Discovering tumour and background mutation profiles for each patient can help to understand the molecular mechanisms of tumour development and to find an efficient treatment for each individual patient. Proteogenomics data integration is a bioinformatics approach aimed at assessing the effect of somatic mutations (occurring during cancer development) and germline mutations (inherited from parents) and is based on genetic or transcriptomics data about proteins. Because proteins fulfil biologically active molecular functions and serve as drug targets, proteogenomics can provide essential information about pathways and about proteins that should be targeted to achieve efficient cancer treatment.
The MCB researchers are developing and implementing proteogenomics data integration strategies in the management of various oncological diseases, such as head and neck cancer, ovarian cancer, and melanoma, as well as respiratory diseases, such as COPD.