Multi‐Transcriptomic Analysis Reveals That <scp>EREG</scp> ‐Driven <scp>TME</scp> Crosstalk Defines Anti‐ <scp>EGFR</scp> Response in Colorectal Cancer

Sidedness influences colorectal cancer (CRC) prognosis and treatment response, yet the mechanism dictating differential EGFR inhibitor (EGFRI) sensitivity is unclear. This study investigated the tumor microenvironment (TME) in relation to EGFRI eligibility-clinically defined by factors such as tumor sidedness (e.g., left-sided), RAS/BRAF wild-type status, and microsatellite stability (MSS)-using integrated single-cell RNA sequencing (scRNA-seq), with bulk RNA-seq and spatial transcriptomics validation. We found cancer cell features reflected EGFRI eligibility more strongly than sidedness. EGFRI eligible tumors exhibited high Epiregulin (EREG) expression by cancer cells. Cell interaction analysis revealed a specific "EREG/EGFR/CSF axis" in EGFRI eligible CRC: EREG derived from cancer cell stimulates EGFR-expressing non-myCAF subtypes of cancer-associated fibroblasts (CAFs), which signal via CSF to M1/M2-like Tumor-Associated Macrophages/Monocytes (TAM/TAMo), potentially promoting M2 polarization. Spatial analysis confirmed the proximity of these interacting cell populations and localized EGFR pathway activation near cancer cells specifically in eligible tumors. This study provides a TME-centric view of EGFRI eligibility, identifying a key intercellular communication network driving differential responses. These findings suggest TME features could offer more precise patient stratification than sidedness alone, potentially improving CRC therapeutic strategies.

Authors

Institutions

Publication Details

Journal
Cancer Medicine
Published
2026-04-27
DOI
https://doi.org/10.1002/cam4.71853
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multi‐Transcriptomic Analysis Reveals That EREG ‐Driven TME Crosstalk Defines Anti‐ EGFR Response in Colorectal Cancer

Hiroshi Tazawa, Atsuki Taniguchi, Nobuhiko Kanaya, Shinji Kuroda et al.
Cancer Medicine
Single-cell and spatial transcriptomics
article

Multi‐Transcriptomic Analysis Reveals That EREG ‐Driven TME Crosstalk Defines Anti‐ EGFR Response in Colorectal Cancer

Hiroshi Tazawa, Atsuki Taniguchi, Nobuhiko Kanaya, Shinji Kuroda, Satoru Kikuchi, Yoshihiko Kakiuchi, Tomohiko Yagi, Shohei Nogi, Toshiyoshi Fujiwara, Shunsuke Kagawa
article en

Abstract

Sidedness influences colorectal cancer (CRC) prognosis and treatment response, yet the mechanism dictating differential EGFR inhibitor (EGFRI) sensitivity is unclear. This study investigated the tumor microenvironment (TME) in relation to EGFRI eligibility-clinically defined by factors such as tumor sidedness (e.g., left-sided), RAS/BRAF wild-type status, and microsatellite stability (MSS)-using integrated single-cell RNA sequencing (scRNA-seq), with bulk RNA-seq and spatial transcriptomics validation. We found cancer cell features reflected EGFRI eligibility more strongly than sidedness. EGFRI eligible tumors exhibited high Epiregulin (EREG) expression by cancer cells. Cell interaction analysis revealed a specific "EREG/EGFR/CSF axis" in EGFRI eligible CRC: EREG derived from cancer cell stimulates EGFR-expressing non-myCAF subtypes of cancer-associated fibroblasts (CAFs), which signal via CSF to M1/M2-like Tumor-Associated Macrophages/Monocytes (TAM/TAMo), potentially promoting M2 polarization. Spatial analysis confirmed the proximity of these interacting cell populations and localized EGFR pathway activation near cancer cells specifically in eligible tumors. This study provides a TME-centric view of EGFRI eligibility, identifying a key intercellular communication network driving differential responses. These findings suggest TME features could offer more precise patient stratification than sidedness alone, potentially improving CRC therapeutic strategies.

Cancer MedicineVol. 15(5)
Okayama University (JP), Okayama University Hospital (JP)
Japan Society for the Promotion of Science
Good health and well-being
Openalex Percentile: Top 14%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.