Search Results - EGA European Genome-Phenome Archive

Intra-tumor heterogeneity of localized lung adenocarcinomas defined by multi-region sequencing

Background: Intra-tumor heterogeneity (ITH) may have profound impacts on biopsy strategy, characterization of actionable targets, treatment planning, and drug resistance. ITH of lung cancers has not been well studied. Methods: We performed multi-region whole exome sequencing (average sequencing depth 277x) on 48 tumor regions from 11 resected lung adenocarcinomas (8 stage I, 2 stage II and one stage III tumors) followed by deep sequencing validation (average sequencing depth 863x). Results: All tumors showed clear evidence of spatial ITH. On average, 76% of all mutations and 20/21 known cancer gene mutations were present in all regions of individual tumors (trunk mutations). Copy number analysis did not show substantial difference in large-scale chromosome aberrations. A canonical KRAS p.G12C mutation was detected in only 1 of 4 tumor regions (branch mutations) at exome depth but detected in all four tumor regions (trunk mutations) at increased sequencing depth. In addition, many heterogeneous branch mutations defined by exome sequencing were detectable in all regions of individual tumors with increasing sequencing depth. Significant differences in mutational spectrum were observed in 6 tumors indicating that specific mutational processes were likely operative at different times during development of these tumors. With a median follow up of 21 months post surgery, 3 patients have relapsed and all 3 patients presented with significantly larger fractions of subclonal mutations in their primary tumors. Conclusions: Although multi-region sampling is still required to fully assess ITH complexity, single biopsy analysis at appropriate depth might be sufficient to identify the majority of known cancer gene mutations in localized lung adenocarcinomas. Larger subclonal mutation fractions may be associated with increased likelihood of postsurgical relapse in patients with localized lung adenocarcinomas. Studies on larger cohort, ideally with comprehensive clinical annotation and repeat biopsy at relapse are needed to fully understand the clinical impact of ITH.

Study EGAS00001000930

High-throughput telomere length measurement at nucleotide resolution using the PacBio high fidelity sequencing platform

Telomeres are specialized nucleoprotein structures at the ends of linear chromosomes that are essential for the stability as well as the complete replication of the human genome. The progressive shortening of steady-state telomere length in normal human somatic cells is a promising biomarker for age-associated diseases. However, there remain substantial challenges in quantifying telomere length in clinics and research laboratories due to the lack of accurate and high-throughput telomere length measurement method. Here, we describe a novel workflow to capture and analyze telomeres accurately at the single-nucleotide resolution. By using newly designed telobaits that are complementary to the single-stranded G-rich 3’ telomeric overhangs, we can specifically and efficiently capture full-length telomeres and subject them to single-molecule real-time (SMRT) sequencing. We show that the telomere length can be measured at nucleotide resolution using the PacBio high fidelity (HiFi) sequencing platform, which provides the necessary accuracy and throughput to uncover the steady-state telomere length distribution in human culture cell lines as well as clinical patient samples. This new method is a valuable tool not only in population-wide epidemiology studies but also for the longitudinal assessment of telomere attrition in individuals. Our results also reveal the extreme heterogeneity of telomeric variant sequences (TVSs) that is dispersed throughout the telomere repeat region. Importantly, the unique distribution pattern and sequence of TVSs in individuals may be used as a fingerprint for sample identification. In addition, the presence of TVSs disrupts the continuity of the canonical (5’-TTAGGG-3’)n telomere repeats, which could affect the binding of shelterin complexes at the chromosomal ends. Therefore, TVSs may act as a form of genetic polymorphisms that impairs telomere protection. Together with the absolute telomere length in each individual, TVSs may have profound implications in human aging and diseases.

Study EGAS00001006103

Whole genome and whole exome sequencing of serial biopsies of relapsed/refractory diffuse large B-cell lymphoma.

Purpose: Diffuse large B-cell lymphoma (DLBCL) is cured in more than 60% of patients, but outcomes remain poor for patients experiencing disease progression or relapse (refractory or relapsed DLBCL [rrDLBCL]), particularly if these events occur early. Although previous studies examining cohorts of rrDLBCL have identified features that are enriched at relapse, few have directly compared serial biopsies to uncover biological and evolutionary dynamics driving rrDLBCL. Here, we sought to confirm the relationship between relapse timing and outcomes after second-line (immuno)chemotherapy and determine the evolutionary dynamics that underpin that relationship. Patients and methods: Outcomes were examined in a population-based cohort of 221 patients with DLBCL who experienced progression/relapse after frontline treatment and were treated with second-line (immuno)chemotherapy with an intention-to-treat with autologous stem-cell transplantation (ASCT). Serial DLBCL biopsies from a partially overlapping cohort of 129 patients underwent molecular characterization, including whole-genome or whole-exome sequencing in 73 patients. Results: Outcomes to second-line therapy and ASCT are superior for late relapse (>2 years postdiagnosis) versus primary refractory (<9 months) or early relapse (9-24 months). Diagnostic and relapse biopsies were mostly concordant for cell-of-origin classification and genetics-based subgroup. Despite this concordance, the number of mutations exclusive to each biopsy increased with time since diagnosis, and late relapses shared few mutations with their diagnostic counterpart, demonstrating a branching evolution pattern. In patients with highly divergent tumors, many of the same genes acquired new mutations independently in each tumor, suggesting that the earliest mutations in a shared precursor cell constrain tumor evolution toward the same genetics-based subgroups at both diagnosis and relapse. Conclusion: These results suggest that late relapses commonly represent genetically distinct and chemotherapy-naïve disease and have implications for optimal patient management.

Study EGAS00001007053

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

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

Study EGAS00001002908

H3Africa - Genomic and Environmental Risk Factors for Cardiometabolic Disease in Africans

The long-term vision of the AWI-Gen Collaborative Centre (CC) is to build sustainable capacity in Africa for research that leads to an understanding of the interplay between genetic, epigenetic and environmental risk factors for obesity and related cardiometabolic diseases (CMD) in sub-Saharan Africa. The CC will be consolidated under the auspices of the University of the Witwatersrand (Wits) and the International Network for the Demographic Evaluation of Populations and Their Health in Developing Countries (INDEPTH). It will capitalize on the unique strengths of existing longitudinal cohorts, including the urban Soweto and rural Agincourt studies in South Africa (Wits based), and the well established INDEPTH demographic health and surveillance centers in Kenya, Ghana, Burkina Faso and South Africa. The centers offer established infrastructure, trained fieldworkers, long-standing community engagement, and detailed longitudinal phenotypic data, focusing on obesity and cardiometabolic health. Key strengths are harmonized phenotyping across sites, building on strong existing cohorts, and representation of the geographic and social variability of African populations. We aim to: 1. Build sustainable infrastructure (biobanks and laboratories) and capabilities (well characterized population cohorts, genotyping and bioinformatics) for genomic research on the African continent; 2. Understand the genomic architecture of sub-Saharan populations from west, east and south Africa to guide genomic studies (genome sequencing and high throughput SNP and CNV arrays using unrelated individuals and family trios to improve the accuracy of haplotype analyses) and; 3. Investigate the independent and synergistic genomic contributions to body fat distribution (BMI, hip/waist circumference, subcutaneous and visceral fat) in these populations considering the relevant environmental and social contexts (rural/urban communities, quickly transitioning obesity prevalence, differential HIV, TB, and malaria infection histories). We will investigate the effect of obesity and fat distribution on the risk for CMD in the longitudinal cohorts.

Study EGAS00001002482

Genome_Diversity_in_Africa_Project__Uganda

Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene–disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group). Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics

Study EGAS00001002523

Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

Background: Cancer patients with advanced disease exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates sequencing data with functional assay data to develop patient-specific combination cancer treatments. Methods: Tissue taken from a murine model of alveolar rhabdomyosarcoma was used to perform single agent drug screening and DNA/RNA sequencing experiments; results integrated via our computational modeling approach identified a synergistic personalized two-drug combination. Cells derived from the tumor were allografted into mouse models and used to validate the personalized two-drug combination. Computational modeling of single agent drug screening and RNA sequencing of multiple heterogenous sites from a single patient’s epithelioid sarcoma identified a personalized two-drug combination effective across all tumor regions. The heterogeneity-consensus combination was validated in a xenograft model derived from the patient’s primary tumor. Cell cultures derived from human and canine undifferentiated pleomorphic sarcoma were assayed by drug screen; computational modeling identified a resistance-abrogating two-drug combination common to both cell cultures. This combination was validated in vitro via a cell regrowth assay. Results Our computational modeling approach addresses three major challenges in personalized cancer therapy: synergistic drug combination predictions (validated in vitro and in vivo in a genetically engineered murine cancer model), identification of unifying therapeutic targets to overcome intra-tumor heterogeneity (validated in vivo in a human cancer xenograft), and mitigation of cancer cell resistance and rewiring mechanisms (validated in vitro in a human and canine cancer model). Conclusions These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy.

Study EGAS00001003564

Successful immune checkpoint blockade in a patient with advanced stage microsatellite unstable biliary tract cancer (H021)

Cancers acquire multiple somatic mutations that can lead to the generation of immunogenic mutation-induced neoantigens. These neoantigens can be recognized by the host’s immune system. However, continuous stimulation of immune cells against tumor antigens can lead to immune cell exhaustion, which allows uncontrolled outgrowth of tumor cells. Recently, immune checkpoint inhibitors have emerged as a novel approach to overcome immune cell exhaustion and re-activate anti-tumor immune responses. In particular, antibodies blocking the exhaustion-mediating programmed death receptor (PD-1)/PD-L1 pathway have shown clinical efficacy. The effects were particularly pronounced in tumors with DNA mismatch repair deficiency and a high mutational load, which typically occur in the colon and endometrium. Here, we report on a 24-year old woman diagnosed with extrahepatic cholangiocarcinoma who showed strong and durable response to the immune checkpoint inhibitor pembrolizumab, although treatment was initiated at an advanced stage of disease. The patient’s tumor displayed DNA mismatch repair deficiency and microsatellite instability (MSI), but lacked other features commonly discussed as predictors of response towards checkpoint blockade, such as PD-L1 expression or dense infiltration with cytotoxic T cells. Notably, high levels of HLA class I and II antigen expression were detected in the tumor, suggesting a potential causal relation between functionality of the tumor’s antigen presentation machinery and the success of immune checkpoint blockade. We suggest determining MSI status in combination with HLA class I and II antigen expression in tumors potentially eligible for immune checkpoint blockade even in the absence of conventional markers predictive for anti-PD-1/PD-L1 therapy and in entities not commonly linked to MSI phenotype. Further studies are required to determine the value of these markers for predicting the success of immune checkpoint blockade. (H021)

Study EGAS00001002441

Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

Study EGAS00001004861

Genetic analysis of HLA and immune escape genes in Diffuse Large B-cell Lymphoma

Fifty percent of diffuse large B-cell lymphoma (DLBCL) cases lack cell-surface expression of the class-I major histocompatibility complex (MHC-I), thereby escaping immune recognition by cytotoxic T cells. In order to comprehensively identify the mechanisms involved in MHC-I loss, we first performed immunophenotypic analysis of both MHC class-I and -II in 657 cases across the spectrum of B-NHL, revealing that loss of MHC-I, but not MHC-II, is preferentially restricted to DLBCL. We then used whole exome and targeted deep-sequencing to examine genes involved in MHC-I expression in 74 DLBCL samples representative of MHC-I positive and negative cases. We show here that somatic biallelic or monoallelic inactivation of B2M and/or HLA-I is present in 80.9% (34/42) of MHC-I negative tumors. Furthermore, 68.8% (22/32) of MHC-I positive DLBCLs also harbored monoallelic HLA-I genetic alterations (MHC-I positivemono) that lead to allelic imbalance, suggesting allele-specific inactivation. Both MHC-I negative and MHC-I positivemono cases showed a significantly higher mutational burden as well as a higher number of inferred neo-antigens, suggesting co-selection of HLA-I loss and sustained neo-antigen production. Interestingly, the analysis of &gt; 500.000 individuals in two databases revealed homozygosity of germline HLA-I genes in 26-38% of DLBCL patients, a frequency significantly higher than that observed in any other cancer type. In mice, germinal-center B cells lacking HLA-I expression did not progress to lymphoma and were counterselected in the context of oncogene-driven lymphomagenesis, suggesting that additional events are needed to license immune evasion. These results suggest a multi-step process of HLA-I loss including both germ-line and somatic events in DLBCL development, and have direct implications for the pathogenesis and immunotherapeutic targeting of this disease.

Study EGAS00001005054

Local In Time Statistics for processual research

Background: Functional genomics in a processual analysis cover the time-dependent changes in transcriptomics and epigenetics before diagnosis of a disease, reflecting the changes in both life style and disease processes. The aim of this paper is to explore the dynamic, time-dependent mechanisms of the metastatic processes, using blood transcriptomics and including time in a continuous manner. For achieving this goal we develop new statistical methods based on statistics that are local in time. Methods: The new statistical method, Local In Time Statistics (LITS), is based on calculating statistics in moving windows and randomization. The method has been tested for the analysis of a dataset that collectively provides information on the blood transcriptome up to eight years before breast cancer diagnosis. The dataset from the NOWAC Post-genome Cohort consists of 467 case-control pairs matched on birth year and time of blood sampling. The data for a pair is the difference in log2 gene expression between the case and control. The stratified analyses are based on important biological differences like metastatic versus non-metastatic cancer, and the mode of cancer detection, i.e. screening detected versus clinically detected cancers. The dataset was used for examining whether the gene expression profile varies between cases and controls, with time, or between cases with and without metastases. Results: The null hypotheses of no differences between cases and controls, no time-dependent changes, and no differences between different strata were all rejected. For screening detected cancers the probability of correct prediction of metastasis status was best in year 1 before diagnosis compared to year 3 and 4 before diagnosis for clinically detected cancers. The predictor was not very sensitive to the number of genes included.Conclusions: Using a new statistical method, LITS, we have demonstrated time-dependent changes of the blood transcriptome up to eight years before breast cancer diagnosis.

Study EGAS00001002520

Same-day genomic and epigenomic diagnosis of brain tumors using realtime nanopore sequencing

Molecular classification of cancer has entered clinical routine to inform diagnosis, prognosis and treatment decisions. At the same time, new tumor entities have been identified that cannot be defined histologically. For central nervous systems tumors, the current World Health Organization classification explicitly demands molecular testing, e.g. for 1p/19q- codeletion or IDH mutations, to make an integrated histomolecular diagnosis. However, a plethora of sophisticated technologies is currently needed to assess different genomic and epigenomic alterations and turnaround times are in the range of weeks, which makes standardized and widespread implementation difficult and hinders timely decision making. Here, we explored the potential of a pocket-size nanopore sequencing device for multimodal and rapid molecular diagnostics of cancer. Low-pass whole genome sequencing was used to simultaneously generate copy number (CN) and methylation profiles from native tumor DNA in the same sequencing run. Single nucleotide variants in IDH1, IDH2, TP53, H3F3A and the TERT promoter region were identified using deep amplicon sequencing. Nanopore sequencing yielded ~0.1X genome coverage within six hours and resulting CN and epigenetic profiles correlated well with matched microarray data. Diagnostically relevant alterations, such as 1p/19q codeletion, and focal amplifications could be recapitulated. Using ad hoc random forests, we could perform supervised pan-cancer classification to distinguish gliomas, medulloblastomas and brain metastases of different primary sites. Single nucleotide variants in IDH1, IDH2 and H3F3A were identified using deep amplicon sequencing within minutes of sequencing. Detection of TP53 and TERT promoter mutations shows that sequencing of entire genes and GC-rich regions is feasible. Nanopore sequencing allows same-day detection of structural variants, point mutations and methylation profiling using a single device with negligible capital cost. It outperforms hybridization-based and current sequencing technologies with respect to time-to diagnosis and required laboratory equipment and expertise, aiming to make precision medicine possible for every cancer patient, even in resource restricted settings.

Study EGAS00001002213

Short and long-read genome sequencing methodologies for somatic variant detection; genomic analysis of a patient with diffuse large B-cell lymphoma

Recent advances in throughput and accuracy mean that the Oxford Nanopore Technologies (ONT) PromethION platform is a now a viable solution for WGS. New bioinformatic methods have been developed to take advantage of this long read data, however much of the validation of these tools has focussed on calling germline variants (both SNVs and structural variants). Somatic variants are outnumbered many-fold by germline variants and their detection is further complicated due to their frequency varying depending on tumour purity/subclonality. Here, we evaluate the extent to which Nanopore WGS enables genome-wide detection and analysis of somatic variation. We do this through sequencing tumour and germline genomes for a patient with diffuse B-cell lymphoma. We examine the capability of currently available tools for calling somatic variants in ONT data by comparing the data with results from 150bp short-read sequencing of the same samples. We then conduct a detailed analysis of the performance of multiple long-read mappers and structural variant callers for calling large, somatic structural variants (SVs) in ONT data. Our protocol achieved yields of up to 96 mapped Gb per PromethION flow cell with average read lengths of ~5kb. Calling germline SNVs from these data achieved good specificity and sensitivity. However, results of somatic SNV calling highlight the need for the development of specialized joint calling algorithms. Our analysis of structural variants shows that the comparative performance of different tools varies significantly between SV types, and suggest long reads are especially advantageous for calling large somatic deletions and duplications. Finally, we highlight the utility of long reads for phasing clinically relevant variants by using the ONT data to confirm that a somatic 1.6Mb deletion and a p.(Arg249Met) mutation involving TP53 are oriented in trans.

Study EGAS00001004266

Reduced Representation Bisulfite Sequencing (RRBS) in various tissues to discover DNA methylation markers for the diagnosis of breast and ovarian cancer.

Despite a myriad of attempts in the last three decades to diagnose ovarian cancer (OC) earlier, this clinical aim still remains a significant challenge. In addition, monitoring treatment and early detection of fatal breast cancer (BC) remains a major unmet need. Aberrant methylation patterns of linked CpGs analyzed in DNA fragments shed by cancers into the bloodstream (i.e. cell-free DNA) can provide highly specific signals indicating cancer presence.In order to discover the most relevant CpG regions, we used RRBS and analysed several tissue samples: 11 prospectively collected invasive epithelial ovarian cancer samples (high grade serous n=8, low grade serous n=1, endometrioid n=1, mucinous n=1, mean age = 54.7 years), 8 prospectively collected invasive ductal breast cancer samples (2/8 triple negative; mean age = 56.6 years), one benign tumor (papillary serous cystadenoma, age = 86 years), 18 non-neoplastic tissue samples (breast n=7 and adnexal n=11, mean age = 60.2 years), two non-neoplastic endometrial tissues (mean age = 68 years) and twenty three white blood cell samples (mean age = 57.8 years) were assessed by RRBS. Genome wide methylation analysis was performed by Reduced Representation Bisulfite Sequencing (RRBS) at GATC Biotech. DNA was digested with MspI followed by size selection of the library, providing enhanced coverage for the CpG-rich regions. The digested DNA was adapter ligated, bisulfite modified and PCR amplified. The libraries were sequenced on Illumina’s HiSeq 2500. Analysis of the first samples sequenced with 100bp paired-end mode showed that the library insert size was small. Therefore, the remaining samples were sequenced with 50 bp paired-end mode. Using Genedata Expressionist® for Genomic Profiling v9.1, we established a bioinformatics pipeline for the detection of cancer specific differentially methylated regions (DMRs). The most promising DMRs were taken forward for the development and validation of serum based clinical assays.

Study EGAS00001002609

GDAP___Genome_Diversity_in_Africa_Project

The Genomic Diversity in Africa Project (GDAP) started with the plan to develop a genomic resource from African populations, characterise genomic diversity and population history, and facilitate clinical studies in Africa. Currently, 25 individuals from 24 ethnolinguistic groups have been whole-genome sequenced at high depth totalling 585 individuals. An additional 41 individuals have been sequenced with 10X Genomics libraries. At this stage, the initial curation of this dataset has been finished and we are performing the analysis in coordination with our collaborators. The current state of the GDAP represents a very diverse panel of African populations that maximizes geographical and ethnic variation and represents a great starting point to achieve the aforementioned goals. However, southern sub-Saharan countries, Bantu speakers and hunter gatherer groups are currently underrepresented, despite being crucial to understand the evolutionary history of the continent. After extensive effort to collate studies documentation, we finally have the opportunity to sequence 600 new individuals from these groups, including countries as Gabon, Rwanda and Zambia, and address these deficiencies. We aim to proceed with the same strategy: to sequence at high depth 25 individuals with standard PCR free libraries, with 2 additional individuals with 10X Genomics Chromium libraries per ethnolinguistic group. The former allows a good representation of variants down to low frequency in any given population, and the latter allows accurate phasing and the analysis of structural variation. By including these new populations, we want to investigate three crucial questions in African history in addition to the initial objectives: the Bantu expansion, the evolutionary history of hunter gatherers and the transatlantic slave trade. Additionally, the expanded dataset will help us better discover the genetic variation present in Africa and characterize the African pangenome. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001003602

High-throughput telomere length measurement at nucleotide resolution using the PacBio high fidelity sequencing platform, P49-P104 and run1 replicates

Telomeres are specialized nucleoprotein structures at the ends of linear chromosomes that are essential for the stability as well as the complete replication of the human genome. The progressive shortening of steady-state telomere length in normal human somatic cells is a promising biomarker for age-associated diseases. However, there remain substantial challenges in quantifying telomere length in clinics and research laboratories due to the lack of accurate and high-throughput telomere length measurement method. Here, we describe a novel workflow to capture and analyze telomeres accurately at the single-nucleotide resolution. By using newly designed telobaits that are complementary to the single-stranded G-rich 3’ telomeric overhangs, we can specifically and efficiently capture full-length telomeres and subject them to single-molecule real-time (SMRT) sequencing. We show that the telomere length can be measured at nucleotide resolution using the PacBio high fidelity (HiFi) sequencing platform, which provides the necessary accuracy and throughput to uncover the steady-state telomere length distribution in human culture cell lines as well as clinical patient samples. This new method is a valuable tool not only in population-wide epidemiology studies but also for the longitudinal assessment of telomere attrition in individuals. Our results also reveal the extreme heterogeneity of telomeric variant sequences (TVSs) that is dispersed throughout the telomere repeat region. Importantly, the unique distribution pattern and sequence of TVSs in individuals may be used as a fingerprint for sample identification. In addition, the presence of TVSs disrupts the continuity of the canonical (5’-TTAGGG-3’)n telomere repeats, which could affect the binding of shelterin complexes at the chromosomal ends. Therefore, TVSs may act as a form of genetic polymorphisms that impairs telomere protection. Together with the absolute telomere length in each individual, TVSs may have profound implications in human aging and diseases.

Study EGAS00001006595

One-step generation of tumor models by base editor multiplexing in adult stem cell-derived organoids

Recent optimization of CRISPR/Cas9-mediated genome engineering has resulted in the development of base editors that can efficiently mediate C>T and A>G transitions. Combining these genome engineering tools with human adult stem cell (ASC)-derived organoid technology holds promise for disease modeling. Here, we demonstrate the application of base editors for the generation of complex tumor models in human ASC-derived hepatocyte, endometrial and intestinal organoids. First, using conventional and evolved Cas9-variants, we show efficacy of both cytosine and adenine base editors and use them to model four hot-spot point mutations in CTNNB1 in hepatocyte organoids. Next, we apply C>T base editors in endometrial organoids to insert nonsense mutations in PTEN and demonstrate tumorigenicity even in the heterozygous state. Furthermore, we use cytosine base editors for simultaneous oncogene activation (PIK3CA) and tumor-suppressor inactivation (APC and TP53). To increase the flexibility of base editor multiplexing, we then combine SpCas9 and SaCas9 base editors for simultaneous C>T and A>G editing at individual target sites. Finally, we show the power of base editor multiplexing by modeling colorectal tumorigenesis in a single step by simultaneously transfecting sgRNA’s targeting four cancer genes. Seven clonal organoid lines and one bulk wild-type control sample were paired-end whole-genome sequenced using the Illumina Novaseq 6000 system. We sequenced four clonal intestinal organoid lines harbouring engineered TP53 and FBXW7 mutations as well as three lines targeted for oncogenic APC/TP53/PIK3CA/SMAD4 mutations. This WGS showed, as previously reported, a genome-wide increase in C>T mutations due to C>T base editor off-target activity, which is not enriched in predicted off-target regions based on the sgRNA sequences. Furthermore, we confirmed the absence of editing-induced driver mutations and lack of off-target mutational hotspots created by the genomic engineering.

Study EGAS00001006886

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

A circulating biomarker for severity of facioscapulohumeral muscular dystrophy

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

Study EGAS00001007350

Dataset for Sarcoma RNA sequencing linked from study EGAS00001004813

Sequencing data of 410 sarcoma tumor runs, which were uploaded to EGAS00001004813. The sequencing was always paired.

Dataset EGAD00001010276

Molecular characterization of Barrett’s esophagus at single cell resolution

Backgrounds & Aims: Patient with Barrett’s esophagus (BE) have an increased risk to develop esophageal adenocarcinoma and are under periodical endoscopic surveillance for malignant transformation. Pathologists distinguish between different BE stages to identify high-risk patients, but this process remains difficult as stage-specific markers are still missing. We established BE organoid cultures, applied single cell sequencing approaches to identify differences in gene expression and genomic alterations, and validated candidate genes for their predictive value on histological sections. Methods: We collected 43 epithelial biopsies from 21 patients, established organoids for the clonal expansion of matching healthy and diseased tissue from two patients to identify genomic alterations by whole genome sequencing (WGS). We performed single cell DNA-sequencing (scDNAseq) to analyse DNA alterations within biopsies from 8 patients and single cell RNA-sequencing (scRNAseq) to identify gene expression differences between BE stages from 19 patients. Candidate marker genes were then validated by RNA in situ hybridization experiments on histological resection specimen. Results: Most BE biopsies were chromosomal stable (CS) and their single base substitution (SBS) signatures were indistinguishable from the healthy control tissues. Dysplastic BE cells contained areas of chromosomal instabilities (CIN), which differed by the presence of the SBS17 signatures from biopsy-matching CS cells or patient-matching healthy control cells. Such CIN areas affected efficient clustering of the scRNAseq data. We identified two sets of marker genes (SLC5A5, PSCA, LIPF and ANPEP, CEACAM6, REG4), which distinguish columnar BE epithelium from non-dysplastic/dysplastic stages. CLDN2 allowed the distinction between dysplastic and more advanced stages as its expression level increased and spread in dysplastic BE glands. Conclusions: Molecular characterization of BE samples identified a correlation between the presence of CIN and COSMIC signature 17, and we report seven marker genes that help in distinguishing different BE stages.

Study EGAS00001005221

Copy-Number Analysis of Understudied Black Women Ovarian Cancers

Two general types of genetic alterations drive cancer progression: mutations and copy number alterations (CNAs). With the exception of p53, single nucleotide variant mutations (here, simply "mutations") are not drivers of 80% of tumors within the most frequent and deadly histotype of ovarian cancer: serous ovarian cancer (SOC). Rather, CNAs are more prevalent in SOC than any other cancer type studied by phs000178 The Cancer Genome Atlas (TCGA). Fully two-thirds of genes are altered by CNAs in the average SOC. Bioinformatic methods have shown that these CNAs modulate specific molecular pathways, such as autophagy, and this finding enabled effective pathway-targeted therapies1. Unfortunately, TCGA ovarian cancer data lacks racial diversity. Only 6% of SOC tumors (n=32) studied are from African origin. Black women diagnosed with ovarian cancer are more likely to die from their disease than white women. Five-year survival after diagnosis is 31% among blacks versus 42% among whites, and this disparity is seen in every age group and tumor stage distribution. Dr. Kelemen examined data from 365 white and 95 black ovarian cancer patients from the Hollings Cancer Center (HCC) Cancer Registry between 2000 and 2015 and found that black women had an 81% higher risk of death after diagnosis compared to white women (HR 1.81, 95% CI 1.35-2.43), independent of diagnosis center (98% were treated at HCC but half were diagnosed elsewhere), tumor stage, histology, extent of residual tumor remaining following surgery, insurance status, smoking, type of treatment for ovarian cancer, and age-adjusted Charlson comorbidity index. This disparity remained even when restricted to women who received the standard of care, surgery-chemotherapy sequence (HR 1.79, 95% CI 1.10-2.89). Despite receiving the same treatment, black race was still associated with inferior survival. A similar disparity has been reported by others, indicating that the HCC experience is representative of national data. Here, an additional set of high-grade serous ovarian cancer primary tumors were acquired from biorepositories with a focus on expanding data originating from African American women. Data were analyzed for copy-number alterations using exome sequencing and control-FREEC software.

Study phs002313

Ulcerative Colitis Human Microbiome Project (UCHMP)

The aims of the multi-center Ulcerative Colitis Human Microbiome Project (UCHMP) are to examine the role of the enteric microbiome in causing human ulcerative colitis, specifically the development of pouchitis. Pouchitis is an inflammatory condition of the surgically-created ileoanal pouch that serves as a pseudo-rectum in patients with ulcerative colitis who have undergone a total colectomy. It is a condition unique to ulcerative colitis (UC), as it rarely occurs in non-UC patients who have the same procedure. Within one year, about 50% of patients will develop pouchitis. The condition is almost certainly due to aspects of the pouch microbiota on a background of genetic susceptibility, as most patients respond to treatment with antibiotics. While there have been reports on the microbiota in pouchitis patients, all have been performed after the inflammatory process is initiated, rendering interpretation of the results difficult, as the inflammatory process itself will change the microbiota. Our project is therefore unique and possibly the only opportunity in the role of the enteric microbiome in IBD in a prospective manner, thereby establishing potentially important causal relationships between microbiota structure or function and development of UC.The studies also offer two additional advantages. First, the development of the pouch microbiota can be observed prospectively. Second, the cause of antibiotic treatment failure in some patients with pouchitis may be revealed. The two aims are (1) to identify causal factors in the structure and/or function of the enteric microbiota in the development of pouchitis, and (2) to determine the basis of treatment failure in UC pouchitis patients. Our analyses will include serial measurements of enteric microbial structure (16S rRNA gene-based), function (metagenomics and functional candidate genes), and cultivation, the latter to enhance interpretation of gene sequences derived from metagenomes and targeted gene surveys (either functional or 16S genes). The insights gained from these studies will help us understand the fundamental and causative roles of the enteric microbiome in human inflammatory bowel diseases (IBD). This information will be the basis for developing strategies to restore host-microbial relationships to prevent and treat IBD.

Study phs000262

A New Reference Panel to Boost African American Genotype Imputation

Modern genetic studies have been conducted predominantly in cohorts of individuals of European ancestry. By 2010, there were approximately ten times as many published genome wide association studies (GWAS) in people of European ancestry than studies in people of all other ancestries combined. This research disparity has led to an uneven understanding of the genetic basis underlying disease in Europeans and non-Europeans. 23andMe's web-based, large scale research model is ideal for scaling genetics research within non-European populations and thereby bringing more parity to genetics research. Our database is composed of genotypes and phenotypes of over 1,000,000 consenting customers, including over 200,000 individuals with non-European ancestry. The data derived from non-European individuals represent a particularly valuable resource for genetic discovery of novel variants that may not be found in the European population. However, research studies in non-European populations are weakened by the lack of availability of large-scale reference datasets and, in particular, genotype imputation panels. Genotype imputation is a statistical methodology that uses observations of genotypes in a large reference panel to infer unobserved genotypes in a target dataset. This methodology is widely used within GWAS, and allows novel genetic associations to be identified and refined. Due to this utility, very large reference panels have been constructed, containing thousands or tens of thousands of whole genome sequences. Unfortunately, the largest imputation panels are composed of predominantly European genomes, reflecting the modern bias towards European studies in GWAS. This proposal aims to address this imbalance by constructing an imputation panel specifically for the African American population. In doing so, we will expand 23andMe's ability to perform genetic discovery in non-European populations, and improve the understanding of global genetic variation underlying diseases and traits. Key commercial outcomes of the research include the identification of novel genetic targets for internal and external therapeutic development. The long-term aim is to improve understanding of disease in minority populations, which we hope may eventually lead to improved treatments of disease in these historically medically understudied groups.

Study phs001798

A Single Cell Atlas of Gene Regulatory Elements in the Human Heart

Background: Cis-regulatory elements such as enhancers and promoters are crucial for directing gene expression in the human heart. Dysregulation of these elements can result in many cardiovascular diseases that are major leading causes of morbidity and mortality worldwide. In addition, genetic variants associated with cardiovascular disease risk are enriched within cis-regulatory elements. However, the location and activity of these cis-regulatory elements in individual cardiac cell types remains to be fully defined. Methods: We performed single nucleus ATAC-seq and single nucleus RNA-seq to define a comprehensive catalogue of candidate cis-regulatory elements (cCREs) and gene expression patterns for the distinct cell types comprising each chamber of four non-failing human hearts. We used this catalogue to computationally deconvolute dynamic enhancers in failing hearts and to assign cardiovascular disease risk variants to cCREs in individual cardiac cell types. Finally, we applied reporter assays, genome editing, and electrophysiogical measurements in in vitro differentiated human cardiomyocytes to validate the molecular mechanisms of cardiovascular disease risk variants. Results: We defined >287,000 candidate cis-regulatory elements (cCREs) in human hearts at single-cell resolution, which notably revealed gene regulatory programs controlling specific cell types in a cardiac region/structure-dependent manner and during heart failure. We further report enrichment of cardiovascular disease risk variants in cCREs of distinct cardiac cell types, including a strong enrichment of atrial fibrillation variants in cardiomyocyte cCREs, and reveal 38 candidate causal atrial fibrillation variants localized to cardiomyocyte cCREs. Two such risk variants residing within a cardiomyocyte-specific cCRE at the KCNH2/HERG locus resulted in reduced enhancer activity compared to the non-risk allele. Finally, we found that deletion of the cCRE containing these variants decreased KCNH2 expression and prolonged action potential repolarization in an enhancer dosage-dependent manner. Conclusion: This comprehensive atlas of human cardiac cCREs provides the foundation for not only illuminating cell type-specific gene regulatory programs controlling human hearts during health and disease, but also interpreting genetic risk loci for a wide spectrum of cardiovascular diseases.

Study phs002204

14305 results for ""Pennsylvania+German"+ACS+study+'Socius'+open+access"

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