Develop and Validate Blood-Borne Lung Cancer Diagnostic Biomarkers Using Multi-Omics and Interpretable AI

Project Overview

Lung cancer is the leading cause of cancer-related death worldwide. This project seeks to develop and validate blood-borne diagnostic biomarkers to enable early detection to save lives. A unique cohort has been collected in Liverpool with matched proteomic, miRNA, and metabolomic profiles from plasma samples collected 1–10 years prior to clinical diagnosis. The project will utilize network-based supervised stratification (NBS2) and time-to-event (TTE) analysis to identify molecular networks indicative of early oncogenesis and late-stage disease.

What You Will Do

• Integrate multi-omics data into consistent analytical frameworks.
• Identify biomarkers by applying NBS2 and TTE analysis alongside benchmarking with other machine learning techniques.
• Validate findings using independent UK Biobank Olink proteins and metabolic datasets.

Expected Outcomes

The project will provide novel insights into the molecular underpinnings of lung cancer progression by leveraging a first-of-its-kind multi-omics dataset sampled years before diagnosis. Outcomes include novel biomarker panels for early detection and improved understanding of the disease biology through pathway-based models.

Why This Matters

Early detection of lung cancer is critical to improving survival rates. Blood-based miRNA screening has recently shown promise, and this studentship will complement ongoing CRUK-funded efforts. The project trains doctoral candidates in cutting-edge multi-omics, network modelling, and survival analysis, equipping them with skills sought by the pharmaceutical industry.