12300 results for "cancer rna-seq"

in 33.28 milliseconds.

• 10x Genomics Single Cell Gene Expression for SA605X3XB01966

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA605 passage 3

  Dataset EGAD00001009142

• 10x Genomics Single Cell Gene Expression for SA1035X8XB03425

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 8

  Dataset EGAD00001009148

• 10x Genomics Single Cell Gene Expression for SA535X6XB03101

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 6

  Dataset EGAD00001009149

• 10x Genomics Single Cell Gene Expression for SA1035X6XB03211

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 6

  Dataset EGAD00001009150

• Whole genome sequencing

  Whole genome sequencing of high-grade serous ovarian cancer (HGSC) tumours and matched normals from 15 patients with homologous recombination deficiencies. The dataset includes fastq files from 56 HGSC tumours (1 primary, 1 relapse, 54 end-stage) and 15 matched normals. Sequence libraries were generated from tumour and matched normal genomic DNA using the KAPA HyperPrep PCR-free library preparation kit (Roche), or the Illumina TruSeq DNA Nano kit according to manufacturer’s instructions. Sequencing was carried out by the Kinghorn Centre for Clinical Genomics Sequencing Laboratory (Sydney, Australia) on the HiSeq X Ten System (Illumina) or by the Australian Genome Research Facility (Melbourne, Australia) on an Illumina NovaSeq to a minimum base coverage of 30-fold for normal DNA and 60-fold for tumour DNA samples.

  Dataset EGAD00001009746

• POETIC clinical Trial Ki67 Bookend Breast Cancer Targeted Exome and RNAseq Project

  Using RNAseq, we compare the 15% of poorest responders (PRs, n=177) as measured by proportional Ki67 changes after 2 weeks of neoadjuvant aromatase inhibitors to good responders (GRs, n=190) selected from the top 50% responders in the POETIC trial and matched for baseline Ki67 categories. In the POETIC trial, 4,480 postmenopausal women with primary ER+ BC were randomised 2:1 to receive either treatment with a non-steroidal AI (letrozole or anastrozole) for 2 weeks before and 2 weeks after surgery or to no perisurgical treatment. Only AI-treated patients with HER2- tumors, paired baseline and surgery Ki67 available, and baseline Ki67 immunohistochemistry (IHC) >10% (to minimise imprecision in proportional Ki67 falls) were included for selection. Data is baseline RNAseq and targeted exome DNA sequencing analysis of POETIC Good/Poor Responders to aromatase inhibitors based on change in Ki67.

  Dataset EGAD00001010919

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010940

• Genome and transcriptome sequence data from a myoepithelioma patient

  Genome and transcriptome sequence data from a myoepithelioma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010938

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010939

• Genome and transcriptome sequence data from a squamous cell carcinoma patient

  Genome and transcriptome sequence data from a squamous cell carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010941

• Genome and transcriptome sequence data from a non-small cell lung carcinoma patient

  Genome and transcriptome sequence data from a non-small cell lung carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010942

• Genome and transcriptome sequence data from a melanoma patient

  Genome and transcriptome sequence data from a melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010943

• Genome and transcriptome sequence data from a carcinoma of unknown primary patient

  Genome and transcriptome sequence data from a carcinoma of unknown primary patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010944

• Genome and transcriptome sequence data from a breast ductal carcinoma patient

  Genome and transcriptome sequence data from a breast ductal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010946

• Genome and transcriptome sequence data from a endometrial adenocarcinoma patient

  Genome and transcriptome sequence data from a endometrial adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010949

• Genome and transcriptome sequence data from a breast ductal carcinoma patient

  Genome and transcriptome sequence data from a breast ductal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010950

• Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010951

• Genome and transcriptome sequence data from a chromophobe renal cell carcinoma patient

  Genome and transcriptome sequence data from a chromophobe renal cell carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010952

• Genome and transcriptome sequence data from a unknown primary adenocarcinoma patient

  Genome and transcriptome sequence data from a unknown primary adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010953

• Genome and transcriptome sequence data from a breast ductal carcinoma patient

  Genome and transcriptome sequence data from a breast ductal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010954

• Genome and transcriptome sequence data from a merkel cell carcinoma patient

  Genome and transcriptome sequence data from a merkel cell carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010955

• Genome and transcriptome sequence data from a uveal melanoma patient

  Genome and transcriptome sequence data from a uveal melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010956

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010957

• Genome and transcriptome sequence data from a metastatic melanoma patient

  Genome and transcriptome sequence data from a metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010958

• Genome and transcriptome sequence data from a metastatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010960

• Genome and transcriptome sequence data from a ovarian serous carcinoma patient

  Genome and transcriptome sequence data from a ovarian serous carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010961

• Genome and transcriptome sequence data from a carcinoma of unknown primary patient

  Genome and transcriptome sequence data from a carcinoma of unknown primary patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010962

• Genome and transcriptome sequence data from a pancreas adenocarcinoma patient

  Genome and transcriptome sequence data from a pancreas adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010963

• Genome and transcriptome sequence data from a carcinoma of unknown primary patient

  Genome and transcriptome sequence data from a carcinoma of unknown primary patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010964

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010965

• Genome and transcriptome sequence data from a metastatic chondrosarcoma patient

  Genome and transcriptome sequence data from a metastatic chondrosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010966

• Genome and transcriptome sequence data from a primary unknown patient

  Genome and transcriptome sequence data from a primary unknown patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010968

• Genome and transcriptome sequence data from a metastatic pleomorphic sarcoma patient

  Genome and transcriptome sequence data from a metastatic pleomorphic sarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010969

• Lactobacillus rhamnosus GG ATCC (LGG) as an immune adjuvant for influenza vaccination in the elderly

  Double blind Randomized Controlled trial to evaluate the safety of Lactobacillus rhamnosus GG ATCC 53103 (LGG) vs placebo in elderly receiving Trivalent Inactivated Influenza Vaccine (TIV) (study 1) or Double blind Randomized Controlled trial to evaluate the safety of Lactobacillus rhamnosus GG ATCC 53103 (LGG) vs. placebo in elderly subjects receiving Live Attenuated Influenza vaccine (LAIV) (study 2). Healthy elderly volunteers, ages 65-80 were enrolled as outpatients in two clinical studies in which they received the TIV vaccine (study 1, n=28) or the LAIV vaccine (study 2, n=30). In each of the 2 studies, subjects were randomized to receive either LGG capsules containing 1 x 1010 CFU, twice daily for 28 days, or matching placebo capsules twice daily for the same period of time. The study subjects completed a daily diary, telephone calls, and study visits at the Massachusetts General Hospital Clinical Research Centers at baseline, days 21, 28 and 56 and month 5 for the TIV study and baseline, days 21, 28, and 56 for the LAIV study. During each visit, the subject diary, interim history, potential adverse effects and concomitant medications were reviewed and vital signs and a physical examination were performed. Routine blood tests were obtained to monitor for safety during visits and nasopharyngeal and stool samples were collected for microbiome analysis. Volunteers in both studies who were interested in participating in the effect of LGG probiotic on the Human whole Blood Transcriptome substudy also had blood drawn for DNA and RNA extraction, after signing the substudy consent form. The main objectives of the TIV and LAIV studies were to assess the safety and tolerability of 2 x 1010 CFU LGG administered orally to elderly subjects for 28 days after administration of TIV (study 1) or LAIV (study 2). Secondary objectives were to evaluate the richness and microbial diversity in nasopharyngeal and stool specimens using pyrosequencing, and to compare cytokine production in response to bacterial stimulation by following the kinetics of mRNA expression of pro and anti-inflammatory genes and different signaling pathways, in relation to changes in stool Bifidobacterium and Lactobacillus spp. The studies were reviewed and approved by the Partners Human Research Committee (TIV study IRB # 2010p001694 and LAIV study IRB # 2011p002849) and were registered at ClinicalTrials.gov (NCT01368029 and NCT01545349, respectively).

  Study phs000981

• Multi-omics data of 1000 Inflammatory Bowel Disease patients

  Portal available at https://1000ibd.org Inflammatory bowel disease (IBD) is a chronic complex disease of the gastrointestinal (GI) tract. Patients with IBD can experience a wide range of symptoms, but the pathophysiological mechanisms that cause these individual differences in clinical presentation remain largely unknown. In consequence, IBD is currently classified into subtypes using clinical characteristics. If we are to develop a more targeted treatment approach, molecular subtypes of IBD need to be discovered that can be used as new drug targets. To achieve this, we need multiple layers of molecular data are generated from the same IBD patients.We initiated the 1000IBD project to prospectively follow more than 1000 IBD patients from the Northern provinces of the Netherlands. For these patients, we have collected a uniquely large number of phenotypes and generated multi-omics profiles. To date, 1,215 participants have been enrolled in the project and enrolment is on-going, with 609 patients being present in the first data release. Phenotype data collected for these participants includes information on dietary and environmental factors, drug responses, and adverse drug events. Genome information has been generated using genotyping (ImmunoChip, Global Screening Array and HumanExomeChip) and sequencing (whole exome sequencing and targeted resequencing of IBD susceptibility loci), transcriptome information generated using RNA-sequencing of intestinal biopsies and microbiome information generated using both sequencing of the 16S rRNA gene and whole genome shotgun metagenomic sequencing.All molecular data generated within the 1000IBD project will be shared in multiple data on the European Genome-Phenome Archive (www.ega-archive.org). The first data release, will contain basic phenotypes for 609 participants, genotypes of 314 participants, gut microbiome data generated by tag sequencing the 16S gene of feces from 315 participants and intestinal biopsies from 107 participants, and gut microbiome metagenomic sequencing of feces of 355 participants . Future releases will comprise many more additional phenotypes and -omics data layers. 1000IBD data can be used by other researchers as a replication cohort, a dataset to test new software tools, or a dataset for applying new statistical models.

  Study EGAS00001002702

• Plasma MicroRNA Signatures of Aging

  Background. MicroRNAs are small non-coding RNAs that regulate gene expression post-transcriptionally and show differential expression in various tissues with aging phenotypes. Detectable in circulation, extracellular microRNAs reflect (patho)physiological processes and hold promise as biomarkers for healthy aging and age-related diseases. This study aimed to explore plasma extracellular microRNAs as biological aging indicator and their associations with health outcomes using population-level data. Methods. We quantified plasma expression levels of 2,083 extracellular microRNAs using targeted RNA-sequencing in 2,684 participants from the population-based Rotterdam Study cohort. The training and test sets included 1,930 participants from the advanced-aged initial and second subcohort (RS-I/RS-II; median age: 70.6), while the validation set comprised 754 participants from the middle-aged fourth subcohort (RS-IV; median age: 53.5). Based on 591 microRNAs well-expressed in plasma, we examined differential expression of microRNAs with chronological age, PhenoAge –a composite score of age and nine multi-system blood biomarkers–, the frailty index, and mortality. Next, elastic net models were employed to construct composite microRNA-based aging biomarkers predicting chronological age (mirAge), PhenoAge (mirPA), frailty index (mirFI), and mortality (mirMort). The association of these aging biomarkers with different age-related health outcomes was assessed using Cox Proportional Hazard, linear regression, and logistic regression models in the test and validation sets. Results. We identified 188 microRNAs differentially expressed with chronological age within the RS-I/RS-II advanced-aged population (ntraining=1158, ntest=772), of which 177 microRNAs (94.1%) were replicated in the middle-aged RS-IV subcohort (nvalidation=754). Moreover, 227 miRNAs showed robust associations with PhenoAge, 61 with FI, and 16 with ten-year mortality independent of chronological age. Subsequently, we constructed four plasma microRNA-based aging biomarkers: mirAge with 108, mirPA with 153, mirFI with 81, and mirMort with 50 miRNAs. Elevated scores on these microRNA-based aging biomarkers were associated with unfavorable health outcomes, including lower subjective physical functioning and self-reported health and increased mortality and frailty risk, but not with first- or multi-morbidity. Overall, larger effect estimates were observed for mirPA, mirFI, and mirMort compared to mirAge. Conclusions. This study describes distinct plasma microRNA-aging signatures and introduces four microRNA-based aging biomarkers with potential to identify accelerated aging and age-related decline, providing insights into the intricate process of human aging.

  Study EGAS00001008117

• Genomic Profiling Reveals Spatial Intra-tumour Heterogeneity in Follicular Lymphoma

  Follicular lymphoma (FL) is an incurable indolent non-Hodgkin’s lymphoma (NHL) that behaves heterogeneously and is synonymous with the reciprocal translocation t(14;18)(q32;q21), leading to aberrant constitutive over-expression of BCL2 [ref]. High risk groups with poor overall survival include patients that transform to a high grade lymphoma, most commonly diffuse large B cell lymphoma (DLBCL) or progress early (within 2 years) of receiving treatment. Recently several studies have shed light on the diverse genomic landscape of FL, with frequently mutated genes including those involved in chromatin remodelling, (CREBBP, KMT2D, EZH2, EP300), immune modulation (TNFRSF14), JAK-STAT (STAT6, SOCS1), NF-ĸB (CARD11, MYD88, TNFAIP3) and mTORC1 signalling (RRAGC) [ref]. To date, the majority of these studies have either focussed on inter-patient genetic heterogeneity or established the extent of clonal heterogeneity as a patient’s tumour evolves over time. Furthermore, these temporal studies have alluded to the existence of a tumour-repopulating population (referred to as the common progenitor cell (CPC)) that evades treatment and acts as a reservoir, seeding each subsequent relapse and transformation event. Although these previous studies have illuminated the longitudinal clonal dynamics that occur in FL, our understanding of the degree of spatial or intra-tumour heterogeneity (ITH) that exists within an individual patient thus far remains limited. Earlier studies have predominantly focused on differences in cytological grade and immunophenotype between spatially separated lymph nodes and bone marrow, the most common site of extra-nodal involvement in FL, with genomic profiling restricted to examining somatic hypermutation patterns in IgVH genes [ref]. In contrast next generation sequencing has been increasingly utilised in solid organ malignancies to derive comprehensive genomic profiles from spatially separated sites. The seminal study by Gerlinger et al revealed profound differences in the genetic make-up between individual primary and metastatic sites of renal cell carcinoma [ref]. Significant heterogeneity has since been demonstrated both between and within lesions in the same patient in lung, pancreas and breast cancer with presumed driver mutations distributed within the “branches” of the evolutionary phylogenetic tree, suggesting that a single biopsy is incapable of capturing the full genomic heterogeneity of an individual’s malignancy [ref]. This geographical heterogeneity not only adds to the diverse pool of tumour subclones that may contribute to drug resistance mechanisms but importantly, presents a major obstacle for precision-based approaches focussed on targeting specific lesions within a single biopsy. In FL, the exponential increase in clinical trials using novel agents such as EZH2, PI3K and BTK inhibitors reflects this shift in cancer care and along with the development of molecular prognostic scores such as the m7-FLIPI highlights the clinical need to accurately define genomic alterations with clinical relevance. As the majority of FL patients manifest disseminated tumour involvement, we sought to uncover the extent and clinical importance of spatial heterogeneity in FL by comprehensively genetically profiling 22 synchronously removed spatially separated biopsies from 9 patients. Using a combination of whole exome and targeted deep sequencing, our results inferred the complex subclonal architecture within these tumours and the mutational differences between anatomical sites, demonstrating cases with significant intrinsic genetic diversity.

  Study EGAS00001002492

• RNA sequencing of CCO- and CCO+ human hepatocytes

  RNAseq data from Passman et al 2023. Clonal CCO-deficient hepatocyte patches and nearby CCO-proficient hepatocytes were identified in morphologically normal human livers and sampled at varying distances along the PT-CV axis. Samples are named according to their location within the liver lobule, with "PT" denoting samples abutting the portal triad, "CV" denoting samples abutting the central hepatic vein, and "Mid" sampled acquired midway between these structures. Normal human liver is thought to be generally quiescent, however clonal hepatocyte expansions have been observed but neither their cellular source nor their expansion dynamics have been determined. Knowing the hepatocyte cell of origin, and their subsequent dynamics and trajectory within the human liver will provide an important basis to understand disease-associated dysregulation. Here we use in vivo lineage tracing and a combination of methylation sequence analysis to demonstrate normal human hepatocyte ancestry. We exploit next generation mitochondrial sequencing to determine hepatocyte clonal expansion dynamics across spatially-distinct areas of laser-capture microdissected clones, in tandem with computational modelling in morphologically-normal human liver.

  Study EGAS00001006984

• MGHBoston_Molpheno_Closed

  This dataset contains Whole Genome Sequencing and, if available, RNA-sequencing and/or ATAC-sequencing data of 17 lymphoblastoid cell lines derived from patients with complex genomic rearrangements. Patients have phenotypes in category of intellectual disability and/or multiple congenital anomalies. Data access is closed.

  Dataset EGAD00001004866

• Whole Exome Sequencing of Chronic Lymphocytic Leukemia

  The somatic genetic basis of chronic lymphocytic leukemia (CLL), a common and clinically heterogenous adult leukemia, remains poorly understood. Massively parallel sequencing technology now provides a method for systematic discovery of genetic alterations that underlie disease, and for uncovering new therapeutic targets and biomarkers. In study version 2 we presented a dataset consisting of DNA sequencing from 169 CLL samples (with matched germline controls). Samples were collected from patients displaying a wide range of characteristics representing the broad clinical spectrum of CLL. Understanding the mutational landscape of CLL provides a starting point for systematic analyses to address fundamental questions in CLL, including how mutated genes alter cellular networks and phenotypes, and thereby contribute to disease heterogeneity. Intratumoral heterogeneity plays a critical role in tumor evolution. To define the contribution of DNA methylation to heterogeneity within tumors, we performed genome-scale bisulfite sequencing of >100 primary chronic lymphocytic leukemias (CLLs; data presented in study version 3). Compared with 26 normal B cell samples, CLLs consistently displayed higher intrasample variability of DNA methylation patterns across the genome, which appears to arise from stochastically disordered methylation in malignant cells. Transcriptome analysis of bulk and single CLL cells revealed that methylationdisorder was linked to low-level expression. Disordered methylation was further associated with adverse clinical outcome. We therefore propose that disordered methylation plays a similar role to that of genetic instability, enhancing the ability of cancer cells to search for superior evolutionary trajectories.

  Study phs000435

• MP2PRT: Comprehensive Genomic Profiling to Identify Alterations Associated with Relapse for NCI Standard Risk (SR) B-Lineage ALL and NCI High Risk (HR) B-Lineage ALL with Favorable Genetic Features

  The Molecular Profiling to Predict Response to Treatment (MP2PRT) program is part of the NCI's Cancer Moonshot Initiative. The aim of this program is the retrospective characterization and analysis of biospecimens collected from completed NCI-sponsored trials of the National Clinical Trials Network and the NCI Community Oncology Research Program. This study, titled "Comprehensive Genomic Profiling to Identify Alterations Associated with Relapse for NCI Standard Risk (SR) B-Lineage ALL and NCI High Risk (HR) B-Lineage ALL with Favorable Genetic Features," is one of the selected studies under this program. For this study, genomic characterization (WGS 30X, WXS, Total RNAseq) was performed on NCI Standard Risk B-lineage ALL patients who relapse and subsets of NCI High Risk B-lineage ALL patients who relapse as well as two non-relapse control cases for each relapse case. It was hypothesized that the comprehensive characterization of these sample sets will allow the identification of somatic genetic features that will facilitate early intervention to improve cure rates for those enrolled on future trials. Data were generated and genetic subtype was integrated with clinical variables, including age, presenting white blood cell count, sex, race, and levels of minimal residual disease at the end of induction. Additional secondary alterations were identified and included if they occurred in more than 10 patients. The study has been completed and a manuscript has been prepared.

  Study phs002005

• A New Pipeline to Predict and Confirm Tumor Neoantigens Predicts Better Response to Checkpoint Blockade

  Mutations that drive oncogenesis in cancer can generate neoantigens that may be recognized by the immune system. Identification of these neoantigens remains challenging due to the complexity of the major histocompatibility complex (MHC) antigen and T-cell receptor interaction. Here we describe the development of a systematic approach to efficiently identify and validate immunogenic neoantigens. Whole exome sequencing of tissue from a melanoma patient was used to identify nonsynonymous mutations, followed by MHC binding prediction and identification of tumor clonal architecture. The top 18 putative class I neoantigens were selected for immunogenicity testing via a novel in vitro pipeline in HLA-A201 healthy donor blood. Naive CD8 T cells from donors were stimulated with allogeneic dendritic cells pulsed with peptide pools and then with individual peptides. The presence of antigen-specific T cells was determined via functional assays. We identified one putative neoantigen that expanded T cells specific to the mutant form of the peptide and validated this pipeline in a subset of patients with bladder tumors treated with durvalumab (N = 5). Within this cohort, the top predicted neoantigens from all patients were immunogenic in vitro. Finally, we looked at overall survival in the whole durvalumab-treated bladder cohort (N = 37) by stratifying patients by tertile measure of tumor mutation burden (TMB) or neoantigen load. Patients with higher neoantigen and TMB load tended to show better overall survival.

  Study phs002269

• Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma

  Immune checkpoint inhibitors are effective cancer treatments, but molecular determinants of clinical benefit are unknown. Ipilimumab and tremelimumab are antibodies against cytotoxic T-lymphocyte antigen 4 (CTLA-4). Anti-CTLA-4 treatment prolongs overall survival in patients with melanoma. CTLA-4 blockade activates T cells and enables them to destroy tumor cells. We obtained tumor tissue from patients with melanoma who were treated with ipilimumab or tremelimumab. Whole-exome sequencing was performed on tumors and matched blood samples. Somatic mutations and candidate neoantigens generated from these mutations were characterized. Neoantigen peptides were tested for the ability to activate lymphocytes from ipilimumab-treated patients. Malignant melanoma exomes from 64 patients treated with CTLA-4 blockade were characterized with the use of massively parallel sequencing. A discovery set consisted of 11 patients who derived a long-term clinical benefit and 14 patients who derived a minimal benefit or no benefit. Mutational load was associated with the degree of clinical benefit (P = 0.01) but alone was not sufficient to predict benefit. Using genomewide somatic neoepitope analysis and patient-specific HLA typing, we identified candidate tumor neoantigens for each patient. We elucidated a neo-antigen landscape that is specifically present in tumors with a strong response to CTLA-4 blockade. We validated this signature in a second set of 39 patients with melanoma who were treated with anti-CTLA-4 antibodies. Predicted neoantigens activated T cells from the patients treated with ipilimumab.

  Study phs001041

• Small Intestine Neuroendocrine Tumors (Carcinoid Tumors)

  The diagnosed incidence of small bowel neuroendocrine tumors (NETs) is increasing. While patients with localized disease can be treated surgically, those with metastatic disease currently have few treatment options. The success of biologically targeted therapies in other malignancies has led to interest in the molecular alterations underlying the pathogenesis of these NETs. To identify genetic aberrations in small intestine NETs, we generated copy number profiles from 31 primary and metastatic tumors and performed whole-exome sequencing on a subset of 29 primary small intestine NETs and 24 metastatic NETs in parallel with normal blood DNA. Whole-genome sequencing data was generated on 15 tumor/normal pairs and 5 primary/metastasis/normal trios. The global genetic landscape of small bowel NETs is relatively quiet. Consistent with previous studies, the overwhelming majority of tumors were characterized by loss of chromosome 18 and, to a lesser extent, other chromosome arm gains and losses. In stark contrast to arm-level alterations, recurrent high-level focal amplifications and deletions were much less prevalent in these tumors. High-throughput mutation screening and exome sequencing revealed similarly low rates of somatic mutation in NETs (median of 0.77 non-silent mutations per megabase (Mb) of coding DNA) compared to other recent cancer exome sequencing efforts. Our analysis of this cohort identified only a single, statistically significant recurrent somatic mutation targeting the cyclin-dependent kinase inhibitor gene, CDKN1B, encoding p27.

  Study phs000579

• MAP Kinase-Mutant Hematologic Malignancies and Their Therapeutic Resistance

  The Mitogen-Activated Protein Kinase (MAPK) signaling pathway has been critically important in understanding pathology and developing targeted therapy for many cancers, but high frequency mutations in this pathway in hematopoietic malignancies were unknown until a series of sequencing studies from our group and others revealed a high frequency of activating mutations in BRAF (GeneID:673), MAP2K1 (GeneID:5604), and other key components of the MAPK pathway in two groups of rare and poorly studied blood cancers: hairy cell leukemia (HCL) and the systemic histiocytoses (SH). Although HCL and the SH both share common gene mutations in BRAF (BRAFV600E) and MAP2K1, these are distinct blood cancers with different clinical behaviors; however, their actual developmental cellular origins, genomic, and pathogenic differences are poorly understood, which led to our project goal of determining how BRAFV600E, MAP2K1, and other MAPK pathway mutations contribute to the pathogenesis of distinct blood cancers and affect their clinical responses to MAPK pathway inhibitors. This study proposal seeks to advance our understanding of the actual cells of origin of cancer-causing MAPK mutations in HCL and the SH, to determine why BRAFV600E and MAP2K1 mutations can cause two distinct blood cancers, and to understand how these mutations in HCL and SH influence responses to MAPK pathway inhibitor drugs and other receptor tyrosine kinase (RTK) inhibitors such as RET and ALK inhibitors that could potentially become effective therapy for these poorly understood blood cancers.

  Study phs001864

• Molecular Characterization of Hemimegalencephaly

  Somatic mutations, in which a fraction of the cells in the body have a deleterious mutation, are well recognized in cancer but only recently appreciated in neurological disease. Given a somatic mutation in a population of progenitor cells, all daughter cells inherit the mutation and are able to express the resultant phenotype as a function of the differentiation program. We recently identified the first de novo somatic mutations in the developing brain in the condition hemimegalencephaly (HME), a catastrophic focal epilepsy condition associated with a malformation of cerebral cortical development (MCD). HME is one of the most severe MCD syndromes, characterized by massive hamartomatous overgrowth of either of the two cerebral hemispheres. Cerebral hemispherectomy is a frequent treatment for refractory epilepsy, allowing the sampling of diseased tissue. By comparing DNA from a diseased brain with DNA from blood/saliva, we identified de novo somatic mutations in PIK3CA, AKT3 or MTOR, part of the mTOR pathway. Mutations were present in 8-40% of sequenced alleles in various brain regions sampled during surgery and in some codons known to activate proteins.• Population informationPatient samples were collected from multiple centers. The population is Caucasian and Hispanic• Molecular technologies employedWhole-exome sequencing• Principal findings of the studyWe were the first to describe mTOR-related and non-mTOR mutations causing hemimegalencephaly, and we described two-hit mutational models to explain the genetic pathogenesis of hemimegalencephaly

  Study phs002156

• The Medical Genome Reference Bank: a whole genome data resource of 4,000 healthy elderly individuals.

  Allele frequency data from human reference populations is of increasing value for filtering and assignment of pathogenicity to genetic variants. Aged and healthy populations are more likely to be selectively depleted of pathogenic alleles, and therefore particularly suitable as a reference populations for the major diseases of clinical and public health importance. However, reference studies of the healthy elderly have remained under represented in human genetics. We have developed the Medical Genome Reference Bank (MGRB), a large scale comprehensive whole genome dataset of confirmed healthy elderly individuals, to provide a publicly accessible resource for health related research, and for clinical genetics. It also represents a useful resource for studying the genetics of healthy aging. The MGRB comprises 4,000 healthy, older individuals with no reported history of cancer, cardiovascular disease or dementia, recruited from two Australian community based cohorts. DNA derived from blood samples will be subject to whole genome sequencing. The MGRB will measure genome wide genetic variation in 4,000 individuals, mostly of European decent, aged 60 to 95 years (mean age 75 years). The MGRB has committed to a policy of data sharing, employing a hierarchical data management system to maintain participant privacy and confidentiality, whilst maximizing research and clinical usage of the database. The MGRB will represent a dataset of international significance, broadly accessible to the clinical and genetic research community.

  Study EGAS00001003511

• ATRX mutant neuroblastoma is sensitive to EZH2 inhibition via modulation of neuronal differentiation.

  Mutations and structural alterations of the SWI/SNF-like chromatin remodeler ATRX have been reported at high frequency in a number of adult and pediatric tumors1. However, the consequences of ATRX (Alpha Thalassemia/Mental Retardation, X-linked) mutations in cancer and their underlying epigenetic sensitivities remain ill defined. Particularly intriguing are the large N-terminal deletions of ATRX in neuroblastoma that generate in-frame fusion (IFF) proteins1–3 devoid of key chromatin interaction domains. Here we demonstrate that neuroblastoma cells harbouring ATRX IFFs have distinct gene expression programs compared to neuroblastoma cells that are wild type for ATRX. This is due in part to H3K27me3-mediated silencing of REST (RE1 Silencing Transcription Factor) target genes involved in neuronal differentiation. In turn, we find that ATRX IFF cells display exquisite sensitivity to EZH2 inhibition in both adherent and tumorsphere conditions, due in part to derepression of neurogenesis genes, including REST targets. Examination of the epigenomic landscape of a pediatric neuroblastoma tumor harboring an ATRX IFF revealed that H3K27me3 occupies a subset of REST target genes that are transcriptionally silenced, and are sensitive to EZH2 inhibition in our cell-based assays. Thus, our study greatly advances our understanding of indolent neuroblastoma and identifies EZH2 inhibition as a potential therapy for patients with ATRX mutant disease. Further, these studies may be applicable to other ATRX mutant pediatric malignancies, particularly those carrying similar structural alterations of ATRX.

  Study EGAS00001002507

• T cell receptor repertoire sequencing reveals chemotherapy-driven clonal expansion in colorectal liver metastases

  Colorectal liver metastasis (CLM) is a leading cause of colorectal cancer mortality, and the response to immune checkpoint inhibition (ICI) in microsatellite stable CRC has been disappointing. Administration of cytotoxic chemotherapy may cause increased density of tumour infiltrating T cells, which has been associated with improved response to ICI. This study aimed to quantify and characterize T cell infiltration in CLM using T cell receptor (TCR) repertoire sequencing. Eighty-five resected CLM from patients included in the Oslo CoMet study were subjected to TCR repertoire sequencing. Thirty-five and 15 patients had received neoadjuvant chemotherapy (NACT) within a short or long interval, respectively, prior to resection, while 35 patients had not been exposed to NACT. T cell fractions were calculated, repertoire clonality was analysed based on Hill evenness curves, and TCR sequential convergence was assessed using network analysis. Increased T cell fractions (10.6% vs 6.3%) were detected in CLM exposed to NACT within a short interval prior to resection, while modestly increased clonality was observed in NACT exposed tumours independently of the timing of NACT administration and surgery. While private clones made up >90% of detected clones, network connectivity analysis revealed that public clones contributed the majority of TCR sequence convergence. TCR repertoire sequencing can be used to quantify T cell infiltration and clonality in clinical samples. This study provides evidence to support chemotherapy-driven T cell clonal expansion in CLM in a clinical context.

  Study EGAS00001007136

• Preclinical Pediatric Molecular Analysis for Therapy Choice (MATCH)

  Purpose: Pediatric solid tumors arise from diverse tissues during development and exhibit a wide range of molecular, cellular and genetic features. This diversity, combined with the low incidence of pediatric cancer makes it increasingly difficult to personalize therapy for individual patients based on the unique features of their tumors. Therefore, well-credentialed preclinical models that capture the diversity and heterogeneity of pediatric solid tumors are essential for identifying molecular targeted therapeutics for precision medicine. Experimental Design: Here, we report 281 orthotopic patient derived xenografts (O-PDXs) from 224 patients representing 24 different types of pediatric solid tumors. We have performed genomic characterization of the O-PDXs and compared them to their corresponding patient tumors. To demonstrate the feasibility and utility of using such a diverse collection of O-PDXs in preclinical studies, we performed a preclinical pediatric precision medicine trial based on the NCI-COG Pediatric MATCH trial enrollment criteria. We also tested molecular targeted therapy for a novel oncogenic fusion recently reported in pediatric melanoma and precision drug delivery using nano-liposomal irinotecan. Results: In the preclinical match study, we identified one specific single agent response to LY3023414 in an osteosarcoma model with a TSC2 variant of unknown significance. Combinations of nano-liposomal irinotecan were effective in treating both Ewing sarcoma and rhabdomyosarcoma xenografts. Conclusion: Our studies demonstrate the value of large, well-credentialed preclinical models for future precision medicine in pediatric oncology using single agents, drug combinations and novel drug formulations.

  Study EGAS00001008011