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• Parallel Genomic Alterations of Antigen and Payload Targets Mediate Polyclonal Acquired Clinical Resistance to the Antibody Drug Conjugate Sacituzumab Govitecan

  Sacituzumab Govitecan (SG), a novel antibody drug conjugate (ADC) incorporating the anti-TROP2 antibody hRS7 conjugated to a topoisomerase-1 inhibitor (SN-38) payload, is the first ADC to be approved for advanced triple negative breast cancer (TNBC). However, mechanisms governing therapeutic resistance to SG are not known. We sought to identify mechanisms of de novo and acquired resistance to SG through unbiased whole-exome sequencing (WES) and RNA sequencing analysis of pre-treatment and multi-site post-progression (autopsy) tumor specimens. We examined three metastatic TNBC cases exhibiting (1) de novo progression, (2) stable disease, and (3) a deep response followed by progression, then mapped the temporal and spatial genomic evolution of acquired resistance in the responding patient. We then conducted additional pre-clinical experiments to validate the observed resistance mechanisms. TROP2 RNA and gene copy number were associated with de novo resistance, as case (1) was found to have absent TROP2 expression in all specimens, case (2) expressed TROP2, while case (3) exhibited both expression and focal genomic amplification of the TACSTD2/TROP2 locus. The genomic phylogeny tree inferred from case (3) post-progression specimens revealed one branch harboring an acquired canonical E418K resistance mutation in TOP1 (encoding topoisomerase 1) and a subsequent sub-clonal TOP1 inactivating frameshift mutation, while a distinct branch exhibited acquisition of a novel T256R missense mutation in TACSTD2 (encoding TROP2). Both the TOP1- and TACSTD2-mutant clones seeded multiple distinct metastatic sites. Through reconstitution experiments in TROP2 negative cells we found that TROP2 T256R is a stable protein with defective cell membrane localization and reduced cell surface binding by RS7 compared to wild-type TROP2. Collectively, these findings underscore TROP2 as a determinant of initial response to SG, and they reveal parallel and mutually exclusive polyclonal molecular mechanisms of acquired resistance involving the direct antibody target and drug payload target in distinct metastatic subclones of a single patient. While further research is needed to extend these novel findings, this study highlights the specificity of SG and illustrates how identifying such mechanisms will inform rational therapeutic strategies to overcome ADC resistance.  

  Study phs002555

• HCI-PDX Trial Center for Breast Cancer Therapy

  The HCI-PDX Trial Center for Breast Cancer Therapy study is a collection of patient-tumor samples that are serially established as patient-derived tumor xenografts (human tumor in mouse) and matching organoids. For this study, we describe valuable methods and resources to generate organoids and use them as cost-effective models for precision drug screens. This study leveraged whole-exome sequencing, RNAseq, and SNP-array data to illustrate how the heterogeneity of tumors is preserved in xenograft and organoid models. Sequencing files are provided for whole-exome and RNAseq data. Processed copy number variant calls from the SNP arrays are also available. A full description of the study can be found in the article entitled, "A human breast cancer-derived xenograft and organoid platform for drug discovery and precision oncology," written by Guillen et al., 2022 in Nature Cancer (PMID: 35221336).

  Study phs002479

• INCLUDE Data Hub: NDA GUIDs for Down Syndrome Research

  The INCLUDE (INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE) Project is an NIH-wide collaboration that seeks to improve health and quality of life for people with Down syndrome. The INCLUDE Project Data Coordinating Center (DCC) and partners created the INCLUDE Data Hub, a centralized data resource that allows access to large-scale clinical and multi-omics datasets specific to Down syndrome and supports collaborative, cloud-based analysis to accelerate scientific discoveries related to Down syndrome and its co-occurring conditions. The INCLUDE Data Hub includes an innovative researcher data repository, a portal, and a cloud-based platform for data analysis. The portal provides access to de-identified demographics and clinical metadata, as well as multi-omics datasets, including whole genome sequences, transcriptomes, proteomes, and metabolomes. The INCLUDE Data Hub uses a 'registered access' model, whereby users can access the portal and associated data after agreeing to terms of use. From the Data Hub, users can also reach 'controlled access' data (e.g., whole genome sequences) only for those studies for which they have obtained approval by an NIH Data Access Committee through the corresponding dbGaP study. A thoughtful linkage strategy to identify duplicate participants across studies enables researchers to merge multiple datasets and data types to create richer datasets and reduce costly redundancies in large-scale data generation (e.g., -omics) while mitigating potential risks introduced by linkage.Based on recommendations from the NICHD Office of Data Science and Sharing, which completed a comprehensive assessment of existing Privacy Protecting Record Linkage (PPRL) and associated data governance solutions, the INCLUDE DCC and the associated NIH Steering Committee have implemented NIMH Data Archive Global Unique Identifiers (NDA GUIDs) in the INCLUDE Data Hub. The NDA GUID Tool is a government-owned and operated PPRL technology that enables researchers to link data from multiple sources to the same individual without revealing personally identifiable information (PII). With the NDA GUID Tool, the same participant information will return the same GUID whenever or wherever it is entered. The GUID itself is not personally identifiable information or protected health information. Sharing data with NDA GUIDs allows approved researchers to link together data on a single participant, even if the data were collected at different locations or through different studies or are distributed from different data repositories. This dbGaP study enables researchers to access an INCLUDE GUID Mapping File that includes all available NDA GUIDs and their associations to study-specific Participant IDs across studies in the INCLUDE Data Hub. This dbGaP study only distributes NDA GUIDs associated with the INCLUDE Data Hub datasets. To access the associated controlled-access datasets, add the corresponding dbGaP studies to your Data Access Request. A list of these studies is available on the INCLUDE Data Hub Portal: https://portal.includedcc.org/studies.

  Study phs003678

• Gut metagenomic data of 2,338 Pinggu adults

  Here we exploited a Han Chinese population-based cohort with extensive host metadata established in the Pinggu (PG) district of Beijing, and investigated gut microbiota from 2,338 adults (26-76 years) by metagenomic sequencing, revealing associations of the gut microbiota with sex, sex hormones, age, and a number of clinical and metabolic parameters.

  Study EGAS00001004820

• GoT2D: Genetics of Type 2 Diabetes, a study of the the genetic architecture of type 2 diabetes using low pass whole genome sequencing and high density SNP genotyping in 2,657 individuals.

  The Genetics of Type 2 Diabetes Consortium (GoT2D) is a collaboration between the University of Michigan, the Broad Institute and the Wellcome Trust Centre for Human Genetics. The overall aim is to extend upon recent efforts, such as genome-wide association studies (GWAS) and large scale meta-analyses. While they have proved successful at mapping genomic loci that influence human diseases, like type 2 diabetes, much of the heritability remains unexplained. In this study, we use next generation sequencing and genotyping technologies to query for lower frequency variants in the human genome. Thereby, allowing a deeper characterization of the spectrum of alleles associated with type 2 diabetes risk, and a better assessment of the genes that play a role in the etiology of type 2 diabetes development. We studied 1,326 T2D cases and 1,331 normoglycemic controls from Northern and Central Europe (Sweden, Finland, UK, and Germany). To efficiently characterize the entire genome sequence of each individual, we performed low-coverage (~5x) whole-genome sequencing, augmented by deep coverage (~100x) sequencing of the exome, and dense (2.5M) single nucleotide polymorphism (SNP) genotyping using the HumanOmni2.5 array. The data deposited in EGA will include all the Swedish, Finnish, UK, and German samples.

  Study EGAS00001001459

• Systematic comparative analysis of single-nucleotide variant detection methods from single-cell RNA sequencing data

  In this study, we performed systematic comparative analysis of seven widely-used SNV-calling methods, including SAMtools, the GATK Best Practices pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, on both simulated and real single-cell RNA-seq datasets. We generated SMART-seq2 data for 70 CD45- single cells, which were derived from two colorectal cancer patients (P0411 and P0413). The average sequencing depths of these cells were 1.4 million reads per cell. We also generated tumor and adjacent normal bulk WES data, as well as tumor bulk RNA-seq data for these patients.

  Dataset EGAD00001005373

• Illumina HumanCoreExome genotyping data from the British Society for Surgery of the Hand Genetics of Dupuytren’s Disease consortium (BSSH-GODD consortium) collection

  Dupuytren's Disease (DD - OMIM126900) is the most common heritable disorder of connective tissue. It is a fibroproliferative disorder of the palmer fascia, causing flexion contractures of affected digits. DD affects men more commonly than women. DD is an archetypal complex disease, with multiple genetic and environmental factors affecting the final expression of the disease phenotype. The incidence increases with age, and the prevalence of DD is therefore increasing as the UK population ages. Half of all patients present before age 60. DD causes significant functional impairment, and severe contractures can lead to permanent disability. The mainstay of current treatment is surgery, but recurrence and complications are both high. For severe contractures, the only suitable treatment option is amputation. The direct costs to the NHS are high, and underestimate the true economic costs to society. We collected salivary samples from adults in the UK who have had surgery for DD. We have genotyped these samples using the Illumina HumanCoreExome Beadchips. https://research.ndorms.ox.ac.uk/public/dupuytrens/what-is-dupuytrens-disease/

  Study EGAS00001001206

• Evolution of GBM through therapy

  Primary glioblastoma (GBM) tumours recur following treatment. This is likely due to intratumour heterogeneity (ITH), which reduces the effectiveness of cancer therapies by enabling therapy-driven tumour evolution: Darwinian selection of genotypically and/or phenotypically distinct cells (subclones) that resist treatment to seed regrowth of an even less treatable recurrence. To investigate this we sequenced a pilot cohort of nine paired primary and locally recurrent GBM tumours, alongside matched blood samples, in order to begin characterising therapy resistant cells and thereby infer the mechanisms by which they evaded treatment. These data were included in the first data release from the Glioma Longitudinal AnalySiS (GLASS) consortium.

  Study EGAS00001003546

• NHLBI TOPMed - NHGRI CCDG: The Vanderbilt AF Ablation Registry

  The Vanderbilt Atrial Fibrillation Ablation Registry (VAFAR) was founded in 2011. Patients with AF referred for AF ablation are prospectively enrolled. A detailed clinical history is recorded, along with imaging data (cardiac MRI or CT). Blood samples are obtained for DNA extraction at the time of ablation. Details of the ablation procedure are recorded. Patients are longitudinally followed to monitor for AF recurrence. VAFAR contributed 171 samples submitted to dbGaP for WGS: 115 were from male subjects, of which 113 were white/non-Hispanic and 2 were Hispanic; 56 were from females, of which all 56 were white/non-Hispanic.

  Study phs000997

• Melanoma_post_mortem_analysis

  This is a targeted pulldown validation in support of the existing whole-genome sequencing study of melanoma metastases (Canapps ID:1888). We are studying the genomic evolution of cutaneous melanoma metastases. In this pulldown analysis we are specifically sequencing the subclonal variants that we believe account for the variability between the metastases.

  Study EGAS00001003531