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

Kód výsledku v 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>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

10608 - Biochemistry and molecular biology

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2023

Kód důvěrnosti údajů

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