2023 World Conference on Lung Cancer (Posters)-P1.13. Deep Multi-omic Blood-Based Biomarker Discovery in People with Smoking History Demonstrates High Early Detection of Nsclc

P1.13. Deep Multi-omic Blood-Based Biomarker Discovery in People with Smoking History Demonstrates High Early Detection of Nsclc - PDF(Abstract)

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This study presents the findings of a case-control study that aimed to discover blood-based biomarkers for the early detection of non-small cell lung cancer (NSCLC) in individuals with a smoking history. The study included 361 subjects with untreated NSCLC and 670 matched controls, and focused on a subset of 444 subjects who were current or former smokers. Deep multi-omic profiling was conducted on each subject, analyzing proteins/peptides, metabolites, and mRNA. The performance of the proteomic platform used in the study was found to be comparable to previous plasma proteomic studies. The study cohort was divided into a training set and a validation set, and the validation set demonstrated a high classification accuracy with an area under the curve (AUC) of 0.93. The multi-omic classifier exhibited a sensitivity of 85% and a specificity of 85% across all stages of NSCLC. The sensitivity for Stage I detection was 80%, while for Stage II-IV it was 87%. Overall, the classifier showed promise in early and all-stage detection of NSCLC in current and former smokers. The study proposes that these findings can serve as the basis for the development of a multi-omics assay for the early detection of lung cancer through blood-based liquid biopsies.

Asset Subtitle

Brian Koh

Meta Tag

Speaker Brian Koh

Topic Screening & Early Detection: Biomarkers/Imaging Technology

Keywords

blood-based biomarkers

non-small cell lung cancer

smoking history

case-control study

proteins/peptides

metabolites

mRNA

multi-omic profiling

sensitivity

specificity