Clinical OMICs - Issue 4 - (Page 23)

Clinical OMICs CASE STUDY Detection and Interpretation of Rare Sub-Clonal Cancer Driver Mutations Anika Jöcker, Rupert Yip, and Salim Essakali W ithin the last decade, our understanding of the molecular biology of cancer and its underlying complexity has experienced unparalleled and exponential growth (Hanahan et al. 2000, Hanahan et al. and 2011)1, 2. Both patients and clinicians have started benefiting from this new level of understanding, which can also be seen in the FDA approval within the last two years of approximately 20 new drugs that target a specific mutation for cancer. With next-generation sequencing technologies, pathologists and clinicians are now empowered to test for several actionable mutations, as well as identify potential drug targets in parallel. This can significantly improve the diagnostic rate, as well as the drug treatment. Furthermore, data from large patient cohorts can be used to develop even better biomarkers, which can be used for prognosis, diagnosis, and drug treatment. However, the bioinformatics analysis tools required to identify and interpret the plethora of variants-which in some cancers may amount to 50 variants per megabase (Vogelstein www.clinicalomics.com et al. 2013)3-still remain highly fragmented and require multiple experts. Two new bioinformatics platforms have been specifically designed to target and streamline the identification (CLC Cancer Research Workbench) and the interpretation (Ingenuity® Variant Analysis) of somatic variants and driver mutations in cancer. This case study was aimed at testing both platforms in combination to identify cancer driver mutations that are present in a low percentage of tumor cells. These mutations are of special interest in a clinical setting as they can drive tumor spread and recurrence. Materials, Methods, and Discussion For this study, we used a publicly available tumor/normal dataset from a patient with massive acinic cell carcinoma, which was published last year by Nichols et al. in Case Reports in Oncological Medicine4. The data is targeted whole exome sequencing prepared using Agilent's Sure Select for the enrichment of exonic regions in the genome then sequenced using Illumina's HiSeq® 2000. Raw reads from the HiSeq 2000 were imported into CLC Cancer Research Workbench for streamlined data analysis and visualization of results. The sequencing reads from the patient's tumor and normal tissues were mapped to the human reference genome and locally realigned to improve sensitivity and specificity of variant calling. Furthermore, variants were called down to an allele frequency of 5%, while potential false positives were filtered out. In addition, a detailed and summary coverage report was generated to check for coverage and uniformity of the targeted regions. All these steps were facilitated (continued on next page) In addition to being an e-publication, Clinical OMICs is a website. www.clinicalomics.com is updated frequently with information about relevant scientific advances, novel tests, new guidelines, and critical ethical and reimbursement issues. You can access the current as well as past issues of Clinical OMICs in the archives tab. Check it out daily! May 29, 2014 Clinical OMICs 23 http://www.clinicalomics.com http://www.clinicalomics.com

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Clinical OMICs - Issue 4