Integrated cancer cell-specific single-cell RNA-seq datasets of immune checkpoint blockade-treated patients
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 conduct...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-04381-6 |
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| author | Mahnoor N. Gondal Marcin Cieslik Arul M. Chinnaiyan |
| author_facet | Mahnoor N. Gondal Marcin Cieslik Arul M. Chinnaiyan |
| author_sort | Mahnoor N. Gondal |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-147abb0f184f46929d107c1871418af7 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-147abb0f184f46929d107c1871418af72025-01-26T12:14:37ZengNature PortfolioScientific Data2052-44632025-01-0112111210.1038/s41597-025-04381-6Integrated cancer cell-specific single-cell RNA-seq datasets of immune checkpoint blockade-treated patientsMahnoor N. Gondal0Marcin Cieslik1Arul M. Chinnaiyan2Department of Computational Medicine & Bioinformatics, University of MichiganDepartment of Computational Medicine & Bioinformatics, University of MichiganDepartment of Computational Medicine & Bioinformatics, University of MichiganAbstract 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.https://doi.org/10.1038/s41597-025-04381-6 |
| spellingShingle | Mahnoor N. Gondal Marcin Cieslik Arul M. Chinnaiyan Integrated cancer cell-specific single-cell RNA-seq datasets of immune checkpoint blockade-treated patients Scientific Data |
| title | Integrated cancer cell-specific single-cell RNA-seq datasets of immune checkpoint blockade-treated patients |
| title_full | Integrated cancer cell-specific single-cell RNA-seq datasets of immune checkpoint blockade-treated patients |
| title_fullStr | Integrated cancer cell-specific single-cell RNA-seq datasets of immune checkpoint blockade-treated patients |
| title_full_unstemmed | Integrated cancer cell-specific single-cell RNA-seq datasets of immune checkpoint blockade-treated patients |
| title_short | Integrated cancer cell-specific single-cell RNA-seq datasets of immune checkpoint blockade-treated patients |
| title_sort | integrated cancer cell specific single cell rna seq datasets of immune checkpoint blockade treated patients |
| url | https://doi.org/10.1038/s41597-025-04381-6 |
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