Amb motiu del tancament d'estiu, la validació de documents es reprendrà a partir del 28 d'agost de 2026. Disculpeu les molèsties.
Con motivo del cierre de verano, la validación de documentos se reanudará a partir del 28 de agosto de 2026. Disculpad las molestias
Due to the summer closure, document validation will resume starting August 28, 2026. We apologize for any inconvenience.

Document type

Article

Version

Published version

Publication date

Publication license

cc-by (c)  Roldán, Fiorella L. et al., 2022
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/209242

Prognostic Gene Expression-Based Signature in Clear-Cell Renal Cell Carcinoma

Journal Title

Director/Tutor

Journal ISSN

Volume Title

Abstract

The inaccuracy of the current prognostic algorithms and the potential changes in the therapeutic management of localized ccRCC demands the development of an improved prognostic model for these patients. To this end, we analyzed whole-transcriptome profiling of 26 tissue samples from progressive and non-progressive ccRCCs using Illumina Hi-seq 4000. Differentially expressed genes (DEG) were intersected with the RNA-sequencing data from the TCGA. The overlapping genes were used for further analysis. A total of 132 genes were found to be prognosis-related genes. LASSO regression enabled the development of the best prognostic six-gene panel. Cox regression analyses were performed to identify independent clinical prognostic parameters to construct a combined nomogram which includes the expression of CERCAM, MIA2, HS6ST2, ONECUT2, SOX12, TMEM132A, pT stage, tumor size and ISUP grade. A risk score generated using this model effectively stratified patients at higher risk of disease progression (HR 10.79; p < 0.001) and cancer-specific death (HR 19.27; p < 0.001). It correlated with the clinicopathological variables, enabling us to discriminate a subset of patients at higher risk of progression within the Stage, Size, Grade and Necrosis score (SSIGN) risk groups, pT and ISUP grade. In summary, a gene expression-based prognostic signature was successfully developed providing a more precise assessment of the individual risk of progression.

Citation

Citation

ROLDÁN, Fiorella L., et al. Prognostic Gene Expression-Based Signature in Clear-Cell Renal Cell Carcinoma. Cancers. 2022. Vol. 14, num. 15. ISSN 2072-6694. [consulted: 16 of August of 2026]. Available at: https://hdl.handle.net/2445/209242

Export metadata

JSON - METS

Share record