ArticleMolecular biotechnology2026
BAX as a Biomarker for Predicting Immunotherapeutic Efficacy in Uveal Melanoma Patients: A Comprehensive Analysis.
Article in Molecular biotechnology, 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Uveal melanoma (UVM) is the second most common type of malignant melanoma occurring in the eye, which arises from the interstitial melanocytes in the uveal tract. This study aims to identify a highly efficient biomarker for the immunotherapy against UVM. Initially, a comprehensive analysis was conducted using the transcriptional and clinical data from The Cancer Genome Atlas (TCGA) database through the immune and stromal scores to assess the composition of infiltrating immune cells in the tumor microenvironment. Further, the expression of BCL2-Associated X, Apoptosis Regulator (BAX), and its co-expression gene networks were analyzed using the weighted gene co-expression network analysis (WGCNA) to identify relevant gene modules and hub genes. The immunohistochemistry (IHC) analysis was carried out to confirm the influence of BAX on immune infiltration. In addition, the survival analysis on the hub genes, including BAX, was performed using an external dataset from the Gene Expression Omnibus (GEO) to corroborate the prognostic significance of these genes in an independent patient cohort. A nomogram integrating patients' clinical features was developed to predict the survival outcomes. Our investigations revealed that high BAX expression was associated with severe clinical characteristics and poor prognosis in UVM. Our analyses identified 12 hub genes at the intersection of differentially expressed genes categorized by BAX expression levels and a co-expression gene model. Further, the GEO database validated the prognostic significance of these hub genes. The IHC analysis established a significant correlation between BAX expression and immune infiltration. This nomogram model demonstrated robust predictive efficiency with a concordance index (C-index) of 0.909 (95% CI: 0.846-0.971), indicating excellent discriminative ability. The calibration curves for 1-year, 3-year, and 5-year overall survival (OS) rates confirmed the nomogram's accuracy, closely reflecting the actual patient outcomes. Finally, the Decision Curve Analysis (DCA) revealed that this nomogram could accurately predict OS for a majority of patients, covering a probability range of 25-95%. Our research may provide a new therapeutic regimen to benefit the UVM patients.
Indexed as
Identifiers
40180694What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.