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An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers

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TLDR
It is shown that throughout cancer genomes APOBEC-mediated mutagenesis is pervasive and correlates withAPOBEC mRNA levels, and that ubiquitous APOBec-mediated Mutagenesis are carcinogenic.
Abstract
Recent studies indicate that a subclass of APOBEC cytidine deaminases, which convert cytosine to uracil during RNA editing and retrovirus or retrotransposon restriction, may induce mutation clusters in human tumors. We show here that throughout cancer genomes APOBEC-mediated mutagenesis is pervasive and correlates with APOBEC mRNA levels. Mutation clusters in whole-genome and exome data sets conformed to the stringent criteria indicative of an APOBEC mutation pattern. Applying these criteria to 954,247 mutations in 2,680 exomes from 14 cancer types, mostly from The Cancer Genome Atlas (TCGA), showed a significant presence of the APOBEC mutation pattern in bladder, cervical, breast, head and neck, and lung cancers, reaching 68% of all mutations in some samples. Within breast cancer, the HER2-enriched subtype was clearly enriched for tumors with the APOBEC mutation pattern, suggesting that this type of mutagenesis is functionally linked with cancer development. The APOBEC mutation pattern also extended to cancer-associated genes, implying that ubiquitous APOBEC-mediated mutagenesis is carcinogenic.

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Integrated Genomic Characterization of Papillary Thyroid Carcinoma

Nishant Agrawal, +242 more
- 23 Oct 2014 - 
TL;DR: The genomic landscape of 496 PTCs is described and a reclassification of thyroid cancers into molecular subtypes that better reflect their underlying signaling and differentiation properties is proposed, which has the potential to improve their pathological classification and better inform the management of the disease.
Journal ArticleDOI

Maftools: efficient and comprehensive analysis of somatic variants in cancer.

TL;DR: An R Bioconductor package, Maftools, is described, which offers a multitude of analysis and visualization modules that are commonly used in cancer genomic studies, including driver gene identification, pathway, signature, enrichment, and association analyses, and is independent of larger alignment files.
Journal ArticleDOI

Tumour heterogeneity and resistance to cancer therapies

TL;DR: The driving forces behind intratumoural heterogeneity and the current approaches used to combat this heterogeneity and its consequences are discussed and how clinical assessments of tumour heterogeneity might facilitate the development of more-effective personalized therapies are explored.
Journal ArticleDOI

Tracking the Evolution of Non–Small-Cell Lung Cancer

Mariam Jamal-Hanjani, +82 more
TL;DR: Intratumor heterogeneity mediated through chromosome instability was associated with an increased risk of recurrence or death, a finding that supports the potential value of chromosome instability as a prognostic predictor.
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Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer

A. Gordon Robertson, +170 more
- 19 Oct 2017 - 
TL;DR: An analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms identified 5 expression subtypes that may stratify response to different treatments and identified a poor-survival "neuronal" subtype in which the majority of tumors lacked small cell or neuroendocrine histology.
References
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Journal ArticleDOI

Controlling the false discovery rate: a practical and powerful approach to multiple testing

TL;DR: In this paper, a different approach to problems of multiple significance testing is presented, which calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate, which is equivalent to the FWER when all hypotheses are true but is smaller otherwise.
Journal ArticleDOI

Hallmarks of cancer: the next generation.

TL;DR: Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer.
Journal ArticleDOI

Comprehensive molecular portraits of human breast tumours

Daniel C. Koboldt, +355 more
- 04 Oct 2012 - 
TL;DR: The ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity.
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