1. Subtype-specific transcriptional regulators in breast tumors subjected to genetic and epigenetic alterations
- Author
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Qian Zhu, Olga G. Troyanskaya, Vessela N. Kristensen, and Xavier Tekpli
- Subjects
Epigenomics ,Statistics and Probability ,Gene Expression ,Breast Neoplasms ,Computational biology ,Disease ,Biology ,Biochemistry ,Epigenesis, Genetic ,03 medical and health sciences ,0302 clinical medicine ,Breast cancer ,medicine ,Humans ,Epigenetics ,Discovery Notes ,Molecular Biology ,Gene ,Transcription factor ,030304 developmental biology ,Epigenesis ,0303 health sciences ,DNA Methylation ,medicine.disease ,3. Good health ,Computer Science Applications ,Computational Mathematics ,Computational Theory and Mathematics ,030220 oncology & carcinogenesis ,DNA methylation ,Transcription Factors - 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.
- Published
- 2019