Related Experiment Video
Updated: Nov 8, 2025
Author Spotlight: Exploring Strategies for Successful Immune Response Against Tumors
Published on: August 16, 2024
STARTRAC analyses of scRNAseq data from tumor models reveal T cell dynamics and therapeutic targets
Dev Bhatt1, Boxi Kang2, Deepali Sawant1
1Department of Inflammation and Oncology, Amgen Research, Amgen, South San Francisco, CA.
Abstract:
Single-cell RNA sequencing is a powerful tool to examine cellular heterogeneity, novel markers and target genes, and therapeutic mechanisms in human cancers and animal models. Here, we analyzed single-cell RNA sequencing data of T cells obtained from multiple mouse tumor models by PCA-based subclustering coupled with TCR tracking using the STARTRAC algorithm. This approach revealed various differentiated T cell subsets and activation states, and a correspondence of T cell subsets between human and mouse tumors. STARTRAC analyses demonstrated peripheral T cell subsets that were developmentally connected with tumor-infiltrating CD8+ cells, CD4+ Th1 cells, and T reg cells. In addition, large amounts of paired TCRα/β sequences enabled us to identify a specific enrichment of paired public TCR clones in tumor. Finally, we identified CCR8 as a tumor-associated T reg cell marker that could preferentially deplete tumor-associated T reg cells. We showed that CCR8-depleting antibody treatment provided therapeutic benefit in CT26 tumors and synergized with anti-PD-1 treatment in MC38 and B16F10 tumor models.
Insights
This study uses single-cell RNA sequencing and STARTRAC to analyze T cells in mouse tumors, identifying CCR8 as a targetable marker on tumor-associated regulatory T cells for cancer therapy.
Area of Science:
- Immunology
- Oncology
- Bioinformatics
Background:
- Single-cell RNA sequencing (scRNA-seq) is crucial for understanding cellular diversity in cancer.
- T cell heterogeneity within tumors influences therapeutic responses.
- Identifying specific T cell subsets and their roles is key to developing novel cancer treatments.
Purpose of the Study:
- To characterize T cell subsets and activation states in mouse tumor models using scRNA-seq.
- To identify developmental relationships between peripheral and tumor-infiltrating T cells.
- To discover novel therapeutic targets for T cell-mediated cancer immunotherapy.
Main Methods:
- Analysis of scRNA-seq data from mouse tumor models.
- Principal Component Analysis (PCA)-based subclustering of T cells.
- T cell receptor (TCR) tracking using the STARTRAC algorithm.
- Identification and validation of CCR8 as a tumor-associated regulatory T cell marker.
Main Results:
- Revealed diverse differentiated T cell subsets and activation states.
- Demonstrated developmental connections between peripheral T cells and tumor-infiltrating CD8+, CD4+ Th1, and T regulatory cells.
- Identified an enrichment of public TCR clones in tumors.
- Validated CCR8 as a marker for tumor-associated regulatory T cells.
Conclusions:
- CCR8-depleting antibody treatment showed therapeutic benefits in CT26 tumors.
- CCR8 depletion synergized with anti-PD-1 therapy in MC38 and B16F10 tumor models.
- Targeting CCR8+ regulatory T cells represents a promising strategy for cancer immunotherapy.
