Cancer Genome Characterization with SNP Array and Whole-Exome Sequencing Analysis

• Main Author: Ramos, Alexis
• Other Authors: Meyerson, Matthew Langer
• Language: en_US
• Published: Harvard University 2013
• Subjects: NSCLC; genetics; bioinformatics; cancer; carcinoid; sequencing; SNP array
• Online Access: http://dissertations.umi.com/gsas.harvard:10036; http://nrs.harvard.edu/urn-3:HUL.InstRepos:10336916

Cancer, the uncontrolled growth of morphologically and genetically abnormal cells in the body, is a major worldwide public health problem and there is a great need for novel insights into this disease. The majority of tumors arise from the acquisition of somatic alterations leading to changes in gene function and expression. The clinical success of targeted therapeutics in molecularly defined subsets of patients has highlighted the need for comprehensive characterization of the somatic alterations in individual cancer types. Copy number profiling using SNP arrays is a common approach for profiling the extent of copy number variation across the cancer genome. In addition, next-generation sequencing technologies now offer researchers the ability to also systematically catalog nucleotide substitutions and structural rearrangements in dramatically less time and expense. In this thesis, we describe the application of SNP arrays and whole-exome sequencing to characterize two separate cohorts of cancer samples, as well as describe the development of a software tool to aid in the annotation of mutational data. Specifically, we detailed focal amplifications of PDGFRA and KIT in a combined set of lung adenocarcinoma and squamous cell carcinomas. Furthermore, in a cohort of small bowel neuroendocrine tumors, we characterized the global genetic landscape to show that these tumors are molecularly distinct from other neuroendocrine tumors. Lastly, we report Oncotator, a novel web application and service for comprehensive annotation of point mutations and indels found in cancer. It is hoped that the knowledge gained from these studies will fuel improvements in cancer diagnosis, prognosis, and therapy.