Proteogenomic Analysis of Single Amino Acid Polymorphisms in Cancer Research
The integration of genomics and proteomics has led to the emergence of proteogenomics, a field of research successfully applied to the characterization of cancer samples. The diagnosis, prognosis and response to therapy of cancer patients will largely ben
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Proteogenomic Analysis of Single Amino Acid Polymorphisms in Cancer Research Alba Garin-Muga, Fernando J. Corrales, and Victor Segura
Abstract
The integration of genomics and proteomics has led to the emergence of proteogenomics, a field of research successfully applied to the characterization of cancer samples. The diagnosis, prognosis and response to therapy of cancer patients will largely benefit from the identification of mutations present in their genome. The current state of the art of high throughput experiments for genome-wide detection of somatic mutations in cancer samples has allowed the development of projects such as the TCGA, in which hundreds of cancer genomes have been sequenced. This huge amount of data can be used to generate protein sequence databases in which each entry corresponds to a mutated peptide associated with certain cancer types. In this chapter, we describe a bioinformatics workflow for creating these databases and detecting mutated peptides in cancer samples from proteomic shotgun experiments. The performance of the proposed method has been evaluated using publicly available datasets from four cancer cell lines. Keywords
Proteogenomics • TCGA project • SAP detection • Cancer research
A. Garin-Muga Proteomics and Bioinformatics Unit, Center for Applied Medical Research, University of Navarra, Pamplona, Spain F.J. Corrales Proteomics and Bioinformatics Unit, Center for Applied Medical Research, University of Navarra, Pamplona, Spain Division of Hepatology and Gene Therapy, Center for Applied Medical Research, University of Navarra, Pamplona, Spain IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
V. Segura (*) Proteomics and Bioinformatics Unit, Center for Applied Medical Research, University of Navarra, Pamplona, Spain IdiSNA, Navarra Institute for Health Research, Pamplona, Spain e-mail: [email protected]
© Springer International Publishing Switzerland 2016 Á. Végvári (ed.), Proteogenomics, Advances in Experimental Medicine and Biology 926, DOI 10.1007/978-3-319-42316-6_7
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Introduction
Cancer is one of the leading causes of death worldwide, accounting for 15 % of the total number of annual deaths. Furthermore, in the next two decades, cancer mortality rates are expected to double. There are more than 200 cancer types and each can be classified into several subtypes with different molecular and clinical characteristics (Tomczak et al. 2015). This complexity explains the heterogeneous response to therapy and expected survival rate of patients (McDermott et al. 2011). DNA sequence mutations drive the neoplastic transformation and cause, among other effects, the uncontrolled cell growth in these patients (Hanahan and Weinberg 2000). Therefore, the identification of the complete catalogue of DNA aberrations becomes a priority since it will be the basis for improving not only cancer prevention and its early detection but also its treatment. The sequencing of the human genome (Lander et al. 2001; Venter et al. 2001) was the first step towards u
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