A CAVIN1/SULF1-associated myCAF signature predicts metastatic progression in colorectal cancer

Abstract Although myofibroblastic cancer-associated fibroblasts (myCAFs) drive colorectal cancer (CRC) progression, the transcriptional dynamics underlying their metastatic maturation remain poorly understood. Here, we integrated five single-cell RNA sequencing datasets and two bulk transcriptomic cohorts encompassing normal colon, primary tumors (pCRC), and metastatic CRC (mCRC), combining pseudotime trajectory inference, consensus molecular subtyping (CMS), and ensemble machine learning. Findings were experimentally validated by qRT-PCR across 185 clinical specimens and four CRC cell lines. Trajectory modeling revealed a progressive myCAF continuum toward an extracellular matrix (ECM)-remodeling phenotype enriched in metastases ( P < 0.05). This myCAF maturation was associated with stroma-rich CMS4 enrichment, increasing from 14.7% in pCRC to 72.9% in liver and 90.0% in peritoneal metastases ( P < 2.2 × 10 − 16 ). Ensemble machine learning prioritized CAVIN1 and SULF1 as top discriminative features (AUCs > 0.90, P < 0.0001), exhibiting synchronized dynamics with canonical myCAF markers ( r = 0.79, P = 2.48 × 10 − 5 ). Experimental validation confirmed their fibroblast-specific expression, significant metastatic upregulation, and robust discriminatory capacity in distinguishing metastatic from pCRC (AUCs ≥ 0.80, P < 0.0001). Delineating the CAVIN1 / SULF1 -associated myCAF maturation continuum provides mechanistic insights into stroma-driven progression and reveals candidate biomarkers for metastatic risk stratification in CRC.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-10-07
DOI
https://doi.org/10.1038/s41598-026-73551-2
Primary Topic
Cancer Cells and Metastasis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A CAVIN1/SULF1-associated myCAF signature predicts metastatic progression in colorectal cancer

Zohreh Hojati, Laleh Shariati, Bahareh Maleki
Scientific Reports
Cancer Cells and Metastasis
article

A CAVIN1/SULF1-associated myCAF signature predicts metastatic progression in colorectal cancer

Zohreh Hojati, Laleh Shariati, Bahareh Maleki
article en

Abstract

Abstract Although myofibroblastic cancer-associated fibroblasts (myCAFs) drive colorectal cancer (CRC) progression, the transcriptional dynamics underlying their metastatic maturation remain poorly understood. Here, we integrated five single-cell RNA sequencing datasets and two bulk transcriptomic cohorts encompassing normal colon, primary tumors (pCRC), and metastatic CRC (mCRC), combining pseudotime trajectory inference, consensus molecular subtyping (CMS), and ensemble machine learning. Findings were experimentally validated by qRT-PCR across 185 clinical specimens and four CRC cell lines. Trajectory modeling revealed a progressive myCAF continuum toward an extracellular matrix (ECM)-remodeling phenotype enriched in metastases ( P < 0.05). This myCAF maturation was associated with stroma-rich CMS4 enrichment, increasing from 14.7% in pCRC to 72.9% in liver and 90.0% in peritoneal metastases ( P < 2.2 × 10 − 16 ). Ensemble machine learning prioritized CAVIN1 and SULF1 as top discriminative features (AUCs > 0.90, P < 0.0001), exhibiting synchronized dynamics with canonical myCAF markers ( r = 0.79, P = 2.48 × 10 − 5 ). Experimental validation confirmed their fibroblast-specific expression, significant metastatic upregulation, and robust discriminatory capacity in distinguishing metastatic from pCRC (AUCs ≥ 0.80, P < 0.0001). Delineating the CAVIN1 / SULF1 -associated myCAF maturation continuum provides mechanistic insights into stroma-driven progression and reveals candidate biomarkers for metastatic risk stratification in CRC.

Scientific Reports
Isfahan University of Medical Sciences (IR), University of Isfahan (IR)
Openalex Percentile: Top 16%
Cancer Cells and Metastasis
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.