equivalent to that received from cosmic radiation in a 1-year period.132 Extra-colonic findings occur in 7% to 11% of cases and lead to extra examinations in about 6% with a relevant new diagnosis made in 2.5%, according to the experience of the largest screening center in the United States.133 Furthermore, when detection of extracolonic cancers and aortoiliac aneurysms is included along with CRC screening, CT colonography (CTC) has been shown to be more clinically effective and more cost-effective than optical colonoscopy.134 In an observational study, CTC accuracy was maintained in patients aged 65 to 79 years, who were compared to the overall general population sample. In the older patients, CTC remained a safe and effective modality and program outcome measures, such as colonoscopy referral and extracolonic work-up rates, remained similar to those in other screened groups.135“

 Detection and Characterization

“Diagnosis and clinical staging of primary colonic adenocarcinoma is most often accomplished by combining colonoscopy with biopsy and performing cross-sectional imaging to detect metastatic disease.

Although CT and MRI are widely used for preoperative whole-body staging, they are not recommended first-line methods for detection of primary lesions. In contradistinction, CTC has matured into an excellent diagnostic method for detection of CRC. Data drawn largely from screening studies tell us that its sensitivity for polyps > 10 mm is 90% or greater, and that it will detect nearly every cancer. In fact, a recent meta-analysis of more than 11,000 patients indicated that CTC had sensitivity of 96.1% (398 of 414) for CRC, and when cathartic cleansing and fecal tagging were used, no cancers were missed (Fig. 16).137 Detection of flat cancers remains a challenge with CTC as compared with endoscopic methods in which mucosal surface details are better appreciated. CTC not only detects CRC, but with its cross-sectional depiction also allows characterization of tumors using the TNM staging system138 with reasonable T- and N-stage accuracies of 83% and 80%, respectively.139 CTC is an operator-dependent technique that has shown great variability between radiologists with different degrees of training. Computer-aided detection (CAD) was developed for this reason and because 10,000 to 15,000 images must be scrutinized for each large adenoma detected. In a screening cohort of 3077 consecutive asymptomatic adults, stand-alone CAD had sensitivities of 97% and 100% for advanced neoplasia and cancer, respectively.140

Coronal reformatted CT scan of the abdomen and pelvis shows a left colon primary adenocarcinoma causing colonic obstruction.

Three-dimensional rendering from CT colonography shows a right colon adenocarcinoma which was stage T1N0.

With magnetic resonance colonography (MRC), detection of masses is limited because techniques employing air cause susceptibility artifacts, and those employing dark-lumen techniques with water-filling and intravenous gadolinium are under scrutiny because of concerns about the potential risk of nephrogenic systemic fibrosis. In addition, in the largest screening study, the sensitivity of MRC was only 70% in patients with colorectal lesions more than 10 mm in size.141

Imaging plays a critical role in detecting liver metastases in order to properly stage and treat the patient with colorectal cancer. NCCN guidelines recommend contrast-enhanced CT or MRI.142 “

MRI is the most promising imaging modality for management of rectal cancer.

Staging of this cancer is primarily accomplished with US, typically performed by surgeons. MRI using phased-array coils provides complete visualization of the pelvic anatomy and, especially, the circumferential resection margin, an important landmark for the standard total mesorectal excision.

In an MRI of rectal carcinoma, the T2-weighted axial image shows rectal mass penetrating the wall and extending to the left posterolateral mesorectal fascia (also known as the circumferential resection margin).

 

 The MERCURY study125established the near equivalence of MRI to histopathology for identification of this margin, an important advantage of MRI over ERUS, with which the margin is not routinely visualized.147 T- and N- stage accuracies of MRI (87% and 74%, respectively) were similar to those of ERUS (82% and 74%, respectively).148 Accurate lymph node identification remains a problem for MRI. Toward this end, a new albumin-bound gadolinium agent has shown some promise, and further results are awaited.149”

 Role of Imaging in Assessing Treatment Response

“Imaging plays a critical role in 1) determining response to systemic and loco-regional treatment of liver metastases, 2) assessing response to local treatment and restaging rectal cancer primary lesions, and 3) detecting and assessing the treatment response of extra-hepatic metastatic disease. Systemic treatment (and in some centers, hepatic artery infusion) of non-resectable liver metastases with chemotherapy aims at reduction of the metastatic burden, which, occasionally may allow attempts at curative liver resection.

Due to the limitations of CT with regard to soft tissue contrast and fatty liver. MRI has greater sensitivity for remaining (or new) lesions < 1.0 cm due to its superior soft tissue contrast. In a recent meta-analysis of 25 eligible studies, MRI showed higher sensitivity than CT on a per-patient basis (P = .05) and on a per-lesion basis as well (P = .0001). With its 81.1% sensitivity and 97.2% specificity, MRI is thus the preferred modality.151 Nonetheless, under the current NCCN guidelines, CT remains the preferred modality.142 

Loco-regional (“liver-directed”) therapies include radiofrequency, microwave ablation, transarterial chemo- or particle embolization and irreversible electroporation. With these treatments, responding lesions can actually increase in size, and simple size criteria are no longer sufficient to determine response. The European Association for the Study of the Liver has issued new criteria to assess viability of remaining tumor based on enhancing residual volume by multiphase CT or MRI.152 However, the field is rapidly changing and there is no consensus on the optimal imaging strategy following loco-regional therapy.

Recent meta-analyses of randomized controlled trials comparing low-intensity and high-intensity surveillance programs have shown advantages for more intense follow-up in Stages I-III disease;170-173 however, controversies remain regarding the optimal surveillance strategy. “

Lymphoma Imaging

To be followed…

Other research papers related to the management of Colorectal cancer were published on this Scientific Web site:

PIK3CA mutation in Colorectal Cancer may serve as a Predictive Molecular Biomarker for adjuvant Aspirin therapy

Personalized Medicine: Cancer Cell Biology and Minimally Invasive Surgery (MIS)

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