ArticleFrontiers in immunology2025
Machine learning identifies PYGM as a macrophage polarization-linked metabolic biomarker in rectal cancer prognosis.
Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed.
- Beyond Feature Selection: Interpretable Machine Learning for Mechanistic Insights in Metabolomics.Biology · 2026Review
- Review
- Glucose metabolism in tumor-associated macrophage plasticity and cancer immunity.Frontiers in cell and developmental biology · 2026Review
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Macrophage polarization plays a pivotal role in shaping the tumor microenvironment and influencing rectal cancer progression. However, the metabolic and prognostic regulators governing this process remain largely undefined. Methods: We constructed a macrophage polarization gene signature (MPGS) by integrating weighted gene co-expression network analysis (WGCNA) with multiple machine learning algorithms across two independent cohorts: 363 rectal cancer samples from GSE87211 and 177 samples from The Cancer Genome Atlas (TCGA). The prognostic performance of MPGS was evaluated across rectal and multiple other cancer types. Functional analyses, single-cell RNA sequencing, immunohistochemistry of clinical specimens, and Results: The MPGS exhibited robust prognostic capability and effectively predicted responses to immunotherapy and various chemotherapeutic agents. Both MPGS and its central metabolic component, Conclusions: This study firstly highlights
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