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• Landscape of somatic mutations and clonal evolution in mantle cell lymphoma

  Mantle cell lymphoma (MCL) is an aggressive tumor, but a subset of patients may follow an indolent clinical course. To understand the mechanisms underlying this biological heterogeneity, we performed whole-genome and/or whole-exome sequencing on 29 MCL cases and their respective matched normal DNA, as well as 6 MCL cell lines. Recurrently mutated genes were investigated by targeted sequencing in an independent cohort of 172 MCL patients. We identified 25 significantly mutated genes, including known drivers such as ataxia-telangectasia mutated (ATM), cyclin D1 (CCND1), and the tumor suppressor TP53; mutated genes encoding the anti-apoptotic protein BIRC3 and Toll-like receptor 2 (TLR2); and the chromatin modifiers WHSC1, MLL2, and MEF2B. We also found NOTCH2 mutations as an alternative phenomenon to NOTCH1 mutations in aggressive tumors with a dismal prognosis. Analysis of two simultaneous or subsequent MCL samples by whole-genome/whole-exome (n = 8) or targeted (n = 19) sequencing revealed subclonal heterogeneity at diagnosis in samples from different topographic sites and modulation of the initial mutational profile at the progression of the disease. Some mutations were predominantly clonal or subclonal, indicating an early or late event in tumor evolution, respectively. Our study identifies molecular mechanisms contributing to MCL pathogenesis and offers potential targets for therapeutic intervention.

  Study EGAS00001000510

• Mutational signatures of aflatoxin

  Aflatoxin B1 (AFB1) is a mutagen and IARC (International Agency for Research on Cancer) Group 1 carcinogen that causes hepatocellular carcinoma (HCC). Here we present the first whole genome data on the mutational signatures of AFB1 exposure from a total of > 40,000 mutations in four experimental systems: two different human cell lines, and in liver tumors in wild-type mice and in mice that carried a hepatitis B surface antigen transgene – this to model the multiplicative effects of aflatoxin exposure and hepatitis B in causing HCC. AFB1 mutational signatures from all four experimental systems were remarkably similar. We integrated the experimental mutational signatures with data from newly-sequenced HCCs from Qidong County, China, a region of well-studied aflatoxin exposure. This indicated that COSMIC mutational signature 24, previously hypothesized to stem from aflatoxin exposure, indeed likely represents AFB1 exposure, possibly combined with other exposures. Among published somatic mutation data, we found evidence of AFB1 exposure in 0.7% of HCCs treated in North America, 1% of HCCs from Japan, but 16% of HCCs from Hong Kong. Thus, aflatoxin exposure apparently remains a substantial public health issue in some areas. This aspect of our study exemplifies the promise of future widespread resequencing of tumor genomes in providing new insights into the contribution of mutagenic exposures to cancer incidence.

  Study EGAS00001002490

• Exon4-mutations in KRAS Affect MEK-ERK and Pi3K-AKT Signaling in Multiple Myeloma

  Approximately 40% of MM cases harbor a point mutation in either KRAS or NRAS. However, it is still unclear whether RAS-mutations are associated with disease outcome. Specifically, no information exists whether KRAS-mutations have an impact on survival in MM patients at diagnosis that were treated with novel agents (e.g. bortezomib, lenalidomide). Targeting KRAS directly for therapeutic purposes is still impossible, but recently the first covalent mutant-specific inhibitor targeting KRASG12C made it into clinical trials. However, other KRAS-hotspot-mutations exist in MM patients, including the less common exon4-mutations. Within the current study, the coding regions of KRAS in 80 MM patients at diagnosis, uniformly treated with bortezomib and high-dose chemotherapy, were deep-sequenced. Moreover, the functional impact of KRASG12A as well as the two exon4-mutations A146T (AMO1) and A146V (MM patient) on different survival pathways was investigated. Specifically, an siRNA-mediated knockdown in AMO1 was performed and KRASWT, KRASG12A, KRAS146T and KRAS146V were overexpressed in the KRASWT cell lines JJN3 and OPM2 using lentiviral transduction and the transposase based Sleeping Beauty system. KRAS-mutations were not associated with survival. Yet, the expression of all KRAS-mutants had an impact on MEK/ERK-signaling in two independent MM cell lines and on AKT/PI3K-signaling in one MM cell line.

  Study EGAS00001004110

• Comprehensive Genomic Characterization of Gene Therapy-Induced T-cell Acute Lymphoblastic Leukemia (H007)

  Six out of ten patients in a hematopoietic stem cell gene therapy (GT) trial for Wiskott-Aldrich syndrome (WAS) developed T-cell acute lymphoblastic leukemia (T-ALL) associated with gamma-retroviral vector integration at the LMO2 locus. We hypothesized that detailed molecular analysis of T-ALL driven by temporally defined first deregulation of LMO2 might offer valuable insights into the pathogenesis of GT-associated and sporadic T-ALL (HIPO project 007). In all six patients whole-genome and transcriptome sequencing demonstrated that in addition to oncogenic chromosomal translocations involving the T-cell receptor loci, retrovirally induced leukemias faithfully recapitulated secondary genomic events observed in sporadic T-ALL. Multiple genetic events culminated in the development of a rapidly proliferating leukemic clone and onset of clinical manifestation at 1.3 to 5 years after infusion of the gene corrected transplant. These genetic alterations affected NOTCH1 and PI3K signaling, cell cycle regulation as wells as T-cell transcription factors LEF1 and TCF1. Two of the six cases displayed a phenotype reminiscent of early immature T-ALLs, and lacked additional T-ALL typical alterations. Our analysis shows that insertional mutagenesis involving the LMO2 locus triggers T-ALL development due to diverse genetic alterations in large parts, but not exclusively, in known T-ALL driver genes, demonstrating the molecular diversity of GT-associated T-ALL.

  Study EGAS00001003870

• Intratumoural heterogeneity and immune modulation in lung adenocarcinoma of female smokers and never smokers

  Lung cancer is still the leading cause of cancer death worldwide despite declining smoking prevalence in industrialised countries. Although lung cancer is highly associated with smoking status, a significant proportion of lung cancer cases develop in patients who never smoked, with an observable bias towards female never smokers. A better understanding of lung cancer heterogeneity and immune system involvement during tumour evolution and progression in never smokers is therefore highly warranted. We employed single nucleus transcriptomics of surgical lung adenocarcinoma (LADC) and normal lung tissue samples from patients with or without smoking history. Immune cells as well as fibroblasts and endothelial cells respond to tobacco smoke exposure by inducing a highly inflammatory state in normal lung tissue. In the presence of LADC, we identified differentially expressed transcriptional programmes in macrophages and cancer-associated fibroblasts, providing insight into how the niche favours tumour progression. Within tumours, we distinguished eight subpopulations of neoplastic cells in female smokers and never smokers. Through pseudotemporal ordering, we inferred a trajectory towards two differentiated tumour cell states implicated in cancer progression and invasiveness. A proliferating cell population sustaining tumour growth exhibits differential immune modulating signatures in both patient groups. Our results resolve cellular heterogeneity and immune interactions in LADC, with a special emphasis on female never smokers and implications for the design of therapeutic approaches.

  Study EGAS00001006331

• 5- FU treated organoids

  5-Fluorouracil (5-FU) is a chemotherapeutic drug component that is commonly used for the treatment of solid cancers. The anticancer properties of 5-FU have been attributed to interference with nucleotide synthesis and through direct incorporation into the DNA as being a pyrimidine analog. As both mechanisms of action may have a mutational impact on surviving tumor cells, we performed three independent analyses to characterize the genomic consequences of 5-FU treatment: i) in vitro treatment of intestinal organoids with 5-FU followed by whole genome sequencing, ii) genome-wide mutation analyses in tumor samples from 5-FU treated patients with breast or colorectal cancer, and iii) analysis of paired biopsies from patients treated with 5-FU between biopsies. Our results demonstrate that both in vitro and in vivo 5-FU causes a mutational pattern that is dominated by T>G substitutions in a CTT context and with strong resemblance to COSMIC signature 17. Interestingly, this signature is also found in non 5-FU treated patients, most prominently in esophageal tumors, indicating that distinct endogenous and exogenous triggers can converge into highly similar mutational signatures. Furthermore, our results suggest that 5-FU may have adverse mutagenic effects on healthy cells and contributes to genetic variability in surviving cancer cells thereby contributing to tumor evolution.

  Study EGAS00001003592

• Genetic insights into the biological mechanisms governing human ovarian ageing

  Reproductive longevity is critical for fertility and impacts healthy ageing in women, yet insights into the underlying biological mechanisms and treatments to preserve it are limited. Here, we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in ~200,000 women of European ancestry. These common alleles influence clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations. Identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increase fertility and extend reproductive life in mice. Causal inference analyses using the identified genetic variants indicates that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases risks of hormone-sensitive cancers. These findings provide insight into the mechanisms governing ovarian ageing, when they act across the life-course, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

  Study EGAS00001004947

• Loss of LGR4/GPR48 causes severe neonatal salt-wasting due to disrupted WNT signaling altering adrenal zonation

  Disorders of isolated mineralocorticoid deficiency causing potentially life-threatening salt-wasting crisis early in life have been associated with gene variants of aldosterone biosynthesis or resistance, but in some patients no such variants are found. WNT/β-catenin signaling is crucial for differentiation and maintenance of the aldosterone producing adrenal zona glomerulosa (zG). We describe a highly consanguineous family with multiple perinatal deaths or infants presenting at birth with failure to thrive, severe salt-wasting crises associated with isolated hypoaldosteronism, nail anomalies, short stature, and deafness. Whole exome sequencing revealed a homozygous splice variant in the R-SPONDIN receptor LGR4 gene (c.618-1G>C) regulating WNT signaling. The resulting transcripts affected protein function and stability, and resulted in loss of Wnt/β-catenin signaling in vitro. The impact of LGR4 inactivation was analyzed by adrenal cortex specific ablation of Lgr4, using Lgr4Flox/Flox mated with Sf1:Cre mice. Inactivation of Lgr4 within the adrenal cortex in the mouse model caused decreased WNT signaling, aberrant zonation with deficient zG and reduced aldosterone production. Thus, human LGR4 mutations establish a direct link between LGR4 inactivation and decreased canonical WNT signaling with abnormal zG differentiation and endocrine function. Therefore, variants in WNT signaling and its regulators should systematically be considered in familial hyperreninemic hypoaldosteronism.

  Study EGAS00001006808

• CYP2C19 long-read sequencing

  Inter-individual differences in drug response based on genetic variations can lead to drug toxicity and treatment inefficacy. A large part of this variability is caused by genetic variants in pharmacogenes. Unfortunately, the Single Nucleotide Variant (SNV) panels currently used in clinical pharmacogenomic (PGx) testing are unable to detect all genetic variability in these genes. Long-read sequencing, on the other hand, has been shown to be able to resolve complex (pharmaco)genes. In this study we have assessed the added value of long-read sequencing for PGx focusing on the clinically important and highly polymorphic CYP2C19 gene. With a capture-based long-read sequencing panel we were able to characterize the entire region and assign variants to their allele of origin (phasing), resulting in the identification of 813 unique variants in 37 samples. To assess the clinical utility of this data we have compared the performance of three different *-allele tools (Aldy, PharmCat and PharmaKU) which are specifically designed to assign clinical haplotypes to pharmacogenes based on all input variants. We conclude that long-read sequencing can improve our ability to characterize the CYP2C19 locus, help to identify novel haplotypes and that *-allele tools are an useful asset in phenotype prediction. Ultimately, this approach could help to better predict an individual’s drug response and improve therapy outcomes.

  Study EGAS00001006929

• BMP4 and temozolomide synergize in the majority of patient derived glioblastoma cultures

  The poor prognosis of patients with glioblastoma is partly due to resistance to standard treatment, which combines chemoradiation using temozolomide (TMZ). The concept of cancer stem cells provided new insight into tumor resistance and management, and isolated Glioblastoma stem-like cells (GSCs) which contribute to this therapy resistance. Bone morphogenetic protein 4 (BMP4) is a differentiation factor that stimulates astroglial differentiation of such GSCs, thereby reducing their self-renewal. Exposing GSCs to BMP4 could therefore sensitize them to chemotherapy with TMZ, but previous studies with various treatment paradigms have produced contradictory results in this matter. Therefore, we re-defined the optimal treatment paradigm for the combination of TMZ and BMP4 and subsequently re-assessed the inter-tumoral variability in response to co-treatment with TMZ+BMP4 in vitro. First, the simultaneous treatment was found more effective than sequential therapy. Second, after application of our optimized treatment protocol, 70% of a total of 20 patient-derived glioblastoma cultures showed synergy when the treatments were combined. The synergistic effect was a result of increased cellular apoptosis and not of decreased proliferation. Comparative RNA-sequencing suggested that combination treatment results in decreased MAPK signaling. We conclude that addition of BMP4 to standard therapy with TMZ could enlarge the group of patients with good therapeutic response.

  Study EGAS00001007095

• What is metadata?

  What is metadata? Data represents units of information and metadata can be seen, simply put, as data about other data. For example, in a simple experiment in which a patient genome was sequenced, there are multiple and diverse fields of metadata: from the biological sex of the patient to the sequencing platform used. Another way to understand metadata, following our genomic experiment example, is going through the different layers of (meta)data: One of the basic units of information (data) would be the sequence of nucleotides (e.g. GCTGG and GCCGG). This DNA sequence can be contextualised within a chromosome by providing its locus (e.g. β-globin gene). This data, the locus, is about other data, the sequence of nucleotides, which would render it metadata. We can go one step further, and provide more context, by giving the associated phenotype of each of these sequences: GCTGG corresponds to a healthy individual, while GCCGG corresponds to a person with β-thalassaemia. Once again, this data is contextualising the data we have provided up to this point, which makes it metadata. With this simple example, what we are doing is adding layers of data that describe the ones below. Had we given the sequences alone, little would be possible from the researchers' point of view. But, now that the data has its accompanying metadata, a researcher could compare both sequences and their phenotypes to infer a possible cause of the disorder. Each layer of information broadens the possible applications of the data. Now that we know what metadata is, it is time to emphasise the importance of submitting good quality metadata. The quality of the metadata will determine whether the data is usable, discoverable, and interpretable by researchers and clinicians. One example that highlights the importance of good quality metadata is the description of biological sex of a patient: while the terms "female," "girl," or "woman" all represent the same concept, they are not harmonised. These different representations of a concept can create confusion and errors in data analysis. By applying standard definitions and terminologies to biological sex metadata, we can avoid misunderstandings and facilitate the integration of different datasets.  In order to comply with the FAIR principles and, more specifically, to allow for the (meta)data to be interoperable (i.e. used universally and unambiguously), we need to place some standards onto the (meta)data EGA  archives. These can be as simple as asserting that the given patient's biological sex is one of the correct terms (e.g. female or male); or as complex as multiple layers and combinations of validation steps with existing records. You can find further details on how EGA manages these standards on our metadata model page.

  Documentation submission/metadata/what-is-metadata

• Target gene sequencing for human normal endometrial glands

  The raw fastq files target sequencing of 112 genes for 1,298 endometrial glands and matched blood samples. The paired-end sequencing data sets (R1 and R2) are deposited. ABCC1, ACRC, ANK3, ARHGAP35, ARID1A, ARID5B, ATCAY, ATM, ATR, BARD1, BCOR, BRCA1, BRCA2, BRD4, BRIP1, CAMTA1, CDC23, CDYL, CFAP54, CHD4, CHEK1, CHEK2, CTCF, CTNNB1, CUX1, DGKA, DISP2, DYNC2H1, EMSY, FAAP24, FAM135B, FAM175A, FAM65C, FANCA, FANCB, FANCC, FANCD2, FANCE, FANCF, FANCG, FANCI, FANCL, FANCM, FAT1, FAT3, FBN2, FBXW7, FGFR2, FRG1, GPR50, HEATR1, HIST1H4B, HNRNPCL1, HOOK3, KIAA1109, KIF26A, KMT2B, KMT2C, KRAS, LAMA2, LRP1B, MLH1, MON2, MRE11A, MSH2, MSH6, MTOR, NBN, PALB2, PHEX, PIK3CA, PIK3R1, PLXNB2, PLXND1, PMS2, POLE, POLR3B, PPP2R1A, PTEN, PTPN13, RAD50, RAD51, RAD51B, RAD51C, RAD51D, RAD52, RAD54B, RAD54L, RICTOR, SACS, SIGLEC9, SLC19A1, SLX4, SPEG, STT3A, TAF1, TAF2, TAS2R31, TFAP2C, TNC, TONSL, TP53, TTC6, UBA7, VNN1, WT1, XIRP2, ZBED6, ZC3H13, ZFHX3, ZFHX4, ZMYM4.

  Dataset EGAD00001008465

• 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 - 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

• Polyclonal selection of immune checkpoint mutations in thyroid autoimmunity - PTA_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 EGAD00001016061

• 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 - PTA_RNA

  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 EGAD00001016063

• 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 - LCMB_WES

  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 EGAD00001016065

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Oesophageal_adenocarcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003702

• The double-hit signature identifies double-hit diffuse large B-cell lymphoma with genetic events cryptic to FISH​

  High-grade B-cell lymphomas with MYC and BCL2 and/or BCL6 rearrangements (HGBL-DH/THs) include a group of diffuse large B-cell lymphomas (DLBCLs) with inferior outcomes after standard chemoimmunotherapy. We recently described a gene expression signature that identifies 27% of germinal center B-cell DLBCLs (GCB-DLBCLs) as having a double-hit-like expression pattern (DHITsig) and inferior outcomes; however, only half of these cases have both MYC and BCL2 translocations identifiable using standard breakapart fluorescence in situ hybridization (FISH). Here, 20 DHITsig+ GCB-DLBCLs apparently lacking MYC and/or BCL2 rearrangements underwent whole-genome sequencing. This revealed 6 tumors with MYC or BCL2 rearrangements that were cryptic to breakapart FISH. Copy-number analysis identified 3 tumors with MYC and 6 tumors with MIR17HG gains or amplifications, both of which may contribute to dysregulation of MYC and its downstream pathways. Focal deletions of the PVT1 promoter were observed exclusively among DHITsig+ tumors lacking MYC translocations; this may also contribute to MYC overexpression. These results highlight that FISH fails to identify all HGBL-DH/THs, while revealing a range of other genetic mechanisms potentially underlying MYC dysregulation in DHITsig+ DLBCL, suggesting that gene expression profiling is more sensitive for identifying the biology underlying poor outcomes in GCB-DLBCL.

  Study EGAS00001004285

• DKFZ-HIPO Data Access Committee of Heidelberg Center for Personalized Oncology

  Dac EGAC00001000452

• Genomic Characterization of Patient-Derived Xenograft Models to Improve Targeted Therapy for HER2+ Breast Cancer Brain Metastases Treatments

  We have developed orthotopic patient-derived xenograft models of HER2 positive breast cancer metastasized into the brain of patients to test novel therapeutic strategies. In this study, we identified a novel combinatorial therapeutic strategy that has resulted in a durable remission and markedly increased overall survival in majority of patient-derived xenograft (PDX) models tested. We performed whole exome sequencing analysis of these PDX tumors and their matched blood and patient samples to investigate drug sensitive and resistance mechanisms. Our sequencing data revealed an interesting association of genotyping and phenotyping with tumors responses to drug treatment.

  Study phs001063

• A whole-genome sequencing study for evolutionary history of Tibetans and their genetic adaptations to high altitude

  Due to a unique adaptation to high altitude, the Tibetan Plateau population has been the subject of much research interest. In this study, we conducted whole genome sequencing of 27 Tibetan individuals. Through our analysis, we inferred a detailed history of demography and revealed the natural selection of Tibetan population. We provided evidence of genetic separation between the two subpopulations of Han and Tibetans as early as 44 to 58 thousand years ago, replicated previously reported high altitude adaptation genes, including EPAS1 and EGLN1, and reported three new candidate genes, including PTGIS, VDR, and KCTD12.

  Study phs001338