Evidence map›Paper›PMID 41165126›Full record

ArticleCancer science2026

A Robust Immunohistochemistry-Based Classification for BRAF V600E-Mutant Colorectal Cancer With Clinical Implications.

Chao Liu, Yuli Ruan, Tong Wu, Xindi Luan, Yue Ma, Hong Wang, Tianjiao Dang, Yiwen Ou, Bojun Wang, Chunhui Zhang and 2 more

Abstract read
In one paragraph

Article in Cancer science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

12 authors.

Chao LiuDepartment of Gastrointestinal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.ORCID https://orcid.org/0009-0001-8104-6750
Yuli RuanDepartment of Gastrointestinal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Tong WuDepartment of Gastrointestinal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Xindi LuanDepartment of Gastrointestinal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Yue MaDepartment of Gastrointestinal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Hong WangDepartment of Gastrointestinal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Tianjiao DangDepartment of Gastrointestinal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Yiwen OuDepartment of Gastrointestinal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Bojun WangDepartment of Gastrointestinal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Chunhui ZhangDepartment of Gastrointestinal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Hongxue MengDepartment of Pathology, Harbin Medical University Cancer Hospital, Harbin, China.
Yanqiao ZhangDepartment of Gastrointestinal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.ORCID https://orcid.org/0000-0002-6206-8364

Funding

Noncommunicable Chronic Diseases-National Science and Technology Major Project 2023ZD0501600the Key Project of Research and Development Plan in Heilongjiang Province 2022ZX06C01the Key Project of Research and Development Plan in Heilongjiang Province JD2023SJ40the National Natural Science Foundation of China 82373372the National Natural Science Foundation of China U22A20330
6 · The paper itself

Abstract

BRAF V600E-mutant colorectal cancer (CRC) represents a distinct molecular subtype with considerable heterogeneity in tumor biology and therapeutic response. Although gene expression-based classifications (BM1/BM2 subtypes) provide valuable insights into underlying molecular and immune features, their clinical application is limited by the need for high-throughput sequencing. This study aims to establish an immunohistochemistry (IHC)-based classification system to enable practical subtype stratification and aid prognostic and therapeutic evaluation. Using two independent cohorts (public dataset, n = 218; institutional cohort, n = 122), we performed differential expression analysis, machine learning modeling, and clinical feasibility evaluation. Fourteen candidate markers were identified, and a decision tree algorithm selected CD8 and ARHGEF17 as optimal classifiers. Based on these markers, two IHC-based subtypes were established: iBM1 (CD8

Indexed as

Biomarkers, TumorColorectal NeoplasmsImmunohistochemistryProto-Oncogene Proteins B-rafAgedFemaleGene Expression ProfilingHumansMachine LearningMaleMiddle AgedMutationPrognosisTranscriptomeBiomarkers, TumorBRAF protein, humanProto-Oncogene Proteins B-rafBM subtypesBRAF V600E‐mutant colorectal cancerICIs therapyimmunohistochemistryprognostic

Identifiers

PMID41165126
PMCPMC12775562

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.