iBRIDGE: A Data Integration Method to Identify Inflamed Tumors from Single-cell RNA-Seq Data and Differentiate Cell...

Area of Science:

• Oncology
• Immunology
• Bioinformatics

Background:

• Immune checkpoint inhibitors have improved cancer treatment, but predicting patient response remains challenging.
• Preexisting T-cell infiltration in the tumor immune microenvironment (TIME) is a key predictor of immunotherapy success.
• Current bulk transcriptomics methods can assess T-cell infiltration but cannot identify cell-type-specific biomarkers.

Purpose of the Study:

• To develop a novel method, iBRIDGE, for identifying patients with a T-cell inflamed TIME using single-cell RNA sequencing (scRNA-seq) data.
• To integrate bulk RNA-seq reference data with scRNA-seq datasets to enable patient classification.
• To discover cell-type-specific biomarkers associated with inflamed or cold tumor phenotypes.

Main Methods:

• Developed iBRIDGE, a computational method integrating bulk RNA-seq reference data with scRNA-seq malignant cell subsets.
• Validated iBRIDGE against bulk RNA-seq deconvolution assessments using matched patient datasets.
• Applied iBRIDGE to identify inflamed and cold phenotype markers across malignant cells, myeloid cells, and fibroblasts.

Main Results:

• iBRIDGE demonstrated high correlation with bulk RNA-seq assessments (0.85 and 0.9 correlation coefficients).
• Identified type I and II interferon pathways as dominant signals in inflamed phenotypes, particularly in malignant and myeloid cells.
• Revealed TGFβ-driven mesenchymal phenotypes in both fibroblasts and malignant cells, and validated iBRIDGE's applicability to cancer cell lines.

Conclusions:

• iBRIDGE enables the identification of patients with a T-cell inflamed TIME from scRNA-seq data, overcoming limitations of bulk analysis.
• The method facilitates the discovery of novel, cell-type-specific biomarkers predictive of immunotherapy response.
• iBRIDGE provides a robust tool for classifying tumor phenotypes and potentially guiding personalized cancer immunotherapy strategies.