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Mar 15, 2012 (Vol. 32, No. 6)

Biomarker Analysis Makes Strides

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    BioMarker Strategies’ SnapPath™ system incorporates an automated, live-tumor-cell processing device with first-in-class, functional, ex vivo biomarker tests to improve drug development and inform clinical decision-making for targeted cancer therapeutics. SnapPath stimulates a patient’s live tumor cells—outside their body—to obtain a Functional Signaling Profile of the signal transduction network that is not possible using static, genomic biomarkers from dead, fixed tissue.

    Personalized medicine made significant strides in 2011 with two new targeted cancer therapies, the FDA release of its companion diagnostics draft guidance, and routine clinical genotyping for some oncology applications. However, many challenges remain. An estimated 90% of currently marketed drugs are effective in only ~40% of patients annually, costing ~$350 billion for medications that don’t work.

    Hope may be on the horizon, though, bolstered by new successes and novel approaches in biomarker analyses. GTC’s “Oncology Biomarkers” conference will feature pointed discussions about overcoming challenges to translation of biomarkers to the clinic. It will also showcase emerging technologies for assessing biomarkers, including the use of isogenic cell lines to stratify patient populations, next-generation sequencing for mutational analysis, and identification of unique biological targets.

    Over the past few years there has been a clear shift in oncology from traditional cytotoxic agents to more molecularly targeted drugs, says Adam Schayowitz, Ph.D., director of business development, BioMarker Strategies.

    “The challenge is how to match patient biomarkers with anticipated drug response. Often a drug is developed for a given indication, without knowing in which subset of patients it will be most effective.”

    Part of the bottleneck is the way tumor specimens are processed. “Typically, when biopsies are obtained, tissue is fixed using an approach that was developed in the 19th century (FFPE sections). Then static biomarker tests are performed using methods such as immunohistochemistry, DNA sequencing, and DNA amplification.

    “The problem with this approach is that this tissue is dead and unable to be interrogated for true functional value. As such, what actually happens within the signal transduction network of living cells is lost.”

    BioMarker Strategies believes one way to bridge the chasm between biomarkers and drug response is by developing a new paradigm for testing tumor specimens.

    “A better approach,” Dr. Schayowitz suggests, “is to keep the cells alive long enough to obtain a functional profile that would reveal information about the signal transduction networks that predict patient response to targeted drug therapy.

    “Our company has developed an ex vivo biomarker testing system called SnapPath™ to enable this approach. It is an automated live tumor cell processing platform that allows us to characterize how a patient’s live tumor cells respond to pathway stimulants (e.g., growth factors) or inhibitors (targeted drugs).”

    Initially, a fine-needle biopsy harvests cells from the patient’s tumor. The sample is then placed in a ready-made cartridge that can be processed in the self-contained instrument. The automated processing takes less than 30 minutes and occurs in steps.

    First cellular aggregates are mechanically dispersed. Nontumor material is depleted, and the purified cells are distributed in up to four chambers. While some cells are untreated and remain at baseline, others are treated with various stimulators and inhibitors (therapeutic drugs). Finally, samples are lysed and stabilized for off-platform extraction and analysis.

    “The idea is to obtain functional signaling profiles of the phosphoprotein signaling networks to compare the treated and untreated malignant cells. SnapPath is amenable to analytic technology procedures that can also be performed for RNA and DNA analysis. We are currently conducting clinical studies at a growing number of cancer centers. While we are starting with advanced melanoma, the SnapPath platform is designed to process all solid tumors.”

  • Isogenic Cell Lines

    Transforming biomarker data into clinically relevant companion diagnostics requires overcoming several key challenges, says Andrew Grupe, Ph.D., senior director of pharmacogenomics discovery research, Celera, a business of Quest Diagnostics.

    “One hurdle is regulatory issues that inevitably arise. These require peer guidance by collaborating with experts who can help transition biomarker assays from research to diagnostic. Second, one needs to address reimbursement issues. In order for tests to be reimbursable, there must be proven clinical utility. For example, we are working with Medco to determine whether genetic testing could impact compliance of patients on statins.

    “A third key aspect for transitioning biomarkers to the clinic is the requirement point to provide solid confirmatory evidence for the utility of specific biomarkers. Also, associated clinical trials must be powered sufficiently. For example, biomarkers may be identified or confirmed in properly powered Phase II trials and then need to be tested in a Phase III trial with a prespecified hypothesis that spells out specifics of anticipated results.”

    According to Dr. Grupe, the use of isogenic cell lines can be a powerful means for assessing biomarkers that help stratify patient populations.

    “Isogenic cell lines are engineered or selected to model human cancer genotypes, i.e., a specific patient population. These are created using homologous recombination techniques that knock-in or knock-out disease causing mutations. Studies are performed comparing these engineered lines with wild-type isogenic cell-line controls. Isogenic cell lines provide an important strategy to assess cancer treatments in the context of somatic mutations.”

    Since hundreds of cancer genes have now been characterized, it is possible to examine specific genetic mutations and evaluate how these interact with the rest of the cellular apparatus to modify patients’ responses to specific treatments. For example, mutations in K-Ras, BRAF, and PI3K may impact response to cancer drugs.

    “We’ve developed expression profiles of individual genes and multigene signatures that give us information related to treatment efficacy. We have identified gene responses to tamoxifen treatment for breast cancer and tested the signatures in isogenic lines. Our isogenic cell-line results demonstrated that the signature can predict results consistent with genetic background.”

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