DIA-MS identifies proteins associated with a poor response of
metastatic renal cell carcinoma to tyrosine kinase inhibitor
treatment

a 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.

Základní údaje

Originální název

DIA-MS identifies proteins associated with a poor response of metastatic renal cell carcinoma to tyrosine kinase inhibitor treatment

Autoři

ŠIMONÍK, Jan, Petr LAPČÍK, Pavla BOUCHALOVÁ, Lucia JANÁČOVÁ, David POTĚŠIL, Ján PODHOREC, Milan HORA, Alexandr POPRACH, Ondřej FIALA a Pavel BOUCHAL

Vydání

In Book of Abstracts of 14th European Summer School, Brixen, Italy 31.7.-6.8. 2022, p.46, 2022

Další údaje

Jazyk

angličtina

Typ výsledku

Konferenční abstrakt

Obor

10608 Biochemistry and molecular biology

Stát vydavatele

Německo

Utajení

není předmětem státního či obchodního tajemství

Organizační jednotka

Přírodovědecká fakulta

Příznaky

Mezinárodní význam

Změněno: 28. 11. 2022 10:15, Ing. Jan Šimoník

Anotace

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

Návaznosti

NV19-08-00250, projekt VaV

Název: Proteotypová klasifikace renálního karcinomu ve vztahu k prognóze a terapeutické odpovědi

Investor: Ministerstvo zdravotnictví ČR, Proteotypová klasifikace renálního karcinomu ve vztahu k prognóze a terapeutické odpovědi

Citovat

ŠIMONÍK, Jan, Petr LAPČÍK, Pavla BOUCHALOVÁ, Lucia JANÁČOVÁ, David POTĚŠIL, Ján PODHOREC, Milan HORA, Alexandr POPRACH, Ondřej FIALA a Pavel BOUCHAL. DIA-MS identifies proteins associated with a poor response of metastatic renal cell carcinoma to tyrosine kinase inhibitor treatment. In In Book of Abstracts of 14th European Summer School, Brixen, Italy 31.7.-6.8. 2022, p.46. 2022.

@proceedings{2235186,
   author = {Šimoník, Jan and Lapčík, Petr and Bouchalová, Pavla and Janáčová, Lucia and Potěšil, David and Podhorec, Ján and Hora, Milan and Poprach, Alexandr and Fiala, Ondřej and Bouchal, Pavel},
   booktitle = {In Book of Abstracts of 14th European Summer School, Brixen, Italy 31.7.-6.8. 2022, p.46},
   language = {eng},
   title = {DIA-MS identifies proteins associated with a poor response of metastatic renal cell carcinoma to tyrosine kinase inhibitor treatment},
   year = {2022}
}

TY  - CONF
ID  - 2235186
AU  - Šimoník, Jan - Lapčík, Petr - Bouchalová, Pavla - Janáčová, Lucia - Potěšil, David - Podhorec, Ján - Hora, Milan - Poprach, Alexandr - Fiala, Ondřej - Bouchal, Pavel
PY  - 2022
TI  - DIA-MS identifies proteins associated with a poor response of metastatic renal cell carcinoma to tyrosine kinase inhibitor treatment
N2  - 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
ER  -

ŠIMONÍK, Jan, Petr LAPČÍK, Pavla BOUCHALOVÁ, Lucia JANÁČOVÁ, David POTĚŠIL, Ján PODHOREC, Milan HORA, Alexandr POPRACH, Ondřej FIALA a Pavel BOUCHAL. DIA-MS identifies proteins associated with a poor response of metastatic renal cell carcinoma to tyrosine kinase inhibitor treatment. In \textit{In Book of Abstracts of 14th European Summer School, Brixen, Italy 31.7.-6.8. 2022, p.46}. 2022.

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