ArticleWorld journal of gastroenterology2026
Lactate metabolism-driven tumor heterogeneity and molecular signatures in intrahepatic cholangiocarcinoma.
Article in World journal of gastroenterology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Lactate metabolism and protein lactylation in inflammatory and tumor microenvironments.Molecular biomedicine · 2026Review
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Authors and funding
12 authors.
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Abstract
backgroundIntrahepatic cholangiocarcinoma (ICC) is a highly aggressive liver malignancy with limited therapeutic options and poor prognosis. Recent evidence indicates that lactate metabolism (LM) plays a pivotal role in tumor metabolic reprogramming, immune evasion, and disease progression; however, the heterogeneity and regulatory mechanisms of LM activity within ICC remain largely undefined.
aimTo systematically characterize LM-driven heterogeneity and its molecular and functional implications in ICC.
methodsSingle-cell RNA sequencing and bulk transcriptomic datasets were integrated to characterize LM heterogeneity in ICC. High-dimensional weighted gene co-expression network analysis and multiple machine-learning algorithms (least absolute shrinkage and selection operator, random forest, gradient boosting machine, adaptive best subset selection, and decision tree) were employed to identify LM-associated feature genes. CytoTRACE and CellChat analyses were used to assess differentiation potential and intercellular communication among malignant epithelial subpopulations. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analyses were performed to elucidate biological functions. A random forest model combined with SHapley Additive exPlanation (SHAP) interpretability analysis identified the most predictive LM-related gene. Functional assays, including quantitative polymerase chain reaction, cell counting kit-8, colony formation, wound-healing, and transwell experiments, were conducted to validate
resultsMalignant ICC cells were stratified into three LM-activity subtypes (high, intermediate, and low) exhibiting distinct transcriptional programs and differentiation trajectories. Twelve LM-associated feature genes
conclusionThis integrative single-cell and machine-learning study delineates the molecular heterogeneity of LM in ICC and identifies twelve feature genes linking LM with tumor aggressiveness. These findings provide novel insight into LM-driven oncogenic mechanisms and propose
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