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• Molecular Analysis of Short- Versus Long-Term Survivors of High-Grade Serous Ovarian Carcinoma

  The underlying determinants for long-term survival (LTS, ≥10 years) versus short-term survival (STS, <3 years) of patients diagnosed with high-grade serous ovarian carcinoma (HGSC) are largely unknown. The present study sought to identify molecular predictors of LTS for women with HGSC. A cohort of 24 frozen HGSC samples (12 LTS and 12 STS) were collected and analyzed at DNA and RNA levels. Copy number variation and mutation did not indicate large differences between LTS and STS. From RNA-Seq analysis, 11 genes were found to be differentially expressed between the STS and LTS groups (fold change >2; false discovery rate <0.01). In the validation cohort, transmembrane protein 62 (TMEM62) was found to be related to LTS. Our in vitro and in vivo studies demonstrate that restoring TMEM62 may be a novel approach for treatment of HGSC. These findings may have implications for biomarker and intervention strategies to help improve patient outcomes.

  Study phs003020

• NIDCD Otitis Media Genetic Susceptibility and Middle Ear Microbial Shifts

  The study funded by R01 DC015004 aims to: (1) Identify rare OM susceptibility variants within families and in probands; and (2) Identify differences in the middle ear microbiome due to OM susceptibility variants. This study will also elucidate mechanisms responsible for the formation and growth of cholesteatoma, and bony erosion and complications due to cholesteatoma e.g. intracranial, hearing/vestibular loss, facial nerve palsy. A better understanding of cholesteatoma pathogenesis will potentially reveal novel drug targets, which can lead to new non-surgical therapies for cholesteatomatous OM. Our specific aims for this administrative supplement are: Aim 1 -- Perform RNA-sequencing using cholesteatoma samples collected from Filipino and Colorado patients who will be screened for FUT2, SPINK5 and A2ML1 variants; and Aim 2 -- Using network analysis, identify bone-expressed proteins potentially interacting with FUT2, SPINK5 or A2ML1, then test protein expression in archival human temporal bone in direct contact with cholesteatoma.

  Study phs001941

• Characterizing Individual Cells Obtained from Bone Marrow Biopsies of MPN Patients

  We profiled the transcriptomes of individual cells obtained from bone marrow aspirates of 7 treatment-naïve newly diagnosed JAK2-mutant myeloproliferative neoplasm (MPN) patients (3 polycythemia vera and 4 essential thrombocythemia patients), and 2 healthy controls. The submitted data corresponds to sequencing reads mapped to the human reference genome GhRC38 build using CellRanger for a total of 9 samples (one per patient). In addition, to reconstruct the lineage histories of single cells in MPN patients, we performed whole-genome sequencing of single-cell-derived colonies of hematopoietic stem and progenitor cells from 2 essential thrombocythemia (ET) patients: 22 JAK2-mutant colonies and 20 WT colonies for patient ET 1; and 13 JAK2-mutant colonies and 21 WT colonies for patient ET 2. The submitted data consists of sequencing reads aligned to the human reference genome GhRC38 build using bwa-mem. Each file corresponds to the whole-genome sequencing data for one colony.

  Study phs002308

• ALLELE Consortium Glioblastoma Project

  Glioblastoma patient samples were sequenced for this project. The purposes of this project are: (1) to establish an umbrella protocol as a mechanism for identifying patients (in the USA and international sites) who agree to the collection, storage, and broad usage of their specimens and ongoing collection, and review of their medical information for the purposes of minimal-risk research and use of such data in clinical trials on which the patient may enroll; (2) to develop operations that facilitate investigator access to the data and/or tissue to conduct research, while minimizing risks to participants and promoting responsible conduct; and (3) to provide the infrastructure for the sharing of de-identified, coded samples, clinical data, and genomic data between participating investigators and institutions. Eligible patients include patients with known or suspected nervous system tumors or other neurologic diseases. Whole exome sequencing from the stated project will be released under this submission.

  Study phs003000

• Spatial Transcriptomics Reveals Discrete Tumor Microenvironments and Autocrine Loops Within Ovarian Cancer Subclones

  Ovarian masses from patients with high grade serous ovarian carcinoma undergoing debulking surgery were subjected to spatial transcriptomics profiling using the 10x Genomics Visium (fresh frozen) platform. Copy number inference using inferCNV predicted the presence of subclones with mutually exclusive copy number alterations (CNAs) in 5 of the 8 patient samples studied. In one patient, 3 subclones were predicted. For this patient sample, a serial section of the same tumor was used to microdissect regions corresponding to each of these subclones, and a 'normal' region predicted to contain only fibroblasts and no tumor cells. These microdissected regions were processed for low pass whole genome sequencing (WGS) and CNAs recorded using ichorCNA. An oral biopsy lacking tumor cells from an unrelated donor was used as a negative control for CNA inference. The CNAs predicted by inferCNV for the three subclones were validated by the low pass WGS and no CNAs were observed in the normal region containing fibroblasts.

  Study phs003561

• NHLBI TOPMed: Genomic Summary Results for the Trans-Omics for Precision Medicine Program

  The NHLBI Trans-Omics for Precision Medicine (TOPMed) program aims to identify the genetic basis of variation in biomedical phenotypes, with emphasis on those related to heart, lung, blood and sleep disorders, as part of a broader Precision Medicine Initiative. The TOPMed program has provided whole genome sequencing (WGS) to over 80 different studies that had previously recruited participants and collected extensive phenotype data. Many TOPMed investigators affiliated with these studies have organized their activities into phenotype-focused Working Groups and have developed genotype-phenotype association projects. These analyses have resulted in valuable cross-study Genomic Summary Results (GSR) that include whole genome association test results of both common and rare variants. Most of the analyses include data from multiple studies, some of which are based on sensitive populations, precluding public sharing of GSR. This dbGaP accession provides a mechanism for sharing sensitive GSR, using the controlled-access mechanisms of dbGaP to provide protections for sensitive populations.

  Study phs001974

• GRIDSS, PURPLE, LINX: Unscrambling the tumor genome via integrated analysis of structural variation and copy number

  We have developed a novel, integrated and comprehensive purity, ploidy, structural variant and copy number somatic analysis toolkit for whole genome sequencing data of paired tumor/normal samples. We show that the combination of using GRIDSS for somatic structural variant calling and PURPLE for somatic copy number alteration calling allows highly sensitive, precise and consistent copy number and structural variant determination, as well as providing novel insights for short structural variants and regions of complex local topology. LINX, an interpretation tool, leverages the integrated structural variant and copy number calling to cluster individual structural variants into higher order events and chains them together to predict local derivative chromosome structure. LINX classifies and extensively annotates genomic rearrangements including simple and reciprocal breaks, LINE, viral and pseudogene insertions, and complex events such as chromothripsis. LINX also comprehensively calls genic fusions including chained fusions. Finally, our toolkit provides novel visualisation methods providing insight into complex genomic rearrangements.

  Study EGAS00001004034

• Serial TERT rearrangement breakpoint quantification in circulating tumor DNA enables minimal residual disease monitoring in patients with neuroblastoma

  Approximately 30% of high-risk neuroblastomas harbor genomic TERT rearrangements at diagnosis, resulting in high TERT transcript levels and active telomerase. Combined with mutations in the RAS/MAPK/ALK signaling transduction network, these patients have a dismal prognosis. Our objective was to establish a liquid biopsy-based monitoring strategy for this particularly vulnerable patient subgroup, for whom no in-time molecular diagnostic tools exist to date. Detection and quantification of TERT rearrangement breakpoints in cell-free tumor DNA circulating in peripheral blood and bone marrow plasma from patients with TERT-driven neuroblastoma improved minimal residual disease monitoring and early relapse detection in individual patients. TERT rearrangement breakpoints, as a single marker or combined with mutations in the RAS/MAPK/ALK signaling transduction network, can be reliably analyzed from 1ng DNA using droplet digital PCR assays fit for clinical routine use. TERT rearrangement breakpoints are reflected in cell-free tumor DNA and can serve as robust biomarkers for disease activity.

  Study EGAS00001007365

• Sequencing data from MethylScan assay on plasma

  Machine learning models in biomedical research are often hindered by demographic imbalances in clinical datasets, leading to biased predictions that disadvantage minority populations. Existing bias correction methods face limitations in handling the heterogeneity of biomedical data and the complexity of demographic influences. Here, we present DeBias, a computational framework for mitigating demographic biases in high-dimensional biomedical datasets. DeBias eliminates bias-associated subspaces within the entire feature space using control samples and enables global bias correction across all features, effectively preserving disease-specific signals while minimizing demographic distortions. To demonstrate its effectiveness, we applied DeBias to cfDNA methylation data for cancer detection. It achieved a >6-fold reduction in the number of features containing biases and outperformed existing methods in improving the cancer detection performance for minority populations. Our method represented a promising step toward developing machine learning models that are more accurate, reliable, and equitable for minority populations.

  Study EGAS00001008127

• HCC.GNE RNA-Seq

  RNA-Sequencing data (raw read sequences) for 23 samples, from 12 patients, for the study "Diverse modes of genomic alterations in Hepatocellular Carcinoma"

  Dataset EGAD00001000886