The figure illustrates the NALUNG project workflow designed to refine neoadjuvant (NA) therapy in resectable non-small-cell lung cancer (NSCLC). Patients receive NA chemotherapy or chemoimmunotherapy prior to surgical tumour resection. Tumour tissue and liquid biopsy samples are collected to identify biomarkers associated with treatment response and toxicity. Multi-omics profiling including genomics-, epigenomics-, transcriptomics-, proteomics-, metabolomics-based biomarkers is integrated to generate comprehensive molecular signatures. These data, combined with clinical, nutritional, and lifestyle factors, feed into AI-driven predictive modelling to stratify patients, distinguish responders from non-responders, and estimate toxicity risk. The overall aim is to support personalised treatment selection and improve outcomes for patients undergoing NA therapy in NSCLC.

Non-Small-Cell Lung Cancer (NSCLC) is the most common type of lung cancer and remains a leading cause of cancer-related death worldwide. Neoadjuvant (NA) treatment, given before surgery, aims to shrink the tumour, eliminate hidden cancer cells, and improve long-term survival, yet patient responses vary widely and some individuals experience significant side effects, making it difficult to determine who will benefit most. This project aims to identify biological markers in tumour tissue and blood that can reliably predict treatment response and the risk of toxicity by applying a comprehensive multi-omics strategy that includes genomics, epigenomics, transcriptomics, proteomics, and metabolomics. By integrating these molecular layers with clinical characteristics, lifestyle information, and nutritional status, the consortium will build predictive models that distinguish responders from non-responders and identify individuals more likely to experience harmful treatment effects. Advanced machine-learning and bioinformatics approaches will be used to uncover molecular signatures linked to outcomes, ultimately enabling more precise and personalised treatment decisions. The project seeks to improve patient selection, reduce unnecessary toxicity, and enhance long-term survival, contributing to the development of biomarker-driven strategies that support better and safer care for patients with resectable NSCLC.