Evidence map›Paper›PMID 39948103›Full record

ArticleScientific reports2025

Comprehensive exploration of programmed cell death landscape in lung adenocarcinoma combining multi-omic analysis and experimental verification.

Peng Yu, Leyang Xiao, Kaibo Hu, Jitao Ling, Yixuan Chen, Ruiqi Liang, Xinyu Liu, Deju Zhang, Yuzhen Liu, Tongchun Weng and 3 more

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

13 authors.

Peng Yu *Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Leyang Xiao *Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Kaibo HuDepartment of Endocrinology and Metabolism, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Jitao LingDepartment of Endocrinology and Metabolism, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Yixuan ChenDepartment of Anesthesiology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Ruiqi LiangDepartment of Endocrinology and Metabolism, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Xinyu LiuDepartment of Biochemistry and Molecular Biology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.
Deju ZhangFood and Nutritional Sciences, School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Pok Fu Lam, Hong Kong.
Yuzhen LiuDepartment of Thoracic Surgery, Jiangxi Provincial Chest Hospital, Nanchang, China.
Tongchun WengDepartment of Thoracic Surgery, Jiangxi Provincial Chest Hospital, Nanchang, China.
Hongfa JiangDepartment of Thoracic Surgery, Jiangxi Provincial Chest Hospital, Nanchang, China.
Jing ZhangDepartment of Anesthesiology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Wuming WangDepartment of Thoracic Surgery, Jiangxi Provincial Chest Hospital, Nanchang, China. zhangyuteam2022@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The mortality and therapeutic failure in lung adenocarcinoma (LUAD) are mainly resulted from the wide metastasis and chemotherapy resistance. Up to now, accurate and stable predictive prognostic indicator for revealing the progress and novel therapeutic strategies of LUAD is infrequent, nonetheless. Diversified programmed cell death (PCD) has been widely confirmed that participated in the occurrence and development of various malignant tumors, respectively. In this research, we integrated fourteen types of PCD, bulk multi-omic data from TCGA-LUAD and other cohorts in gene expression omnibus (GEO) and clinical LUAD patients to develop our analysis. Consequently, pivotal fourteen PCD genes, especially CAMP, CDK5R1, CTSW, DAPK2, GAB2, GAPDH, GATA2, HGF, MAPT, NAPSA, NUPR1, PIK3CG, PLA2G3, and SLC7A11, were utilized to establish the prognostic signature, namely cell death index (CDI). The validation in several external cohorts indicated that CDI can be regarded as a potential risk factor of LUAD patients. Combined with other common clinical information, a nomogram with potential predictive ability was constructed. Besides, according to the CDI signature, the tumor microenvironment (TME) and sensitivity to some potential chemotherapeutic drugs were further and deeply explored. Notably, verification and functional experiments further demonstrated the remarkable correlation between CDI and unfold protein response. Given all the above, a novel CDI gene signature was indicated to predict the prognosis and exploit precision therapeutic strategies of LUAD patients.

Indexed as

Adenocarcinoma of LungApoptosisLung NeoplasmsBiomarkers, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMultiomicsNomogramsPrognosisTumor MicroenvironmentBiomarkers, TumorLung adenocarcinomaPrecision treatmentProgrammed cell deathUnfold protein response

Identifiers

PMID39948103
PMCPMC11825851

What OpenQuestion 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 OpenQuestion graph.