ArticleJournal of advanced research2026
Cholesterol Metabolism-related Characteristics Predict Therapeutic Response and Survival in Esophageal Cancer.
Article in Journal of advanced research, 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.
- Development and validation of prognostic nomograms for patients with cervical cancer and liver metastasis: a SEER-based study.Translational cancer research · 2026Article
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10 authors.
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Abstract
introductionCholesterol homeostasis has been identified as an essential downstream pathway of mutations in TP53. Esophageal cancer is one of the most prevalent malignancies exhibiting the mutation.
objectivesTo explore the significance of cholesterol metabolism-related characteristics in tumor phenotype and treatment outcomes of esophageal cancer.
methodsWe established a cholesterol metabolism-related gene set (CMGs) and performed Lasso-Cox analysis to identify prognostic signatures. Nomogram-based risk scores and clinical stages afterwards were constructed and evaluated. We simultaneously identified two metabolic subtypes based on the distinct features of the CMGs. We annotated the functional and pathway characteristics of differentially expressed genes between the clusters and compared the differences in clinical and immune characteristics. Finally, we assessed the prognostic value of signatures in the GSE53625 and two clinical cohorts using whole-exon sequencing and multiplex immunofluorescence.
resultsOur study identified five cholesterol prognosis-related genes (CRGs) that demonstrated superior prognostic efficacy in the training set compared to clinical staging, validated in independent public databases and two clinical cohorts. According to the different expression patterns of the signatures, patients were divided into two subtypes. The C1 group demonstrated poorer overall survival, response to immunotherapy, and downregulation of the p53 pathway. In the immune correlation analysis, we found that the risk score based on 5-signature model was significantly positively correlated with the abundance of suppressive immune cells and the immune checkpoints. Finally, we explored the impact of expression and genomic polymorphism of the signatures on the prognosis at the pan-cancer level.
conclusionsOur findings underscore the distinct expression patterns of CRGs in esophageal cancer. These signatures are efficient to serve as prognostic indicators and assess the effectiveness of immunotherapy. They may also represent promising targets in other TP53 mutant malignancies.
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