The Identification of reliable Biomarkers able to predict the outcome after nephrectomy of patients with clear cell renal cell carcinoma (ccRCC) is an unmet need. The gene expression analysis in tumor tissues represents a promising tool for better stratification of ccRCC subtypes and patients’ evaluation. Methods: In our study we retrospectively analyzed using Next-Generation expression analysis (NanoString), the expression of a gene panel in tumor tissue from 46 consecutive patients treated with nephrectomy for non-metastatic ccRCC at two Italian Oncological Centres. Significant differences in expression levels of selected genes was sought. Additionally, we performed a univariate and a multivariate analysis on overall survival according to Cox regression model. Results: A 17-gene expression signature of patients with a recurrence-free survival (RFS) < 1 year (unfavorable genomic signature (UGS)) and of patients with a RFS > 5 years (favorable genomic signature (FGS)) was identified and resulted in being significantly correlated with overall survival of the patients included in this analysis (HR 51.37, p < 0.0001). Conclusions: The identified Genomic Signatures may serve as potential biomarkers for prognosis prediction of non-metastatic RCC and could drive both follow-up and treatment personalization in RCC management.

A 17-gene expression signature for early identification of poor prognosis in clear cell renal cell carcinoma / Bassanelli, M.; Borro, M.; Roberto, M.; Giannarelli, D.; Giacinti, S.; Di Martino, S.; Ceribelli, A.; Russo, A.; Aschelter, A.; Scarpino, S.; Montori, A.; Pescarmona, E.; Tomao, S.; Simmaco, M.; Cognetti, F.; Milella, M.; Marchetti, P.. - In: CANCERS. - ISSN 2072-6694. - 14:1(2022). [10.3390/cancers14010178]

A 17-gene expression signature for early identification of poor prognosis in clear cell renal cell carcinoma

Bassanelli M.
Co-primo
;
Borro M.
Co-primo
;
Roberto M.
;
Giacinti S.;Scarpino S.;Montori A.;Pescarmona E.;Tomao S.;Simmaco M.;Marchetti P.
Ultimo
2022

Abstract

The Identification of reliable Biomarkers able to predict the outcome after nephrectomy of patients with clear cell renal cell carcinoma (ccRCC) is an unmet need. The gene expression analysis in tumor tissues represents a promising tool for better stratification of ccRCC subtypes and patients’ evaluation. Methods: In our study we retrospectively analyzed using Next-Generation expression analysis (NanoString), the expression of a gene panel in tumor tissue from 46 consecutive patients treated with nephrectomy for non-metastatic ccRCC at two Italian Oncological Centres. Significant differences in expression levels of selected genes was sought. Additionally, we performed a univariate and a multivariate analysis on overall survival according to Cox regression model. Results: A 17-gene expression signature of patients with a recurrence-free survival (RFS) < 1 year (unfavorable genomic signature (UGS)) and of patients with a RFS > 5 years (favorable genomic signature (FGS)) was identified and resulted in being significantly correlated with overall survival of the patients included in this analysis (HR 51.37, p < 0.0001). Conclusions: The identified Genomic Signatures may serve as potential biomarkers for prognosis prediction of non-metastatic RCC and could drive both follow-up and treatment personalization in RCC management.
2022
biomarker; clear cell renal cancer cell (ccRCC); next-generation expression analysis (NanoString); next-generation sequencing (NGS); prognosis; recurrence
01 Pubblicazione su rivista::01a Articolo in rivista
A 17-gene expression signature for early identification of poor prognosis in clear cell renal cell carcinoma / Bassanelli, M.; Borro, M.; Roberto, M.; Giannarelli, D.; Giacinti, S.; Di Martino, S.; Ceribelli, A.; Russo, A.; Aschelter, A.; Scarpino, S.; Montori, A.; Pescarmona, E.; Tomao, S.; Simmaco, M.; Cognetti, F.; Milella, M.; Marchetti, P.. - In: CANCERS. - ISSN 2072-6694. - 14:1(2022). [10.3390/cancers14010178]
File allegati a questo prodotto
File Dimensione Formato  
Bassanelli_A 17-gene_2022.pdf

accesso aperto

Note: https://www.mdpi.com/2072-6694/14/1/178
Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Creative commons
Dimensione 465.44 kB
Formato Adobe PDF
465.44 kB Adobe PDF

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1638105
Citazioni
  • ???jsp.display-item.citation.pmc??? 2
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 2
social impact