Cross-cohort multi-omics analysis identifies novel clusters driven by EMT signatures in colorectal cancer

IntroductionThe pronounced heterogeneity of colorectal cancer (CRC) significantly impacts patient prognosis and therapeutic response, making elucidation of its molecular mechanisms critical for developing precision treatment strategies. This study aimed to systematically characterize tumor cell hete...

Full description

Saved in:
Bibliographic Details
Main Authors: Wu Ning, Wenqing Jia, Jingyuan Ning, Lei Zhou, Zongze Li, Lin Zhang, Xin Song
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Immunology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2025.1628005/full
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849469801710223360
author Wu Ning
Wenqing Jia
Jingyuan Ning
Lei Zhou
Zongze Li
Lin Zhang
Xin Song
author_facet Wu Ning
Wenqing Jia
Jingyuan Ning
Lei Zhou
Zongze Li
Lin Zhang
Xin Song
author_sort Wu Ning
collection DOAJ
description IntroductionThe pronounced heterogeneity of colorectal cancer (CRC) significantly impacts patient prognosis and therapeutic response, making elucidation of its molecular mechanisms critical for developing precision treatment strategies. This study aimed to systematically characterize tumor cell heterogeneity and explore its clinical implications.MethodsFive single-cell RNA sequencing cohorts were integrated (comprising 70 CRC samples and 164,173 cells) to systematically analyze tumor cell heterogeneity. Unsupervised clustering analysis based on VEGFR+ tumor cell signature genes was used to stratify CRC patients. Key molecular mechanisms were validated through in vitro cellular experiments, in vivo animal models, molecular docking, and dynamics simulations.ResultsThe analysis successfully identified five distinct tumor cell subtypes, with the VEGFR+ subtype exhibiting marked epithelial-mesenchymal transition (EMT) activation signatures and strong association with metastasis and poor clinical outcomes. Based on VEGFR+ signature genes, CRC patients were stratified into three subgroups: C1 (metabolically active), C2 (proliferative), and C3 (invasive), with the C3 subtype demonstrating high metastatic potential, stem-like properties, and an immunosuppressive microenvironment, along with a five-year survival rate below 50%. Mechanistic investigations identified HOXC6 as a key driver of the C3 subtype, with HOXC6 knockout significantly suppressing CRC cell proliferation, migration, and invasion. Furthermore, molecular docking revealed that the targeted agent abemaciclib effectively binds HOXC6, with both cellular and animal experiments confirming its ability to inhibit CRC cell functions and significantly reduce tumor burden in nude mice.DiscussionThis study establishes the first single-cell-resolution molecular classification system for CRC, delineates the mechanistic link between EMT subtypes and metastatic progression, and identifies HOXC6 as a novel therapeutic vulnerability. These findings provide a translational foundation for precision oncology and offer new rationale for precision diagnosis and treatment of colorectal cancer.
format Article
id doaj-art-871dcc09b5ee43beb6a47c13a9e19175
institution Kabale University
issn 1664-3224
language English
publishDate 2025-06-01
publisher Frontiers Media S.A.
record_format Article
series Frontiers in Immunology
spelling doaj-art-871dcc09b5ee43beb6a47c13a9e191752025-08-20T03:25:20ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-06-011610.3389/fimmu.2025.16280051628005Cross-cohort multi-omics analysis identifies novel clusters driven by EMT signatures in colorectal cancerWu Ning0Wenqing Jia1Jingyuan Ning2Lei Zhou3Zongze Li4Lin Zhang5Xin Song6Department of General Surgery, China-Japan Friendship Hospital, Beijing, ChinaInstitute of Clinical Medicine, China-Japan Friendship Hospital, Beijing, ChinaInstitute of Basic Medical Sciences, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, ChinaDepartment of General Surgery, China-Japan Friendship Hospital, Beijing, ChinaDepartment of General Surgery, China-Japan Friendship Hospital, Beijing, ChinaDepartment of General Surgery, China-Japan Friendship Hospital, Beijing, ChinaDepartment of General Surgery, China-Japan Friendship Hospital, Beijing, ChinaIntroductionThe pronounced heterogeneity of colorectal cancer (CRC) significantly impacts patient prognosis and therapeutic response, making elucidation of its molecular mechanisms critical for developing precision treatment strategies. This study aimed to systematically characterize tumor cell heterogeneity and explore its clinical implications.MethodsFive single-cell RNA sequencing cohorts were integrated (comprising 70 CRC samples and 164,173 cells) to systematically analyze tumor cell heterogeneity. Unsupervised clustering analysis based on VEGFR+ tumor cell signature genes was used to stratify CRC patients. Key molecular mechanisms were validated through in vitro cellular experiments, in vivo animal models, molecular docking, and dynamics simulations.ResultsThe analysis successfully identified five distinct tumor cell subtypes, with the VEGFR+ subtype exhibiting marked epithelial-mesenchymal transition (EMT) activation signatures and strong association with metastasis and poor clinical outcomes. Based on VEGFR+ signature genes, CRC patients were stratified into three subgroups: C1 (metabolically active), C2 (proliferative), and C3 (invasive), with the C3 subtype demonstrating high metastatic potential, stem-like properties, and an immunosuppressive microenvironment, along with a five-year survival rate below 50%. Mechanistic investigations identified HOXC6 as a key driver of the C3 subtype, with HOXC6 knockout significantly suppressing CRC cell proliferation, migration, and invasion. Furthermore, molecular docking revealed that the targeted agent abemaciclib effectively binds HOXC6, with both cellular and animal experiments confirming its ability to inhibit CRC cell functions and significantly reduce tumor burden in nude mice.DiscussionThis study establishes the first single-cell-resolution molecular classification system for CRC, delineates the mechanistic link between EMT subtypes and metastatic progression, and identifies HOXC6 as a novel therapeutic vulnerability. These findings provide a translational foundation for precision oncology and offer new rationale for precision diagnosis and treatment of colorectal cancer.https://www.frontiersin.org/articles/10.3389/fimmu.2025.1628005/fullcolorectal cancerEMTHOXC6scRNA-seqmetastatic
spellingShingle Wu Ning
Wenqing Jia
Jingyuan Ning
Lei Zhou
Zongze Li
Lin Zhang
Xin Song
Cross-cohort multi-omics analysis identifies novel clusters driven by EMT signatures in colorectal cancer
Frontiers in Immunology
colorectal cancer
EMT
HOXC6
scRNA-seq
metastatic
title Cross-cohort multi-omics analysis identifies novel clusters driven by EMT signatures in colorectal cancer
title_full Cross-cohort multi-omics analysis identifies novel clusters driven by EMT signatures in colorectal cancer
title_fullStr Cross-cohort multi-omics analysis identifies novel clusters driven by EMT signatures in colorectal cancer
title_full_unstemmed Cross-cohort multi-omics analysis identifies novel clusters driven by EMT signatures in colorectal cancer
title_short Cross-cohort multi-omics analysis identifies novel clusters driven by EMT signatures in colorectal cancer
title_sort cross cohort multi omics analysis identifies novel clusters driven by emt signatures in colorectal cancer
topic colorectal cancer
EMT
HOXC6
scRNA-seq
metastatic
url https://www.frontiersin.org/articles/10.3389/fimmu.2025.1628005/full
work_keys_str_mv AT wuning crosscohortmultiomicsanalysisidentifiesnovelclustersdrivenbyemtsignaturesincolorectalcancer
AT wenqingjia crosscohortmultiomicsanalysisidentifiesnovelclustersdrivenbyemtsignaturesincolorectalcancer
AT jingyuanning crosscohortmultiomicsanalysisidentifiesnovelclustersdrivenbyemtsignaturesincolorectalcancer
AT leizhou crosscohortmultiomicsanalysisidentifiesnovelclustersdrivenbyemtsignaturesincolorectalcancer
AT zongzeli crosscohortmultiomicsanalysisidentifiesnovelclustersdrivenbyemtsignaturesincolorectalcancer
AT linzhang crosscohortmultiomicsanalysisidentifiesnovelclustersdrivenbyemtsignaturesincolorectalcancer
AT xinsong crosscohortmultiomicsanalysisidentifiesnovelclustersdrivenbyemtsignaturesincolorectalcancer