Evidence map›Paper›PMID 42445428›Full record

ArticleTranslational cancer research2026

Construction of a ferroptosis-related prognostic signature and identification of

Jian Wang, Yixi Wei, Jia Zhang, Wenshu Chai, Yubin Li

Abstract read
In one paragraph

Article in Translational cancer research, 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
–field-weighted citation impact
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

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.

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

5 authors.

Jian Wang *First Affiliated Hospital of Jinzhou Medical University, Jinzhou Medical University, Jinzhou, China.
Yixi Wei *First Affiliated Hospital of Jinzhou Medical University, Jinzhou Medical University, Jinzhou, China.
Jia ZhangFirst Affiliated Hospital of Jinzhou Medical University, Jinzhou Medical University, Jinzhou, China.
Wenshu ChaiFirst Affiliated Hospital of Jinzhou Medical University, Jinzhou Medical University, Jinzhou, China.
Yubin LiFirst Affiliated Hospital of Jinzhou Medical University, Jinzhou Medical University, Jinzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Ferroptosis is a distinct form of regulated cell death characterized by iron-dependent lipid peroxidation, which plays crucial roles in tumor biology and therapeutic response. However, the prognostic significance of ferroptosis-related genes (FRGs) in lung adenocarcinoma (LUAD) remains incompletely understood. This study aimed to construct and validate a ferroptosis-related prognostic model for LUAD by integrating single-cell and bulk transcriptomic data. Methods: Single-cell RNA sequencing (scRNA-seq) data from GSE127465 were integrated with bulk transcriptomic data from The Cancer Genome Atlas lung adenocarcinoma cohort (TCGA-LUAD). FRGs were identified through single-cell gene set scoring with the AUCell algorithm and differential expression analysis. A least absolute shrinkage and selection operator (LASSO)-Cox regression model was constructed and externally validated using the GSE72094 and GSE68465 cohorts. Associations between the model, genomic features, and the tumor immune microenvironment were systematically analyzed. The functional role of Results: A total of 93 candidate genes significantly associated with ferroptosis activity were identified, and an 8-gene prognostic signature ( Conclusions: The ferroptosis-related prognostic signature established in this study may facilitate risk stratification in LUAD patients.

Indexed as

ferroptosisLung adenocarcinoma (LUAD)prognostic modelSRSF9tumor microenvironment

Identifiers

PMID42445428
PMCPMC13357108

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.