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  • Poster presentation
  • P-II-0622

Integrative proteomic and AI-based histopathologic profiling reveals new prognostic subclusters in early-stage non-small cell lung cancer

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Clinical Proteomics

Poster

Integrative proteomic and AI-based histopathologic profiling reveals new prognostic subclusters in early-stage non-small cell lung cancer

Thema

  • Clinical Proteomics

Mitwirkende

Corinna Friedrich (Berlin / DE), Simon Schallenberg (Berlin / DE), Matthias Ziehm (Berlin / DE), Gabriel Dernbach (Berlin / DE), Philipp Keyl (Berlin / DE; Munich / DE), Hannah Demeke (Berlin / DE), Keziban Merve Alp (Berlin / DE), Dražen Papić (Berlin / DE), Rebecca Fritz (Berlin / DE), Mohamed Haji (Berlin / DE), David Horst (Berlin / DE), Frederick Klauschen (Berlin / DE; Munich / DE), Philipp Mertins (Berlin / DE)

Abstract

Understanding the early stages of lung cancer progression at the molecular and cellular levels is crucial for improving patient outcomes. Our study employed an innovative integrative approach combining advanced deep proteomics profiling with cutting-edge histopathology foundation models. This method facilitated a comprehensive analysis of protein regulation, cell composition, and clinical outcomes in a formalin-fixed, paraffin-embedded (FFPE) cohort comprising over 1,000 non-small cell lung cancer cases.

We identified a novel proteomic subcluster associated with a favorable prognosis, characterized by an enrichment of cytotoxic T cells. Our analysis differentiated between three-year relapse-free survivors and non-survivors of lung squamous cell carcinoma, revealing that non-survivors exhibited specific upregulation of the inflammation-promoting complement-based membrane attack complex, alongside higher neutrophil granulocyte counts. In contrast, adenocarcinomas in non-survivors showed upregulation of the minichromosome maintenance (MCM) replication complex, accompanied by higher tumor-associated macrophage counts at diagnosis.

Our discovery-driven proteomics approach successfully identified both tissue-resident and systemic protein markers linked to poor outcomes in lung cancer, alongside distinctive protein signatures correlating with cell types identified through histopathological analysis. Notable potential biomarkers, including complement protein C7 and the MCM2 component of the replication complex, were further validated using multiplexed immunohistochemistry.

This research underscores the potential of combining high-throughput proteomics with histopathology foundation models to elucidate molecular and cellular interactions that correlate with prognosis in extensive cohorts of solid tumors. These findings not only enhance our understanding of lung cancer biology but also pave the way for the development of new diagnostic strategies.

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