The Curated Cancer Cell Atlas provides a comprehensive characterization of tumors at single-cell resolution

Michael Tyler; Avishai Gavish; Chaya Barbolin; Roi Tschernichovsky; Rouven Hoefflin; Michael Mints; Sidharth V. Puram; Itay Tirosh

doi:10.1038/s43018-025-00957-8

The Curated Cancer Cell Atlas provides a comprehensive characterization of tumors at single-cell resolution

Michael Tyler^*
, Avishai Gavish
, Chaya Barbolin
, Roi Tschernichovsky
, Rouven Hoefflin
, Michael Mints
, Sidharth V. Puram
, Itay Tirosh^*

^*Corresponding author for this work

Department of Molecular Cell Biology

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

Recent years have seen a rapid proliferation of single-cell cancer studies, yet most of these studies profiled few tumors, limiting their statistical power. Combining data and results across studies holds great promise but also involves various challenges. We recently began to address these challenges by curating a large collection of cancer single-cell RNA-sequencing datasets, leveraging it for systematic analyses of tumor heterogeneity. Here we greatly extend this repository to 124 datasets for over 40 cancer types, together comprising 2,836 samples, with improved data annotations, visualizations and exploration. Using this vast cohort, we generate an updated map of recurrent expression programs in malignant cells and systematically quantify context-dependent gene expression and cell-cycle patterns across cell types and cancer types. These data, annotations and analysis results are all freely available for exploration and download through the Curated Cancer Cell Atlas, a central community resource that opens new avenues in cancer research.

Original language	English
Pages (from-to)	1088-1101
Number of pages	14
Journal	Nature Cancer
Volume	6
Issue number	6
DOIs	https://doi.org/10.1038/s43018-025-00957-8
Publication status	Published Online - 8 May 2025

Funding

We thank all members of the I.T. lab for helpful discussions and comments. We thank the Weizmann Information Technology Internet and Mobile Development Team for their work on the 3CA website. This work was supported by the Israeli Council for Higher Education through the Weizmann Data Science Research Center and by the Israel Science Foundation. I.T. is the incumbent of the Dr. Celia Zwillenberg-Fridman and Dr. Lutz Zwillenberg Career Development Chair and is supported by the Zuckerman Science, Technology, Engineering and Mathematics Leadership Program, the Mexican Friends New Generation and the Benoziyo Endowment Fund. R.H. is funded by the Walter Benjamin Program from the German Research Foundation.

All Science Journal Classification (ASJC) codes

Oncology
Cancer Research

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10.1038/s43018-025-00957-8

Cite this

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title = "The Curated Cancer Cell Atlas provides a comprehensive characterization of tumors at single-cell resolution",

abstract = "Recent years have seen a rapid proliferation of single-cell cancer studies, yet most of these studies profiled few tumors, limiting their statistical power. Combining data and results across studies holds great promise but also involves various challenges. We recently began to address these challenges by curating a large collection of cancer single-cell RNA-sequencing datasets, leveraging it for systematic analyses of tumor heterogeneity. Here we greatly extend this repository to 124 datasets for over 40 cancer types, together comprising 2,836 samples, with improved data annotations, visualizations and exploration. Using this vast cohort, we generate an updated map of recurrent expression programs in malignant cells and systematically quantify context-dependent gene expression and cell-cycle patterns across cell types and cancer types. These data, annotations and analysis results are all freely available for exploration and download through the Curated Cancer Cell Atlas, a central community resource that opens new avenues in cancer research.",

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AU - Mints, Michael

AU - Puram, Sidharth V.

AU - Tirosh, Itay

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The Curated Cancer Cell Atlas provides a comprehensive characterization of tumors at single-cell resolution

Abstract

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All Science Journal Classification (ASJC) codes

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