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Critical Evaluation of a microRNA-Based Risk Classifier Predicting Cancer-Specific Survival in Renal Cell Carcinoma with Tumor Thrombus of the Inferior Vena Cava.
- Source :
-
Cancers [Cancers (Basel)] 2023 Mar 26; Vol. 15 (7). Date of Electronic Publication: 2023 Mar 26. - Publication Year :
- 2023
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Abstract
- (1) Background: Clear cell renal cell carcinoma extending into the inferior vena cava (ccRCC <superscript>IVC</superscript> ) represents a clinical high-risk setting. However, there is substantial heterogeneity within this patient subgroup regarding survival outcomes. Previously, members of our group developed a microRNA(miR)-based risk classifier-containing miR-21-5p, miR-126-3p and miR-221-3p expression-which significantly predicted the cancer-specific survival (CSS) of ccRCC <superscript>IVC</superscript> patients. (2) Methods: Examining a single-center cohort of tumor tissue from n = 56 patients with ccRCC <superscript>IVC</superscript> , we measured the expression levels of miR-21, miR-126, and miR-221 using qRT-PCR. The prognostic impact of clinicopathological parameters and miR expression were investigated via single-variable and multivariable Cox regression. Referring to the previously established risk classifier, we performed Kaplan-Meier analyses for single miR expression levels and the combined risk classifier. Cut-off values and weights within the risk classifier were taken from the previous study. (3) Results: miR-21 and miR-126 expression were significantly associated with lymphonodal status at the time of surgery, the development of metastasis during follow-up, and cancer-related death. In Kaplan-Meier analyses, miR-21 and miR-126 significantly impacted CSS in our cohort. Moreover, applying the miR-based risk classifier significantly stratified ccRCC <superscript>IVC</superscript> according to CSS. (4) Conclusions: In our retrospective analysis, we successfully validated the miR-based risk classifier within an independent ccRCC <superscript>IVC</superscript> cohort.
Details
- Language :
- English
- ISSN :
- 2072-6694
- Volume :
- 15
- Issue :
- 7
- Database :
- MEDLINE
- Journal :
- Cancers
- Publication Type :
- Academic Journal
- Accession number :
- 37046643
- Full Text :
- https://doi.org/10.3390/cancers15071981