The development and progression of cancer, a collection of diseases with complex genetic architectures, is facilitated by the interplay of multiple etiological factors. This complexity challenges the traditional single-platform study design and calls for an integrated approach to data analysis. However, integration of heterogeneous measurements of biological variation is a non-trivial exercise due to the diversity of the human genome and the variety of output data formats and genome coverage obtained from the commonly used molecular platforms. This review article will provide an introduction to integration strategies used for analyzing genetic risk factors for cancer. We critically examine the ability of these strategies to handle the complexity of the human genome and also accommodate information about the biological and functional interactions between the elements that have been measured—making the assessment of disease risk against a composite genomic factor possible. The focus of this review is to provide an overview and introduction to the main strategies and to discuss where there is a need for further development.
Germline pathogenic variants in BRCA1 confer a high risk of developing breast and ovarian cancer. The BRCA1 exon 11 (formally exon 10) is one of the largest exons and codes for the nuclear localization signals of the corresponding gene product. This exon can be partially or entirely skipped during pre‐mRNA splicing, leading to three major in‐frame isoforms that are detectable in most cell types and tissue, and in normal and cancer settings. However, it is unclear whether the splicing imbalance of this exon is associated with cancer risk. Here we identify a common genetic variant in intron 10, rs5820483 (NC_000017.11:g.43095106_43095108dup), which is associated with exon 11 isoform expression and alternative splicing, and with the risk of breast cancer, but not ovarian cancer, in BRCA1 pathogenic variant carriers. The identification of this genetic effect was confirmed by analogous observations in mouse cells and tissue in which a loxP sequence was inserted in the syntenic intronic region. The prediction that the rs5820483 minor allele variant would create a binding site for the splicing silencer hnRNP A1 was confirmed by pull‐down assays. Our data suggest that perturbation of BRCA1 exon 11 splicing modifies the breast cancer risk conferred by pathogenic variants of this gene.
Developmental dysplasia of the hip (DDH) is a common condition involving instability of the hip with multifactorial etiology. Early diagnosis and treatment are critical as undetected DDH is an important cause of long-term hip complications. Better diagnostics may be achieved through genetic methods, especially for patients with positive family history. Several candidate genes have been reported but the exact molecular etiology of the disease is yet unknown. In the present study, we performed whole exome sequencing of DDH patients from 28 families with at least two affected first-degree relatives. Four genes previously not associated with DDH (METTL21B, DIS3L2, PPP6R2, and TM4SF19) were identified with the same variants shared among affected family members, in more than two families. Among known association genes, we found damaging variants in DACH1, MYH10, NOTCH2, TBX4, EVC2, OTOG, and SHC3. Mutational burden analysis across the families identified 322 candidate genes, and enriched pathways include the extracellular matrix, cytoskeleton, ion-binding, and detection of mechanical stimulus. Taken altogether, our data suggest a polygenic mode of inheritance for DDH, and we propose that an impaired transduction of the mechanical stimulus is involved in the etiopathological mechanism. Our findings refine our current understanding of candidate causal genes in DDH, and provide a foundation for downstream functional studies.
Glioblastoma is one of the most aggressive cancers, but the molecular evolution is still not fully understood. We used PET imaging combined with deep sequencing of glioblastoma biopsies at both the RNA and DNA levels to get a deeper insight into molecular evolution. In the clinical setting, PET imaging provides information about metabolically active tumor areas, but the molecular interpretation is unclear. Our primary objective was to perform an intratumoral spatial comparison of biopsies from potentially aggressive and less aggressive areas in glioblastomas according to PET scans. Additionally, tissue from the tumor periphery was included. We used MRI, 11C-methionine(MET) PET, and 18F-FDG PET was used in combination to obtain a series of neurosurgical stereotactic biopsies from tumor areas with high MET and 18F-FDG uptake (hotspot), low MET and 18F-FDG uptake (coldspot), as well as tumor periphery of six glioblastoma patients that were processed for whole genome, exome, and transcriptome sequencing. Differential gene expression and gene ontology analysis showed that hotspots were enriched in gene sets associated with DNA replication, cell cycle, and ligand receptor interaction. Genome and exome analysis suggested hotspots and coldspots to have similar mutational profiles. However, a limited number of hotspot-specific mutations and fusion transcripts indicated that hotspot tumor cells developed from coldspot cells and point at the potential role of hotspot driver genes in glioblastoma. Our findings reveal that hotspots in glioblastomas represent a more advanced stage of molecular evolution than coldspots.
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