Evidence map›Paper›PMID 42407120›Full record

ArticleBriefings in bioinformatics2026

FerroScore: a statistical approach for quantifying tumor-related ferroptosis based on omics data.

Jiaqi Teng, Qi Gong, Zhaohang Cai, Tianshou Zhou

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 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

4 authors.

Jiaqi TengSchool of Mathematics, Sun Yat-sen University, No. 135 Xingang Xi Road, Haizhu District, Guangzhou, Guangdong Province 510275, China.
Qi GongSchool of Mathematics, Sun Yat-sen University, No. 135 Xingang Xi Road, Haizhu District, Guangzhou, Guangdong Province 510275, China.ORCID 0009-0008-2785-0992
Zhaohang CaiSchool of Mathematics, Sun Yat-sen University, No. 135 Xingang Xi Road, Haizhu District, Guangzhou, Guangdong Province 510275, China.
Tianshou ZhouSchool of Mathematics, Sun Yat-sen University, No. 135 Xingang Xi Road, Haizhu District, Guangzhou, Guangdong Province 510275, China.ORCID 0000-0002-0797-0531

Funding

National Key Research and Development Program of China 2021YFA1302500National Natural Science Foundation of China 12571551National Natural Science Foundation of China 62373384
6 · The paper itself

Abstract

Ferroptosis is a novel form of programmed cell death driven by iron-dependent lipid peroxidation, and can significantly influence the progression of complex diseases such as cancer. Current methods of detecting ferroptosis rely primarily on experimental techniques that are typically low-throughput and costly, limiting their clinical applications. Here we develop an effective statistical method, FerroScore, to quantify ferroptosis by generating a score that integrates the activities of three core pathways-iron, glutathione, and lipid metabolism. This method enables the cross-resolution assessment of ferroptosis and provides mechanistic insights into tumor, immune, and neurodegenerative diseases, thus having potential applications in targeted therapy and drug discovery. When applied to pancreatic cancer transcriptomic data, FerroScore reveals: (i) a U-shaped relationship between ferroptosis and patient survival; (ii) heterogeneous ferroptosis activity across cell types in the tumor microenvironment, with high sensitivity to Macrophages, CD8 Tcm cells, and a population of nCAFs; (iii) the role of ferroptosis-active cells in reshaping the immunosuppressive and pro-metastatic microenvironment through intercellular communication.

Indexed as

Computational BiologyFerroptosisPancreatic NeoplasmsHumansIronLipid MetabolismTranscriptomeTumor MicroenvironmentIroncomputational biologyferroptosisnetworksingle-cell RNA sequencingtumor

Identifiers

PMID42407120
PMCPMC13336637

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.