Bridging cancer cell-intrinsic driver genes and -extrinsic cell-cell communication with Driver2Comm

Area of Science:

• Cancer Biology
• Computational Biology
• Immunology

Background:

• Tumor progression is influenced by both cancer cell genetics and the tumor microenvironment (TME).
• Cell-cell communication (CCC) within the TME, particularly immunosuppression, is a key extrinsic factor.
• The interplay between intrinsic cancer drivers and extrinsic CCC remains poorly understood.

Purpose of the Study:

• To develop a computational framework, Driver2Comm, for systematically identifying intrinsic-extrinsic (IE) pathways.
• To connect cancer cell driver genes with their associated CCC signatures in the TME.
• To explore the functional roles and clinical implications of these IE pathways.

Main Methods:

• Development of the Driver2Comm computational framework.
• Application of Driver2Comm to single-cell and spatial transcriptomic data from various cancer types.
• Analysis of driver gene-associated CCC signatures for immune regulation, metastasis, and therapy response.

Main Results:

• Driver2Comm successfully identified IE pathways linking driver genes to CCC signatures.
• These signatures are crucial for immune regulation, metastasis, and predicting therapy response.
• The framework revealed higher-order CCC modules and spatially coherent patterns.
• Clinical value demonstrated in predicting patient survival and response to immune checkpoint blockade.

Conclusions:

• Driver2Comm provides a generalizable method to bridge cancer genomics and the tumor's cellular ecosystem.
• Identified CCC signatures offer insights into TME remodeling mechanisms.
• The findings support biomarker discovery and the development of novel combination therapy strategies.