Evidence map›Paper›PMID 41972548›Full record

ArticleBiology2026

Identification of a Novel Disulfidptosis-Related Five-Gene Signature for Prognostic Prediction and Immune Characterization in Esophageal Cancer.

Yiru Chen, Xuefeng Li, Hui Jiang, Xiaohui Liu, Nan Ma, Xuemei Wang

Abstract read
In one paragraph

Article in Biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yiru ChenState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
Xuefeng LiState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
Hui JiangState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.ORCID 0000-0001-8044-758X
Xiaohui LiuState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
Nan MaState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
Xuemei WangState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.ORCID 0000-0001-6882-7774

Funding

National Natural Science Foundation of China 92461308, 82027806, U25A20566, 21974019
6 · The paper itself

Abstract

Esophageal cancer is a highly aggressive malignancy with a poor prognosis. More precise prognostic biomarkers are therefore needed. Disulfidptosis is a recently identified form of regulated cell death driven by disulfide stress. It has been implicated in tumor progression. However, its prognostic role in esophageal cancer remains largely unexplored. This study aimed to develop a disulfidptosis-related gene signature for risk stratification and outcome prediction in esophageal cancer patients. Based on 23 disulfidptosis-related genes, consensus clustering was performed to identify molecular subtypes. Differentially expressed genes (DEGs) between subtypes were subjected to functional enrichment, immune microenvironment, and drug sensitivity analyses. Univariate and multivariate Cox regression were used to construct a prognostic risk model, which was evaluated using time-dependent receiver operating characteristic (ROC) curve and Kaplan-Meier analysis. A clinical nomogram integrating the risk score and clinicopathological factors was developed and validated. Two distinct disulfidptosis-related subtypes were identified, showing significant differences in gene expression, immune infiltration, and stromal scores. A total of 1080 DEGs were enriched in pathways related to epidermal differentiation, NRF2 signaling, and glucocorticoid receptor activity. A five-gene prognostic signature was established and effectively stratified patients into high- and low-risk groups. The risk model exhibited strong discrimination for 1-, 3-, and 5-year overall survival outcomes. The predictive accuracy was further maximized through an integrated clinical nomogram, which achieved an outstanding area under the curve (AUC) of 0.94 for 5-year survival predictions. Drug sensitivity analysis revealed subtype-specific therapeutic vulnerabilities, supporting potential precision treatment strategies. This study proposes a novel disulfidptosis-related five-gene signature and nomogram that robustly predict prognosis in esophageal cancer. The findings highlight the clinical relevance of disulfidptosis in tumor biology and offer a potential tool for risk stratification and personalized therapeutic decision-making.

Indexed as

disulfidptosisesophageal cancernomogramprognostic signaturetumor microenvironment

Identifiers

PMID41972548
PMCPMC13072260

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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.