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Old 01-04-2015, 07:26 PM
gdpawel gdpawel is offline
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Default Genomic Profiling for Lung Cancer: the Good, the Bad and the Ugly

Robert A. Nagourney, M.D.

Genomic profiling has gained popularity in medical oncology. Using NextGen platforms, protein coding regions of human tumors known as exomes can be examined for mutations, amplifications, deletions, splice variants and SNPs. In select tumors the results can be extremely helpful. Among the best examples are adenocarcinomas of the lung where EGFr, ALK and ROS-1 mutations, deletions and/or re-arrangements identified by DNA analysis can guide the selection of “targeted agents” like Erlotinib and Crizotinib.

An article published in May 2014 issue of JAMA reported results using probes for 10 “oncogenic driver” mutations in lung cancer patients. They screened for at least one gene in 1,007 patients and all 10 genes in 733. The most common was k-ras at 25%, followed by EGFR in 17% and ALK in 8%. The incidence then fell off with other EGFr mutations in 4%, B-raf mutations in 2%, with the remaining mutations each found in less than 1%.

[url] s+in+lung+cancers+to+select+targeted+drugs.+JAMA+3 11:1998-2006,+2014

Median survival at 3.5 vs 2.4 years was improved for patients who received treatments guided by the findings (Kris MG et al, Using multiplex assays of oncogenic drivers in lung cancers to select targeted drugs. JAMA, May 2014). Do these results indicate that genomic analyses should be used for treatment selection in all patients? Yes and no.

Noteworthy is the fact that 28% of the patients had driver mutations in one of three genes, EGFr, HER2 or ALK. All three of these mutations have commercially available chemotherapeutic agents in the form of Erlotinib, Afatinib and Crizotinib. Response rates of 50% or higher, with many patients enjoying durable benefits have been observed. Furthermore, patients with EGFr mutations are often younger, female and non-smokers whose tumors often respond better to both targeted and non-targeted therapies. These factors would explain in part the good survival numbers reported in the JAMA article. Today, a large number of commercial laboratories offer these tests as part of standard panels. And, like k-ras mutations in colon cancer or BCR-abl in CML (the target of Gleevec), the arguments in favor of the use of these analyses is strong.

But what of the NSCLC patients for whom no clear identifiable driver can be found? What of the 25% with k-ras mutations for whom no drug exists? What of those with complex mutational findings? And finally what of those patients whose tumors are driven by normal genes functioning abnormally? In these patients no mutations exists at all. How best do we manage these patients?

I was reminded of this question as I reviewed a genomic analysis reported to one of my colleagues. He had submitted a tissue block to an east coast commercial lab when one of his lung cancer patients relapsed. The results revealed mutations in EGFr L858R & T790M, ERBB4, HGF, JAK2, PTEN, STK11, CCNE1, CDKN2A/B, MYC, MLL2 W2006, NFKB1A, and NKX2-1. With a tumor literally bristling with potential targets, what is a clinician to do? How do we take over a dozen genetically identified targets and turn them into effective treatment strategies? In this instance, too much information can be every bit as paralyzing as too little.

Our preferred approach is to examine the small molecule inhibitors that target each of the identified aberrancies in our laboratory platform. We prefer to drill down to the next level of certainty e.g. cellular function. After all, the presence of a target does not a response make.

In this patient I would conduct a biopsy. This would enable us to examine the drugs and combinations that are active against the targets. A “hit” by the EVA-PCD assay would then isolate the “drivers” from the “passengers” and enable the clinician to intelligently select effective treatments. Combining genomic analyses with functional profiling (phenotypic analyses) provides the opportunity to turn speculative observations into actionable events.
Gregory D. Pawelski
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Old 07-02-2015, 11:10 PM
gdpawel gdpawel is offline
Join Date: Feb 2007
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Default The DNA and RNA protein ranch

The latest thing in cancer treatment are so-called "targeted" therapies, the most prominent of which now are tyrosine kinase inhibitors (e.g. gefitinib, erlotinib, sunitinib, sorafenib). These drugs are very expensive and work most often modestly in a minority of cases.

We are now beginning to be able to use molecular profiling to provide personalized treatment that offers hope of improved survival and less toxicity from therapy. And the ability to provide this molecular diagnostic test on a worldwide basis with rapid turnaround will be critical for further clinical research and application in the clinic.

What were the data supporting the use of this testing?

Prospective, randomized trials showing improved treatment outcomes in patients so tested? Nope.

Prospective trials, showing survival advantages in patients with "positive" test results? Nope.

Prospective trials, showing response advantages in patients with "positive" test results? Nope.

Retrospective trials, showing both response and survival advantages in patients with "positive" test results, in thousands of patients, from multiple laboratories? Nope.

Two entirely retrospective studies, from two Harvard-affiliated hospitals, showing response, but not survival, advantages with a grand total of 26 assay/treatment correlations? Yes.

A subsequent study from another laboratory did not show correlations between gene mutations and patient survival.

So, the clinical application of DNA content assays have been shown to correlate only with response and not survival, and only in a handful of patients, and only in entirely retrospective studies.

What is going on here?

The benefits of newer targeted therapies are marginal. These targeted therapies may impart a clinical benefit by stabilizing tumors, rather than shrinking them (substituting shrinkage for stabilization).

No genetic profile can discriminate differing levels of anti-tumor activity occurring among different targeted therapy drugs. Nor can it identify situations in which it is advantageous to combine a targeted drug with other types of conventional cancer drugs.

I would not want to be denied treatment with any targeted therapy because of a gene mutation or amplification study. Neither would I want to receive treatment with any targeted therapy because of a gene mutation or amplification study. Genetic testing is not a clear predictor of a benefit or a lack of benefit.

They don't tell you if one targeted drug or another targeted drug is worse or better than some other drug which may target a particular pathway. The cell is a system, an integrated, interacting network of genes, proteins and other cellular constituents that produce functions.

Genomics is far too limited in scope to encompass the vagaries and complexities of human cancer biology. To inhibit the mutant decoy receptor, you need to inhibit the domain of the driver molecule that lies within the cell, as opposed to the domain that lies outside the cell.

There have been no static genetic testing that can accurately predict markers for selecting the patients who will benefit from treatment with targeted therapies.
Gregory D. Pawelski
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