Abstract 303P
Background
Small cell lung cancer (SCLC) is among the most aggressive malignancies, characterized by rapid disease progression. The early onset of distant organ metastases underlines the urgent need for reliable prognostic markers to guide the development of personalized treatment and follow-up strategies. Here, we aimed to identify and validate robust prognostic markers in SCLC by analyzing publicly available transcriptomic datasets and conducting subsequent immunohistochemistry (IHC) analyses.
Methods
Three previously published SCLC tissue transcriptomic datasets were accessed, quantifying over 50,000 transcripts accompanied by overall survival data. Cox regression analysis was conducted, using the clinical stage as a stratification variable to identify genes with potential prognostic significance among the 16,594 overlapping genes. The most promising markers across the three cohorts were identified based on their alignment with corresponding protein expression data and insights from our comprehensive literature search. To validate our in-silico findings, we will perform IHC analyses on a cohort of 50 surgically resected SCLC specimens using specific antibodies.
Results
Our comprehensive bioinformatic analysis revealed 25 genes with potential prognostic significance in SCLC, exhibiting (marginally) significant associations (p < 0.15) across all three cohorts. Altogether, we identified three unfavorable (HR>1) and 22 favorable (HR
Conclusions
Analyzing publicly available gene and protein expression datasets facilitates the identification of novel prognostic markers applicable to the diverse SCLC population, paving the way toward more personalized management of SCLC patients.
Legal entity responsible for the study
National Koranyi Institute of Pulmonology, Budapest, Hungary.
Funding
B.D. was supported by the Austrian Science Fund (FWF I3522, FWF I3977, and I4677) and the ‘BIOSMALL’ EU HORIZON-MSCA-2022-SE-01 project. B.D. and Z.M. were supported by funding from the Hungarian National Research, Development, and Innovation Office (2020-1.1.6-JO?VŐ, TKP2021-EGA-33, FK-143751 and FK-147045). Z. M. was supported by the New National Excellence Program of the Ministry for Innovation and Technology of Hungary (UNKP-20-3, UNKP-21-3 and UNKP-23-5), and by the Bolyai Research Scholarship of the Hungarian Academy of Sciences. Z.M. is also the recipient of the International Association for the Study of Lung Cancer/International Lung Cancer Foundation Young Investigator Grant (2022).
Disclosure
All authors have declared no conflicts of interest.