Proteotype classification of localized and metastatic renal cell carcinoma for prognosis and therapy response

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F23%3A00132863" target="_blank" >RIV/00216224:14310/23:00132863 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Proteotype classification of localized and metastatic renal cell carcinoma for prognosis and therapy response

Original language description

Renal cell carcinoma (RCC) represents a serious oncological disease with one of the highest incidences in the Czech Republic across the world. Reliable molecular prognostic and predictive biomarkers for RCC are mostly unavailable, namely at protein level. To quantify proteins associated with pro-tumorigenic and pro-metastatic mechanisms in RCC, we first generated a comprehensive RCC-specific spectral library of targeted proteomic assays for 7960 protein groups (FDR=1%) [1]. Second, we have applied data independent acquisition mass spectrometry (DIA-MS) on QExactive HF-X LC-MS system to analyze a well-characterized set of initially localized RCC tumors (n=86) of which a half exhibited a relapse in &lt;5 years after diagnosis. We have identified a single potential biomarker and two protein classifiers able to predict the relapse, for which we have developed selected reaction monitoring assay for further validation and routine quantification. CRISPR/Cas9 knockdown confirmed the role of the key protein in cell migration in 786-0 cells, supporting its role in metastatic potential of RCC. Third, we have analyzed a well-characterized set of metastatic RCC tumors (training set n=53, validation set n=22) and adjacent non-cancerous tissues (n=17) a part of which responded and a part did not respond to tyrosine kinase inhibitor (TKI) treatment. We have identified and validated a single protein biomarker and one classifier associated with a poor response to TKI but not with tumor grade and lymph node status. Functional assays using CRISPR/Cas9 knockdown confirmed its role in metastatic potential of 786-0 cells. In a summary, next generation proteomics based on DIA-MS is a powerful tool to classify RCC tissues, to identify prognostic biomarkers and alternative therapeutic targets. Supported by Ministry of Health of the Czech Republic, project No. NV19-08-00250, all rights reserved. CIISB, Instruct-CZ Centre of Instruct-ERIC EU consortium, funded by MEYS CR infrastructure project LM2018127, is gratefully acknowledged for the financial support of the measurements at the CEITEC Proteomics Core Facility. Supported by the project National Institute for Cancer Research (Programme EXCELES, ID Project No. LX22NPO5102) - Funded by the European Union - Next Generation EU.

Czech name

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Czech description

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Type

O - Miscellaneous

CEP classification

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OECD FORD branch

10608 - Biochemistry and molecular biology

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů