ArticleJournal of translational medicine2025
Prognostic models of immune-related cell death and stress unveil mechanisms driving macrophage phenotypic evolution in colorectal cancer.
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.
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Who cites it
7 citing papers in PubMed.
- Neutrophil extracellular traps as biomarkers for predicting prognosis and chemotherapy response in colorectal cancer.Scientific reports · 2026Article
- Remodeling the tumor immune microenvironment: mechanisms of crosstalk between regulated cell death macrophages.Frontiers in immunology · 2026Review
- Prognostic biomarkers related to PANoptosis in esophageal cancer and their immune microenvironment: multi-omics analysis and therapeutic significance.Frontiers in oncology · 2026Article
- Adaptive resilience: agarikon mycelium modulates immune responses and provides oxidative stress buffering in human immune cells.Frontiers in immunology · 2026Article
- Relationship between LILRB2 and APE1 levels and pathological characteristics in colorectal cancer patients and their predictive value for prognosis.Frontiers in cellular and infection microbiology · 2025Article
- Immunogenic cell death genes in single-cell and transcriptome analyses perspectives from a prognostic model of cervical cancer.Frontiers in genetics · 2025Article
- Unveiling the prognostic role of FABP4 in early-onset colorectal cancer through big data analysis and preliminary clinical validation.Frontiers in oncology · 2025Article
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Authors and funding
8 authors.
Funding
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.
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