Evidence map›Paper›PMID 33823856›Full record

ArticleBiomedical engineering online2021

A signature of 24 aging‑related gene pairs predict overall survival in gastric cancer.

Yankai Zhang, Yichao Yan, Ning Ning, Zhanlong Shen, Yingjiang Ye

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Article in Biomedical engineering online, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

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9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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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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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yankai ZhangDepartment of Gastroenterological Surgery, Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Peking University People's Hospital, No.11 Xizhimen South Street, Xicheng, Beijing, 100044, People's Republic of China.
Yichao YanDepartment of Gastrointestinal Surgery, Peking University International Hospital, No.1 Life Park Road, Life Science Park of Zhong Guancun, Changping, Beijing, 102206, People's Republic of China. 18810057399@126.com.ORCID http://orcid.org/0000-0002-3816-7610
Ning NingDepartment of Gastrointestinal Surgery, Peking University International Hospital, No.1 Life Park Road, Life Science Park of Zhong Guancun, Changping, Beijing, 102206, People's Republic of China.
Zhanlong ShenDepartment of Gastroenterological Surgery, Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Peking University People's Hospital, No.11 Xizhimen South Street, Xicheng, Beijing, 100044, People's Republic of China.
Yingjiang YeDepartment of Gastroenterological Surgery, Laboratory of Surgical Oncology, Beijing Key Laboratory of Colorectal Cancer Diagnosis and Treatment Peking University People's Hospital, No.11 Xizhimen South Street, Xicheng, Beijing, 100044, People's Republic of China. yjye101@sina.com.

Funding

National Natural Science Foundation of China 81702336
6 · The paper itself

Abstract

backgroundAging is the major risk factor for most human cancers. We aim to develop and validate a reliable aging-related gene pair signature (ARGPs) to predict the prognosis of gastric cancer (GC) patients.

methodsThe mRNA expression data and clinical information were obtained from two public databases, The Cancer Genome Atlas (TCGA) dataset, and Gene Expression Omnibus (GEO) dataset, respectively. The best prognostic signature was established using Cox regression analysis (univariate and least absolute shrinkage and selection operator). The optimal cut-off value to distinguish between high- and low-risk patients was found by time-dependent receiver operating characteristic (ROC). The prognostic ability of the ARGPS was evaluated by a log-rank test and a Cox proportional hazards regression model.

resultsThe 24 ARGPs were constructed for GC prognosis. Using the optimal cut-off value - 0.270, all patients were stratified into high risk and low risk. In both TCGA and GEO cohorts, the results of Kaplan-Meier analysis showed that the high-risk group has a poor prognosis (P < 0.001, P = 0.002, respectively). Then, we conducted a subgroup analysis of age, gender, grade and stage, and reached the same conclusion. After adjusting for a variety of clinical and pathological factors, the results of multivariate COX regression analysis showed that the ARGPs is still an independent prognostic factor of OS (HR, 4.919; 95% CI 3.345-7.235; P < 0.001). In comparing with previous signature, the novel signature was superior, with an area under the receiver operating characteristic curve (AUC) value of 0.845 vs. 0.684 vs. 0.695. The results of immune infiltration analysis showed that the abundance of T cells follicular helper was significantly higher in the low-risk group, while the abundance of monocytes was the opposite. Finally, we identified and incorporated independent prognostic factors and developed a superior nomogram to predict the prognosis of GC patients.

conclusionOur study has developed a robust prognostic signature that can accurately predict the prognostic outcome of GC patients.

Indexed as

AgingStomach NeoplasmsAgedFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateMaleMiddle AgedPrognosisProportional Hazards ModelsROC CurveSurvival AnalysisAging-related gene pairsGastric cancerNomogramPrognosis

Identifiers

PMID33823856
PMCPMC8025368

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