Molecular Characterisation and Prognostic Biomarker Discovery in Human Non-Small Cell Lung Cancer

Abstract: Non-small cell lung cancer (NSCLC) constitutes a clinically, histologically, and genetically heterogeneous disease entity that represents a major cause of cancer-related death. Early-stage patients, who undergo surgery with curative intent, experience high recurrence rates and the effect of adjuvant treatment is modest. Prognostic biomarkers would be of particular relevance to guide intensified treatment depending on expected outcome and moreover often infer a biological role in tumourigenesis.This thesis presents a translational study approach to establish a well-characterised NSCLC frozen-tissue cohort and to obtain a profile of each specimen with regard to genome-wide copy number alterations, global gene expression levels and somatic mutations in selected cancer-related genes. Furthermore, the generation of a formalin-fixed, paraffin-embedded tissue microarray enabled validation of findings on the protein level using immunohistochemistry. The comprehensive molecular characterisation, combined with data on clinical parameters, enabled the analysis of biomarkers linked to disease outcome. In Paper I, single nucleotide polymorphism arrays were applied to assess copy number alterations in NSCLC and associations with overall survival in adenocarcinoma and squamous cell carcinoma were described. In Paper II, we evaluated expression levels of selected stromal proteins in NSCLC using immunohistochemistry and the adhesion molecule CD99 was identified as an outcome-related biomarker in two independent cohorts. Paper III presents a strategy for prognostic biomarker discovery based on gene expression profiling, meta-analysis, and validation of protein expression on tissue microarrays, and suggests the putative tumour suppressor CADM1 as a candidate biomarker. In Paper IV, we propose a prognostic role for tumour-infiltrating IGKC-expressing plasma cells in the local tumour microenvironment, indicating an involvement of the humoral immune response in anti-tumor activity. In Paper V, we combined next-generation deep sequencing with statistical analysis of the TP53 database to define novel parameters for database curation.In summary, this thesis exemplifies the benefits of a translational study approach, based on a comprehensive tumour characterisation, and describes molecular markers associated with clinical outcome in NSCLC.