Cancer is a complex disease shaped by a heterogeneous landscape of inherited genetic variants and acquired somatic aberrations. Although specific patterns of somatic aberrations within key pathways are recognized as hallmarks of many cancers, and mounting evidence suggests a significant interplay between germline and somatic variants, the intricate relationship between germline predisposition and the disruption of these pathways remains poorly understood. Here, I present an integrative approach using multi-omics data to functionally characterize germline variants and explore the heterogeneous landscape of somatic mutations, with the aim of establish mechanistic links between functional variants and the disruption of cancer-related biological processes. To enable the identification of functional variants, I initially performed a comprehensive characterization of functionally annotated transcriptional regulatory elements, establishing a hierarchy of ‘consensus’ elements across multiple levels of abstraction. This analysis generated a vast collection of consensus promoters, enhancers, and active enhancers, spanning 198 cell lines and 38 tissue types, with aggregate data providing global consensus definitions for each element type. Additionally, ‘total binding affinity’ method was employed, integrating 1000 Genomes Project genotype data and thousands of transcription factor binding motifs, to further characterize and functionally annotate these regulatory elements. The results generated from this analysis can be interactively explored and visualized through the CONREL web application. To allow effective annotation of individual’s ancestry, I developed and successfully employed an improved version of EthSEQ (version 3), an R package that provides a rapid and reliable pipeline for ancestry annotation. Accurate stratification of individual ancestry is essential for correctly interpreting the impact of genomic variations in associations studies. EthSEQ version 3 was successfully utilized to determine the genetic ancestry of over 500 pediatric patients diagnosed with 11 different tumor types, enabling further investigation into the genetic landscape of patients confidently identified as of European ancestry.To further investigate into the interplay between germline and somatic variants, I conducted genome-wide association studies across 33 cancer types characterized by The Cancer Genome Atlas, using binary traits defined by somatic aberration profiles in ten oncogenic signaling pathways. Functional links between associated variants and somatic profiles were investigated through cis-eQTL data to identify regulatory interactions with pathway-related genes. Additionally, using GWAS summary statistics I employed polygenic scores to examine the contribution of germline genetic variation to somatic molecular profiles, tumor subtypes, and clinical outcomes such as patient survival and tumor aggressiveness. Polygenic scores were validated using external data from PCAWG and CCLE datasets. Lastly, to explore the heterogeneity of somatic mutational profiles, I employed a network-based approach to propagate somatic alterations through a molecular interaction network, aiming to reveal novel patterns of somatic alteration with potential significance in cancer. I then conducted a series of GWAS analyses, utilizing traits defined by combinations of these propagated somatic scores across genes involved in well-defined DNA repair pathways. Overall, I demonstrate that germline genetics can describe patients’ genetic liability to develop specific cancer molecular and clinical profiles. Understanding the functional roles of genetic variants can provide valuable insights into the biological mechanisms underlying a disease or trait.