Evidence map›Paper›PMID 32194677›Full record

ArticleOncology letters2020

Distinct expression and prognostic values of the replication protein A family in gastric cancer.

Yujie Zhang, Chaoran Yu

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.8field-weighted citation impact, top 31% of its field
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

6 citing papers in PubMed, 9 citations in OpenAlex.

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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

2 authors at 2 institutions in 1 country.

Yujie ZhangDepartment of Gastrointestinal Surgery, Tongji Hospital, Tongji Medical College in Huazhong University of Science and Technology, Wuhan, Hubei 430030, P.R. China.
Chaoran YuFudan University Shanghai Cancer Center, Fudan University, Shanghai 200025, P.R. China.
Fudan University Shanghai Cancer Center · CNHuazhong University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The replication protein A (RPA)1-4 family are single-stranded DNA-binding proteins that are essential components of DNA replication, repair and recombination, and cell cycle regulation. The present study aimed to evaluate the prognostic value of the RPA family members in patients with gastric cancer (GC), using datasets retrieved from the Oncomine public database. Datasets were retrieved for the purpose of comparing the RPA expression levels between GC and normal tissues. Additionally, Kaplan-Meier analysis was used to compare the overall survival (OS) times of GC patients that expressed different levels of RPA proteins. RPA1, 2, and 3 expression levels were all significantly upregulated in gastric intestinal-type, diffuse gastric, and gastric mixed adenocarcinomas, compared with those in normal mucosal tissues. Moreover, high mRNA expression levels of RPA3 and 4 predicted poorer OS times in all GCs, as well as patients with human epidermal growth factor receptor 2-negative and -positive GC. The high-risk group, separated by RPA signature, showed a poorer outcome than the low-risk group. RPA3 was the most strongly correlated with CD4+ T-cell levels. In conclusion, RPAs are novel prognostic indicators in GC, and can also predict the features of immunological diseases. Future experimental investigation into the roles of RPAs concerning the pathogenesis and development of GC may provide a novel biomarker or therapeutic target, improving the prognosis of patients with GC.

Indexed as

gastric cancerKM plotterOncomineprognosisRPA

Identifiers

PMID32194677
PMCPMC7038973
OpenAlexW2999041166

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

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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.