Česká společnost pro hmotnostní spektrometrii

(13. ročník České konference hmotnostní spektrometrie a 11. Neformální proteomické setkání - ThO-09)
Integrated multiomics classification of triple negative breast cancer

Jan Šimoník ¹, Pavla Bouchalová ¹, Petr Lapčík ¹, Kateřina Jurásková ², Ingrid Kováčová ^2,1, David Potěšil ³, Vojtěch Bystrý ², Rudolf Nenutil ⁴, Roman Hrstka ⁵, Pavel Bouchal ^1 *

1. Department of Biochemistry, Faculty of Science, Masaryk University
2. Core Facility Bioinformatics, Central European Institute for Technology (CEITEC), Masaryk University
3. Proteomics Core Facility, Central European Institute for Technology (CEITEC), Masaryk University
4. Department of Oncological Pathology, Masaryk Memorial Cancer Institute
5. Research Centre for Applied Molecular Oncology, Masaryk Memorial Cancer Institute

Abstrakt

Triple-negative breast cancer (TNBC) is the most aggressive and heterogeneous BC subtype [1] primarily treated with systemic chemotherapy. To identify novel therapeutic targets, we performed a multiomics study using LC-diaPASEF-MS/MS-based proteomics, RNA sequencing, and whole-exome sequencing, generating an integrated dataset for 96 samples. A hybrid proteomics assay library contained 244,464 precursors and 11,564 protein groups (FDR=1%) [2]. Hierarchical clustering utilizing the proteomics data for 1,223 mostly correlated transcript–protein pairs stratified TNBC into 7 clusters designated as (i) mesenchymal stem like, (ii) basal/mesenchymal, (iii) cell cycle, (iv) immunomodulatory, (v) luminal androgen receptor, (vi) ER+metabolism and (vii) immunomodulatory+cell cycle. Among 225001 germinal mutations identified, high impact ones included those in known tumor suppressor genes (BRCA1, BRCA2, BARD1, BRIP1, PALB2, and CHEK1), distributed mainly in Clusters 7 and 2. Out of 12070 somatic mutations, TP53 was the mostly mutated gene (in 67.71%), with the highest frequency in cluster 7 (86.36 %, p=0.038). Protein quantitative trait locus (pQTL) analysis identified gene variants asssociated with changes in protein levels. Analysis of proteomics data using alteredPQR tool assigned alterations of protein complexes involved in hormonal signaling and lipid metabolism to cluster 5, immune response and interferon signaling to clusters 4 and 7, extracellular matrix organization to cluster 2, cell cycle regulation and DNA repair to cluster 3, and protein phosphorylation and fibrinolysis to cluster 6. In a summary, our study represents the most complete proteomics-driven multiomics study of the set of TNBC tissues, providing highly relevant molecular classification of the patients.

* Korespondující autor: bouchal@chemi.muni.cz

Literatura

1. Bouchal P et al, Cell Reports 2019, 28 (3), "832".
2. Lapcik P et al, Scientific Data 2024, 11(1), 794-800.

Poděkování:

This work was supported by Ministry of Health of the Czech Republic (project NU22-08-00230), all rights reserved. Supported by the project National Institute for Cancer Research (Programme EXCELES, ID Project No. LX22NPO5102)—Funded by the European Union—Next Generation EU.