Abstract

Cancer evolves as a result of an accumulation of mutations and chromosomal aberrations. Developments in sequencing technologies have enabled the discovery and cataloguing of millions of such mutations. The identification of protein-level alterations, typically by using reversed-phase protein arrays or mass spectrometry, has lagged, however, behind gene and transcript-level observations. In this study, we report the use of mass spectrometry for detecting the presence of mutations-missense, indels and frame shifts-in MCF7 and SKBR3 breast cancer, and non-tumorigenic MCF10A cells. The mutations were identified by expanding the database search process of raw mass spectrometry files by including an in-house built database of mutated peptides (XMAn-v1) that complemented a minimally redundant, canonical database of Homo sapiens proteins. The work resulted in the identification of nearly 300 mutated peptide sequences, of which ~50 were characterized by quality tandem mass spectra. We describe the criteria that were used to select the mutated peptide sequences, evaluate the parameters that characterized these peptides, and assess the artifacts that could have led to false peptide identifications. Further, we discuss the functional domains and biological processes that may be impacted by the observed peptide alterations, and how protein-level detection can support the efforts of identifying cancer driving mutations and genes. Mass spectrometry data are available via ProteomeXchange with identifier PXD014458.

Highlights

  • Earlier studies have identified ~140 genes that drive tumorigenesis, when altered by mutations[1]

  • From the same source of PanCancer tumor exomes, Bailey et al proposed a total of 299 cancer driver genes encompassing over 3,400 putative missense driver mutations, which when further refined by using three structural level tools, resulted in 579 driver mutations associated with 53 genes[14]

  • The missense driver mutations appeared to be more prevalent in oncogenes than in tumor suppressors, the driver genes being associated with biological processes related to RTK and immune signaling, transcription, preservation of genome integrity and protein homeostasis and ubiquitination

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Summary

Introduction

Earlier studies have identified ~140 genes that drive tumorigenesis, when altered by mutations[1]. The field of cancer genomics, supported by the advance of sequencing technologies, has witnessed, a remarkable growth in the past decade, leading to joint multi-institutional efforts aimed at creating comprehensive resources that encompass hundreds to thousands of gene alterations with potential diagnostic and prognostic significance Some of these resources include the Wellcome Sanger Institute’s COSMIC (Catalogue of Somatic Mutations in Cancer) and CGC (Cancer Gene Census) databases[2], the cancer-specific projects supported by the International Cancer Genome Consortium (ICGC)[3], the Cancer Cell Line Encyclopedia (CCLE)[4], and the PanCancer Atlas project conducted by The Cancer Genome Atlas (TCGA) collaboration[5]. We describe the data selection process, evaluate the mass spectrometric quality of the data, and assess the biological relevance of the observed peptide alterations

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