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Characterization of potential driver mutations involved in human breast cancer by computational approaches

Barani Kumar Rajendran and Chu-Xia Deng _

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Oncotarget. 2017; 8:50252-50272. https://doi.org/10.18632/oncotarget.17225

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Abstract

Barani Kumar Rajendran1 and Chu-Xia Deng1

1Cancer Research Centre, Faculty of Health Sciences, University of Macau, Macau SAR, China

Correspondence to:

Chu-Xia Deng, email: cxdeng@umac.mo

Keywords: driver mutations, breast cancer, cancer drivers, breast cancer driver genes, genetic mutations

Received: February 08, 2017     Accepted: March 26, 2017     Published: April 19, 2017

ABSTRACT

Breast cancer is the second most frequently occurring form of cancer and is also the second most lethal cancer in women worldwide. A genetic mutation is one of the key factors that alter multiple cellular regulatory pathways and drive breast cancer initiation and progression yet nature of these cancer drivers remains elusive. In this article, we have reviewed various computational perspectives and algorithms for exploring breast cancer driver mutation genes. Using both frequency based and mutational exclusivity based approaches, we identified 195 driver genes and shortlisted 63 of them as candidate drivers for breast cancer using various computational approaches. Finally, we conducted network and pathway analysis to explore their functions in breast tumorigenesis including tumor initiation, progression, and metastasis.


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PII: 17225