4.5 Article

Genome-wide analysis of alternative transcripts in human breast cancer

期刊

BREAST CANCER RESEARCH AND TREATMENT
卷 151, 期 2, 页码 295-307

出版社

SPRINGER
DOI: 10.1007/s10549-015-3395-2

关键词

Breast cancer; Transcriptome; Classification; Alternative transcript; Splicing; Network

类别

资金

  1. NIGMS/NIH [R01GM104975]
  2. NSF [CCF-1319981]
  3. Bankhead Coley Cancer Research Program [09BN-05]
  4. NCI/NIH [R21CA178675]
  5. Direct For Computer & Info Scie & Enginr
  6. Division of Computing and Communication Foundations [1319981] Funding Source: National Science Foundation

向作者/读者索取更多资源

Transcript variants play a critical role in diversifying gene expression. Alternative splicing is a major mechanism for generating transcript variants. A number of genes have been implicated in breast cancer pathogenesis with their aberrant expression of alternative transcripts. In this study, we performed genome-wide analyses of transcript variant expression in breast cancer. With RNA-Seq data from 105 patients, we characterized the transcriptome of breast tumors, by pairwise comparison of gene expression in the breast tumor versus matched healthy tissue from each patient. We identified 2839 genes, similar to 10 % of protein-coding genes in the human genome, that had differential expression of transcript variants between tumors and healthy tissues. The validity of the computational analysis was confirmed by quantitative RT-PCR assessment of transcript variant expression from four top candidate genes. The alternative transcript profiling led to classification of breast cancer into two subgroups and yielded a novel molecular signature that could be prognostic of patients' tumor burden and survival. We uncovered nine splicing factors (FOX2, MBNL1, QKI, PTBP1, ELAVL1, HNRNPC, KHDRBS1, SFRS2, and TIAR) that were involved in aberrant splicing in breast cancer. Network analyses for the coordinative patterns of transcript variant expression identified twelve hub genes that differentiated the cancerous and normal transcriptomes. Dysregulated expression of alternative transcripts may reveal novel biomarkers for tumor development. It may also suggest new therapeutic targets, such as the hub genes identified through the network analyses of transcript variant expression, or splicing factors implicated in the formation of the tumor transcriptome.

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