Evidence map›Paper›PMID 40410615›Full record

ArticleDiscover oncology2025

Machine learning explores the prognostic and immuno-oncological impact of mitochondrial unfolded protein response in CESC.

Keh-Sen Liu, Yen-Hsiang Chang, Hsing-Ju Wu, Hung-Yu Lin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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.

Keh-Sen Liu *Division of Infectious Diseases, Department of Internal Medicine, Show Chwan Memorial Hospital, Changhua, 500, Taiwan.
Yen-Hsiang Chang *Department of Nuclear Medicine, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, 833, Taiwan.
Hsing-Ju WuDepartment of Nursing, Jenteh Junior College of Medicine, Nursing and Management, Miaoli, 356, Taiwan.
Hung-Yu LinResearch Assistant Center, Show Chwan Memorial Hospital, Changhua, 500, Taiwan. linhungyu700218@gmail.com.

Funding

Chang Bing Show Chwan Memorial Hospital SRD-112029National Science and Technology Council NSTC 112-2314-B-442-003National Science and Technology Council NSTC 113-2314-B-442-002
6 · The paper itself

Abstract

backgroundCervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) pose significant global health challenges. While the mitochondrial unfolded protein response (UPR

methodsWe employed machine learning to analyze UPR

resultsATF5 emerged as the most significant prognostic factor among UPR

conclusionsOur findings establish ATF5 as both a favorable prognostic marker and a key immune response regulator in CESC. Its influence on the tumor microenvironment and treatment response suggests potential therapeutic applications. These insights into UPR

Indexed as

Activating transcription factor 5Cervical cancerDrug sensitivityMachine learningMitochondrial unfolded protein responseTumor microenvironment

Identifiers

PMID40410615
PMCPMC12102417

What OpenQuestion holds

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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.