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• Somatic copy number alteration and fragmentation analysis in circulating tumor DNA for cancer screening and treatment monitoring in colorectal cancer patients

  Background: Analysis of circulating free DNA (cfDNA) is a promising tool for personalized management of colorectal cancer (CRC) patients. Untargeted cfDNA analysis using whole-genome sequencing (WGS) does not need a priori knowledge of the patient´s mutation profile. Methods: Here we established LIquid biopsy Fragmentation, Epigenetic signature and Copy Number Alteration analysis (LIFE-CNA) using WGS with ~6x coverage for detection of circulating tumor DNA (ctDNA) in CRC patients as a marker for CRC detection and monitoring. Results: We describe the analytical validity and a clinical proof-of-concept of LIFE-CNA using a total of 259 plasma samples collected from 50 patients with stage I-IV CRC and 61 healthy controls. To reliably distinguish CRC patients from healthy controls, we determined cutoffs for the detection of ctDNA based on global and regional cfDNA fragmentation patterns, transcriptionally active chromatin sites, and SCNAs. We further combined global and regional fragmentation pattern into a machine learning classifier to accurately predict ctDNA for cancer detection. By following individual patients throughout their course of disease, we show that LIFE-CNA enables the reliable prediction of response or resistance to treatment up to 3.5 months before commonly used CEA. Conclusion: In summary, we developed and validated a sensitive and cost-effective method for untargeted ctDNA detection at diagnosis as well as for treatment monitoring of all CRC patients based on genetic as well as non-genetic tumor-specific cfDNA features. Thus, once sensitivity and specificity have been externally validated, LIFE-CNA has the potential to be implemented into clinical practice. To the best of our knowledge, this is the first study to consider multiple genetic and non-genetic cfDNA features in combination with ML classifiers and to evaluate their potential in both cancer detection and treatment monitoring.

  Study EGAS00001006490

• Separation of chronic myeloid leukemia stem cells from normal hematopoietic stem cells at single-cell resolution

  Chronic myeloid leukemia (CML) is a clonal disease, initiated and sustained by a subpopulation of CML stem cells (CML-SC) containing the BCR::ABL1 oncogene. Genetic markers that enrich for CML-SC have been identified, including CD26 being most specific. Genome sequencing analysis remain yet to be performed at single cell level in order to determine differences and heterogeneity in the genetic profile of CML-SC versus normal hematopoietic stem cells (HSC). Here we show that CD26 and CD33 separate CML-SC from normal HSC in freshly isolated bone marrow samples from newly diagnosed CML patients. DNA sequencing confirms that single CML-SC derived colonies are positive for BCR::ABL1 and harbor a recurrent set of patient-specific clonal somatic mutations across different CML-SC derived colonies. In contrast, marker-negative (CD26-CD33-) HSC from the same patients are negative for the BCR::ABL1 oncogene and do not carry recurrent, clonal mutation across different colonies. These results support the concept that CD26/CD33 expression separates genetically defined, clonal mutant CML-SC from normal HSC that carry individual sets of random mutations in CML patients. We provide whole exome DNA sequencing data for 23 clinical samples of CML-SC plus two buccal swipes derived normal samples. CML samples are comprised of 4 to 8 replicates from two patients, at diagnosis and after treatment. Single CML stem cells before treatment and single non-transformed HSC at remission were selected from bone marrow samples by FACS, according to genetic markers CD33+CD26+ at diagnosis and CD33+CD26-/CD33-CD26- at remission. WES libraries of colony forming assays derived CML-SC and HSC populations were prepared using Agilent SureSelect Human All Exon V6 kit and sequenced running 150 cycles (2x 75bp paired-end) on an Illumina NextSeq 500 platform. Following GATK best practices for somatic mutation calling, novel CML variants and random mutation events during remission phase were obtained.

  Study EGAS00001006904

• Proteomic Analysis of Non-Muscle Invasive and Muscle Invasive Bladder Cancer Highlights Distinct Subgroups With Metabolic, Matrisomal, and Immune Hallmarks

  We present the proteome biology of bladder cancer based on a cohort comprising treatment-naïve non-muscle invasive (NMIBC, N=17) and treatment-naïve muscle-invasive bladder cancer (MIBC, N=51), as well as neoadjuvant-treated MIBC (N=11); using formalin-fixed, paraffin-embedded samples and data-independent acquisition yielding >8,000 protein identifications. The NMIBC proteome reveals two subgroups that represent cell adhesion or lipid metabolism biology. MIBC, compared to NMIBC, shows an altered metabolic proteome together with enrichment of extracellular matrix (ECM), immune response, and complement proteins; in line with three proteomic MIBC subgroups that represent ECM, metabolic, or immune signatures. The ECM and immune subgroups are enriched for markers of M2-like tumor-associated macrophages and dendritic cells, while markers for natural killer cells are exclusive for the ECM subgroup, and markers for cytotoxic T-cells are a hallmark of the immune subgroup. Infiltration of CD8+ PD1+ positive cytotoxic T cells correlated with PD-L1 expression of MIBC, as demonstrated by multiplex immunofluorescence analysis. The metabolic subgroup presents a comparably immune-depleted microenvironment. YAP1 signaling is particularly prominent in the ECM subgroup. The protein BSCL2 emerges as a prognostic marker for MIBC. We highlight increased endogenous proteolysis in MIBC alongside the upregulation of matrix metalloproteases exceeding the upregulation of their endogenous inhibitors. Genomic panel sequencing underlines prevalent FGFR3 mutations in NMIBC and prevalent TP53 mutations in MIBC, but a genomic underpinning of the MIBC subgroups remains elusive. Proteogenomic analysis yields protein-level evidence for more than 1,300 single amino acid variants. The proteomes of neoadjuvant-treated MIBC resembled treatment-naïve MIBC. Tumor-stroma interaction of MIBC was further investigated by proteomic analysis of patient-derived xenografts of MIBC. Our study adds to the proteome-level understanding of bladder cancer.

  Study EGAS00001007290

• Genomic Analysis of Mycosis Fungoides and Sézary Syndrome Identifies Recurrent Alterations in TNFR2

  Mycosis Fungoides (MF) and Sézary Syndrome (Sz) comprise the majority of Cutaneous T-Cell Lymphoma (CTCL) cases and are characterized by clinical heterogeneity. This array of symptoms includes skin patches, plaques and tumors as well as blood involvement and erythroderma. Because the genetic basis of CTCL is still poorly understood, we performed whole-exome sequencing on 11 MF/Sz samples and their matched, normal control DNA. Upon analyzing this data, we distilled a list of an additional 494 genes to be sequenced at depth. The majority of these 494 genes were sequenced in the exons alone, however, for a small subset of these genes we sequenced the entire genomic locus in search of structural variation events. This 494 gene targeted resequencing effort was performed upon 72 patients with MF/Sz and their matched, normal control DNA. An additional 5 MF/Sz and matched, normal DNA samples underwent whole genome amplification (WGA) prior to library preparation, which appears to have introduced mutations into these samples, however we also include them here. We additionally include 10 MF/Sz samples without a matched, normal control samples, 1 of which underwent WGA. In addition to primary disease samples, we also performed targeted resequencing on 4 CTCL cell lines (HH, MyLa, SeAx and Hut78) as well as on H9 cells (a subclone of Hut78 cells) and Jurkat cells, a T-ALL derived cell line that was used as an experimental system for our work. In sum, this data deposition includes exome and/or targeted resequencing from 92 individuals with 192 samples submitted.

  Study phs000913

• Exome Sequencing to Identify Medically Relevant Associations in Finnish Sub-Isolate Samples from the FINRISK Cohort

  We propose to undertake, at the McDonnell Genome Institute of Washington University, a collaborative exome sequencing project of ~10,000 samples from a large Finnish population cohort, FINRISK, a participating component of the Sequencing Initiative Suomi (SISu) consortium. Together these sequenced samples will provide a unique resource for identification of infrequent or rare variants with a large impact on cardiovascular and metabolic disorders as well as on a wide range of heritable, disease-related quantitative phenotypes. Our collaborative group has already shown, in exome sequencing studies of smaller Finnish samples, that numerous loss of function variants are dramatically more frequent in Finland compared to other European populations, and that such variants demonstrate strong associations to several disease-related traits. Finland is the largest population isolate in Europe and the enrichment of these variants reflects its rapid growth from a severe population bottleneck about 100 generations ago. Northern and Eastern parts of Finland experienced additional, more recent bottlenecks, and therefore the enrichment of particular high-impact variants in these regions is even more extreme (Stoll et al., 2013, PMID: 23912948). We therefore propose to focus exome sequencing efforts on about 10,000 members of FINRISK who are specifically drawn from these sub-isolate regions. As a very wide range of phenotypes are available from this cohort (including cardiovascular and metabolic disease outcomes obtained from national registries) we hypothesize that the proposed exome sequencing will identify numerous new disease-related associations. Within the National Biobanks of Finland (www.nationalbiobanks.fi) we have DNA and tissue samples from over 200,000 individuals of whom 50,000 have GWAS data; these samples provide an exceptional resource for both imputation from the sequencing studies proposed here, as well as for replication of associations.

  Study phs000756

• Non-coding RNAs Activated by the Wnt/Beta-catenin Signaling Pathway in Hepatoblastoma

  Hepatoblastoma (HB) is the most common pediatric liver tumor, affecting mostly children under 3 years of age. This rare tumor represents 1% of all pediatric cancers. Genetic studies have shown that HB is characterized by high frequency mutations of the CTNNB1 gene encoding beta-catenin (around 75%) and relative genomic stability. Here we have analyzed the transcriptional profile of 21 HBs compared to matched non-tumor livers by Cap Analysis of Gene Expression (CAGE), which provides accurate and quantitative profiling of all transcripts. CAGE analysis revealed strong upregulation of known Wnt target coding genes in most tumors analyzed, consistent with previous transcriptomic studies. To better define the Wnt-dependent transcriptional landscape of HB, we integrated CAGE data with TCF4 ChIP-seq data from a CTNNB1-mutated cancer cell line and with the FANTOM5 genomic coordinates of TCF/LEF binding motifs. Both TCF/LEF binding motifs and ChIP-seq peaks were strongly enriched in the immediate upstream region, not only for protein-coding genes, but also for non-coding transcripts. Among the selected 112 top Wnt target genes at FDR<1.0E-6 and fold change>8, we found clear over-representation (66%) of distant transcription start sites (TSSs) representing lncRNAs and enhancer RNAs, which raises the question of their role in HB pathogenesis. Analysis of the 112 promoters using CAGEd-oPOSSUM confirmed the predominant involvement of Tcf/Lef transcription factors, together with HNF4G, GATA2, Sox3 and Ets-related genes. Finally, the 112 Wnt target signature defined 3 tumor subclasses, T1, T2 and T3, characterized by progressive alteration of the non-coding part of the transcriptome and significant differences in clinical behavior.

  Study phs001433

• Discovery and Characterization of Genetic Risk Loci in Sjogren's Syndrome

  The Sjögren's Genetics Network (SGENE) is an international collaboration focused on identifying and understanding the genetic variations that influence Sjögren’s pathology. Collectively, SGENE collaborators from 26 different sites (5 in the United States; 21 in foreign countries) have recruited a large cohort of geographically diverse participants of European ancestry. Recruitment, sample collection, and genotyping were performed at unique SGENE sites in compliance with local institutional review board approval. High-density SNP genotyping data were collated by the Oklahoma Medical Research Foundation (OMRF) and used to perform a GWAS of Sjögren's of European ancestry. Participants underwent extensive medical assessment for Sjögren's Syndrome using internationally accepted American-European Consensus Group (AECG) classification criteria or the American College of Rheumatology/European League Against Rheumatism classification criteria. Data quality control, GWAS imputation using the Haplotype Reference Consortium, panel version 1.1, and dbGaP preparation/posting were performed at the OMRF. To facilitate research focused on understanding the genetics of Sjögren's syndrome, the Genomic Summary Results from this GWAS are being made available herein using a total of n=3232 Sjögren's cases and n=17,481 controls. A total of n=8962 controls were obtained from our SGENE collaborators or from our previous study (Lessard, et al. Nature Genetics 2013. PMID: 24097067). To achieve adequate case-to-control ratios for the GWAS analyses, population-based control GWAS data were also obtained from dbGaP (phs000428.v2.p2; phs000672.v1.p1; phs000196.v3.p1; phs000187.v1.p1). In accordance with IRB approval, subject consents, and data sharing restrictions, we are also making available the individual-level genotyping data for a subset of Sjögren's cases (n=1,199) that were genotyped at the OMRF.

  Study phs002723

• The ClinSeq Project: Piloting Large-Scale Genome Sequencing for Research in Genomic Medicine

  ClinSeq is a pilot project to investigate the use of whole-genome sequencing as a tool for clinical research. By piloting the acquisition of large amounts of DNA sequence data from individual human subjects, we are fostering the development of hypothesis-generating approaches for performing research in genomic medicine, including the exploration of issues related to the genetic architecture of disease, implementation of genomic technology, informed consent, disclosure of genetic information, and archiving, analyzing, and displaying sequence data. In the initial phase of ClinSeq, we are enrolling roughly 1000 participants; the evaluation of each includes obtaining a detailed family and medical history, as well as a clinical evaluation. The participants are being consented broadly for research on many traits and for whole-genome sequencing. Initially, Sanger-based sequencing of 300-400 genes thought to be relevant to atherosclerosis is being performed, with the resulting data analyzed for rare, high-penetrance variants associated with specific clinical traits. The participants are also being consented to allow the contact of family members for additional studies of sequence variants to explore their potential association with specific phenotypes. Here, we present the general considerations in designing ClinSeq, preliminary results based on the generation of an initial 826 Mb of sequence data, the findings for several genes that serve as positive controls for the project, and our views about the potential implications of ClinSeq. The early experiences with ClinSeq illustrate how large-scale medical sequencing can be a practical, productive, and critical component of research in genomic medicine. Reprinted from Genome Res. 2009 Sep; 19(9): 1665-1674, with permission from Genome Research, PMID: 19602640.

  Study phs000971

• Breast Cancer in Blacks: Impact of Genomics, Healthcare Use and Lifestyle on Outcomes (BRIGHT)

  Young Black females bear a disproportionate burden of breast cancer (BC) mortality compared to White females and are underrepresented in clinical studies. It remains critical to understand factors that contribute to the high mortality from BC among young Black females in order to improve outcomes. The higher BC mortality rate among young Black females with breast cancer is partially attributed to the disproportionately higher proportions who develop the aggressive triple-negative breast cancer (TNBC). In addition to biologic factors, timely access to care, and lifestyle factors contribute to this disparity. Consequently, we sought to evaluate the interplay between biologic and non-biologic contributors to BC outcomes (i.e., BC disease-free survival (DFS)), and to better characterize the highly aggressive TNBC among young Black females based on distinct molecular subtypes. Ultimately, it is critical to assess both biologic and non-biologic factors to fully understand and address existing health disparities in this population. Through prior and subsequent recruitment of a population-based study of young Black females diagnosed with invasive breast cancer spanning 2009-2016, we: 1) assessed the contribution of biologic and non-biologic factors on BC-DFS observed among young Black females with BC, and 2) investigated molecular features of the subgroup with TNBC. Through this study, consented participants were asked to provide a saliva sample from which DNA was extracted for germline analyses, including germline inherited cancer genetic testing and Infinium Expanded Multi-Ethnic Genotyping Array. Breast cancer tumor specimens were also collected, and tumor RNA was extracted from viable FFPE tumor samples. Tumor RNA analyses included gene expression profiling through NanoString PAM50.Data that will be available through dbGaP for this study include SNP array data and PAM50 data.

  Study phs003466

• Sudden Death in the Young Case Registry

  Knowledge gaps persist about the incidence of and risk factors for sudden death in the young (SDY). The SDY Case Registry is a collaborative effort between the National Institutes of Health, the Centers for Disease Control and Prevention, and the Michigan Public Health Institute. Its goals are to: (1) describe the incidence of SDY in the United States by using population-based surveillance: (2) compile data from SDY cases to create a resource of information and DNA samples for research; (3) encourage standardized approaches to investigation, autopsy, and categorization of SDY cases; (4) develop partnerships between local, state, and federal stakeholders toward a common goal of understanding and preventing SDY; and (5) support families who have lost loved ones to SDY by providing resources on bereavement and medical evaluation of surviving family members. Built on existing Child Death Review programs and as an expansion of the Sudden Unexpected Infant Death Case Registry, the SDY Case Registry achieves its goals by identifying SDY cases, providing guidance to medical examiners/coroners in conducting comprehensive autopsies, evaluating cases through child death review and an advanced review by clinical specialists, and classifying cases according to a standardized algorithm. The SDY Case Registry also includes a process to obtain informed consent from next-of-kin to save DNA for research, banking, and, in some cases, diagnostic genetic testing. The SDY Case Registry will provide valuable incidence data and will enhance understanding of the characteristics of SDY cases to inform the development of targeted prevention efforts. For cases where informed consent has been obtained for research genomic sequencing has been performed. On these cases genomic data, phenotype information and on a limited number of cases redacted autopsy reports will be available through dbGaP.

  Study phs003221

• Genome Studies in Hereditary Spastic Paraplegia

  Next-generation sequencing technology is opening up new opportunities to rethink the way we identify disease causing genetic variation. An early application, whole exome sequencing, has now been established by a small number of research labs, including ours. Exome sequencing allows obtaining a near complete set of protein coding genomic variation in single individuals for less than $5,000. Promising targets for exome sequencing studies are Mendelian diseases, such as hereditary spastic paraplegias (HSP). HSP comprise a genetically very heterogeneous set of neurological disorders with currently 39 different HSP chromosomal loci being reported; yet, the identified genes explain only 60% of the genetic effect at best. Traditional methods of gene identification require linkage analysis of large families, but face increasing difficulties to identify such extended pedigrees for rare HSP forms. However, the innovative approach described in this application will overcome some of these limitations and utilize relatively small pedigrees for highly effective gene identification. We will apply exome sequencing, which will characterize all coding changes and flanking exonic variation in two individuals of a family. We have developed a multi-tiered strategy to reduce the number of identified novel variants to the very causative change in an individual family. We propose to study at least 60 HSP families, which are too small to yield conclusive results with linkage analysis. If the developing technology permits we will consider a larger sample or perform whole genome sequencing. Beyond the important benefit to genetics of HSP, this study will allow us to further establish this new method, which will benefit a large range of additional disease studies.

  Study phs001080

• MUSIC: Long-TerM OUtcomes after the Multisystem Inflammatory Syndrome In Children

  This study is an observational cohort study that will use routinely-collected clinical and cardiac (EKG, echocardiogram, CMR, exercise testing) data to assess the association between MIS-C (multisystem inflammatory syndrome in children) and cardiac outcomes within the first year after hospital discharge. Research funding will be available for EKGs, echocardiograms and MRIs in protocol windows that are not ordered by primary caregivers. Our principal goal is to determine the spectrum and early time course of coronary artery involvement, LV systolic function, and arrhythmias or conduction system abnormalities, and, using these data, to define associated clinical and laboratory factors. We will include all eligible patients, including retrospective cases beginning January 1, 2020, with follow-up (in-person or telehealth) up to one year and annual medical history forms until up to 5 years have elapsed since illness onset. Because many patients will have been identified by retrospective review, we will obtain consent at different times in their illness course. For this reason, it may be hard to reach some patients and their families. Waiver of consent will be obtained after three attempts have been made to locate the patient and family without success, as well as for the rare child who dies before informed consent can be obtained. We will include a HIPAA-compliant cryptographic algorithm to create a sharable “hashed” identifier from patient information. If blood work for research purposes is added to usual clinically-indicated blood work during follow-up visits, this will be covered by other informed consent forms. Our primary outcomes are the largest proximal Left Anterior Descending Coronary Artery (LAD) or Right Coronary Artery (RCA) z score and lowest Left Ventricular Ejection Fraction (LVEF).

  Study phs002770

• CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Summary Results from Genomic Studies

  GWAS have successfully identified genetic loci associated with a variety of conditions such as type 2 diabetes and coronary disease. The large number of statistical tests required in GWAS has posed a special challenge because few studies that have DNA and high-quality phenotype data are sufficiently large to provide adequate statistical power for detecting small to modest effect sizes. Even before the era of GWAS, the requirement for large sample sizes and the importance of replication have served as powerful incentives for collaboration. Meta-analyses combining summary data from multiple sources have improved the ability to detect new loci. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium was formed to facilitate GWAS meta-analyses and replication among multiple large and well-phenotyped cohort studies. The design of the CHARGE Consortium was formed initially from 5 prospective cohort studies from the United States and Europe: the Age, Gene/Environment Susceptibility (AGES) - Reykjavik Study, the Atherosclerosis Risk in Communities (ARIC) Study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), and the Rotterdam Study (RS). Additional studies have expanded the CHARGE consortium based upon the phenotypes and willingness to share information across the research community. In order to facilitate investigators across the world to examine relationships between phenotypes and genetic markers within CHARGE published reports, an open site is made available on dbGaP that provides the rsID and the p-value for inspection. Access to detailed summary statistics (including minor allele frequency, odds ratio/effect size) requires approval of a Data Access Request (DAR).

  Study phs000930

• Convergent evolution towards CD38 biallelic loss is a recurrent mechanism of resistance to anti-CD38 antibodies in multiple myeloma.

  Monoclonal antibodies directed against CD38 are a therapeutic mainstay in multiple myeloma (MM). While they have contributed to improved outcomes, most patients will still experience disease relapse. Despite their ubiquity, little is known about tumor-intrinsic mechanisms of resistance to these drugs. Antigen escape, whereby tumor cells alter expression of cell surface immunotherapy targets, has been proposed as a potential avenue, and has been seen with other immunotherapies in MM. Yet, it is unknown whether MM cells can develop permanent resistance to anti-CD38 antibodies by acquiring genomic events leading to biallelic disruption of the CD38 gene locus. Here, by using whole genome and whole exome sequencing data from 701 newly diagnosed patients, 72 patients at relapse with naivety to anti-CD38 antibodies, and 52 patients collected at relapse following anti-CD38 antibodies, we report biallelic inactivation of CD38 as a recurrent mechanism of resistance in 6% of patients, often via convergent evolution where distinct subclones are advantaged towards the same selective endpoint within the same patient. Monoallelic loss of the CD38 locus was seen in another 14% post-CD38-directed therapy. Three of the cases with biallelic events on CD38 presented with missense mutations and retained CD38 expression. Functional work demonstrated that two of these mutations decreased binding affinity and antibody-dependent cellular cytotoxicity of commercial antibodies Daratumumab and Isatuximab. However, the third mutation (R140G) provided relative resistance only towards one commercial product. Given that patients are often rechallenged with CD38 antibodies following disease progression, these data support the need for next generation sequencing to guide treatment selection.

  Study EGAS50000000709

• An integrative model of pathway convergence in genetically heterogeneous blast crisis chronic myeloid leukemia (CML)

  Targeted therapies against the BCR-ABL1 kinase have revolutionized treatment of chronic phase (CP) chronic myeloid leukemia (CML). In contrast, management of blast crisis (BC) CML remains challenging because BC cells acquire complex molecular alterations that confer stemness features to progenitor populations and resistance to BCR-ABL1 tyrosine kinase inhibitors. Comprehensive models of BC transformation have proved elusive because of the rarity and genetic heterogeneity of BC, but are important for developing biomarkers predicting BC progression and effective therapies. To better understand BC, we performed an integrated multiomics analysis of 74 CP and BC samples using whole-genome and exome sequencing, transcriptome and methylome profiling, and chromatin immunoprecipitation followed by high-throughput sequencing. Employing pathway-based analysis, we found the BC genome was significantly enriched for mutations affecting components of the polycomb repressive complex (PRC) pathway. While transcriptomically, BC progenitors were enriched and depleted for PRC1- and PRC2-related gene sets respectively. By integrating our data sets, we determined that BC progenitors undergo PRC-driven epigenetic reprogramming toward a convergent transcriptomic state. Specifically, PRC2 directs BC DNA hypermethylation, which in turn silences key genes involved in myeloid differentiation and tumor suppressor function via so-called epigenetic switching, whereas PRC1 represses an overlapping and distinct set of genes, including novel BC tumor suppressors. On the basis of these observations, we developed an integrated model of BC that facilitated the identification of combinatorial therapies capable of reversing BC reprogramming (decitabine+PRC1 inhibitors), novel PRC-silenced tumor suppressor genes (NR4A2), and gene expression signatures predictive of disease progression and drug resistance in CP.

  Study EGAS00001001751

• Whole exome sequencing of cell-free DNA reveals temporo-spatial heterogeneity and identifies treatment-resistant clones in neuroblastoma

  Background: Neuroblastoma (NB) displays important clinical and genetic heterogeneity, with emergence of new mutations at tumor progression. Patients and Methods: To study clonal evolution during treatment and follow-up, an innovative method based on circulating cell-free DNA (cfDNA) analysis by whole exome sequencing (WES) paired with target sequencing was realized in sequential liquid biopsy samples of 19 NB patients. Results: WES of the primary tumor and cfDNA at diagnosis showed overlap of Single Nucleotide Variants (SNVs) and Copy Number Alterations (CNAs), with 41% and 93% of all detected alterations common to the primary NB and cfDNA. CfDNA WES at a second time point indicated a mean of 22 new SNVs for patients with progressive disease. Relapse-specific alterations included genes of the MAPK pathway and targeted the protein kinase A signaling pathway. Deep coverage target sequencing of intermediate timepoints during treatment and follow-up identified distinct subclones. For 17 seemingly relapse-specific SNVs detected by sequencing detected these alterations in minor subclones, with relapse-emerging SNVs targeting genes of neuritogenesis and cell cycle. Furthermore a persisting, resistant clone with concomitant disappearance of other clones was identified by a mutation in the ubiquitin protein ligase HERC2. Conclusion: Modelisation of mutated allele fractions in cfDNA indicated distinct patterns of clonal evolution, with either a minor, treatment-resistant clone expanding to a major clone at relapse, or minor clones collaborating towards tumor progression. Identification of treatment-resistant clones will enable development of more efficient treatment strategies.cfDNA WES at relapse but not tumor or cfDNA WES at diagnosis, deep coverage target.

  Study EGAS00001002705

• Exploiting immune cell receptor information to quantify index switching in single cell transcriptome sequencing experiment

  By offering high sequencing speed and ultra-high-throughput at a low price, Illumina next-generation sequencing platforms has been widely adopted in recent years. However, an experiment with multiplexed library could be at risk of molecular recombination, known as “index switching”, which causes certain amount of reads to be assigned to an incorrect library. It is reported that a new advance, exclusion amplification (ExAmp) in conjunction with the patterned flow cell technology introduced on HiSeq 3000/HiSeq 4000/HiSeq X sequencing systems, potentially suffers from a higher rate of index switching than conventional bridge amplification. We took advantage of the diverse but highly cell-unique expression of immune cell receptors to quantify index switching on single cell RNA-seq data that were sequenced on HiSeq 3500 and HiSeq 4000. By utilizing the unique T-cell receptor (TCR) expression, we could quantify the spread-of-signal from many different wells (n=51 from total three batches) due to index switching. We used TraCer to reconstruct full-length TCR from all samples, and then used Kallisto to quantify TCR gene expression. We found index switching in all three batches of experiments investigated. The median percentage of incorrectly detected markers was estimated to be 4.2% (interquartile range (IQR): 2.0%-8.7%). We did not detect any consistent pattern of certain indices to be more prone for switching than others, suggesting that index switching is a stochastic process. We confirm that index switching is a problem that affects all samples run in multiplexed libraries on Illumina HiSeq 3500 and HiSeq 4000 platforms.

  Study EGAS00001002911

• Persistence of circulating tumor DNA in breast cancer patients during neoadjuvant treatment is a significant predictor of poor tumor response

  Purpose:Accurate assessment of response during neoadjuvant systemic treatment (NST) poses a major clinical challenge. Therefore, a minimally-invasive assessment of tumor response based on cell-free circulating tumor DNA (ctDNA) may be beneficial to guide treatment decisions.Experimental Design: We profiled 93 genes in tissue from 193 early breast cancer patients. Patient-specific assays were designed to track ctDNA during NST from 145 patients with available plasma. ctDNA presence and levels were correlated with complete pathological response (pCR) and residual cancer burden (RCB) as well as with clinicopathologic characteristics of the tumor to identify potential proxies for ctDNA release. Moreover, we tested the predictive value of driver events identified in the tumor.Results:At baseline, ctDNA could be detected in 63/145 (43.4%) patients and persisted in 25/63 (39.7%) patients at mid-therapy (MT) and 15/63 (23.8%) patients at the end of treatment. ctDNA detection at MT was significantly associated with higher RCB (OR 0.062, 95% CI 0.01-0.48, P=0.0077). Out of 31 patients with detectable ctDNA at MT, 30 patients (96.8%) were non-responders (RCB II, n=8; RCB III, n=22) and only one patient responded to the treatment (RCB I). Considering all 145 patients with baseline (BL) plasma, none of the patients with RCB 0 and only 6.7% of patients with RCB I had ctDNA detectable at MT, while 30.6% and 29.6% of patients with RCB II/III, respectively, had a positive ctDNA result. Conclusion:Overall, our results demonstrate that the detection and persistence of ctDNA at mid-therapy may have the potential to negatively predict response to neoadjuvant treatment and identify patients who will not achieve pCR or be classified with RCB II/III.

  Study EGAS00001005798

• Analysis of error profiles in deep next-generation sequencing data

  BackgroundSequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, PCR enrichment, and sequencing. In this study, we use current NGS technology to systematically investigate these questions.ResultsBy evaluating read-specific error distributions, we discover that the substitution error rate can be computationally suppressed to 10-5 to 10-4, which is 10- to 100-fold lower than generally considered achievable (10-3) in the current literature. We then quantify substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing by using multiple deep sequencing datasets. We find that error rates differ by nucleotide substitution types, ranging from 10-5 for A>C/T>G, C>A/G>T, and C>G/G>C changes to 10-4 for A>G/T>C changes. Furthermore, C>T/G>A errors exhibit strong sequence context dependency, sample-specific effects dominate elevated C>A/G>T errors, and target enrichment PCR led to aprox 6-fold increase of overall error rate. We also find that more than 70% of hotspot variants can be detected at 0.1% - 0.01% frequency with the current NGS technology by applying in-silico error suppression.ConclusionsWe present the first comprehensive analysis of sequencing error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS analysis accuracy both experimentally and computationally, ultimately enhancing the precision of deep sequencing.

  Study EGAS00001003444

• BCR Signaling in human BM PC

  The functions of bone marrow plasma cells (BMPC) beyond antibody production are not fully elucidated and distinct subsets of BMPC suggest potential different functions. Phenotypic differences were identified for human BMPC depending on CD19 expression. Since CD19 is a co-stimulatory molecule of the B-cell-receptor (BCR), and IgA+ and IgM+ BMPC express the BCR on their surface, we here studied whether CD19 expression affects cellular responses, such as BCR signaling and the expression of checkpoint molecules. We analyzed 132 BM samples from individuals undergoing routine total hip arthroplasty. We found that both CD19+ and CD19- BMPC expressed BCR signaling molecules. Notably, the BCR-associated kinase spleen tyrosine kinase (SYK) including pSYK was higher expressed in CD19+BMPC compared to CD19- BMPC. BCR stimulation also resulted in increased kinase phosphorylation downstream of the BCR while expression of CD19 remained stable afterwards. Interestingly, the BCR response was restricted to IgA+ BMPC independently of CD19 expression. With regard to the expression of checkpoint molecules, CD19- BMPC expressed higher levels of co-inhibitory molecule programmed cell death protein-1 (PD-1) than CD19+ BMPC. IgA+ BMPC characteristically upregulated PD-1 upon BCR stimulation in contrast to other PC subsets and inhibition of the kinase SYK abrogated PD-1 upregulation. In contrast, expression of PD-1 ligand, B and T lymphocyte attenuator (BTLA) and CD28 did not change upon BCR activation of IgA+ BMPC. Here, we identify a distinct functiotype of IgA+ BMPC that is independent of the phenotypic heterogeneity of the subsets according to their CD19 expression. The data suggest that IgA+ BMPC underlie different regulatory principles and/or exert distinct regulatory functions.

  Study EGAS00001004948

• Genetic heritage of the Baphuthi highlights an over-ethnicised notion of 'Bushman' in the Maloti-Drakensberg, southern Africa

  Using contemporary people as proxies for ancient communities is a contentious but necessary practice in anthropology. In southern Africa, the distinction between the Cape KhoeSan and eastern KhoeSan remains unclear as ethnicity labels have been changed through time and most communities were decimated if not extirpated. The eastern KhoeSan may have had genetic distinctions from neighbouring communities who speak Bantu languages and KhoeSan further away, alternatively the identity may not have been tied to any notion of biology, instead denoting communities with a nomadic 'lifeway' distinct from African agro-pastoralism. The Baphuthi of the 1800s in the Maloti-Drakensberg, southern Africa had a substantial KhoeSan constituency and a lifeway of nomadism, cattle raiding, and horticulture. Baphuthi heritage could provide insights into the history of the eastern KhoeSan. We examine genetic affinities of 23 Baphuthi to discern whether the narrative of KhoeSan descent reflects distinct genetic ancestry. Genome-wide SNP data (Illumina GSA) were merged with 52 global populations, for 160K SNPs. Genetic analyses show no support for a unique eastern KhoeSan ancestry distinct from other KhoeSan or southern Bantu-speakers. The Baphuthi have strong affinities with early-arriving southern Bantu-speaking (Nguni) communities, as the later-arriving non-Nguni show strong evidence of recent African admixture possibly related to Late-Iron Age migrations. The references to communities as 'San',and 'Bushman' in historic literature has often been misconstrued as notions of ethnic/biological distinctions. The terms may have reflected ambiguous references to non-sedentary polities instead, as seems to be the case for the eastern ‘Bushman’ heritage of the Baphuthi.

  Study EGAS00001007080

• T-cell receptor sequencing of tumor-infiltrating lymphocytes (TIL) in breast cancer

  The spatial distribution of tumor-infiltrating lymphocytes (TIL) predicts breast cancer outcome and response to systemic therapy, highlighting the importance of an intact tissue structure for characterizing patients’ tumors. Here, we present ST-FFPE, a spatial transcriptomics method for the analysis of formalin-fixed paraffin-embedded samples, which opens the possibility of interrogating widely available archival tissue. The method involves extraction, exome capture and sequencing of RNA from different tumor compartments microdissected by laser-capture, and can be used to study the cellular composition of various tumor environments. Focusing on triple-negative breast cancer (TNBC), we characterized T cells, B cells, dendritic cells, fibroblasts and endothelial cells in both stromal and intra-epithelial compartments. We found a highly variable spatial distribution of immune cell subsets among tumors. This analysis revealed that the immune repertoires of intra-epithelial T and B cells were consistently less diverse than those of stromal T and B cells. T-cell receptor (TCR) sequencing confirmed a reduced diversity and revealed higher clonality of intra-epithelial T cells relative to the corresponding stromal T cells. Analysis of the top ten dominant clonotypes in the two compartments showed a majority of shared but also some unique clonotypes both in stromal and intra-epithelial T cells. Hyperexpanded clonotypes were more abundant among intra-epithelial than stromal T cells. These findings validate the ST-FFPE method and suggest an accumulation of antigen-specific T cells within tumor core. Because ST-FFPE is readily applicable for analysis of previously collected tissue samples, it could be useful for rapid assessment of intratumoral cellular heterogeneity in multiple disease and treatment settings.

  Study EGAS00001007125

• A study of the genetic basis of evation by Acute Myeloid Leukaemia of Graft vs Leukaemia effects after allogeneic bone marrow transplantation

  Acute myeloid leukaemia (AML) is an aggressive and molecularly diverse disease with a poor overall survival of 20-25%. With an annual incidence of 2.9 per 100,000, AML is currently the commonest myeloid malignancy in Europe, yet the two main therapeutic options for this disease, anthracyclines and purine analogues, have remained unchanged for over 20 years. Currently patients are stratified at diagnosis according to a series of clinicopathological parameters (e.g. age, white cell count and presence/absence of previous clonal haematological disease) and molecular markers (e.g. chromosomal translocations/deletions, aneuploidy and mutations in genes such as FLT3 and NPM1). Patients with adverse prognostic features, whose prognosis is particularly poor (e.g. <15% long-term survival) are offered treatment with allogeneic bone marrow transplantation (allo-BMT) if a sibling or unrelated donor is available. This can significantly improve survival (e.g. up to 40% long-term survival in some contexts), albeit at the expense of significant toxicity and transplant-related mortality (TRM). Allo-BMT is thought to work in part by allowing the delivery of large doses of chemotherapy followed by haemopoietic "rescue" with donor haemopoietic stem cells (haemopoietic failure would otherwise ensue). However, potentially the most potent effect of allo-BMT is the cytotoxic effect of donor lymphocytes against AML blasts, a phenomenon known as graft-vs-leukaemia (GVL) effect. Increasingly, transplants using reduced chemotherapy intensity (mini-allografts) are being used that partially circumvent the toxicity from chemotherapy and rely on GVL to effect cure. Nevertheless, AML relapse after allo-BMT still occurs at a significant rate of up to 80% depending on the type of transplant. There is accumulating evidence that genetic events in residual leukaemic cells enable them to evade immunodetection and therefore survive the GVL effect and expand to cause relapse. The most striking example of this is the loss of HLA antigens after transplants in which donor and recipient are not fully HLA-matched. In these cases, the leukaemia "deletes" the genomic region containing the disparate HLA antigen which was preferentially targeted as "foreign" by the GVL effect. However, the genetic basis of immune evasion in the majority of transplants, which are fully HLA matched, is not known. One possibility is that loss of genes coding for antigens outside the HLA locus but which are also targets of GVL may operate, alternatively genetic events that affect processes downstream of immunological cytotoxicity may be responsible. The identification of genetic events that mediate immune evasion would not only facilitate the understanding of this process but can help plan therapeutic interventions that improve the outcomes of allogeneic transplantation for AML and other disorders. We intend to study this by conducting exome sequencing on 6 cases of AMLs from patients that attend my clinic at Addenbrooke's hospital and have relapsed after allogeneic transplantation. Samples from AML diagnosis, remission/normal and AML relapse (total n=18) will be studied to identify somatic mutations in the primary AML and those acquired by the relapsed clone. The 18 samples will also be studied by array CGH to detect regions of genomic amplification or deletion.

  Dataset EGAD00001000404

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: Multimodal Developmental Neurogenetics of Females

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002043

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Genomics of Autism Spectrum Disorder (GASD)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal.An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002509