Evidence map›Paper›PMID 31598158›Full record

ArticleJournal of Cancer2019

The use of DNA repair genes as prognostic indicators of gastric cancer.

Chang Jinjia, Wang Xiaoyu, Sun Hui, Li Wenhua, Zhang Zhe, Zhu Xiaodong, Xu Midie

Abstract read
In one paragraph

Article in Journal of Cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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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3 · Its place in the literature

Who cites it

12 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

7 authors.

Chang JinjiaDepartment of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Wang XiaoyuExperiment Center for Science and Technology, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Sun HuiDepartment of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Li WenhuaDepartment of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Zhang ZheDepartment of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Zhu XiaodongDepartment of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Xu MidieDepartment of Pathology & biobank, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA repair genes can be used as prognostic biomarkers in many types of cancer. We aimed to identify prognostic DNA repair genes in patients with gastric cancer (GC) by systematically bioinformatic approaches using web-based database. Global gene expression profiles from altogether 1,325 GC patients' samples from six independent datasets were included in the study. Clustering analysis was performed to screen potentially abnormal DNA repair genes related to the prognosis of GC, followed by unsupervised clustering analysis to identify molecular subtypes of GC. Characteristics and prognosis differences were analyzed among these molecular subtypes, and modular key genes in molecular subtypes were identified based on changes in expression correlation. Multivariate Cox proportional hazard analysis was used to find the independent prognostic gene. Kaplan-Meier method and log-rank test was used to estimate correlations of key DNA repair genes with GC patients'overall survival. There were 57 key genes significantly associated to GC patients' prognosis, and patients were stratified into three molecular clusters based on their expression profiles, in which patients in Cluster 3 showed the best survival (P < 0.05). After a three-phase training, test and validation process, the expression profile of 13 independent key DNA repair genes were identified can classify the prognostic risk of patients. Compared with patients with low-risk score, patients with high risk score in the training set had shorter overall survival (P < 0.0001). Furthermore, we verified equivalent findings by these key DNA repair genes in the test set (P < 0.0001) and the independent validation set (P = 0.0024). Our results suggest a great potential for the use of DNA repair gene profiling as a powerful marker in prognostication and inform treatment decisions for GC patients.

Identifiers

PMID31598158
PMCPMC6775511

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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.