Evidence map›Paper›PMID 39619906›Full record

ArticleIranian journal of public health2024

Tumor Microenvironment in Clear Cell Renal Cell Carcinoma: A Comprehensive Analysis.

Zhuangyu Guo, Xue Wang, Shuaishuai Huang, Guobin Weng

Abstract read
In one paragraph

Article in Iranian journal of public health, 2024. 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
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

4 authors.

Zhuangyu GuoUrology Department, Ningbo Yinzhou No. 2 Hospital. Ningbo, Zhejiang Province, China.
Xue WangUrology Department, Ningbo Yinzhou No. 2 Hospital. Ningbo, Zhejiang Province, China.
Shuaishuai HuangUrology Department, Ningbo Yinzhou No. 2 Hospital. Ningbo, Zhejiang Province, China.
Guobin WengUrology Department, Ningbo Yinzhou No. 2 Hospital. Ningbo, Zhejiang Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: M6A RNA methylation and the tumor microenvironment (TME) have been reported to play important roles in the progression and prognosis of clear cell renal cell carcinoma (ccRCC). However, whether m6A RNA methylation regulators affect the TME in ccRCC remains unknown. Thus, we aimed to evaluate comprehensively the effect of m6A RNA methylation regulators on the TME in ccRCC. Methods: Transcriptome data of ccRCC were obtained from TCGA database. Consensus clustering analysis was conducted based on the expression of m6A RNA methylation regulators. Survival differences were evaluated by Kaplan-Meier analysis between the clusters. The DESeq2 package was used to analyze the differentially expressed genes (DEGs) between the clusters. GO and KEGG pathway analyses were performed by the ClusterProfiler R package. The CIBERSORT algorithm was used to evaluate immune infiltration. Results: The expression of 15 m6A regulators significantly differed between ccRCC and normal kidney tissues. Based on the expression of these 15 m6A regulators, two clusters were identified by consensus clustering, in which cluster 1 had better overall survival (OS). Overall, 4,429 DEGs were identified between the two clusters and were enriched in immune-related biological processes. Cluster 1 had lower immune and ESTIMATE scores, higher expression of HLA and lower expression of immune checkpoint molecules. Moreover, immune infiltration and expressions of Th1/IFNγ gene signature were also significantly different between the two clusters. Conclusion: Our study revealed m6A regulators were important participants in the development of ccRCC, with a close relationship with the TME.

Indexed as

Clear cell renal cell carcinomaM6A RNA methylation regulatorTumor microenvironment

Identifiers

PMID39619906
PMCPMC11607164

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