Literature DB >> 29429018

MOBCdb: a comprehensive database integrating multi-omics data on breast cancer for precision medicine.

Bingbing Xie1,2, Zifeng Yuan3, Yadong Yang1,2, Zhidan Sun3, Shuigeng Zhou4, Xiangdong Fang5,6.   

Abstract

BACKGROUND: Breast cancer is one of the most frequently diagnosed cancers among women worldwide, characterized by diverse biological heterogeneity. It is well known that complex and combined gene regulation of multi-omics is involved in the occurrence and development of breast cancer.
RESULTS: In this paper, we present the Multi-Omics Breast Cancer Database (MOBCdb), a simple and easily accessible repository that integrates genomic, transcriptomic, epigenomic, clinical, and drug response data of different subtypes of breast cancer. MOBCdb allows users to retrieve simple nucleotide variation (SNV), gene expression, microRNA expression, DNA methylation, and specific drug response data by various search fashions. The genome-wide browser /navigation facility in MOBCdb provides an interface for visualizing multi-omics data of multi-samples simultaneously. Furthermore, the survival module provides survival analysis for all or some of the samples by using data of three omics. The approved public drugs with genetic variations on breast cancer are also included in MOBCdb.
CONCLUSION: In summary, MOBCdb provides users a unique web interface to the integrated multi-omics data of different subtypes of breast cancer, which enables the users to identify potential novel biomarkers for precision medicine.

Entities:  

Keywords:  Breast cancer; Database; Epigenome; Genome; Multi-omics; Precision medicine; Transcriptome

Mesh:

Year:  2018        PMID: 29429018     DOI: 10.1007/s10549-018-4708-z

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  7 in total

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4.  Topological integration of RPPA proteomic data with multi-omics data for survival prediction in breast cancer via pathway activity inference.

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Journal:  BMC Med Genomics       Date:  2019-07-11       Impact factor: 3.063

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6.  OVOL1 inhibits breast cancer cell invasion by enhancing the degradation of TGF-β type I receptor.

Authors:  Chuannan Fan; Qian Wang; Gerard van der Zon; Jiang Ren; Cedrick Agaser; Roderick C Slieker; Prasanna Vasudevan Iyengar; Hailiang Mei; Peter Ten Dijke
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7.  The effect of protein mutations on drug binding suggests ensuing personalised drug selection.

Authors:  Shunzhou Wan; Deepak Kumar; Valentin Ilyin; Ussama Al Homsi; Gulab Sher; Alexander Knuth; Peter V Coveney
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  7 in total

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