Evidence map›Paper›PMID 37282651›Full record

ArticleCombinatorial chemistry & high throughput screening2025

A Novel Hypoxia-related lncRNA Risk Score Model for Prognosis Evaluation of Clear Cell Renal Cell Carcinoma.

Fu Liu, Xinyuan Li, Xiang Zhou, Hang Tong, Zili Hu, Xuesong Bai, Xin Gou

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Article in Combinatorial chemistry & high throughput screening, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Fu LiuDepartment of Urology, The First People's Hospital of Ziyang, Sichuan, China.
Xinyuan LiDepartment of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xiang ZhouDepartment of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Hang TongDepartment of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Zili HuDepartment of Urology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xuesong BaiDepartment of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xin GouDepartment of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Funding

Joint Research Fund Project of Chengdu Medical College and Ziyang First People's Hospital 2022LHZY02
6 · The paper itself

Abstract

backgroundRenal cell carcinoma is the most common aggressive tumor of the genitourinary system. The main pathological subtype is clear cell renal cell carcinoma (ccRCC), and its treatment options are very limited. Therefore, identifying specific biomarkers of ccRCC is of great significance for diagnosis and prognosis.

methodsFirst, we obtained transcriptome data and clinical data of 611 patients with renal clear cell carcinoma to analyze the relationship between hypoxia-related lncRNAs and overall survival (OS). We screened hypoxia-related lncRNAs through Pearson correlation and Cox regression analysis. Univariate and multivariate regression analysis were applied to assess survival-related risk factors. According to the median risk score, patients were divided into two groups. Next, a nomogram map was built, and GSEA was used for gene function annotation. RT-qPCR, Western Blot, and Flow Cytometry were used to determine the role of SNHG19 in RCC cells.

resultsBy analyzing the co-expression of hypoxia genes and lncRNAs, 310 hypoxia-related genes were obtained. Four sHRlncRs (AC011445.2, PTOV1-AS2, AP004609.3, and SNHG19) with the highest prognostic values were included in the group to construct the HRRS model. The high-risk group had a shorter OS than the low-risk group. HRRS was considered to be an independent prognostic factor and associated with OS. The two groups showed different pathways in GSEA. Experiments showed that SNHG19 plays essential roles in the autophagy and apoptosis of RCC cells.

conclusionWe constructed and validated a hypoxia-related lncRNA model for ccRCC patients. This study also provides new biomarkers for the poor prognosis of ccRCC patients.

Indexed as

Carcinoma, Renal CellHypoxiaKidney NeoplasmsRNA, Long NoncodingBiomarkers, TumorFemaleHumansMaleMiddle AgedNomogramsPrognosisRisk FactorsBiomarkers, TumorRNA, Long NoncodingccRCCGSEAhypoxia-related geneslong non-coding RNAsprognosis modelrenal cell carcinoma.

Identifiers

PMID37282651
PMCPMC12824858

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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.