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Clinicopathological and Molecular Prognostic Classifier for Intermediate/High-Risk Clear Cell Renal Cell Carcinoma

Authors :
Fiorella L. Roldán
Juan J. Lozano
Mercedes Ingelmo-Torres
Raquel Carrasco
Esther Díaz
Miguel Ramirez-Backhaus
José Rubio
Oscar Reig
Antonio Alcaraz
Lourdes Mengual
Laura Izquierdo
Source :
Cancers, Vol 13, Iss 6338, p 6338 (2021), Cancers; Volume 13; Issue 24; Pages: 6338, Cancers
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

Simple Summary In this report, we identified biomarkers for tumor progression from tissue samples of intermediate/high-risk ccRCC. Using the molecular findings and the clinical data, we developed an improved prognostic model which could help to provide better individualized management recommendations. Abstract The probability of tumor progression in intermediate/high-risk clear cell renal cell carcinoma (ccRCC) is highly variable, underlining the lack of predictive accuracy of the current clinicopathological factors. To develop an accurate prognostic classifier for these patients, we analyzed global gene expression patterns in 13 tissue samples from progressive and non-progressive ccRCC using Illumina Hi-seq 4000. Expression levels of 22 selected differentially expressed genes (DEG) were assessed by nCounter analysis in an independent series of 71 ccRCCs. A clinicopathological-molecular model for predicting tumor progression was developed and in silico validated in a total of 202 ccRCC patients using the TCGA cohort. A total of 1202 DEGs were found between progressive and non-progressive intermediate/high-risk ccRCC in RNAseq analysis, and seven of the 22 DEGs selected were validated by nCounter. Expression of HS6ST2, pT stage, tumor size, and ISUP grade were found to be independent prognostic factors for tumor progression. A risk score generated using these variables was able to distinguish patients at higher risk of tumor progression (HR 7.27; p < 0.001), consistent with the results obtained from the TCGA cohort (HR 2.74; p < 0.002). In summary, a combined prognostic algorithm was successfully developed and validated. This model may aid physicians to select high-risk patients for adjuvant therapy.

Details

ISSN :
20726694
Volume :
13
Database :
OpenAIRE
Journal :
Cancers
Accession number :
edsair.doi.dedup.....41f675772bd23fcb35cdc41db8e43945
Full Text :
https://doi.org/10.3390/cancers13246338