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<p>Gastrointestinal cancer is one of the most burdensome health threats worldwide, accounting for approximately one-quarter of all cancer incidences. Gastric and colorectal cancers are among the most prevalent and lethal malignancies of the gastrointestinal tract globally. Despite steadily rising incidence, the complex cellular landscape comprising the tumor microenvironment and accelerating tumorigenesis remains insufficiently explored. Although single-cell transcriptomics has been employed to investigate this complexity, previous studies are limited by the small number of cells analyzed. In this study, we present a comprehensive single-cell transcriptomic atlas comprising 574,532 cells across 70 cell types from 229 human stomach tissues and 479,629 cells across 70 cell types from 220 human colorectal tissues, spanning diverse phenotypes. Data quality and cell type annotations were rigorous validated utilizing multiple computational tools. Additionally, standardized cell type definitions and annotated clinical information facilitate the usability of this dataset, enabling analysis across clinical subtypes and metastatic states. This resource provides a valuable foundation for meta-analyses of gastric and colorectal cancers at single-cell resolution.</p>

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Integrated single-cell transcriptomic atlas of human gastric and colorectal tissues across diverse phenotypes

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月26日

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  • Yunjin Go,
  • Aki Uesugi,
  • Dakeun Lee,
  • Su Bin Lim

摘要

Gastrointestinal cancer is one of the most burdensome health threats worldwide, accounting for approximately one-quarter of all cancer incidences. Gastric and colorectal cancers are among the most prevalent and lethal malignancies of the gastrointestinal tract globally. Despite steadily rising incidence, the complex cellular landscape comprising the tumor microenvironment and accelerating tumorigenesis remains insufficiently explored. Although single-cell transcriptomics has been employed to investigate this complexity, previous studies are limited by the small number of cells analyzed. In this study, we present a comprehensive single-cell transcriptomic atlas comprising 574,532 cells across 70 cell types from 229 human stomach tissues and 479,629 cells across 70 cell types from 220 human colorectal tissues, spanning diverse phenotypes. Data quality and cell type annotations were rigorous validated utilizing multiple computational tools. Additionally, standardized cell type definitions and annotated clinical information facilitate the usability of this dataset, enabling analysis across clinical subtypes and metastatic states. This resource provides a valuable foundation for meta-analyses of gastric and colorectal cancers at single-cell resolution.