Hannah Demeke (Berlin / DE), Corinna Friedrich (Berlin / DE), Rebecca Fritz (Berlin / DE), Liliana H. Mochmann (Munich / DE; Berlin / DE), Dražen Papić (Berlin / DE), Oliver Popp (Berlin / DE), Mohamed Haji (Berlin / DE), Sylvia Niquet (Berlin / DE), Janine Wolff (Berlin / DE), Melissa Klingeberg (Berlin / DE), Florian Mutschler (Berlin / DE), Simon Schallenberg (Berlin / DE), Fabian Coscia (Berlin / DE), Frederick Klauschen (Berlin / DE; Munich / DE), Philipp Mertins (Berlin / DE)
Early detection of non-small cell lung cancer (NSCLC) is crucial for effective therapeutic intervention and improving the survival rate of patients.
Herein we present our strategy and initial results on the comparison of lung cancer subtypes in clinical patient samples and lung cancer cell lines as part of the BIFOLD LungCAIRE project.
Our aim is to use multiple proteomic approaches to study early-stage lung cancer, focusing on the identification of biomarkers and prognostic signatures within a diverse patient cohort including matched NSCLCpatient-derived plasma, fresh primary bulk tissue specimens, and single cells.
The study highlights the latest developments in single-cell proteomics, from buffer comparisons to sorting techniques, and evaluates two MS measurement methods (DIA-PASEF and Slice-PASEF) for low-input samples.
We conducted a comparative analysis of adenocarcinoma (ADC) and squamous cell carcinoma (SCC) subtypes using cell culture models, tissue samples and patient plasma.
Our results reveal the differences between these subtypes, identifying distinct proteomic profiles correlating with disease state and co-regulation of oncogenic protein networks and candidate biomarkers.
Our long-term goal is to improve the understanding of the mechanisms driving non-small cell lung cancer (NSCLC) by an innovative approach of profiling tumor-associated proteins in both bulk and single cell models, including plasma proteins from NSCLC-derived tumors.