BCMA: An integrative and versatile database for multi-scale and multi-omics molecular atlas of breast cancer

Breast cancer (BC) is one of the most common cancer types among women worldwide. Understanding the complex molecular and cellular characteristics of BC is crucial for advancing precision treatment. To enable more reliable and reproducible biological discoveries, it is critical to collect molecular data from diverse BC cohorts and establish an integrative, versatile analysis platform. Here, we present BCMA (Breast Cancer Molecular Atlas, http://lifeome.net/database/bcma/), a multi-scale, multi-omics BC database that encompasses 6 bulk multi-omics datasets and 9 single-cell transcriptomics datasets, collectively covering 5424 cases and 236,363 cells. The BCMA systemically characterizes the molecular features of BC, including gene mutations, copy number alterations, RNA expression, miRNA expression, DNA methylation, as well as clinical phenotypes and cell heterogeneity. Meanwhile, a user-friendly interface for gene-centered search is provided, achieving the clinical information statistics, genomic events analysis, differential multi-omics feature identification, functional enrichment analysis, survival analysis, co-expression analysis, as well as single-cell gene expression profiling and cell type annotation. This platform holds great potential to enhance the understanding of molecular characteristics underlying BC and to facilitate the identification of disease-associated biomarkers.

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Publication Details

Journal
Computational and Structural Biotechnology Journal
Published
2025-01-01
DOI
https://doi.org/10.1016/j.csbj.2025.06.031
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

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article

BCMA: An integrative and versatile database for multi-scale and multi-omics molecular atlas of breast cancer

Zongsheng Yin, Jin Gu, Bingqiang Liu, Qinglin Mei et al.
Computational and Structural Biotechnology Journal
Single-cell and spatial transcriptomics
article

BCMA: An integrative and versatile database for multi-scale and multi-omics molecular atlas of breast cancer

Zongsheng Yin, Jin Gu, Bingqiang Liu, Qinglin Mei, Xinqi Li, Lianshuo Li, Mei Yang, Wenbo Guo, Lei Wang, Wei Zhang, Yonghui Gong, Lin Hou
article en

Abstract

Breast cancer (BC) is one of the most common cancer types among women worldwide. Understanding the complex molecular and cellular characteristics of BC is crucial for advancing precision treatment. To enable more reliable and reproducible biological discoveries, it is critical to collect molecular data from diverse BC cohorts and establish an integrative, versatile analysis platform. Here, we present BCMA (Breast Cancer Molecular Atlas, http://lifeome.net/database/bcma/), a multi-scale, multi-omics BC database that encompasses 6 bulk multi-omics datasets and 9 single-cell transcriptomics datasets, collectively covering 5424 cases and 236,363 cells. The BCMA systemically characterizes the molecular features of BC, including gene mutations, copy number alterations, RNA expression, miRNA expression, DNA methylation, as well as clinical phenotypes and cell heterogeneity. Meanwhile, a user-friendly interface for gene-centered search is provided, achieving the clinical information statistics, genomic events analysis, differential multi-omics feature identification, functional enrichment analysis, survival analysis, co-expression analysis, as well as single-cell gene expression profiling and cell type annotation. This platform holds great potential to enhance the understanding of molecular characteristics underlying BC and to facilitate the identification of disease-associated biomarkers.

Computational and Structural Biotechnology JournalVol. 27
Shandong University (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Zhujiang Hospital (CN), Hainan Agricultural School (CN), Institute of Hematology & Blood Diseases Hospital (CN), Tsinghua University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Key Technologies Research and Development Program, National Key Research and Development Program of China
Good health and well-being
Openalex Percentile: Top 87%
Single-cell and spatial transcriptomics
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