Skip to main content
Erschienen in: Breast Cancer Research and Treatment 3/2018

10.02.2018 | Brief Report

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

verfasst von: Bingbing Xie, Zifeng Yuan, Yadong Yang, Zhidan Sun, Shuigeng Zhou, Xiangdong Fang

Erschienen in: Breast Cancer Research and Treatment | Ausgabe 3/2018

Einloggen, um Zugang zu erhalten

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.
Anhänge
Nur mit Berechtigung zugänglich
Literatur
1.
2.
Zurück zum Zitat Zagouri F et al (2014) Female breast cancer in Europe: statistics, diagnosis and treatment modalities. J Thorac Dis 6(6):589–590PubMedPubMedCentral Zagouri F et al (2014) Female breast cancer in Europe: statistics, diagnosis and treatment modalities. J Thorac Dis 6(6):589–590PubMedPubMedCentral
3.
4.
Zurück zum Zitat Sorlie T et al (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 98(19):10869–10874CrossRefPubMedPubMedCentral Sorlie T et al (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 98(19):10869–10874CrossRefPubMedPubMedCentral
5.
Zurück zum Zitat Ignatiadis M, Sotiriou C (2013) Luminal breast cancer: from biology to treatment. Nat Rev Clin Oncol 10(9):494–506CrossRefPubMed Ignatiadis M, Sotiriou C (2013) Luminal breast cancer: from biology to treatment. Nat Rev Clin Oncol 10(9):494–506CrossRefPubMed
6.
Zurück zum Zitat Arteaga CL et al (2011) Treatment of HER2-positive breast cancer: current status and future perspectives. Nat Rev Clin Oncol 9(1):16–32CrossRefPubMed Arteaga CL et al (2011) Treatment of HER2-positive breast cancer: current status and future perspectives. Nat Rev Clin Oncol 9(1):16–32CrossRefPubMed
7.
Zurück zum Zitat Rakha EA, Reis-Filho JS, Ellis IO (2008) Basal-like breast cancer: a critical review. J Clin Oncol 26(15):2568–2581CrossRefPubMed Rakha EA, Reis-Filho JS, Ellis IO (2008) Basal-like breast cancer: a critical review. J Clin Oncol 26(15):2568–2581CrossRefPubMed
8.
9.
Zurück zum Zitat Varn FS et al (2015) Integrative analysis of survival-associated gene sets in breast cancer. BMC Med Genom 8:11CrossRef Varn FS et al (2015) Integrative analysis of survival-associated gene sets in breast cancer. BMC Med Genom 8:11CrossRef
11.
12.
13.
Zurück zum Zitat Szabo C et al (2000) The breast cancer information core: database design, structure, and scope. Hum Mutat 16(2):123–131CrossRefPubMed Szabo C et al (2000) The breast cancer information core: database design, structure, and scope. Hum Mutat 16(2):123–131CrossRefPubMed
14.
Zurück zum Zitat Baasiri RA et al (1999) The breast cancer gene database: a collaborative information resource. Oncogene 18(56):7958–7965CrossRefPubMed Baasiri RA et al (1999) The breast cancer gene database: a collaborative information resource. Oncogene 18(56):7958–7965CrossRefPubMed
15.
Zurück zum Zitat Sims D et al (2010) ROCK: a breast cancer functional genomics resource. Breast Cancer Res Treat 124(2):567–572CrossRefPubMed Sims D et al (2010) ROCK: a breast cancer functional genomics resource. Breast Cancer Res Treat 124(2):567–572CrossRefPubMed
18.
Zurück zum Zitat Cerami E et al (2012) The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data (vol 2, pg 401, 2012). Cancer Discov 2(10):960–960CrossRef Cerami E et al (2012) The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data (vol 2, pg 401, 2012). Cancer Discov 2(10):960–960CrossRef
19.
22.
Zurück zum Zitat Wang K, Li M, Hakonarson H (2010) ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res 38(16):e164CrossRefPubMedPubMedCentral Wang K, Li M, Hakonarson H (2010) ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res 38(16):e164CrossRefPubMedPubMedCentral
23.
Zurück zum Zitat Griffiths-Jones S et al (2008) miRBase: tools for microRNA genomics. Nucl Acids Res 36(Database issue):D154–D158PubMed Griffiths-Jones S et al (2008) miRBase: tools for microRNA genomics. Nucl Acids Res 36(Database issue):D154–D158PubMed
24.
Zurück zum Zitat Xu J et al (2012) Genome-wide association study in Chinese men identifies two new prostate cancer risk loci at 9q31.2 and 19q13.4. Nat Genet 44(11):1231–1235CrossRefPubMedPubMedCentral Xu J et al (2012) Genome-wide association study in Chinese men identifies two new prostate cancer risk loci at 9q31.2 and 19q13.4. Nat Genet 44(11):1231–1235CrossRefPubMedPubMedCentral
25.
Zurück zum Zitat Lin KT et al (2014) Identification of latent biomarkers in hepatocellular carcinoma by ultra-deep whole-transcriptome sequencing. Oncogene 33(39):4786–4794CrossRefPubMed Lin KT et al (2014) Identification of latent biomarkers in hepatocellular carcinoma by ultra-deep whole-transcriptome sequencing. Oncogene 33(39):4786–4794CrossRefPubMed
26.
Zurück zum Zitat van Veldhoven K et al (2015) Epigenome-wide association study reveals decreased average methylation levels years before breast cancer diagnosis. Clin Epigenet 7:67CrossRef van Veldhoven K et al (2015) Epigenome-wide association study reveals decreased average methylation levels years before breast cancer diagnosis. Clin Epigenet 7:67CrossRef
Metadaten
Titel
MOBCdb: a comprehensive database integrating multi-omics data on breast cancer for precision medicine
verfasst von
Bingbing Xie
Zifeng Yuan
Yadong Yang
Zhidan Sun
Shuigeng Zhou
Xiangdong Fang
Publikationsdatum
10.02.2018
Verlag
Springer US
Erschienen in
Breast Cancer Research and Treatment / Ausgabe 3/2018
Print ISSN: 0167-6806
Elektronische ISSN: 1573-7217
DOI
https://doi.org/10.1007/s10549-018-4708-z

Weitere Artikel der Ausgabe 3/2018

Breast Cancer Research and Treatment 3/2018 Zur Ausgabe

Update Onkologie

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.