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

## TL;DR

Driver2Comm is a tool that connects cancer cell mutations to cell communication in the tumor environment, revealing insights into tumor progression and treatment response.

## Contribution

Driver2Comm introduces a novel framework to systematically link cancer driver genes with cell-cell communication signatures in the tumor microenvironment.

## Key findings

- Driver gene-associated communication signatures are linked to immune regulation, metastasis, and therapy response.
- These signatures predict patient survival and response to immune checkpoint blockade.
- Driver2Comm identifies cell-type-specific and spatially coherent communication patterns in tumors.

## Abstract

Tumor development and progression are affected not only by cancer cell-intrinsic factors comprising complex genetic variations, but also by -extrinsic factors such as cell-cell communication (CCC)-mediated immunosuppression. However, whether and how these two types of factors influence each other remains an open question. We present Driver2Comm, a general computational framework designed to systematically identify intrinsic-extrinsic (IE) pathways that functionally connect cancer cell driver genes with their associated CCC signatures in the tumor microenvironment (TME). By applying Driver2Comm to single-cell and spatial transcriptomic datasets of multiple cancer types, we find that driver gene-associated CCC signatures play critical roles in immune regulation, metastasis, and therapy response. These signatures not only illuminate mechanisms of TME remodeling but also demonstrate clinical value in predicting patient survival and response to immune checkpoint blockade. Furthermore, Driver2Comm captures higher-order, cell-type-pair-specific CCC functional modules and spatially coherent CCC patterns in tissue contexts. As a generalizable tool, Driver2Comm bridges cancer genomics and cellular ecosystems, offering insights into biomarker discovery and combination therapy strategies.

In this study, we introduce Driver2Comm, a computational tool designed to bridge two critical aspects of cancer biology: intrinsic genetic drivers and extrinsic cellular communication. It is well known that cancer progression is influenced not only by mutations within cancer cells but also by interactions between different cell types in the tumor microenvironment. However, how these two layers connect has remained largely unclear. Using single-cell and spatial transcriptomic data, Driver2Comm enables the identification of potential signaling pathways linking cancer driver genes to their associated cell-cell communication events. We applied Driver2Comm across multiple cancer types, including pancreatic cancer, breast cancer, neuroblastoma, and oral squamous cell carcinoma, and discovered genetic driver-associated cellular communication signatures tied to key processes such as immune evasion, metastasis, and treatment response. These signatures also showed clinical value in predicting patient survival and immunotherapy outcomes. By making these connections visible and interpretable, our work provides a new way to understand how tumors function as complex ecosystems, offering potential clues for future combination therapies.