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• Genomic Analyses of Germline and Somatic Variation in High-Grade Serous Ovarian Cancer

  The goal of this study was to identify and characterize germline and somatic genetic variation in women with high grade serous ovarian cancers treated at a single cancer center and their associations with relapse-free and overall survival. We conducted paired tumor/normal targeted next-generation sequencing of 577 genes in pathways of DNA repair, response to DNA damage, cell-cycle regulation, programmed cell death, MAPK, and P13K/AKT/MTOR signaling in 114 tumors from 71 women. In addition, we investigated single copy number alterations (SCNAs) and loss of heterozygosity in a subset of 61 tumors. We validated our results with data from ovarian tumors in TCGA. Our results were similar to other studies of high-grade serous carcinomas. As an example, we found that approximately one third of the tumors harbored loss of function variants in homologous recombination genes and that >90% had TP53 somatic mutations. Through GISTIC analysis of the OncoScan data on tumor DNA from 61 cases, we identified several regions of high copy number alterations including including NOTCH3 and PIK3R2 that were significantly associated with an increase in cancer recurrence and a reduction in overall survival. We identified few changes in mutation profiles where we had multiple tissues, either from multiple surgeries or from the primary site to metastatic sites within the same surgery. However, we did not investigate copy number alterations in multiple tissues from the same individuals, and so it may be that copy number alterations are more important. Data available through dbGAP will be the BAM files and the phenotypic data on the tumor samples, the age, race, ethnicity of the participants and their outcomes, and the Oncoscan OSCHP files.

  Study phs003198

• A Personalized Neoantigen Vaccine Generates Anti-Tumor Immunity in High-Risk Renal Cell Carcinoma

  Personalized cancer vaccines (PCVs) can generate circulating immune responses against predicted neoantigens. However, whether such responses can target cancer driver mutations, lead to immune recognition of a patient's tumor, and result in clinical activity are largely unknown, particularly in patients with lower mutation burden tumors. We conducted a phase I trial testing a neoantigen-targeting PCV in patients with high-risk, fully resected clear cell renal cell carcinoma (RCC; stage III or IV), with or without ipilimumab administered adjacent to the vaccine. At a median follow-up of 40.2 months from surgery, none of the 9 initial participants experienced a recurrence of RCC. No dose-limiting toxicities were observed. All patients generated T cell immune responses against PCV antigens, including RCC driver mutations in VHL, PBRM1, BAP1, KDM5C, and PIK3CA. Following vaccination, there was a durable expansion of peripheral T cell clones, and T cell reactivity against autologous tumor was detected in 7 of the 9 patients. Our results demonstrate that neoantigen-targeting PCVs in high-risk RCC are highly immunogenic, capable of targeting key driver mutations, and induce anti-tumor immunity. These observations, in conjunction with the absence of recurrence in all 9 vaccinated patients, highlights the promise of PCV as effective adjuvant therapy in RCC. We are submitting WES data from whole blood samples and tumor FFPE samples, and RNA-Seq data from tumor FFPE samples. We are also submitting RNA-Seq data from purified tumor samples. scRNA-seq data will be submitted for skin samples (vaccine site biopsies at Weeks 0, 4, and 13), tumor samples (including resected metastatic tumor samples for two patients), and normal kidney samples. Bulk TCR-seq data will be submitted for blood samples.

  Study phs003710

• Combining a Universal Telomerase Based Cancer Vaccine with Ipilimumab in Patients with Metastatic Melanoma - Five-year Follow up of a Phase I/IIa Trial

  Background Ipilimumab improves survival for patients with metastatic malignant melanoma. Combining a therapeutic cancer vaccine with ipilimumab may increase efficacy by providing enhanced anti-tumor immune responses. UV1 consists of three synthetic long peptides from human telomerase reverse transcriptase (hTERT). These peptides comprise epitopes recognized by T cells from cancer patients experiencing long-term survival following treatment with a first-generation hTERT vaccine, and generate long-lasting immune responses in cancer patients when used as monotherapy. The objective of this trial was to investigate the safety and efficacy of combining UV1 with ipilimumab in metastatic melanoma. Patients and methods In this phase I/IIa, single center trial [NCT02275416], patients with metastatic melanoma received repeated UV1 vaccinations, with GM-CSF as an adjuvant, in combination with ipilimumab. Patients were evaluated for safety, efficacy and immune response. Immune responses against vaccine peptides were monitored in peripheral blood by measuring antigen-specific proliferation and IFN-γ production. Results Twelve patients were recruited. Adverse events were mainly diarrhea, injection site reaction, pruritus, rash, nausea and fatigue. Ten patients showed a Th1 immune response to UV1 peptides, occurring early and after few vaccinations. Three patients obtained a partial response and one patient a complete response. Overall survival was 50% at 5 years. Conclusion Treatment was well tolerated. The rapid expansion of UV1-specific Th1 cells in the majority of patients indicates synergy between UV1 vaccine and CTLA-4 blockade. This may have translated into clinical benefit, encouraging the combination of UV1 vaccination with standard of care treatment regimes containing ipilimumab/CTLA-4 blocking antibodies.

  Study EGAS00001005253

• Genomics of acral lentiginous melanoma

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010126

• Whole genome sequence: cardiomyopathy, 1 myotonic dystrophy patient

  In this study, we analyzed the genomic information by whole genome sequencing using peripheral blood samples from patients with various cardiovascular diseases including severe heart failure to identify genetic variants related to the pathology of cardiovascular diseases. The purpose is to elucidate the underlying mechanism and develop new therapeutic interventions for cardiovascular disease.

  Study JGAS000706

• Test dataset with ligh-weight files

  This is a test dataset derived from public data of the 1000 Genomes Project. Its purpose is not to allow for any inference about cohort data or results, but to aid bioinformaticians in the technical development and testing of tools, as well as data consumers in learning how to access information. This dataset consists of 3 pairs of light-weight (sliced) files: BAM + BAI, CRAM + CRAI and VCF + TBI. These files can be downloaded directly through the EGA-download-client PyEGA3 (https://github.com/EGA-archive/ega-download-client). For any further questions, please contact the DAC (Helpdesk - email: helpdesk [at] ega-archive [dot] org).

  Dataset EGAD00001009826

• BRCA2, ATM, and CDK12 defects differentially shape prostate tumor driver genomics and clinical aggression

  This dataset contains all available targeted exon sequencing bam files from our study, "BRCA2, ATM, and CDK12 defects differentially shape prostate tumor driver genomics and clinical aggression". Patient identifiers are denoted by the first segment of the sample aliases (e.g. "P1"), and additional information is appended to reflect which sample is referenced. These include serial cfDNA samples ("-1", "-2", "-3", etc.), paired white blood cell or benign tissue control samples ("-Control"), or primary archival tissue samples derived from a diagnostic biopsy, prostatectomy, or transurethral resection of the prostate ("-Tissue"). All samples were sequenced using Illumina technology.

  Dataset EGAD00001006733

• Analysis of Donor Pancreata Defines the Transcriptomic Signature and Microenvironment of Early Neoplastic Pancreatic Lesions

  The adult healthy human pancreas has been poorly studied given lack of indication to obtain tissue from the pancreas in the absence of disease and rapid postmortem degradation. We obtained pancreata from brain dead donors thus avoiding any warm ischemia time. We found that neoplastic lesions occur frequently in healthy organs, in donors as young as in their 3rd decade of life. Using the 10X Genomics Platform, we performed single cell RNA sequencing on 7 donor pancreata, 6 of which we separately sequenced tissue from the pancreas head and tail, for a total of 11 sequencing runs. Of note, because one of our runs (containing sequencing from pancreas head and tail) did not pass qc, our final analysis in our study utilized 6 donor pancreata, 5 of which contained pancreas head and tail sequenced separately. This is a robust single-cell dataset of healthy, nonpathologic pancreas tissue and includes acinar, ductal, and non-epithelial cells (myeloid cells, fibroblasts, endothelial cells, lymphocytes).Briefly, the donor pancreas was dissected by a clinically-trained pancreatobiliary surgeon. The organ was dissected into head, body, and tail, with portions of each placed into DMEM media with 1% BSA/10µM Y27632. Tissue was minced into 1mm3 pieces, then digested with 1 mg/mL collagenase P for 20-30 min at 37°C with gentle agitation. Digested tissue was rinsed three times with DMEM/1% BSA/10µM Y27632, then filtered through a 40µm mesh. Resulting cells were submitted to the University of Michigan Advanced Genomics Core for single cell sequencing using the 10x Genomics Platform. FASTQ files of all sequencing runs along with clinical annotation of donors is available through this dbGaP submission.

  Study phs003229

• Male Infertility: Genetics of Spermatogenic Failure

  Spermatogenesis is a complex biological process that requires the coordination of thousands of genes. Perhaps because of the large number of genes involved, spermatogenic failure occurs frequently and affects approximately 1% of men. While environmental and genetic factors likely contribute to this disorder, it is thought that the majority of cases have an underlying genetic basis. The two most common genetic causes are deletions on the Y chromosome and cytogenetic abnormalities (/e.g./ Klinefelter syndrome, XXY), which each account for roughly 10-15% of cases of complete spermatogenic failure. Point mutations in several other genes have also been linked to spermatogenic failure, but their collective prevalence is very low. Thus, for approximately 70% of men with spermatogenic failure, the genetic cause remains unknown. We hypothesize that a disproportionate number of these remaining genetic variants reside on the sex chromosomes because they are hemizygous in males and contain a disproportionate number of genes expressed in the testis. To identify genes that are required for spermatogenesis, we have performed capture-based targeted sequencing in 301 men with azoospermia (complete absence of sperm) and 300 fertile controls. Our sequencing is focused on coding genes and conserved, non-coding sequences of the X and Y chromosomes. In addition, we have targeted ~497 autosomal genes that display exclusive or predominant expression in the testis. The total sequence space targeted is 21.3 Mb, and we require >70% of targets reach an average coverage of 20X.

  Study phs001023

• Mixture of 4

  Mixture of 4 unrelated individuals sequenced by 10x as a scRNA-seq. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile. The clustering of SNPs is submitted as the processed file. The Sequencing fastqs are submitted as unprocessed files.

  Dataset EGAD00001008724