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• A comprehensive proteogenomic pipeline for neoantigen discovery to advance personalized cancer immunotherapy

  The accurate identification and prioritization of antigenic peptides is crucial for the development of personalized cancer immunotherapies. Publicly available pipelines to predict clinical neoantigens do not allow direct integration of mass spectrometry immunopeptidomics data, which can uncover antigenic peptides derived from various canonical and non-canonical sources. To address this, we present an end-to-end clinical proteogenomic pipeline, called NeoDisc, that combines state-of-the-art publicly available and in-house software for immunopeptidomics, genomics and transcriptomics with in-silico tools for the identification, prediction, and prioritization of tumor-specific and immunogenic antigens from multiple sources, including neoantigens, viral antigens and high-confidence tumor-specific antigens.

  Study EGAS50000000228

• ARDSnet and the iSPAAR Consortium: Genomic Basis of Susceptibility and Outcomes in Patients with the Acute Respiratory Distress Syndrome (ARDS)

  Acute Respiratory Distress Syndrome (ARDS)/ Acute Lung Injury (ALI) is a syndrome defined by the presence of acute hypoxemic respiratory failure, bilateral pulmonary infiltrates on chest radiograph, a known clinical risk factor (e.g. sepsis, pneumonia, trauma, gastric fluid aspiration, pancreatitis, massive transfusion), and the absence of physiologic or clinical evidence of congestive heart failure. The Identification of SNPs Predisposing to Altered ALI Risk (iSPAAR) study is a multi-institutional cooperative study, funded through the NHLBI Recovery Act, that assembled samples and phenotype information from existing cohorts. The consortium included samples from patients with ARDS from the NIH NHLBI ARDS Clinical Trials Network (ARDSNet). Samples were obtained from 3 interventional treatment trials in patients with ARDS, including the Fluid and Catheter Treatment Trial (FACTT), the Albuterol to Treat Acute Lung Injury (ALTA) trial, and the Omega-3 Fatty Acid/Antioxidant Supplementation for ALI trial (Omega). In addition to ARDSnet samples, samples from the other cohorts included cases of established ARDS but also controls: critically ill patients who were at-risk for ARDS but who did not develop ARDS during their hospital course. These cohorts included the Molecular Epidemiology of Acute Respiratory Distress (MEA) Study enrolled at the Harvard University/Massachusetts General Hospital, the Systemic Inflammatory Immune Response Syndrome (SIRS) Patient Database and ICU Traumatic Injury cohorts from Harborview Medical Center, and cohorts collected from the ALI research programs at the University of Pennsylvania and the University of California, San Francisco. The Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000631 ARDSnet iSPAAR Consortium. phs000334 ESP_LungGO_ALI phs000686 ALI_GeneticRisk

  Study phs000631

• Single-Cell RNA-Sequencing of Human Prostatectomy Tissue

  The tissue microenvironment in prostate cancer is profoundly altered. How prostate cancer cells and their precursors mediate those changes is unclear, in part due to the inability to longitudinally study the disease evolution in human tissues. To overcome this limitation, we performed extensive single-cell RNA-sequencing (scRNA-seq) to assess the transcriptional profiles of the tissue microenvironment in prostate tissues from prostatectomies from men diagnosed with prostate cancer. For each subject, benign-enriched and tumor-enriched tissues were collected from the peripheral zone of the prostate. Our studies of human tissues revealed that cancer cell-intrinsic activation of MYC signaling was the top up-regulated pathway in human cancers, representing a common denominator across the well-known molecular and pathological heterogeneity of human prostate cancer. Numerous non-malignant cell states in the tumor microenvironment (TME), including non-cancerous epithelial, immune, and fibroblast cell compartments, were conserved across individuals, suggesting that these cell types may be a sequelae of the convergent MYC activation in the cancer cells.

  Study phs003480

• MOSAIC - Multi-Omics Spatial Atlas In Cancer

  MOSAIC is a collaborative initiative founded by Owkin, Lausanne University Hospital (CHUV), Charité Universitätsmedizin Berlin, University Hospital Erlangen (UKER), Gustave Roussy Institute in Paris, and University of Pittsburgh. The goal of MOSAIC is to build the largest collection of spatial omics data in cancer. By integrating comprehensive high quality clinical annotations with advanced deep profiling techniques, MOSAIC aims to uncover novel cancer subtypes and identify key drug targets and biomarkers within them.

  Study EGAS50000000689

• Genomic characterization of co-existing biliary tract intraepithelial neoplasia and carcinoma lesions reveals distinct evolutionary paths of gallbladder cancer

  Gallbladder carcinoma is the most common cancer of the biliary tract with dismal survival largely due to delayed diagnosis. Biliary tract intraepithelial neoplasia (BilIN) is the common benign tumor that is suspected to be precancerous lesions. However, the genetic and evolutionary relationships between BilIN and carcinoma remain unclear. Here we performed whole-exome sequencing of coexisting low-grade BilIN (adenoma), high-grade BilIN, and carcinoma lesions, and normal tissues from the same patients.

  Dataset EGAD00001007792

• Aberrant Oligoclonal Hematopoiesis in Remission AML and Relapse from Rare Cells Genomically Resembling Leukemic Blasts

  Acute myelogenous leukemia (AML) is a hematological malignancy that often responds well to initial treatment in which patients achieve a complete remission (CR). Nevertheless, most patients will relapse after achieving a CR, which is often fatal. This minimal residual disease (MRD) that remains after CR is likely the source of relapse and so improved measurement and characterization of these residual cells is critical. Employing droplet digital PCR (ddPCR), we were able to measure mutated alleles of many recurrently mutated genes in bone marrow samples acquired during CR from AML patients at levels as low as 0.002% variant allele frequency. Most of these gene mutations persisted in CR but at very variable and gene-dependent levels. Most AML cases involved residual aberrant oligoclonal hematopoiesis, and rare cell populations (as few as 1 in 15,000) were detected that were genomically similar to the AML blast populations at that dominated at diagnosis and were fully clonally represented at relapse. From a clinical perspective, the mutant allele frequency correlated closely with relapse-free and overall survival.

  Study phs001408

• High volume culture initiating in vitro evolution in neuroblastoma cell lines

  Despite the advent of advanced molecular prognostic tools, it is still difficult to predict the course of disease for cancer patients at the individual level. This lack of predictability is also reflected in many experimental cancer model systems, begging the question of whether certain biological aspects of cancer (eg. growth, evolution etc.) can ever be anticipated or if there remains an inherent unpredictability to cancer, similar to other complex biological systems. We demonstrate by a combination of agent-based mathematical modelling, analysis of patient-derived xenograft systems from multiple cancer types, and in-vitro culture that certain conditions may invoke chaotic fluctuations in the clonal landscape of cancer growth. Our findings indicate that under those conditions, the cancer genome may behave as a complex dynamic system, making its long-term evolution inherently unpredictable.

  Study EGAS00001007962

• The molecular basis of T-PLL is an actionable perturbation of TCL1/ATM- and epigenetically instructed damage responses

  T-cell prolymphocytic leukemia (T-PLL) is a rare and poor-prognostic mature T-cell malignancy. To address its incomplete molecular concept, we integrated large-scale profiling data of alterations in gene expression, allelic copy number (CN), and nucleotide sequences in 111 well-characterized patients. Besides prominent signatures of T-cell activation and prevalent clonal variants, we also identified novel hot-spots for CN variability, fusion molecules, alternative transcripts, and progression-associated dynamics. The overall lesional spectrum of T-PLL is mainly annotated to axes of DNA damage responses, T-cell receptor/cytokine signaling, and histone modulation. We formulate a multi-dimensional model of T-PLL pathogenesis centered around a unique combination of TCL1 overexpression with damaging ATM aberrations as initiating core lesions. The effects imposed by TCL1 cooperate with compromised ATM towards a leukemogenic phenotype of impaired DNA damage processing. Dysfunctional ATM appears inefficient in alleviating elevated redox burdens and telomere attrition and in evoking a p53-dependent apoptotic response to genotoxic insults. As non-genotoxic strategies, synergistic combinations of p53 reactivators and deacetylase inhibitors reinstate such cell death execution.

  Study EGAS00001002744

• NHLBI TOPMed: San Antonio Family Heart Study (SAFHS)

  The San Antonio Family Heart Study (SAFHS) is a complex pedigree-based mixed longitudinal study designed to identify low frequency or rare variants influencing susceptibility to cardiovascular disease, using whole genome sequence (WGS) information from 2,590 individuals in large Mexican American pedigrees from San Antonio, Texas. The major objectives of this study are to identify low frequency or rare variants in and around known common variant signals for CVD, as well as to find novel low frequency or rare variants influencing susceptibility to CVD. WGS of the SAFHS cohort has been obtained through three efforts. Approximately 540 WGS were performed commercially at 50X by Complete Genomics, Inc (CGI) as part of the large T2D-GENES Project. The phenotype and genotype data for this group is available at dbGaP under accession number phs000462. An additional ~900 WGS at 30X were obtained through Illumina as part of the R01HL113322 "Whole Genome Sequencing to Identify Causal Genetic Variants Influencing CVD Risk" project. Finally, ~1,150 WGS at 30X WGS were obtained through Illumina funded by a supplement as part of the NHLBI's TOPMed program. Extensive phenotype data are provided for sequenced individuals primarily obtained from the P01HL45522 "Genetics of Atherosclerosis in Mexican Americans" for adults and R01HD049051 for children in these same families. Phenotype information was collected between 1991 and 2016. For this dataset, the SAFHS appellation represents an amalgamation of the original SAFHS participants and an expansion that reexamined families previously recruited for the San Antonio Family Diabetes Study (R01DK042273) and the San Antonio Family Gall Bladder Study (R01DK053889). Due to this substantial examination history, participants may have information from up to five visits. The clinical variables reported are coordinated with TOPMed and include major adverse cardiac events (MACE), T2D status and age at diagnosis, glycemic traits (fasting glucose and insulin), blood pressure, blood lipids (total cholesterol, HDL cholesterol, calculated LDL cholesterol and triglycerides). Additional phenotype data include the medication status at each visit, classified in four categories as any current use of diabetes, hypertension or lipid-lowering medications, and, for females, current use of female hormones. Anthropometric measurements include age, sex, height, weight, hip circumference, waist circumference and derived ratios. PBMC derived gene expression assays for a subset of ~1,060 individuals obtained using the Illumina Sentrix-6 chip is also available from the baseline examination. The WGS data have been jointly called and are available in the current TOPMed accession (phs001215).

  Study phs001215

• CancerLocator: Non-Invasive Cancer Diagnosis and Tissue-of-Origin Prediction Using Methylation Profiles of Cell-Free DNA

  Background: The detection and characterization of cell-free DNA in plasma is one of the most promising new areas in cancer diagnosis. Liquid biopsy, unlike traditional tissue biopsy, has the potential to diagnose a variety of different malignancies. Results: Here we propose a probabilistic method, CancerLocator, which exploits the diagnostic potential of cell-free DNA by determining not only the presence but also the location of tumors. CancerLocator simultaneously infers the proportions and the tissue-of-origin of tumor-derived cell-free DNA in a blood sample using genome-wide DNA methylation data. We comprehensively evaluate CancerLocator with simulations and real data, and compare its performance with that of two established multi-class classification methods. We show that the predicted tumor burdens are highly consistent with the true values. In addition, when the proportion of tumor-derived DNAs in the cell-free DNAs is low, the two popular machine learning methods completely fail for cancer diagnosis, while CancerLocator successfully overcomes the challenge. CancerLocator also achieves promising results on patient plasma samples, despite the fact that the DNA methylation data from these samples has very low sequencing coverage. Conclusions: CfDNA methylation may be developed as an important approach for non-invasive early cancer diagnosis.

  Study EGAS00001002211