Approaches to integrating germline and tumor genomic data in cancer research

Abstract

Cancer is characterized by a diversity of genetic and epigenetic alterations occurring in both the germline and somatic (tumor) genomes. Hundreds of germline variants associated with cancer risk have been identified, and large amounts of data identifying mutations in the tumor genome that participate in tumorigenesis have been generated. Increasingly, these two genomes are being explored jointly to better understand how cancer risk alleles contribute to carcinogenesis and whether they influence development of specific tumor types or mutation profiles. To understand how data from germline risk studies and tumor genome profiling is being integrated, we reviewed 160 articles describing research that incorporated data from both genomes, published between January 2009 and December 2012, and summarized the current state of the field. We identified three principle types of research questions being addressed using these data: (i) use of tumor data to determine the putative function of germline risk variants; (ii) identification and analysis of relationships between host genetic background and particular tumor mutations or types; and (iii) use of tumor molecular profiling data to reduce genetic heterogeneity or refine phenotypes for germline association studies. We also found descriptive studies that compared germline and tumor genomic variation in a gene or gene family, and papers describing research methods, data sources, or analytical tools. We identified a large set of tools and data resources that can be used to analyze and integrate data from both genomes. Finally, we discuss opportunities and challenges for cancer research that integrates germline and tumor genomics data.

Fig. 1.

Process of identifying and selecting articles for inclusion. The process for identifying articles for inclusion in the literature review is shown and described in the Materials and Methods section. Multiple searches of PubMed were performed and additional sources were used to identify articles for consideration. After review, 160 articles were included in the analysis.

Fig. 2.

Articles analyzing germline and tumor genomic data by cancer type. A total of 160 articles in which data from the germline and tumor genomes were analyzed specified cancer type, encompassing 19 different cancer types. Articles in the ‘multiple or NOS’ category, multiple or not otherwise specified, reported more than one cancer type or were review articles or best practice articles which did not specify a cancer type.

Fig. 3.

Approaches used for germline genomic data analysis. The approaches used for analysis of germline variation reported in the 160 included publications were tabulated. Targeted analysis of germline variants are solid bars. Genome-wide analysis of germline variants are striped bars. Articles used ‘known mutation status’ if the germline mutations were determined previously. ‘Other’ methods included methylation, karyotyping, or phenotype to assume genotype. Multiple approaches may have been used in a single article.

Fig. 4.

Approaches used for tumor genomic data analysis.The approaches used for analysis of somatic variation reported in the 160 included publications were tabulated. Targeted analysis of germline variants are solid bars. Genome-wide analysis of germline variants are striped bars. Multiple approaches may have been used in a single article.