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• Enzymatic Methyl-Seq Rectal Mucus

  Enzymatic methyl sequencing of rectal mucus samples from patients suspected to have colorectal cancer. This is 1 of 4 sequencing experiments on the same sample type.

  Study EGAS50000001314

• Advancing Precision Oncology in a Humanized, Fully Autologous Mouse Model

  Progress in the early detection and treatment of cancer requires accurate model systems to further evaluate new, promising discoveries. Small animal and, in particular, mouse model systems are attractive to researchers for numerous reasons, including their ease of use and well-described platforms. The ability to grow human tumors in immune-deficient mice (so-called patient-derived xenografts, or PDXs) allows researchers to work directly with human cancer tissue in a controlled setting. However, PDX models are limited by their lack of an intact immune system. Immunotherapy has revolutionized clinical oncology, but lacks pre-clinical models of the human immune system and human cancer to investigate new modalities and limitations/toxicities of treatment regimens. The broad objective of this study is to validate an in vivo model to evaluate human tumors in the context of a complete and intact human immune system in a completely personalized and autologous fashion to study cancer immunotherapy. Herein, we will: (1) validate the ability of our humanized system to serve as a model for cancer immunotherapy treatment response and toxicity in patients with melanoma, including immunotherapy checkpoint blockade and vaccine strategies, and (2) extend our current work in melanoma by validating the ability to establish humanized mice and evaluate tumor growth and leukocyte development in autologous human pancreatic and colorectal tumors established in humanized mice. In each of these areas, we will leverage our multi-institutional team's individual expertise along with our institutional infrastructure to maximize the success of the experimental aims. The results from this project will be widely available to the general research community for future, hypothesis-driven research. Taken together, our study will meet multiple goals and address several unmet needs in cancer immunotherapy, thus significantly enhancing the applicability of a fully autologous and immunocompetent precision model system for use in translational oncology research.

  Study phs003090

• Machine Learning Signal Enrichment for Ultrasensitive Plasma Tumor Burden Monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007451

• Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007545

• Identification of New Therapeutic Targets for Renal Medullary Carcinoma via Integrated Genomic and Transcriptomic Profiling

  Renal medullary carcinoma (RMC) is a rare, aggressive kidney cancer associated with sickle cell trait, characterized by SMARCB1 loss and resistance to conventional therapies used for other renal cell carcinomas (RCC). We conducted whole exome sequencing (WES) on RMC samples. This study provides a large molecular characterization of RMC, highlighting TROP2 and other cell surface markers as promising therapeutic targets.

  Study EGAS50000001280

• DAC for study CMMRD–associated high-grade glioma

  This Data Access Committee (DAC) is responsible for de-identified, summarized somatic variant call data derived from paired tumor–blood Whole-exome sequencing of human samples in a glioma research study. Access requests are approved without additional restrictions and are granted solely for health-related research purposes.

  Dac EGAC50000000855

• Characterization of arrested B-lymphoid differentiation and leukemic cell states in ETV6-RUNX1-positive pediatric leukemia

  RNA was extracted from eight diagnostic ETV6-RUNX1 positive acute lymphoblastic leukemia samples collected in PAXgene blood RNA tubes using PAXgene Blood RNA kit (cat #762174, Qiagen GmbH, Hilden, Germany), following the version 2 instructions for manual purification. Samples were processed with Globin-Zero Gold rRNA Removal Kit (Illumina) and directional libraries were prepared using NEBNext Ultra Directional RNA Library Prep kit (New England Biolabs). The library preparation and paired end (150 bp) sequencing were performed by Novogene (HK) Company Limited (Hong Kong, China) using Illumina Novaseq 6000 aiming at 70 million read pairs per sample.

  Dataset EGAD00001006406

• Genetic and immune landscape evolution defines subtypes of MMR deficient colorectal cancer

  Mismatch repair deficient colorectal cancers have high mutation loads and many respond to immune checkpoint-inhibitors. We investigated how genetic and immune landscapes co-evolve in these tumors. All cases had high truncal mutation loads. Driver aberrations showed a clear hierarchy despite pervasive intratumor heterogeneity: Those in WNT/βCatenin, mitogen-activated protein kinase and TGFβ receptor family genes were almost always truncal. Immune evasion drivers were predominantly subclonal and showed parallel evolution. Pan-tumor evolution, subclonal evolution, and evolutionary stasis of genetic immune evasion drivers defined three MMRd CRC subtypes with distinct T-cell infiltrates. These immune evasion drivers have been implicated in checkpoint-inhibitor resistance. Clonality and subtype assessments are hence critical for predictive immunotherapy biomarker development. Cancer cell PD-L1 expression was conditional on loss of the intestinal homeobox transcription factor CDX2. This explains infrequent PD-L1 expression by cancer cells and likely contributes to the high recurrence risk of MMRd CRCs with impaired CDX2 expression.

  Study EGAS00001005769

• RNA sequencing data for primary and recurrent ovarian granulosa cell tumors

  RNA sequencing dataset for primary and recurrent ovarian granulosa cell tumors consists of 24 .bam files with aligned reads, including 8 primary and 16 recurrent tumors. Total RNA was extracted from cryopreserved tissue of adult-type granulosa cell tumor samples. Libraries were prepared from cDNA using the NuGEN Ovation Ultralow Library System V2 (San Carlos, CA). Paired-end bulk RNA sequencing was performed on the Illumina HiSeq 2000 platform. RNA sequencing reads were aligned to the hg19/GRCh37 reference human genome using the STAR software (version 2.6.0b) with default parameters. Samples description: GCT001 Adult-type Granulosa Cell Tumor: recurrent tumor GCT002 Adult-type Granulosa Cell Tumor: primary tumor GCT003 Adult-type Granulosa Cell Tumor: recurrent tumor GCT004 Adult-type Granulosa Cell Tumor: primary tumor GCT005 Adult-type Granulosa Cell Tumor: recurrent tumor GCT006 Adult-type Granulosa Cell Tumor: recurrent tumor GCT007 Adult-type Granulosa Cell Tumor: primary tumor GCT008 Adult-type Granulosa Cell Tumor: recurrent tumor GCT009 Adult-type Granulosa Cell Tumor: recurrent tumor GCT010 Adult-type Granulosa Cell Tumor: recurrent tumor GCT011 Adult-type Granulosa Cell Tumor: primary tumor GCT012 Adult-type Granulosa Cell Tumor: recurrent tumor GCT013 Adult-type Granulosa Cell Tumor: recurrent tumor GCT014 Adult-type Granulosa Cell Tumor: recurrent tumor GCT015 Adult-type Granulosa Cell Tumor: recurrent tumor GCT016 Adult-type Granulosa Cell Tumor: recurrent tumor GCT017 Adult-type Granulosa Cell Tumor: recurrent tumor GCT018 Adult-type Granulosa Cell Tumor: primary tumor GCT019 Adult-type Granulosa Cell Tumor: recurrent tumor GCT020 Adult-type Granulosa Cell Tumor: primary tumor GCT021 Adult-type Granulosa Cell Tumor: primary tumor GCT022 Adult-type Granulosa Cell Tumor: recurrent tumor GCT023 Adult-type Granulosa Cell Tumor: recurrent tumor GCT024 Adult-type Granulosa Cell Tumor: primary tumor

  Dataset EGAD00001009108

• Genomic Tumor Correlates of Clinical Outcomes Following Organ-Sparing Chemoradiation Therapy for Bladder Cancer

  Bladder preservation with trimodality therapy (TMT), consisting of transurethral tumor resection followed by chemoradiation, is an alternative to radical cystectomy for muscle-invasive bladder cancer (MIBC), but molecular determinants of response are poorly understood. Patients with cT2-T4aN0M0 MIBC treated with definitive-intent chemoradiation as part of TMT were retrospectively identified from a single institution between 1986-2015. Pre-treatment Formalin Fixed Paraffin Embedded (FFPE) tumors from 76 MIBC patients were subjected to whole exome sequencing (WES). Our integrated analysis yielded insights into molecular features associated with favorable long-term response to TMT, including alterations in DNA damage response genes. Of these, mutations in ERCC2, a DNA helicase in the nucleotide excision repair pathway, were significantly associated with improved long-term outcomes after TMT, particularly in patients who received concurrent cisplatin-based chemotherapy.

  Study phs003402

• RNA-sequencing of ex vivo exhausted human antigen-specific T cells

  Tumor-specific T cells are frequently exhausted by chronic antigenic stimulation. To explore new pathways for reinvigoration of anti-tumor immune functions, we developed a human ex vivo exhaustion model by repetitive antigenic stimulation of primary CD8 T cells. This results in T cells that resemble patient-derived T cells in tumors on a phenotypic and transcriptional level. Four human healhy donor CD8+ T cells were isolated, transduced with an NY-ESO-1 TCR lentivirus construct, stimulated in four different conditions (Trested, Ttumor, Tex, Teff) with T2 tumor cells and specific peptides over 12 days. Cells were then sorted for TCR Vbeta 13.1+ (NY-ESO-1 TCR) CD8+ CD3+ CD56- CD4- DAPI- cells. RNA-seq TruSeq libraries were generated from polyA-enriched mRNA isolated from the samples, and sequenced in paired-end mode (2x51bp) on 2 lanes of an Illumina NovaSeq 6000 flow-cell. FASTQ sequence files were generated with the Illumina RTA version 3.4.4 and Base-calling Version bcl2fastq-2.20.0.422.

  Dataset EGAD00001009754

• Children's Hospital of Philadelphia (CHOP) Control Copy Number Variation (CNV) Study

  We present a database of copy number variations (CNVs) detected in 2,026 disease-free individuals, using high-density, SNP-based oligonucleotide microarrays. This large cohort analyzed for CNVs in a single study using a uniform array platform and computational tools, comprises mainly of Caucasians (65.2%) and African-Americans (34.2%), We have catalogued and characterized 54,462 individual CNVs, 77.8% of which were identified in multiple unrelated individuals. These non-unique CNVs mapped to 3,272 distinct regions of genomic variation spanning 5.9% of the genome; 51.5% of these were previously unreported, and >85% are rare. Our annotation and analysis confirmed and extended previously reported correlations between CNVs and several genomic features such as repetitive DNA elements, segmental duplications and genes. We demonstrate the utility of this data set in distinguishing CNVs with pathologic significance from normal variants. Together, this analysis and annotation provides a useful resource to assist with the assessment of CNVs in the contexts of human variation, disease susceptibility, and clinical molecular diagnostics. The CNV resource is available at: http://cnv.chop.edu. Reprinted from Shaikh T., et al., High-Resolution Mapping and Analysis of Copy Number Variations in the Human Genome: A Data Resource for Clinical and Research Applications Genome Research. 2009, with permission from Genome Research. CHOP CNVs from 2,026 disease-free individuals are available through dbVar at http://www.ncbi.nlm.nih.gov/dbvar/studies/nstd21.

  Study phs000199

• National Cancer Institute Multi-Ancestry Genome-Wide Association Study of Kidney Cancer (NCI-3)

  The National Cancer Institute (NCI) multi-ancestral genome-wide association study (GWAS) of kidney cancer ("NCI-3") was performed by NCI to further investigate common genetic variants associated with risk of kidney cancer and its two major subtypes across individuals of different ancestries (European, African, East Asian, Latin American). The NCI-3 GWAS includes 12,315 cases and 73,091 controls from 25 centers in North America, South America and Europe, genotyped using the Illumina Global Screening Array v2.0. SNP-level results from this GWAS were combined by meta-analysis with results from two earlier NCI European-ancestry GWAS (RCC; phs000351: 1,311 cases and 3,424 controls and phs001736: 2,417 cases and 4,391 controls), a NCI GWAS of African Americans (phs000863; 255 cases and 375 controls), GWAS conducted at other institutions [International Agency for Research on Cancer (scan 1: 2,438 cases and 5,071 controls; scan 2: 2,781 cases and 2,940 controls), The University of Texas MD Anderson Cancer Center (scan 1: 893 cases and 556 controls, scan 2: 1,241 cases and 1,712 controls) and the Institute for Cancer Research, UK (944 cases and 4,024 controls)] and GWAS analyses of data from three large biobanks (Biobank Japan: 523 cases and 86,306 controls; FinnGen: 2,095 cases and 304,956 controls; UK Biobank: 1,807 cases and 348,824 controls). Only individual-level data from NCI-3 and the two MD Anderson Cancer Center scans are included in this dbGaP submission. All study-specific and meta-analysis summary statistics are included.

  Study phs003505

• Nasopharyngeal RNASeq Comparing SARS-CoV-2+ Patients and SARS-CoV-2 Negative Control Subjects

  The goal of this analysis was to compare RNAs enriched in the upper respiratory tract of SARS-CoV-2 patients and SARS-CoV-2 negative controls. RNA-sequencing of RNA isolated from the viral transport medium associated with nasopharyngeal swab samples from SARS-CoV-2+ patients and SARS-COV-2 negative controls.

  Study phs002433

• RNA sequencing of genetically modified human iPSCs modeling patients with autism spectrum disorders (ASD)

  We generated two genetically modified iPSC lines. In each line, a single promoter variant identified in a patient with autism spectrum disorder (ASD) was introduced by using the CRISPR/Cas9 system. These mutant lines were analyzed by RNA-seq together with control lines to assess the impact of the introduced variant.

  Study JGAS000651

• RNA-seq following miR-130a overexpression (OE) in human CD34+cord blood cells

  We performed RNA-seq on CD34+ human cord blood (CB) cells transduced with Control or miR-130a OE lentiviruses to identify differentially expressed genes. Sorted CD34+ cells from 3 independent cord blood pools were transduced with lentiviruses containing mOrange (mO) reporter gene. mO+ cells were sorted 3 days post-transduction and RNA was harvested for library preparation and sequencing.

  Study EGAS00001005868

• Bisulfite sequencing of cell-free DNA in NMOSD patients

  Cell-free DNA was extracted from plasma and analyzed by bisulfite sequencing in Neuromyelitis Optica Spectrum Disorders(NMOSD) patients and healthy controls(HC). we aimed to investigate the primary source of cell-free DNA production.

  Study JGAS000515

• Whole exome sequence of human XXY fibroblasts

  This dataset contains Whole exome sequence generated using human skin fibroblast sample (ID 419281) from Klinefelter XXY syndrome patient fibroblasts. These fibroblasts were used to generate autosomally isogenic human iPSCs. The sample DNA was collected using commercial kit and Human All Exon v5 capture paired library was sequenced using Illumina HiSeq device. The fastq file (ID 493224) and analysis (ID 3209) bam files have been deposited.

  Dataset EGAD50000001362

• (h)MeDIP-Seq of high-risk prostate cancer

  Immunoprecipitation of methylated and hydroxymethylated DNA was performed on DNA isolated from tumoral and non-tumoral prostate tissue of patients with high-risk disease. Samples were sequenced on the Illumina HiSeq as 50 bp single end.

  Study EGAS00001001019

• Whole-exome sequencing of P2RY8-CRLF2-positive ALL on Illumina HiSeq 2000, 100 bp paired-end

  Genomic DNA from leukemic and remission bone marrow mononuclear cells was isolated with the QIAamp DNA Blood Extraction Kit (Qiagen, Venlo, The Netherlands). Libraries were prepared using Nextera Rapid Capture Exome Kit (Illumina, San Diego, USA). Paired-end sequencing of 100 bp reads was performed on a HiSeq 2000 (Illumina) to obtain at least a 50 x coverage.

  Dataset EGAD00001002666

• Paired-WGS-two-families-with-GBA-variants-and-Parkinsons-disease

  We performed whole- genome sequencing, rare variant filtering, segregation analysis and functional validation of PD cosegregating rare genetic variation in two families (6 samples) segregating PD associated GBA variants c.115+1G>A (ClinVar ID: 93445, ) and p.L444P (ClinVar ID: 4288) respectively. The paired WGS sequencing was run on HiSeq X Ten and the library preparation kit was Illumina TruSeq DNA nano.

  Dataset EGAD00001006561

• WES data of central nervous system neoplasm patients

  Dataset containing 2068 WES tumor and control samples of central nervous system neoplasm patients. The data was sequenced on a Illumina NextSeq 500 using a NPHD2015A kit. The sequencing was always paired.

  Dataset EGAD00001009855

• Single cell RNAseq and TCRseq data from tumor and blood samples from 4 patients with muscle invasive bladder cancer

  For this dataset we performed single cell RNAseq paired with single cell TCR-seq on tumor and blood samples from 4 patients. This dataset contains 4 tumor samples as well as 4 blood samples. Each sample is made up of 2 sets of paired fastq files. The first pair contains reads corresponding to RNA transcripts (_Transcripts in file name), while the second pair contain reads corresponding to TCRs (_VDJ in file name). Sequenced on the Illumina NovaSeq6000 platform in a paired-end run using an SP flow cell (v1.5, 300 cycles).

  Dataset EGAD50000001381

• Exploiting New Patterns of Genome Damage in Triple Negative Breast Cancer

  Genomic instability, a feature of triple negative breast cancers (TNBC), represents an opportunity for discovery of biologic and clinically relevant subgroups of patients. Owing to TP53 mutation in the majority of cases, DNA repair deficiency through loss of BRCA1 and BRCA2, and by expression features patterning a basal cell of origin, TNBC represents a molecularly and clinically distinct group of breast cancer patients. Unfortunately, targetable molecular features of TNBC remain elusive and TNBC patients suffer the poorest outcomes amongst clinical subgroups. Within TNBC patients, responses to treatment vary and although gene expression patterns within TNBC have been identified, little progress has been made in developing biomarkers; effective stratification as a route to directing patients to more targeted therapy is lacking. In this study, we exploit mutational processes in TNBC as a new opportunity to stratify patients and to understand the evolutionary progression of TNBC cells harboring specific DNA repair properties.

  Study phs003038

• Integrative Molecular Characterization of Breast Cancer

  Version 1: We have performed integrative analyses of breast cancer tumors, including whole exome sequencing (WES) of tumor and normal pairs, whole transcriptome sequencing, and single-cell RNA sequencing (scRNA-seq) or single-nucleus RNA sequencing (snRNA-seq), to determine molecular correlates of response to novel and immune therapies. We have focused on dissecting the role of anticancer immunity in response to these therapies and understanding biological mechanisms underlying therapeutic resistance. The goal of this work is to advance a precision medicine approach to breast cancer treatment by identifying molecular biomarkers to improve therapy selection and novel therapeutic targets to overcome resistance. Version 2: We performed bulk whole exome sequencing (WES) of fresh frozen tissue from primary hormone receptor-positive breast cancer. Additionally, where available, we performed bulk whole transcriptome sequencing for the same individuals (tumor only). Additionally, we performed single cell sequencing on fresh frozen tissue from primary hormone receptor-positive breast cancer.

  Study phs002419