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• A Multifactorial Tumor and Immune Cell Profile Determines Response to Immune Checkpoint blockade in Melanoma

  The complex crosstalk between tumor and immune cells during immune checkpoint blockade mandates the development of integrated models that interpret the anti-tumor immune response and predict clinical outcome. We have integrated genome-wide sequence and structural alterations with pre and on-therapy transcriptomic and T cell repertoire features for a cohort of 64 immunotherapy-naïve melanomas treated with anti-PD1 monotherapy or combined anti-PD1 and anti-CTLA4 therapy. While tumor mutation burden (TMB) was associated with improved response to therapy, expressed mutation burden was superior to TMB in predicting outcome. An increased pre-existing T cell density differentiated responding from non-responding tumors independent of therapy. Importantly, T cell repertoire reshaping determined by T cell receptor (TCR) clonotypic regressions and expansions reflected response to therapy such that a more dynamic repertoire predicted improved clinical outcome. Through whole-transcriptome analyses, we discovered differential abundance of B cell subsets in responding tumors, which highlights the importance of the interplay between pre-existing T and B cell immunity in shaping therapeutic response. Tumor temporal trajectories during therapy revealed distinct patterns of molecular response related to expressed mutation elimination or retention that accurately interpreted clinical response. High-dimensional genomic, transcriptomic and immune repertoire data were integrated by both a machine learning and a censored regression approach, resulting in a harmonized multi-modal predictor of response to immune checkpoint blockade. B cell abundance, expressed mutation load and tumor aneuploidy were combined to identify patients at high risk for recurrence, such that high risk patients had a significantly shorter progression-free survival (HR=9.18, 95% CI: 3.14-26.85, p=3.4e-06) especially in the anti-PD1/anti-CTLA4 group (HR=20.34, 95% CI: 4.08-101.32, p=1.68e-06).

  Study EGAS00001004548

• Development and validation of multivariate predictors of primary endocrine resistance to tamoxifen and aromatase inhibitors in luminal breast cancer reveal drug-specific differences

  Background: Endocrine therapy is highly effective in blocking the estrogen receptor pathway in HR+/HER2- early breast cancer (EBC). However, up to 40% of patients experience relapse during or after adjuvant endocrine therapy. Here, we investigate molecular mechanisms associated with primary resistance to endocrine therapy and develop predictive models. Results: TP53 mutations were prominently associated with primary resistance to both tamoxifen (TAM) and aromatase inhibitors (AI), with AI non-responders exhibiting resistance in up to 32% of cases. Additionally, we identified distinct DNA methylation patterns in TAM and AI non-responders, with TAM non-responders showing global DNA methylation loss, associated with KRAS signaling, apical junctions and epithelial-mesenchymal transition (EMT). Conversely, we observed methylation gain in AI non-responders affecting developmental transcription factors, hypoxia and estrogen signaling. TAM or AI resistance was associated with increased methylation-inferred proportions of immune cells and decreased proportions of endothelial cells. Based on these findings and patient age, we developed the Predictive Endocrine ResistanCe Index (PERCI). PERCI stratified NR and R cases in both treatment groups and cohorts with high accuracy (ROC AUC TAM discovery 93.9%, validation 83%; AI discovery 98.6%, validation 76.9%). A simplified PERCI efficiently predicted progression-free survival in the TCGA-BRCA sub-cohort (Kaplan-Meier log-rank p-value = 0.03 between low and high PERCI groups). Conclusions: We identified genomic and epigenomic features associated with primary resistance to TMA and AI. By combining information on genomic alterations, patient age, differential methylation and tumor microenvironment (TME) composition, we developed PERCI TAM and PERCI AI as novel predictors of primary resistance, with potential additional prognostic value. Applying PERCI in a clinical setting may allow patient-specific drug selection to overcome resistance.

  Study EGAS50000001102

• How to use the EGA search box

  Tips on how to search Tip 1: Use simple and clear keywords No matter what you are searching: a study, a dataset or a committee; the search will look recursively in all the fields of all the entities in the database. Thus, there is no need to specify which type of data you are looking for. Try to use single and specific words and avoid long and complex expressions. Try it out: cancer rna-seq instead of cancer studies using RNA-seq. Tip 2: Narrow your results using search operators Search operators give you more control over the results. They manage the way keywords are used to restrict the search. By default, the search engine applies an OR operator when a space is inserted between two words. Include AND (capitalised) between the keywords in your search in order to show only pages containing both terms. Try it out: Search all the studies based on transcriptomic data, including those ones that use RNA sequencing to obtain this data. Tip 3: Do not worry about details The search engine automatically checks for the most common spelling mistakes of given words and suggests the use of the correct version. It also ignores capital letters and most punctuation so none of these mistakes will hamper the accuracy of your search. Besides, when using a combination of words, the search engine will suggest similar combinations with a higher number of results. Tip 4: Use words that are likely to appear within the text Unfortunately, our search engine is not able to interpret words yet. Therefore, words which do not appear in the body text will not return any result despite them denoting a group of present terms. For instance, if we are looking for studies focused on neurological diseases, using neurological as a keyword would not be the best option. Instead, you should use the name of each neurological disease such as bipolar disorder, schizophrenia or depression. In the same fashion, incomplete words do not return any result. Please include an asterisk (*) before and/or after the incomplete word in order to allow for partial matching. Try it out: canc* instead of canc(without wildcard). Also you can try out *oma, or even *geneti* Tip 5: Narrow down your search by filtering the results You can filter the results by the following options: general, study, and dataset. Under these categories, you will find more sub-filters to refine your search. Make sure that you click on Apply in order to filter the results. You can clear the filtering anytime. Advanced Searches Additional example queries: Search for DUO:0000005 and word lung example query Or write: DUO:0000005 AND lung Search for an exome sequencing study in dbGaP example query Or write: study_type: "exome sequencing" AND repository:dbGaP Search for an exome sequencing study in EGA example query Or write: study_type: "exome sequencing" AND repository:ega Search for a dataset that is at the EGA beacon and with type "Whole genome sequencing" and with number of samples between 100 and 2000 and with technology "Illumina HiSeq 2000" example query Or write: is_in_beacon:true AND dataset_types:"Whole genome sequencing" AND samples:[100 TO 2000] AND dataset_technologies:"Illumina HiSeq 2000" Search for PMIDS example query Or write: pmids:32025007

  Documentation discovery/metadata/search-box

• New England-Based Case-Control Study of Ovarian Cancer

  The case-control data provided to dbGaP were collected under NCI grant number CA54419 which had 3 enrollment phases: I (1992-1997), II (1998-2002) and III (2003-2008). Altogether, CA54419 funded 15 years of data and specimen collection, resulting in one of the longest running population based case-control studies of ovarian cancer. The study goal was to examine reproductive factors, lifestyle exposures, and genetic background in relation to ovarian cancer risk. The project recruited cases from Eastern Massachusetts and New Hampshire, and became known as the New England-based Case-Control study (NECC) of ovarian cancer. 3957 ovarian cancer cases diagnosed at ages 18-80 and residing in Eastern Massachusetts and New Hampshire were identified through tumor boards and registries. Of these, 3083 (78%) were eligible and among those eligible, 2203 (71%) were enrolled. After excluding 127 non-epithelial and 35 mixed mesodermal tumors, 2041 cases with epithelial tumors of ovarian, primary peritoneal, and fallopian tube origin, including borderline malignancies were included. On average, cases were interviewed 10 months after their diagnosis. A pathologist reviewed pathology reports and recorded histologic subtype, grade, and stage. Mixed ovarian cancers described as predominantly one type were classified as that type. Undifferentiated, transitional cell tumors, or mixed serous/transitional cell tumors were counted as serous. Other mixed epithelial, malignant Brenner, and unspecified epithelial tumors were classified as other. 2100 controls were identified through random digit dialing (RDD), driver-license lists, and town-resident lists. During the first funding phase from 1992 to 1997, 420 (72%) controls identified through RDD and 102 (51%) through town-resident lists agreed to participate. From 1998 to 2008, only town-resident lists were used to identify potential controls. 4366 controls were identified, of whom 1426 (33%) were ineligible if they had died, moved, or were seriously ill or if they did not have a working telephone, speak English, or have at least one ovary. Of eligible controls, 1362 (46%) declined to participate by phone or via 'opt-out' postcard and 1578 (54%) were enrolled. Controls were frequency matched to cases by 5-year age groups and region of residence. In all phases, after written informed consent, demographic information, reproductive and medical history, and habits were assessed by in-person or telephone interview (in a few instances). All of the questions were framed with respect to a reference date defined as 1 year before the diagnosis date for women in the case group and the date of interview for those in the control group. This study was approved by institutional review boards at Dana Farber Harvard Cancer Center and Dartmouth Medical Center.

  Study phs001034

• Neoantigen-Targeted CD8+ T-Cell Responses 1 With PD-1 Blockade Therapy

  Background: The primary target of T-cell responses induced against cancer cells are peptides derived from non-synonymous mutations presented by HLA (neoantigens). However, the large diversity of HLA alleles and restricted availability of clinical samples have limited the study of the specificity and the evolution over time of the neoantigen-specific T cell responses induced after treatment with immune checkpoint blockade (ICB) immunotherapy. Methods: We applied a newly developed neoepitope-specific T cell isolation technology to perform a longitudinal landscape analysis of the neoepitope-specific T cells in peripheral blood and tumor from 11 patients with metastatic melanoma; 7 with response and 4 with no response to ICB. Briefly, first using computational prediction, the putative neoantigens in each patient were ranked based on affinity for the patient's HLA and expression levels. Then hundreds of barcoded capture reagents consisting of the patient HLA class I subtypes loaded with the corresponding predicted neoantigen were made and used to isolate neoepitope-specific T cells. Once isolated, the TCRs and the barcodes were sequenced. Finally, the tumor reactivity of the isolated neoepitope-specific TCRs (neoTCRs) was assessed upon co-culture of autologous melanoma cell lines from each patient with primary human T cells expressing the neoTCRs generated using a CRISPR-based non-viral gene editing to replace the endogenous TCRs. Results: The tumor mutation burden ranged between 3507 and 177 for patients with response to therapy and 977 to 31 for patients without response to therapy. We screened a median of 172 predicted neoantigen-HLA per patient across their 6 HLA molecules and isolated neoTCRs in all 11 patients. The number of mutations targeted ranged between 13 and 1. We assessed the neoTCR-tumor reactivity in samples from 3 patients with response and 3 patients without response. 39 of the 62 neoTCRs demonstrated specific recognition and cytotoxicity to patient-matched melanoma cell lines. Multiple T cell clonotypes recognized a limited number of mutations in 7 patients with response (median of 41 different neoTCR clonotypes per patient), and the T cell specificities were recurrently detected in the blood and the tumor over time. Samples from 4 patients without response to therapy also demonstrated neoepitope-specific T cell responses in blood and tumor to a similarly restricted number of mutations, but lacked TCR polyclonality (median 6.5 neoTCR clonotypes per patient) and were not recurrently detected in sequential samples. Conclusion: Effective ICB therapy is associated with polyclonal neoepitope-specific T-cell responses in the tumor and blood that recognize a limited number of immunodominant mutations and are recurrently detected over time.

  Study phs003153

• Heart Failure Network Aldosterone Targeted Neurohormonal Combined with Natriuresis Therapy - (HFN ATHENA-BioLINCC)

  ObjectiveTo assess whether high-dose spironolactone treatment for patients with acute heart failure lowers natriuretic peptide levels and improves outcomes better than usual care.BackgroundAcute heart failure (AHF) accounts for more than a million hospitalizations in the United States annually. The role of low-dose mineralocorticoid receptors antagonists (MRAs) therapy as a neurohormonal antagonist is well established for the treatment of chronic heart failure and reduced ejection fraction. However, the role of high-dose MRA therapy in AHF remained uncertain. A previous clinical trial suggested that the benefits of high-dose MRA therapy in AHF included lower natriuretic peptide levels, less congestion, better renal function, and less need for an intravenous diuretic. The use of intravenous loop diuretics can intensify secondary hyperaldosteronism among AHF patients, and hyperaldosteronism directly contributes to diuretic resistance in AHF. Elevated aldosterone levels in AHF are associated with an increased risk of cardiovascular mortality and HF readmission. Hospitalizations for heart failure are associated with increased risk of mortality and/or readmission.The HFN-ATHENA trial was conducted to determine if mineralocorticoid receptor antagonists administered at high doses relieved congestion, decreased diuretic resistance, and mitigated the effects of adverse neurohormonal activation in AHF.SubjectsThe ATHENA trial enrolled 360 participants. Of these, 178 participants were randomized to usual care treatment (placebo or low-dose spironolactone) and 182 participants were randomized to high-dose spironolactone.DesignThe study intervention was initiated within 24 hours of patients receiving the first dose of intravenous diuretics. Participants not taking spironolactone at enrollment were randomized to 100 mg spironolactone or a placebo. Participants taking low-dose spironolactone before their hospital admission were randomized to 100 mg or 25 mg per day in the usual care treatment arm. Prescription of all other medications, including diuretics, was left at the discretion of the treating physician. The study drug was discontinued after 96 hours and further MRA use was left to the treating physician's discretion. The primary end point was the proportional change in the log NT-proBNP levels from randomization to 96 hours (or at the hospital discharge if the discharge occurred earlier than 96 hours). Secondary endpoints included: (1) a clinical congestion score; (2) dyspnea relief; (3) daily cumulative net urine output for up to 96 hours; (4) net weight change from baseline to 96 hours or discharge (whichever came first); (5) furosemide equivalents of the loop diuretic dosage at discharge; and (6) the development of in-hospital worsening HF, with signs and symptoms requiring additional therapy.ConclusionsThere was no significant difference in the primary or secondary endpoints between the high-dose treatment arm and the usual care treatment arm.

  Study phs003506

• Patient Registry for Primary Pulmonary Hypertension (PPH Registry-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 Establish a patient registry to evaluate the natural history, etiology, pathogenesis and treatment of primary pulmonary hypertension. Specific aims included the characterization of the demographic, medical history, family history, physical and laboratory findings of patients at time of diagnosis, and to characterize the survival duration of patients by traits evaluated at diagnosis and by medical interventions. Background There are several known causes of pulmonary hypertension: chronic obstructive pulmonary disease, congenital heart disease, mitral stenosis, left ventricular dysfunction and recurrent pulmonary emboli. Primary Pulmonary Hypertension is a disorder of unknown etiology which is diagnosed only after the known causes of pulmonary hypertension have been eliminated. Prior to the PPH registry, little was known regarding the epidemiology, etiology, natural history or ultimate survival among patients with PPH. In 1973, the WHO met to review the current state of knowledge on PPH and proposed the establishment of a multicenter collaborative study. The NHLBI PPH registry enrolled patients in the registry from 1981 to 1985. Participants Participants were enrolled into the registry from 32 medical centers throughout the US. Pulmonary hypertension was defined as a mean pulmonary arterial pressure of >25 mmHg at rest or 30 mmHg with exercise at catheterization. The diagnosis of primary pulmonary hypertension was only accepted after the following secondary causes of pulmonary hypertension had been excluded: pulmonary hypertension within the first year of life, congenital abnormalities of the heart, lungs, or diaphragm, pulmonary thromboembolic disease, diagnosis of sickle cell anemia, history of intravenous drug abuse, obstructive lung disease, interstitial lung disease, arterial hypoxemia, collagen vascular disease, parasitic disease affecting the lungs, pulmonary artery or valve stenosis, or pulmonary venous hypertension. Baseline and follow-up data collected on participants include demographic characteristics, chest radiograph, pulmonary function tests, lung perfusion scan or pulmonary angiogram, intracardiac left-to-right shunt, pulmonary hemodynamics, as well as a history, physical findings and other laboratory measurements. Participants were followed for approximately 5 years. Conclusions There were 1.7 females for each male in the registry, and females tended to present with more severe symptoms. The mean time from onset of symptoms to diagnosis was 2 years. Right ventricular hypertrophy was found in 87% of participants and right atrial pressure was elevated in 72% of participants. The estimated median survival was 2.8 years with single year survival rates of: 1 year, 68%; 3 years, 48%; and 5 years, 34%. (Ann Intern Med, 1987; 107:216-23, Ann Intern Med, 1991; 115:343-49).

  Study phs004275

• Therapy-Induced APOBEC3A Drives Evolution of Resistance to Targeted Therapies in Non-Small Cell Lung Cancer

  The purpose of this study was to identify mechanisms of resistance and associated mutational signatures in non-small cell lung cancers (NSCLCs) treated with targeted therapies. Whole genome sequencing (WGS) and whole exome sequencing (WES) were performed on tumor tissue or cell lines derived from oncogene-driven NSCLCs before and after treatments with tyrosine kinase inhibitors. Somatic mutations were called and mutational signature analysis was performed, revealing enrichment of APOBEC mutational signatures mutational signatures in post-treatment tumors after the development to resistance to targeted therapies. The cohort includes WGS and WES data of tumor and normal tissues from patients with oncogene-driven NSCLCs harboring EGFR mutations, ALK fusions or NTRK1 fusions, who were treated with molecularly targeted therapies that target these oncogenes.

  Study phs003256

• Targeted Genomic Sequencing in Large Human Genes to Detect Induced Structural Variants

  Partial inhibition of DNA replication leads to de novo copy number variant (CNV) formation throughout the genome, especially at common fragile sites (CFSs). We previously showed that these hotspots for genome instability reside in late-replicating domains associated with large, transcribed genes. In this study, we performed targeted, error-corrected genomic sequencing of multiple large genes in several human cell lines. The svCapture pipeline was used to call novel structural variant junctions in co-analyzed samples. Multiple samples were analyzed from cell populations under different replication stresses, with suppression of DNA repair pathways, and in different cell cycle stages, to determine the mechanisms underlying CNV formation at these loci. Data are provided as raw genome sequencing reads and processed multi-sample VCF files with sequenced junctions encoded as breakends.

  Study phs003121

• Hereditary Gastric Cancer Syndromes: An Integrated Genomic and Clinicopathologic Study of the Predisposition to Gastric Cancer

  Gastric cancers are cancers of the stomach. Hereditary cancers are passed from parent to child. Researchers want to gather data about hereditary gastric cancers. Bulk RNA sequencing (RNA-seq) of signet ring cells (SRCs) and adjacent non-SRC epithelium (NEP) was performed on laser-capture microdissected (LCM) regions of interest found in risk-reducing total gastrectomy specimens from hereditary diffuse gastric cancer (HDGC) patients (Clinicaltrials.gov ID: NCT03030404). Twenty patients (6 male, 14 female) with confirmed HDGC were identified. Analysis of differentially expressed genes (DEGs) demonstrated upregulation of certain individual epithelial–mesenchymal transition (EMT) and proliferation genes. SRC regions had significant enrichment in pathways involved in T cell signaling. CIBERSORTx predicted significant increases in the presence of regulatory T cells (Tregs) specific to SRC regions.

  Study phs003422