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• Whole-genome plasma sequencing reveals focal amplifications as a driving force in metastatic prostate cancer

  Genomic alterations in metastatic prostate cancer remain incompletely characterized. Here we analyze 493 prostate cancer cases from the TCGA database and perform whole-genome plasma sequencing on 95 plasma samples derived from 43 patients with metastatic prostate cancer. From these samples, we identify established driver aberrations in a cancer-related gene in nearly all cases (97.7%), including driver gene fusions (TMPRSS2:ERG), driver focal deletions (PTEN, RYBP, SHQ1), and driver amplifications (AR, MYC). In serial plasma analyses, we observe changes in focal amplifications in 40% of cases. The mean time interval between new amplifications was 26.4 weeks (range: 5-52 weeks), suggesting that they represent rapid adaptations to selection pressure. An increase in neuron-specific enolase is accompanied by clonal pattern changes in the tumor genome, most consistent with subclonal diversification of the tumor. Our findings suggest a high plasticity of prostate cancer genomes with newly occurring focal amplifications as a driving force in progression

  Study EGAS00001001018

• A comprehensive assessment of somatic mutation detection in cancer using whole genome sequencing

  As whole genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Using tumor-normal sample pairs from two different types of cancer, chronic lymphocytic leukemia and medulloblastoma, we conducted a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines, and even validation methods. Here we show that using PCR-free methods and increasing sequencing depth to ~100x showed benefits, as long as the tumor:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artifact-prone nature of the raw data and lack of standards for dealing with the artifacts. However, armed with the benchmark mutation set we have created, we show that many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy.

  Study EGAS00001001539

• A comprehensive characterization of the cell-free transcriptome reveals tissue- and subtype-specific biomarkers for cancer detection

  Cell-free RNA (cfRNA) is a promising analyte for cancer detection. However, a comprehensive assessment of cfRNA in individuals with and without cancer has not been conducted. We performed the first transcriptome-wide characterization of cfRNA in cancer (stage III breast [n=46], lung [n=30]) and non-cancer (n=89) participants from the Circulating Cell-free Genome Atlas (NCT02889978). Of 57,820 annotated genes, 39,564 (68%) were not detected in cfRNA from non-cancer individuals. Within these low-noise regions, we identified tissue- and cancer-specific genes, defined as "dark channel biomarker" (DCB) genes, that were recurrently detected in individuals with cancer. DCB levels in plasma were correlated with tumor shedding rate and RNA expression in matched tissue, suggesting that DCBs with high expression in tumor tissue could enhance cancer detection in patients with low levels of circulating tumor DNA. Overall, cfRNA provides a unique opportunity to detect cancer, predict the tumor tissue of origin, and determine the cancer subtype.

  Study EGAS00001004704

• A cycling, progenitor-like cell population at the root of atypical teratoid rhabdoid tumor subtype differentiation trajectories.

  Background: Atypical teratoid rhabdoid tumors (ATRTs), characterized by the loss of SMARCB1, are among the most lethal pediatric central nervous system (CNS) tumors. Three molecular subtypes have been identified, each defined by distinct molecular and clinical features. No subtype-specific treatments are available, highlighting the necessity to better understand inter- and intra-subtype heterogeneity. Methods: We generated a single-nucleus transcriptome atlas of ATRTs, validated by single-cell ATAC-seq and spatial transcriptomics, to study subtype-specific differentiation trajectories. Results: We identified brain progenitor-like expression profiles within unique subtype-specific differentiation lineages. A shared cycling, progenitor-like cell population, interspersed throughout tumors, was observed across all ATRT samples. Moreover, we demonstrate that subtype-specific differentiation trajectories can be induced pharmacologically in ATRT tumoroids directing tumor cells towards a non-proliferative, mature phenotype. Conclusions: Our study reveals that ATRT subtypes exhibit signaling trajectories mirroring normal fetal brain development, enabling the development of maturation therapies tailored towards ATRTs.

  Study EGAS00001008108

• Somatic mutation and selection at epidemiological scale - TwinsUK_ExomeNanoSeq_Buccal

  Exome NanoSeq in buccal swab samples obtained from patients with a wide range of clinical phenotypes. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015620

• Polyclonal selection of immune checkpoint mutations in thyroid autoimmunity - ExomeNanoSeq

  Our immune system contains multiple tolerance checkpoints to prevent the activation of self-reactive lymphocytes. How some lymphocytes escape these constraints to cause autoimmune disease remains poorly understood. A long-standing hypothesis in autoimmunity posits that somatic mutations in immune regulatory genes may enable self-reactive lymphocytes to bypass tolerance checkpoints. However, testing this hypothesis has proved challenging due to technical limitations in detecting somatic mutations in polyclonal cell populations. Here, we use deep whole-exome and targeted NanoSeq, a highly accurate single-molecule DNA sequencing protocol, to comprehensively search for driver mutations in autoimmune thyroid disease. This revealed a remarkably high number of B cell clones convergently acquiring loss-of-function somatic mutations in key immune checkpoint genes TNFRSF14 (also known as HVEM) and CD274 (encoding PD-L1), as well as less frequent driver mutations in a diversity of other immune genes. In highly inflamed biopsies, we detected tens to hundreds of independent immune-checkpoint mutant clones. Laser capture microdissection, methylation sequencing, spatial transcriptomics, immunohistochemistry and single-nucleus DNA sequencing localised these mutations to non-naive B cells and revealed frequent co-occurrence of drivers in single cells. We found widespread TNFRSF14 biallelic loss in mutant B cells, and several clones with as many as 4-6 driver mutations. Whilst each clone accounts for a small proportion of cells (typically <1%), the myriad mutant clones in each donor collectively amounted to a substantial fraction of B cells harbouring one or more driver mutations. Our results support the hypothesis that somatic mutations in autoimmune lymphocytes may allow them to escape tolerance constraints through a polyclonal cascade of somatic evolution. These findings provide new insights into the molecular basis of autoimmune disease and suggest novel diagnostic and therapeutic avenues.

  Dataset EGAD00001016058

• Polyclonal selection of immune checkpoint mutations in thyroid autoimmunity - PTA_DNAHyb

  Our immune system contains multiple tolerance checkpoints to prevent the activation of self-reactive lymphocytes. How some lymphocytes escape these constraints to cause autoimmune disease remains poorly understood. A long-standing hypothesis in autoimmunity posits that somatic mutations in immune regulatory genes may enable self-reactive lymphocytes to bypass tolerance checkpoints. However, testing this hypothesis has proved challenging due to technical limitations in detecting somatic mutations in polyclonal cell populations. Here, we use deep whole-exome and targeted NanoSeq, a highly accurate single-molecule DNA sequencing protocol, to comprehensively search for driver mutations in autoimmune thyroid disease. This revealed a remarkably high number of B cell clones convergently acquiring loss-of-function somatic mutations in key immune checkpoint genes TNFRSF14 (also known as HVEM) and CD274 (encoding PD-L1), as well as less frequent driver mutations in a diversity of other immune genes. In highly inflamed biopsies, we detected tens to hundreds of independent immune-checkpoint mutant clones. Laser capture microdissection, methylation sequencing, spatial transcriptomics, immunohistochemistry and single-nucleus DNA sequencing localised these mutations to non-naive B cells and revealed frequent co-occurrence of drivers in single cells. We found widespread TNFRSF14 biallelic loss in mutant B cells, and several clones with as many as 4-6 driver mutations. Whilst each clone accounts for a small proportion of cells (typically <1%), the myriad mutant clones in each donor collectively amounted to a substantial fraction of B cells harbouring one or more driver mutations. Our results support the hypothesis that somatic mutations in autoimmune lymphocytes may allow them to escape tolerance constraints through a polyclonal cascade of somatic evolution. These findings provide new insights into the molecular basis of autoimmune disease and suggest novel diagnostic and therapeutic avenues.

  Dataset EGAD00001016062

• Polyclonal selection of immune checkpoint mutations in thyroid autoimmunity - LCMB_WGS

  Our immune system contains multiple tolerance checkpoints to prevent the activation of self-reactive lymphocytes. How some lymphocytes escape these constraints to cause autoimmune disease remains poorly understood. A long-standing hypothesis in autoimmunity posits that somatic mutations in immune regulatory genes may enable self-reactive lymphocytes to bypass tolerance checkpoints. However, testing this hypothesis has proved challenging due to technical limitations in detecting somatic mutations in polyclonal cell populations. Here, we use deep whole-exome and targeted NanoSeq, a highly accurate single-molecule DNA sequencing protocol, to comprehensively search for driver mutations in autoimmune thyroid disease. This revealed a remarkably high number of B cell clones convergently acquiring loss-of-function somatic mutations in key immune checkpoint genes TNFRSF14 (also known as HVEM) and CD274 (encoding PD-L1), as well as less frequent driver mutations in a diversity of other immune genes. In highly inflamed biopsies, we detected tens to hundreds of independent immune-checkpoint mutant clones. Laser capture microdissection, methylation sequencing, spatial transcriptomics, immunohistochemistry and single-nucleus DNA sequencing localised these mutations to non-naive B cells and revealed frequent co-occurrence of drivers in single cells. We found widespread TNFRSF14 biallelic loss in mutant B cells, and several clones with as many as 4-6 driver mutations. Whilst each clone accounts for a small proportion of cells (typically <1%), the myriad mutant clones in each donor collectively amounted to a substantial fraction of B cells harbouring one or more driver mutations. Our results support the hypothesis that somatic mutations in autoimmune lymphocytes may allow them to escape tolerance constraints through a polyclonal cascade of somatic evolution. These findings provide new insights into the molecular basis of autoimmune disease and suggest novel diagnostic and therapeutic avenues.

  Dataset EGAD00001016064

• Polyclonal selection of immune checkpoint mutations in thyroid autoimmunity - TargetedNanoSeq

  Our immune system contains multiple tolerance checkpoints to prevent the activation of self-reactive lymphocytes. How some lymphocytes escape these constraints to cause autoimmune disease remains poorly understood. A long-standing hypothesis in autoimmunity posits that somatic mutations in immune regulatory genes may enable self-reactive lymphocytes to bypass tolerance checkpoints. However, testing this hypothesis has proved challenging due to technical limitations in detecting somatic mutations in polyclonal cell populations. Here, we use deep whole-exome and targeted NanoSeq, a highly accurate single-molecule DNA sequencing protocol, to comprehensively search for driver mutations in autoimmune thyroid disease. This revealed a remarkably high number of B cell clones convergently acquiring loss-of-function somatic mutations in key immune checkpoint genes TNFRSF14 (also known as HVEM) and CD274 (encoding PD-L1), as well as less frequent driver mutations in a diversity of other immune genes. In highly inflamed biopsies, we detected tens to hundreds of independent immune-checkpoint mutant clones. Laser capture microdissection, methylation sequencing, spatial transcriptomics, immunohistochemistry and single-nucleus DNA sequencing localised these mutations to non-naive B cells and revealed frequent co-occurrence of drivers in single cells. We found widespread TNFRSF14 biallelic loss in mutant B cells, and several clones with as many as 4-6 driver mutations. Whilst each clone accounts for a small proportion of cells (typically <1%), the myriad mutant clones in each donor collectively amounted to a substantial fraction of B cells harbouring one or more driver mutations. Our results support the hypothesis that somatic mutations in autoimmune lymphocytes may allow them to escape tolerance constraints through a polyclonal cascade of somatic evolution. These findings provide new insights into the molecular basis of autoimmune disease and suggest novel diagnostic and therapeutic avenues.

  Dataset EGAD00001016059

• Polyclonal selection of immune checkpoint mutations in thyroid autoimmunity - TargetedEMSeq

  Our immune system contains multiple tolerance checkpoints to prevent the activation of self-reactive lymphocytes. How some lymphocytes escape these constraints to cause autoimmune disease remains poorly understood. A long-standing hypothesis in autoimmunity posits that somatic mutations in immune regulatory genes may enable self-reactive lymphocytes to bypass tolerance checkpoints. However, testing this hypothesis has proved challenging due to technical limitations in detecting somatic mutations in polyclonal cell populations. Here, we use deep whole-exome and targeted NanoSeq, a highly accurate single-molecule DNA sequencing protocol, to comprehensively search for driver mutations in autoimmune thyroid disease. This revealed a remarkably high number of B cell clones convergently acquiring loss-of-function somatic mutations in key immune checkpoint genes TNFRSF14 (also known as HVEM) and CD274 (encoding PD-L1), as well as less frequent driver mutations in a diversity of other immune genes. In highly inflamed biopsies, we detected tens to hundreds of independent immune-checkpoint mutant clones. Laser capture microdissection, methylation sequencing, spatial transcriptomics, immunohistochemistry and single-nucleus DNA sequencing localised these mutations to non-naive B cells and revealed frequent co-occurrence of drivers in single cells. We found widespread TNFRSF14 biallelic loss in mutant B cells, and several clones with as many as 4-6 driver mutations. Whilst each clone accounts for a small proportion of cells (typically <1%), the myriad mutant clones in each donor collectively amounted to a substantial fraction of B cells harbouring one or more driver mutations. Our results support the hypothesis that somatic mutations in autoimmune lymphocytes may allow them to escape tolerance constraints through a polyclonal cascade of somatic evolution. These findings provide new insights into the molecular basis of autoimmune disease and suggest novel diagnostic and therapeutic avenues.

  Dataset EGAD00001016060