Evidence map›Paper›PMID 39748113›Full record

ArticleScientific reports2025

Identification of ferroptosis-related signature predicting prognosis and therapeutic responses in pancreatic cancer.

Ting Ting Chung, Zanyue Piao, Seung Jin Lee

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

3 authors.

Ting Ting ChungCollege of Pharmacy, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon, 34134, Republic of Korea.
Zanyue PiaoCollege of Pharmacy, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon, 34134, Republic of Korea.
Seung Jin LeeCollege of Pharmacy, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon, 34134, Republic of Korea. s.j.lee@cnu.ac.kr.

Funding

National Research Foundation of Korea 2021R1A2C2014145
6 · The paper itself

Abstract

Ferroptosis plays a role in tumorigenesis by affecting lipid peroxidation and metabolic pathways; however, its prognostic or therapeutic relevance in pancreatic adenocarcinoma (PAAD) remains poorly understood. In this study, we developed a prognostic ferroptosis-related gene (FRG)-based risk model using cohorts of The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), proposing plausible therapeutics. Differentially expressed FRGs between tumors from TCGA-PAAD and normal pancreatic tissues from Genotype-Tissue Expression were analyzed to construct a prognostic risk model using univariate and multivariate Cox regression and LASSO analyses. A model incorporating AURKA, CAV1, and PML gene expression effectively distinguished survival differences between high- and low-risk groups among TCGA-PAAD patients, with validation in two ICGC cohorts. The high-risk group was enriched in gene sets involving mTOR, MAPK, and E2F signaling. The immune and stromal cells infiltration score did not differ between the groups. Analysis of PRISM datasets using our risk model to classify pancreatic cell lines suggested the dasatinib's efficacy in the high-risk group, which was experimentally confirmed in four cell lines with a high- or low-risk signature. In conclusion, this study proposed a robust FRG-based prognostic model that may help stratify PAAD patients with poor prognoses and select potential therapeutic avenues.

Indexed as

FerroptosisPancreatic NeoplasmsBiomarkers, TumorCell Line, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMaleMiddle AgedPrognosisBiomarkers, TumorAurora kinase ACaveolin 1FerroptosisPancreatic adenocarcinomaPrognosisPromyelocytic leukemia

Identifiers

PMID39748113
PMCPMC11695983

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Registered trials

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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.