Detailed Information on Publication Record
2022
DIA-MS identifies proteins associated with a poor response of metastatic renal cell carcinoma to tyrosine kinase inhibitor treatment
ŠIMONÍK, Jan, Petr LAPČÍK, Pavla BOUCHALOVÁ, Lucia JANÁČOVÁ, David POTĚŠIL et. al.Basic information
Original name
DIA-MS identifies proteins associated with a poor response of metastatic renal cell carcinoma to tyrosine kinase inhibitor treatment
Authors
ŠIMONÍK, Jan, Petr LAPČÍK, Pavla BOUCHALOVÁ, Lucia JANÁČOVÁ, David POTĚŠIL, Ján PODHOREC, Milan HORA, Alexandr POPRACH, Ondřej FIALA and Pavel BOUCHAL
Edition
In Book of Abstracts of 14th European Summer School, Brixen, Italy 31.7.-6.8. 2022, p.46, 2022
Other information
Language
English
Type of outcome
Konferenční abstrakt
Field of Study
10608 Biochemistry and molecular biology
Country of publisher
Germany
Confidentiality degree
není předmětem státního či obchodního tajemství
Organization unit
Faculty of Science
Tags
International impact
Změněno: 28/11/2022 10:15, Ing. Jan Šimoník
Abstract
V originále
Metastatic renal cell carcinoma (mRCC) represents a systemic disease with very poor prognosis. mRCC patients have been typically treated by tyrosine kinase inhibitors (TKI), however, many patients respond poorly, or do not respond to this treatment. To understand the molecular mechanisms associated with a poor response to TKI and to identify patients who would benefit from an alternate treatment (e.g. immunotherapy or clinical trial), we performed a proteomics study on the set of 75 tumor tissues and 17 adjacent non-cancerous tissues from patients treated by TKI inhibitors sunitinib or pazopanib in the first line, of which half did not respond to the treatment. The tumors were further divided into training (n=53; 23 responders and 30 non-responders) and validation (n=22; 10 responders and 12 non-responders)) set. Tryptic digests of fresh frozen tissues were analyzed in data independent acquisition mode (DIA) on QExactive HF-X nanoLC-MS/MS system. The spectral library generated in Spectronaut 13.9 software (Biognosys) covered 7960 protein groups represented by 77817 peptides (FDR=0.01). Of these, 6252 protein groups were consistently quantified in the set of tissues (FDR=0.01). Using statistical analysis, we selected proteins which were deregulated between responders and non-responders’ tissues, were differentially abundant between tumor and normal tissue and unrelated to tumor grade (|log2FC| ˃0.58 and q˂0.05) in both the training and validation set, were significantly associated with progression free survival (FDR<0.05) and were able to divide patients between responders and non-responders based on area-under-curve (AUC; p<0.05). This gave us panel of 14 proteins that exhibited the best characteristics. We are now working of functional characterization of these targets using CRISPR/Cas9 to investigate their role in RCC cell migration and metastasis and confirm their roles as potential therapeutic targets. This work was supported by Ministry of Health of the Czech Republic, grant No. NV19- 08-00250. The first author is holder of a travel grant for 14th European Summer School: Advanced Proteomics from Proteomic section of Czech Society for Biochemistry and Molecular Biology
Links
NV19-08-00250, research and development project |
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