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  #11  
Old 12-30-2012, 03:08 PM
gdpawel gdpawel is offline
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Default Next-generation Sequencing

The theory behind so-called next-generation sequencing is that fine needle biopsies provide enough tissue to adequately perform the test. However, according to Dr. Eric Topol, Director, Scripps Translational Science Institute, almost all samples go into formalin-fixed, paraffin-embedded blocks, which "alters" the DNA and makes sequencing quite compromised and difficult.

He said that they get about 250-300 genes, the exons or coding elements in those genes, and reads out any "potential" links to drugs. But the rate-limiting step appears to be getting something beyond these paraffin blocks. He feels that they could do better if they could use either fresh formalin-fixed or frozen tissue samples from a biopsy or surgical specimen.

Recent papers in multiple journals in Nature, Science, Nature Genetics and Cell have shown that with hundreds of tumor samples fully sequenced, no two cancers are the same and a lot of the action is not in the coding elements of the genes per se. Whole genome sequencing cannot do it with the fixed problems that they have with the way samples are handled today.

The reason they use a smaller sample is because the test is based on "cell proliferation" - meaning that a few cancer cells are amplified and grown to generate enough "cloned" cancer cells for testing. These new cell cultures are then exposed to the various chemotherapies to see which ones the cells resist and which ones cause the most to die. The problem with this method is that the "cloning" process can create changes in the cell biology so that the cancer cells may not react the same in the presence of chemotherapy agents as the actual cancer cells in your body will - kind of like creating an artificial environment. It also takes a few weeks longer because of the timeframe to "grow" the cells.

Theoretical objections to this kind of testing are that it is monolayer and is testing a subcultured cell population, and studies by the NCI Navy medical oncology branch did not find that monolayer assays performed on pre-cultured, pre-amplified tumor cells gave clinical relevant results. It is entirely unclear what would be the advantages of this technology over "actual" cell death assay systems performed on three dimensional clusters of non-precultured cells (true fresh tumor cells).

In regards to gene sequencing for drug selection, researchers have realized that cancer biology is driven by signaling pathways. Cells speak to each other and the messages they send are interpreted via intracellular pathways known as signal transduction. Many of these pathways are activated or deactivated by phosphorylations on select cellular proteins.

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.

Although the theory behind inhibitor targeted therapy is appealing, the reality is more complex. Cancer cells often have many mutations in many different pathways, so even if one route is shut down by a targted treatment, the cancer cell may be able to use other routes.

In other words, cancer cells have "backup systems" that allow them to survive. The result is that the drug does not affect the tumor as expected. The cancer state is typically characterized by a signaling process that is unregulated and in a continuous state of activation.

In chemotherapy selection, molecular (genetic) profiling examines a single process within the cell or a relatively small number of processes. All a gene mutation study can tell is whether or not the cells are potentially susceptible to a mechanism of attack. The aim is to tell if there is a theoretical predisposition to drug response.

It doesn't tell you the effectiveness of one drug (or combination) or any other drug which may target this in the individual. There are many pathways to altered cellular function. Functional cytometric profiling measures the end result of pathway activation or deactivation to predict whether patients will actually respond (clinical responders).

It measures what happens at the end, rather than the status of the individual pathway, by assessing the activity of a drug (or combinations) upon combined effect of all cellular processes, using combined metabolic and morphologic endpoints, at the cell population level, measuring the interaction of the entire genome.

In laying the foundation for personalized cancer treatment using DNA sequencing, the ultimate 'driver' is functional cytometric profiling.

The assumption behind all these recent genomic efforts has been the gene mutation theory of cancer. Mutated genes somehow either cause cancer directly or inactivategenes though to guard against cancer, the so-called oncogenes and tumor suppressor genes.

However, there is no functional proof that the gene mutation theory is correct. Only 1 to 2 percent of the genome consists of genes. DNA is not the whole story.

Cells speak to each other and the messages they send are interpreted via intracellular pathways. You wouldn't know this using genotype analysis (molecular profiling). Phenotype analysis (functional cytometric profiling) provides the window. It can test various cell-death signaling pathways downstream.

While most scientists use genotype platforms to detect mutations in these pathways that might result in response to chemicals, phenotype platforms have taken a different tack. By applying cell functional analysis, to measure the end result of pathway activation or deactivation, it can predict whether patients will "actually" respond, not theoretical susceptibility.

Even if cancers are from the same tissue, and are generated with the same carcinogen, they are never the same. There is always a cytogenetic and a biochemical individuality in every cancer.

The phenotype platform has the capacity to measure genetic and epigenetic events as a functional, real-time adjunct to static genotype platforms. The "key" to understanding the genome is understanding how cells work. The ultimate "driver" is functional cytometric profiling.

Sometimes the genetic signal may not be the driver mutation. Other signaling pathways, like passenger mutations, could be operative. Driver mutations are the ones that cause cancer cells to grow, whereas passengers are co-travellers that make no contribution to cancer development. It turns out that most mutations in cancers are passengers. However, buried among them are much larger numbers of driver mutations than was previously anticipated. This suggests that many more genes contribute to cancer development than was thought.

Cells speak to each other and the messaages they send are interpreted via these intracellular pathways. You wouldn't know this using analyte-based genomic and proteomic methodologies. Again, functional cytometric profiling provides the window. It can test various cell-death signaling pathways downstream.

While most scientists use genomic or proteomic platforms to detect mutations in these pathways that might result in response to chemicals, functional cytometric profiling platforms have taken a different tack. By applying functional analysis, to measure the end result of pathway activation or deactivation, they can predict whether patients will actually respond. The platform has the capacity to measure genetic and epigenetic events as a functional, real-time adjunct to static genomic and proteomic platforms.
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  #12  
Old 05-23-2013, 02:59 AM
gdpawel gdpawel is offline
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Default Accuracy and Clinical Utility of In Vitro Cytometric Profiling

This report, shown at the American Society of Clinical Oncology trade show of 2013, showed a 2.02 higher response rate (P < 0.001) and a 1.44 improvement in one year survival (P < 0.02) for patients who received assay-guided therapy. This established the predicative validity of the functional profiling approach.

Accuracy and clinical utility of in vitro cytometric profiling to personalize chemotherapy: Preliminary findings of a systematic review and meta-analysis.

Sub-category: Molecular Diagnostics and Imaging

Category: Tumor Biology

Meeting: 2013 ASCO Annual Meeting

Abstract No: e22188

Citation: J Clin Oncol 31, 2013 (suppl; abstr e22188)

Author(s): Christian Apfel, Kimberly Souza, Cyrill Hornuss, Larry Weisenthal, Robert Alan Nagourney; SageMedic, Inc, Larkspur, CA; Ludwig Maximilians University of Munich, Munich, Germany; Weisenthal Cancer Group, Huntington Beach, CA; Rational Therapeutics, Long Beach, CA

Abstract:

Background:

Cytometric analysis, or in-vitro functional profiling, has been developed as a method to predict tumor response to different drugs with the premise to personalize chemotherapy and improve patient outcomes.

Methods:

We performed a systematic review and a meta-analysis a) of correlative studies using cytometric profiling that reported diagnostic accuracy (sensitivity and specificity) and b) of effectiveness studies comparing patient outcomes when allocated to treatment guided by a cytometric assay versus population-based standard of care. We used Meta-DiSc software to find pooled sensitivity and specificity and analyze the summary receiver operating characteristic (sROC) curve and used Review Manager 5.1 to generate forest plots on overall tumor response (50% or greater decrease in tumor diameter) and on 1-year overall survival.

Results:

We included 28 mostly retrospective trials (n=664) reporting accuracy data and 15 prospective trials (n=1917) reporting therapeutic efficacy data. The accuracy of correlative study revealed an overall sensitivity of 0.922 (95% confidence interval 0.888 to 0.948), specificity of 0.724 (95% CI 0.669 to 0.774) and an area under the sROC curve of 0.893 (SE=0.023, p<0.001). Studies comparing the clinical utility revealed a two-fold overall tumor response for an assay-guided therapy versus standard of care therapy (odds ratio 2.04, 95% CI 1.62 to 2.57, p<0.001). Similarly, patients who received assay-guided therapy compared to those who received standard of care or physician’s choice had a significantly higher 1-year survival rate (OR 1.44, 95% CI 1.06 to 1.95, p=0.02).

Conclusions:

Despite various limitations of individual studies, the aggregate and fairly consistent evidence of these data suggests cytometric profiling to be accurate, to improve overall tumor response, and to increase 1-year patient survival. Given the enormous potential for our society, a well-designed and sufficiently-powered randomized controlled trial is urgently needed to validate these results.

[url]http://meetinglibrary.asco.org/content/118466-132
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  #13  
Old 02-21-2014, 01:40 PM
gdpawel gdpawel is offline
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Default Scientists challenge the genetic interpretation of biology

A proposal for reformulating the foundations of biology, based on the 2nd law of thermodynamics and which is in sharp contrast to the prevailing genetic view, is published in the Journal of the Royal Society Interface under the title "Genes without prominence: a reappraisal of the foundations of biology". The authors, Arto Annila, Professor of physics at Helsinki University and Keith Baverstock, Docent and former professor at the University of Eastern Finland, assert that the prominent emphasis currently given to the gene in biology is based on a flawed interpretation of experimental genetics and should be replaced by more fundamental considerations of how the cell utilises energy. There are far-reaching implications, both in research and for the current strategy in many countries to develop personalised medicine based on genome-wide sequencing.

Is it in your genes?

By "it" we mean intelligence, sexual orientation, increased risk of cancer, stroke or heart attack, criminal behaviour, political preference and religious beliefs, etcetera. Genes have been implicated in influencing, wholly or partly, all these aspects of our lives by researchers. Genes cannot cause any of these features, although geneticists have found associations between specific genes and all of these features, many of which are entirely spurious and a few are fortuitous.

How can we be so sure?

When a gene, a string of bases on the DNA molecule, is deployed, it is first transcribed and then translated into a peptide - a string of amino acids. To give rise to biological properties it needs to "fold" into a protein.

This process consumes energy and is therefore governed by the 2nd law, but also by the environment in which the folding takes place. These two factors mean that there is no causal relationship between the original gene coding sequence and the biological activity of the protein.

Is there any empirical evidence to support this?

Yes, a Nordic study of twins conducted in 2000 showed there was no evidence that cancer was a "genetic" disease - that is - that genes play no role in the causation of cancer. A wider international study involving 50,000 identical twin pairs published in 2012, showed that this conclusion applied to other common disease as well. Since the sequencing of the human genome was completed in 2001 it has not proved possible to relate abnormal gene sequences to common diseases giving rise to the problem of the "missing heritability".

What is the essence of the reformulation?

At the most fundamental level organisms are energy-consuming systems and the appropriate foundation in physics is that of complex dissipative systems. As energy flows in and out and within, the complex molecular system called the cell, fundamental physical considerations, dictated by the 2nd law of thermodynamics, demand that these flows, called actions, are maximally efficient (follow the path of least resistance) in space and time. Energy exchanges can give rise to new emergent properties that modify the actions and give rise to more new emergent properties and so on. The result is evolution from simpler to more complex and diverse organisms in both form and function, without the need to invoke genes. This model is supported by earlier computer simulations to create a virtual ecosystem by Mauno Rönkkö of the University of Eastern Finland.

What implications does this have in practice?

There are many, but two are urgent.

1. to assume that genes are unavoidable influences on our health and behaviour will distract attention from the real causes of disease, many of which arise from our environment;

2. the current strategy towards basing healthcare on genome-wide sequencing, so called "personalised healthcare", will prove costly and ineffective.

What is personalised health care?

This is the idea that it will be possible to predict at birth, by determining the total DNA sequence (genome-wide sequence), health outcomes in the future and take preventive measures. Most European countries have research programmes in this and in the UK a pilot study with 100,000 participants is underway.

Reference: University of Eastern Finland

Citation: "Scientists challenge the genetic interpretation of biology." Medical News Today. MediLexicon, Intl., 21 Feb. 2014.
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  #14  
Old 03-27-2014, 10:19 PM
gdpawel gdpawel is offline
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Default Is It Ethical to Deny Cancer Patients Functional Analyses?

Robert A. Nagourney, M.D.

The ethical standards that govern human experimentation have become an important topic of discussion. Clinical trials are conducted to resolve medical questions while protecting the rights and well-being of the participants. Human subject committees known as Institutional Review Boards (IRB’s) not only confront questions of protocol design and patient protection but also the appropriateness of the questions to be answered. The Belmont Report (1979) defined three fundamental principles i) respect for persons, ii) beneficence and iii) justice. These have been incorporated into regulatory guidelines codified in the code of federal regulations like 45 CFR 46.111. One historical experience offers an interesting perspective upon contemporary oncologic practice.

[url]http://www.hhs.gov/ohrp/humansubjects/guidance/belmont.html

With advances in cardiac surgery in the1970s and 1980s, in both valvular and coronary artery bypass, an alarming amount of post-operative bleeding was being observed. To address this complication an enzyme inhibitor named Aprotinin was developed by Bayer pharmaceuticals. The drug works by preventing the body from breaking down blood clots (thrombolysis). This is critical for the prevention of postoperative bleeding. Concerns regarding its safety led to Aprotinin’s temporary withdrawal from the market, but those have been resolved and the drug is again available.

After Aprotinin’s introduction, clinical trials were conducted to test its efficacy. Initial results were highly favorable as the drug consistently reduced post-op bleeding. By December 1991, 455 patients had been evaluated providing strong statistical evidence that Aprotinin reduced bleeding by more than 70 percent. Despite this, trialists continued to accrue patients to Aprotinin versus “no treatment” studies. By December 1992, more than 2,000 patients had been accrued and by October of 1994, the number had increased to more than 3,800 patients. Yet the 75 percent risk reduction remained entirely unchanged. Thus, 3,400 patients at untold cost and hardship were subjected to the risk of bleeding to address a question that had long since been resolved.

In a 2005 analysis, Dean Fergusson et al, decried that it should have been evident to anyone who cared to review the literature that Aprotinin’s efficacy had been established. Further accrual to clinical trials beyond 1991 only exposed patients to unwarranted risk of bleeding, and had no possible chance of further establishing the clinical utility of the intervention. This stands as a striking lack of consideration for patient well-being. Fergusson’s review raises further questions about the ethics of conducting studies to prove already proven points. With this as a backdrop, it is instructive to examine functional profiling for the prediction of response to chemotherapy.

Beginning in 1997, a cumulative meta-analysis of 34 clinical trials (1,280 patients), which correlated drug response with clinical outcome was reported. Drug sensitive patients had a significantly higher objective response rate of 81 percent over the response rate of 13 percent for those found drug resistant (P < 0.0000001).

[url]http://htaj.com/current.pdf

This was met by the ASCO/Blue Cross-Blue Shield Technology Assessment published in Journal of Clinical Oncology (Schrag, D et al J Clin Oncol, 2004) that cried for further clinical trials. A subsequent meta-analysis correlated the outcome of 1929 patients with leukemia and lymphoma against laboratory results and again showed significantly superior outcomes for assay directed therapy (P <0.001) (Bosanquet AG, Proc. Amer Soc Hematology, 2007).

[url]http://jco.ascopubs.org/content/22/17/3631.full

In response, a second ASCO Guideline paper was published in 2011. (Burstein H et al J Clin Oncol, 2011) Although the authors were forced to concede the importance of the field, they concluded that “participation in clinical trials evaluating these technologies remains a priority.”

[urlhttp://jco.ascopubs.org/content/early/2011/07/18/JCO.2011.36.0354.full.pdf

Most recently we conducted a cumulative meta-analysis of 2581 treated patients that established that patients who receive laboratory “sensitive” drugs are 2.04 fold more likely to respond (p < 0.001) and 1.4 fold more likely to survive one year or more (p <0.02) (Apfel C. Proc Am Soc Clin Oncol 2013).

[url]http://meetinglibrary.asco.org/content/118466-132

Each successive meta-analysis has concluded, beyond a shadow of a doubt, that human tumor functional analyses (e.g. EVA-PCD) identify effective drugs and eliminate ineffective drugs better than any other tool at the disposal of cancer physicians today. Not unlike those investigators who continued to accrue patients to trials testing Aprotinin, long after the result were in, oncologists today continue to clamor for trials to prove something which, to the dispassionate observer, is already patently obvious. If we now pose the question “Is it ethical to deny patients functional analyses to select chemotherapy?” the answer is a resounding No!
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Old 07-08-2014, 09:01 PM
gdpawel gdpawel is offline
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Default Are Genomic Studies Useful in Our Patients?

Cary A. Presant, M.D., FACP

Knowing the gene mutations or polymorphisms in a patient’s tumor should help us in giving the correct therapy. However, the Institute of Medicine report of 9-11-2013 on Cancer Care in Crisis indicates that physicians lack the core competencies to match a tumor’s molecular characteristics to a drug. This implies that the grand trend in oncology to match tumor genomics to therapy is only limited by our lack of core competencies.

But is that truly a defect that oncologists have, or is there too much uncertainty in the genomic testing itself and in commonly accepted interpretations of genetic mutations.

A recent article gives us pause to think about whether genomic studies are ready for use. F. Dewey and coauthors (JAMA 2014; 311: 1035) studied whole genome sequencing in 12 normal people using 2 assays. They showed that there was agreement between the 2 assays of 99% for common genetic variants, but only 57% for small insertion or deletion variants, 66% for protein coding regions, and only 33% for gene mutations that are candidates for inherited disease risks. Furthermore, the 2 assays missed coding 5% and 3.4% of the genes.

How many mutations did these 12 normal individuals have in their normal cells? Amazingly, there were a median per patient of 2,403,504 single nucleotide variants, 583,273 small insertions and deletions, and 120 exonic structural variants. Per patient!

Of course, oncologists have core competencies in understanding molecular changes that are common: ER, PR, Her2, bcr/abl, alk, KRAS, BRAF, BRCA 1 or 2, and Lynch. But with the extraordinary numbers of all mutations found by Dewey et. al., no one can yet understand the implications of all these changes on drug selection for the individual patient. Since these were systemic genetic changes most of which will be present in the whole genome of the cancers, along with other cancer specific mutations (both drivers and passengers), the analysis will be more complex than even the Dewey article indicates. Big data may help (ASCO and NCI imply this will be so), but with 3-5% gene misses and unknown reproducibility of the sequencing studies, when will the Big Data be accurate enough to make robust analyses? How will we determine which of the many genomic mutations are driver mutations that can be targeted with cancer controlling drugs and which are merely non-targetable passenger mutations?

I hate to be discouraged, but whole genome studies or whole exome studies are likely to require considerable rigorous review of large numbers of patients and their tumors before we have clinically useful patterns.
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Old 04-22-2015, 12:13 AM
gdpawel gdpawel is offline
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Default Is Cancer a Genetic Disease?

Robert A. Nagourney, M.D.

I recently had the opportunity to meet two charming young patients: One, a 32-year-old female with an extremely rare malignancy that arose in her kidney and the other a 33-year-old gentleman with widely metastatic sarcoma.

Both patients had obtained expert opinions from renowned cancer specialists and both had undergone aggressive multi-modality therapies including chemotherapy, radiation and surgery. Although they suffered significant toxicities, both of their diseases had progressed unabated. Each arrived at my laboratory seeking assistance for the selection of effective treatment.

With the profusion of genomic analyses available today at virtually every medical center, it came as no surprise that both patients had undergone genetic profiling. What struck me were the results. The young woman had “no measurable genetic aberrancies” from a panoply of 370 cancer-causing exomes, while the young man’s tumor revealed no somatic mutations and only two germ-line SNV’s (single nucleotide variants) from a 50 gene NextGen sequence, neither of which had any clinical or therapeutic significance.

What are we to make of these findings? By conventional wisdom, cancer is a genetic disease. Yet, neither of these patients carried detectable “driver” mutations. Are we to conclude that the tumors that invaded the cervical vertebra of the young woman, requiring an emergency spinal fusion, or the large mass in the lung of the young man are not “cancers”? It would seem that if we apply contemporary dogma, these patients do not have a cancer at all. But nothing could be further from the truth.

Cancer as a disease is not a genomic phenomenon. It is a phenotypic one. As such, it is extremely likely that these patients’ tumors are successfully exploiting normal genes in abnormal ways. The small interfering RNAs or methylations or acetylation or non-coding DNA’s that conspired to create these monstrous problems are too deeply encrypted to be easily deciphered by our DNA methodologies. These changes are effectively gumming up the works of the cancer cell’s biology without leaving a fingerprint.

I have long recognized that cellular studies like the EVA-PCD platform provide the answers, through functional profiling, that genetic analyses can only hope to detect. The assay did identify drugs active in these patients’ tumor, which will offer meaningful benefit, despite the utter lack of genetic targets. Once again, we are educated by cellular biology in the absence of genomic insights. This leaves us with a question however – is cancer a genetic disease?
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Old 12-19-2017, 12:52 PM
gdpawel gdpawel is offline
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Default The flawed premise of cancer being a genetic disease

Confusing correlation with causation is a common scientific error in the genomic basis of cancer. It is known that cancer cells carry mutations and that cancer cells use DNA. Cancer cells > DNA = cancer is a genetic disease. However, no one has taken the time to prove this hypothesis. In the study of human tumor biology, DNA mutations appear to be the “whipping boy” of cancer.

Stepping around this plausible yet flawed premise, genomic analyses is actually an altered cellular system and DNA is only a small part of the puzzle. Yet a generation of cancer scientists have become so absorbed in their own dogma that they cannot (or will not) hear the news that cancer is a cellular process that must be studied at the cellular level if we are ever to have any hope of unraveling its many mysteries.

Genomic testing looks for mutations and other changes in each patient’s gene makeup that might guide drug selection. Although the concept is appealing, in reality, a minority of patients have genetic changes that can be used for therapy.

Functional profiling is very different from genomic testing which is offered by most medical centers. Functional profiling is a laboratory technique that measures how cancer cells respond when they are exposed to drugs and drug combinations. Each cancer patient is unique and their response to therapy is very different from one person to the next.

Programmed cell death is the key. It is a real-time measure of which drugs cause your cancer cells to die, through a process called programmed cell death. By using this approach, they can determine in the laboratory the best drugs for each patient before they receive them. The selection of agents used for testing are disease specific and based on your individual diagnosis, not from your neighbor down the street or someone else across town.

After non-stop chatter about cancer being a genetic disease, there are other long held beliefs in the medical community, such as those surrounding the use of human tissue to select active cancer therapies, that bare careful re-examination.
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