Evidence map›Paper›PMID 37035172›Full record

ArticleFrontiers in oncology2023

Identification of an immune subtype-related prognostic signature of clear cell renal cell carcinoma based on single-cell sequencing analysis.

Zongyao Fan, Hewei Xu, Qingyu Ge, Weilong Li, Junjie Zhang, Yannan Pu, Zhengsen Chen, Sicong Zhang, Jun Xue, Baixin Shen and 2 more

Abstract read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Zongyao FanDepartment of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Hewei XuDepartment of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Qingyu GeDepartment of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Weilong LiDepartment of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Junjie ZhangDepartment of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Yannan PuDepartment of Rehabilitation Medicine, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Zhengsen ChenDepartment of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Sicong ZhangDepartment of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Jun XueDepartment of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Baixin ShenDepartment of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Liucheng DingDepartment of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Zhongqing WeiDepartment of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: There is growing evidence that immune cells are strongly associated with the prognosis and treatment of clear cell renal cell carcinoma (ccRCC). Our aim is to construct an immune subtype-related model to predict the prognosis of ccRCC patients and to provide guidance for finding appropriate treatment strategies. Methods: Based on single-cell analysis of the GSE152938 dataset from the GEO database, we defined the immune subtype-related genes in ccRCC. Immediately afterwards, we used Cox regression and Lasso regression to build a prognostic model based on TCGA database. Then, we carried out a series of evaluation analyses around the model. Finally, we proved the role of VMP1 in ccRCC by cellular assays. Result: Initially, based on TCGA ccRCC patient data and GEO ccRCC single-cell data, we successfully constructed a prognostic model consisting of five genes. Survival analysis showed that the higher the risk score, the worse the prognosis. We also found that the model had high predictive accuracy for patient prognosis through ROC analysis. In addition, we found that patients in the high-risk group had stronger immune cell infiltration and higher levels of immune checkpoint gene expression. Finally, cellular experiments demonstrated that when the VMP1 gene was knocked down, 786-O cells showed reduced proliferation, migration, and invasion ability and increased levels of apoptosis. Conclusion: Our study can provide a reference for the diagnosis and treatment of patients with ccRCC.

Indexed as

ccRCCimmuneprognostic signaturesingle-cell sequencing analysisvmp1

Identifiers

PMID37035172
PMCPMC10073649

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.