Evidence map›Paper›PMID 38855504›Full record

ArticleOncology letters2024

Disulfidptosis‑related lncRNA prognosis model to predict survival therapeutic response prediction in lung adenocarcinoma.

Xiaoming Sun, Jia Li, Xuedi Gao, Yubin Huang, Zhanyue Pang, Lin Lv, Hao Li, Haibo Liu, Liangming Zhu

Abstract read
In one paragraph

Article in Oncology letters, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

9 authors.

Xiaoming SunDepartment of Thoracic Surgery, Jinan Central Hospital, Jinan, Shandong 250013, P.R. China.
Jia LiDepartment of Thoracic Surgery, Jinan Central Hospital, Shandong University, Jinan, Shandong 250013, P.R. China.
Xuedi GaoDepartment of Ophthamology, Jinan Mingshui Eye Hospital, Jinan, Shandong 250200, P.R. China.
Yubin HuangDepartment of Thoracic Surgery, Jinan Central Hospital, Shandong First Medical University, Jinan, Shandong 250013, P.R. China.
Zhanyue PangDepartment of Thoracic Surgery, Jinan Central Hospital, Jinan, Shandong 250013, P.R. China.
Lin LvDepartment of Thoracic Surgery, Jinan Central Hospital, Shandong University, Jinan, Shandong 250013, P.R. China.
Hao LiDepartment of Thoracic Surgery, Jinan Central Hospital, Shandong First Medical University, Jinan, Shandong 250013, P.R. China.
Haibo LiuDepartment of Thoracic Surgery, Jinan Central Hospital, Jinan, Shandong 250013, P.R. China.
Liangming ZhuDepartment of Thoracic Surgery, Jinan Central Hospital, Shandong University, Jinan, Shandong 250013, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, and disulfidptosis is a newly discovered mechanism of programmed cell death. However, the effects of disulfidptosis-related lncRNAs (DR-lncRNAs) in LUAD have yet to be fully elucidated. The aim of the present study was to identify and validate a novel lncRNA-based prognostic marker that was associated with disulfidptosis. RNA-sequencing and associated clinical data were obtained from The Cancer Genome Atlas database. Univariate Cox regression and lasso algorithm analyses were used to identify DR-lncRNAs and to establish a prognostic model. Kaplan-Meier curves, receiver operating characteristic curves, principal component analysis, Cox regression, nomograms and calibration curves were used to assess the reliability of the prognostic model. Functional enrichment analysis, immune infiltration analysis, somatic mutation analysis, tumor microenvironment and drug predictions were applied to the risk model. Reverse transcription-quantitative PCR was subsequently performed to validate the mRNA expression levels of the lncRNAs in normal cells and tumor cells. These analyses enabled a DR-lncRNA prognosis signature to be constructed, consisting of nine lncRNAs; U91328.1, LINC00426, MIR1915HG, TMPO-AS1, TDRKH-AS1, AL157895.1, AL512363.1, AC010615.2 and GCC2-AS1. This risk model could serve as an independent prognostic tool for patients with LUAD. Numerous immune evaluation algorithms indicated that the low-risk group may exhibit a more robust and active immune response against the tumor. Moreover, the tumor immune dysfunction exclusion algorithm suggested that immunotherapy would be more effective in patients in the low-risk group. The drug-sensitivity results showed that patients in the high-risk group were more sensitive to treatment with crizotinib, erlotinib or savolitinib. Finally, the expression levels of AL157895.1 were found to be lower in A549. In summary, a novel DR-lncRNA signature was constructed, which provided a new index to predict the efficacy of therapeutic interventions and the prognosis of patients with LUAD.

Indexed as

disulfidptosisdisulfidptosis-related lncRNAdisulfidptosis related lncRNA signaturelncRNAlung adenocarcinoma

Identifiers

PMID38855504
PMCPMC11157670

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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.