'Systems biology' study of breast cancer

[News]

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.

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[gdpawel]

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.

[gdpawel]

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

[gdpawel]

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

[gdpawel]

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.

http://www.translational-medicine.com/content/9/1/94

[gdpawel]

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.

http://www.guidetocancertreatment.com/
or
http://www.youtube.com/watch?v=mAGhNhrHMJs

[gdpawel]

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.)

http://www.nytimes.com/2011/08/16/he...pagewanted=all

[gdpawel]

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.

[gdpawel]

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.

http://www.ascopost.com/articles/sep...hallenges.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. He posted about this on his blog.

[gdpawel]

Researchers at Columbia University Medical Center (CUMC) and two other institutions have uncovered a vast new gene regulatory network in mammalian cells that could explain genetic variability in cancer and other diseases. The studies appear in the online edition of Cell.

"The discovery of this regulatory network fills in a missing piece in the puzzle of cell regulation and allows us to identify genes never before associated with a particular type of tumor or disease," said Andrea Califano, PhD, professor of systems biology, director of the Columbia Initiative in Systems Biology, and senior author of the CUMC research team.

For decades, scientists have thought that the primary role of messenger RNA (mRNA) is to shuttle information from the DNA to the ribosomes, the sites of protein synthesis. However, these new studies suggest that the mRNA of one gene can control, and be controlled by, the mRNA of other genes via a large pool of microRNA molecules, with dozens to hundreds of genes working together in complex self-regulating sub-networks.

The findings have the potential to broaden investigations into how tumors develop and grow, who is at risk for cancer, and how to identify and inactivate key molecules that encourage the growth and spread of cancer.

For example, in the case of the phosphatase and tensin homolog gene (PTEN), a major tumor suppressor, deletions of its mRNA network regulators in patients appear to be as damaging as mutations of the gene itself in several types of cancer, the studies show.

The newly identified regulatory network (called the mPR network by the CUMC investigators) allows mRNAs to communicate through small bits of RNA called microRNAs. Researchers first realized about a decade ago that microRNAs, by binding to complementary genetic sequences on mRNAs, can prevent those mRNAs from making proteins. Turning this concept on end, the new studies reveal that mRNAs actually use microRNAs to influence the expression of other genes.

When two genes share a set of microRNA regulators, changes in expression of one gene affects the other. If, for instance, one of those genes is highly expressed, the increase in its mRNA molecules will "sponge up" more of the available microRNAs. As a result, fewer microRNA molecules will be available to bind and repress the other gene's mRNAs, leading to a corresponding increase in expression. Although such an effect had been previously elucidated, the range and relevance of this kind of interaction had not been characterized.

"It turns out that this type of microRNA-mediated regulation is commonplace in the cell, and thousands of genes are regulating one another through hundreds of thousands of microRNA-mediated interactions," says Pavel Sumazin, PhD, research scientist in systems biology and a first author of the CUMC paper. "This is similar in size and effect to other regulatory networks, such as transcriptional regulatory networks, where target genes are regulated by transcription factors."

In the CUMC study, Dr. Sumazin and his colleagues analyzed glioblastoma mRNA and microRNA expression data from the Cancer Genome Atlas, a public database, uncovering a regulatory layer comprising more than 248,000 microRNA-mediated interactions.

Looking specifically at the tumor suppressor gene PTEN, the researchers found that it is part of a sub-network of more than 500 genes. Of these genes, 13 are frequently deleted in glioblastoma and seem to work together through microRNAs to stop PTEN activity - achieving the same result as if the tumors had inactivating mutations or deletions of PTEN itself.

The finding explains, at least in part, why all patients with glioblastoma do not share the same genetic profile. In about 80 percent of patients, their tumors have a deletion of PTEN. In most of the remaining 20 percent, PTEN is intact, but the gene is not expressed - an observation that had confounded researchers. "This suggested that there must be some other mechanism by which PTEN can be completely suppressed," said Dr. Sumazin. "Now we know that there are at least 13 other genes - none of which had ever been implicated in cancer - that can 'gang up' on PTEN to suppress its activity, with different combination of deletions in different patients."

"This network helps explain the so-called dark matter of the genome," added Dr. Califano. "For years, scientists have been cataloguing all the genes involved in particular diseases. But if you add up all the genetic and epigenetic alterations that have been identified, even with high-resolution studies, there are still many cases where you cannot explain why a person has the disease. Now we have a new tool for explaining these genetic variations, for gaining a better understanding of the disease and, ultimately, for finding new treatments."

Source: Columbia University Medical Center. "Gene Expression In Cancer Regulated By Vast Hidden Network." (2011, October 17)

[gdpawel]

Systems biology is a holistic approach to the study of how a living organism emerges from the interactions of the individual elements that make up its constituent cells. Embracing a broad range of disciplines, this field of science that is just beginning to come into public prominence holds promise for advances in a number of important areas, including safer, more effective pharmaceuticals, improved environmental remediation, and clean, green, sustainable energy. However, the most profound impact of systems biology, according to one of its foremost practitioners, is that it might one day provide an answer to the central question: What is life?

Adam Arkin, director of the Physical Biosciences Division of the U.S. Department of Energy (DOE)'s Lawrence Berkeley National Laboratory and a leading computational biologist, is the corresponding author of an essay in the journal Cell which describes in detail key technologies and insights that are advancing systems biology research. The paper is titled "Network News:Innovations in 21st Century Systems Biology." Co-authoring the article is David Schaffer, a chemical engineer with Berkeley Lab's Physical Biosciences Division. Both Arkin and Schaffer also hold appointments with the University of California (UC) Berkeley.

"System biology aims to understand how individual elements of the cell generate behaviors that allow survival in changeable environments, and collective cellular organization into structured communities," Arkin says. "Ultimately, these cellular networks assemble into larger population networks to form large-scale ecologies and thinking machines, such as humans."

In their essay, Arkin and Schaffer argue that the ideas behind systems biology originated more than a century ago and that the field should be viewed as "a mature synthesis of thought about the implications of biological structure and its dynamic organization." Research into the evolution, architecture, and function of cells and cellular networks in combination with ever expanding computational power has led to predictive genome-scale regulatory and metabolic models of organisms. Today systems biology is ready to "bridge the gap between correlative analysis and mechanistic insights" that can transform biology from a descriptive science to an engineering science.

Discoveries in systems biology, the authors say, can generally be divided between those that relied on a "mechanistic approach to causal relationships," and those that relied on "large-scale correlation analysis." The results of these discoveries can also be categorized according to whether they primarily pertained to the principles behind cellular network organization, or to predictions about the behavior of these networks.

"As systems biology matures, the number of studies linking correlation with causation and principles with prediction will continue to grow," Schaffer says. "Advances in measurement technologies that enable large-scale experiments across an array of parameters and conditions will increasingly meld these correlative and causal approaches, including correlative analyses leading to mechanistic hypothesis testing, as well as causal models empowered with sufficient data to make predictions."

As the complete genomes of more organisms are sequenced, and measurement and genetic manipulation technologies are improved, scientists will be able to compare systems across a broader expanse of phylogenetic trees. This, Arkin and Schaffer say, will enhance our understanding of mechanistic features that are necessary for function and evolution.

"The increasing integration of experimental and computational technologies will thus corroborate, deepen, and diversify the theories that the earliest systems biologists used logic to infer," Arkin says. "This will thereby inch us ever closer to answering the What is Life question."

The systems biology research cited in this essay by Arkin and Schaffer was supported by DOE's Office of Science (Biological and Environmental Research), and by the National Institutes of Health.

Source: Lawrence Berkeley National Laboratory

http://www.cell.com/abstract/S0092-8674(11)00245-5

[gdpawel]

The genomic profile is so complicated, with one thing affecting another, that it isn't sufficient and not currently useful in selecting drugs. Because metabolic changes are complex and hard to predict, metabolic profiling will be essential for selecting best treatment.

In drug selection, molecular (genomic) testing examines a single process within the cell or a relatively small number of processes. The aim is to tell if there is a theoretical predisposition to drug response. It attempts to link surrogate gene expression to a theoretical potential for drug activity.

It relies upon a handful of gene patterns which are thought to imply a potential for drug susceptibility. In other words, molecular testing tells us whether or not the cancer cells are potentially susceptible to a mechanism/pathway of attack.

It doesn't tell you if one targeted drug (or combination of targeted drugs) is better or worse than another targeted drug (or combination) which may target a certain or a small number of mechanisms/pathways.

Functional profile testing doesn't dismiss DNA testing, it uses all the information, both genomic and functional, to design the best targeted treatment for each individual, not populations. It tests for a lot more than just a few mutations.

Functional profiling consists of a combination of a (cell morphology) morphologic endpoint and one or more (cell metabolism) metabolic endpoints. It studies cells in small clusters or micro-spheroids (micro-clusters). The combination of measuring morphologic and metabolic effects at the whole cell level.

The cell is a system, an integrated, interacting network of genes, proteins and other cellular constituents that produce functions. One needs to analyze the systems' response to targeted drug treatments, not just a few targets (pathways).

http://www.medicalnewstoday.com/releases/241306.php