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• Pancreatic, Small-intestinal and Pulmonary Neuroendocrine Tumors

  Purpose: The primary origin of neuroendocrine tumor metastases can be difficult to determine by histopathology alone, but is critical for therapeutic decision making. DNA methylation-based profiling is now routinely used in the diagnostic workup of brain tumors. This has been enabled by the availability of cost-efficient array-based platforms. We have extended these efforts to augment histopathological diagnosis in neuroendocrine tumors. Experimental Design and Results: We compiled data of 69 small-intestinal, pulmonary, and pancreatic neuroendocrine tumors. These data were used to build a ridge regression calibrated random forest classification algorithm (NEN-ID) that predicts the origin of tumor samples with high accuracy (> 95%). The model was validated during 3x3 nested cross validation and tested in a local (n=26) and external (n=172) cohort. In addition, we show that our diagnostic approach is robust across a range of possible confounding experimental parameters such as tumor purity and array quality. A software infrastructure and online user interface was built to make the model available to the scientific community. Conclusions: This DNA methylation-based prediction model can be used in the workup for patients with neuroendocrine tumors of unknown primary. To facilitate validation and clinical implementation, we provide a user-friendly, publicly available web-based version of NEN-ID.

  Study EGAS00001004878

• Spatiotemporal Genomic Profiling of Intestinal Metaplasia Reveals Clonal Dynamics of Gastric Cancer Progression

  Intestinal metaplasia (IM) is a pre-malignant condition of the gastric mucosa associated with increased gastric cancer (GC) risk. We analyzed 1256 gastric samples (1152 IMs) from 692 subjects from a 10-year prospective study. We identified 26 IM driver genes in diverse pathways including chromatin regulation (ARID1A) and intestinal homeostasis (SOX9), largely occurring as subclonal events. Analysis of clonal dynamics between and within subjects, and also longitudinally across time, revealed that IM clones are likely transient but increase in size upon progression to dysplasia, with eventual transmission of genetic events to paired GCs. Single-cell and spatial profiling highlighted changes in tissue ecology and lineage heterogeneity in IM, including an intestinal stem-cell dominant cellular compartment linked to early malignancy. Expanded transcriptome profiling revealed expression-based molecular subtypes of IM, including a body-resident “pseudoantralized” subtype associated with incomplete histology, antral/intestinal cell types, ARID1A mutations, inflammation, and microbial communities normally associated with the healthy oral tract. We demonstrate that combined clinical-genomic models outperform clinical-only models in predicting IMs likely to progress. Our results raise opportunities for GC precision prevention and interception by highlighting strategies for accurately identifying IM patients at high GC risk and a role for microbial dysbiosis in IM progression.

  Study EGAS00001007067

• EGA FUSE Client

  EGA FUSE Client What is EGA FUSE Client? The EGA FUSE Client is a Java Native Runtime (JNR) based Filesystem in Userspace (FUSE) client that allows users to access authorised EGA files by presenting them in a virtual directory. This means that users can use authorised EGA files like regular files without having to download them first. The EGA FUSE Client is a useful tool for researchers who need to access and work with large amounts of EGA data. Why use EGA FUSE Client? The EGA FUSE Client provides several benefits for researchers working with EGA data: Efficient use of storage space: With the EGA FUSE Client, users can access authorised EGA files without having to download them first. This means that users can save storage space on their local machines. Faster access to data: Since users can access authorised EGA files directly through the EGA FUSE Client, they can work with the data more quickly than if they had to download the files first. Simplified workflow: The EGA FUSE Client presents authorised EGA files in a virtual directory, allowing users to work with the files like regular files. This simplifies the workflow for researchers who need to access and work with large amounts of EGA data. Get started with EGA FUSE Client To get started with EGA FUSE Client visit the EGA FUSE Client GitHub repository for more information and installation instructions.

  Documentation access/download/visualisation/fuse-client

• Effects of Metformin on Transcriptomic and Metabolomic Profiles in Breast Cancer Survivors Enrolled in the Randomized Placebo-Controlled MetBreCS Trial

  RNA from snap-frozen breast tissue biopsies were purified after lysing by tissuelyser (Qiagen) and using RNA Purification Plus Kit (Norgen biotek CORP, 47700) with additional on-column DNase-I treatment (Qiagen, 79254) at 27 °C. RNA purity and integrity (RIN) were quantified using RNA 6000 Nano kit (Agilent Technologies, 5067-1511) on the 4200 TapeStation (Agilent, Santa Clara, USA). Library preparation and 2x75bp paired-end of 160 ng total RNA input was performed using Illumina Stranded Total RNA Prep Ligation kit and Illumina HiSeq4000 system (Illumina, Sand Diego, CA, USA). RNA sequencing data from HiSeq4000 were quality checked and aligned to GRCh38 (GCA_000001405.15) reference genome using HISAT2 2.0.5 and submitted to subread v.1.5.2 for feature counts calculation. Finally, 36 paired biopsies samples (metformin n=26 and placebo n=12) were sequenced and included in the final analyses.

  Dataset EGAD50000001274

• NHLBI TOPMed: GOLDN Epigenetic Determinants of Lipid Response to Dietary Fat and Fenofibrate

  The GOLDN study was initiated to assess how genetic factors interact with environmental (diet and drug) interventions to influence blood levels of triglycerides and other atherogenic lipid species and inflammation markers (registered at clinicaltrials.gov, number NCT00083369). The study recruited Caucasian participants primarily from three-generational pedigrees from two NHLBI Family Heart Study (FHS) field centers (Minneapolis, MN and Salt Lake City, UT). Only families with at least two siblings were recruited and only participants who did not take lipid-lowering agents (pharmaceuticals or nutraceuticals) for at least 4 weeks prior to the initial visit were included. The diet intervention followed the protocol of Patsch et al. (1992). The whipping cream (83% fat) meal had 700 Calories/m2 body surface area (2.93 mJ/m2 body surface area): 3% of calories were derived from protein (instant nonfat dry milk) and 14% from carbohydrate (sugar). The ratio of polyunsaturated to saturated fat was 0.06 and the cholesterol content of the average meal was 240 mg. The mixture was blended with ice and flavorings. Blood samples were drawn immediately before (fasting) and at 3.5 and 6 hours after consuming the high-fat meal. The diet intervention was administered at baseline as well as after a 3-week treatment with 160 mg micronized fenofibrate. Participants were given the option to complete one or both (diet and drug) interventions. Of all participants, 1079 had phenotypic data and provided appropriate consent, and underwent whole genome sequencing through the Trans-Omics for Precision Medicine (TOPMed) program. Comprehensive phenotypic and pedigree data for GOLDN study participants are available through dbGaP phs000741.

  Study phs001359

• Genetic Epidemiology Network of Arteriopathy (GENOA)

  The Genetic Epidemiology Network of Arteriopathy (GENOA) is one of four networks in the NHLBI Family-Blood Pressure Program (FBPP). GENOA's long-term objective is to elucidate the genetics of target organ complications of hypertension, including both atherosclerotic and arteriolosclerotic complications involving the heart, brain, kidneys, and peripheral arteries. The longitudinal GENOA Study recruited European-American and African-American sibships with at least 2 individuals with clinically diagnosed essential hypertension before age 60 years. All other members of the sibship were invited to participate regardless of their hypertension status. Participants were diagnosed with hypertension if they had either 1) a previous clinical diagnosis of hypertension by a physician with current anti-hypertensive treatment, or 2) an average systolic blood pressure ≥ 140 mm Hg or diastolic blood pressure ≥ 90 mm Hg based on the second and third readings at the time of their clinic visit. The Family Blood Pressure Program (FBPP), GENOA's parent program, is an unprecedented collaboration to identify genes influencing blood pressure (BP) levels, hypertension, and its target-organ damage. This program has conducted over 21,000 physical examinations, assembled a shared database of several hundred BP and hypertension-related phenotypic measurements, completed genome-wide linkage analyses for BP, hypertension, and hypertension associated risk factors and complications, and published over 130 manuscripts on program findings. The FBPP emerged from what was initially funded as four independent networks of investigators (HyperGEN, GenNet, SAPPHIRe and GENOA) competing to identify genetic determinants of hypertension in multiple ethnic groups. Realizing the greater likelihood of success through collaboration, the investigators created a single confederation with program-wide and network-specific goals.

  Study phs001238

• NHLBI TOPMed: Genetic Epidemiology Network of Arteriopathy (GENOA)

  The Genetic Epidemiology Network of Arteriopathy (GENOA) is one of four networks in the NHLBI Family-Blood Pressure Program (FBPP). GENOA's long-term objective is to elucidate the genetics of target organ complications of hypertension, including both atherosclerotic and arteriolosclerotic complications involving the heart, brain, kidneys, and peripheral arteries. The longitudinal GENOA Study recruited European-American and African-American sibships with at least 2 individuals with clinically diagnosed essential hypertension before age 60 years. All other members of the sibship were invited to participate regardless of their hypertension status. Participants were diagnosed with hypertension if they had either 1) a previous clinical diagnosis of hypertension by a physician with current anti-hypertensive treatment, or 2) an average systolic blood pressure = 140 mm Hg or diastolic blood pressure = 90 mm Hg based on the second and third readings at the time of their clinic visit. Only participants of the African-American Cohort were sequenced through TOPMed. The Family Blood Pressure Program (FBPP), GENOA's parent program, is an unprecedented collaboration to identify genes influencing blood pressure (BP) levels, hypertension, and its target-organ damage. This program has conducted over 21,000 physical examinations, assembled a shared database of several hundred BP and hypertension-related phenotypic measurements, completed genome-wide linkage analyses for BP, hypertension, and hypertension associated risk factors and complications, and published over 130 manuscripts on program findings. The FBPP emerged from what was initially funded as four independent networks of investigators (HyperGEN, GenNet, SAPPHIRe and GENOA) competing to identify genetic determinants of hypertension in multiple ethnic groups. Realizing the greater likelihood of success through collaboration, the investigators created a single confederation with program-wide and network-specific goals. Comprehensive phenotypic data for GENOA study participants are available through dbGaP phs001238.

  Study phs001345

• The Human Phenotype Project (HPP) is a large-scale deep-phenotype prospective longitudinal and ethnically diverse cohort

  The Human Phenotype Project (HPP) is a large-scale deep-phenotype prospective longitudinal and ethnically diverse cohort and biobank that we established. To date, approximately 28,000 participants have enrolled in the study, with over 13,000 having completed their initial visit. The project is aimed at identifying novel molecular signatures with diagnostic, prognostic and therapeutic value, and at developing AI-based predictive models for disease onset and progression. A unique feature of the HPP is its deep and longitudinal profiling that includes medical history, lifestyle and nutritional habits, vital signs, anthropometrics, blood tests, continuous glucose and sleep monitoring, imaging modalities and molecular profiling of the transcriptome, genetics, gut, vaginal and oral microbiome, metabolome and immune system. For several of these modalities, the HPP is the first or largest cohort of its kind. Our analyses of this data provide novel insights into the variation of phenotypes with age and ethnicity, highlighting the importance of having ethnically diverse cohorts and the need for establishing age-dependent norms. We demonstrate how the HPP can be used to unravel personalized molecular signatures of disease by comparison to patient-specific and disease-specific matched healthy controls. Leveraging the extensive dietary and lifestyle HPP data, we systematically identify associations between lifestyle factors and health outcomes. Finally, we present a multi-modal foundation AI model that is trained using self-supervised learning on diet and CGM data and outperforms existing methods in predicting future onset of disease. We extend this AI framework to integrate all data modalities of each subject as a continuous sequence of diverse medical events, creating a digital twin that can simulate interventions and predict health trajectories and outcomes.

  Study EGAS00001008040

• Oncogenic Ectodomain deletion of FGFR1 caused by Breakage-Fusion-Bridges in Squamous Cell lung Cancer

  The identification of recurrent 8p11.23 amplifications including FGFR1 raised the hope of a treatable target in squamous cell lung cancer (SQLC). However, only a minority of patients with FGFR1-amplified tumors respond to single agent inhibitor therapy targeting FGFR. To understand the underlying mechanism of FGFR1 dependency, we performed whole genome and transcriptome sequencing of 25 FGFR1-amplified primary tumors with unknown response upon FGFR inhibition. In addition, we performed deep sequencing of 26 FGFR1-amplified samples whereof the response upon FGFR inhibition was known for 25 samples. In both cohorts we identified intra-chromosomal tail-to-tail breaks close to the FGFR1 transcription start site, being responsible for focal amplification of FGFR1. These specific breaks are caused by a Breakage-Fusion-Bridge-like (BFB-like) mechanism. Here, we associate these breaks with FGFR inhibitor sensitivity. Moreover, in some cases these breaks are located within the open reading frame of FGFR1, which leads to the expression of an ΔEC-FGFR1 transcript that lacks the ecto-domain. Overexpression of ΔEC-FGFR1 transforms Baf3 cells and lead to an FGFR1-dependent phenotype. Our results demonstrate that the truncation of the FGFR1 ectodomain is a frequent event in 8p11.23-amplified squamous cell lung cancer caused by tail-to-tail breaks. These breaks might be used as a predictive therapeutic marker to stratify patients for FGFR-inhibitor therapy.

  Study EGAS00001005059

• Neoadjuvant immune checkpoint blockade in mismatch-repair proficient colon cancers

  Immune checkpoint blockade has led to paradigm shifts in the treatment of various tumour types, yet limited efficacy has been observed in patients with metastatic mismatch-repair proficient (pMMR) colorectal cancer. Here we report an in-depth analysis of patients with early-stage pMMR colon cancer from the phase II NICHE study (ClinicalTrials.gov: NCT03026140). A total of 31 patients received neoadjuvant treatment of nivolumab plus ipilimumab followed by surgery. The response rate was 26% and included six patients with a major pathological response (≤10% residual viable tumour). One patient with an ongoing clinical complete response did not undergo surgery. Responses were observed despite a low tumour mutational burden in all tumours, while chromosomal genomic instability scores were significantly higher in responders compared to non-responders. Responding tumours were more likely to be TP53 mutant, KRASG12 wildtype and had significantly higher baseline expression of proliferation signatures and TCF1. Imaging mass cytometry also revealed a higher percentage of Ki-67+ cancer and Ki-67+ CD8+ T cells in responders compared to non-responders. Meanwhile, in non-responders, we observed an enrichment for an inflamed-fibrotic microenvironment associated with TGF-β expression, hinting towards possible resistance mechanisms. These results provide a comprehensive analysis of response to neoadjuvant ICB in early-stage pMMR colon cancers and identify potential biomarkers for patient selection.

  Study EGAS50000000856