Work

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

Year: 2017

Type: review

Abstract: // Barani Kumar Rajendran 1 and Chu-Xia Deng 1 1 Cancer Research Centre, Faculty of Health Sciences, University of Macau, Macau SAR, China Correspondence to: Chu-Xia Deng, email: [email protected] 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.

Source: Oncotarget

DOI: 10.18632/oncotarget.17225

Authors: Barani Kumar Rajendran, Chu-Xia Deng

Institution: University of Macau

Language: English

Topic: Cancer Genomics and Diagnostics

Subfield: Cancer Research

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: diamond

Funders: Universidade de Macau, Fundo para o Desenvolvimento das Ciências e da Tecnologia