Search

Most breast cancer heritability is unexplained. We hypothesized that analysis of unrelated familial cases in a GWAS context could enable the identification of novel susceptibility loci. In order to examine the association of a haplotype with breast cancer risk, we performed a genome-wide haplotype association study using a sliding window analysis of window sizes 1-25 SNPs in 650 familial invasive breast cancer cases and 5021 controls. We identified five novel risk loci on 9p24.3 (OR 3.4; p 4.9 x 10(-11)), 11q22.3 (OR 2.4; p 5.2 x 10(-9)), 15q11.2 (OR 3.6; p 2.3 x 10(-8)), 16q24.1 (OR 3; p 3 x 10(-8)) and Xq21.31 (OR 3.3; p 1.7 x 10(-8)) and confirmed three well-known loci on 10q25.13, 11q13.3, and 16q12.1. In total, 1593 significant risk haplotypes and 39 risk SNPs were distributed on the eight loci. In comparison with unselected breast cancer cases from a previous study, the OR was increased in the familial analysis in all eight loci. Analyzing familial cancer cases and controls enabled the identification of novel breast cancer susceptibility loci.

To search for colorectal cancer (CRC) risk loci, Swedish samples were used for a genome-wide haplotype analysis. A logistic regression model was employed in 2663 CRC cases and 1642 controls in the discovery analysis. Three analyses were done, on all, familial-, and nonfamilial CRC samples and only results with odds ratio (OR) > 1 were analyzed. single nucleotide polymorphism (SNP) analysis did not generate any statistically significant results. Haplotype analysis suggested novel loci, on chromosome 2q36.1 (OR = 1.71, p value = 5.6924 × 10-8 ) in all CRC samples, chromosome 1q43 (OR = 4.04 p value = 3.24 × 10-8 ) in familial CRC samples, and two hits in nonfamilial CRC samples, chromosomes 2q36.1 (OR = 1.71 p value = 5.69 × 10-8 ) and 3p24.3 (OR = 1.62 p value = 6.21 × 10-9 ). Moreover, one locus on chromosome 20q13.33 was suggested in analyses of all samples, and five more novel loci were suggested on chromosomes 10q25.3, 15q,22.31, 17p11.2, 1p34.2, and 3q24. The haplotypes from the analysis of all samples were replicated in a second study of CRC cases and controls from the same part of Sweden. In summary, using haplotype analysis in Swedish CRC samples, the best hits were novel loci and the locus on chromosomes 2q36.1 and 20q13.33 suggested in the analysis of all samples were confirmed in a second cohort. The ORs were often higher than ORs from published genome-wide association study (GWAS). The study suggested it was possible that a risk locus could involve more than one gene, and that haplotypes could give information on the gene or genes possibly involved in the risk at specific locus.

The genetics underlying thyroid cancer dedifferentiation is only partly understood and has not yet been characterised using comprehensive pan‐genomic analyses. We investigated a unique case with synchronous follicular thyroid carcinoma (FTC), poorly differentiated thyroid carcinoma (PDTC), and anaplastic thyroid carcinoma (ATC), as well as regional lymph node metastases from the PDTC and ATC from a single patient using whole‐genome sequencing (WGS). The FTC displayed mutations in CALR, RB1, and MSH2, and the PDTC exhibited mutations in TP53, DROSHA, APC, TERT, and additional DNA repair genes – associated with an immense increase in sub‐clonal somatic mutations. All components displayed an overrepresentation of C>T transitions with associated microsatellite instability (MSI) in the PDTC and ATC, with borderline MSI in the FTC. Clonality analyses pinpointed a shared ancestral clone enriched for mutations in TP53‐associated regulation of DNA repair and identified important sub‐clones for each tumour component already present in the corresponding preceding lesion. This genomic characterisation of the natural progression of thyroid cancer reveals several novel genes of interest for future studies. Moreover, the findings support the theory of a stepwise dedifferentiation process and suggest that defects in DNA repair could play an important role in the clonal evolution of thyroid cancer., De 3 första författarna delar förstaförfattarskapet

In 2015, Cancer is the second leading cause of death worldwide. Genetic predisposition in familial cancer cases is largely unexplained. At the same time, rapid development in sequencing technology results in an unprecedented increase in the amount of whole exome- and whole genome sequencing data. The studies in this thesis take advantage of the technology and explore possibilities to identify genetic factors behind cancer development. In paper I, we identified 12 novel non-synonymous single nucleotide variants, which were shared among 5 affected members of a family with gastric- and rectal cancer. The mutations were found in 12 different genes; DZIP1L, PCOLCE2, IGSF10, SUCNR1, OR13C8, EPB41L4B, SEC16A, NOTCH1, TAS2R7, SF3A1, GAL3ST1, and TRIOBP. None of the mutations was suggested as a high penetrant mutation We propose this family, suggested to segregate dominant disease, could be an example of complex inheritance. In paper II, we identified a pathogenic variant in PTEN in a patient with a Cowden syndrome. We confirmed a pathogenic variant in PMS2 found in one of the samples suggested by another study. In addition, the study proposed 3 candidate missense variant in known cancer susceptibility genes (BMPR1A, BRIP1 and SRC), 3 truncating variants in possibly novel cancer genes (CLSPN, SEC24B and SSH2), 4 candidate missense variants (ACACA, NR2C2, INPP4A and DIDO1), and 5 possible autosomal recessive genes (ATP10B, PKHD1, UGGT2, MYH13 and TFF3). The study in paper III was to provide a comprehensive local reference database of 1,000 whole genome sequenced Swedish individuals. The samples were selected by principal component analysis from the Swedish Twin Registry (n=942) and The Northern Sweden Population Health Study (n=58). The result illustrated that the genetic diversity within Sweden is substantial compared with the diversity among continental European populations, confirming the importance this database. The aim of paper IV was to identify combinations of both kn

Here we describe the SweGen data set, a comprehensive map of genetic variation in the Swedish population. These data represent a basic resource for clinical genetics laboratories as well as for sequencing-based association studies by providing information on genetic variant frequencies in a cohort that is well matched to national patient cohorts. To select samples for this study, we first examined the genetic structure of the Swedish population using high-density SNP-array data from a nation-wide cohort of over 10 000 Swedish-born individuals included in the Swedish Twin Registry. A total of 1000 individuals, reflecting a cross-section of the population and capturing the main genetic structure, were selected for whole-genome sequencing. Analysis pipelines were developed for automated alignment, variant calling and quality control of the sequencing data. This resulted in a genome-wide collection of aggregated variant frequencies in the Swedish population that we have made available to the scientific community through the website https://swefreq.nbis.se. A total of 29.2 million single-nucleotide variants and 3.8 million indels were detected in the 1000 samples, with 9.9 million of these variants not present in current databases. Each sample contributed with an average of 7199 individual-specific variants. In addition, an average of 8645 larger structural variants (SVs) were detected per individual, and we demonstrate that the population frequencies of these SVs can be used for efficient filtering analyses. Finally, our results show that the genetic diversity within Sweden is substantial compared with the diversity among continental European populations, underscoring the relevance of establishing a local reference data set.