Non-small cell lung cancer (NSCLC) comprises 85% of all lung cancer cases and, for the majority of the patients, the diagnosis is performed in advanced stages (locally advanced-stage III or stage IV metastatic disease). Inter-patient, inter-tumor and intra-tumor heterogeneity are responsible of such a large prognosis variability, representing a challenge for the scientific community. Precision medicine has become a key focus of modern bioscience and medicine. NSCLC is an example to show the advantages of a tailored therapy.
Within this frame, radiomics and pathomics approaches are capable of quantifying tumor phenotype using data-characterization algorithms, which extract features from the radiological and histologic images respectively, mine the data for hypothesis generation, testing and association with biological and clinical endpoints. This investigation will result in prognostic and predictive personalized models for patients affected by locally advanced or metastatic NSCLC.