Integrated cancer cell-specific single-cell RNA-seq datasets of immune checkpoint blockade-treated patients

Immune checkpoint blockade (ICB) therapies have emerged as a promising avenue for the treatment of various cancers. Despite their success, the efficacy of these treatments is variable across patients and cancer types. Numerous single-cell RNA-sequencing (scRNA-seq) studies have been conducted to unravel cell-specific responses to ICB treatment. However, these studies are limited in their sample sizes and require advanced coding skills for exploration. Here, we have compiled eight scRNA-seq datasets from nine cancer types, encompassing 223 patients, 90,270 cancer cells, and 265,671 other cell types. This compilation forms a unique resource tailored to investigate how cancer cells respond to ICB treatment across cancer types. We meticulously curated, quality-checked, pre-processed, and analyzed the data, ensuring easy access for researchers. Moreover, we designed a user-friendly interface for seamless exploration. By sharing the code and data for creating these interfaces, we aim to assist fellow researchers. These resources offer valuable support to those interested in leveraging and exploring single-cell datasets across diverse cancer types, facilitating a comprehensive understanding of ICB responses.

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Publication Details

Journal
Scientific Data
Published
2025-01-22
DOI
https://doi.org/10.1038/s41597-025-04381-6
Citations
10
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
10.45

Funders

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article

Integrated cancer cell-specific single-cell RNA-seq datasets of immune checkpoint blockade-treated patients

Arul M. Chinnaiyan, Mahnoor Gondal, Marcin Cieślik
10 citations
Scientific Data
Cancer Immunotherapy and Biomarkers
10.45
article

Integrated cancer cell-specific single-cell RNA-seq datasets of immune checkpoint blockade-treated patients

Arul M. Chinnaiyan, Mahnoor Gondal, Marcin Cieślik
article en
10 citations

Abstract

Immune checkpoint blockade (ICB) therapies have emerged as a promising avenue for the treatment of various cancers. Despite their success, the efficacy of these treatments is variable across patients and cancer types. Numerous single-cell RNA-sequencing (scRNA-seq) studies have been conducted to unravel cell-specific responses to ICB treatment. However, these studies are limited in their sample sizes and require advanced coding skills for exploration. Here, we have compiled eight scRNA-seq datasets from nine cancer types, encompassing 223 patients, 90,270 cancer cells, and 265,671 other cell types. This compilation forms a unique resource tailored to investigate how cancer cells respond to ICB treatment across cancer types. We meticulously curated, quality-checked, pre-processed, and analyzed the data, ensuring easy access for researchers. Moreover, we designed a user-friendly interface for seamless exploration. By sharing the code and data for creating these interfaces, we aim to assist fellow researchers. These resources offer valuable support to those interested in leveraging and exploring single-cell datasets across diverse cancer types, facilitating a comprehensive understanding of ICB responses.

Scientific DataVol. 12(1)
Howard Hughes Medical Institute (US), University of Michigan (US), Michigan Medicine (US), Michigan Center for Translational Pathology (US), Michigan Cancer Research Consortium (US)
Vanderbilt University Medical Center, National Cancer Institute
Openalex Percentile: Top 2%
Cancer Immunotherapy and Biomarkers
10.45
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