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• National Cancer Institute Cancer Genome Characterization Initiative (CGCI)

  The Office of Cancer Genomics at the National Cancer Institute sponsored a series of studies as part of the Cancer Genome Characterization Initiative (CGCI) to assess novel emerging sequencing technologies in cancer. The CGCI program included comprehensive characterization of the genetic aberrations found in different pediatric and/or adult tumors. CGCI characterized a number of B-cell non-Hodgkin lymphomas (including diffuse large B-cell lymphoma (DLBCL) from patients with and without HIV+ infection, follicular lymphoma (FL), as well as adult and pediatric Burkitt lymphomas), and additional HIV-associated tumors (including DLBCL, lung, and cervical cancers). All data from these projects is available at the NCI Genomic Data Commons. Individual project descriptions are available by disease on the substudy pages (links are included at the top of this page). Brief summaries are as follows: Non-Hodgkin Lymphoma (NHL) - CGCI investigators probed genomic alterations more deeply than had previously been possible by using state-of-the-art RNA sequencing (mRNA-seq) and whole genome shotgun sequencing (WGS) coupled with leading edge bioinformatics, data management and analysis approaches. The project sequenced tumor DNA and/or RNA from 117 NHL tumor samples and 10 cell lines. This included the genomes or exomes of 1 Follicular Lymphoma (FL) and 13 diffuse large B-cell lymphoma (DLBCL) cases, all with matched constitutional DNA sequenced to comparable depths, RNA-sequencing (mRNA-seq) of 92 DLBCL, 12 FL and 8 B-cell NHL cases with other histologies and 10 DLBCL-derived cell lines. The DLBCL cases and cell-lines are from the two major subtypes of DLBCL: germinal center B-cell (GCB) and activated B-cell (ABC). HIV+ Tumor Molecular Characterization Project (HTMCP) - This project was a joint effort of the Office of Cancer Genomics (OCG) and the Office of HIV and AIDS Malignancy (OHAM). Its goals were to characterize HIV-associated cancers (obtained from HIV-infected patients) and compare them to the same types of cancers from patients without HIV infection. Investigators performed 30X genome sequencing of 100 cases of paired tumor and germline DNA, along with transcriptome sequencing in each of 3 types of HIV+ tumors (DLBCL, lung and cervical cancers). These platforms allow discovery of mutations both in coding and non-coding genomic regions, gene expression and genomic alterations (including translocations, insertions and deletions). Comparing tumors of cancer patients both with and without HIV-infection provides insight into the potential function of this virus in certain cancers. Burkitt Lymphoma Genome Sequencing Project (BLGSP) - This project was a collaborative effort between the National Cancer Institute and the Foundation for Burkitt Lymphoma Research to develop a databank of the many alterations found in Burkitt lymphoma (BL), an uncommon type of Non-Hodgkin lymphoma that occurs most often in children and young adults. The goal of the BLGSP was to explore potential genetic changes in patients with BL that could lead to better prevention, detection and treatment of the cancer. The project characterized the alterations of the tumors' genomes (with matched normal as control) and transcriptomes by sequencing the DNA and RNA of each case. Using the data generated, the ultimate goals of the project was to discover the molecular changes that are present in BL patients and then determine how those changes correlate with treatment regimen and outcome. CGCI data is accessible at the NCI's Genomic Data Commons (GDC) via the GDC's Data Portal and from each of the CGCI Publication Pages at the GDC (Please see the "Supplemental Links" section of any CGCI publication's "Publication Information and Associated Data Files page" at the GDC.). Available datasets include raw sequencing data, datasets generated by the original CGCI research teams (fully annotated clinical information and higher-level/analyzed molecular characterization data), as well as higher level data generated by the GDC. Please see the CGCI Use and Publication Guidelines for updated details on the sharing of any CGCI substudy data, including how to cite CGCI.To learn more about the CGCI studies, please visit the CGCI Program website.

  Study phs000235

• FASTQ Files from Breast Tumor Biopsies Collected Across Five Timepoints in the PROMETEO Phase II Trial

  The dataset contains RNA sequencing raw data from tumor biopsies collected at five time points during the SOLTI-1503 PROMETEO trial: baseline (pre-NAC), post-NAC screening, Cycle 2 Day 1, Cycle 3 Day 1, and surgery. The study intervention consisted of intratumoral injections of T-VEC followed by intravenous administrations of atezolizumab prior to surgery. The data is obtained from tumor samples of patients included in the study: female breast cancer patients with residual disease after neoadjuvant chemotherapy, including both triple-negative and Luminal B-like subtypes. Each sample includes raw paired-end RNAseq reads (~110 million reads per library) aligned to the GRCh38/hg38 reference genome

  Dataset EGAD50000002165

• Mechanisms_of_patient_response_to_Dabrafenib_in_Melanoma

  Samples will be from the BRF113683 (BREAK-3) study which is a Phase III Randomized, Open-label Study Comparing GSK2118436 to Dacarbazine (DTIC) in Previously Untreated Subjects With BRAF Mutation Positive Advanced (Stage III) or Metastatic (Stage IV) Melanoma (n=250 enrolled)•NGS [Agilent capture (Sanger V2 panel): 360 genes and 20 gene fusions; Illumina HiSEQ Sequencing]•CNV: [via NGS or Affy SNP 6.0 or Illumina Omni (TBD)]Bioinformatics: Analysis will be performed using core Sanger informatics pipelines similar to those previously described (Papaemmanuil E et al. (2013) Blood. 22:3616 -3627). Briefly, copy number analysis will be performed using the ASCAT algorithm, and base substitutions, small insertions and deletions using the CAVEMAN and Pindel algorithms, respectively. Statistical approaches including generalized linear models will be used to predict clinical variables such as maximum clinical response and duration of response using genetic data. Sanger and EBI to conduct analysis; Raw data and correlation with clinical endpoints to be analyzed by both EBI/Sanger and GSK (unique pipeline analyses to increase call confidence)

  Study EGAS00001000946

• Passive and active DNA methylation and the interplay with genetic variation in gene regulation

  DNA methylation is an essential1 epigenetic mark whose role in gene regulation and its dependency on genomic sequence and environment are not yet fully understood2,3. In this study we provide novel insights into the mechanistic relationships between genetic variation, DNA methylation and transcriptome sequencing data in three different cell-types of the GenCord human population cohort4. We find that the association between DNA methylation and gene expression variation among individuals are likely due to different mechanisms from those establishing methylation-expression patterns during differentiation. Furthermore, cell-type differential DNA methylation may delineate a platform in which more local inter-individual changes may respond to or act in gene regulation. We show that unlike genetic regulatory variation, DNA methylation alone does not significantly drive allele specific expression.. Finally, inferred mechanistic relationships using genetic variation as well as correlations with TF abundance reveal both a passive and active role of DNA methylation to regulatory interactions influencing gene expression.

  Study EGAS00001000446

• Longitudinal sequencing of a recurrent paediatric high grade neuroepithelial tumour

  We have studied a unique case of astroblastoma arising in a 6 year-old girl, with multiple recurrences over a period of 10 years, with the pathognomonic MN1:BEND2 fusion 11 surgical samples from either fresh frozen of paraffin embedded material and 1 blood sample were subjected to Illumina short read whole exome sequencing using Agilent SureSelect whole exome v4. Data is provided as 15 BAM files aligned to hg19 with bwa.

  Dataset EGAD00001004118

• GBM-Space: Whole Genome Sequencing of Laser Capture Microdissected Glioblastoma (LCM-WGS)

  Cancer cells display heterogeneous and dynamic states in glioblastoma, but how these malignant states arise and whether they follow a tractable cellular trajectory across tumours is poorly understood. Here, we generate a deep single cell and spatial multi-region atlas of 12 isocitrate dehydrogenase wild-type (IDH-wt) primary glioblastomas that integrates transcriptomic, epigenomic and genomic analysis to comprehensively characterise their tumour heterogeneity. This dataset contains whole genome sequencing (WGS) data generated from regions of interest (ROIs) collected via laser capture microdissection (LCM), towards identifying copy number alterations and subclones directly at the DNA level.

  Dataset EGAD00001016155

• RNA-seq of iPSC-derived oligodendrocytes of individuals with and without t(1;11) translocation

  This dataset contains high-throughput RNA-sequencing of 14 samples, each sample comprising oligodendrocytes derived from human induced pluripotent stem cells, from individuals with and without a balanced t(1;11) translocation which substantially increases risk of major mental illness. 5 samples derive from 2 control individuals, and 9 samples from 3 individuals carrying the translocation. Libraries were prepared from each total-RNA sample using the TruSeq Stranded Total RNA with Ribo-Zero kit. Libraries were then sequenced using the NextSeq 500/550 High-Output v2 (150 cycle) Kit on the NextSeq 550 platform. Raw paired-end sequencing data is stored in two FASTQ files per sample.

  Dataset EGAD00001006341

• Widespread DNA hypomethylation and differential gene expression in Turner syndrome

  Adults with 45,X monosomy (Turner syndrome) reflect a surviving minority since more than 99% of fetuses with 45,X monosomy die in utero. In adulthood 45,X monosomy is associated with increased morbidity and mortality, although strikingly heterogeneous with some individuals left untouched while others suffer from cardiovascular disease, autoimmune disease and infertility. The present study investigates the leukocyte DNAmethylation profile by using the 450K-Illumina Infinium assay and the leukocyte RNA-expression profile in 45,X monosomy compared with karyotypically normal female and male controls. We present results illustrating that genome wide X-chromosome RNA-expression profile, autosomal DNA-methylation profile, and the X-chromosome methylation profile clearly distinguish Turner syndrome from controls. Our results reveal genome wide hypomethylation with most differentially methylated positions showing a medium level of methylation. Contrary to previous studies, applying a single loci specific analysis at well-defined DNA loci, our results indicate that the hypomethylation extend to repetitive elements. We describe novel candidate genes that could be involved in comorbidity in TS and explain congenital urinary malformations (PRKX), premature ovarian failure (KDM6A), and aortic aneurysm formation (ZFYVE9 and TIMP1)

  Study EGAS00001002190

• The proliferative history shapes the DNA methylome of B-cell tumor and predicts clinical outcome

  Here, we provide access to CLL and DLBCL DNA methylation and gene expression data in the context of a systematic analysis of the DNA methylation variability in 1,595 samples of normal cell subpopulations and 14 tumor subtypes spanning the entire human B-cell lineage. This approach showed that differential methylation among tumor entities relates to differences in cellular origin and to de novo epigenetic alterations, which allowed us to build an accurate machine learning-based diagnostic algorithm. We identify extensive patient-specific methylation variability in silenced chromatin associated with the proliferative history of normal and neoplastic B cells. Mitotic activity generally leaves both hyper- and hypomethylation imprints, but some B-cell neoplasms preferentially gain or lose DNA methylation. Subsequently, we construct a DNA methylation-based mitotic clock called epiCMIT, whose lapse magnitude represents a strong independent prognostic variable in B-cell tumors and is associated with particular driver genetic alterations. Our findings reveal DNA methylation as a holistic tracer of B-cell tumor developmental history, with implications in the differential diagnosis and prediction of clinical outcome.

  Study EGAS00001004640

• Resistance to Checkpoint Blockade Therapy Through Inactivation of Antigen Presentation

  Although immune checkpoint blockade (CPB) leads to prolonged responses in 15-40% of patients with metastatic melanoma, treatment refractory disease and progression after initial response remain major causes of mortality. While predictors of response have been reported, the common mechanisms of both primary and acquired resistance are poorly understood. To identify mechanisms of resistance and examine the evolving landscape in response to CPB, we performed whole exome sequencing (WES), immunohistochemistry (IHC), and RNA-sequencing (RNAseq) of longitudinal tumor biopsies from 17 metastatic melanoma patients treated with various CPB therapies. We found no significant changes in both mutational and neoantigen loads over time between responders and nonresponders. However, we identified abnormalities in one gene, beta-2-microglobulin (B2M), an essential component of MHC Class I antigen presentation, that were present in samples during disease progression but not regression. In total, we identified B2M aberrations in 29.4% of patients, including multiple early frameshift mutations, loss of heterozygosity (LOH) overlapping B2M, and absence of tumor-specific B2M protein expression. Additional defects in the antigen presentation and IFNγ pathways were identified but were not restricted to progressing lesions in our cohort. In two independent cohorts of 105 and 38 melanoma patients treated with ipilimumab (anti-CTLA4) and pembrolizumab (anti-PD1) respectively, we found that B2M LOH was enriched 3-fold in nonresponders (~30%) vs. responders (~10%) and associated with poorer overall survival (log-rank p=0.01, p=0.006). Loss of both copies of B2M was found only in nonresponders. We also found evidence for association of LOH overlapping IFNGR1 with poorer overall survival exclusively in the anti-PD1 cohort. Thus, B2M loss is likely a common mechanism of primary and acquired resistance to therapies targeting CTLA4 or PD-1.

  Study phs001427