3735 results for "*oma"

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• Tumor Mutation Burden, Expressed Neoantigen and Immune Microenvironment in Diffuse Gliomas

  A consistent correlation between tumor mutation burden (TMB) and tumor immune microenvironment has not been observed in gliomas as in other cancers. Driver germline and somatic mutations, TMB, neoantigen, and immune cell signatures were analyzed using whole exome sequencing (WES) and transcriptome sequencing of tumor and WES of matched germline DNA in a cohort of 66 glioma samples (44 IDH-mutant and 22 IDH-wildtype). Fourteen samples revealed a hypermutator phenotype (HMP). Eight pathogenic (P) or likely pathogenic (LP) germline variants were detected in 9 (19%) patients. Six of these 8 genes were DNA damage repair genes. P/LP germline variants were found in 22% of IDH-mutant gliomas and 12.5%of IDH-wildtype gliomas (p= 0.7). TMB was correlated with expressed neoantigen but showed an inverse correlation with immune score (R =−0.46, p= 0.03) in IDH-wildtype tumors and no correlation in IDH-mutant tumors. Antigen Processing and Presentation (APP) score correlates with immune score. The APP is higher in non-hypermutator phenotype (NHMP) samples versus HMP samples in the IDH-wildtype gliomas, but higher in HMP samples versus NHMP samples in the IDH-mutant gliomas. Conclusion: TMB was inversely correlated with the immune score in the IDH-wildtype gliomas, and showed no correlation in the IDH-mutant tumors. The APP was correlated with the immune score, and may be further investigated as a biomarker for response to immunotherapy in gliomas. Studies of germline variants in a large glioma cohort are warranted.

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• Multi-Omic Investigation of Beckwith-Wiedemann Syndrome Hepatoblastoma

  Hepatoblastoma (HB) is the most common malignant liver tumor diagnosed in children under 5 years of age. One of the most common HB predisposition syndromes is Beckwith-Wiedemann Syndrome (BWS, OMIM 130650), which affects approximately 1/10,000 live births. In this study, we perform Whole Exome Sequencing (WES), DNA methylation array, messenger RNA-Sequencing (mRNA-Seq), and microRNA-Sequencing (miRNA-Seq) to examine the genomic, methylomic, and transcriptomic signature of BWS HB. We analyzed five tumor-normal paired samples, two BWS tumor only samples, and five non-BWS control samples to identify a predisposition and oncogenic signature of BWS HB development. 

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• The Spatio-Temporal Evolution of Multiple Myeloma from Baseline to Relapse-Refractory States

  In multiple myeloma, the spatio-temporal evolution patterns of cancer cells in the bone marrow remain largely unknown. Here, we applied spatial-longitudinal sequencing, including a total of 179 samples collected from 25 patients during a follow-up of up to 14 years. Our study highlights focal bone lesions (FL) as hotspots of tumor evolution and provides possible explanations for their negative prognostic impact. We show a close phylogenetic relationship between baseline FL and relapse clones. In patients with ≥3 FDG-PET-positive FL at diagnosis, relapse was driven by multiple distinct sub-clones, whereas in other patients, a single-cell expansion was typically seen (p<0.01). Applying imaging-guided sampling, we identified a novel evolutionary pattern with unique treatment-resistant sub-clones at distinct locations. We observed multiple selective clonal sweeps, resistant clones that can be hidden over years, and epigenetic modifier mutations as a new class of relapse aberrations. Here we show that imaging can enhance tumor evolution studies and response assessment. The sophisticated evolution mechanisms in myeloma and presence of single cells that can drive relapse even after 10 years of remission suggest that a prerequisite for curative therapies would be to overcome not only tumor heterogeneity but also dormancy.

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• CIDR: The Role of Rare Coding Variation in Prostate Cancer in Men of African Ancestry - RESPOND Project 2

  In RESPOND Project 2, we seek to identify rare genetic factors that are associated with prostate cancer (PCa) risk and aggressiveness in men of African ancestry (AA). We will conduct exome sequencing of 15,000 prostate cancer cases and 5,000 controls from the RESPOND cohort and the African Ancestry Prostate Cancer Consortium (AAPC) with cases selected based on risk categories: high-risk (stage T3/T4 or Gleason 8+ or PSA>20 ng/ml), intermediate-risk (stage T2b/T2c or Gleason 7 or PSA 10-20 ng/ml) and low-risk disease (stage T1/T2a and Gleason ≤ 6 and PSA<10 ng/ml). We expect the findings from this Project to significantly advance knowledge of susceptibility to aggressive PCa and racial/ethnic disparities in PCa risk, and to guide the development of future preventive, early detection and prognostic measures for AA men. The first phase of the study will include exome sequence data for approximately 7,500 cases and 5,000 controls from AAPC. The second phase of the study will include exome data for 5,000 cases from RESPOND and AAPC.ACKNOWLEDGMENTS and CONTRIBUTING SITES Multiethnic Cohort (MEC): The MEC and the genotyping in this study were supported by National Institutes of Health (NIH) grants CA63464, CA54281, CA1326792, CA148085, and HG004726. Cancer incidence data for the MEC and Los Angeles Study of Aggressive Prostate Cancer (LAAPC) studies have been collected by the Los Angeles Cancer Surveillance Program of the University of Southern California with federal funds from the National Cancer Institute (NCI)/NIH/Department of Health and Human Services (DHHS) under Contract No. N01-PC-35139, and the California Department of Health Services as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885, and grant 1U58DP000807-3 from the Centers for Disease Control and Prevention (CDC). Ghana Prostate Study (GPS): The Ghana Prostate Study was funded by the Intramural Program of the NCI/NIH/DHHS under Contract No. HHSN261200800001E. Men of African Descent and Carcinoma of the Prostate (MADCaP): We thank all MADCaP study participants. This work is a product of the MADCaP network. This work was supported by NCI/NIH grant U01CA184374 to Timothy Rebbeck and National Institute of General Medical Sciences (NIGMS) MIRA grant R35GM133727 to Joseph Lachance. Additional funding includes a seed grant from the Integrated Cancer Research Center at Georgia Institute of Technology. UGANDA: The UGANDA study was supported by NIH grant R01CA165862. Southern Community Cohort (SCCS) is funded by NIH grant CA092447. SCCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt Ingram Cancer Center (CA68485). Data on SCCS cancer cases were provided by Alabama Statewide Cancer Registry, Kentucky Cancer Registry, Office of Cancer Surveillance at Tennessee Department of Health, Florida Cancer Data System, Central Cancer Registry at North Carolina Division of Public Health, Georgia Comprehensive Cancer Registry, Louisiana Tumor Registry, Mississippi Cancer Registry, South Carolina Central Cancer Registry, Virginia Cancer Registry at Virginia Department of Health, and Cancer Registry at Arkansas Department of Health. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries (NPCR)/Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the NPCR/CDC. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. Karuprostate: The Karuprostate study was supported by the French National Health Directorate and by the Association pour la Recherche sur les Tumeurs de la Prostate. Séverine Ferdinand, Marc Romana. The North Carolina - Louisiana Prostate Cancer Project (PCaP) is carried out as a collaborative study supported by the Department of Defense contract DAMD 17-03-2-0052. The authors thank the staff, advisory committees and research subjects participating in the PCaP study for their important contributions. We would also like to acknowledge the UNC BioSpecimen Facility and the LSUHSC Pathology Lab for our DNA extractions, blood processing, storage and sample disbursement (https://genome.unc.edu/bsp). Gene-Environment Interaction in Prostate Study (GECAP) was supported by NIH grant ES011126. King County Prostate Cancer Study (KCPCS) was supported by NIH grants CA056678, CA082664, and CA092579, with additional support from the Fred Hutchinson Cancer Research Center. We thank the participants in these studies, and Ms. Suzanne Kolb for help with study management. The Los Angeles Study of Aggressive Prostate Cancer (LAAPC) was funded by grant 99-00524V-10258 from the Cancer Research Fund, under Interagency Agreement #97-12013 (University of California contract #98-00924V) with the Department of Health Services Cancer Research Program. Cancer incidence data for the MEC and LAAPC studies have been collected by the Los Angeles Cancer Surveillance Program of the University of Southern California with Federal funds from the NCI/NIH/DHHS under Contract No. N01-PC-35139, and the California Department of Health Services as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885, and grant 1U58DP000807-3 from the CDC. Prostate Cancer Studies at MD Anderson (MDA) was supported by grants CA68578, ES007784, DAMD W81XWH-07-1-0645, and CA140388.

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• Microbiome-Host Interactions in Oral Squamous Cell Carcinoma: a Metatranscriptomic Exploratory Study

  Oral cancer (predominantly squamous cell carcinoma; OSCC) is the 14th most prevalent malignancy worldwide, accounting for more than 300,000 new cases and 145,000 deaths annually. Despite advances in cancer treatment modalities, OSCC continues to have poor prognosis with 5-year survival rates less than 50%. Although use of tobacco and alcohol consumption constitute the major risk factors, there is emerging evidence for the role of the microbiome in OSCC. However, studies on the association between the microbiome and OSCC has so far focused on compositional analysis and has been largely limited to the bacterial component of the microbiome. The aim of this study is to characterize the transcriptional activity (function) as well as composition of the multi-kingdom microbiome associated with OSCC and correlate it with the gene expression of the host using ultra-deep metatranscriptome sequencing, which will provide new insight into the role of the microbiome in OSCC and the possible mechanisms by which the tumor’s microbial community may influence on its behavior. This project comprises RNA-Seq data from twenty OSCC tumor/normal tissue pairs and twenty tongue scraping samples from healthy controls. However, due to consent constraints, the human sequences from the control data are filtered out.

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• Combined Tumor and Immune Signals From Genomes or Transcriptomes Predict Outcomes of Checkpoint Inhibition in Melanoma

  Cancer immunotherapy with checkpoint blockade (CPB) leads to improved outcomes in melanoma and other tumor types, but a majority of patients do not respond. High tumor mutation burden (TMB) and high levels of tumor-infiltrating T cells have been associated with response to immunotherapy, and integrative models using DNA and RNA have improved predictions of clinical benefit. However, identification of immune and tumor-intrinsic features in models using DNA or RNA alone have not been comprehensively explored in melanoma. In this study, we sequenced DNA and RNA of tumors from 67 melanoma patients receiving CPB, and aggregated this cohort with previously published data, yielding whole exome sequencing (WES) data for 189 patients and bulk RNA sequencing data for 178 patients. Using these datasets, we derived genomic and transcriptomic factors that predict overall survival (OS) and response to immunotherapy. Using whole exome DNA data alone, we calculated T cell burden (TCB) and B cell burden (BCB) based on rearranged TCR/Ig DNA sequences, and found that melanoma patients with high TMB and either high TCB or high BCB survived longer and had higher response rates, as compared to patients with low TMB and either low TCB or low BCB. Next, using bulk RNA-Seq data, differential expression analysis identified 83 genes which are associated with high or low OS. By combining pairs of immune-expressed genes with tumor-expressed genes, we identified three gene pairs which are associated with response and survival (Bonferroni P<0.05). All three gene pair models were validated in an independent cohort (n=180) (Bonferroni P<0.05). The best performing gene pair model included the lymphocyte-expressed MAP4K1 (Gene ID: 11184) and the transcription factor TBX3 (Gene ID: 6926) which is overexpressed in poorly differentiated melanomas. We concluded that RNA-based (MAP4K1 and TBX3) or DNA-based (TCB and TMB) models combining with immune and tumor measures improve predictions of outcome after checkpoint blockade in melanoma.

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• Transformation of Dysplasia in Barrett's Esophagus

  Complex chromosomal alterations are a hallmark of advanced cancers but rarely seen in normal tissue. The progression of precancerous lesions to malignancy is often accompanied by increasing complexity of chromosomal alterations that can drive their transformation through focal oncogenic amplifications. However, the etiology and evolution dynamics of these alterations are poorly understood. Here we study chromosomal copy-number evolution in the progression of Barrett's esophagus (BE) to esophageal adenocarcinoma (EAC) by multi-regional whole-genome sequencing analysis of BE samples with dysplasia and microscopic EAC foci. Through haplotype-specific copy-number analysis of BE genome evolution, we identified distinct patterns of episodic copy-number evolution consistent with the outcomes of abnormal mitosis and dicentric chromosome breakage. While abnormal mitosis, including whole-genome duplication, accounts for most chromosome or arm-level copy-number changes, segmental copy-number alterations display signatures of multi-generational evolution of unstable dicentric chromosomes. Continuous evolution of dicentric chromosomes through breakage-fusion-bridge cycles and chromothripsis rapidly increases genomic complexity and diversity among BE cells, culminating in the generation of distinct focal amplifications. These mutational processes enable multiple subclones within small dysplastic areas to undergo parallel transformation to cancer following acquisition of distinct oncogenic amplifications. Our results demonstrate how chromosomal instability drives clonal diversification in precancer evolution and promotes tumorigenesis in primary human samples.

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• Study of Cutaneous Biology of Cutaneous T Cell Lymphoma

  This study is designed to help us understand the biological factors that contribute to the development of Cutaneous T Cell Lymphoma (CTCL) through the use of single-cell -omics technologies. The data that will be available include single-cell RNAseq and paired single-cell TCRseq data from the primary lesions of CTCL patients.The number of consented subjects listed here is artificially inflated by one to account for the pooling of all subjects.

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• Genetics of Prostate Cancer in Africa

  African Americans (AA) suffer from the highest rates of Prostate Cancer (CaP) in the world, but while men of African descent around the world suffer disproportionately from CaP compared to men of other races or ethnicities, our understanding of the reasons for these disparities remains incomplete. To date, few exposure, lifestyle, or environmental influences have been identified in CaP etiology. In contrast, CaP is among the most heritable of common cancers, and over 290 susceptibility loci have been identified. However, many of these loci have not been replicated in AA, in part because of limited African descent sample sizes, incomplete capture of African alleles, and a limited understanding of African genomic architecture. To better understand the etiology of CaP in African descent men, we established a large, multicenter consortium known as “Men of African Descent and Carcinoma of the Prostate” (MADCaP). Using resources of this consortium, we have undertaken a multicenter study of CaP in Sub-Saharan Africa, enrolling CaP cases from 7 institutions in 4 countries in Africa (Nigeria, Senegal, Ghana, and South Africa) and age matched controls from the same institutions. We designed a novel genotyping array, in partnership with Thermo Fisher Scientific, leveraging its Applied BiosystemTM AxiomTM Genotyping solution, to provide good coverage of African genomic variation, as well as incorporating cancer loci, with the goal of being able to fine-map existing prostate cancer loci, as well as mapping novel loci. The data available encompasses genotyping our Africa cohort on this array.

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• 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.

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