PhD Scientific Days 2024

Budapest, 9-10 July 2024

Pathological and Oncological Sciences III.

Blood-Based Subtype-Specific Diagnostic and Predictive Biomarkers in Small Cell Lung Cancer

Előadó neve

Dr. Horváth, Lilla

Neptun code

GK36R7

Előadó munkahelye

National Koranyi Institute of Pulmonology

Előadó telefonszáma

06307052974

Előadó e-mail címe

lilla.drhorvath@gmail.com

Az előadás címe

Blood-Based Subtype-Specific Diagnostic and Predictive Biomarkers in Small Cell Lung Cancer

Szerző(k) neve és munkahelye

Lilla Horváth1, Téglás Vivien Beatrix1,2, Szeitz Beáta1, Kristiina Boettiger3, Christian Lang3, Anna Solta3, Ferencz Bence1,2, Clemens Aigner3, Borbély Barbara2, Szánthó Anna2, Szegedi Róbert1, Gálffy Gabriella4, Bujdosó Réka4, Hegedűs Balázs5, Gil Jeovanis Valdés6, Bogos Krisztina1, Rényi-Vámos Ferenc1,2, Marko-Varga György7, Karin Schelch3, Rezeli Melinda7, Megyesfalvi Zsolt1,2,3, Döme Balázs1,2,3,7

1: National Koranyi Institute of Pulmonology, Budapest, Hungary
2: Department of Thoracic Surgery, Semmelweis University and National Institute of Oncology, Budapest, Hungary
3: Department of Thoracic Surgery, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
4: Pulmonology Hospital Törökbálint, Törökbálint, Hungary,
5: Ruhrlandklinik, Clinic of Thoracic and Cardiovascular Surgery, Essen, Germany
6: Department of Translational Medicine, Lund University, Lund, Sweden.
7: Department of Translational Medicine, Lund University, Lund, Sweden

Bemutatás módja

Szóbeli

Szekció

Pathological and Oncological Sciences III.

Language of the presentation

English

Preferred session

Pathological and Oncological Sciences

Összefoglaló szövege

Introduction: Investigation of recently described molecular subtypes of small cell lung cancer
(SCLC) may provide opportunities for developing personalized treatment strategies. Our
research aims to identify subtype-specific diagnostic and predictive markers using proteomic
methods.
Aims and Methods: In the initial phase of our study, we analyzed 26 SCLC cell lines
and their supernatant fractions using mass spectrometry-based proteomic assays. The obtained
patterns were evaluated based on subtype-specific gene expression profiles and growth
characteristics of the cell lines. In the second phase of our study, we extended our proteomic
investigations to human SCLC blood samples to identify subtype-specific proteins in clinical
settings.
Results: Our investigations identified more than 8500 proteins per cell line. Based on the
proteomic patterns, the four molecular subgroups were clearly distinct from each other. These
subgroups exhibit different neuroendocrine and epithelial-mesenchymal characteristics. In
total, 367 subtype-specific proteins were detected in the cell pellet, while 34 such proteins
were found in the supernatant fraction. Notable findings include increased expression of
oxidative phosphorylation pathway elements in SCLC-A, increased DNA replication in
SCLC-N, intense neurotrophin signaling in SCLC-P, and elevated expression of the MAP
kinase signaling pathway in SCLC-Y. Regarding human blood samples, we identified a total
of 2179 different proteins, allowing for well-defined patient subgroups. It is noteworthy that
the prognostic value of these subgroups significantly differs. The investigation and validation
of diagnostic and predictive biomarkers within these subgroups are ongoing, and the results
will be presented at the congress.
Conclusion: Well-distinguishable SCLC subgroups, which bear diagnostic and prognostic value can be identified both in SCLC cell lines and in human blood samples. Mapping the diverse protein expression profiles observed among these subgroups may pave the way for the design of subtype-specific clinical trials.

Funding: -BD and ZM: 2020‐1.1.6‐JÖVŐ, TKP2021‐EGA‐33, FK‐143751 and FK-147045
-ZM: UNKP‐20‐3, UNKP‐21‐3 and UNKP-23-5, Bolyai Research Scholarship of the Hungarian Academy of Sciences, International Association for the Study of Lung Cancer/International Lung Cancer Foundation Young Investigator Grant (2022)

University

Semmelweis University

Supervisor

Dr. Döme Balázs, Dr. Megyesfalvi Zsolt

Publication of my abstract

I do not give consent to the publication of my abstract on the website of the congress.

Kind

Szabad

Status

elfogadva

Accepted presentation method

szóbeli

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

8240

Start

10:45

End

10:55