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Updated: May 6, 2026
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Integrated cancer cell-specific single-cell RNA-seq datasets of immune checkpoint blockade-treated patients
Mahnoor N Gondal1,2, Marcin Cieslik1,2,3,4, Arul M Chinnaiyan1,2,3,5,6,4
1Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI USA.
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 174 patients, and 90,270 cancer cells. This compilation forms a unique resource tailored for investigating 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.
Insights
This study compiles single-cell RNA sequencing data from 174 patients across nine cancer types to explore immune checkpoint blockade (ICB) responses. The resource offers a user-friendly interface for investigating cancer cell behavior during ICB therapy.
Area of Science:
- Oncology
- Immunology
- Bioinformatics
Background:
- Immune checkpoint blockade (ICB) therapies show promise for cancer treatment but exhibit variable efficacy.
- Understanding cell-specific responses to ICB is crucial for improving treatment outcomes.
- Existing single-cell RNA sequencing (scRNA-seq) studies are often limited in scope and accessibility.
Approach:
- Compiled eight scRNA-seq datasets from nine cancer types, including 174 patients and 90,270 cancer cells.
- Meticulously curated, quality-checked, pre-processed, and analyzed the integrated dataset.
- Developed a user-friendly interface for seamless data exploration and shared underlying code and data.
Key Points:
- The integrated resource facilitates investigation of cancer cell responses to ICB across diverse cancer types.
- Provides a large-scale dataset (90,270 cells) for robust analysis of ICB treatment effects.
- Enhanced accessibility through a dedicated interface and shared code empowers researchers.
Conclusions:
- This comprehensive scRNA-seq resource aids in understanding cancer cell heterogeneity and response to ICB.
- Facilitates deeper insights into the mechanisms of ICB therapy across various malignancies.
- Supports researchers in leveraging single-cell data for advancing cancer immunotherapy strategies.
