Subtype-specific transcriptional regulators in breast tumors subjected to genetic and epigenetic alterations

Author:

Zhu Qian1,Tekpli Xavier23,Troyanskaya Olga G456,Kristensen Vessela N237

Affiliation:

1. Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA

2. Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Radiumhospitalet, Oslo, Norway

3. Division of Medicine, Department of Clinical Molecular Biology (EpiGen), Akershus University Hospital, Lørenskog, Norway

4. Department of Computer Science, USA

5. Lewis-Siegler Institute of Integrative Genomics, Princeton University, Princeton, NJ 08540, USA

6. Simons Foundation, Flatiron Institute, New York, NY 10010, USA

7. Institute for Clinical Medicine, University of Oslo, Oslo, Norway

Abstract

Abstract Motivation Breast cancer consists of multiple distinct tumor subtypes, and results from epigenetic and genetic aberrations that give rise to distinct transcriptional profiles. Despite previous efforts to understand transcriptional deregulation through transcription factor networks, the transcriptional mechanisms leading to subtypes of the disease remain poorly understood. Results We used a sophisticated computational search of thousands of expression datasets to define extended signatures of distinct breast cancer subtypes. Using ENCODE ChIP-seq data of surrogate cell lines and motif analysis we observed that these subtypes are determined by a distinct repertoire of lineage-specific transcription factors. Furthermore, specific pattern and abundance of copy number and DNA methylation changes at these TFs and targets, compared to other genes and to normal cells were observed. Overall, distinct transcriptional profiles are linked to genetic and epigenetic alterations at lineage-specific transcriptional regulators in breast cancer subtypes. Availability and implementation The analysis code and data are deposited at https://bitbucket.org/qzhu/breast.cancer.tf/. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

National Institute of Health

National Science Foundation (NSF) CAREER

NIH

Canadian Institute For Advanced Research in the Genetic Networks group

Norwegian Cancer Society

Radiumhospitalets Legater

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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