Multi-omics molecular profiling of lung tumours

Abstract

Lung Cancer (LC) is one of the most common malignancies and is the leading cause of cancer death worldwide among both men and women. Current LC classifications are based on histopathological features which poorly reflect the molecular diversity of these tumours. Consequently, primary and secondary drug resistance are very frequent, and a high mortality is usual in LC patients. Despite the fact that LC has been intensively studied, there is a lack of effective biomarkers for early detection, stratification and prognosis. Integration of omics data is a powerful approach that can be used to identify molecular subgroups relevant in the clinical setting. This thesis addresses this challenge by characterising the molecular alterations accompanying LC at the genetic and DNA methylation level, using a combination of Whole-Exome Sequencing (WES), Targeted Capture Sequencing (TCS), Single Nucleotide Polymorphism (SNP) genotyping, Whole-Genome Bisulfite Sequencing and RNA-sequencing. The integration of different types of omics data first validated previous molecular alterations in frequently diagnosed LC tumours. This allowed comparison of the genomic and epigenomic landscapes between these common and rarer LC subtypes. Next, novel molecular subgroups of Non-Small Cell Lung Cancer (NSCLC) tumours with bad prognostic, as well as subgroups of Lung Carcinoids (L-CDs, an understudied LC subtype) have been identified and their molecular alterations and signatures characterised. Significant associations with histological features and gene expression programmes have been found by using several bioinformatic tools. These results show the value of multi-omics approaches to better understand the molecular mechanisms underlying LC and to identify new biomarkers. Importantly, some of these findings may be translatable and are likely to improve the detection, monitoring and stratification for targeted therapies in LC patients.