Clinical Variant Analysis for Cancer: Part IV

· Andreas Scherer · How To's & Advanced Workflows, VSClinical

Clinical Variant Analysis for Cancer – Applying AMP Guidelines to Analyze Somatic Variants

Somatic variants can manifest in different ways:

  • Single Nucleotide Variants
  • Indels
  • Fusions and
  • Copy Number Variations

There is a difference between the interpretation of germline and somatic variants. The former is exclusively focused on establishing the level of pathogenicity vis a vis a particular disease. In contrast to that, when we assess the clinical implication of a somatic variant, we are interested in the following:

  • Sensitivity: Does a particular variant imply the sensitivity to a particular drug or treatment.
  • Resistance: Here, we might establish that certain drugs are not effective.
  • Toxicity: In this case, we might find that a certain biomarker implies that a certain drug has adverse or toxic side effects.

The AMP guidelines suggest to cluster the available clinical evidence in four levels:

  1. Level A: This is the highest level of available evidence. Biomarkers in this category are clearly established to either create a definitive tumor response for a specific tumor type or are known to indicate resistance of the tumor based on US-FDA or other professionally accepted guidelines.
  2. Level B: There is still very strong evidence of a predicted tumor response or resistance based on numerous large studies. Experts agree on the findings, and the assembled body of knowledge is consistent in the clinical interpretation of a given biomarker.
  3. Level C:  Biomarkers in this category point towards efficacy or resistance in a different type of tumor. Clinicians use Level C to recommend off-label use of a drug. Sometimes they are used to recommend the inclusion of a patient in a clinical trial.
  4. Level D:  In this category, evidence from pre-clinical studies or other smaller studies on a smaller scale is collected. This is generally seen as the weakest of all pieces of evidence that can yield a clinical decision.

The available clinical evidence is then sorted into four tiers that describe the clinical impact of any given variant (see fig 11).

Fig 11: Evidence-based variant categorization

Tier I Variants

Here we have clear evidence of therapeutic, diagnostic, and or prognostic value. In this tier, we are mainly interested in variants with a predicted response or resistance to FDA approved drugs or others are documented in professional guidelines for a specific tumor. We include only Level A and B evidence in this tier.  Let’s look at a few examples.

One of the most well-known cancer mutations, BRAF V600E is predictive for a positive response for the drug vemurafenib in melanoma (see fig 12). Therapeutically, this would be a valid and likely choice based on the observed biomarker.

Figure 12: Impact of vemurafenib

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Andreas Scherer

About Andreas Scherer

Dr. Andreas Scherer is CEO of Golden Helix. The company has been delivering industry leading bioinformatics solutions for the advancement of life science research and translational medicine for over a decade. Its innovative technologies and analytic services empower scientists and healthcare professionals at all levels to derive meaning from the rapidly increasing volumes of genomic data produced from next-generation sequencing. With its solutions, hundreds of the world’s hospitals and testing labs are able to harness the full potential of genomics to identify the cause of disease, develop genomic diagnostics, and advance the quest for personalized medicine. Golden Helix products and services have been cited in thousands of peer-reviewed publications. Golden Helix is also on the Inc 5000 list of the fastest-growing private companies in the US. He is also Managing Partner of Salto Partners, Inc, a management consulting firm headquartered in Nevada.  He has extensive experience successfully managing growth as well as orchestrating complex turnaround situations. His company, Salto Partners, advises on business strategy, financing, sales, and operations. Clients are operating in the high-tech and life sciences space. Dr. Scherer holds a Ph.D. in computer science from the University of Hagen, Germany, and a Master of Computer Science from the University of Dortmund, Germany. He is author and co- author of over 20 international publications and has written books on project management, the Internet, and artificial intelligence. His latest book, “Be Fast Or Be Gone”, is a prizewinner in the 2012 Eric Hoffer Book Awards competition, and has been named a finalist in the 2012 Next Generation Indie Book Awards! 

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