Explore the vast range of titles available.

Somatic variant calling is a critical step in cancer genome analysis, but the performance of available tools can vary depending on their underlying algorithms and filtering strategies. We compared three widely used variant callers—Mutect2, Strelka2, and FreeBayes—for their performance in somatic single-nucleotide variant (SNV) detection using both synthetic and real whole-exome sequencing (WES) data. Synthetic data were generated by introducing 4709 SNVs into a variant-free BAM file, while real data consisted of tumor and matched normal WES samples from five ovarian cancer (OC) patients. All callers were run using the nf-core/sarek pipeline with default settings and appropriate filtering. In the synthetic dataset, all tools showed high precision (~99.9%), with Mutect2 achieving the highest recall (63.1%), followed by Strelka2 (46.3%) and FreeBayes (45.2%). In real samples, FreeBayes detected the most variants, and only 5.1% of SNVs were shared across all three tools. We then integrated calls with SomaticSeq in consensus mode (Mutect2 + Strelka2) and kept variants with stronger allelic signals—showing higher VAFs and, typically, higher coverages relative to single-caller only. Caller-exclusive variants showed significant differences in allele frequency and sequencing depth. These results highlight substantial variability in SNV detection across tools. While all showed high specificity, differences in sensitivity and variant profiles underscore the need for context-specific caller selection or ensemble approaches in cancer genomics.

We assessed the associations between population-based polygenic risk scores (PRS) for breast (BC) or epithelial ovarian cancer (EOC) with cancer risks for BRCA1 and BRCA2 pathogenic variant carriers. Retrospective cohort data on 18,935 BRCA1 and 12,339 BRCA2 female pathogenic variant carriers of European ancestry were available. Three versions of a 313 single-nucleotide polymorphism (SNP) BC PRS were evaluated based on whether they predict overall, estrogen receptor (ER)–negative, or ER-positive BC, and two PRS for overall or high-grade serous EOC. Associations were validated in a prospective cohort. The ER-negative PRS showed the strongest association with BC risk for BRCA1 carriers (hazard ratio [HR] per standard deviation=1.29 [95% CI 1.25–1.33], P=3×10−72). For BRCA2, the strongest association was with overall BC PRS (HR=1.31 [95% CI 1.27–1.36], P=7×10−50). HR estimates decreased significantly with age and there was evidence for differences in associations by predicted variant effects on protein expression. The HR estimates were smaller than general population estimates. The high-grade serous PRS yielded the strongest associations with EOC risk for BRCA1 (HR=1.32 [95% CI 1.25–1.40], P=3×10−22) and BRCA2 (HR=1.44 [95% CI 1.30–1.60], P=4×10−12) carriers. The associations in the prospective cohort were similar. Population-based PRS are strongly associated with BC and EOC risks for BRCA1/2 carriers and predict substantial absolute risk differences for women at PRS distribution extremes.

Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in nonbreast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer.

BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.761028, HR = 1.14, 95% CI: 1.09–1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.461028, HR = 1.27, 95% CI: 1.17–1.38) and 4q32.3 (rs4691139, P = 3.461028, HR = 1.20, 95% CI: 1.17–1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific association. The 17q21.31 locus was also associated with ovarian cancer risk in 8,211 BRCA2 carriers (P = 261024). These loci may lead to an improved understanding of the etiology of breast and ovarian tumors in BRCA1 carriers. Based on the joint distribution of the known BRCA1 breast cancer risk-modifying loci, we estimated that the breast cancer lifetime risks for the 5% of BRCA1 carriers at lowest risk are 28%–50% compared to 81%–100% for the 5% at highest risk. Similarly, based on the known ovarian cancer risk-modifying loci, the 5% of BRCA1 carriers at lowest risk have an estimated lifetime risk of developing ovarian cancer of 28% or lower, whereas the 5% at highest risk will have a risk of 63% or higher. Such differences in risk may have important implications for risk prediction and clinical management for BRCA1 carriers.

Pathogenic germline variants in the ATM gene are associated with a 20–30% lifetime risk of breast cancer. Crucially, a relevant fraction of loss-of-function variants in breast cancer susceptibility genes disrupts pre-mRNA splicing. We aimed to perform splicing analysis of ATM splice-site variants identified in the large-scale sequencing project BRIDGES (Breast Cancer After Diagnostic Gene Sequencing). To this end, we bioinformatically selected 47 splice-site variants across 17 exons that were genetically engineered into three minigenes and assayed in MCF-7 cells. Aberrant splicing was observed in 38 variants. Of these, 30 variants, including 7 missense, yielded no or negligible expression of the minigene full-length (mgFL) transcript. A total of 69 different transcripts were characterized, 48 of which harboured a premature termination codon. Some variants, such as c.2922-1G>A, generated complex patterns with up to 10 different transcripts. Alternative 3′ or 5′ splice-site usage was the predominant event. Integration of ATM minigene read-outs into the ACMG/AMP (American College of Medical Genetics and Genomics/Association for Molecular Pathology)-based specifications for the ATM gene enabled the classification of 30 ATM variants as pathogenic or likely pathogenic and 9 as likely benign. Overall, splicing assays provide key information for variant interpretation and the clinical management of patients.

A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P¼9.2 10 20), ER-negative BC (P¼1.1 10 13), BRCA1-associated BC (P¼7.7 10 16) and triple negative BC (P-diff¼2 10 5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P¼2 10 3) and ABHD8 (Po2 10 3). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 30-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk.

Half of the high-risk colorectal cancer families that fulfill the clinical criteria for Lynch syndrome lack germline mutations in the mismatch repair (MMR) genes and remain unexplained. Genetic testing for hereditary cancers is rapidly evolving due to the introduction of multigene panels, which may identify more mutations than the old screening methods. The aim of this study is the use of a Next Generation Sequencing panel in order to find the genes involved in the cancer predisposition of these families. For this study, 98 patients from these unexplained families were tested with a multigene panel targeting 94 genes involved in cancer predisposition. The mutations found were validated by Sanger sequencing and the segregation was studied when possible. We identified 19 likely pathogenic variants in 18 patients. Out of these, 8 were found in MMR genes (5 in MLH1, 1 in MSH6 and 2 in PMS2). In addition, 11 mutations were detected in other genes, including high penetrance genes (APC, SMAD4 and TP53) and moderate penetrance genes (BRIP1, CHEK2, MUTYH, HNF1A and XPC). Mutations c.1194G>A in SMAD4, c.714_720dup in PMS2, c.2050T>G in MLH1 and c.1635_1636del in MSH6 were novel. In conclusion, the detection of new pathogenic mutations in high and moderate penetrance genes could contribute to the explanation of the heritability of colorectal cancer, changing the individual clinical management. Multigene panel testing is a more effective method to identify germline variants in cancer patients compared to single-gene approaches and should be therefore included in clinical laboratories.

To identify colorectal cancer (CRC) susceptibility alleles, we conducted a genome-wide association study. In phase 1, we genotyped 550,163 tagSNPs in 940 familial colorectal tumor cases (627 CRC, 313 high-risk adenoma) and 965 controls. In phase 2, we genotyped 42,708 selected SNPs in 2,873 CRC cases and 2,871 controls. In phase 3, we evaluated 11 SNPs showing association at P < 10 −4 in a joint analysis of phases 1 and 2 in 4,287 CRC cases and 3,743 controls. Two SNPs were taken forward to phase 4 genotyping (10,731 CRC cases and 10,961 controls from eight centers). In addition to the previously reported 8q24, 15q13 and 18q21 CRC risk loci, we identified two previously unreported associations: rs10795668, located at 10p14 ( P = 2.5 × 10 −13 overall; P = 6.9 × 10 −12 replication), and rs16892766, at 8q23.3 ( P = 3.3 × 10 −18 overall; P = 9.6 × 10 −17 replication), which tags a plausible causative gene, EIF3H . These data provide further evidence for the 'common-disease common-variant' model of CRC predisposition.

BACKGROUND : Most BRCA1 or BRCA2 mutation carriers have inherited a single (heterozygous) mutation. Transheterozygotes (TH) who have inherited deleterious mutations in both BRCA1 and BRCA2 are rare, and the consequences of transheterozygosity are poorly understood. METHODS : From 32,295 female BRCA1/2 mutation carriers, we identified 93 TH (0.3 %). “Cases” were defined as TH,and “controls” were single mutations at BRCA1 (SH1) or BRCA2 (SH2). Matched SH1 “controls” carried a BRCA1 mutation found in the TH “case”. Matched SH2 “controls” carried a BRCA2 mutation found in the TH “case”. Aftermatching the TH carriers with SH1 or SH2, 91 TH were matched to 9316 SH1, and 89 TH were matched to 3370SH2. RESULTS : The majority of TH (45.2 %) involved the three common Jewish mutations. TH were more likely than SH1 and SH2 women to have been ever diagnosed with breast cancer (BC; p = 0.002). TH were more likely to be diagnosed with ovarian cancer (OC) than SH2 (p = 0.017), but not SH1. Age at BC diagnosis was the same in TH vs. SH1 (p = 0.231), but was on average 4.5 years younger in TH than in SH2 (p < 0.001). BC in TH was more likely to be estrogen receptor (ER) positive (p = 0.010) or progesterone receptor (PR) positive (p = 0.013) than in SH1, but less likely to be ER positive (p < 0.001) or PR positive (p = 0.012) than SH2. Among 15 tumors from TH patients, there was no clear pattern of loss of heterozygosity (LOH) for BRCA1 or BRCA2 in either BC or OC. CONCLUSIONS : Our observations suggest that clinical TH phenotypes resemble SH1. However, TH breast tumor marker characteristics are phenotypically intermediate to SH1 and SH2.