Evidence map›Paper›PMID 37275334›Full record

ArticleInternational journal of general medicine2023

Integrated Bioinformatics Analysis for the Identification of Key lncRNAs, mRNAs, and Potential Drugs in Clear Cell Renal Cell Carcinomas.

Sheng Liu, Guanyun Shi, Zhengbo Pan, Weisong Cheng, Linfei Xu, Xingzhang Lin, Yongfeng Lin, Liming Zhang, Guanghua Ji, Xin Lv and 1 more

Open access · goldAbstract read
In one paragraph

Article in International journal of general medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Review
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

11 authors at 1 institution in 1 country.

Sheng Liu *Department of Urinary Surgery, Taizhou Municipal Hospital Affiliated with Taizhou University, Taizhou, Zhejiang Province, People's Republic of China.
Guanyun ShiDepartment of Urinary Surgery, Taizhou Municipal Hospital Affiliated with Taizhou University, Taizhou, Zhejiang Province, People's Republic of China.
Zhengbo PanDepartment of Urinary Surgery, Taizhou Municipal Hospital Affiliated with Taizhou University, Taizhou, Zhejiang Province, People's Republic of China.
Weisong ChengDepartment of Urinary Surgery, Taizhou Municipal Hospital Affiliated with Taizhou University, Taizhou, Zhejiang Province, People's Republic of China.
Linfei XuDepartment of Urinary Surgery, Taizhou Municipal Hospital Affiliated with Taizhou University, Taizhou, Zhejiang Province, People's Republic of China.
Xingzhang LinDepartment of Urinary Surgery, Taizhou Municipal Hospital Affiliated with Taizhou University, Taizhou, Zhejiang Province, People's Republic of China.
Yongfeng LinDepartment of Urinary Surgery, Taizhou Municipal Hospital Affiliated with Taizhou University, Taizhou, Zhejiang Province, People's Republic of China.
Liming ZhangDepartment of Urinary Surgery, Taizhou Municipal Hospital Affiliated with Taizhou University, Taizhou, Zhejiang Province, People's Republic of China.
Guanghua JiDepartment of Urinary Surgery, Taizhou Municipal Hospital Affiliated with Taizhou University, Taizhou, Zhejiang Province, People's Republic of China.
Xin LvDepartment of Urinary Surgery, Taizhou Municipal Hospital Affiliated with Taizhou University, Taizhou, Zhejiang Province, People's Republic of China.
Dongguo Wang *Department of Central Laboratory, Taizhou Municipal Hospital Affiliated with Taizhou University, Taizhou, Zhejiang Province, People's Republic of China.ORCID 0000-0003-1886-0810
Taizhou Municipal Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The overall survival of clear cell renal cell carcinoma (ccRCC) is poor. Markers for early detection and progression could improve disease outcomes. This study aims to reveal the potential pathogenesis of ccRCC by integrative bioinformatics analysis and to further develop new therapeutic strategies. Patients and Methods: RNA-seq data of 530 ccRCC cases in TCGA were downloaded, and a comprehensive analysis was carried out using bioinformatics tools. Another 14 tissue samples were included to verify the expression of selected lncRNAs by qRT-PCR. DGIdb database was used to screen out potential drugs, and molecular docking was used to explore the interaction and mechanism between candidate drugs and targets. Results: A total of 58 differentially expressed lncRNAs (DElncRNAs) and 660 differentially expressed mRNAs (DEmRNAs) were identified in ccRCC. LINC02038, FAM242C, LINC01762, and PVT1 were identified as the optimal diagnostic lncRNAs, of which PVT1 was significantly correlated with the survival rate of ccRCC. GO analysis of cell components showed that DEmRNAs co-expressed with 4 DElncRNAs were mainly distributed in the extracellular area and the plasma membrane, involved in the transport of metal ions, the transport of proteins across membranes, and the binding of immunoglobulins. Immune infiltration analysis showed that MDSC was the most correlated immune cells with PVT1 and key mRNA SIGLEC8. Validation analysis showed that GABRD, SIGLEC8 and CDKN2A were significantly overexpressed, while ESRRB, ELF5 and UMOD were significantly down-regulated, which was consistent with the expression in our analysis. Furthermore, 84 potential drugs were screened by 6 key mRNAs, of which ABEMACICLIB and RIBOCICLIB were selected for molecular docking with CDKN2A, with stable binding affinity. Conclusion: In summary, 4 key lncRNAs and key mRNAs of ccRCC were identified by integrative bioinformatics analysis. Potential drugs were screened for the treatment of ccRCC, providing a new perspective for disease diagnosis and treatment.

Indexed as

bioinformatics analysisclear cell renal cell carcinomadrugs predictionlncRNAmolecular dockingmRNA

Identifiers

PMID37275334
PMCPMC10238222
OpenAlexW4378716099

What OpenQuestion holds

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LicenceCC BY-NC
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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.