MSACL 2019 EU Abstract

Proteomic Analysis of Prostate Cancer Biopsies

Gábor Tóth (1,2), Simon Sugár (1,2), András Ács (1,3), Ágnes Révész (1), Károly Vékey (1), László Drahos (1), Lilla Turiák (1)
(1) MS Proteomics Research Group, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Magyar tudósok körútja 2., H-1117 Budapest, Hungary (2) Budapest University of Technology and Economics, Faculty of Chemical Technology and Biotechnology, Műegyetem rkp. 3., H-1111 Budapest, Hungary (3) Semmelweis University, PhD School of Pharmaceutical Sciences, Üllői út 26., H-1085 Budapest, Hungary

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Gábor Tóth (Presenter) MS Proteomics Research Group, RCNS-HAS

Presenter Bio: My name is Gábor Tóth, I am a chemical engineer graduated from the Budapest University of Technology and Economics. I am at the beginning of my professional scientific career as I proceeded with starting my Ph.D. programme in September 2018.
I have now been a student researcher at the MS Proteomics Group of the Research Centre for Natural Sciences, Hungarian Academy of Sciences for five years and despite being a chemical engineer I am dedicated to life science research. My Ph.D. program is related to clinical proteomics and glycomics, the main aim is to discover possible new biomarkers for prostate cancer.
I am completely overwhelmed with the depth of natural sciences, I have always loved solving problems and searching for the reasons behind the events, therefore it is a great pleasure to step on this path.

Relevant Financial Disclosures (within past 24 months) No relevant financial relationship(s) to disclose. Discussing Products? NO, presenter will NOT present educational content related to products/services of the ineligible company(ies) listed above. Conflict mitigation NOT REQUIRED.

INTRODUCTION: Cancer research is among the most studied areas of science and prostate cancer (PCa) is one of the most common types of cancer among men. Tissue samples, especially biopsies are often used in mass spectrometry based biomarker research as they have a great potential in understanding biochemical mechanisms underlying diseases such as cancer. Tissue microarrays (TMA) consist of several biopsies of different patients placed on a microscope slide.
The aim of our work was to develop and apply advanced nanoLC MS(MS) techniques to reliably identify specific proteins and cancer associated protein pathways from the surface of PCa TMAs (ca. 10 µg tissue).
METHODS: A previously published surface proteolytic digestion method was used for the sample preparation of the TMA cores, the glycopeptide enrichment was based on acetone precipitation; and these were followed by reversed phase nanoHPLC-MS(MS) measurements. For the data evaluation Scaffold, MaxQuant label-free quantitation and for protein pathway analysis STRING softwares were used.
RESULTS: The samples of normal, grade 1, 2, and 3 patients were compared in terms of identified proteins and the statistical changes occurring in the 100 most abundant common proteins between each groups. Several protein pathways were identified which change significantly and have already been presented to have crucial effects in prostate cancer progression. Besides, several unique proteins were identified some of which pose the potential as new biomarkers for diagnostics. Results on i) direct analysis of all the peptides after proteolytic digestion, and ii) the remaining peptides after glycopeptide enrichment were compared. The proteomics results obtained with and without glycoprotein enrichment pave the way for future utility of the methodology in combined glycomic and proteomic studies of TMA spots.
CONCLUSION: The presented TMA surface proteolytic digestion methodology and the glycopeptide enrichment step are extremely efficient and enable an alternative means of diagnostics supplementing histological analysis. The possibility to obtain bottom-up proteomics results after the enrichment of glycopeptides in the sample allows a higher level of structural characterization of biological processes. A further in-depth characterization is in progress in order to find specific proteins and pathways for possible diagnostics use.

ACKNOWLEDGMENTS: LT and KV are grateful for funding from the National Research Development and Innovation Office (NKFIH PD-121187 and NKFIH K-119459). LT and ÁR are grateful for support from the János Bolyai Research Scholarship of the Hungarian Academy of Sciences.