Evidence map›Paper›PMID 40640295›Full record

ArticleScientific reports2025

In-depth exploration of programmed cell death-related subtypes and development of a prognostic signature model in lung adenocarcinoma.

Desheng Zhou, Yachao Cui, Jing Guo, Zhenpeng Wu, Lin Li, Wenguang Yin, Min Deng, Meiyuan Liu

Abstract read
PubMed Full text at PMC Publisher
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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

8 authors.

Desheng Zhou *Guangzhou Institute of Cancer Research, The Affiliated Cancer Hospital, Guangzhou Medical University, Guangzhou, 510095, Gongdong, China.
Yachao Cui *Guangzhou Institute of Respiratory Health, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510095, Gongdong, China.
Jing Guo *Center of Oncology, Heyou Hospital, Foshan, China.
Zhenpeng WuGuangzhou Institute of Cancer Research, The Affiliated Cancer Hospital, Guangzhou Medical University, Guangzhou, 510095, Gongdong, China.
Lin LiGuangzhou Institute of Cancer Research, The Affiliated Cancer Hospital, Guangzhou Medical University, Guangzhou, 510095, Gongdong, China.
Wenguang YinGuangzhou Institute of Respiratory Health, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510095, Gongdong, China. yin_wenguang@gzhmu.edu.cn.
Min DengGuangzhou Institute of Cancer Research, The Affiliated Cancer Hospital, Guangzhou Medical University, Guangzhou, 510095, Gongdong, China. mindeng@gzhmu.edu.cn.
Meiyuan LiuGuangzhou Institute of Cancer Research, The Affiliated Cancer Hospital, Guangzhou Medical University, Guangzhou, 510095, Gongdong, China. liumeiyuan203@126.com.

Funding

Guangzhou Science and Technology Project of Guangzhou Municipal Science and Technology Bureau No. 2023A03J0428The Key Areas Project of Education Department of Guangdong Province No. 2021ZDZX2017The Tertiary Education Scientific research project of Guangzhou Municipal Education Bureau No. 202235387
6 · The paper itself

Abstract

Lung cancer ranks as the primary contributor to cancer-related fatalities on a global scale, hallmarked by a poor prognosis. Programmed cell death (PCD) is critically involved in regulating the onset, progression, and treatment of lung adenocarcinoma (LUAD). Existing prognostic models concerning PCD focus solely on individual mechanisms and fail to account for the intricate interaction among multiple regulatory mechanisms. In this study, the LUAD samples were sorted into low immune cell invasion subtype (C1) and high immune cell invasion subtype (C2) by clustering analysis. A PCD prognostic signature model was developed by LASSO Cox regression analysis. Tumors in the high-risk group were categorized as "cold" and characterized by immunosuppression, which was linked to an unfavorable prognosis and sensitivity to drug therapy. However, the opposite was true for the low-risk group, which was associated with a favorable prognosis and sensitivity to immunotherapy. Single-cell analysis found that the PCD signature model could activate several immune cells, thereby affecting the tumor microenvironment (TME) of LUAD. Furthermore, ENO1, could be used as a target for LUAD prognosis and immunotherapy. This study aims to comprehensively explore the functional mechanisms of various PCD regulatory patterns in LUAD to provide accurate prognosis and personalized treatment plans.

Indexed as

Adenocarcinoma of LungApoptosisLung NeoplasmsBiomarkers, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMalePrognosisSingle-Cell AnalysisTumor MicroenvironmentBiomarkers, TumorCluster analysisENO1ImmuneLung adenocarcinomaProgrammed cell deathSignature model

Identifiers

PMID40640295
PMCPMC12246073

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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.