Evidence map›Paper›PMID 39398028›Full record

ArticleHeliyon2024

Comprehensive analysis of multiple regulated cell death risk signatures in lung adenocarcinoma.

Shan Gao, Jiaqi Huang, Rui Zhao, Haiqi He, Jia Zhang, Xiaopeng Wen

Abstract read
In one paragraph

Article in Heliyon, 2024. 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

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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Shan GaoDepartment of Thoracic Surgery, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China.
Jiaqi HuangDepartment of Thoracic Surgery, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China.
Rui ZhaoDepartment of Thoracic Surgery, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China.
Haiqi HeDepartment of Thoracic Surgery, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China.
Jia ZhangDepartment of Thoracic Surgery, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China.
Xiaopeng WenDepartment of Thoracic Surgery, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Regulated cell death (RCD) has considerable impact on tumor progress and sensitivity of treatment. Lung adenocarcinoma (LUAD) show a high resistance for conventional radiotherapies and chemotherapies. Currently, regulation of cancer cell death has been emerging as a new promising therapeutic avenue for LUAD patients. However, the crosstalk in each pattern RCD is unclear. Methods: We integrated collected the hub-genes of 12 RCD subroutines and compressively analyzed these hub-genes synergistic effect in LUAD. The characters of RCD genes expression and prognosis were developed in The Cancer Genome Atlas (TCGA)-LUAD data. We developed and validated an RCD risk model based on TCGA and GSE70294 data set, respectively. Functional annotation and tumor immunotherapy based on the risk model were also investigated. Results: 28 RCD-related genes and two LUAD molecular cluster were identified. Survival analysis revealed that the prognosis in high-risk group was worser than those in low-risk group. Functional enrichment analysis indicated that the RCD risk model correlated with immune responses. Further analysis indicated that the high-risk group in RCD risk model exhibited an immunosuppressive microenvironment and a lowly immunotherapy responder ratio. Conclusions: We present an RCD risk model which have a promising ability in predicting LUAD prognosis and immunotherapy response.

Indexed as

Bioinformatic analysisImmunotherapyLung cancerPrognosisregulated cell death

Identifiers

PMID39398028
PMCPMC11471212

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LicenceCC BY-NC-ND
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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.