Here we focus on the questions of how reliably we can detect somatic mutations in cancer using a targeted sequencing panel-especially in comparison to the currently available clinical assays-and whether hard-to-detect mutations that require high sequencing coverage are clinically relevant. At this time, such information is available only for a relatively small set of hotspot mutations.Īs the catalog of hotspot mutations that are associated with clinical outcome and the drugs that target those mutations continue to expand, a critical area of improvement is to increase the sensitivity of detecting known hotspot mutations. However, a large integrated database of cancer genome profiling and clinical data to infer whether a mutation might be correlated with treatment response is lacking. A variety of resources such a catalog of previously observed somatic mutations 10 and computational tools for predicting the effect of an observed coding mutation on protein function exist 11, 12. Third, even when a somatic mutation is found, assessing whether it plays a role as a ‘driver’ rather than a ‘passenger’ is difficult. All these assays are complimentary and can be useful for cross-validating mutations, but performing multiple assays is often prohibitive due to the cost and the lack of expertise needed for data analysis. Sequencing RNA is also an attractive option, as it can be used to identify single nucleotide variants (SNVs)/insertions and deletions (indels) and gene fusions from expressed transcripts. These platforms offer a trade-off between the depth and breadth of profiling. The assay platform ranges from full genome coverage (typically at 30–60×) with WGS to exome-only coverage (typically 100-200×) to narrow genome coverage (typically at 500–1000×) with panel sequencing. Second, a comprehensive profiling of mutations in a tumor is possible but requires multiple assays and extensive bioinformatic analysis. Profiling of circulating tumor cells offers a promising approach for a non-invasive and serial characterization, but it is limited to a minority of tumor types and relies on a less mature technology and extremely deep sequencing 9. Given the heterogeneity of a tumor in an individual 8, a full description of the tumor may require multiple samplings of different geographic regions, but this is not feasible in the clinic. First, obtaining a representative tumor specimen of sufficient quality for genome profiling is an on-going challenge. But the repertoire of drugs available for treatment has not been expanding as rapidly as our ability to identify the mutation, limiting the usefulness of whole-exome sequencing (WES) or WGS.Ī number of factors are prerequisite for a successful implementation of a genome-guided therapy selection in routine cancer care. Several studies have shown that selection of therapy based on genomic profiling of few hotspot mutations could lead to prolonged survival for patients 5, 6, 7. However, translation of the insights from molecular profiling to patient care has been much slower. Sequencing technology continues to advance quickly, notably with whole-genome sequencing (WGS) becoming more affordable, and amplification and sequencing of RNA and DNA at the single cell level becoming possible 3, 4. Genomic profiling of tumors by high-throughput sequencing has fueled rapid progress on our understanding of the molecular features underlying all steps of carcinogenesis-tumor initiation, progression, response to treatment, and relapse 1, 2. These results show that capturing low VAF mutations at hotspots by sufficient sequencing coverage and carefully tuned algorithms is imperative for a clinical assay. We also characterize the read depths necessary to achieve sensitivity and specificity comparable to current laboratory assays. For clinical relevance, we describe two patients for whom targeted therapy achieved remission despite low VAF mutations. The percentages of mutations under 5% VAF across hotspots in EGFR, KRAS, PIK3CA, and BRAF are 16%, 11%, 12%, and 10%, respectively, with 24% for EGFR T790M and 17% for PIK3CA E545. Our results demonstrate that a significant fraction of clinically actionable variants have low VAFs, often due to low tumor purity and treatment-induced mutations. We characterize the variant allele fractions (VAFs) of somatic single nucleotide variants and indels across 5095 clinical samples profiled using a custom panel, CancerSCAN. Accurate detection of genomic alterations using high-throughput sequencing is an essential component of precision cancer medicine.
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