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• 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

• Small_molecule_inhibitors_in_melanoma___Kenski___Kong___WES

  Small-molecule inhibitors targeting the most commonly activated pathway in melanoma, MAPK pathway (either alone or in combination) are already given to melanoma patients for few years, and initially reduce tumour burden dramatically, eventually melanomas become resistant and tumours progress while on treatment. Resistance to this treatment occurs by acquisition of additional mutations or other alterations that affect the mitogen-activated protein kinase (MAPK) pathway by either direct or indirect signalling. Many resistance mechanisms somehow lead to reactivation of extracellular signal-regulated kinase (ERK), thereby restoring signalling of the oncogenic BRAF/MEK/ERK pathway. In addition, PI3K pathway activation contributes to resistance to BRAF inhibition. Less frequent but equally important to the phenomenon of targeted drug resistance is the observation that B15–20% of BRAF mutant melanoma patients fail to respond to BRAF inhibition already early on treatment, owing to intrinsic resistance. These patients have little therapeutic options, unless immunotherapy can be given. To better understand the resistance mechanisms in MAPK inhibitor-treated melanoma patients and melanoma biology, our lab generated a big panel of MAPK inhibitor resistant melanoma cell lines by continuous drug exposure. The understanding of the genetic landscape and gene expression as well as cross resistance to other treatment regimens, and other aspects of melanoma biology such as phenotype switch, will allow us to better exploit new therapeutic strategies for melanoma patients.

  Study EGAS00001002863

• scRNA-seq data of human nuclei collected from the temporal cortex of 17 individuals.

  Transcriptome analysis of single cells has tremendously increased our understanding of cellular heterogeneity in complex tissues. However, whole-cell transcriptomics cannot be applied to frozen tissue due to poor cell recovery after freezing. Human tissue is usually limited to tissue banks containing frozen material, and since single nuclei can be readily isolated from frozen tissues, human cell nuclei can substitute whole-cell analysis to extract single cell transcriptomes from human cells. Despite the importance of human tissue analysis, single-nucleus RNA-sequencing protocols are less developed than those for whole cells. SMARTSeq, either in form of custom-made SMARTSeq2 or as part of the Fluidigm C1 platform, provides a high resolution view of the transcriptome, has proven effective for whole-cell analysis and has recently been adapted to nuclei. Here, we show that the standard SMARTSeq2 protocol applied to single nuclei biases the amplification of single-nucleus transcriptomes due to unspecific capturing of transcripts, which can comprise the majority of reads in single-nucleus RNA-sequencing libraries. We demonstrate that modification of the SMARTSeq2 protocol with respect to template switching and cDNA amplification conditions generates sequencing libraries of higher complexity, allows for detection of more genes and reduces biases of the amplified transcriptome. In addition, modification of SMARTSeq2 chemistry allows for gene detection at shallower sequencing depth, thus increasing efficiency and decreasing cost.

  Study EGAS00001002882

• Deep multi-region whole-genome sequencing reveals heterogeneity and gene-by-environment interactions in treatment-naive, metastatic lung cancer

  Our understanding of genomic heterogeneity in lung cancer is largely based on the analysis of early-stage surgical specimens. Here we used endoscopic sampling of paired primary and intrathoracic metastatic tumors from 11 lung cancer patients to map genomic heterogeneity inoperable lung cancer with deep whole-genome sequencing. Intra-patient heterogeneity in driver or targetable mutations was predominantly in the form of copy number gain. Private mutation signatures, including patterns consistent with defects in homologous recombination, were highly variable both within and between patients. Irrespective of histotype, we observed a smaller than expected number of private mutations, suggesting that ancestral clones accumulated large mutation burdens immediately prior to metastasis. Single-region whole-genome sequencing of from 20 patients showed that tumors in ever-smokers with the strongest tobacco signatures were associated with germline variants in genes implicated in the repair of cigarette-induced DNA damage. Our results suggest that lung cancer precursors in ever-smokers accumulate large numbers of mutations prior to the formation of frank malignancy followed by rapid metastatic spread. In advanced lung cancer, germline variants in DNA repair genes may interact with the airway environment to influence the pattern of founder mutations, whereas similar interactions with the tumor microenvironment may play a role in the acquisition of mutations following metastasis.

  Study EGAS00001003830

• Sequence Data from the phase 2 PrE0505 trial of Durvalumab with First Line Platinum-Pemetrexed for Unresectable Pleural Mesothelioma

  Mesothelioma is a rare and fatal cancer with limited therapeutic options until the recent approval of combination immune checkpoint blockade. We report the results of the phase 2 PrE0505 trial (NCT02899195) of the anti-PD-L1 antibody, durvalumab, plus platinum-based and pemetrexed chemotherapy for patients with previously untreated unresectable pleural mesothelioma. The primary endpoint was overall survival compared to historic control with cisplatin and pemetrexed chemotherapy. The combination of durvalumab with chemotherapy met the pre-specified primary endpoint reaching a median survival of 20.4 months vs. 12.1 months with historic control. Treatment emergent adverse events were consistent with known side effects of chemotherapy and all adverse events due to immunotherapy were grade ≤2. Integrated genomic and immune cell repertoire analyses revealed that a higher immunogenic mutation burden coupled with a more diverse T cell repertoire were linked with favorable clinical outcome. Structural genome-wide analyses demonstrated a higher degree of genomic instability in responding tumors of epithelioid histology. Patients with germline alterations in cancer predisposing genes, especially those involved in DNA repair, were more likely to attain long term survival. Our findings indicate that concurrent durvalumab with platinum-based chemotherapy has promising clinical activity and that responses are driven by the complex genomic background of malignant pleural mesothelioma.

  Study EGAS00001005426

• Patient-derived tumor organoids for personalized medicine in a rare case of hepatocellular carcinoma with neuroendocrine differentiation.

  We report the case of a 74-year-old man with a very rare subtype of hepatocellular carcinoma with neuroendocrine differentiation (HCC-NED). The patient presented with two independent tumors, a gastrointestinal stromal tumor in the stomach and a hepatocellular carcinoma in the liver. Both tumors were surgically removed in curative intent. Histopathological work-up of the liver tumor revealed poorly differentiated hepatocellular carcinoma (Edmondson-Steiner grade IV) with diffuse expression of neuroendocrine markers synaptophysin (SYP) and chromogranin (CHGA). Three months after resection, multifocal recurrence of the HCC with neuroendocrine differentiation (HCC-NED) was observed. In the meantime, tumor organoids have been generated from the resected HCC-NED and extensively characterized. Sensitivity to a number of drugs approved for the treatment of HCC or neuroendocrine carcinomas was tested in vitro. Based on their in vitro efficacy, etoposide and carboplatin were used as first line palliative combination treatment. Because genomic analysis revealed a NTRK1-mutation (kinase domain) and tumor organoids were sensitive to entrectinib, a pan-TRK inhibitor, the patient received entrectinib as second line therapy. After only two weeks, treatment had to be discontinued due to deterioration of the patient’s general condition. In conclusion, we demonstrate for the first time that preclinical drug testing using organoids is feasible in selected HCC cases.

  Study EGAS00001005887

• 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

• Control of Focal Adhesion Kinase Activation by RUNX1-regulated miRNAs in high-risk AML

  We recently described a 16-gene expression signature for improved risk stratification of acute myeloid leukemia (AML) patients called the AML Prognostic Score (APS). A subset of APS high-risk AML patients showed increased levels of focal adhesion kinase (FAK), encoded by the Protein Tyrosine Kinase 2 (PTK2) gene, which was correlated with RUNX1 mutations. RUNX1 mutant cells are more sensitive to PTK2 inhibitors. As we were not able to detect RUNX1 binding sites in the PTK2 promoter, we hypothesized that RUNX1 might regulate micro(mi)RNAs that repress PTK2, such that loss-of-function RUNX1 mutations would result in reduced miRNA expression and derepression of PTK2. Examination of paired RNA-seq and miRNA-seq data from 301 AML cases revealed two miRNAs that positively correlated with RUNX1 expression, contained RUNX1 binding sites in their promoters and were predicted to target PTK2. We show that the hsa-let7a-2-3p and hsa-miR-135a-5p promoters are regulated by RUNX1, and that PTK2 is a direct target of both miRNAs. Even in the absence of RUNX1 mutations, hsa-let7a-2-3p and hsa-miR-135a-5p regulate PTK2 expression, and reduced expression of these two miRNAs sensitizes AML cells to PTK2 inhibition. These data explain how RUNX1 regulates PTK2, and identify potential miRNA biomarkers for targeting AML with PTK2 inhibitors.

  Study EGAS00001006491

• BinDel: software tool for detecting clinically significant microdeletions in low-coverage WGS-based NIPT samples

  Clinically pathogenic chromosomal microdeletions causing genetic disorders such as DiGeorge syndrome are rare genetic aberrations that can cause clinically relevant fetal and childhood developmental deficiencies. Clinical severity of such deficiencies depend on the exact genomic location and genes affected by the fetal chromosomal aberration. Here we present the BinDel, a novel region-aware microdeletion detection software package developed to infer clinically relevant microdeletion risk in low-coverage whole-genome sequencing NIPT data. To test BinDel, we quantified the impact of sequencing coverage, fetal DNA fraction, and region length on microdeletion risk detection accuracy. We also estimated BinDel accuracy on known microdeletion samples and clinically validated aneuploidy samples. BinDel identified each positive control sample as high risk. We also determined that it is critical to take into account that the sample with a detected high microdeletion risk does not have a full chromosome aneuploidy, as the latter can cause erroneous high microdeletion risk findings. We observed that lower sequencing coverage resulted in reduced microdeletion detection accuracy, and higher fetal fractions considerably increased the microdeletion detection accuracy, with coverage becoming increasingly relevant as fetal DNA fraction decreased. In conclusion, we developed an R package-based software tool BinDel for inferring fetal microdeletion risks, which accurately identified all positive control samples with microdeletion or -duplication aberrations as high-risk samples.

  Study EGAS00001006663

• Uncovering tumor intrinsic and extrinsic factors that regulate hepatocellular carcinoma growth using patient derived xenograft assays

  Several major factors limit our understanding of hepatocellular carcinoma (HCC). First, human HCCs are infrequently biopsied for diagnosis and thus are not often biologically interrogated. Second, HCC initiation and progression are strongly influenced by the cirrhotic microenvironment, and the exact contributions of intrinsic and extrinsic tumor factors are unclear. A powerful approach to examine the personalized biology of liver cancers and the influence of host tissues is with patient derived xenograft (PDX) models. In Asia, HCCs from hepatitis B virus patients have been efficiently converted into PDXs, but few parallel efforts from the west have been reported. In a large-scale analysis, we implanted 93 HCCs and 8 cholangiocarcinomas (CCAs) to systematically analyze host factors and to define an optimized platform for PDX development from both surgical and biopsy samples. NSG mice that had undergone partial hepatectomy (PHx) represented the best combination of engraftability, growth, and passageability, but overall rates were low and indicative of a unique intrinsic biology for HCCs in the US. PDX models preserved the histology and genetic features of parental tumors, and ultimately, 9 new models were usable for pre-clinical studies. Intriguingly, HCC PDXs were differentially sensitive to regorafenib and sorafenib and CCA PDXs were also highly sensitive to regorafenib. PDX models functionalize early and advanced stage HCCs and revealed unique biological features of liver cancers from the US.

  Study EGAS00001004020

• 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

• PD-L1 blockade immunotherapy rewires cancer-induced emergency myelopoiesis

  Introduction Immune checkpoint blockade (ICB) immunotherapy has revolutionized cancer treatment, demonstrating exceptional clinical responses in a wide range of cancers. Despite the success, a significant proportion of patients still fail to respond, highlighting the existence of unappreciated mechanisms of immunotherapy resistance. Delineating such mechanisms is paramount to minimize immunotherapy failures and optimize the clinical benefit. Methods In this study, we treated tumour-bearing mice with PD-L1 blockage antibody (aPD-L1) immunotherapy, to investigate its effects on cancer-induced emergency myelopoiesis, focusing on bone marrow HSPCs. We examined the impact of aPD-L1 treatment on HSPC quiescence, proliferation, transcriptomic profile, and functionality. Results Herein, we reveal that aPD-L1 in tumour-bearing mice targets the hematopoietic stem and progenitor cells (HSPCs) in the bone marrow (ΒΜ), mediating their exit from quiescence and promoting their proliferation. Notably, disruption of the PDL1/PD1 axis induces transcriptomic reprogramming in HSPCs, observed in both individuals with Hodgkin lymphoma (HL) and tumour-bearing mice, shifting towards an inflammatory state. Furthermore, HSPCs from aPDL1-treated mice demonstrated resistance to cancer-induced emergency myelopoiesis, evidenced by a lower generation of MDSCs compared to control-treated mice. Discussion: Our findings shed light on unrecognized mechanisms of action of ICB immunotherapy in cancer, which involves targeting of BM-driven HSPCs and reprogramming of cancer-induced emergency myelopoiesis.

  Study EGAS00001007873

• Genome wide variation in the Angolan Namib desert reveals unique Pre-Bantu ancestry

  The populations of the Angolan Namib Desert have been largely neglected in previous surveys of the genomic landscape of southern Africa. Although at present, the Namib is culturally dominated by Southwest Bantu-speaking cattle-herders, the region exhibits an extraordinary ethnographic diversity which includes an array of semi-nomadic peoples whose subsistence strategies fall outside the traditional division between foraging and food production and can thus be referred to as “peripatetic”. Among these small-scale populations are the last speakers of the Kwadi branch of the Khoe-Kwadi language family associated with the introduction of pastoralism into southern Africa (Kwepe), as well as a range of groups whose origins remain enigmatic (Kwisi, Twa and Tjimba). Using genome-wide data from 208 individuals belonging to nine ethnically diverse groups from the Angolan Namib and adjacent areas (Kwepe, Kwisi, Twa, Tjimba, !Xun, Kuvale, Himba, Nyaneka, Ovimbundu) in combination with published data from other regions of Africa, we reconstruct in detail the histories of contact emerging from pre-historic migrations to southern Africa and show that peripatetic groups from southwestern Angola stand out for exhibiting elevated levels of an unique, regionally-specific and highly divergent Pre-Bantu ancestry. These findings highlight the importance of the Namib for understanding the deep genetic structure of Africa.

  Study EGAS00001007011

• deep-learning-powered tissue deconvolution for cfDNA

  Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Despite the great promise, the sensitive and accurate quantification of tissue-derived cfDNA remains challenging to existing methods due to the limited characterization of tissue methylation and the reliance on unsupervised methods. To fully exploit the clinical potential of tissue-derived cfDNA, here we present one of the largest comprehensive and high-resolution methylation atlas based on 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively validated them in orthogonal datasets. Based on the rich tissue methylation atlas, we develop the first supervised tissue deconvolution approach, a deep-learning-powered model, cfSort, for sensitive and accurate tissue deconvolution in cfDNA. On the benchmarking data, cfSort showed superior sensitivity and accuracy compared to the existing methods. We further demonstrated the clinical utilities of cfSort with two potential applications: aiding disease diagnosis and monitoring treatment side effects. The tissue-derived cfDNA fraction estimated from cfSort reflected the clinical outcomes of the patients. In summary, the tissue methylation atlas and cfSort enhanced the performance of tissue deconvolution in cfDNA, thus facilitating cfDNA-based disease detection and longitudinal treatment monitoring.

  Study EGAS00001007213

• Machine Learning Signal Enrichment for Ultrasensitive Plasma Tumor Burden Monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007451

• Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007545

• 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

• Bulk-tissue RNA-sequencing paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen tissues from post-mortem neuropathologically-confirmed control individuals.

  Gaining insight into the genetic regulation of gene expression in human brain is key to the interpretation of genome-wide association studies for major neurological and neuropsychiatric diseases. Expression quantitative trait loci (eQTL) analyses have largely been used to achieve this, providing valuable insights into the genetic regulation of steady-state RNA in human brain, but not distinguishing between molecular processes regulating transcription and stability. RNA quantification within cellular fractions can disentangle these processes in cell types and tissues which are challenging to model in vitro. We investigated the underlying molecular processes driving the genetic regulation of gene expression specific to a cellular fraction using allele-specific expression (ASE). Applying ASE analysis to genomic and transcriptomic data from paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen tissues from 4 post-mortem neuropathologically-confirmed control human brains, we demonstrate that a significant proportion of genetic regulation of gene expression occurs post-transcriptionally in the cytoplasm, with genes undergoing this form of regulation more likely to be synaptic. These findings have implications for understanding the structure of gene expression regulation in human brain, and importantly the interpretation of rapidly growing single-nucleus brain RNA-sequencing and eQTL datasets, where cytoplasm-specific regulatory events could be missed.

  Study EGAS00001006380

• Gene Expression and Regulatory Networks in Human Leukocytes - Immunological Variation Consortium

  Profiling of gene expression with microarrays holds great potential for human health, for illuminating disease pathways or providing biomarkers to monitor disease or its resolution. Using high-throughput approaches for genotyping, immunophenotyping and gene expression analysis, the project will examine the basis for the control of gene expression in human immune cells, and how it is influenced by natural genetic variation or aging. In practice, the project will combine several cross-informative approaches: 1) Building on the established sample/data pipelines and robust protocols of the Immunological Genome (ImmGen) project, and on established cohorts of ethnically diverse healthy volunteers at hand, microarray techniques will be used to generate whole-genome expression profiles from purified naive CD4+ lymphocytes and monocytes from 600 healthy volunteers. A dense genetic map will be established for all donors. The results will elucidate how variation in the human genome affects the expression of immune genes, of key importance in understanding gene variants that bring susceptibility to immune or inflammatory disease. Computational analysis of these rich data will allow the reconstruction of regulatory connections between genes, helping to establish general modules and those specific of a given immune cell type. These data will be complemented by an orthogonal data group, generated from a restricted subset of 10 individuals, in which we will profile a larger set of 28 carefully delineated cell populations that exist in human blood. This work will also benefit from powerful interspecies comparison with similar experiments being performed in mice by ImmGen. 2) In addition, RNA from the same set of 28 defined cell populations will be probed with microarrays that explore other aspects of the transcriptome: i) microRNAs and other non-coding RNAs; ii) exon or splice junction arrays that will establish a map of differential splicing in human blood leukocyte. 3) The composition and reactivity of blood cells from the same donors will be established at the time of sample collection using high-throughput flow cytometry, correlating immune phenotypes with gene expression and genetic variation. 4) Genetic variability conditions the baseline levels of gene expression, but also the responsiveness to activating challenges. With samples from the same donors, NanoString technology for transcript counting will be used to analyze the transcriptional response of defined gene sets, representing response signatures of T or dendritic cells, for a fine-grained dissection of responses to different triggers (different bacterial ligands for dendritic cells, different cytokine environment for T cells). In keeping with the resource aspect of this project, all data and interpretations will be made publicly available rapidly upon curation, allowing public querying and browsing of the data, by using and evolving the existing web architectures of the ImmGen project, of the Broad Institute, and of international repositories. RELEVANCE: Exploration with DNA chips of the genome's expression microarrays holds great potential for human health, to better understand disease and to serve as diagnostic tools. Using a combination of high-throughput genomic techniques and computational biology, we will perform a broad exploration of gene expression in human blood cells across groups of African-American, Asian and European ancestry, asking how these profiles are affected by genetic variation or by age. These results will provide an invaluable reference benchmark for the interpretation of genetic and immunological studies. Additionally, over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, in a second study we analyzed ATAC-seq and RNA-seq profiles from stimulated primary CD4+ T cells in up to 105 healthy donors. We found regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution. 15% of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (ATAC-QTLs). ATAC-QTLs have the largest effects on co-accessible peaks, are associated with gene expression, and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis-regulatory elements, in isolation or in concert, to influence gene expression. In another study we analyzed RNA-seq profiles from primary CD4+ T cells of two healthy donors at six time points from 0 to 72 hours after stimulation with bead-bound antibodies against CD3 and CD28.

  Study phs000815

• Whole Genome Scan for Pancreatic Cancer Risk in the Pancreatic Cancer Cohort Consortium and Pancreatic Cancer Case-Control Consortium (PanScan)

  Within the framework of the NCI-sponsored Cohort Consortium, investigators from 12 prospective epidemiologic cohorts formed the Pancreatic Cancer Cohort Consortium in 2006. This study, also known as "PanScan", is funded by the National Cancer Institute (NCI) and involves conducting a genome-wide association study (GWAS) of common genetic variants to identify markers of susceptibility to pancreatic cancer. In 2007, the study was expanded to include 8 case-control studies. The study team includes scientists from the cohorts comprising the Consortium, the NCI and the Pancreatic Cancer Case Control Consortium (PanC4). PanScan I and II were conducted in 12 cohort studies and 8 case-control studies, leading to the discovery of four novel regions in the genome associated with risk for pancreatic adenocarcinoma. The third phase of PanScan (PanScan III) was conducted using recently identified incident pancreatic cancer cases drawn from fourteen cohorts from the cohort consortium, including nine prospective cohorts who participated in PanScan I, and five newly joined cohorts. The nine cohort studies that participated in PanScan I and had new genotyping of cases in PanScan III include ATBC, CPS-II, EPIC, HPFS, NHS, PHS, PLCO, SMWHS, and WHI; the five newly joined cohort studies include the Agricultural Health Study (AHS), the Multiethnic Cohort Study (MEC), the Melbourne Collaborative Cohort Study (MCCS), the Vitamins and Lifestyle Study (VITAL), and Selenium and Vitamin E Cancer Prevention Trial (SELECT). In addition to the cases from cohorts, we also included cases from the Gastrointestinal Cancer Clinic of Dana-Farber Cancer Institute Study (DFCI-GCC); from the University Hospital in Heidelberg, Germany, which is part of a larger European clinical case-control study (PANDoRA); and from clinic-based cases from eastern Spain (PANKRAS-II). The dbGaP datasets available include all subjects previously made available from PanScan I and II, plus 1,582 new incident pancreatic cancer cases of European descent from prospective cohorts, case-control studies or case series (genotyped as part of PanScan III). Also included are 61 pancreatic cancer cases and 67 control subjects from PanScan I as well as 173 pancreatic cancer cases from PanScan III of Asian ancestry from the Shanghai Men's and Women's Health Study (Supplemental Table 10, Wolpin et al. (Nat Genet, 2014)). The control population used in the analysis for the Wolpin et al. manuscript included cancer-free individuals from the prospective cohorts that contributed pancreatic cancer cases to PanScan III and controls from the Spanish Bladder Cancer SBC/EPICURO study that were previously genotyped using the OmniExpress, Omni 1M or Omni 2.5M SNP arrays. The data from these control subjects were posted to dbGaP under the GWAS in which they were initially genotyped and will not be made available in duplicate under this dbGaP study.The summary statistics for PanScan I-III were generated as detailed in Wolpin BM. et al., Genome-wide association study identifies multiple susceptibility loci for pancreatic cancer, Nature Genetics 2014; 46(9):994-1000 (https://www.nature.com/articles/ng.3052), and Klein, A. et al., Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer, Nature Communications, 2018;9(1):556 (https://www.nature.com/articles/s41467-018-02942-5). The dataset includes results from an association study of 5,117 individuals diagnosed with pancreatic ductal adenocarcinoma (PDAC) and 8,845 control individuals, or a total of 13,962 subjects of European ancestry (as compared to the genotype and phenotype information under this project that includes 9,437 individuals (PanScan I and II PDAC case and control individuals and PanScan III PDAC cases only). This is due to the fact that PanScan III “borrowed” GWAS data from control individuals genotyped separately from the PanScan GWAS project and are therefore not included as raw genotypes in phs000206.v5.p3. Association analysis was performed separately for PanScan I-II and PanScan III, followed by a meta-analysis of the two datasets. Results were filtered based on a minor allele frequency (MAF) < 0.01, an imputation INFO score < 0.3 and a heterogeneity P-value < 1x10-10 leaving a total of 9,758,390 variants. Columns in the summary statistics dataset are as follows: ID: variant rsIDChr: chromosome numberPosition: position in the chromosome, genome build GRCh37/hg19MarkerName: variant identifierAllele1: reference alleleAllele2: alternative alleleFreq1: allele frequency for allele2FreqSE: standard error of the allele frequencyMinFreq: the minimal allele frequency across studiesMaxFreq: the max allele frequency across studiesEffect: effect size for allele2StdErr: standard errorP-value: meta-analysis p-valueDirection: summary of effect direction for each studyHetISq: I^2 statistic which measures heterogeneity on scale of 0-100%HetChiSq: chi-squared statistic in simple test of heterogeneityHetDf: degrees of freedom for heterogeneity statisticHetPVal: P-value for heterogeneity statistic

  Study phs000206

• 300BCG study ATAC-seq data: human population variation of trained immunity

  ATAC-seq dataset for the paper: Title Multi-omics analysis of human population variation in immune function and in vivo response to BCG vaccination Abstract Immune responses are tightly regulated, yet highly variable between individuals. To investigate human population variation of trained immunity, we immunized healthy individuals with Bacillus Calmette-Guérin (BCG). This live attenuated vaccine induces not only an adaptive immune response against tu-berculosis, but also triggers innate immune activation and memory. We established personal immune profiles and chromatin accessibility maps over a time course of BCG vaccination in 323 individuals. This large resource uncovered genetic and epigenetic predictors of baseline immunity and BCG vaccine response. We found that BCG vaccination enhances the innate immune response only in individuals with dormant immune states at baseline, suggesting that exogeneous induction of trained immunity is not a universal booster of innate immunity, but specifically elevates weak innate immune responses. This study advances our understanding of BCG’s heterologous immune-stimulatory effects and trained immunity in humans. Moreover, our results highlight the value of epigenetic cell states as an “endo-phenotype” that connects immune function with genotype and the environment.

  Dataset EGAD50000000123

• Proteomic predictors of individualized nutrient-specific insulin secretion in health and disease

  Population level variation and molecular mechanisms behind insulin secretion in response to carbohydrate, protein, and fat remain uncharacterized despite ramifications for personalized nutrition. We now define prototypical insulin secretion dynamics in response to the three macronutrients in islets from 140 cadaveric donors, including those diagnosed with type 2 diabetes. We leverage the insulin response heterogeneity and use transcriptomics and proteomics to identify molecular pathways of specific nutrient responsiveness. Surprisingly, we find robust insulin secretion to fatty acid stimulus in ~8% of donors, challenging the idea that fat has negligible effects on insulin release. Distinct islet proteomes with differences in metabolic signalling networks convey this hyper-responsiveness to fat relative to carbohydrate. By comparing human islets to human embryonic stem cell-derived islet clusters, we show that, unlike glucose-responsiveness, fat hyper-responsiveness is equivalent and may be a hallmark of functionally immature cells. Our study represents the first comparison of dynamic responses to nutrients and multi-omics analysis in human insulin secreting cells. Responses of different people’s islets to carbohydrate, protein, and fat lay the groundwork for personalized nutrition.

  Dataset EGAD50000000519

• TSO500 STJAN33, BRAF mutated CUP

  The data set contains FASTQ files (filetype) of a NEXTSEQ550DX run (instrument). De FASTQ files are from DNA and RNA sample. The Library prep is a NGS TSO500 library prep (Illumina) (technology). A Study to Examine the Clinical Value of Comprehensive Genomic Profiling Performed by Belgian NGS Laboratories: a Belgian Precision Study of the BSMO in Collaboration With the Cancer Centre (BALLETT) This 2-year study involves the consortium of 9 cooperating Belgian NGS laboratories and will enroll 936 metastatic or locally advanced cancer patients coming from 13 different Belgian hospitals and cancer centers. Upon inclusion, all cancer patients will be offered 'comprehensive genomic profiling' (CGP) using Illumina's TSO500 NGS panel. This targeted NGS panel of 523 genes allows for the detection of single nucleotide variants, small indels, copy number variations and fusions, as well as for the determination of the 'tumor mutational burden' (TMB) and the 'microsatellite-instability' status (MSI). Both the wet lab execution of the CGP as well as the biological and clinical classification of the variants will be performed in a fully standardized way among the 9 participating Belgian local NGS laboratories.

  Dataset EGAD50000000689

• Spatial predictors of response to immunotherapy in microsatellite stable metastatic colorectal cancer

  Microsatellite stable (MSS) colorectal cancers (CRC) are largely unresponsive to immune checkpoint inhibition (ICI), prompting investigation into strategies to enhance sensitivity. The MAYA trial, which utilized temozolomide (TMZ) in MGMT-silenced MSS mCRC, hypothesized that TMZ-induced hypermutation could sensitize tumors to ICI. This phase II trial met its primary endpoint, demonstrating durable clinical responses with TMZ combined with ipilimumab and nivolumab. To elucidate factors in uencing response heterogeneity, we conducted multi-omic spatial pro ling of samples from patients who participated in the MAYA trial, including baseline and on-treatment tissue and blood specimens. While increased neoantigen load following TMZ exposure did not consistently predict for deep responses, spatial profiling revealed key determinants. Lymphocyte proportions, particularly CD8+KI67+ cells, within stromal and tumor compartments, along with macrophage composition (CD68+CD163+ cells) at the tumor-stromal interface, were predictive of response. Treatment pressures dynamically altered the tumor microenvironment composition and activated peripheral immune cells. This study is the first to identify spatial predictors of response to this promising novel treatment approach for MSS CRC.

  Dataset EGAD50000002244