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• A microRNA-signature that correlates with cognition and is a target against cognitive decline

  While some individuals age without pathological memory impairments, others develop age-associated cognitive diseases. Since changes in cognitive function develop slowly over time in these patients, they are often diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. Thus, there is great need for the identification of inexpensive and minimal invasive approaches that could be used for screening with the aim to to identify individuals at risk for cognitive decline that can then undergo further diagnostics and eventually stratified therapies. In this study we use an integrative approach combining the analysis of human data and mechanistic studies in model systems to identify a circulating 3-microRNA signature that reflect key processes linked to neural homeostasis and informs about cognitive status. We furthermore provide evidence that expression changes of this signature represent multiple mechanisms de-regulated in the aging and diseased brain and are a suitable target for RNA therapeutics.

  Study EGAS00001005627

• Genomic Studies of Bipolar Disorder in a Large Cohort from The Netherlands

  The transcriptomes of whole blood samples of a large cohort of individuals from the Netherlands were assayed using RNA-seq. These whole blood samples included patients diagnosed with schizophrenia or bipolar disorder, family members of patients, and healthy controls. Within the whole blood dataset, about 600 of the samples were sequenced to an average of 13.9 million mapped reads per sample, while about 2,000 were sequenced to an average of 5.9 million mapped reads per sample, in order to assess changes in power to detect eQTLs based on sample size. We find that expression, defined as the log transcripts per million reads (TPMs), is highly correlated when comparing the moderate (13.9M) and lower (5.9M) coverage datasets. Additionally, a subset of about 150 individuals provided fibroblast cell lines which were assessed for the levels of gene expression using RNA-seq at an average of 50 million mapped reads per sample. We use downsampling techniques to generate synthetic datasets derived from this real fibroblast RNA-Seq data to explore the relationship between coverage and number individuals in an eQTL analysis. Corresponding individual-level genotypes for the samples included in the expression matrix are also made available. The genotypes were derived from multiple other project cohorts, each using different genotyping platforms including OmniExpress Exome, Global Screening Array, Illumina550, and PsychChip. A Plink file set of these cohorts is provided here after merging the separate project file sets and extracting only the individuals who have expression data also provided here; quality control for SNP-missingness is recommended. We demonstrate in this study that given a fixed budget, eQTL discovery power can be increased by lowering the sequencing depth per sample to allow for an a greater number of individuals sequenced. 

  Study phs002856

• Epigenetic memory of SARS-CoV-2 mRNA vaccination in monocyte-derived macrophages

  Immune memory is key to effective antimicrobial responses, but the impact of mRNA vaccines on this process is not fully understood. Our research shows that SARS-CoV-2 mRNA vaccines alter the epigenetic profile of human macrophages, specifically enhancing histone acetylation, which is linked to immune training. Significant epigenetic changes, along with increased cytokine release, require two vaccine doses. However, these effects diminish over time but can be restored with a booster dose six months later, maintaining a strong pro-inflammatory response.

  Study EGAS50000000341

• Kids First: Whole Genome Sequencing in Structural Defects of the Neural Tube

  Myelomeningocele (aka meningomyelocele, MM) is the most severe form of spina bifida, a neural tube defect (NTD) in humans and the most common CNS birth defect. MM is considered a genetically complex disease, and occurs in 3.72/10,000 live US birth, and is partly preventable with prenatal folate, but the genetic basis and the mechanisms by which folate work to reduce disease incidence remain obscure. MM is associated nearly uniformly with prenatal hydrocephalus and the Arnold-Chiari malformation, as well as paraplegia and lifelong neuromotor disability. The genes for several rare syndromic forms of NTDs are known, but the causes for the majority with sporadic MM remain unknown. Despite the importance of MM, most previous research has been limited to targeted sequencing and association studies of folate metabolism genes, or very small-scale exome sequencing. We hypothesize that de novo mutations (DNMs) produce likely gene disrupting (LGD) events that contribution to MM risk. Using conservative estimates of between 50-100 recurrently mutated discoverable genes contributing to risk, and our preliminary data demonstrating an excess of LGD DNMs in MM compared with control individuals, we estimate that with a cohort size of 1000 trios, we should uncover between 5-20 new recurrently mutated genes underlying MM, with minimal false-discovery. With this in mind, we formed the Spina Bifida Sequencing Consortium, and established a platform for data and sample sharing. Preliminary analysis of our first batch of 100 trios analyzed by WGS from GMKF suggests a wealth of important gene mutations. We have embarked on a new recruitment effort of an additional cohort of 400 new simplex MM trios, in collaboration with the US Spina Bifida Association, consented trios to allow for data sharing, and have performed detailed sample quality control. We also have preliminary data that use of dried bloodspot DNA from trios performs comparably to whole blood DNA, so will be happy to swap saliva for bloodspot recruitment at NIH's preference. This cohort is now half-way assembled, with the remaining cohort to be ascertained in the next 6 months. We have established a workflow for de novo SNP/INDEL/SV detection from WGS and have ample computer storage and nodes to see the project to completion. We also plan to continue recruitment into the future with the goal of 2000 trios in the next 5 years. We propose a detailed bioinformatics workflow to identify gene mutations within a statistical framework, considering detailed scRNA expression profiling from developing mammalian neural tube, and have developed a robust functional validation workflow using Xenopus and mouse gene targeting. Our project has the potential to uncover a host of causes for this most common of the CNS birth defects, paving the way for future breakthroughs in detection, treatment, and prevention.

  Study phs002591

• Exome Sequencing of Schizophrenia Cases and Controls in the South African Xhosa Population

  The goal of this international collaborative project is to identify genes responsible for Schizophrenia in the Xhosa population of South Africa. The vast majority of the genetic basis for Schizophrenia has yet to be explained. We hypothesize that genes and pathways important to Schizophrenia will harbor different, severe disease-causing mutations in different affected individuals. Given the genetic diversity of African populations, we expect to find genes for Schizophrenia that have not yet emerged from studies of other populations. This project will also foster the development of gene discovery research for neuropsychiatric disorders in Africa. Our approach will identify genes important for the disorder in populations worldwide. These genes will stimulate future efforts to develop more effective treatment and prevention strategies.

  Study phs000959

• Collaborative Association Study of Psoriasis

  The goal of this collaborative study is to combine the resources and expertise of three groups with long-standing studies of psoriasis genetics in order to identify new genetic susceptibility factors for psoriasis, a common inflammatory skin disease that affects over 4 million Americans. Consent groups and participant set General research use (GRU): 1677 (950 cases, 692 controls, 35 others) Autoimmune disease (AD): 1198 (449 cases, 734 controls, 15 others)

  Study phs000019

• Brazilian Thyroid WES

  Medullary thyroid cancer (MTC) is a rare malignant tumor that arises from parafollicular cells. Approximately 8% of thyroid cancer cases are MTC, and about 25% of these have a hereditary component. Incorporating molecular parameters into tumor classification is important. Besides, the presence of pathogenic germline variants can impact directly on cancer prevention. Thus, the aim of this study was to perform whole exome sequencing (WES) on a consecutive series of hereditary RET wild-type MTC patients to identify genetic variants that may be involved in the carcinogenesis of this tumor. WES was performed on 28 patients negative for germline RET pathogenic variants using the NovaSeq 6000 platform. Variant classification followed American College of Medical Genetics and Genomics guidelines.Our study represents a significant advancement in gene discovery for MTC genetics.

  Dataset EGAD50000000086

• Preeclampsia InterPregGen Consortium: Whole Genome Sequencing of 100 unrelated Uzbeks (DNA samples from the Institute of Immunology, Uzbek Academy of Sciences, Tashkent, Uzbekistan; Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology, Tashkent, Uzbekistan)

  Whole genome sequencing of 100 unrelated Uzbeks in order to impute genotypes into PE cases and controls from Uzbekistan and to provide genetic data and infrastructure for future genetic studies in Uzbekistan and Central Asia more generally and to fill a gap in worldwide information as Central Asia is not adequately represented in available genomic data. This dataset is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators in Tashkent, Uzbekistan at the Institute of Immunology, Uzbek Academy of Sciences and at the Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology.

  Dataset EGAD00001005466

• Gut microbiome dynamics unravelled with metagenomics sequencing

  It has been already several years since we discovered that microbial therapeutics like Faecal Microbiota Transplantation can be used to treat Clostridium difficile infection (CDI) and Inflammatory bowel disease (IBD) with great success. The concept has challenged us to test the limits of our knowledge with the perspective to improve health in the most diverse conditions like Parkinson disease, depression, autism and obesity, just to mention a few. Note: the figure belongs to the original paper and is owned by the authors. Allyson L.Bird and colleagues from Genentech Inc. (San Francisco) recently published an interesting study building up on the key concept that “As microbial therapeutics are increasingly being tested in diverse patient populations, it is essential to understand the host and environmental factors influencing the microbiome.” The authors of this work analysed 1359 gut microbiome samples using shotgun metagenomics sequencing.  The results of the comparison done between microbiota composition across the different groups showed that biological sex is the strongest driver of diversity, while aging (age range studied: 20–69) appears to be the second factor. As smartly outlined in the authors’ own graphical abstract (figure to the left), Bacteroidota species consistently increased with donors' age while Actinobacteriota species, including Bifidobacterium, decreased. This study also integrated data from oncological patients to draw cancer-related evidences. After correcting the biases for technical and geographic differences, they found that cancer patients show significantly altered gut bacterial communities compared with their healthy counterparts. Eg. E.coli was found to be increased in cancer patients together with Bacteroidota/Firmicutes ratios. By comparing sequential samples taken from the same donors (413) within short-distance time points, the authors found that in the short term, intra-individual differences were less than the inter-individual ones, indicating a certain community stability being the norm. One of the pivotal points from this interesting study is that the data proceeds from extremely well-defined and selected donors. Specifically, the data for 949 selected healthy donors came from the Milieu Intérieur (MI) Consortium and extensive metadata, including demographic variables, serological measures, dietary information, and systemic immune profiles, are available. This precise stratification allowed for the robust detection of smaller changes, compared to former works. All sequencing data has been deposited in the EGA archive under the accession number EGAS00001004437. Enjoy this amazing open access paper published in the Experimental Journal of Medicine on January 2021.

  Blog gut-microbiome-dynamics-unravelled

• Kidney tumour_DNA (2018-09-19)

  This is a bulk DNA and RNA sequencing study of human renal tumours . This dataset contains all the data available for this study on 2018-09-19.

  Dataset EGAD00001004346

• EORTC study on the evolution of driver mutations and MGMT promotor methylation in glioblastomas treated with standard of care: Correlation with survival and impact on trial design

  Precision medicine trials in glioblastoma should be conducted at tumor recurrence. However, second surgery for recurrent GBMs is not routinely performed and therefore molecular data is predominantly derived from primary samples. This study aims to establish the frequency of driver changes at tumor recurrence.

  Dataset EGAD00001004593

• Rapid Acceleration of Diagnostics - Digital Health Technologies (RADx-DHT): NIH Digital Health Solutions for COVID-19: IBM Covid19 Contact Tracing and Data Exchange Tools

  The goal of this project is to develop both contact tracing and secure data exchange tools. The contact tracing solution securely combines data from a variety of sources (including manual self-report data and mobile device surveys) to enable tracing of contacts with individuals that have tested positive for COVID-19 or have been exposed to COVID-19. The data exchange solution is a secure mechanism that empowers users to control the data they share in the course of their return to work, including the ability to provide a verifiable health status claim. These tools are being used by an employer to evaluate the risk of allowing individuals to return to normal activities, and also the ability to trace user contact with individuals diagnosed with or suspected of having contracted COVID-19. DOI: https://rapids.ll.mit.edu/10.57895/h0an-m559

  Study phs002516

• Exploring the Microbiome-Gut-Brain Axis with Respect to Psychoneurological Symptoms for Children with Solid Tumors

  The human body hosts tens of trillions of microbes, a number 10 times greater than the number of human body cells. The collection of these human-associated microbes and their genomes is called the “human microbiome”. More than 90% of these microbes live in the gastrointestinal (GI) tract, representing 500 species on average. With the development of high-throughput sequencing technology and bioinformatics tools (e.g., 16S ribosomal RNA or 16S rRNA sequencing and shotgun metagenomics analysis), recent progress has been made to elaborate the critical role that the gut microbiome plays in human health and disease. A significant disruption (dysbiosis) of the composition and function of the gut microbiome is associated with carcinogenesis, chemotherapeutic metabolism, and treatment-related symptom toxicities. The current state of science on the gut microbiome in cancer has only recently started in animal models and adults, and has not been well investigated in children diagnosed and treated for cancer, nor with respect to associations with cancer treatment-related toxicities. This proposed study will explore the hypothesis that dysbiosis of the gut microbiome is associated with cancer treatment-related GI and psychoneurological symptoms. We will collect both stool samples (for the gut microbiome) and patient-reported outcomes across chemotherapy.

  Study phs002960

• National Institute on Aging (NIA) SardiNIA Study

  Sardinia is the second largest island in the Mediterranean and constitutes a genetically isolated founder population. This population has aided in the identification of genes involved in several Mendelian disorders and is attractive for genetic studies due to its organization in long-established settlements that developed from an initial group of founder settlers (~1,000) thousands of years ago. The current study has recruited 6,148 Sardinians aged 14 and older, from a cluster of four towns in the Lanusei Valley in the Ogliastra region of the province of Nuoro. This sample corresponds to approximately 62% of the population eligible in the area for recruitment. Information collected during enrollment allowed the individuals to be organized into 711 complex pedigrees, each up to five generations deep, with an average kinship coefficient of 0.1628. All volunteers have been characterized for 98 quantitative traits. Traits include anthropomorphic measures, plasma and serum markers (including cholesterol and other markers of cardiovascular disease), and personality traits (using the five-factor model). The main goal of the study is to examine phenotypic similarities between relatives that yield information on the overall contributions of genes to trait variability. Data given here provide p-values for 98 traits studied in 1,412 individuals, based on genotyping with the Affymetrix 500K chip and imputed markers using the HapMap population as a reference (N=2,259,179). Sharing this genome assessment data at high level of resolution for a variety of quantitative traits will be useful for other groups to validate newly observed associations and to investigate possible pleiotropic effects. For ulterior information, and in particular for any individual genotype information, a formal request should be addressed to the Steering Committee, c/o David Schlessinger, Chief, Laboratory of Genetics, National Institute on Aging, National Institutes of Health, NIH Biomedical Research Center, 251 Bayview Blvd., Suite 100 Baltimore, MD 21224 USA and should include IRB approval of a detailed proposal, along with a signed statement guaranteeing that no attempt will be made to identify any individual participant.

  Study phs000338

• Upcycling and merging data to challenge the dogma and identify new therapeutic targets for Glioblastoma

  Glioblastoma is the most common brain tumour. Characterised by a poor prognosis and its recurrence after multimodal treatments, the search for preventable risk factors has been mainly inconclusive up to date. Recently, the data merge from datasetsdeposited at the EGA allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. Challenges in glioblastoma research As for virtually all cancer types, many efforts have been made to unveil the molecular features responsible of the disease, and several cellular pathways have indeed been identified as being frequently mutated in glioblastoma. Nonetheless, targeted therapies based on identified genes have so far failed to improve outcome, thus survival mostly relies on a standard treatment unchanged since 2005. This is a frustrating situation for both the scientific and medical communities, and above all for the patients, still facing a dreadful path. Some researchers hypothesised that this may be due to the inability to efficiently target cancer stem cells, the originators of the other cell types, thus inducing cancer relapse. In 2019 Charles P. Couturier and colleagues sequenced RNA from single cells of freshly excised glioblastomas of 16 patients, and demonstrated that glioblastoma cells replicate normal brain cell development with a conserved neural cancer cell hierarchy centered around glial progenitor-like cells. In this way, they helped identify the possible target cells to improve efficacy and durability of treatment. Data upcycling at the EGA: the glioblastoma case study Single cell RNA sequencing is generated with a laborious and expensive protocol. The quality of the starting material is crucial (cells sample freshly extracted from the patients) and often several attempts are needed before producing reliable quality sequencing results. Collecting big numbers of patients is also challenging. The sequencing data produced by Kevin Petrecca’s group in Montreal, Canada and deposited at the EGA (EGAS00001004422) was recently upcycled by Lin Wang in San Francisco, California and pooled with their freshly produced ones, and then deposited at the EGA as Dataset EGAS00001004909 The data merge allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. They profiled 86 primary-recurrent patient-matched paired glioblastoma samples with single-nucleus RNA, among other techniques. These very comprehensive results lead the team to challenge the findings from several other cancer fields where chemotherapy standard chemo-radiation therapy selection pressure at the level of genomic alterations; this is indeed not the case for glioblastoma, where the pressure results in phenotypic transition between cellular states. Several technical controls were made to ensure that the merge of the data was not introducing a bias in the results, and an Inter-table analysis demonstrated nearly equal contribution to overall variance from each of the studies included, indicating that the findings were not due to inter-laboratory technical effect. A novel principal-component analysis showed that the largest contribution to variation in primary glioblastoma neoplastic cells was an axis between MES (mesenchymal) and proneural expression programs. In summary, treating glioblastoma often makes a MES, as commented by Lucy Stead about this remarkable work. Check Aaron Diaz’s team Nature Cancer paper, with strong technical tools, state of the art analysis and data from different sources converging to the same outcomes that made possible a significant step toward a better handling of a frightful cancer. References Couturier, C.P., Ayyadhury, S., Le, P.U. et al. Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. Nat Commun 11, 3406 (2020). Stead, L.F. Treating glioblastoma often makes a MES. Nat Cancer 3, 1446–1448 (2022). Wang, L., Jung, J., Babikir, H. et al. A single-cell atlas of glioblastoma evolution under therapy reveals cell-intrinsic and cell-extrinsic therapeutic targets. Nat Cancer 3, 1534–1552 (2022). Related links: Kevin Petrecca’s group dataset deposited at the EGA: EGAS00001004422 Lin Wang dataset deposited at the EGA: EGAS00001004909

  Blog upcycling-and-merging-data-to-challenge-glioblastoma

• Reliable assessment of telomere maintenance mechanisms in neuroblastoma

  Telomere maintenance mechanisms (TMM) are a hallmark of high-risk neuroblastoma, and are conferred by activation of telomerase or alternative lengthening of telomeres (ALT). However, detection of TMM is not yet part of the clinical routine, and consensus on TMM detection, especially on ALT assessment, remains to be achieved. We here propose a workflow to reliably detect TMM in neuroblastoma. We show that unambiguous classification is feasible following a stepwise approach that determines both, activation of telomerase and ALT. The workflow proposed in this study can be used in clinical routine and provides a framework to systematically and reliably determine telomere maintenance mechanisms for risk stratification and treatment allocation of neuroblastoma patients.

  Study EGAS00001006510

• Double mutant DNMT3A AML: a unique subtype

  Mutation of DNMT3A, encoding a de novo methyltransferase essential for cytosine methylation, is a common early event in clonal hematopoiesis (CH) and adult acute myeloid leukemia (AML). Spontaneous deamination of methylated cytosines damages DNA, which is repaired by the base excision repair (BER) enzymes MBD4 and TDG. Congenital MBD4-deficiency has been linked to early-onset CH and AML, and is marked by exceedingly high levels of DNA damage and mutation of DNMT3A. Strikingly, wildtype (WT) DNMT3A binds TDG, thereby potentiating its repair activity. Since TDG is the only remaining BER enzyme in MBD4-deficient AML patients capable of repairing methylation damage, we investigated whether mutant DNMT3A negatively affects the repair function of TDG. We found that, whereas WT DNMT3A stimulates TDG function, mutant DNMT3A impairs TDG-mediated repair of DNA damage in vitro. In light of this finding and to extrapolate our observations to the broader AML patient population, we investigate here the genetic profiles and survival outcomes of AML patients with single (SM) versus double mutant (DM) DNMT3A. DM DNMT3A AML patients show a characteristic driver mutation landscape and reduced overall survival when compared to SM DNMT3A AML patients. Importantly, whole-genome sequencing showed a trend for increased DNA damage in primary DM DNMT3A AML samples, especially when DNMT3A mutations are located at the DNMT3A-TDG interaction interface.

  Study EGAS00001007966

• bulk RNAseq analysis of tumor from 3 non-muscle-invasive bladder cancer patients

  We performed screenings of patient-specific neo-epitopes by tumor-infiltrating CD8+ T lymphocytes of 4 non-muscle invasive bladder cancer patients. After the tumor resection, these patients went on to receive BCG treatment as they had high-risk disease. In order to select the neo-epitopes, we performed bulk RNAseq of the bladder tumor to select the mutated genes that were expressed in the tumor (TPM >1). For patient UC2, 3 different tumors were resected at the same time and RNA from these 3 tumors were sent separately for RNAseq. For patient UC4, no RNA was available, so this patient is not included in this study.

  Study EGAS50000001383

• ApoA-1 and Atherosclerosis in Psoriasis

  Apolipoprotein A-1 is a protein localized to high-density lipoprotein that functions to remove cholesterol from tissues for transport back to the liver. Psoriasis is a systemic inflammatory disease associated with poor high-density lipoprotein function and accelerated non-calcified burden by coronary computed tomographic angiography. In this study, 310 psoriasis patients from The Psoriasis, Atherosclerosis, and Cardiometabolic Disease Initiative (PACI) were studied at baseline to determine if levels of circulating apolipoprotein A-1 predict early onset coronary artery disease in inflammatory conditions. Of the 310 participants, 124 were followed for four years to determine if apolipoprotein A-1 predicts non-calcified coronary burden over time. The primary outcome of this study was non-calcified coronary burden by coronary computed tomography angiography. To assess non-calcified coronary burden, participants underwent coronary computed tomography angiography using the same scanner (320-detector row Aquilion ONE ViSION, Toshiba, Japan). For ApoA-1 quantification, fasting blood draw was performed the same day as the coronary computed tomography angiography. The 400MHz proton Vantera Clinical Analyzer was used to quantify Plasma apolipoprotein A-1. The study determined that low levels of apolipoprotein A-1 are associated with increased coronary artery burden and that this relationship persists over time. The data are available through dbGaP and the dataset includes all variables reported in the manuscript.

  Study phs003231

• Single cell RNA seq of breast cancer stem cells

  RNA sequences of breast cancer have been investigated for many patients. Recently it has been shown that there are intra-heterogeneity in tumor tissues. When the tumor cells were sequenced in bulk condition, only the major populations' mRNA will be detected. With respect to breast cancer, it has been also reported that cancer cells can sub-gropued into cancer stem cells and non-cancer stem cells. Although the mRNA expressions' difference between this two groups has been profoundly investigated, whether each group is composed by unique cell or not is yet to be elucidated. Since cancer stem cells are the thought to be the major contributor of metastasis and/or recurrence, we focused on cancer stem cells in this study. We separated cancer cells into cancer stem cells and non-cancer stem cells exploiting cancer stem cell specific surface markers. Thereafter, we sequenced mRNA of cancer stem cells in single cell resolution. From this result, we examined whether these cells can be sub-grouped or not.

  Study JGAS000305

• Comprehensive analyses of somatic TP53 mutation in tumors with variable mutant allele frequency

  Somatic mutation of the tumor suppressor gene TP53 is reported in at least 50% of human malignancies. Most high-grade serous ovarian cancers (HGSC) have a mutant TP53 allele. Accurate detection of these mutants in heterogeneous tumor tissue is paramount as therapies emerge to target mutant p53. We used a Fluidigm Access Array™ System with Massively Parallel Sequencing (MPS) to analyze DNA extracted from 76 serous ovarian tumors. This dataset has been made available to researchers through the European Genome-phenome Archive (EGA). Herein, we present detailed analyses of this dataset using HaplotypeCaller and MuTect2 through the Broad Institute’s Genome Analysis Toolkit (GATK). We also present comparisons of the ability to detect TP53 mutation by MPS and Sanger sequencing in these tumors. We anticipate that this TP53 mutation dataset will be useful to researchers developing and testing new software to accurately determine high and low frequency variant alleles in heterogeneous aneuploid tumor tissue. Further, the analysis pipeline we present provides a valuable framework for determining somatic variants more broadly in tumor tissue.

  Study EGAS00001002200

• Visium Spatial transcriptomics

  This study consists of the spatial transcriptomics data generated by : Visium CytAssist Spatial Gene Expression for FFPE (10x) for steatotic liver disease-associated hepatocellular carcinoma (SLD-HCC) (n=7) and non-SLD-HCC (n=5) The goal of this data is to compare SLD-HCC vs non-SLD-HCC as well as response to immunotherapy

  Dataset EGAD50000001506

• Next-generation sequencing-based comprehensive genetic analysis of undiagnosed disease

  The purpose of this study is to perform comprehensive genetic analysis using next-generation sequencers to make genetic diagnosis of "undiagnosed diseases".

  Study JGAS000522

• Helleday_HRAS_Project

  This experiment is looking at the mutational signatures generated by engineered HRAS mutations by using whole genome sequence generated on massively parallel next generation sequencers.

  Study EGAS00001000332

• Multiple Myeloma Genomic Study (MMGS)

  Multiple Myeloma (MM) is a plasma cell dyscrasia characterized by bone marrow (BM) infiltration and lytic bone lesions. Recent studies of massive parallel sequencing of tumor cells obtained from the BM of patients with MM have demonstrated significant clonal heterogeneity in MM. Despite this remarkable clonal heterogeneity, it could be envisioned that such clonal diversity may be even higher since single BM samples only represent a small fraction of the whole BM compartment, and the pattern of BM infiltration in MM is typically patchy. In addition, BM biopsies are painful and cannot be repeated multiple times during the course of therapy, indicating a need for less invasive methods to molecularly characterize MM patients and monitor disease progression during the therapy. Thus, optimal characterization of circulating tumor cells (CTCs) may represent a non-invasive method to capture relevant mutations present in PC clones. In addition, MM almost always progresses from precursor states of monoclonal gammopathy of undetermined significance (MGUS)/smoldering multiple myeloma (SMM) to overt MM. However, some patients rapidly progress from MGUS/SMM to overt MM (progressors) with a rate of progression of up to 70% over 5 years, while others remain indolent with minimal progression over the same time period (non-progressors). Although many patients are diagnosed with earlier phases of disease, most patients do not receive treatment until their disease progresses, at which time they have overt end-organ damage. This concept of initiating therapy at the time of symptomatic disease is analogous to initiating therapy in patients with solid tumors only after the development of measurable metastatic disease. It is therefore not surprising that cure is not achieved for most patients with MM. Interestingly, studies have demonstrated that MGUS/SMM clones may already harbor chromosomal alterations (Ig loci or hyperdiploidy) and that progression to MM is mainly due to expansion of clones that were already present in the early stages of MGUS/SMM. However, the biological factors that discriminate progressors from non-progressors in MGUS/SMM are not well known. Therefore, our overarching hypothesis is that an effective therapeutic intervention will result from defining genomic and transcriptomic markers that are associated with disease progression. We believe, therefore, that focused research studies that define molecular mechanisms of clonal evolution in MGUS/SMM/MM will identify novel biomarkers of disease progression and help develop therapeutic agents that prevent or delay progression from MGUS to overt MM. Indeed, by eradicating the disease at the precursor stages, MM may become a preventable disease. Recently, a new term called Clonal Hematopoiesis of Indeterminate Potential (CHIP) has been proposed to describe asymptomatic individuals with hematologic malignancy-associated somatic mutations. Those individuals do not fulfill any diagnostic criteria for any hematological malignancy yet they have a tendency to progress into myelodysplastic syndrome (MDS) or myeloid or lymphoid neoplasia at a rate of around 0.5-1% per year, similar to MGUS. The frequency of CHIP and role of HSCs mutations in enhancing acquisition of somatic mutations in MM plasma cells, allowing progression following treatment, has not been studied. Investigating the dysregulated pathways in early progenitor cells would allow us to understand the reasons of progression and establish novel therapeutic and potentially preventive strategies. This study dissects genomic and transcriptomic characteristics of clonal evolution from MGUS/SMM to MM as well as the characteristics of the tumor microenvironment/immune cells/peripheral blood. Our hypothesis is that molecular biomarkers will be strong predictors of progression from MGUS/SMM to MM and will allow for the development of novel therapeutic agents that prevent or delay this progression. We aim to define genomic and transcriptomic markers that lead to progression from MGUS/SMM to MM in tumor cells, blood biopsies (cell free DNA and circulating tumor cells), and the tumor microenvironment.

  Study phs001323