Pavel Bouchal

A primary reason is a technological difficulty of protein profiling and namely the absence of suitable methods providing complete data matrices essential for tumor classification. Next generation proteomics based on data independent acquisition mass spectrometry represents a new tool for which we have proved applicability, as one of the first ones, for solid tumor classification (Guo & Aebersold, Nature Medicine 2015; Bouchal & Aebersold, Cell Reports 2019). Identified proteins associated with metastatic potential, cancer relapse or poor response to the current treatment may -after a validation- serve as potential diagnostic or therapeutic targets. We use additional state-of-the-art approaches such as CRISPR/Cas9, analysis of cell migration and invasiveness, 3D cultures, functional proteomics and interactomics for the functional validation, and targeted proteomics and immunohistochemistry for the clinical validation.

Research objectives

1. Tumor classification using integrated “high-throughput“ approaches (proteomics, RNA-Seq, exome sequencing), analysis of interactome and protein complexes in relationship to tumor development and metastasis.
2. Functional characterization of selected pro-metastatic proteins and their therapeutic modulation in in vitro and in vivo studies.
3. Identification and validation of proteins involved in molecular mechanisms of solid tumors (breast cancer, renal cell carcinoma, endometrial, colorectal and ovarian cancer and others) based on next-generation proteomics profiling to identify new diagnostic and therapeutic targets, including development of new classifiers.
4. Development and application of new targeted proteomics methods for a routine clinical quantification of selected proteins, development of new sensitive immunocytochemistry and immunohistochemistry approaches.