Abstract
Renal 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. First, 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. By 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. We constructed and validated a hypoxia-related lncRNA model for ccRCC patients. This study also provides new biomarkers for the poor prognosis of ccRCC patients.
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