Publication details
Proteogenomic Classification of Triple-Negative Breast Cancer for Prognosis and Targeted Therapy
| Authors | |
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| Year of publication | 2023 |
| Type | Conference abstract |
| MU Faculty or unit | |
| Citation | |
| Description | Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer characterised by the absence of estrogen, progesterone, and HER2 receptors. This subtype accounts for approximately 15% of all breast cancers and mainly affects premenopausal women under the age of 40. Unfortunately, TNBC has a very poor prognosis, with chemotherapy as the typical primary treatment due to the lack of targetable receptors. Currently, TNBC is classified based on histological features and molecular profiling. The widely accepted classifications by Lehmann (2011 and 2016) and Burstein (2015) utilise gene expression profiling data and suggest ~four TNBC groups with different characteristics. However, we hypothesise that next-generation proteomics should provide a more relevant classification of the TNBC phenotype, as proteins are the true molecular effectors in cells. The unique and well-characterised set of 114 TNBC fresh frozen tissues from the Masaryk Memorial Cancer Institute was processed for this project. Whole exome sequencing (WES), RNA sequencing on Illumina NovaSeq, and proteomics analysis in DIA-MS mode on timsTOF Pro were performed, resulting in a set of 101 samples with high-quality genomics, transcriptomics, and proteomics data. We will classify these samples based on RNA and protein profiles and will use WES data to identify somatic variants in coding genomic regions responsible for this proteogenomic classification. The key milestone of this project is to identify new potential therapeutic targets that could be potentially utilised to improve TNBC therapy. |
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