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• RNAseq

  Familial Mediterranean Fever (FMF) is a prototypical periodic fever syndrome caused by genetic variation in MEFV. While it is known that especially IL-1β responses are dysregulated in FMF, its innate immune landscape has not been comprehensively described. Therefore, we extensively characterized the function of monocytes and neutrophils in patients with FMF in between disease attacks, as well as their circulating inflammatory proteome. We found that monocyte IL-1 and IL-6 production was enhanced following a range of stimulations, in concordance with alterations in the plasma inflammatory proteome. In contrast, neutrophil function in FMF was normal. Additionally, ATAC-seq and RNA-seq analyses revealed important epigenetic and transcriptional reprogramming arguing for monocyte function dysregulation. Interestingly, chromatin-accessibility was down-regulated in genomic regions related to cellular responses. This argues that the primary immune dysregulation in monocytes due to MEFV mutations leads to a chronic inflammatory profile that is subsequently associated with counterregulatory epigenetic and transcriptional changes reminiscent of tolerance (rather than trained immunity) induction. These data increase our understanding of the innate immune changes in FMF, that can be used in the design of novel approaches to manage chronic inflammation of these patients.

  Study EGAS00001007165

• Immune and clinicopathological features predict HER2-positive breast cancer prognosis in the neoadjuvant NeoALTTO and CALGB 40601 trials

  The identification of prognostic drivers in patients receiving neoadjuvant therapy is crucial for treatment optimization in HER2-positive breast cancer, with the immune microenvironment being a key factor. Here, we investigated the complexity of B and T cell receptor (BCR and TCR) repertoires, reflecting antigen-specific immune response, in the context of two phase III trials, namely NeoALTTO and CALGB 40601, evaluating neoadjuvant paclitaxel with trastuzumab and/or lapatinib in women affected by HER2-positive breast cancer. BCR/TCR features were heterogeneous, and BCR measures describing clonal expansion demonstrated independent prognostic value. A model developed in NeoALTTO and validated in CALGB 40601 predicted event-free survival (EFS) by integrating hormone receptor and clinical nodal status, treatment response (breast pCR)breast pathological complete response (pCR) as well as tumor-infiltrating lymphocytes and BCR evenness, measuring the equality of BCR clonal distribution. The HER2-EveNT score derived from the model allows the identification of patients with 5-year EFS > 90%, and, in those not achieving pCR, of a subgroup of immune-enriched tumors with an excellent outcome despite residual disease.

  Study EGAS00001007563

• H3Africa - Identification and characterization of novel hereditary neurological disease genes in Mali.

  Despite the vast diversity of its populations, genetic studies in Africa have been limited. African populations, Malians in particular, have a high rate of intra-ethnic and consanguineous marriage, resulting in increased prevalence of autosomal recessive diseases. Family-based genetic studies can be limited in developed countries due to small sibships. The average fertility rate in Mali is over 6 births per woman, offering a unique opportunity to find new disease genes or mutations that can then be studied in other populations. Hereditary neurological diseases are very debilitating diseases, and developing countries, particularly in Africa, pay a high price in terms of disability-adjusted life years. Although most are currently untreatable, increasing awareness about hereditary neurological disorders can reduce this burden. This study will help to identify and characterize novel hereditary neurological disease genes in Mali. These genes are likely to be important in the normal function of the nervous system and to have important pathophysiological implications for African and other populations. This study will also train physicians and students in the characterization of neurodegenerative diseases as well as in genetic technology and molecular biology, and build a suitable research environment that will retain them.

  Study EGAS00001003016

• Genome‐wide postnatal changes in immunity following fetal inflammatory response

  The fetal inflammatory response (FIR) increases the risk of perinatal brain injury, particularly in extremely low gestational age newborns (ELGANs, < 28 weeks of gestation). One of the mechanisms contributing to such a risk is a postnatal intermittent or sustained systemic inflammation (ISSI) following FIR. The link between prenatal and postnatal systemic inflammation is supported by the presence of well‐established inflammatory biomarkers in the umbilical cord and peripheral blood. However, the extent of molecular changes contributing to this association is unknown. Using RNA sequencing and mass spectrometry proteomics, we profiled the transcriptome and proteome of archived neonatal dried blood spot (DBS) specimens from 21 ELGANs. Comparing FIR‐affected and unaffected ELGANs, we identified 782 gene and 27 protein expression changes of 50% magnitude or more, and an experiment‐wide significance level below 5% false discovery rate. These expression changes confirm the robust postnatal activation of the innate immune system in FIR‐affected ELGANs and reveal for the first time an impairment of their adaptive immunity. In turn, the altered pathways provide clues about the molecular mechanisms triggering ISSI after FIR, and the onset of perinatal brain injury.

  Study EGAS00001003635

• 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

• Center for Education and Drug Abuse Research (CEDAR)

  Under its programmatic name, the Center for Education and Drug Abuse research (CEDAR), this Center of Excellence project was completed in 2015. The CEDAR sample consists of 775 nuclear families comprising an adult male (proband), his spouse/mate, and their biological child who is 10-12 years of age at recruitment. This child is designated as index child (IC), and is followed through age 30. Minimal exclusionary criteria were applied to maximize the sample's representativeness. Follow-up evaluations on ICs were conducted at ages 14, 16, 19, 22, 25, 27 and 30. Interim questionnaires were mailed annually beginning at age 20. CEDAR utilizes the family/high-risk paradigm. The offspring thus comprise high average risk (HAR) and low average risk (LAR) groups, constituting the majority of the CEDAR children sample: 250 HAR males, 100 HAR females, 250 LAR males and 94 LAR females. The remainder of the IC sample, 50 males and 31 females, are the offspring of fathers who have a lifetime non-SUD psychiatric dis-order. The follow-up rate from baseline to the final assessment is ~65%. The cohort of children is 76% White and 22% Black. The representation of females among ICs is lower than males, due to the later start of recruit-ment (2nd funding cycle; the study originally focused on males). The CEDAR genetic study has been augmented by the inclusion of its sample into the whole-genome genotyping effort conducted under the Genes, Environment and Development Initiative (GEDI). DNA from the blood samples of target children (index cases) and their siblings submitted to the NIDA Genetics Depository a Rutgers University was obtained and genotyped on Illumina Human660W-Quad Beadchips, with a high average genotyping rate of 99.8%. The sample comprised 158 females and 271 males (37 and 63 %), ~70:30 European- and African- American, with approximately 1:1 ratio of children of affected fathers and normal controls.

  Study phs001649

• Whole Genome Sequencing of Asian Lung Cancers: Second Hand Smoke is Not Responsible for Higher Incidence of Lung Cancer Among Asian Never-Smokers

  Background Asian nonsmoking populations have a higher incidence of lung cancer compared to their European counterparts. There is a long-standing hypothesis that the increase of lung cancer in Asian never-smokers is due to environmental factors such as second-hand smoke. Results We analyzed whole-genome sequencing of 30 Asian lung cancers. Unsupervised clustering of mutational signatures separated the patients into two categories: i) all of the never-smokers, and ii) only smokers or ex-smokers. Half of the ex-smokers / smokers were in the never-smoker-like cluster. The overall somatic variant profiles of Asian lung cancers were similar to that of European origin with G.C>T.A being predominant in smokers. We found EGFR and TP53 are the most frequently mutated genes with mutations in 50% and 27% of individuals, respectively. Among these Asian never-smokers, 71% had an EGFR mutation compared to 20% of the smokers in the smoking cluster. Other frequently mutated genes include RYR2, SATB2, C1orf88, FERMT1 and CTNNB1. Somatic alterations occurred in WNT signaling pathway genes, suggesting this pathway plays a role in both Western and Asian lung cancers. Conclusions Asian never-smokers have lung cancer signatures distinct from the smoker signature and their mutation profiles are similar to that of European never-smokers. The profiles of Asian and European smokers are also similar. This suggests that the same mutational mechanisms underlie the etiology for both ethnic groups, and the high incidence of lung cancer in Asian never-smokers might not be due to second hand smoke or other carcinogens that cause oxidative DNA damage. Half of the ex-smokers/smokers have a molecular phenotype similar to never-smokers; of which, 50% had EGFR mutations. This suggests that routine EGFR testing is warranted in the Asian population, regardless of smoking status.

  Study EGAS00001000621

• Dynamics of multiple resistance mechanisms in plasma DNA and their clinical implications for NSCLC patients receiving EGFR-targeted therapies

  Background:The development of resistance mechanisms to targeted therapies is complicated by underlying tumour heterogeneity. When multiple resistance mechanisms co-exist, identifying the dominant driver(s) is critical for selection of treatment. Patients and methods:We studied the relative dynamics of multiple oncogenic drivers and resistance mechanisms in 50 patients with EGFR-mutant non-small cell lung cancer (NSCLC), during treatment with gefitinib and hydroxychloroquine (NCT00809237). We performed digital PCR and targeted deep sequencing of cell-free DNA from longitudinal plasma samples from all patients, and shallow whole genome sequencing of serial samples from three patients who underwent histological transformation to small-cell lung cancer (SCLC). ResultsEGFR activating mutations were assessed in tumour samples and accurately identified in plasma samples of 95% of patients (41/43). We identified additional mutations including EGFR T790M (31/50, 62%), TP53 (23/50, 46%), PIK3CA (7/50, 14%), and PTEN (4/50, 8%), and tracked their relative levels in plasma. Patients with both TP53 and EGFR mutations detected in plasma pre-treatment tended to have worse overall survival than those where only EGFR was detected. The resistance-conferring EGFR T790M mutation was identified in 62% of the patients who progressed. Changes in relative levels of T790M and activating mutations in EGFR corresponded to clinical responses in two patients who were given sequential treatments. Patients who progressed without T790M detected in plasma had worse PFS during TKI continuation, and developed alternative resistance mechanisms, that could be identified in plasma DNA, including SCLC-associated copy number changes and TP53 mutations, that tracked with progression and response to subsequent therapies. Conclusion:Longitudinal analysis of multiple oncogenic drivers in ctDNA may help identifying dominant mechanisms of resistance to EGFR-targeted therapies, and highlight the importance of monitoring genetic events that are not direct drug targets but provide non-invasive molecular information that may guide clinical management.

  Study EGAS00001002908

• Deep single-cell RNA sequencing data for 11138 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naive CRC patients. The DATA ACCESS AGREEMENT is provided at https://github.com/zhangyybio/single-T-cell-data-access. Applicants can request access to the data by directly downloading it or by sending an email to cancerpku@pku.edu.cn. The process that is used to approve an application includes verifying the institution, participants and research purposes of the application. In general this process will take about two weeks. In principal, any scientific research program complying with the laws and bioethic regulation policies of China will be approved.

  T cells are central players in cancer immunotherapy1, yet some of their fundamental properties such as development and migration within tumours remain elusive. The enormous T cell receptor (TCR) repertoire, required for recognising foreign and self-antigens2,3, could serve as lineage tags to track these T cells in tumours4. Here, we obtained transcriptomes of 11,138 single T cells from 12 colorectal cancer (CRC) patients and developed STARTRAC (Single T-cell Analysis by Rna-seq and Tcr TRACking) indices to quantitatively analyse dynamic relationships among 20 identified T cell subsets with distinct functions and clonalities. While both CD8+ effector and “exhausted” T cells exhibited high clonal expansion, they were independently connected with tumour-resident CD8+ effector memory cells, implicating a TCR-based fate decision. Of the CD4+ T cells, the majority of tumour-infiltrating Tregs showed clonal exclusivity, whereas certain Treg clones were developmentally linked to multiple TH clones. Notably, we identified two IFNG+ TH1-like clusters in tumours, the GZMK+ TEM and CXCL13+ TH1-like clusters, which were associated with distinct IFN-γ-regulating transcription factors, EOMES/RUNX3 and BHLHE40, respectively. Only CXCL13+BHLHE40+ TH1-like cells were preferentially enriched in tumours of microsatellite-instable (MSI) patients, which might explain their favourable response rates to immune-checkpoint blockade. Furthermore, we found IGFLR1 to be highly expressed in both CXCL13+BHLHE40+ TH1-like and CD8+ exhausted T cells and possessed co-stimulatory functions. Our integrated STARTRAC analyses provides a powerful avenue to comprehensively dissect the T cell properties in CRC, which could shed new insights into the dynamic relationships of T cells in other cancers

  Study EGAS00001002791

• A circulating biomarker for severity of facioscapulohumeral muscular dystrophy

  Facioscapulohumeral muscular dystrophy (FSHD) is a prevalent, incurable skeletal myopathy. Clinical trials for FSHD are hindered by heterogeneous biomarkers poorly associated with clinical severity, requiring invasive muscle biopsy. Macroscopically FSHD presents with slow fatty replacement of muscle, rapidly accelerated by inflammation. Mis-expression of the transcription factor DUX4 is currently accepted to underlie FSHD pathogenesis and mechanisms including PAX7 target gene repression have been proposed. Here we perform RNA-sequencing on MRI guided inflamed (n=24) and isogenic non-inflamed (n=24) muscle biopsies from the same clinically characterised FSHD patients, alongside isogenic peripheral blood mononucleated cells from a subset of patients (n=13), and unaffected controls. We employ multivariate models to evaluate the clinical associations of 5 published FSHD transcriptomic biomarkers. We demonstrate that PAX7 target gene repression can discriminate control, inflamed and non-inflamed FSHD muscle independently of age and sex (p<0.013), while the discriminatory power of DUX4 target genes is limited to distinguishing FSHD muscle from control. Importantly, the level of PAX7 target gene repression in non-inflamed muscle associates with clinical assessments of FSHD severity (p=0.04). DUX4 target gene biomarkers in FSHD muscle show associations with lower limb fat fraction and D4Z4 array length, but not clinical assessment. Lastly, PAX7 target gene repression in FSHD muscle correlates with the level in isogenic peripheral blood mononucleated cells (p=0.002). A refined PAX7 target gene biomarker comprising 143/601 PAX7 target genes computed in peripheral blood (the FSHD muscle-blood biomarker) associates with clinical severity in FSHD patients (p<0.036). Our new circulating biomarker validates as a classifier of clinical severity in an independent data set of 54 FSHD patient blood samples, with improved power in older patients (p=0.03). In summary, we present the minimally invasive FSHD muscle-blood biomarker of FSHD clinical severity valid in patient muscle and blood, with potential utility in routine disease monitoring and clinical trials.

  Study EGAS00001007350

• Substantial somatic genomic variation and selection for BCOR mutations in human induced pluripotent stem cells

  Human Induced Pluripotent Stem Cells (hiPSC) are an established patient-specific model system where opportunities are emerging for cell-based therapies. We compared and contrasted hiPSCs derived from different tissues, skin and blood, in the same individual. We show extensive single-nucleotide mutagenesis in all hiPSC lines, although fibroblast-derived hiPSCs (F-hiPSCs) are particularly heavily mutagenized by ultraviolet (UV)-related damage. We utilized genome sequencing data on 454 F-hiPSCs and 44 blood-derived hiPSCs (B-hiPSCs) to gain further insights. Across 324 whole genome sequenced (WGS) F-hiPSCs derived by the Human Induced Pluripotent Stem Cell Initiative (HipSci), UV-related damage is present in ~72% of cell lines, sometimes causing substantial mutagenesis (range 0.25-15 per Mb). Furthermore, we find remarkable genomic heterogeneity between independent F-hiPSC clones derived from the same reprogramming process in the same donor, due to oligoclonal populations within fibroblasts. Combining WGS and exome-sequencing data of 452 HipSci F-hiPSCs, we identify 272 predicted pathogenic mutations in cancer-related genes, of which 21 genes were hit recurrently three or more times, involving 77 (17%) lines. Notably, 151 of 272 mutations were present in starting fibroblast populations suggesting that more than half of putative driver events in F-hiPSCs were acquired in vivo. In contrast, B-hiPSCs reprogrammed from erythroblasts show lower levels of genome-wide mutations (range 0.28-1.4 per Mb), no UV damage, but a strikingly high prevalence of acquired BCOR mutations in ~57% of lines, indicative of strong selection pressure. All hiPSCs had otherwise stable, diploid genomes on karyotypic pre-screening, highlighting how copy-number-based approaches do not have the required resolution to detect widespread nucleotide mutagenesis. This work strongly suggests that models for cell-based therapies require detailed nucleotide-resolution characterization prior to clinical application.

  Dataset EGAD00001007029

• Molecular Signatures of DCIS to Invasive Progression for Basal-Like Breast Cancers: An Integrated Mouse Model and Human Tumor Study

  We studied the genomic signatures of progression in breast ductal carcinoma in situ (DCIS) as it progresses towards triple negative invasive breast cancer (TNBC). Single cell RNA sequencing (scRNAseq) was performed on the C3Tag genetically engineered mouse model that forms human breast-like DCIS and TNBC. Bulk RNA sequencing was performed on RNA harvested from archival formalin-fixed, paraffin embedded (FFPE) pairs comprising of estrogen receptor (ER) positive (ER+) and negative (ER-) subsets of DCIS. 

  Study phs002443

• Human Skin Cancer Atlas, Medical University of Vienna Data Access Policy

  Cancer-associated fibroblasts (CAFs) play a key role in cancer progression and treatment outcome. Here, we elucidate the yet unresolved intra-tumoral CAF variety in three skin cancer types at molecular and spatial single-cell resolution in a large cohort. We show that two out of three CAF subtypes contribute to tumor immune surveillance with distinct mechanisms. Matrix CAFs (mCAFs) ensheath tumor nests and synthesize extracellular-matrix to prevent T cell invasion. Immunomodulatory CAFs (iCAFs), which express proinflammatory and immunomodulatory factors, are only detected in high abundance in aggressive tumors. Strikingly, iCAFs but not tumor cells are (apart from immune cells) the exclusive cell type producing chemokines and, thus, play a key role in immune cell recruitment and activation. Mechanistically, we show that cancer cells transform adjacent healthy fibroblasts into cytokine-expressing iCAFs, which subsequently recruit immune cells and modulate the immune response. In conclusion, targeting CAF variants holds promise for improved efficacy of immunotherapy.

  Dac EGAC50000000154

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  To elucidate the feature of age-associated helper T (ThA) cells and its contribution to autoimmune diseases, various peripheral blood immune cell subsets from 136 systemic lupus erythematosus (SLE) and 89 healthy controls (HC) were collected (Naive_CD4, Th1, Th2, Th17, Tfh, Fr._I_nTreg, Fr._II_eTreg, Fr._III_T, ThA, Naive_CD8, Naive_B, SM_B, USM_B, DN_B, Plasmablast, NK, CD16p_Mono, CL_Mono, Neu, mDC, pDC, TEMRA_CD8, CM_CD8, EM_CD8, NC_Mono, Int_Mono, LDG). RNA-seq was performed with each cell subset samples.

  Study JGAS000627

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  To elucidate the regulation of gene expression in immune cell subsets and its contribution to autoimmune diseases, 24 peripheral blood immune cell subsets from 50 Systemic Sclerosis and 48 Healthy Controls were collected (Naive_CD4, Mem_CD4, Fr._I_nTreg, Fr._II_eTreg, Fr._III_T, Th1, Th2, Th17, Tfh, NK, Naive_CD8, EM_CD8, CM_CD8, TEMRA_CD8, Naive_B, USM_B, SM_B, DN_B, Plasmablast, CL_Mono, Int_Mono, NC_Mono, mDC, pDC). RNA-seq was performed with each immune cell subset samples. After gene expression quantification samples were filtered.

  Study JGAS000296

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  Various peripheral blood immune cell subsets from 89 healthy volunteers and 136 systemic lupus erhythematosus (SLE) donors were collected (Naive_CD4, Mem_CD4, Th1, Th2, Th17, Tfh, Fr._I_nTreg, Fr._II_eTreg, Fr._III_T, Naive_CD8, EM_CD8, CM_CD8, TEMRA_CD8, NK, Naive_B, USM_B, SM_B, DN_B, Plasmablast, CL_Mono (or CD16n_Mono), CD16p_Mono, Int_Mono, NC_Mono, mDC, pDC, Neu, LDG). 22 SLE donors were analyzed longitudinally. RNA-seq was performed with each immune cell subset samples. After gene expression quantification samples were filtered.

  Study JGAS000486

• Identification of therapeutic target molecules for prostate cancer by using next generation sequencer

  Comprehensive transcriptional characterization of cancer tissues can reveal important molecular signatures associated with the disease progression. Long non-coding RNA (LncRNA) has a diversity of functions such as transcription, epigenetic and gene regulation in cancer cells including prostate cancer cells. Here, we performed directional RNA-sequence (RNA-seq) on clinical samples obtained from prostate cancer (PC) and lethal castration-resistant PC (CRPC) patients to identify novel molecular signatures including protein coding genes and non-coding RNAs induced in CRPC tissues.

  Study JGAS000198

• Progressive supranuclear palsy - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=42 samples. Tissue samples correspond to donors with pathologically confirmed progressive supranuclear palsy. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13).

  Dataset EGAD50000002623

• Multiple system atrophy - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=35 samples. Tissue samples correspond to donors with pathologically confirmed multiple system atrophy. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13). N=6 samples are overlapping with EGAS50000000301.

  Dataset EGAD50000002624

• Alzheimer's disease - bulk RNA seq of prefrontal cortex

  Dataset corresponding to the bulk RNA-seq dataset from prefrontal cortex for a total of N=72 samples. Tissue samples correspond to donors with pathologically confirmed Alzheimer's disease. RNA-seq was carried out using ribosomal depletion. Dataset contains paired fastq files, sample metadata and downstream quantification files. Quantification was performed with salmon v1.3.0 with Gencode 35 (GRCh38.p13).

  Dataset EGAD50000002625