Evidence map›Paper›PMID 40433044›Full record

ArticleInternational journal of general medicine2025

Identification and Experimental Validation of Prognostic Signature and Peroxisome-Related Key Genes in Clear Cell Renal Cell Carcinoma.

Congcong Fan, Yifei Li, Weizhi Zhang, Yining Wang, Yanzhen Li, Jianjian Zheng, Zhixian Yu, Yong Guo

Abstract read
In one paragraph

Article in International journal of general medicine, 2025. 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
–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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Congcong FanZhejiang Key Laboratory of Intelligent Cancer Biomarker Discovery and Translation, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People's Republic of China.
Yifei LiZhejiang Key Laboratory of Intelligent Cancer Biomarker Discovery and Translation, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People's Republic of China.
Weizhi ZhangZhejiang Key Laboratory of Intelligent Cancer Biomarker Discovery and Translation, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People's Republic of China.
Yining WangZhejiang Key Laboratory of Intelligent Cancer Biomarker Discovery and Translation, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People's Republic of China.
Yanzhen LiZhejiang Key Laboratory of Intelligent Cancer Biomarker Discovery and Translation, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People's Republic of China.
Jianjian ZhengZhejiang Key Laboratory of Intelligent Cancer Biomarker Discovery and Translation, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People's Republic of China.
Zhixian YuDepartment of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People's Republic of China.
Yong GuoDepartment of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Clear cell renal cell carcinoma (ccRCC) is a common urological malignant tumor. Dysregulated peroxisomes contribute to the progression of cancers. However, the prognostic significance of peroxisome-related genes (PGs) in ccRCC is still poorly understood. Methods: PGs were collected from MsigDB. Prognostic differentially expressed genes were filtered via differentially expression analysis and univariate Cox regression analysis. The construction of risk model was performed by the least absolute shrinkage selection operator Cox regression analysis. Subsequently, the clinical application of risk model in prognosis prediction, tumor microenvironment (TME) and drug sensitivity was comprehensively evaluated. The expression levels of genes were measured by qRT-PCR and immunohistochemistry. Finally, the role of the genes of this risk model in biological behaviors of RCC cells was further verified via CCK-8, transwell invasion and wound healing assay. Results: A risk model, including 9 PGs, was established. The risk model exhibited a robust and accurate performance in prognostic prediction across TCGA, GSE167573 and the local cohorts. Moreover, the risk model was closely correlated with clinical characteristics, TME and drug sensitivity. Silencing of the key genes attenuated the proliferation, migration, and invasion ability of RCC cells. Conclusion: The novel peroxisome-related risk model holds promise as a prognostic tool for estimating the prognosis of ccRCC patients and provides insights into treatment strategies.

Indexed as

clear cell renal cell carcinomaperoxisomesprognosisrisk model

Identifiers

PMID40433044
PMCPMC12109615

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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.