Evidence map›Paper›PMID 39875913›Full record

ArticleJournal of translational medicine2025

Prognostic models of immune-related cell death and stress unveil mechanisms driving macrophage phenotypic evolution in colorectal cancer.

Hao Liu, Chuhan Zhang, Sanfei Peng, Yuhan Yin, Yishi Xu, Sihan Wu, Liping Wang, Yang Fu

Abstract read
In one paragraph

Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Hao Liu *Department of Gastrointestinal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Chuhan Zhang *Department of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Sanfei PengDepartment of Gastrointestinal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Yuhan YinDepartment of Gastrointestinal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Yishi XuDepartment of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Sihan WuDepartment of Gastrointestinal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Liping WangDepartment of Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Yang FuDepartment of Gastrointestinal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China. fuyang@zzu.edu.cn.ORCID 0000-0002-8221-3354

Funding

Cancer research funding of the Bethune Foundation J202101E005Henan Provincial Science and Technology Research Project 242301420008Scientific Research and Innovation Team of The First Affiliated Hospital of Zhengzhou University QNCXTD2023022
6 · The paper itself

Abstract

backgroundTumor microenvironment (TME), particularly immune cell infiltration, programmed cell death (PCD) and stress, has increasingly become a focal point in colorectal cancer (CRC) treatment. Uncovering the intricate crosstalk between these factors can enhance our understanding of CRC, guide therapeutic strategies, and improve patient prognosis.

methodsWe constructed an immune-related cell death and stress (ICDS) prognostic model utilizing machine learning methodologies. Furthermore, we performed enrichment analyses and deconvolution algorithms to elucidate the complex interactions between immune cell infiltration and the processes of PCD and stress within a substantial array of transcriptomic data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus data base (GEO) related to CRC. Single-cell sequencing and biochemical experiments were used to validate the interaction between the model genes and programmed cell death in tumor cells.

resultsThe ICDS prognostic model exhibited robust predictive performance in seven independent cohorts, revealing an inverse correlation between model scores and patient prognosis. Meanwhile, the ICDS index was positively correlated with clinical stage. Model analysis indicated that patient subgroups with low ICDS index exhibited heightened immune activation features and elevated activity in PCD and stress pathways. Single-cell analysis further revealed that macrophages were the central drivers of immune characteristics underlying prognostic differences within the ICDS prognostic model. Pseudotime analysis and cellular experiments indicated that the model gene GAL3ST4 promotes the transition of macrophages toward an M2 pro-tumor phenotype. Furthermore, cell communication analysis and experimental validation revealed that the cuproptosis in tumor cells suppress GAL3ST4 expression, thereby inhibiting M2-like macrophage polarization.

conclusionIn summary, we constructed the ICDS prognostic model and uncovered the mechanism by which tumor cells downregulate GAL3ST4 expression via cuproptosis to inhibit M2-like macrophage polarization, providing new targets and biomarkers for CRC treatment and prognosis evaluation.

Indexed as

Cell DeathColorectal NeoplasmsMacrophagesModels, BiologicalStress, PhysiologicalGene Expression Regulation, NeoplasticHumansMachine LearningPhenotypePrognosisReproducibility of ResultsSingle-Cell AnalysisTumor MicroenvironmentColorectal cancerMachine learningMacrophage polarizationProgrammed cell deathSingle cell RNA sequencing

Identifiers

PMID39875913
PMCPMC11776142

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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.