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• GATA2 Deficiency

  The aim of this study is to identify somatic mutations that contribute to the progression of GATA2 Deficiency patients from bone marrow failure to myelodysplastic syndrome (MDS) to acute myeloid leukemia (AML) or chronic myelomonocytic leukemia (CMML). We investigated somatic mutations in >100 patients by whole exome and myeloid malignancy targeted array sequencing to identify acquired mutations associated with myeloid malignancies. MDS was the most common diagnosis (~45%), followed by GATA2 Bone Marrow Immunodeficiency Disorder (G2BMID) (~35%). Approximately ten percent of our cohort were unaffected "carrier" family members with no disease manifestations. In contrast, about ten percent had progressed to a proliferative leukemia. There were no correlations with GATA2 mutation, patient age or gender and disease progression or survival. Somatic Recurrent somatic mutations were uncommon in cancer associated genes, and virtually absent in asymptomatic patients. However, mutations in the cohesin gene STAG2 and chromatin remodeling gene ASXL1 were detected in ~20% of patients. Patients with ASXL1 mutations had a lower survival. ASXL1 mutations were ~10-times more prevalent in female patients than males. Other recurrent mutations were in the DNMT3A, BCOR, and SETBP1 genes. There was a conspicuous absence of the most commonly mutated genes associated with myeloid malignancies, including TET2, RUNX, IDH1/2 and splicing factor genes. 

  Study phs002311

• GoNL release 5 haplotype panel

  The samples in this panel come from 250 families: 248 parents-child trios and 2 parent-child duos. As the children do not provide additional haplotypes or population information, they were excluded from the panel. The samples present in the release are composed of 248 couples, 2 single individuals and 1 sample composed from the 2 haplotypes from the duo's children transmitted by their missing parent. The composed sample is named gonl-220c_223c.The files contain a total of 18.9M SNVs and 1.1M INDELs in autosomal chromosomes. They were generated by phasing/imputing the SNVs (a) and INDELs (b) using MVNCall. Only sites passing filters are reported. Sites filtered as part of the GoNL inaccessible genome were kept (but flagged as filtered) and still may contain true positive calls but should be used with care as they are located in parts of the genome that are less well captured (systematic under or over-covered or low-mapping quality)

  Dataset EGAD00001000744

• Single-cell RNA sequencing of T-LGLL patients

  Single-cell RNA sequencing was performed on viably frozen cells from 11 T-LGLL samples from 9 T-LGLL patients and 6 age-matched healthy samples. The raw data is available as fastq files.

  Dataset EGAD00001008409

• Ither2 WXS dataset - Implementation of pediatric precision oncology into clinical practice: The individualized Therapies for Children with cancer program “iTHER”

  iTHER is a prospective national precision oncology program aiming to define tumor molecular profiles in children and adolescents with primary very high-risk, relapsed, or refractory pediatric tumors in order to identify relevant aberrations to inform treatment.

  Dataset EGAD00001010178

• Ither2 RNA-Seq dataset - Implementation of pediatric precision oncology into clinical practice: The individualized Therapies for Children with cancer program “iTHER”

  iTHER is a prospective national precision oncology program aiming to define tumor molecular profiles in children and adolescents with primary very high-risk, relapsed, or refractory pediatric tumors in order to identify relevant aberrations to inform treatment.

  Dataset EGAD00001010179

• Neutrophils and emergency granulopoiesis drive immune suppression and an extreme response endotype during sepsis

  This dataset contains raw sequencing files associated with the paper "Neutrophils and emergency granulopoiesis drive immune suppression and an extreme response endotype during sepsis" (https://doi.org/10.1038/s41590-023-01490-5). It is composed of two experiments, which are as follows: 1. Single-cell profiling of whole blood leukocytes: This experiment comprises sequencing files generated using the BD Rhapsody single-cell multi-omics profiling (RNA + protein) platform. This platform was used to profile the whole blood leukocyte population in a cohort of sepsis patients, cardiac surgery controls and healthy controls. There are 48 samples and four files per sample: two paired-end FASTQ files (R1 and R2) corresponding to the RNA-seq library, and two paired-end FASTQ files (R1 and R2) corresponding to the protein profiling (ADT-based AbSeq) library. 2. Single-cell profiling of circulating HSPCs: This experiment comprises sequencing files generated using the 10X single-cell multi-omics (RNA-seq + ATAC-seq) profiling platform. This platform was used to profile circulating HSPCs in a cohort of sepsis patients and healthy controls. There are 5 samples (or plexes), each of which consists of a pool of individuals for whom cells were multiplexed and sequenced as a single sample. There are four files per sample: two paired-end FASTQ files (R1 and R2) corresponding to the RNA-seq library, and two paired-end FASTQ files (R1 and R2) corresponding to the ATAC-seq library. Because these samples consists of multiplexed pools, index files are also provided. These can be used for sample deconvolution using the Cell Ranger pipeline. NOTE: Due to EGA's constrains in the number of files permitted per sample, index files (I1 and I2) for the HSPC data set are provided as a separate experiment named "FASTQ index files (I1 and I2) for deconvolution of 10X single-cell multiomics libraries".

  Dataset EGAD00001010927

• Human placenta microRNA sequencing dataset

  Human placenta samples from 52: 5 first trimester , 7 second trimester, and 40 term placenta. Data is uploaded as BAM files.

  Dataset EGAD00001007766

• 54 metastatic colorectal cancer patients from Schleswig-Holstein in North Germany

  Personalized treatment vs standard of care is much debated, especially in clinical practice. Here we investigated whether overall survival differences in metastatic colorectal cancer patients are explained by their tumor mutation profiles or by their treatment differences in real clinical practice.

  Study EGAS00001004108

• Increased trunk fat is associated with altered gene expression in breast tissue of normal weight women

  Dac EGAC00001002031

• Oxidative phosphorylation is a key ontogenetic feature of monocyte immunometabolism promoting myeloid differentiation after birth

  Dac EGAC00001003420

• Single Cell and Tissue Level Functional Genomics Analysis of Astrocyte-Related Mechanisms in Taupathy

  This data is the first part of a larger single cell and tissue level functional genomics analysis of dementias with tau pathology.  Cellular resolution will clarify the role of glial genes and pathways in neurodegenerative disease. This includes understanding the role of microglia and astrocytes in neurodegenerative disorders characterized by Tau protein pathology. To achieve a refined view of microglial neuroinflammatory signaling in tau-associated neurodegeneration, we performed a functional genomic analysis that integrated time-course gene expression data from mouse models expressing human mutant MAPT (the tau gene) with single nuclear sequencing data obtained from patients with frontotemporal dementia with Tau protein pathology (Pick’s disease). This included microglia-specific gene expression data obtained from single nuclear sequencing of postmortem frozen precentral gyrus samples collected from 16 total individuals, including 8 subjects with clinical diagnosis of behavior variant frontotemporal dementia and neuropathological diagnosis of Pick’s disease (Tau protein pathology) and controls (n=8). Our findings present detailed molecular profiles of disease-associated microglial transitions over the course of tau-associated neurodegeneration. Furthermore, we demonstrate overlap between microglia profiles obtained from precentral gyrus of patients with Pick’s disease with those up-regulated during the neurodegenerative stage in mice expressing human MAPT mutations.

  Study phs002197

• Poikiloderma syndrome RNAseq

  We will sequence the RNA of lymphoblast samples, transformed with EBV, which have poikiloderma syndrome with mutations in c16orf57. The aim of the experiment is to characterise RNA structural effects in this disease.

  Dataset EGAD00001000324

• NHLBI GO-ESP: Early-Onset Myocardial Infarction (Broad EOMI)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. In the Grand Opportunities Exome Sequencing Program Early MI Project (GO ESP - EOMI), we are sequencing cases with extremely early-onset MI drawn from 8 cohorts. These cohorts include five hospital or community-based studies that ascertained individuals based on MI status. These include PennCATH, Cleveland Clinic Genebank, Massachusetts General Hospital Premature Coronary Artery Disease Study (MGH-PCAD), Heart Attack Risk in Puget Sound (HARPS), and Translational Research Investigating Underlying Disparities in Myocardial Infarction Patients' Health Status (TRIUMPH). Cases were selected based on MI occurring in men aged ≤50 years and women aged ≤60 years. In addition, early-MI cases are being drawn from three population-cohort studies including the Framingham Heart Study, the Women's Health Initiative, and the Atherosclerosis Risk in Communities Study. MI-free controls are being drawn from five population-based cohort studies including the Framingham Heart Study, the Women's Health Initiative, Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, and the Jackson Heart Study. Controls were selected based on two factors: (1) highest predicted risk for MI based on Framingham risk score; and (2) absence of prevalent or incident MI despite a high predicted risk.

  Study phs000279

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities WGS

  Atypical teratoid/rhabdoid tumors (ATRTs) represent a rare, but aggressive pediatric brain tumor entity. They are genetically uniquely defined by alterations in the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. ATRTs can be further classified in different molecular subgroups based on their epigenetic profiles. Although recent studies suggest that the different subgroups have distinct clinical features, subgroup-specific treatment regimens have not been developed thus far. This is hampered by the lack of pre-clinical in vitro models representative of the different molecular subgroups. Here, we describe the establishment of ATRT tumoroid models from the ATRT-MYC and ATRT-SHH subgroups. We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles. High throughput drug screens on our ATRT tumoroids revealed distinct drug sensitivities between and within ATRT-MYC and ATRT-SHH subgroups. Whereas ATRT-MYC universally displayed high sensitivity to multi-targeted tyrosine kinase inhibitors, ATRT-SHH showed a more heterogeneous response with a subset showing high sensitivity to Notch inhibitors, which corresponded to high expression of Notch receptors. Our ATRT tumoroids represent the first pediatric brain tumor organoid model, providing a representative pre-clinical model which enables the development of subgroup-specific therapies.

  Study EGAS00001006865

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities RNA-Seq

  Atypical teratoid/rhabdoid tumors (ATRTs) represent a rare, but aggressive pediatric brain tumor entity. They are genetically uniquely defined by alterations in the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. ATRTs can be further classified in different molecular subgroups based on their epigenetic profiles. Although recent studies suggest that the different subgroups have distinct clinical features, subgroup-specific treatment regimens have not been developed thus far. This is hampered by the lack of pre-clinical in vitro models representative of the different molecular subgroups. Here, we describe the establishment of ATRT tumoroid models from the ATRT-MYC and ATRT-SHH subgroups. We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles. High throughput drug screens on our ATRT tumoroids revealed distinct drug sensitivities between and within ATRT-MYC and ATRT-SHH subgroups. Whereas ATRT-MYC universally displayed high sensitivity to multi-targeted tyrosine kinase inhibitors, ATRT-SHH showed a more heterogeneous response with a subset showing high sensitivity to Notch inhibitors, which corresponded to high expression of Notch receptors. Our ATRT tumoroids represent the first pediatric brain tumor organoid model, providing a representative pre-clinical model which enables the development of subgroup-specific therapies.

  Study EGAS00001006866

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities DNA-Methylation

  Atypical teratoid/rhabdoid tumors (ATRTs) represent a rare, but aggressive pediatric brain tumor entity. They are genetically uniquely defined by alterations in the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. ATRTs can be further classified in different molecular subgroups based on their epigenetic profiles. Although recent studies suggest that the different subgroups have distinct clinical features, subgroup-specific treatment regimens have not been developed thus far. This is hampered by the lack of pre-clinical in vitro models representative of the different molecular subgroups. Here, we describe the establishment of ATRT tumoroid models from the ATRT-MYC and ATRT-SHH subgroups. We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles. High throughput drug screens on our ATRT tumoroids revealed distinct drug sensitivities between and within ATRT-MYC and ATRT-SHH subgroups. Whereas ATRT-MYC universally displayed high sensitivity to multi-targeted tyrosine kinase inhibitors, ATRT-SHH showed a more heterogeneous response with a subset showing high sensitivity to Notch inhibitors, which corresponded to high expression of Notch receptors. Our ATRT tumoroids represent the first pediatric brain tumor organoid model, providing a representative pre-clinical model which enables the development of subgroup-specific therapies.

  Study EGAS00001006881

• RNAseq of 76 samples from Uveal Melanoma tumors

  Hotspot mutations in the spliceosome gene SF3B1 are reported in 20% of uveal melanomas. SF3B1 is involved in 3'-splice site (3'ss) recognition during RNA splicing; however, the molecular mechanisms of its mutation have remained unclear. Here we show, using RNA-Seq analyses of uveal melanoma, that the SF3B1 R625/K666 mutation results in deregulated splicing at a subset of junctions, mostly by the use of alternative 3'ss.

  Dataset EGAD00001004398

• The Cardiogenics study

  Cardiogenics is an European collaborative project, it started in January 2007 and was funded by the European Commission through its Sixth Framework Program (reference LSHM -CT-2006-037593) until 2011. It involved several laboratories from France (INSERM UMRS937), Germany (Lübeck University; Regensburg University), United Kingdom (the Welcome Trust Sanger Institute; University of Leicester) and Sweden (Uppsala University Hospital) and was coordinated by a management group composed of scientists from these different institutions. Under the coordination of the management group the laboratories are still developing projects using Cardiogenics data sets. As part of the Cardiogenics project, RNA from monocytes and macrophages of 363 patients with coronary artery disease and 395 healthy individuals was prepared and genome-wide expression was assessed in both cell types using the Illumina HumanRef 8 v3 Beadchip . The DNA of all these individuals was genotyped using the Human 610 Quad custom arrays. Both data sets were used to conduct eQTL analyses. A subsample of subjects included in an allelic-imbalance substudy were also genotyped using the Illumina Human Custom 1.2M array. Detailed description of these datasets can be found in Shah S et al. Circ Cardiovs Genet 2011; Rotival M et al. Plos Genet 2011, Almlöf et al. Plos One 2012 and Garnier S et al. Plos Genet 2013

  Study EGAS00001000411

• ProstOmics - Bulk Transcriptomics

  Bulk transcriptomics data from 176 prostate tissue samples (37 patients, 27 with post-surgery relapse) that were acquired using the SENSE mRNA-Seq Library Prep Kit V2 and Illumina NextSeq 500 instrument. The raw transcriptomics data is single-read RNA-seq. The individual samples have information on patient origin and sample type (cancer, cancer-adjacent field-effect normal or normal sample far from cancer). Patient metadata include information of age at surgery, time (months) until reported relapse, pre-surgery PSA and post-surgery T-stage.

  Dataset EGAD50000000604

• Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) - OncoArray Genotypes

  Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) was one of five projects funded in 2010 as part of the NCI's Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (http://epi.grants.cancer.gov/gameon/). GAME-ON's overall goal was to foster an intra-disciplinary and collaborative approach to the translation of promising research leads deriving from the initial wave of cancer GWAS. Specific goals included replication of previous GWAS findings and identification of new susceptibility loci through meta analyses of existing GWAS data and fine mapping of identified loci to better pinpoint causal variants; and identify germline variants that are associated with risk of multiple cancers. The other four funded GAME-ON projects were: the ColoRectal TransdisciplinaryStudy (CORECT), Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE), Follow-up of Ovarian Cancer Genetic Association and Interaction Study (FOCI), and Transdisciplinary Research in Cancer of the Lung (TRICL). To identify additional cancer risk loci, improve the precision of fine-mapping, and facilitate cross-cancer analyses, the GAME-ON projects and other consortia formed the OncoArray network (http://epi.grants.cancer.gov/oncoarray/), which developed and genotyped a new custom genotyping array (the "OncoArray") in large numbers of cancer cases and controls (over 400,000 samples). The OncoArray is a custom array manufactured by Illumina. The array includes a backbone of approximately 260,000 SNPs that provide genome-wide coverage of most common variants, together with markers of interest for each of the five GAME-ON cancers identified through genome-wide association studies (GWAS), fine-mapping of known susceptibility regions, sequencing studies, and other approaches. The array also includes loci of interest identified through studies of other cancer types, and other loci of interest to multiple cancer types (including loci associated with cancer related phenotypes, drug metabolism and radiation response). Additionally, SNPs relating to quantitative phenotypes such as body mass index (BMI), height, and breast density that correlate with common cancer risks are also included. The DRIVE data included under this dbGAP submission include OncoArray data from 60,015 breast cancer cases and controls genotyped at the Center for Inherited Disease Research (CIDR), University of Cambridge, National Cancer Institute, University of Copenhagen, University of Southern California and Mayo Clinic. Details on an additional approx. 80,000 breast cancer cases and controls genotyped at other centers can be found at http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/.

  Study phs001265

• The Finland-United States Investigation of NIDDM Genetics (FUSION) Study - Islet Expression and Regulation by RNAseq and ATACseq

  This study evaluates gene expression and its regulation in human pancreatic islets, a tissue relevant in the study of genetic risk factors contributing to diabetes. We obtained pancreatic tissue sections and purified pancreatic islets from deceased donors and processed these biological samples to generate various data types. We generated spatial transcriptomic data from pancreatic tissue samples using the 10X Genomics VISIUM technology with sequencing on the Illumina NovaSeq platform. We also generated multiple data types from the purified pancreatic islets using genome-wide SNP chips, bulk RNA-Seq, microRNA (miRNA)-Seq, whole genome sequence, DNA methylation (methyl)-Seq, cap analysis of gene expression (CAGE)-Seq, single cell RNA-seq, and single nuclei ATAC-seq approaches. These data include ATAC-seq of two islet subjects, RNA-seq of 31 additional subjects, genome-wide chip genotypes, and imputed genotypes of the 33 subjects released with phs001188.v1. For genotyping, 500-1000 islet equivalents (IEQ) were cultured as in Gershengorn (Science, 2004, PMID: 15564314); genomic DNA isolated from islet cultures. For RNA analyses, 2500-5000 IEQ from each islet source were used for bulk or single-cell RNA isolation. Messenger RNA was isolated with trizol extraction and 12-plex libraries were generated using the Illumina TruSeq directional mRNA-seq library protocol. Bulk RNA sequencing was performed on HiSeq2000/HiSeq2500/Hiseq4000/NovaSeq6000 sequencers using paired-end reads at the NIH Intramural Sequencing Center (NISC). miRNA libraries were prepared from total RNA from 68 samples, pooled and sequenced 50bp single-end reads on Illumina HiSeq2500. CAGE libraries were prepared from total RNA samples using the nAnT-iCAGE protocol at DNAFORM, Japan. CAGE libraries were sequenced at the NIH Intramural Sequencing Center (NISC) on the HiSeq2000 sequencer. Genotyping on the Illumina Omni2.5M array was performed at the NHGRI Genomics Core facility. Genotypes were imputed using the HRC.r1.1.2016 reference panel. To assess regions of open chromatin in islets, we performed bulk ATAC-seq on HiSeq2000 sequencers using paired-end reads at NISC. Single-nuclei ATAC-seq libraries were prepared using single-cell-combinatorial-indexing (sci-) ATAC-seq protocol and sequenced on Illumina NextSeq using paired-end reads. scRNA-seq libraries were generated using the 10X Genomics platform and sequenced on Illumina HiSeq3000 at the Genomics Technology Core of the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS). Greater than 90% of the loci associated with T2D through genome-wide association studies occur in non-coding regions, suggesting a strong regulatory component to disease susceptibility. Therefore, there is a critical need to understand the full spectrum of genetic variation and regulatory element usage in T2D-relevant tissues. To that end, this study contains multiple genomic and transcriptomic data sets from pancreas tissue sections and pancreatic islets, a resource that will contribute to our efforts to investigate the genetic risk factors for type 2 diabetes.

  Study phs001188

• Proteomic Biomarkers of Progressive Fibrosing Interstitial Lung Disease: a Multicentre Cohort Analysis (PF-ILD Proteomics-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To identify novel plasma biomarkers of progressive fibrosing interstitial lung disease and develop a proteomic signature to predict this phenotype. Background: Progressive fibrosing interstitial lung disease (ILD) is a devastating condition characterized by parenchymal scar formation, leading to deteriorating lung function and early death. Whereas almost all patients with idiopathic pulmonary fibrosis (IPF) progress, a variable proportion of patients with other common ILDs, including connective tissue disease associated ILD, chronic hypersensitivity pneumonitis, and unclassifiable ILD, develop progressive fibrosing ILD. There are criteria that effectively identify those experiencing ILD progression. However, the criteria do not allow patients who are at risk to be identified before progression occurs. Several blood-based biomarkers have been linked to differential progression in patients with IPF and other fibrosing ILDs. Inflammatory signaling also appears to have a prominent role in fibrotic-predominant ILDs. As such, cytokines, interleukins, and other immune mediators might serve as useful biomarkers of progressive fibrosing ILD. The PF-ILD Proteomics study was a targeted investigation of inflammation-related proteins to identify and validate novel biomarkers of progressive fibrosing ILD in patients with fibrotic connective tissue disease-associated ILD, chronic hypersensitivity pneumonitis, and unclassifiable ILD. Participants: There were 589 participants. The discovery cohort comprised 385 participants and the validation cohort comprised 204 participants. Design: PF-ILD Proteomics was a multicenter cohort analysis study. Peripheral blood was collected from consenting patients and plasma was isolated according to center-specific protocols. Relative plasma concentrations for 368 biomarkers were determined with use of a semi-quantitative, targeted proteomic platform. Patients from UC Davis and UCSF comprised the discovery cohort and those from UTSW comprised the validation cohort. Participants who were alive with less than 10% relative decline in forced vital capacity (FVC) at 12 months-after blood draw were considered to have non-progressive ILD. Participants who died of any cause, underwent lung transplant, or experienced 10% or greater relative FVC decline within 12 months of blood draw were deemed to have progressive fibrosing ILD. Conclusions: 17 plasma biomarkers of progressive fibrosing interstitial lung disease were identified and showed consistent associations across ILD subtypes.

  Study phs003954

• WGBS Discovery Samples

  The dataset contains valuable genomic data from a discovery cohort consisting of 29 individuals. This cohort is comprised of 8 healthy individuals (control), 8 patients with ST-segment elevation myocardial infarction (STEMI), 7 patients with non-ST-segment elevation myocardial infarction (NSTEMI), and 6 patients with unstable angina (UA). The genomic data was obtained by isolating cell-free circulating DNA (ccfDNA) and subjecting it to bisulfite conversion using a low-input BS-seq (PBAT) protocol. Sequencing was done on the Novaseq 6000 platform.

  Dataset EGAD00001010935

• Pre-neoadjuvant treatment biopsy RNAseq breast cancer dataset

  This dataset contains RNAseq data of n=87 pre-treatment biopsies of triple negative and luminal- type breast cancer patients, all scheduled to receive neoadjuvant chemotherapy. Gene expression data is linked with treatment response and survival.

  Dataset EGAD00001008433

• Evolution of Core Archetypal Phenotypes in High-Grade Serous Ovarian Cancer (HGSOC)

  The evolution of resistance in high-grade serous ovarian cancer (HGSOC) cells in response to chemotherapy is only partially understood. To uncover phenotypic changes associated with chemotherapy resistance, we performed single-cell RNA-sequencing (scRNA-seq) or whole-genome sequencing of 23 total patients, with longitudinal samples collected from 9, treatment-naïve samples from 8 patients, and post-treatment samples from 6 patients. Our study revealed that the HGSOC transcriptome could be described using three core archetypal phenotypes, defined as oncogenic tasks that describe majority of the transcriptional data. We implemented a multi-task learning approach to identify the biological tasks of each archetype and identified metabolism and proliferation, cellular defense response, and DNA repair signaling. The “metabolism and proliferation” archetype evolved during treatment and was enriched in cancer cells from patients that received multiple-lines of treatment and had elevated tumor burden indicated by CA-125 levels. The emergence of archetypes was not consistently linked to specific whole-genome driver mutations. However, archetypes were closely associated with sub-clonal clusters at the single-cell level, indicating that cancer cell sub-populations specialize in particular biological tasks. Our study reveals a defining principle of ovarian tumor evolution using temporal scRNA-seq profiles, identifies the key phenotypic features across patients and links metabolic shifts with a response to chemotherapy.

  Study phs002294