Guo Wenbo, Yin Zikang, Mei Qinglin, Li Lianshuo, Gong Yonghui, Li Xinqi, Zhang Wei, Lei Wenjie, Liu Bingqiang, Hou Lin, Yang Mei, Gu Jin
MOE Key Lab of Bioinformatics, BNRIST Bioinformatics Division, Department of Automation, Tsinghua University, Beijing, China.
State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
Comput Struct Biotechnol J. 2025 Jun 20;27:2701-2710. doi: 10.1016/j.csbj.2025.06.031. eCollection 2025.
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.
乳腺癌（BC）是全球女性中最常见的癌症类型之一。了解BC复杂的分子和细胞特征对于推进精准治疗至关重要。为了实现更可靠和可重复的生物学发现，从不同的BC队列中收集分子数据并建立一个综合、通用的分析平台至关重要。在此，我们展示了BCMA（乳腺癌分子图谱，http://lifeome.net/database/bcma/），这是一个多尺度、多组学的BC数据库，包含6个批量多组学数据集和9个单细胞转录组学数据集，共涵盖5424个病例和236,363个细胞。BCMA系统地表征了BC的分子特征，包括基因突变、拷贝数改变、RNA表达、miRNA表达、DNA甲基化以及临床表型和细胞异质性。同时，提供了一个以基因为中心的用户友好搜索界面，可实现临床信息统计、基因组事件分析、差异多组学特征识别、功能富集分析、生存分析、共表达分析以及单细胞基因表达谱分析和细胞类型注释。该平台在增强对BC潜在分子特征的理解以及促进疾病相关生物标志物的识别方面具有巨大潜力。
