Evidence map›Paper›PMID 31719794›Full record

ArticleCancer cell international2019

Evaluating the role of RAD52 and its interactors as novel potential molecular targets for hepatocellular carcinoma.

Ping Li, YanZhen Xu, Qinle Zhang, Yu Li, Wenxian Jia, Xiao Wang, Zhibin Xie, Jiayi Liu, Dong Zhao, Mengnan Shao and 13 more

Open access · goldAbstract read
In one paragraph

Article in Cancer cell international, 2019. 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
1.7field-weighted citation impact, top 14% 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

11 citing papers in PubMed, 14 citations in OpenAlex.

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  8. Pan-cancer analysis of mWorld journal of surgical oncology · 2021
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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

23 authors at 5 institutions in 2 countries.

Ping Li *1Center of Diabetic Systems Medicine, Guangxi Key Laboratory of Excellence, Guilin Medical University, Guilin, Guangxi China.
YanZhen Xu *1Center of Diabetic Systems Medicine, Guangxi Key Laboratory of Excellence, Guilin Medical University, Guilin, Guangxi China.
Qinle Zhang *Genetic and Metabolic Central Laboratory, The Maternal and Children Health Hospital of Guangxi, Guangxi, China.
Yu Li *Medical Science Laboratory at Liuzhou Worker's Hospital, Liuzhou, Guangxi China.
Wenxian Jia1Center of Diabetic Systems Medicine, Guangxi Key Laboratory of Excellence, Guilin Medical University, Guilin, Guangxi China.
Xiao Wang3Medical Scientific Research Center, Guangxi Medical University, Nanning, Guangxi China.
Zhibin Xie1Center of Diabetic Systems Medicine, Guangxi Key Laboratory of Excellence, Guilin Medical University, Guilin, Guangxi China.
Jiayi Liu1Center of Diabetic Systems Medicine, Guangxi Key Laboratory of Excellence, Guilin Medical University, Guilin, Guangxi China.
Dong Zhao1Center of Diabetic Systems Medicine, Guangxi Key Laboratory of Excellence, Guilin Medical University, Guilin, Guangxi China.
Mengnan Shao1Center of Diabetic Systems Medicine, Guangxi Key Laboratory of Excellence, Guilin Medical University, Guilin, Guangxi China.
Suixia Chen1Center of Diabetic Systems Medicine, Guangxi Key Laboratory of Excellence, Guilin Medical University, Guilin, Guangxi China.
Nanfang Mo3Medical Scientific Research Center, Guangxi Medical University, Nanning, Guangxi China.
Zhiwen Jiang3Medical Scientific Research Center, Guangxi Medical University, Nanning, Guangxi China.
Liuyan Li3Medical Scientific Research Center, Guangxi Medical University, Nanning, Guangxi China.
Run Liu3Medical Scientific Research Center, Guangxi Medical University, Nanning, Guangxi China.
Wanying Huang3Medical Scientific Research Center, Guangxi Medical University, Nanning, Guangxi China.
Li Chang3Medical Scientific Research Center, Guangxi Medical University, Nanning, Guangxi China.
Siyu Chen3Medical Scientific Research Center, Guangxi Medical University, Nanning, Guangxi China.
Hongtao Li2Scientific Research Center, Guilin Medical University, Guilin, Guangxi China.
Wenpu Zuo3Medical Scientific Research Center, Guangxi Medical University, Nanning, Guangxi China.
Jiaquan Li3Medical Scientific Research Center, Guangxi Medical University, Nanning, Guangxi China.
Ruoheng Zhang10Penn State College of Medicine, Hershey, PA USA.
Xiaoli Yang1Center of Diabetic Systems Medicine, Guangxi Key Laboratory of Excellence, Guilin Medical University, Guilin, Guangxi China.ORCID 0000-0002-5141-3476
Guangxi Medical University · CNGuilin Medical University · CNGuangxi Maternal and Child Health Hospital · CNLiuzhou Maternal and Child Health Hospital · CNPenn State Milton S. Hershey Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRadiation sensitive 52 (RAD52) is an important protein that mediates DNA repair in tumors. However, little is known about the impact of RAD52 on hepatocellular carcinoma (HCC). We investigated the expression of RAD52 and its values in HCC. Some proteins that might be coordinated with RAD52 in HCC were also analyzed.

methodsGlobal RAD52 mRNA levels in HCC were assessed using The Cancer Genome Atlas (TCGA) database. RAD52 expression was analyzed in 70 HCC tissues and adjacent tissues by quantitative real-time PCR (qRT-PCR), Western blotting and immunohistochemistry. The effect of over-expressed RAD52 in Huh7 HCC cells was investigated. The String database was then used to perform enrichment and functional analysis of RAD52 and its interactome. Cytoscape software was used to create a protein-protein interaction network. Molecular interaction studies with RAD52 and its interactome were performed using the molecular docking tools in Hex8.0.0. Finally, these DNA repair proteins, which interact with RAD52, were also analyzed using the TCGA dataset and were detected by qRT-PCR. Based on the TCGA database, algorithms combining ROC between RAD52 and RAD52 interactors were used to diagnose HCC by binary logistic regression.

resultsIn TCGA, upregulated RAD52 related to gender was obtained in HCC. The area under the receiver operating characteristic curve (AUC) of RAD52 was 0.704. The results of overall survival (OS) and recurrence-free survival (RFS) indicated no difference in the prognosis between patients with high and low RAD52 gene expression. We validated that RAD52 expression was increased at the mRNA and protein levels in Chinese HCC tissues compared with adjacent tissues. Higher RAD52 was associated with older age, without correlation with other clinicopathological factors. In vitro, over-expressed RAD52 significantly promoted the proliferation and migration of Huh7 cells. Furthermore, RAD52 interactors (radiation sensitive 51, RAD51; X-ray repair cross complementing 6, XRCC6; Cofilin, CFL1) were also increased in HCC and participated in some biological processes with RAD52. Protein structure analysis showed that RAD52-RAD51 had the firmest binding structure with the lowest E-total energy (- 1120.5 kcal/mol) among the RAD52-RAD51, RAD52-CFL1, and RAD52-XRCC6 complexes. An algorithm combining ROC between RAD52 and its interactome indicated a greater specificity and sensitivity for HCC screening.

conclusionsOverall, our study suggested that RAD52 plays a vital role in HCC pathogenesis and serves as a potential molecular target for HCC diagnosis and treatment. This study's findings regarding the multigene prediction and diagnosis of HCC are valuable.

Indexed as

Diagnostic markerDNA repairHepatocellular carcinomaMolecular interactionRAD52

Identifiers

PMID31719794
PMCPMC6836504
OpenAlexW2983663624

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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.