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• A Combined Omics and Tissue Biobank for Paediatric Cancers

  The Swedish Childhood Tumour Biobank (BTB) is a nonprofit national infrastructure for samples and genomic data collection from pediatric patients diagnosed with central nervous system and other solid tumours in Sweden. Fresh frozen tumour tissue and patient’s matched blood are collected from affected patients and genomic data is continuously generated and made available for approved medical research projects. We expect that the accessibility of biological samples and/or data to the research community will contribute to further advances in the understanding of tumour biology, which in turn will impact many aspects of clinical care of children with cancer, by refining diagnosis and/or identifying oncogenic drivers and therapeutic targets.

  Study EGAS50000000209

• RNA sequencing of undifferentiated sarcomas

  Undifferentiated sarcomas (USARCs) of adults are diverse, rare, and aggressive soft tissue cancers. Recent sequencing efforts have confirmed that USARCs exhibit one of the highest burdens of structural aberrations across human cancer. Here, we sought to unravel the molecular basis of the structural complexity in USARCs by integrating DNA sequencing, ploidy analysis, gene expression, and methylation profiling. We identified whole genome duplication as a prevalent and pernicious force in USARC tumorigenesis. Using mathematical deconvolution strategies to unravel the complex copy-number profiles and mutational timing models we infer distinct evolutionary pathways of these rare cancers. In addition, 15% of tumors exhibited raised mutational burdens that correlated with gene expression signatures of immune infiltration, and good prognosis.

  Study EGAS00001003291

• Genomic and clinical characterization of a familial GIST kindred intolerant to imatinib

  Familial gastrointestinal stromal tumors (GIST) are rare. We present a kindred with multiple family members affected with multifocal GIST who underwent whole genome sequencing of the germline and tumor. Affected individuals with GIST harbored a germline variant found within exon 13 of the KIT gene, (c.1965T>G; p.Asn655Lys, p.N655K) and a variant in the MSR1 gene (c.877C>T; p.Arg293*, pR293X). Multifocal GISTs in the proband and her mother were treated with preoperative imatinib, and resulted in severe intolerance. The clinical features of multifocal GIST, cutaneous mastocytosis, allergies and gut motility disorders seen in the affected individuals may represent manifestations of the multifunctional roles of KIT in interstitial cells of Cajal or mast cells and/or may be suggestive of additional molecular pathways which can contribute to tumorigenesis.

  Study EGAS50000000372

• Identifying genetic variants that alter TCR usage in the peripheral repertoire

  The relationship between genetic variation and CD8+ T-cell receptor (TCR) repertoire usage in patients receiving Immune Checkpoint Blockade (ICB) therapy for cancer is unexplored. We have conducted a genome-wide and human leukocyte antigen (HLA)-focused analysis of CD8+ T-cell TCR repertoire to identify genetic determinants of variable gene (V-gene) and CDR3 K-mer usage from samples taken prior to and after ICB (n=250). We identify 11 cis and 10 trans V-gene associations, primarily to the MHC, that meet genome-wide significance. TCR clones containing HLA associated V-genes were less stable across treatment, whilst at the single-cell level, genetically associated clones demonstrate subset enrichment and increased tumor reactivity expression profiles. Notably, patients with HLA-matched TCR clones demonstrate improved overall survival. Our work indicates a complex relationship between genotype and TCR repertoire in the context of ICB treatment, with novel implications for understanding factors relating to therapeutic response and patient outcomes.

  Study EGAS00001008189

• Understanding the genetic risk underlying racial disparities in uterine fibroids

  Fibroids affect 77% of women by onset of menopause in the U.S. and account for $2.1 billion in healthcare costs each year. Fibroids negatively impact reproductive health causing heavy and painful menses, pelvic pain and pressure, pregnancy complications, and interventions including myomectomy and hysterectomy. Until recently, tumor tissue and cell culture studies investigating fibroid growth have been the primary sources for understanding fibroid pathophysiology. Genetic analysis can provide a powerful and cost effective tool to identify etiological and causal factors, especially since a genetic predisposition to fibroids has already been documented from twin studies. As much as 69% of risk is explained by genetic factors. Racial disparities also support a role for genetics with fibroid risk. African American women have earlier age of onset, more numerous and larger fibroids with a greater lifetime incidence compared to Caucasians. We propose to identify genetic markers for risk of fibroids through a genome-wide association study (GWAS) of African American and Caucasian participants, leveraging ancestral differences to narrow down genomic regions for targeted follow- up analyses. To accomplish this we will take advantage of a unique Vanderbilt resource, the BioVU DNA databank. BioVU currently has over 122,470 adults linked to electronic medical records. From BioVU we have already identified 2,902 African American and Caucasian subjects who meet our stringent inclusion criteria to conduct a GWAS of fibroids, including pelvic imaging. Available imaging is critical, because many women with fibroids are asymptomatic and without imaging, studies may misclassify as many as 51% of women. We have also defined definitive controls who reached menopause without fibroids. We have a strong group of nationally known fibroid researchers who will provide over 10,000 samples for replication. Our first Specific Aim is to conduct a GWAS for association between common single nucleotide polymorphisms (SNPs) and fibroid risk. Using a case-control design we will perform a GWAS in 2,902 (1,451 fibroid cases and 1,451 controls) women from BioVU stratified by African American and Caucasian race. Secondary admixture mapping (AM) analyses will also be performed to identify chromosomal regions of interest to prioritize for replication. Our second Aim is to resequence chromosome regions identified from GWAS and AM to discover rare variants. Finally, in Aim 3 we will replicate SNPs selected from Aim 1 and 2 in independent samples of at least 3,230 fibroid cases and 7,097 controls. We propose an efficient and cost-effective approach to identify genetic risk factors for fibroids, by taking advantage of imaging information and DNA available through BioVU. This study represents the largest GWAS of uterine fibroids and the first among African Americans leveraging emerging technologies and new statistical approaches to conduct this study. Our proposed study will fundamentally change knowledge about fibroids and lay the ground work for breakthroughs in understanding mechanisms of fibroid formation and in identifying novel therapeutic approaches.

  Study phs001409

• two tables containing RNASeq expression values to patients with RNA-Seq data in the study "Comprehensive genomic characterization of refractory multiple myeloma (H067)"

  two tables containing RNASeq expression values to patients with RNA-Seq data in the study "Comprehensive genomic characterization of refractory multiple myeloma (HIPO_067)". From the bam files gene expression was calculated with the annotation of Gencode.v19. Raw Counts and TPM values are given in one table, the other contains filtered TMM normalized CPM values (genes < 1CPM omitted).

  Dataset EGAD00001008363

• BAM files of total RNA-Seq data of POPS control samples (GRCh37)

  Placental biopsies (n = 64 female placentas, n = 67 male placentas) were selected from healthy pregnancies from the POPs cohort. A quality control process was also applied for the RNA-Seq datasets: reads were trimmed with Trim Galore!, which uses cutadapt internally and were mapped to the same version of human genome reference (hg19). TopHat2, a splice-aware mapper built on top of Bowtie2 short-read aligner, was used in the mapping process in which so-called two-pass (or two-scan) alignment protocol was applied to rescue unmapped reads from the initial mapping step. In the second mapping, previously unmapped reads were re-aligned to the exon-intron junctions detected in the first-mapping by TopHat2 and were combined across all 131 placenta samples. The initial and second mapped reads were merged by samtools

  Dataset EGAD00001003462

• in silico drug target prediction for melanoma

  The in silico single gene deletion step was adapted to simulate the knock-out of all targets of a drug on an objective function such as growth or energy balance. Based on publicly available and in-house large scale transcriptomic data, metabolic models for melanoma were reconstructed, enabling the prediction of 28 candidate drugs and estimating their respective efficacy.

  Study EGAS00001006463

• COVID-19 GWAS in Japanese

  The Japan COVID-19 Task Force (JCTF) was established in early 2020 as a nation-wide multicenter consortium to overcome the COVID-19 pandemic in Japan. We conducted a genome-wide association study (GWAS) involving 2,393 Japanese COVID-19 cases collected in initial pandemic waves with 3,289 controls. GWAS genotyping was performed using Infinium Asian Screening Array (Illumina, USA).

  Study EGAS00001006284

• Prediction of Trastuzumab Benefit in Adjuvant Breast Cancer: Gene Expression Profiling in NSABP B31

  Background National Surgical Adjuvant Breast and Bowel Project (NSABP) trial B-31 suggested the efficacy of adjuvant trastuzumab, even in HER2-negative breast cancer. This finding prompted us to develop a predictive model for degree of benefit from trastuzumab using archived tumor blocks from B-31. Methods Case subjects with tumor blocks were randomly divided into discovery (n = 588) and confirmation cohorts (n = 991). A predictive model was built from the discovery cohort through gene expression profiling of 462 genes with nCounter assay. A predefined cut point for the predictive model was tested in the confirmation cohort. Gene-by-treatment interaction was tested with Cox models, and correlations between variables were assessed with Spearman correlation. Principal component analysis was performed on the final set of selected genes. All statistical tests were two-sided. Results Eight predictive genes associated with HER2 (ERBB2, c17orf37, GRB7) or ER (ESR1, NAT1, GATA3, CA12, IGF1R) were selected for model building. Three-dimensional subset treatment effect pattern plot using two principal components of these genes was used to identify a subset with no benefit from trastuzumab, characterized by intermediate-level ERBB2 and high-level ESR1 mRNA expression. In the confirmation set, the predefined cut points for this model classified patients into three subsets with differential benefit from trastuzumab with hazard ratios of 1.58 (95% confidence interval [CI] = 0.67 to 3.69; P = .29; n = 100), 0.60 (95% CI = 0.41 to 0.89; P = .01; n = 449), and 0.28 (95% CI = 0.20 to 0.41; P < .001; n = 442; P interaction between the model and trastuzumab < .001). Conclusions We developed a gene expression-based predictive model for degree of benefit from trastuzumab and demostrated that HER2-negative tumors belong to the moderate benefit group, thus providing justification for testing trastuzumab in HER2-negative patients (NSABP B-47). ** Reprinted from J Natl Cancer Inst;2013;105:1782-1788 with permission from Oxford University Press.

  Study phs000826