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Ergin, Enes Kemal

University of British Columbia

Pediatric cancer presents unique challenges due to its distinct molecular profiles compared to adult cancers. While bottom-up proteomics offers a powerful tool for investigating disease mechanisms, traditional protein-level analyses may obscure crucial details during protein inference.I hypothesize that analyzing data at the fragment, peptide, and post-translational modification (PTM) levels and aggregation into proteoforms can reveal critical insights masked by protein-level aggregation. To test this hypothesis, I developed QuEStVar, a novel framework employing equivalence testing alongside traditional t-tests to identify stable and variable analytes across biological conditions. Furthermore, I enhanced peptide-level analysis through new filtering, scoring, and imputation methods, including a biotin labelling selection algorithm and a downshifted imputation method. This culminated in the development of SQuAPP, a web-based tool for multi-level proteomics analysis. Finally, I established a framework for identifying and deconvoluting functional proteoform groups from peptide-level data to pinpoint specific proteoforms as potential biomarkers or therapeutic targets. My results demonstrate that peptide-level analysis provides access to novel features, including improved precision in identifying significantly changing analytes and revealing unique PTM patterns. The proteoform deconvolution framework successfully identified multiple functional proteoform groups, including potential therapeutic targets in Neuroblastoma. My thesis expands the analytical capabilities of bottom-up proteomics by enabling more comprehensive and precise analyses, paving the way for accelerated biomarker discovery and drug target identification, ultimately contributing to improved outcomes in pediatric oncology.

Text

2025-04-09

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/90620

Bioinformatics

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/