ArticleJournal of gastrointestinal oncology2026
A
Article in Journal of gastrointestinal oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Cholangiocarcinoma (CCA) is a highly malignant tumor with a poor prognosis, and reliable biomarkers for postoperative risk stratification remain limited. This study aimed to develop and validate a Methods: Differentially expressed genes were screened from GSE26566. Integrative machine learning (least absolute shrinkage and selection operator-Cox, random forest, and univariate Cox regression) was performed in the training cohort (GSE89749; n=115) to construct a risk model, which was externally validated in two independent cohorts: cohort 1 (E-MTAB-6389; n=75) and cohort 2 [The Cancer Genome Atlas Cholangiocarcinoma (TCGA-CHOL) data set; n=36]. Systematic analysis was conducted and included examinations of immune infiltration [via single-sample gene set enrichment analysis (ssGSEA)], pathway enrichment (via hallmark GSEA), cellular localization (via single-cell RNA sequencing), and drug sensitivity (via the Genomics of Drug Sensitivity in Cancer 2 database). Results: Two genes, Conclusions: The
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Registered trials
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