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• The Innate Immune Response as a Therapeutic Target for Cutaneous Leishmaniasis

  The overall goal of the proposed project is to identify innate host functions that contribute to cure or failure during antileishmanial drug therapy, and their related biomarkers. Results from this project enabled the identification of host-specific predictive and prognostic signatures of therapeutic responsiveness, and the bases for rational selection of host-targeted therapeutics that redirect inflammation and revert pathogenicity. Through sequential transcriptomic profiling of blood monocytes (Mo), neutrophils (Nφ), and eosinophils (Eφ) over the course of systemic treatment with meglumine antimoniate, we discovered that a heightened and sustained Type I interferon (IFN) response signature is a hallmark of treatment failure (TF) in Cutaneous Leishmaniasis (CL) patients. The transcriptomes of pre-treatment, mid-treatment and end-of-treatment samples were interrogated to identify predictive and prognostic biomarkers of TF. Results from this study instigate the evaluation of Type-I IFN responses as new immunological targets for host-directed therapies for treatment of CL, and highlight the feasibility of using transcriptional signatures as predictive biomarkers of outcome for therapeutic decision making.

  Study phs003545

• Pharmacokinetics and Pharmacogenomics of Ribociclib in Race-Based Cohorts (LEANORA)

  Underrepresented populations' participation in clinical trials remains limited, and the potential impact of genomic variants on drug metabolism remains elusive. This study aimed to assess the pharmacokinetics (PK) and pharmacogenomics (PGx) of ribociclib in self-identified Black women with hormone receptor positive (HR+)/human epidermal growth factor receptor 2-negative (HER2) advanced breast cancer. LEANORA (NCT04657679) was a prospective, observational, multicenter cohort study involving 14 Black women. PK and PGx were evaluated using tandem mass spectrometry and PharmacoScan microarray. CYP3A5*3, CYP3A5*6, and CYP3A5*7 variants were genotyped and CYP3A5 phenotypes were constructed from these data. We observed 7 poor metabolizers (PM), 6 intermediate metabolizers (IM), and one normal metabolizer (NM). The area under the curve of plasma concentration versus time curve (AUC) of ribociclib did not differ between PMs (39,230 hr*ng/mL) and IM/NMs (43,546 hr*ng/mL; P=0.38). The incidence of adverse events (AEs) was also similar. We found no association between CYP3A5 genotype and ribociclib exposure. Continued efforts are needed to include diverse populations in clinical trials to ensure equitable treatment outcomes.

  Study phs003770

• Proteogenomic Analysis of CALGB40601 (ALLIANCE) a Neoadjuvant Phase III HER2-Positive Breast Cancer Trial

  80 frozen core needle biopsies from 54 HER2+ breast cancer patients from the CALGB 40601 trial (NCT00770809) were processed for proteogenomic analysis to identify genes, proteins, and phosphosites associated with pathological complete response to neodjuvant anti-HER2 therapies. The final set included 22 patients treated with trastuzumab plus lapatinib in combination with pacletaxel (THL arm), 24 patients treated with trastuzumab in combination with pacletaxel (TH arm), and 8 patients treated lapatinib in combination with pacletaxel (TL arm). Principal findings of this study included identifying negative cases misdiagnosed as HER2+ that did not respond to targeted therapy and observing higher levels of two biomarker candidates in non-pCR tumors. Mass spec-based proteomics and phosphoproteomics data generated from 75 biopsies (all 54 patients) will be made available via the Proteomic Data Commons. Whole exome- (67 biopsies from 49 patients) and RNA-sequencing (52 biopsies from 39 patients) data for the subset profiled with proteogenomics will be made available through dbGaP, but genomic and transcriptomic profiling data for the whole cohort has previously been deposited (phs001570).

  Study phs003576

• Fetal Genomics Consortium (FGC)

  Many of the congenital anomalies and associated genomic variants identified during prenatal care are rare, requiring aggregation and harmonization to assure their appropriate clinical interpretation and to support the expanding utility of genomics in perinatal medicine. The primary step in accomplishing this is the creation of interoperability allowing collection, collaborative storage, dissemination and use of harmonized and vetted genomic and phenotypic data. The overall goal of this project is to generate a prenatal repository for both clinical care and research ensuring data are Findable; Accessible; Interoperable; and Reusable. The specific goals are: (1) collect and organize data contributions from multiple sites using the cloud-based Terra platform; (2) establish a governance structure for data contributions across sites; (3) develop and implement a pipeline for phenotype driven analysis and implementation of fetal specific Phenopackets on Terra; (4) generate a searchable callset of genomic variants and phenotype features on Terra; and (5) explore methods for facilitating broad access and sharing of longitudinal phenotype and genomic data facilitating genomic analysis in the prenatal space.

  Study phs003193

• 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

• Chromatin remodeler CHD7 regulates the stem cell identity of human neural progenitors

  Multiple congenital disorders often present complex phenotypes, but how the mutation of individual genetic factors can lead to multiple defects remains poorly understood. In the present study, we used human neuroepithelial (NE) cells and CHARGE patient-derived cells as an in vitro model system to identify the function of chromodomain helicase DNA-binding 7 (CHD7) in NE?neural crest bifurcation, thus revealing an etiological link between the central nervous system (CNS) and craniofacial anomalies observed in CHARGE syndrome. We found that CHD7 is required for epigenetic activation of superenhancers and CNS-specific enhancers, which support the maintenance of the NE and CNS lineage identities. Furthermore, we found that BRN2 and SOX21 are downstream effectors of CHD7, which shapes cellular identities by enhancing a CNS-specific cellular program and indirectly repressing non- CNS-specific cellular programs. Based on our results, CHD7, through its interactions with superenhancer elements, acts as a regulatory hub in the orchestration of the spatiotemporal dynamics of transcription factors to regulate NE and CNS lineage identities.

  Study JGAS000131

• Single cell RNA seq of breast cancer stem cells

  RNA sequences of breast cancer have been investigated for many patients. Recently it has been shown that there are intra-heterogeneity in tumor tissues. When the tumor cells were sequenced in bulk condition, only the major populations' mRNA will be detected. With respect to breast cancer, it has been also reported that cancer cells can sub-gropued into cancer stem cells and non-cancer stem cells. Although the mRNA expressions' difference between this two groups has been profoundly investigated, whether each group is composed by unique cell or not is yet to be elucidated. Since cancer stem cells are the thought to be the major contributor of metastasis and/or recurrence, we focused on cancer stem cells in this study. We separated cancer cells into cancer stem cells and non-cancer stem cells exploiting cancer stem cell specific surface markers. Thereafter, we sequenced mRNA of cancer stem cells in single cell resolution. From this result, we examined whether these cells can be sub-grouped or not.

  Study JGAS000305

• Introducing Federated EGA Affiliates: a newly defined tier in the Federated EGA Network

  We're happy to announce that we are now accepting Affiliates in the Federated EGA Network! Federated EGA is a global network of repositories enabling secure discovery and access to sensitive human data. Currently, Federated EGA consists of Central EGA (CEGA), which serves the global community, and nine national Nodes that serve respective jurisdictions. Did you know that the Federated EGA (FEGA) has always envisioned a third tier within the network? This brings us to FEGA Affiliates, recently defined in the newly approved "Federated EGA Structure and Organisation" document. This new tier broadens the range of institutions or organisations that can become part of FEGA. Thus begins a new era for the network. What is a FEGA Affiliate? A FEGA Affiliate archives and serves controlled-access data within its own governance scope, while still participating in federated discovery through the EGA catalogue. Affiliates can be individual organisations or institutions, healthcare genomics initiatives, consortia of institutions, as well as project-specific consortia (national or international). In practical terms, a FEGA Affiliate: Hosts and safeguards the data it archives. Submits non-personal metadata to CEGA so studies are discoverable and can receive EGA accessions. Manages permissions and data access workflows for its datasets. Provides data access and/or distribution, along with support, to authorised users. Key takeaways about FEGA Affiliates FEGA is now organised into three tiers: CEGA, FEGA Nodes, and FEGA Affiliates. Affiliates archive data from their own organisation and/or selected partner institutions (for example, an international consortium). Affiliates make studies discoverable through the EGA catalogue by submitting non-personal metadata for accessioning. Access decisions and conditions are managed locally by the Affiliate (e.g. distribution or access in a trusted research environment). Are you considering whether your institution or project might be a good fit as a FEGA Affiliate? Would you like to learn more about this tier? We have published a blog post that addresses potential common questions, providing answers on this topic. You can read it here.

  Blog fega-affiliates

• Passive and active DNA methylation and the interplay with genetic variation in gene regulation

  DNA methylation is an essential1 epigenetic mark whose role in gene regulation and its dependency on genomic sequence and environment are not yet fully understood2,3. In this study we provide novel insights into the mechanistic relationships between genetic variation, DNA methylation and transcriptome sequencing data in three different cell-types of the GenCord human population cohort4. We find that the association between DNA methylation and gene expression variation among individuals are likely due to different mechanisms from those establishing methylation-expression patterns during differentiation. Furthermore, cell-type differential DNA methylation may delineate a platform in which more local inter-individual changes may respond to or act in gene regulation. We show that unlike genetic regulatory variation, DNA methylation alone does not significantly drive allele specific expression.. Finally, inferred mechanistic relationships using genetic variation as well as correlations with TF abundance reveal both a passive and active role of DNA methylation to regulatory interactions influencing gene expression.

  Study EGAS00001000446

• HIV-phyloTSI: Subtype-independent estimation of time since HIV-1 infection for cross-sectional measures of population incidence using deep sequence data

  Estimating the time since HIV infection (TSI) at population level is essential for tracking changes in the global HIV epidemic. Most methods for determining TSI give a binary classification of infections as recent or non-recent within a window of several months, and cannot assess the cumulative impact of an intervention. We developed a Random Forest Regression model, HIV-phyloTSI, which combines measures of within-host diversity and divergence to generate continuous TSI estimates directly from viral deep-sequencing data, with no need for additional variables. HIV-phyloTSI provides a continuous measure of TSI up to 9 years, with a mean absolute error of less than 12 months overall and less than 5 months for infections with a TSI of up to a year. It performs equally well for all major HIV subtypes based on data from African and European cohorts. We demonstrate how HIV-phyloTSI can be used for incidence estimates on a population level.

  Study EGAS50000000895