Data from: The cancer microbiome atlas (TCMA): A pan-cancer comparative analysis to distinguish organ-associated microbiota from equiprevalent contaminants

Studying the microbial composition of internal organs and their associations with disease remains challenging due to the difficulty of acquiring clinical biopsies. We designed a statistical model to analyze the prevalence of species across sample types from The Cancer Genome Atlas (TCGA), revealing that species equiprevalent across sample types are predominantly contaminants, bearing unique signatures from each TCGA-designated sequencing center. Removing such species mitigated batch effects and isolated the tissue-resident microbiome, which was validated with original TCGA samples. "Mixed-evidence"species can be further distinguished by gene copy and nucleotide variants. We thus present The Cancer Microbiome Atlas (TCMA), a collection of curated, decontaminated microbial compositions of oropharyngeal, esophageal, gastrointestinal, and colorectal tissues. This led to discovery of prognostic species and blood signatures of mucosal barrier injuries, and enabled systematic matched microbe-host multi-omics analyses, which will help guide future studies of the microbiome's role in human health and disease.

由于临床活检样本获取难度较大，解析内脏器官微生物组构成及其与疾病的关联始终是一项具有挑战性的研究课题。本研究设计了一款统计模型，用于分析癌症基因组图谱（The Cancer Genome Atlas, TCGA）不同样本类型中微生物物种的检出率，结果发现，在各类样本中检出率一致的物种大多为外源污染物，且带有各TCGA指定测序中心特有的特征信号。去除这类污染物可有效减少批次效应，并分离得到组织原位微生物组，该结果通过原始TCGA样本得到了验证。‘证据混杂型’微生物物种可进一步通过基因拷贝数与核苷酸变异进行区分。基于此，本研究构建了癌症微生物组图谱（The Cancer Microbiome Atlas, TCMA），该数据集收录了经过质控筛选与去污染处理的口腔咽部、食管、胃肠道以及结直肠组织的微生物组构成数据。该数据集助力研究人员发现了与黏膜屏障损伤相关的预后微生物物种及血液特征信号，并支持开展系统性的匹配型微生物-宿主多组学分析，将为后续探究微生物组在人类健康与疾病中的作用提供重要支撑。