Evidence map›Paper›PMID 36305249›Full record

ArticleCancer medicine2023

Costimulatory molecule-related lncRNA model as a potential prognostic biomarker in non-small cell lung cancer.

Yuanshan Yao, Fuzhi Yang, Anna Chen, Qingwang Hua, Wen Gao

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Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

11 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

5 authors.

Yuanshan YaoDepartment of Thoracic Surgery, Shanghai Key Laboratory of Clinical Geriatric Medicine, Huadong Hospital Affiliated to Fudan University, Shanghai, China.
Fuzhi YangDepartment of Thoracic Surgery, Shanghai Key Laboratory of Clinical Geriatric Medicine, Huadong Hospital Affiliated to Fudan University, Shanghai, China.
Anna ChenNingbo CRRC Times Transducer Technology Co., Ltd., Ningbo, China.
Qingwang HuaDepartment of Thoracic Oncology, Ningbo No. 2 Hospital, Ningbo, China.
Wen GaoDepartment of Thoracic Surgery, Shanghai Key Laboratory of Clinical Geriatric Medicine, Huadong Hospital Affiliated to Fudan University, Shanghai, China.ORCID 0000-0003-0077-4236

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveCostimulatory molecules have been demonstrated to exert essential roles in multiple cancers. However, their role in lung cancer remains elusive. Here, we sought to identify costimulatory molecule-related lncRNAs in non-small cell lung cancer (NSCLC) and establish a prognostic signature to predict the prognosis of patients with NSCLC.

methodsA total of 535 lung adenocarcinoma (LUAD) and 502 lung squamous cell carcinoma (LUSC) patients from the cancer genome atlas (TCGA) database were recruited. A novel costimulatory molecule-based lncRNA prognostic model was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm to predict the overall survival. The Homo_sapiens.GRCh38 data set was set as a reference file for probe annotation.

resultsA total of 593 costimulatory molecule-related lncRNAs were extracted. After analysis, six costimulatory molecule-related lncRNAs (AC084859.1, AC079949.2, HSPC324, LINC01150, LINC01150, and AC090617.5) were screened. A prognostic model based on the six lncRNAs was established using systematic bioinformatics analyses. The prognostic model had a prognostic value in NSCLC patients. Furthermore, a prognostic nomogram was established based on clinical parameters and a risk-score model. Patients with different risk scores had considerably different tumor-infiltrating immune cells, somatic mutational loading, clinical outcomes, signaling pathways, and immunotherapy efficacy. In addition, LINC01137 was associated with unfavorable disease outcomes and fueled tumor progression in NSCLC.

conclusionTaken together, our study demonstrated that a costimulatory molecule-related lncRNA model could be a potential prognostic biomarker in NSCLC. Moreover, LINC01137 could facilitate the proliferation and invasion of lung cancer.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsRNA, Long NoncodingBiomarkersHumansPrognosisBiomarkersRNA, Long Noncodingcostimulatory moleculeLINC01137non-small cell lung cancerprognosisrisk model

Identifiers

PMID36305249
PMCPMC10028169

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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.