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Old 07-29-2011, 05:01 PM
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Default Systems Biology Is The Future Of Medical Research

Crucial breakthroughs in the treatment of many common diseases such as diabetes and Parkinson's could be achieved by harnessing systems biology, according to scientists from across Europe. In a Science Policy Briefing released today by the European Science Foundation, they provide a detailed strategy for the application of systems biology to medical research over the coming years.

Systems biology is a rapidly advancing field that combines empirical, mathematical and computational techniques to gain understanding of complex biological and physiological phenomena. For example, dozens, or even hundreds, of proteins can be involved in signalling processes that ensure the proper functioning of a cell. If such a signalling network is disturbed in any way, diseases such as cancer and diabetes can result.

Conventional approaches of biology do not have the capacity to unravel these elaborate webs of interactions, which is why drug design often fails. Simply knocking out one target molecule in a biochemical pathway is turning out to be a flawed strategy for drug design, because cells are able to find alternative routes. It is a similar scenario to setting up a roadblock: traffic will grind to a standstill for a short time, but soon motorists will start turning around and using side-roads to get to their destination. Just as the network of roads allows alternative routes to be used, the network of biochemical pathways can enable a disease to by-pass a drug.

Systems biology is now shedding light on these complex phenomena by producing detailed route maps of the subcellular networks. These will make it possible for scientists to develop smarter therapeutic strategies - for example by disrupting two or three key intersections on a biochemical network. This could lead to significant advances in the treatment of disease and help with the shrinking pipeline of pharmaceutical companies using traditional reductionist approaches to drug discovery.

The new policy document, produced by the Life Sciences and Medical Sciences units of the Strasbourg-based European Science Foundation (ESF) calls for a co-ordinated strategy towards systems biology across Europe. The scientists have pinpointed several key disease areas that are ripe for a systems biology approach. These include cancer and diabetes, inflammatory diseases and disorders of the central nervous system.

The report's authors state that the recommendations outlined in the Science Policy Briefing provide a more specific, practical guide towards achieving major breakthroughs in biomedical systems biology, thereby covering issues that had not been previously addressed in sufficient detail. In particular we identify and outline the necessary steps of promoting the creation of pivotal biomedical systems biology tools and facilitating their translation into crucial therapeutic advances.

The report highlights some recent successes where mathematical modelling has played a key role. The conclusions from these examples are that success was achieved when quantitative data became available; that even simple mathematical models can be of practical use and that the interdisciplinary process leading to the formulation of a model is in itself of intrinsic value.

The report's authors believe that, if this document succeeds in prodding European institutions into supporting systems biology, the implementation of the recommendations presented will propel Europe to the forefront of research in systems biology and, in particular, help this interdisciplinary field to fulfil its promise of making a reality of personalised medicine, combinatorial therapy, shortened drug discovery and development, better targeted clinical trials and reduced animal testing.

This Science Policy Briefing is the contribution of the ESF to the EC funded Specific Support Action entitled "Advancing Systems Biology for Medical Applications" (SSA LSSG-CT-2006-037673). The recommendations resulted from ten workshops, in which more than 110 acknowledged experts from across Europe participated.
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Old 07-29-2011, 05:03 PM
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Default Systems Biology in Cancer Drug Selection

One of the hallmarks of cancer is the complex interaction of genes, networks, and cells in order to initiate and maintain a cancerous state. This inherent complexity constantly challenges our ability to develop effective and specific treatments. A systems biology approach towards the understanding and treatment of cancer examines the many components of the disease simultaneously.

Genes do not operate alone within the cell but in an intricate network of interactions. The cell is a system, an integrated, intereacting network of genes, proteins and other cellular constituents that produce functions. One needs to analyze the systems' response to drug treatments, not just one or a few targets (pathways/mechanisms).

Sequencing the genome of cancer cells is explicitly based upon the assumption that the pathways - network of genes - of tumor cells can be known in sufficient detail to control cancer. Each cancer cell can be different and the cancer cells that are present change and evolve with time.

There are many pathways/mechanisms to the altered cellular (forest) function, hence all the different "trees" which correlate in different situations. Improvement can be made by measuring what happens at the end (the effects on the forest), rather than the status of the indivudal trees.

Dealing with genome-scale data in this context requires of its functional profiling, but this step must be taken within a systems biology framework, in which the collective properties of groups of genes are considered.

The importance of mechanistic work around targeted therapy as a starting point should be downplayed in favor of a systems biology approach were compounds are first screened in cell-based assays, with mechanistic understanding of the target coming after validation of its impact on the biology of the cancer cells.

What would be more beneficial is to measure the net effect of all processes within the cancer (cell-based functional profiling), acting with and against each other in real-time, and test living (fresh) cells actually exposed to drugs and drug combinations of interest. The key to understanding the genome is understanding how cells work. How is the cell being killed regardless of the mechanism.

Like the various influences on a flower seed that cause one blossom to turn out differently from another, there are biological processes in the body that affect the development of cancer in each patient and determine how that patient's cancer cells will uniquely react to treatment.

Source: Cell Function Analysis
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Old 08-14-2011, 06:44 PM
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Default 'Systems biology' study of breast cancer

Using a 'systems biology' approach, which focuses on understanding the complex relationships between biological systems, to look under the hood of an aggressive form of breast cancer, researchers for the first time have identified a set of proteins in the blood that change in abundance long before the cancer is clinically detectable.

The findings, by co-authors Christopher Kemp, Ph.D., and Samir Hanash, M.D., Ph.D., members of Fred Hutchinson Cancer Research Center's Human Biology and Public Health Sciences divisions, respectively, were published in the August 1, 2011 issue of Cancer Research.

Studying a mouse model of HER2-positive breast cancer (cancer that tests positive for a protein called human epidermal growth factor receptor 2) at various stages of tumor development and remission, the researchers found that even at the very earliest stages the incipient tumor cells communicate to normal tissues of the host by sending out signals and recruiting cells, while the host tissues in turn respond to and amplify the signals.

"It is really a 'systems biology' study of cancer, in that we simultaneously examined many genes and proteins over time - not just in the tumor but in blood and host tissues," Kemp said. "The overall surprising thing we found was the degree to which the host responds to cancer early in the course of disease progression, and the extent of that response.

While a mouse - or presumably a human - with early-stage cancer may appear normal, our study shows that there are many changes occurring long before the disease can be detected clinically. This gives us hope that we should be able to identify those changes and use them as early detection tools with the ultimate goal of more effective intervention."

Traditionally, it has been thought that tumor cells shed telltale proteins into the blood or elicit an immune response that can lead to changes in blood-protein levels. "What is new here is that the predominant protein signals we see in blood originate from complex interactions and crosstalk between the tumor cells and the local host microenvironment," Kemp said.

Until now, such tumor/host interactions have been primarily studied one gene at a time locally, within the tumor; this is the first study to monitor the systemic response to cancer in a preclinical tumor model, tracking the abundance of cancer-related proteins throughout tumor induction, growth, and regression. Of approximately 500 proteins detected, up to a third changed in abundance; the number increased with cancer growth and decreased with tumor regression.

"We found a treasure trove of proteins that are involved in a variety of mechanisms related to cancer development, from the formation of blood vessels that feed tumors to signatures of early cancer spread, or metastasis," Kemp said.

Proteins associated with wound repair were most prevalent during the earliest stages of cancer growth, which could point to a potential target for early cancer detection.

"Rather than blindly search for cancer biomarkers, an approach based on comprehensive understanding of the systems biology of the disease process is likely to increase the chances to identify blood-based biomarkers that will work in the clinic," Kemp said.

The next steps will involve selecting the most promising protein candidates found in mice and determining whether the same circulating proteins are markers of early breast cancer development in humans, with the ultimate goal of designing a blood test for earlier breast cancer detection.

Source: Fred Hutchinson Cancer Research Center
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Old 08-18-2011, 01:03 PM
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Default Personalized Cancer Cytometrics More Accurate than Molecular Gene Testing

Clinical Trial Finds Personalized Cancer Cytometrics More Accurate than Molecular Gene Testing

In the first head-to-head clinical trial comparing gene expression patterns with Personalized Cancer Cytometric testing (also known as “functional tumor cell profiling” or “chemosensitivity testing”), Personalized Cancer Cytometrics was found to be substantially more accurate.

In a clinical trial involving ovarian cancer patients, patterns of gene expression identified through molecular gene testing were compared with results of Personalized Cancer Cytometric testing (in which whole, living cancer cells are exposed to candidate chemotherapy drugs). Four different genes were included in the molecular part of the study. The four genes were selected as those which researchers believe to have the greatest likelihood of accurately predicting individual patient response to specific anti-cancer drugs.

Study Results:

For two of the genes studied, there was no significant correlation between gene expression pattern and patient response. In other words, results for these genes were found to be meaningless. For the third gene studied, there was a 75% correlation between expression and patient response. This means that the gene was 75% accurate when it came to identifying an active drug for that patient. For the fourth gene studied, the accuracy in identifying an active drug was only 25%. In marked contrast, Personalized Cancer Cytometric testing was found by the researchers to be 90% accurate in identifying active drugs for ovarian cancer patients in this study.

Discussion:

Molecular testing – that is, testing for gene expression patterns – is widely studied and heavily promoted as a method to identify effective chemotherapy drugs for individual cancer patients. However, most studies of molecular testing carried-out to date show only modest correlation or no correlation between test results and actual patient response. In other words, much work remains to be done before molecular gene testing can be regarded as an accurate tool for chemotherapy selection. And yet in this, first ever, head-to-head study of test accuracy, Personalized Cancer Cytometrics was found to be highly accurate when it came to identifying effective drugs.

Comparing this study with previous studies:

Although this was the first head-to-head trial, the accuracy levels found in this trial for Personalized Cancer Cytometric testing are strikingly consistent with those documented in dozens of previous studies, published by respected cancer researchers around the world. In those studies, as in this one, extremely high levels of correlation (in other words, high levels of test accuracy) were found for Personalized Cancer Cytometrics.

Arienti et al. Peritoneal carcinomatosis from ovarian cancer: chemosensitivity test and tissue markers as predictors of response to chemotherapy. Journal of Translational Medicine 2011, 9:94.

[url]http://www.translational-medicine.com/content/9/1/94
[url]http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141502/
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Old 08-18-2011, 04:26 PM
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Default The Future of Cancer Research Lies Behind Us

The TED (Technology Entertainment Design) conferences have been held annually for almost two decades. It draws together innovators in a broad spectrum of disciplines. With invited speakers ranging from Harvard's Edward O. Wilson to business leaders like Microsoft's Bill Gates, the lectures cover a panoply of interesting topics.

Dr. Robert Nagourney was invited to present at the TEDxSoCal conference held in Long Beach, CA on July 16th. His interest was to engage this group in a discussion of cancer biology with the focus on biochemistry and metabolism. His lecture was timely in the context of the New York Times article on the failures of genomics platforms for cancer treatment.

Over the past year, there has been a growing recognition that genomic analyses are not providing the therapeutic insights that patients so desperately need. The Duke University lung cancer gene program, which received much attention, is emblematic of the hubris associated with contemporary genomic analytic platforms.

Dr. Nagourney has reviewed the contemporary experience in clinical trials, examined the potential pitfalls of gene-based analysis, and described the brilliant work conducted by biochemists and cell biologists, like Hans Krebs and Otto Warburg, who published their seminal observations decades before the discovery of the double helix structure of DNA.

He described insights gained using the cell-based funtional profiling analytic platform, that lead to treatments used today around the world, all of which were initially discovered using cell-based studies. More interesting still will be the opportunity to use these platforms to explore the next generation of cancer therapies – those treatments that influence the cell at its most fundamental level – its metabolism.

Much like genomics aims to unravel the structure of the genome, metabolomics focuses on understanding the many small molecule metabolites that result from a cell’s metabolic processes.

There are an estimated 5,000 - 20,000 endogenous human metabolites, and analysing their production gives an accurate picture of the physiology of a cell at a given moment in time. Whereas the cell’s genotype can predict its physiology to a limited extent, metabolomics also takes phenotype – and therefore environmental conditions – into account, allowing a more precise measure of actual cell physiology.

For research, the study of metabolomics provides the means to measure the effects of a variety of stimuli on individual cells, tissues, and bodily fluids.

By studying how their metabolic profiles change with the introduction of chemicals or the expression of known genes, for example, researchers can more effectively study the immediate impact of disease, nutrition, pharmaceutical treatment, and genetic modifications while using a systems biology approach.

[url]http://www.guidetocancertreatment.com/

Metabolomics is a newly emerging field of "omics" research concerned with the comprehensive characterization of the small molecule metabolites in biological systems. It can provide an overview of the metabolic status and global biochemical events associated with a cellular or biological system.

An increasing focus in metabolomics research is now evident in academia, industry and government, with more than 500 papers a year being published on this subject. Indeed, metabolomics is now part of the vision of the NIH road map initiative (E. Zerhouni (2003) Science 302, 63-64&72).

Many other government bodies are also supporting metabolomics activities internationally. Studying the metabolome (along with other "omes") will highlight changes in networks and pathways and provide insights into physiological and pathological states.

The concept of Systems Biology and the prospect of integrating transcriptomics, proteomics, and metabolomics data is exciting and the integration of these fields continues to evolve at a rapid pace. Developments in informatics, flux analysis and biochemical modeling are adding new dimensions to the field of metabolomics.

To be able to walk from genetic or environmental perturbations to a phenotype to a specific biochemical event is exciting. Metabolomics has the promise to enable detection of disease states and their progression, monitor response to therapy, stratify patients based on biochemical profiles, and highlight targets for drug design.

The metabolomics field builds on a wealth of biochemical information that was established over many years.

The Metabolomics Society

http://www.youtube.com/watch?v=mAGhNhrHMJs
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Old 09-02-2011, 05:02 PM
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Default Cancer’s Secrets Come Into Sharper Focus

An article in the New York Times, "Cancer's Secrets Come into Sharper Focus" examined the growing complexity of cancer research. This article explored the growing realization that human biology is not linear.

Included were references to the groundbreaking work of Pier Paolo Pandolfi. It also described the interaction between the human body and its microbial flora. We have long recognized that human health is, in part, associated with our interaction with microbes in our environment.

The gastrointestinal tract has numerous species that are increasingly believed to contribute to our health. The growing field of probiotics, wherein people consume “healthy organisms,” has gone from quackery to community standard in less than a decade.

Dr. Robert Nagourney put this in context back in May, on his blog. Dr. Pandolfi’s findings suggest that the 2 percent of the human genome that codes for known proteins (the part that everyone currently studies) represents only 1/20 of the whole story. One of the most important cancer related genes (PTEN), is under the regulation of 250 separate, unrelated genes. Thus, PTEN, KRAS and all genes, are under the direct regulation and control of genetic elements that no one has ever studied.

This observation represents one more nail in the coffin of unidimensional thinkers who have attempted to draw straight lines from genes to functions. This further suggests that attempts on the part of gene profilers to characterize patients likelihoods of response based on gene mutations are not only misguided but, may actually be dishonest.

The need for phenotype analyses like the functional profiling performed at Rational Therapeutics has never been greater. As the systems biologists point out, complexity is the hallmark of biological existence. Attempts to oversimplify phenomena that cannot be simplified, have, and will continue to, lead us in the wrong direction.

Cancer biology does not conform to the dictates of molecular biology. Genotype does not equal phenotype. Genes do not operate alone within the cell but in an intricate network of interactions. The particular sequence of DNA that an organism possess (genotype) does not determine what bodily or behaviorial form (phenotype) the organism will finally display. Among other things, environmental influences can cause the suppression of some gene functions and the activation of others. Out knowledge of genomic complexity tells us that genes and parts of genes interact with other genes, as do their protein products, and the whole system is constantly being affected by internal and external environmental factors.

The gene may not be central to the phenotype at all, or at least it shares the spotlight with other influences. Environmental tissue and cytoplasmic factors clearly dominate the phenotypic expression processes, which may in turn, be affected by a variety of unpredictable protein-interaction events. This view is not shared by all molecular biologists, who disagree about the precise roles of genes and other factors, but it signals many scientists discomfort with a strictly deterministic view of the role of genes in an organism's functioning.

Until such time as cancer patients are selected for therapies predicated upon their own unique biology, we will confront one targeted drug after another. Our solution to this problem has been to investigate the targeting agents in each individual patient's tissue culture, alone and in combination with other drugs, to gauge the likelihood that the targeting will favorably influence each patient's outcome. Functional profiling results to date in patients with a multitude type of cancers suggest this to be a highly productive direction.

The endpoints (point of termination) of molecular profiling are gene expression, examining a single process (pathway) within the cell or a relatively small number of processes (pathways) to test for "theoretical" candidates for targeted therapy.

The endpoints of functional profiling are expression of cell-death, both tumor cell death and tumor associated endothelial (capillary) cell-death (tumor and vascular death), and examines not only for the presence of the molecular profile but also for their functionality, for their interaction with other genes, proteins and other processes occuring within the cell, and for their "actual" response to anti-cancer drugs (not theoretical susceptibility).

A few labs, like Rational Therapeutics and Weisenthal Cancer Group, utilize functional profiling, because cancer dynamics are not linear.

Literature Citation: Poliseno, L., et al. 2010. A coding-independent function of gene and pseudogene mRNAs regulates tumor biology. Nature. 2010 Jun 24; 465(7301):1016-7.)

[url]http://www.nytimes.com/2011/08/16/health/16cancer.html?_r=1&pagewanted=all
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Old 09-16-2011, 09:16 AM
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Default Hedgehog Signaling is a Potent Regulator of Angiogenesis

Blocking the embryonic signalling pathway, known as Hedgehog (Hh), could form a basis of new treatments. By using drugs to inhibit the Hedgehog signalling, they should be able to increase the effectiveness of chemotherapy and reduce the risk of cancer relapse.

Erivedge (vismodegib) is such a drug that inhibits Hh signaling by targeting the serpentine receptor Smoothened (SMO), and has produced promising anti-tumor responses in clinical studies of cancers driven by mutations in this pathway.

Cancer stem cells (CSCs), are aggressive cells thought to be resistant to current anti-cancer therapies and which promote metastasis, are stimulated via a pathway that mirrors normal stem cell development. Disrupting the pathway, researchers are able to halt expansion of CSCs.

One approach is to force the CSCs into a differentiated state, thereby impairing stem characteristics, such as self-renewal. Interference with the Notch, Wnt, or Hedgehog pathways that are thought to regulate differentiation, are strategies that have been proposed.

Cell-based functional profiling labs have recognized the interplay between cells, stroma, vascular elements, cytokines, macrophages, lymphocytes and other environmental factors. This lead to their focus on the human tumor primary culture microspheroid (microclusters), which contains all of these elements.

In their earlier work, they endeavored to isolate tumor cells from their benign constituents so as to study “pure” tumor cells. As time went on, however, they found that these disaggregated cells were artificially sensitized to the effects of chemotherapy and provided false positive results in vitro.

Early work by Beverly Teicher and Robert Kerbel that examined cells alone and in three-dimensional (3D) structures, lead to the realization that cancer cells inhabit a microenvironment. Functional profiling labs now study cancer response to drugs within this microenvironment, enabling them to provide clinically relevant predictions to cancer patients.

It is their capacity to study human tumor microenvironments that distinguishes them from other lab platforms in the field. And, it is this capacity that enables them to conduct discovery work on the most sophisticated classes of compounds that influence cell signaling at the level of notch, hedgehog and WNT, among others (Gonsalves, F, et al. (2011).

An RNAi-based chemical genetic screen identifies three small-molecule inhibitors of WNT/wingless signaling pathway (PNAS vol. 108, no. 15, pp. 5954-5963). With this clinically validated platform they are now positioned to streamline drug development and advance experimental therapeutics.

Source: Dr. Robert Nagourney; Rational Therapeutics, Inc.

[url]http://www.rational-t.com/downloads/pdfs/WNT_Inhibitor.pdf
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Old 09-22-2011, 12:20 PM
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Default Research in Combining Targeted Agents Faces Numerous Challenges

In a conference sponsored by the Institute of Medicine, scientists representing both public and private institutions examined the obstacles that confront researchers in their efforts to develop effective combinations of targeted cancer agents.

In a periodical published by the American Society of Clinical Oncology (ASCO) in their September 1, 2011 issue of the ASCO Post, contributor Margo J. Fromer, who participated in the conference, wrote about it.

[url]http://www.ascopost.com/articles/september-1-2011/research-in-combining-targeted-agents-faces-numerous-challenges.aspx

One of the participants, Jane Perlmutter, PhD, of the Gemini Group, pointed out that advances in genomics have provided sophisticated target therapies, but noted, “cellular pathways contain redundancies that can be activated in response to inhibition of one or another pathway, thus promoting emergence of resistant cells and clinical relapse.”

James Doroshow, MD, deputy director for clinical and translational research at the NCI, said, “the mechanism of actions for a growing number of targeted agents that are available for trials, are not completely understood.”

He went on to say that the “lack of the right assays or imaging tools means inability to assess the target effect of many agents.” He added that “we need to investigate the molecular effects . . . in surrogate tissues,” and concluded “this is a huge undertaking.”

Michael T. Barrett, PhD, of TGen, pointed out that “each patient’s cancer could require it’s own specific therapy.” This was followed by Kurt Bachman of GlaxoSmithKline, who opined, “the challenge is to identify the tumor types most likely to respond, to find biomarkers that predict response, and to define the relationship of the predictors to biology of the inhibitors.”

What they were describing was precisely the work that clinical oncologists involved with cell culture assays have been doing for the past two decades. One of those clinicians, Dr. Robert Nagourney felt that there had been an epiphany.

The complexities and redundancies of human tumor biology had finally dawned on these investigators, who had previously clung unwaiveringly to their analyte-based molecular platforms.

The molecular biologists humbled by the manifest complexity of human tumor biology had finally recognized that they were outgunned and whole-cell experimental models had gained the hegemony they so rightly deserved.

Source: Dr. Robert A. Nagourney, medical director, Rational Therapeutics and instructor in Pharmacology at the University of California, Irvine School of Medicine.
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Old 09-23-2011, 08:06 AM
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Default Novel Translational Research Presented

Anna Azvolinsky, PhD
Cancernetwork.com

Hani Gabra, Professor of Medical Oncology at the Department of Surgery & Cancer at the Imperial College in London gave a talk during the EUTROC/ENTRIGO session at the ESGO meeting on Sunday September 11, 2011. The European Network for Translational Research in Ovarian Cancer (EUTROC) was created to improve the current and future management of ovarian cancer ([url]http://www.eutroc.org). The goal of EUTROC is to create a multidisciplinary platform by bringing together the complexity of basic science to study the mechanism underlying ovarian cancer and its progression with its application through patient clinical trials. Essentially, EUTROC brings translational researchers in Europe together to facilitate “bench to bedside” research and vice versa.

Professor Gabra stressed the importance of translational research in light of the current hurdles that face ovarian cancer researchers. These include a lack of an integrated, "systems biology" approach to the study of ovarian cancer, a lack of a translation from basic science to clinical studies, and a lack of ovarian cancer models to study the mechanism of the disease. He presented the goals of the European Network of Translational Research In Gynaecological Oncology (ENTRIGO), which was formed through ESGO as being: to establish a network of biobanks of patient samples to facilitate research, and to focus on new predictive/prognostic biomarker development in order to facilitate the monitoring of treatment and execute clinical trials that take advantage of the biobanks and biomarker research. The long-term goal of ENTRIGO is to develop at least two innovative tests, techniques or devices, which will be applied to clinical routine care for women-specific cancers within the next 10 years.

“We don’t do well in turning our science into new patient benefit,” said Professor Gabra, and stressed the importance of well-executed, enhanced larger scale phase 2 trials, on the order of 100 to 250 patients, that will test hypotheses and include target validation. These trials, according to Professor Gabra, should be performed in both academic centers and the community in order to better integrate community oncologists into innovative research. “We need to develop information to design better effective pivotal trials,” he stated. Importantly, these trials should provide a firm “go/no go” decision for large-scale phase 3 development.

He believes that the effort should focus on predictive algorithms, which can help determine whether a patient will respond to a specific treatment, in order to enrich a clinical trial population and see a real and lasting effect of a treatment, rather than concentrating on prognostic factors.

Professor Gabra presented his translational, unpublished work on the “mechanisms of chemotherapy resistance in ovarian cancer." The research focuses on using cell lines; the hypothesis is that platinum-sensitive clones within the tumor exist prior to treatment and are enriched following relapse after a platinum-based chemotherapy regimen. The idea is that at relapse, the disease that manifests is a second disease from a dominant clone that has existed, but in smaller numbers, during the original presentation of the cancer. Because ovarian cancer comes back in over 70% of patients, research to understand the underlying mechanism of chemotherapy resistance is highly important. So far, the research shows that the AKT pathway is activated in platinum-resistance ovarian cancer cells.

“AKT does something very different in the platinum-resistant cells but not in isogenic platinum-sensitive cells…and this is not a PI3 kinase dependent AKT change. So this means that we need to think differently about treatment in platinum-resistant disease. PI3 kinase drugs are not interchangeable in platinum sensitive and platinum-resistant cells” he explained. The current focus of the research is to further understand the AKT-based mechanism of resistance and to begin clinical trials with various targeted agents to test their hypotheses.

Classification of epithelial ovarian cancer

During the plenary session, on Monday September 12, 2011, Dr. Charlie Gourley of the University of Edinburgh Cancer Research Centre presented novel research on ways to differentiate epithelial ovarian cancer (EOC), which is mostly treated as a single disease but is in fact an histologically and phenotypically heterogeneous group of diseases. Microarray expression analysis of EOC samples demonstrated six different subgroups of EOC that were linked to their underlying histology and overall survival. The serous subtype was highly correlated with vasculature development and the angiogenesis process. The overall goal of the research is to identify new molecular subgroups of EOC to take advantage of their unique characteristics for targeted treatments. For example, the angiogenesis genes that appear to be upregulated in the serous EOC subtype may be linked to this type of tumor’s response to bevicizumab, seen in the GOG218 and ICON7 trials.

Detecting and characterizing circulating tumor cells

At the late-breaking oral presentation session on Wednesday, September 14, 2011, researcher Eva Obermayr of the Department of Obstetrics and Gynecology, Medical University of Vienna presented a talk on the molecular markers used to detect circulating tumor cells (CTCs) in ovarian cancer patients.

CTCs are generally precursors to metastatic lesions, have a clinical impact in cancers, and have been detected in breast, colorectal, lung, and liver cancers, among others but are not well-studied in ovarian cancer. The challenge of their detection is that they are rare events among white blood cells and better enrichment and detection technologies are needed in order to identify them.

The overall goal of the study is to find early molecular traces that may indicate recurrence of ovarian cancer. Peripheral blood samples from ovarian cancer and healthy subjects as well as tumor tissue were taken and subjected to a whole genome expression. 11 genes that were highly expressed in the tumor tissue but not in the normal tissues were measured in the blood fraction of cancer patients with advanced EOC, both before primary treatment and after adjuvant chemotherapy. CTCs were detected in ~25% of the pre-treatment patients and ~20% of the post-treatment samples. CTC presence was correlated with sub-optimal debulking and presence of ascites before treatment. After treatment, CTCs occurred more often in older age patients (P = 0.016), those with a higher FIGO stage of cancer (P = 0.035), and those with chemo-resistant disease (P = 0.035).

Cyclophilin C (CypC) was the most frequently overexpressed gene marker in both pre-treated and post-treated samples, followed by the GPX8 (probably glutathione peroxidase 8) gene in the pre-treated samples. CYpC functions in protein folding and apoptosis. Overexpression of CypC in cancer cells has been previously shown to result in resistance to hypoxia and cisplatin-induced cell death.

Patients with CPC-positive disease generally had a shorter disease free (pre-therapeutic, P= 0.033; post-therapeutic, P = 0.046) and overall survival (pre-therapeutic, P = 0.018; post-therapeutic, P = 0.104). CTC presence was an independent prognostic factor for shorter disease-free survival and overall survival (pre-therapeutic P = 0.014, post-therapeutic P = 0.129). The authors concluded that the presence of CTCs in ovarian cancer patients results in an overall worse outcome and further characterization and utility of CTCs as a marker of prognosis are ongoing.
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Old 09-26-2011, 01:41 PM
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Default The Systems Biology Approach

I am familiar with the "systems biology" approach, the contribution of the ESF to the EC funded Specific Support Action entitled "Advancing Systems Biology for Medical Applications" (SSA LSSG-CT-2006-037673). Systems biology is the future of medical research.

In regards to predictive algorithms which can help determine whether a patient will respond to a specific treatment, the Bayesian method is not stranger to the technology of cell culture assay testing, a "functional" biomarker. In fact, it is what gives credit to the accuracy of these assays tests.

Traditionally, in-vitro (in lab) "cell-lines" have been studied in 2 dimensions (2D), which has inherent limitations in applicability to real life 3D in-vivo (in body) states. Researchers at Johns Hopkins and Washington University at St. Louis had found out, our body is 3D, not 2D in form. Older assay technology was in 2D form. Other researchers have pointed to the limitations of 2D "cell-line" study and chemotherapy to more correctly reflect the human body.

Established "cell-lines" have been a huge disappointment over the decades, with respect to their ability to correctly model the disease-specific activity of new drugs. What works in "cell-lines" do not often translate into human beings. You get different results when you test passaged cells compared to primary, "fresh" tumor.

There has been cutting-edge techniques that have made the cell-based functional profiling platform mimic what will happen in the human body. Cancer is already in 3D (3 dimensional) conformation. Cell-based functional profiling cultures "fresh" live tumor cells in 3D conformation and profiles the function of cancer cells (is the whole cell being killed regardless of the targeted mechanism or pathway).

In regards to platinum resistance, cell-based functional profiling provides a window on the complexity of cellular biology in real-time, gauging tumor cell response to chemotherapies (conventional and targeted). By examining drug induced cell death, functional analyses measure the cumulative result of all of a cell's mechanisms of resistance and response acting in concert. Functional profiling approximates the cancer of the "individual" not populations.

Platinum resistance is just a clinical term applied to those who relapse within 6 months of platinum-based therapy, based on some population based studies. Even in those patients who relapse within 6 months, platinum-based combinations may prove effective if they play upon the "resistance" mechanisms deemed operative.

For example: Topol upregulation can confer collateral sensitivity to Topoisomerase inhibitors; ERCC1 upregulation can confer collateral sensitivity to antimetabolites. Upregulation is the increase in the number of receptors on the surface of target cells, making the cells more sensitive to an agent.

The need for phenotype analyses like the functional profiling performed has never been greater. As the systems biologists point out, complexity is the hallmark of biological existence. Attempts to oversimplify phenomena that cannot be simplified, have, and will continue to, lead us in the wrong direction.

Genotype does not equal phenotype. Genes do not operate alone within the cell but in an intricate network of interactions. The particular sequence of DNA that an organism possess (genotype) does not determine what bodily or behaviorial form (phenotype) the organism will finally display.

Among other things, environmental influences can cause the suppression of some gene functions and the activation of others. Out knowledge of genomic complexity tells us that genes and parts of genes interact with other genes, as do their protein products, and the whole system is constantly being affected by internal and external environmental factors.

CTC (circulating tumor cell) technology is has great potential - for drug selection - ten or twenty years down the road, and they should continue to try and make strides. However - in drug selection - there is a problem with growing or manipulating tumor cells in any way. When looking for cell-death-related events, which mirror the effect of drugs on living tumors, cells are generally not grown or amplified in any way. The object is occurrence of programmed cell death in cells that come into contact with therapeutic agents.

How do you aggregate a sufficient number of cancer cells to make accurate determinations? Detectable tumor cells in the peripheral blood are present only in extremely small numbers. This precludes allowing a sufficient number of cells to incubate for a few days in the presence of chemotherapeutic agents. Analysis of a relatively small number of isolated cancer cells cannot yield the same quality information as subjecting living cells to chemotherapeutic agents, begging the question of whether or not it can accurately predict which drugs will work and which will not.

CTCs are free-floating cancer cells that can remain in isolation from a tumor for over twenty years. What is the relationship of such long-lasting cells to the tumor cells that need to be attacked through tested substances? Then there is the question of heterogeneity.

The original Immunicon research team really became known for their ability to track and isolate circulating tumor, endothelial, immune and other disease associated circulating cell populations and then using every tool available to further characterize them. The problem they know is the heterogeneity of all these cell populations is greater than any one thought thus defining and characterizing them is more difficult as is finding them - also finding vital ones - as many if not most are dead or dying - this is one of the reasons why the metastatic process is so inefficient.

Tumors in the body are genetically variable. What is the relationship between CTCs and primary tumors or their already established metastases? It has already been established that the gene expression profile of a metastatic lesion can be different compared to that of the primary. In short, CTC technology is not ready for prime time - in regards to drug selection. However, the number of cells discovered in the CTC technique has turned out to be a good prognosticator of how well empiric or even assay-directed treatments are working.

Basically, CTC labs use "negative selection" to isolate alleged circulating tumor cells. What that means is methods to "selectively" remove circulating normal cells, such as monocytes, lymphocytes, neutrophils, circulating endothelial cells, etc. The problem is that these normal cells outnumber circulating tumor cells by a factor of a million to one, and no "negative selection" procedure (or combination of procedures) can possibly strip away all the normal cells, leaving behind a relatively pure population of tumor cells.

What you have to do is to use a "positive selection" procedure, meaning selectively extracting the tumor cells out of the vastly larger milieu of normal cells. The problem is, when you do this, there is only a teeny tiny yield of tumor cells:

Here's from Wikipedia:

Circulating tumor cells are found in frequencies on the order of 1-10 CTC per mL of whole blood in patients with metastatic disease. For comparison, a mL of blood contains a few million white blood cells and a billion red blood cells.

So, from a typical 7 ml blood draw into a purple top tube, you are going to get, on average, 7 to 70 tumor cells -- total. This may be sufficient for certain molecular type tests (although the degree to which this tiny sample of cells is representative may be questioned), but it isn't nearly sufficient to test even a single drug in a cell culture assay, where one requires millions of cells for quality testing, including requirements for negative and positive controls.

Source: Cell Function Analysis
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Gregory D. Pawelski

Last edited by gdpawel : 10-21-2012 at 11:57 AM. Reason: additional info
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