MASS SPECTROMETRY-BASED ANALYSIS OF CHONDROITIN SULFATE AND HEPARAN SULFATE GLYCOSAMINOGLYCANS IN LUNG CANCER TISSUE SAMPLES USING OPTIMIZED SAMPLE PREPARATION CONDITIONS
Pál Domonkos
Gyógyszertudományok és Egészségügyi Technológiák Tagozat
Dr. Zelkó Romána
MTA TTK nagy előadóterem
2025-12-08 11:00:00
A gyógyszerészeti tudományok korszerű kutatási irányai
Dr. Antal István
Dr. Turiák Lilla
Dalmadiné Dr. Kiss Borbála
Dr. Takátsy Anikó
Dr. Tábi Tamás
Dr. Csernák Orsolya
Dr. Abrankó László
My PhD work comprises three interlinked research projects that collectively aim to improve analytical reliability in glycosaminoglycan (GAG) research and to advance the understanding of structural alterations in GAGs associated with lung cancer.
The first part of my work focused on the optimization of sample preparation for heparan sulfate (HS) disaccharides, addressing key factors influencing sample integrity, stability, and reproducibility. The standard workflow for HS analysis involves multiple critical steps including extraction, enzymatic digestion, derivatization, purification, and instrumental analysis. Each step has the potential to introduce sample loss or analytical bias. Systematic evaluation of parameters such as digestion buffer composition, injection conditions, solvent evaporation methods, and freezing cycles were performed. Optimal conditions were identified to minimize degradation and improve recovery, establishing standardized protocols for reliable and reproducible HS analysis.
In the second part of my work the aim was to characterize compositional differences in chondroitin/dermatan sulfate (CS/DS) and HS disaccharides between various lung tumor phenotypes and corresponding normal lung tissues. Using tissue surface enzymatic digestion followed by solid-phase extraction (SPE) and HPLC–MS analysis on a custom HILIC–WAX capillary column, the study revealed both quantitative and qualitative alterations in GAG structures. These molecular differences may provide insights into tumor-related extracellular matrix remodeling and offer potential for diagnostic and therapeutic applications.
The last part of the study focused to extend the investigation to lung adenocarcinoma (AC) tissues harboring ALK, EGFR, and KRAS genetic alterations, comparing them with triple wild-type (WT) tumors. Given that these oncogenic alterations drive distinct signalling pathways, the study explored how they may also influence tumor microenvironment composition and GAG remodelling. The analysis identified genetic alteration-specific GAG signatures, suggesting that extracellular matrix composition is closely linked to underlying genetic drivers. These findings highlight the potential of GAG profiling to aid in patient stratification, to predict therapeutic responses, and to identify GAG-modifying enzymes or structural motifs as novel therapeutic targets complementary to existing treatments.
This dissertation establishes improved analytical approaches for GAG characterization and reveals key molecular patterns linking glycosaminoglycan composition to lung cancer phenotypes and genetic backgrounds.
