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• Transcriptome of 2-Hydroxypropyl-Beta-Cyclodextrin Treatment in Niemann-Pick Disease Type C1

  Niemann-Pick type C (NPC) disease is a rare and fatal lysosomal storage disorder. Classically, children with NPC demonstrate neurological dysfunction with cerebellar ataxia, dysarthria, seizures, vertical gaze palsy, motor impairment, dysphagia, psychotic episodes, and progressive dementia. In general, adolescent and adult onset forms have a more insidious onset and slower progression. As part of a multi-omics approach to address the genetic architecture of NPC1 disease, we have recently completed a transcriptome analysis using 43 primary NPC1 patient-derived fibroblasts from an NIH-cohort study (NCT00344331) where extensive clinical data has been obtained regarding the natural history of the disease. Initial transcriptome analysis of this dataset demonstrated a set of 485 genes that are significantly upregulated in patient samples and subsequently downregulated in response to 2-hydroxypropyl-beta-cyclodextrin treatment. 

  Study phs002392

• Genome-wide integrative analysis of pediatric pancreatoblastoma

  Pancreatoblastoma is the most common pancreatic malignancy of young children, but its molecular pathogenesis remains poorly understood. To understand the molecular pathogenesis of pancreatoblastoma, we comprehensively analysed the whole exome sequencing, RNA sequencing, SNP array, and methylation array data of pancreatoblastoma.

  Study JGAS000088

• The chemotherapeutic CX-5461 is extremely mutagenic and may increase cancer risk

  Deposited here are whole-genome sequencing bam or fastq files from the experimental isogenic cell lines used in the study "The chemotherapeutic CX-5461 is extremely mutagenic and may increase cancer risk, Koh, Gene (2023)". The bam files were aligned to GRCh38/hg38 using BWA-MEM. The corresponding variant call data have been deposited on Mendeley Data, V2, doi: 10.17632/d58cv549v6.2

  Dataset EGAD50000000036

• High-resolution testing of ctDNA dynamics predicts survival in metastatic NSCLC

  One of the great challenges of therapeutic oncology is determining who might achieve survival benefit from a particular therapy. Circulating tumor DNA (ctDNA) provides real-time assessments of patient prognosis and response to treatment using a simple blood draw. While ctDNA positivity is established as a poor prognostic factor, studies on longitudinal ctDNA dynamics have been small and non-randomized, with ctDNA assessments done at disparate time points. To address this, we performed high-sensitivity longitudinal ctDNA testing in 466 patients across 5 time points (1,954 samples total) in a randomized phase III study comparing different chemotherapy-immunotherapy combinations. We leverage machine learning to jointly model multiple ctDNA metrics to predict overall survival in a training/testing framework. _ . Treatment initiation correlated with reductions in ctDNA levels, and training of our machine learning model suggests that assessment of ctDNA dynamics at C3D1 (cycle 3 day 1) of chemo-IO treatment may be optimal to predict OS. The model performs well in the hold-back test data, enabling stratification of patients with Stable Disease (SD) into high-risk vs low-intermediate-risk (HR = 3.2 [2.0-5.3], p <0.001; median 7.1 versus 22.3 months respectively); similarly, the model stratifies patients with a Partial Response (PR) (HR =3.3 [1.7-6.4], p <0.001; median 8.8 versus 28.6 months). Importantly, the model validates well in an external cohort of patients in a different treatment setting and assayed with a different ctDNA technology, in which model predictions similarly identified high-risk patients (OS HR=3.73 [1.83-7.60], logrank p=0.00012). Simulations of clinical trial scenarios employing our ctDNA model further suggest that early ctDNA testing outperforms early radiographic imaging for predicting trial outcomes (increasing the rate of ‘True Go’ decisions by 5.2 - 22.8% depending on the drug combination). Overall, we show that measuring ctDNA dynamics during the course of therapy dramatically improves patient risk stratification, and may provide a means to differentiate between competing therapies at an early time point during clinical trials.

  Study EGAS00001006703

• Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma

  Immune checkpoint inhibitors are effective cancer treatments, but molecular determinants of clinical benefit are unknown. Ipilimumab and tremelimumab are antibodies against cytotoxic T-lymphocyte antigen 4 (CTLA-4). Anti-CTLA-4 treatment prolongs overall survival in patients with melanoma. CTLA-4 blockade activates T cells and enables them to destroy tumor cells. We obtained tumor tissue from patients with melanoma who were treated with ipilimumab or tremelimumab. Whole-exome sequencing was performed on tumors and matched blood samples. Somatic mutations and candidate neoantigens generated from these mutations were characterized. Neoantigen peptides were tested for the ability to activate lymphocytes from ipilimumab-treated patients. Malignant melanoma exomes from 64 patients treated with CTLA-4 blockade were characterized with the use of massively parallel sequencing. A discovery set consisted of 11 patients who derived a long-term clinical benefit and 14 patients who derived a minimal benefit or no benefit. Mutational load was associated with the degree of clinical benefit (P = 0.01) but alone was not sufficient to predict benefit. Using genomewide somatic neoepitope analysis and patient-specific HLA typing, we identified candidate tumor neoantigens for each patient. We elucidated a neo-antigen landscape that is specifically present in tumors with a strong response to CTLA-4 blockade. We validated this signature in a second set of 39 patients with melanoma who were treated with anti-CTLA-4 antibodies. Predicted neoantigens activated T cells from the patients treated with ipilimumab.

  Study phs001041

• Validation of a Haloplex platform for targeted re-sequencing of the exons of 25 genes

  We recently used the Agilent SureSelect platform to re-sequence a set of genes known to be mutated in human AML. The results from 10 AML DNA samples were very satisfactory, but the effort required was significant. Thus, we decided to re-sequence the same genes using the Haloplax system for target enrichment in 48 AML samples. We planned to do this using MiSeq and have data from a pilot of 3 samples. The data is promising but coverage appears pathcy so far. However, in order to get a better understanding of the data we will need deeper sequencing. We will need two lanes of HiSeq to get the same degree coverage as Sureselect. his data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000603

• Ameloblastoma Cell Line Resource

  Ameloblastoma (AB) is an odontogenic tumor that is locally destructive to the jaw bone. Treatment entails surgical resection, but AB often recurs locally. Recent driver mutations have been identified in the MAPK and Hedgehog pathways. However, translation to molecularly-targeted therapies has been hampered by the lack of AB cell line models. The goal of our study has been to create a new AB cell line resource that reflects the spectrum of AB driver mutations. We created 6 new AB cell lines, and by targeted exome sequencing, defined their driver mutations. We showed the utility of these cell lines in preclinical studies of oncogene dependence and drug sensitivity (which includes whole transcriptome assays).

  Study phs002753

• Tracing the origin of disseminated tumor cells in breast cancer using single-cell sequencing

  Background Single-cell micro-metastases of solid tumors often occur in the bone marrow. These disseminated tumor cells (DTCs) may resist therapy and lay dormant or progress to cause overt bone and visceral metastases. The molecular nature of DTCs remains elusive, as well as when and from where in the tumor they originate. Here, we apply single-cell sequencing to identify and trace the origin of DTCs in breast cancer. Results We sequence the genomes of 63 single cells isolated from six non-metastatic breast cancer patients. By comparing the cells DNA copy number aberration (CNA) landscapes with those of the primary tumors and lymph node metastasis, we establish that 53% of the single cells morphologically classified as tumor cells are DTCs disseminating from the observed tumor. The remaining cells represent either non-aberrant ‘normal’ cells or aberrant cells of unknown origin that have CNA landscapes discordant from the tumor. Further analyses suggest that the prevalence of aberrant cells of unknown origin is age-dependent, and that at least a subset is hematopoietic in origin. Evolutionary reconstruction analysis of bulk tumor and DTC genomes enables ordering of CNA events in molecular pseudo-time and traced the origin of the DTCs to either the main tumor clone, primary tumor subclones, or subclones in an axillary lymph node metastasis. Conclusions Single-cell sequencing of bone marrow epithelial-like cells, in parallel with intra-tumor genetic heterogeneity profiling from bulk DNA, is a powerful approach to identify and study DTCs, yielding insight into metastatic processes. A heterogeneous population of CNA-positive cells is present in the bone marrow of non-metastatic breast cancer patients, only part of which are derived from the observed tumor lineages.

  Study EGAS00001002102

• Drug Development against Tumor Microtube Networks in Glioblastoma

  Glioblastomas are aggressive brain tumors that resist current therapies by hijacking neurodevelopmental programs to invade the brain and form resilient multicellular networks. Tumor Microtubes (TMs), neurite-like processes extended by cancer cells, drive this pathobiology, but TM-inhibiting drugs are lacking. Here we developed a comprehensive, combined in vitro and in vivo drug screening approach, including novel AI-based analysis tools of TM parameters. Two Protein Kinase C (PKC) activators, TPPB and PMA, exhibited robust inhibition of TM formation in cell-based assays. Since unconnected glioblastoma cells exhibit increased sensitivity to cytotoxic therapy in vivo, brain tumor-bearing mice received TPPB, the most consistent TM-inhibiting compound, in combination with radiotherapy. Long-term intravital 2-photon microscopy confirmed anti-TM and anti-tumor effects of the co-treatment. Mechanistically, TPPB treatment inhibited several key molecular and functional components of TM-related glioblastoma cell network communication and decreased the expression of TTYH1, a key driver of invasive TMs. By establishing a novel screening pipeline for anti-TM drug development, our study identifies a druggable TM master regulator pathway and a small molecule with robust anti-TM effects. It provides a proof-of-principle that disrupting TMs and disconnecting tumor networks is a pharmacologically feasible strategy to make therapies against glioblastoma more effective.

  Study EGAS50000000477

• Genome_Diversity_in_Africa_Project__Benin

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene–disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region.The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group).Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformaticsThis data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001688

• Determination of cell specific regulatory enhancers in hematopoetic models

  The BLUEPRINT project is a large-scale project investigating epigenetic mechanisms involved in blood formation, in health and disease. The human variation workpackage (WP10, led by NS) of the project seeks to characterize the effect of common sequence variation on the epigenome status of a cell. To do this, the project will use highly purified blood cells to minimise "experimental noise" and therefore enhance the power to discover modest effects. Two peripheral blood cell types, the CD14+CD16- monocyte (an important central orchestrator of adaptive immunity and a bridge between innate and adaptive immunity) and the CD65+CD9- neutrophilic granulocyte (the frontline cell for innate immunity) have been selected for this purpose. The two types of cells will be obtained at high purity from adult blood (AB) of 200 healthy males and females, respectively. Cells will be purified by using already validated and fully operational protocols that are based on density gradient centrifugation of the buffy coat obtained from whole blood, followed by magnetic bead-based purification using monoclonal antibodies against Cluster of Differentiation (CD) lineage-specific cell surface markers. Units of 475 ml of AB will be obtained from consenting volunteers of the Cambridge BioResource (CBR), a panel of 10,000 healthy volunteers local to Cambridge who have already consented to participate in biomedical research and of whom biological samples (DNA, plasma, serum) and lifestyle data have been deposited in a repository and database, respectively. We are requesting funding from the Human Diversity project to sequence the genomes of the 200 CBR volunteers at low pass (6x coverage). Nuclei, DNA and RNA will be recovered from the purified cells and made available for RNA-seq, DNA-seq and ChIP-seq and genomic DNA for entire genome sequencing will be recovered from the DNA repository.

  Dataset EGAD00001002205

• Single nuclei sequencing of early, late-term, and early-onset pre-eclamptic decidua and villi.

  Hypertensive disorders in pregnancy, of which the multisystem syndrome pre-eclampsia is the most severe, leading to preterm delivery, maternal mortality, and life-long complications. To elucidate early disease dynamics, we present the first spatio-temporal study comparing single-nuclei transcriptomes of human preterm pre-eclamptic placentae and healthy controls, contextualizing this in a comprehensive study including early and late gestational placentae. This study includes early placentae samples from the fetal part (villi; n=10), maternal part (Decidua; n=3), late placentae samples from healthy pregnancies, villi (n=6), decidua (n=4), and late placentae samples from early-onset preeclamptic pregnancies, villi (n=5) and decidua (n=5).

  Dataset EGAD00001008273

• Bulk RNA-seq dataset of Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  In this study, we demonstrate that primary AML cells harboring the chromosomal translocation t(8;21) are critically dependent on the corresponding fusion gene, RUNX1::RUNX1T1, to suppress differentiation and maintain stemness. Silencing RUNX1::RUNX1T1 expression using siRNA-loaded lipid nanoparticles induces significant changes in chromatin accessibility, redirecting the leukemia-associated transcriptional network towards a myeloid differentiation program. Single-cell analyses reveal that this transcriptional reprogramming is associated with the depletion of immature stem and progenitor-like cell populations, accompanied by an expansion of granulocytic and eosinophilic/mast cell-like populations with impaired self-renewal capacity.

  Dataset EGAD00001015508

• ATAC-seq dataset of Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  In this study, we demonstrate that primary AML cells harboring the chromosomal translocation t(8;21) are critically dependent on the corresponding fusion gene, RUNX1::RUNX1T1, to suppress differentiation and maintain stemness. Silencing RUNX1::RUNX1T1 expression using siRNA-loaded lipid nanoparticles induces significant changes in chromatin accessibility, redirecting the leukemia-associated transcriptional network towards a myeloid differentiation program. Single-cell analyses reveal that this transcriptional reprogramming is associated with the depletion of immature stem and progenitor-like cell populations, accompanied by an expansion of granulocytic and eosinophilic/mast cell-like populations with impaired self-renewal capacity.

  Dataset EGAD00001015509

• scRNA-seq dataset of Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  In this study, we demonstrate that primary AML cells harboring the chromosomal translocation t(8;21) are critically dependent on the corresponding fusion gene, RUNX1::RUNX1T1, to suppress differentiation and maintain stemness. Silencing RUNX1::RUNX1T1 expression using siRNA-loaded lipid nanoparticles induces significant changes in chromatin accessibility, redirecting the leukemia-associated transcriptional network towards a myeloid differentiation program. Single-cell analyses reveal that this transcriptional reprogramming is associated with the depletion of immature stem and progenitor-like cell populations, accompanied by an expansion of granulocytic and eosinophilic/mast cell-like populations with impaired self-renewal capacity.

  Dataset EGAD00001015510

• Combining transcription factor binding affinities with open chromatin data for accurate gene expression prediction

  The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid cost and labour intensive TF ChIP-seq assays.It is important to develop reliable and fast computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices.TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq, using either peaks or footprints as input.In addition to open-chromatin data, also Histone-Marks (HMs) can be used in TEPIC to identify candidate TF binding sites.TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength.Using machine learning techniques, we show that incorporating low affinity binding sites improves our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites.Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance.In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq datasets.Finally, we show that these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

  Study EGAS00001002073

• A single-cell atlas of the early COPD lung

  Single cell atlas of the human airways from 10 patients suffering of early stage Chronic Obstructive Pulmonary Disease and 12 healthy age matched volunteers. This dataset was sequenced by 10X Genomics 3’ RNA-seq profiling. It is composed of more than 400 000 cells coming from 119 samples total. Sampling was performed by brushings and biopsies from the nose to the 6 th division of the airways.

  Dataset EGAD50000001001

• Adeno-associated virus in the liver: natural history and consequences in tumor development

  Adeno-associated virus (AAV) is a defective mono-stranded DNA virus, endemic in human population (35-80%). Recurrent clonal AAV2 insertions are associated with the pathogenesis of rare human hepatocellular carcinoma (HCC) developed on normal liver. This study aimed to characterize the natural history of AAV infection in the liver and its consequence in tumor development. In silico analyses using viral capture data explored viral variants and new clonal insertions. Clonal AAV insertions were positive selected during HCC development on non-cirrhotic liver challenging the notion of AAV as a non-pathogenic virus.

  Dataset EGAD00001004484

• Peruvian Genome Project

  Through the Peruvian Genome Project we generate and analyze the high coverage genomes of 150 individuals where the majority have >90% Native American ancestry and explore questions at the interface of evolutionary genetics, history, anthropology, and medicine. This is the most extensive sampling of high-coverage Native American and mestizo whole genomes to date. Reference: https://doi.org/10.1073/pnas.1720798115

  Dataset EGAD00001007082

• Biobank Japan genotype and phenotype data

  The Biobank Japan (BBJ) Project started at the Institute of Medical Science, the University of Tokyo in 2003. To date, the BBJ Project has collected around 200,000 individuals with disease cases consisting of 47 diseases. The purpose of the BBJ is to realize personalized medicine.

  Study JGAS000114

• A capture methyl-seq protocol with improved efficiency and cost-effectiveness using pre-pooling and enzymatic conversion

  The opportunities for sequencing-based methylome analysis of clinical samples are increasing. To reduce its cost and the amount of genomic DNA required for library preparation, we aimed to establish a capture methyl-seq protocol, which adopts pre-pooling of multiple libraries before hybridization capture and TET2/APOBEC-mediated conversion of unmethylated cytosine to thymine. We compared a publicly available dataset generated by the standard Agilent protocol of SureSelect XT Human Methyl-Seq Kit and our dataset obtained by our modified protocol, EMCap, that adopted sample pre-pooling and enzymatic conversion. We confirmed that the quality of DNA methylation data was comparable between the two datasets. As our protocol, EMCap, is more cost-effective and reduces the amount of input genomic DNA, it would serve as a better choice for clinical methylome sequencing.

  Study JGAS000605

• National Institute of General Medical Sciences (NIGMS) Human Genetic Cell Repository Human Variation Panels including 100 African-Americans (HD100AA), 100 Caucasians (HD100CAU), 100 Han People of Los Angeles (HD100CHI) and 100 Mexican American Community of Los Angeles (HD100MEX)

  The Human Genetic Cell Repository is sponsored by the National Institute of General Medical Sciences (NIGMS) with the mission of supplying scientists with the materials for accelerating disease gene discovery and functional studies. The resources available include highly-characterized, contaminant-free cell cultures and high quality, well-characterized DNA samples derived from these cultures, both subjected to rigorous quality control. The Repository was established in 1972 at Coriell and contains more than 9,500 cell lines, primarily fibroblasts and transformed lymphoblasts. The Repository has a major emphasis on inherited diseases and chromosomally aberrant cell lines. In addition, it contains a large collection dedicated to understanding human variation that includes samples from populations around the world, the CEPH collection, the Polymorphism Discovery Resource, Human Variation and many apparently healthy controls. The Human Variation collection provides cell lines and DNA samples from a variety of populations. The panels of African-Americans (HD100AA) and Caucasians (100CAU) used for this study are comprised of samples present in the Repository that were originally collected over the years from apparently healthy people to be used as "controls", for example, unaffected family members of persons with identified mono-genetic diseases. The samples for the Han people of Los Angeles (HD100CHI) and the Mexican American Community of Los Angeles (HD100MEX), however, were collected relatively recently from volunteers, identified as member of these communities, specifically for use in these panels. The Coriell Genotyping and Microarray Center in conjunction with the NIGMS repository used the Affymetrix Genome-Wide Human SNP 6.0 platform to genotype 400 samples from the NIGMS human variation panels. The populations genotyped included Americans of African, Caucasian, Mexican, and Han Chinese ancestry. The Affymetrix SNP 6.0 array detects approximately 940,000 SNPs and provides copy number information for more than 900,000 additional locations across the genome.

  Study phs000211

• Cancer Moonshot Biobank

  The National Cancer Institute initiated the Cancer Moonshot Biobank to accelerate research through the collection and distribution of biospecimens for key research efforts. The Biobank will engage with over one thousand cancer patients, being treated with standard-of-care therapies, for longitudinal biospecimen and data collection. Cancer patients will be enrolled into the study from a diverse participant population engaged at medical institutions throughout the U.S. The biospecimens will be distributed to qualified scientists to accelerate research progress. The Biobank program, working closely with Leidos Biomedical, Inc. (LBR), will partner with community hospitals and other medical institutions, designated as Biospecimen Source Sites (BSS), to engage and consent eligible participants and collect biospecimens and associated clinical data; work with a central Biospecimen Core Resource (BCR) to support biospecimen collection, processing and storage activities and perform pathology quality control; work with LBR's Molecular Characterization (MoCha) lab to perform clinical tumor molecular characterization assays and return results to patients and their physicians; and make the biospecimens and associated data available to researchers to accelerate cancer research progress. Return of clinical results, a dedicated Patient and Provider Engagement (PPE) website, electronic informed consent, local participant engagement projects, and an embedded ethical, legal and social issues sub-study will together support patient and provider engagement in the program. Cancer Moonshot Biobank imaging data is being made available in The Cancer Imaging Archive (TCIA) on a release schedule that is coordinated with the program releases of data to dbGaP. The imaging data can be found at the following link: Cancer Moonshot Biobank Imaging

  Study phs002192

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

  Metformin reduces the incidence of breast cancer in patients with obesity and type 2 diabetes. However, our knowledge of the effects of metformin on breast cancer recurrence is limited. Within the randomized double-blind placebo-controlled phase II trial MetBreCS, we examined changes in breast tissue from breast cancer survivors with BMI >25 kg/m2 after treatment with metformin. To identify metformin-regulated signaling pathways, we integrated the transcriptomic, metabolomic and steroid hormone profiles using bivariate and functional analyses. We identified MS4A1, HBA2, MT-RNR1 and MT-RNR2 expression to be differentially expressed in breast tissues from metformin-treated women. We also found metformin-associated down-regulation of EGFL6 and FDCSP in postmenopausal women. The integration of transcriptomic and metabolomic profiles revealed down-regulation of immune response genes associated with reduced levels of arginine and citrulline in the metformin-treated group. The integration of transcriptomic and steroid hormone profiles showed an enrichment of steroid hormone biosynthesis and metabolism pathways with highly negatively correlated CYP11A1 and CYP1B1 expression in breast tissue from postmenopausal metformin-treated women. Our results indicate that breast cancer survivors treated with metformin have specific changes in breast tissue gene expression that may prevent the development of new tumors. Within the randomized double-blind placebo-controlled phase II trial MetBreCS, we examined changes in breast tissue from breast cancer survivors with BMI >25 kg/m2 after treatment with metformin using bulk RNAseq (total mRNA sequencing), that is deposited in Federated EGA. The steroid hormones, and metabolomics and the insulin sensitivity serum biomarker data underlying this article may be shared upon reasonable request to the PI of the MetBreCS study (Dr. Bernardo Bonanni), following approval by the Data and Safety Monitoring Board at IEO, Milan.

  Study EGAS50000000874

• ChIP-seq for G3-MB

  ChIP-seq for H3K27ac and NeuroD1 in Group 3 Medulloblastoma cell models. Input DNA for each sample and target is also included.

  Dataset EGAD50000002303