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Despite improvements in genomics technology, the detection of structural variants (SVs) from short-read sequencing still poses challenges, particularly for complex variation. Here we analyse the genomes of two patients with congenital abnormalities using the MinION nanopore sequencer and a novel computational pipeline—NanoSV. We demonstrate that nanopore long reads are superior to short reads with regard to detection of de novo chromothripsis rearrangements. The long reads also enable efficient phasing of genetic variations, which we leveraged to determine the parental origin of all de novo chromothripsis breakpoints and to resolve the structure of these complex rearrangements. Additionally, genome-wide surveillance of inherited SVs reveals novel variants, missed in short-read data sets, a large proportion of which are retrotransposon insertions. We provide a first exploration of patient genome sequencing with a nanopore sequencer and demonstrate the value of long-read sequencing in mapping and phasing of SVs for both clinical and research applications. The detection of structural variants can be difficult with short-read sequencing technology, especially when variants are highly complex. Here, the authors use a MinION nanopore sequencer to analyse two patient genomes and develop NanoSV to map known and novel structural variants in long read data.

Over the past years, large consortia have been established to fuel the sequencing of whole genomes of many cancer patients. Despite the increased abundance in tools to study the impact of SNVs, non-coding SVs have been largely ignored in these data. Here, we introduce svMIL2, an improved version of our Multiple Instance Learning-based method to study the effect of somatic non-coding SVs disrupting boundaries of TADs and CTCF loops in 1646 cancer genomes. We demonstrate that svMIL2 predicts pathogenic non-coding SVs with an average AUC of 0.86 across 12 cancer types, and identifies non-coding SVs affecting well-known driver genes. The disruption of active (super) enhancers in open chromatin regions appears to be a common mechanism by which non-coding SVs exert their pathogenicity. Finally, our results reveal that the contribution of pathogenic non-coding SVs as opposed to driver SNVs may highly vary between cancers, with notably high numbers of genes being disrupted by pathogenic non-coding SVs in ovarian and pancreatic cancer. Taken together, our machine learning method offers a potent way to prioritize putatively pathogenic non-coding SVs and leverage non-coding SVs to identify driver genes. Moreover, our analysis of 1646 cancer genomes demonstrates the importance of including non-coding SVs in cancer diagnostics.

Background Testicular germ cell cancer (TGCC), being the most frequent malignancy in young Caucasian males, is initiated from an embryonic germ cell. This study determines intratumour heterogeneity to unravel tumour progression from initiation until metastasis. Methods In total, 42 purified samples of four treatment-resistant nonseminomatous (NS) TGCC were investigated, including the precursor germ cell neoplasia in situ (GCNIS) and metastatic specimens, using whole-genome and targeted sequencing. Their evolution was reconstructed. Results Intratumour molecular heterogeneity did not correspond to the supposed primary tumour histological evolution. Metastases after systemic treatment could be derived from cancer stem cells not identified in the primary cancer. GCNIS mostly lacked the molecular marks of the primary NS and comprised dominant clones that failed to progress. A BRCA-like mutational signature was observed without evidence for direct involvement of BRCA1 and BRCA2 genes. Conclusions Our data strongly support the hypothesis that NS is initiated by whole-genome duplication, followed by chromosome copy number alterations in the cancer stem cell population, and accumulation of low numbers of somatic mutations, even in therapy-resistant cases. These observations of heterogeneity at all stages of tumourigenesis should be considered when treating patients with GCNIS-only disease, or with clinically overt NS.

Most tumors are composed of a heterogeneous population of subclones. A more detailed insight into the subclonal evolution of these tumors can be helpful to study progression and treatment response. Problematically, tumor samples are typically very heterogeneous, making deconvolving individual tumor subclones a major challenge. To overcome this limitation, reducing heterogeneity, such as by means of microdissections, coupled with targeted sequencing, is a viable approach. However, computational methods that enable reconstruction of the evolutionary relationships require unbiased read depth measurements, which are commonly challenging to obtain in this setting. We introduce TargetClone, a novel method to reconstruct the subclonal evolution tree of tumors from single-nucleotide polymorphism allele frequency and somatic single-nucleotide variant measurements. Furthermore, our method infers copy numbers, alleles and the fraction of the tumor component in each sample. TargetClone was specifically designed for targeted sequencing data obtained from microdissected samples. We demonstrate that our method obtains low error rates on simulated data. Additionally, we show that our method is able to reconstruct expected trees in a testicular germ cell cancer and ovarian cancer dataset. The TargetClone package including tree visualization is written in Python and is publicly available at https://github.com/UMCUGenetics/targetclone.

Background: Testicular germ cell cancer (TGCC), being the most frequent malignancy in young Caucasian males, is initiated from an embryonic germ cell. This study determines intratumor heterogeneity to unravel tumor progression from initiation till metastasis. Methods: In total 42 purified samples of four treatment-resistant nonseminomatous TGCC (NS) were investigated, including the precursor germ cell neoplasia in situ (GCNIS) and metastatic specimens, using whole genome- and targeted sequencing. Their evolution was reconstructed. Results: Intratumor molecular heterogeneity did not correspond to the supposed primary tumor histological evolution. Metastases after systemic treatment could be derived from cancer stem cells not identified in the primary cancer. GCNIS mostly lacked the molecular marks of the primary NS and comprised dominant clones that failed to progress. A BRCA-like mutational signature was observed without evidence for direct involvement of BRCA1 and BRCA2 genes. Conclusions: Our data strongly support the hypothesis that NS is initiated by whole genome duplication, followed by chromosome copy number alterations in the cancer stem cell population, and accumulation of low numbers of somatic mutations. These observations of heterogeneity at all stages of tumorigenesis should be considered when treating patients with GCNIS-only disease, or with clinically overt NS. Footnotes * Text, Figure 2, Figure 3, Supplemental Figures and Supplemental Tables S7 and S8 were updated

Regular physical activity (PA) is associated with improved overall survival (OS) in stage I–III colorectal cancer (CRC) patients. This association is less defined in patients with metastatic CRC (mCRC). We therefore conducted a study in mCRC patients participating in the Prospective Dutch Colorectal Cancer cohort. PA was assessed with the validated SQUASH questionnaire, filled-in within a maximum of 60 days after diagnosis of mCRC. PA was quantified by calculating Metabolic Equivalent Task (MET) hours per week. American College of Sports and Medicine (ACSM) PA guideline adherence, tertiles of moderate to vigorous PA (MVPA), and sport and leisure time MVPA (MVPA-SL) were assessed as well. Vital status was obtained from the municipal population registry. Cox proportional-hazards models were used to study the association between PA determinants and all-cause mortality adjusted for prognostic patient and treatment-related factors. In total, 293 mCRC patients (mean age 62.9 ± 10.6 years, 67% male) were included in the analysis. Compared to low levels, moderate and high levels of MET-hours were significantly associated with longer OS (fully adjusted hazard ratios: 0.491, (95% CI 0.299–0.807, p value = 0.005) and 0.485 (95% CI 0.303–0.778, p value = 0.003), respectively), as were high levels of MVPA (0.476 (95% CI 0.278–0.816, p value = 0.007)) and MVPA-SL (0.389 (95% CI 0.224–0.677, p value < 0.001)), and adherence to ACSM PA guidelines compared to non-adherence (0.629 (95% CI 0.412–0.961, p value = 0.032)). The present study provides evidence that higher PA levels at diagnosis of mCRC are associated with longer OS.