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• Exome sequencing of osteosarcoma, blood and saliva

  We profiled 31 osteosarcoma tumor patient samples, 18 blood and 1 saliva control samples by exome sequencing, for a total of 50 samples. The raw fastqs are provided.

  Dataset EGAD00001011370

• 10x Single Cell Gene Expression Library TENX068

  10x Single Cell Gene Expression library TENX068 for Triple negative breast cancer patient-derived xenograft SA609X4XB03080

  Dataset EGAD00001011210

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0146_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0146_002 for Triple negative breast cancer patient-derived xenograft SA609X5XB03223

  Dataset EGAD00001011214

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0182_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0182_001 for Triple negative breast cancer patient-derived xenograft SA535X7XB03304

  Dataset EGAD00001011225

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0189_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0189_002 for Triple negative breast cancer patient-derived xenograft SA535X8XB03663

  Dataset EGAD00001011229

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0145_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0145_001 for Triple negative breast cancer patient-derived xenograft SA1035X7XB03338

  Dataset EGAD00001011244

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0175_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0175_002 for Triple negative breast cancer patient-derived xenograft SA1035X8XB03631

  Dataset EGAD00001011249

• Genome and transcriptome sequence data from a plexiform neurofibroma tumor patient

  Genome and transcriptome sequence data from a plexiform neurofibroma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015305

• Genome and transcriptome sequence data from a metastatic osteosarcoma tumor patient

  Genome and transcriptome sequence data from a metastatic osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015306

• Proteomics of 7-member healthy family (father, mother, their three biological daughters and monozygotic twin sons)

  The dataset contains proteomics data of seven healthy family members. The samples were taken from peripheral blood mononuclear cells.

  Dataset EGAD00001009985

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0020_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0020_002 for Triple negative breast cancer patient-derived xenograft SA604X8XB02164

  Dataset EGAD00001011254

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0187_002A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0187_002A for Diffuse large B-cell lymphoma patient sample TFRIPAIR10_DLBCL

  Dataset EGAD00001010233

• Illumina_WXS_T-CELL-XEN

  Whole-exome sequencing on Illumina HiSeq2000/2500 of Patient-derived xenograft derived from PDO culture derived from colorectal cancer primary tumor sample

  Dataset EGAD00001002101

• Bulk exome sequencing of primary GBM - SF 10360

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10360

  Dataset EGAD00001002274

• McGill EMC Release 4 in tissue "Brodmann (1909) area 8;Brodmann (1909) area 9"

  McGill EMC Release 4 in tissue "Brodmann (1909) area 8;Brodmann (1909) area 9"

  Dataset EGAD00001001286

• RNA-sequencing of cohesin-mutated and wildtype adult AMLs

  Transcriptomic data generated by RNA-sequencing for adult human AMLs with STAG2 or RAD21 mutations or no cohesin mutations (CTRL-AMLs).

  Dataset EGAD00001011197

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0063_000

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0063_000 for Triple negative breast cancer patient-derived xenograft SA609X3XB01584

  Dataset EGAD00001011209

• ATAC-seq of cohesin-mutated and -wildtype adult AMLs

  ATAC-seq (Illumina TDE1 Transposase) to profile accessible chromatin regions of cohesin-mutated (STAG2 or RAD21 mutations) and -wildtype adult AMLs.

  Dataset EGAD00001011267

• Genome and transcriptome sequence data from a plexiform neurofibroma tumor patient

  Genome and transcriptome sequence data from a plexiform neurofibroma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015283

• Genome and transcriptome sequence data from a relapsed osteosarcoma tumor patient

  Genome and transcriptome sequence data from a relapsed osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015311

• Genome and transcriptome sequence data from a synovial sarcoma tumor patient

  Genome and transcriptome sequence data from a synovial sarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015313

• Genome and transcriptome sequence data from a ewing sarcoma tumor patient

  Genome and transcriptome sequence data from a ewing sarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015315

• Genome and transcriptome sequence data from a rhabdomyosarcoma, alveolar tumor patient

  Genome and transcriptome sequence data from a rhabdomyosarcoma, alveolar patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015318

• Genome and transcriptome sequence data from a anaplastic astrocytoma tumor patient

  Genome and transcriptome sequence data from a anaplastic astrocytoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015319

• Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma tumor patient

  Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015324

• Genome and transcriptome sequence data from a alveolar rhabdomyosarcoma tumor patient

  Genome and transcriptome sequence data from a alveolar rhabdomyosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015329

• Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma tumor patient

  Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015330

• Genome and transcriptome sequence data from a pIlomyxoid astrocytoma tumor patient

  Genome and transcriptome sequence data from a pIlomyxoid astrocytoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015333

• Genome and transcriptome sequence data from a wilms tumor tumor patient

  Genome and transcriptome sequence data from a wilms tumor patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015334

• Genome and transcriptome sequence data from a rhabdomyosarcoma, alveolar tumor patient

  Genome and transcriptome sequence data from a rhabdomyosarcoma, alveolar patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015335

• Genome and transcriptome sequence data from a infantile fibrosarcoma tumor patient

  Genome and transcriptome sequence data from a infantile fibrosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015263

• Genome and transcriptome sequence data from a CNS sarcoma tumor patient

  Genome and transcriptome sequence data from a CNS sarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015268

• Genome and transcriptome sequence data from a ocular melanoma tumor patient

  Genome and transcriptome sequence data from a ocular Melanoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015269

• Genome and transcriptome sequence data from a aggressive fibromatosis tumor patient

  Genome and transcriptome sequence data from a aggressive fibromatosis patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015279

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0163_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0163_001 for Triple negative breast cancer patient-derived xenograft SA609X7XB03505

  Dataset EGAD00001011219

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0206_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0206_002 for Triple negative breast cancer patient-derived xenograft SA535X10XB03696

  Dataset EGAD00001011235

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0014_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0014_001 for Triple negative breast cancer patient-derived xenograft SA604X6XB01979

  Dataset EGAD00001011251

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0015_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0015_001 for Triple negative breast cancer patient-derived xenograft SA604X6XB01979

  Dataset EGAD00001011252

• Engineered cartilage: deriving design principles from human developmental: RNA (2025-07-30)

  Engineered cartilage: deriving design principles from human developmental pathways . This dataset contains all the data available for this study on 2025-07-30.

  Dataset EGAD00001015664

• Geographic and age-related variations in mutational processes in colorectal cancer - filtered vcf files (Mutographs)

  Geographic and age-related variations in mutational processes in colorectal cancer - filtered vcf files (Mutographs)

  Dataset EGAD00001015486

• The Finland-United States Investigation of NIDDM Genetics (FUSION) Tissue Biopsy Study

  The Finland-United States Investigation of NIDDM Genetics (FUSION) study is a long-term effort to identify genetic variants that predispose to type 2 diabetes (T2D) or that impact the variability of T2D-related quantitative traits (QTs). Most of the variants associated with T2D and related traits (glucose and insulin, anthropometrics, lipids) through genome-wide association studies (GWAS) occur in non-coding regions, suggesting a strong regulatory component to disease susceptibility. Regulatory element activity is often tissue-specific, which further complicates discovery of the causal/functional variation. Therefore, there is a critical need to identify the appropriate cell type, regulatory elements, target genes, and causal variants(s) in T2D-relevant tissues. We hypothesize that a subset of T2D and related variants alter gene expression regulation in skeletal muscle and adipose tissue - two major insulin target tissues and play key roles in insulin resistance. To that end, our study contains a comprehensive survey of genomics, epigenomics and transcriptomics in skeletal muscle and adipose tissue from individuals with glucose tolerance categories ranging from normal to T2D.For this FUSION Tissue Biopsy Study, we obtained RNA-Seq, microRNA (miRNA)-Seq, and DNA methylation (methyl)-Seq data on biopsy samples from 331 individuals from across the range of glucose tolerance: 124 normal glucose tolerance (NGT), 77 impaired glucose tolerance (IGT), 44 impaired fasting glucose (IFG), and 86 newly-diagnosed T2Ds. Participants completed two study visits, two weeks apart. First visits comprised most of the clinical phenotyping, including four-point OGTT (fasting, and 30, 60, and 120 minute post-load); BMI, WHR; lipids; blood pressure; and many other variables. Participants also completed FUSION health history, medication, and lifestyle questionnaires. On the second visit, we obtained ~250mg vastus lateralis skeletal muscle, ~750mg abdominal subcutaneous adipose, and a ~5x15mm section of abdominal skin. Visits were completed in March 2013. RNA isolation is ongoing in the Collins laboratory at the NIH, RNA and miRNA sequencing at the NIH Intramural Sequencing Center (NISC), and genotyping at the Center for Inherited Disease Research (CIDR). Individual-level data is available here for the 306 individuals who consented to data deposit. To focus on evaluation of gene expression and its regulation in skeletal muscle, we analyzed mRNA extracted from vastus lateralis skeletal muscle obtained from 271 of the 331 individual subjects from Finland, along with genome-wide genotypes. Individual-level data is available here for the 250 subjects who consented to the use of their data.Release phs001048.v2.p1 adds muscle data for an additional 42 subjects and data from adipose tissue for 276 subjects. Total RNA was isolated using Trizol extraction in the Collins laboratory at the NIH. The mRNA was poly-A selected, 24-plex libraries were generated using the Illumina TruSeq directional mRNA-seq library protocol and RNA sequencing was performed on HiSeq2000 sequencers using 101bp paired-end reads at NISC. miRNA libraries were prepared from total RNA from 296 muscle and 270 adipose samples, pooled and sequenced 50bp single-end reads on Illumina HiSeq2500. Data for 272 muscle and 251 adipose samples are available here for individuals with consent for data deposit. DNA was extracted from blood in the Collins laboratory, and genotyping on the Illumina Omni2.5M array was performed at CIDR. Genotypes were imputed using the HRC 2016 reference panel. In order to assess regions of open chromatin in skeletal muscle, we obtained muscle tissue from a commercial provider to perform ATAC-seq; these samples were sequenced at the University of Michigan DNA Sequencing Core.Release phs001048.v3.p1 adds single-nucleus (sn) RNA-seq and ATAC-seq data in 287 skeletal muscle samples out of the original 331 individuals. Individual-level data is available here for the 265 subjects who consented to the use of their data. The frozen tissue biopsy samples were processed in ten batches, each consisting of 40-41 samples. These batches were organized using a randomized block design to protect against experimental contrasts of interest including cohort, age, sex, BMI among others. Samples in each batch were pulverized, pooled together followed by nuclei isolation. The nuclei were processed on the 10X Genomics Chromium platform separately for snATAC-seq and snRNA-seq (v. 3.1 chemistry for snRNA-seq).Release phs001048.v4.p1 adds additional phenotypes and provides some corrections to several previous phenotypes.

  Study phs001048

• CpG methylation changes associated with hyperglycemia in type 1 diabetes occur at angiogenic glomerular and retinal gene loci.

  Retinal and glomerular microangiopathy, and cardiovascular disease, contribute to the morbidity and mortality observed in adults with type 1 diabetes (T1D). While the level and duration of hyperglycemia are primary factors influencing these complications, the underlying molecular mechanisms behind glucose-induced organ damage remain poorly understood. In this study, blood samples from young T1D patients at diagnosis and three years later in average were analyzed for DNA methylation using whole-genome bisulfite sequencing. Significant DNA methylation changes in critical angiogenic gene loci were associated with HbA1c, a direct hallmark of chronic hyperglycemia. This finding may offer novel epigenetic insights for a better understanding of T1D complications.

  Study EGAS50000000370

• Developmental Mechanisms of Human Congenital Heart Disease in Subjects with 22q11.2 Deletion Syndrome (DiGeorge Syndrome/Velocardiofacial Syndrome)

  The study is designed to identify genetic modifiers of cardiovascular defects in subjects with 22q11.2 deletion syndrome (22q11.2DS), also known as DiGeorge syndrome or velo-cardio-facial syndrome. Affymetrix 6.0 arrays were processed on 1,480 subjects with known cardiovascular anomalies or with normal structures, all with 22q11.2DS. One sample is a duplicate so it was removed. There are 1,472 samples total of unrelated, de-identified, probands. Over 90% have the same sized 3 million base pair deletion flanked by low copy repeats (LCR22) A and D, while approximately 6% have nested A to B deletions. The rest have other nested deletions, that include a deletion in the vicinity of TBX1 (between LCR22 A and B). A subset of the data was used to identify copy number variations serving as modifiers. Some data were previously published by Dr. Emanuel's team at Children's Hospital of Philadelphia in PA, USA (PMID:26742502; PMID:4896312; PMID:25892112; PMID:4570279). The de-identified DNA data from unrelated subjects come from multiple research sites in the US and Europe as part of the International 22q11.2 Consortium and the International 22q11.2 Brain and Behavior Consortium.

  Study phs001339

• Rare Disease Susceptibility Variant Study in Children with Crohn's Disease and Their Parents Using Targeted Gene Sequencing.

  We performed targeted, massively-parallel sequencing of 101 genes in 205 children with Crohn's disease, including 179 parent-child trios and 200 controls, both of European ancestry. We identified three genes with nominally significant p-values: NOD2, RTKN2, and MGAT3. Only NOD2 was significant after correcting for multiple comparisons. We identified eight novel rare variants in NOD2 that are likely disease-associated. Incorporation of rare variation and compound heterozygosity nominally increased the proportion of variance explained from 0.074 to 0.089. We estimated the population attributable risk and total heritability of variation in NOD2 to be 32.9% and 3.4%, respectively, with 3.7% and 0.25% accounted for by rare putatively functional variants. Sequencing probands (as opposed to genotyping) to identify rare variants and incorporating phase by sequencing parents can recover a portion of the missing heritability of Crohn's disease. (Reprinted from G3 2018;8(9): 2881-2888; PMID: 30166421. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.)

  Study phs001751

• Nicotine dependence GWAS meta-analysis across European and African American ancestries

  Cigarette smoking is the leading cause of preventable morbidity and mortality. Knowledge is evolving on genetics underlying initiation, regular smoking, nicotine dependence (ND), and cessation. We performed a genome-wide association study using the Fagerström Test for ND (FTND) in 58,000 smokers of European or African ancestry. Five genome-wide significant loci, including two novel loci MAGI2/GNAI1 (rs2714700) and TENM2 (rs1862416) were identified, and loci reported for other smoking traits were extended to ND. Using the heaviness of smoking index (HSI) in the UK Biobank (N=33,791), rs2714700 was consistently associated, but rs1862416 was not associated, likely reflecting ND features not captured by the HSI. Both variants were cis-eQTLs (rs2714700 for MAGI2-AS3 in hippocampus, rs1862416 for TENM2 in lung), and expression of genes spanning ND-associated variants was enriched in cerebellum. SNP-based heritability of ND was 8.6%, and ND was genetically correlated with 13 other smoking traits (rg=0.40-0.95) and co-morbid diseases. Our results emphasize the FTND as a composite phenotype that expands genetic knowledge of smoking, including loci specific to ND.

  Study phs001532

• Genetic Basis of Breast Cancer Resistance in BRCA1 Mutation Carrier

  Our study addressed a specific question in NCI RFA-CA-12-022: "What underlying causal events - e.g., genetic, epigenetic, biologic, behavioral, or environmental - allow certain individuals to survive beyond the expected limits of otherwise highly lethal cancers?". A germline mutation in BRCA1 (BRCA1+) is the most penetrant genetic predisposition for breast cancer. Nevertheless, a portion of BRCA1+ carriers does not develop breast cancer in their lifetime, suggesting that the genetic predisposition can be antagonized by resistant factors. BRCA1+ was inherited from an ancestor of the carrier family thousand years ago. We hypothesize that evolution could select certain genetic components to suppress oncogenesis caused by the predisposition. We compared germline variants in all genes in 27 pairs of breast cancer-unaffected and -affected BRCA1+ carriers, each pair inherited the same BRCA1+. We identified 12 deleterious variants enriched in breast cancer-unaffected carriers, all are common variants. A variant rs3735400 is located in ANLN, a cytokinesis-essential gene. Overexpression of variant-containing ANLN and suppressed expression of endogenous ANLN decrease ANLN nuclear localization and delay cell growth. Our findings suggest that common variants can be selected to resist oncogenesis imposed by BRCA1+.

  Study phs001243

• NIH Roadmap Epigenomics Program - Broad Institute

  For the NIH Roadmap Epigenomics project, we applied ChlP-Seq, HTBS and WGBS pipelines to generate comprehensive high-resolution maps of chromatin state and DNA methylation for 100 diverse cell types. Cell types were selected for their biological and medical importance, and for their potential to maximize the comprehensiveness of acquired epigenomic data. They include human ES cells, ES-derived cells, mesenchymal stem cells, reprogrammed stem cells and primary tissues. Comprehensive characterization of epigenetic marks ("the epigenome") is a critical step towards a global understanding of the human genome in health and disease. In this study we provide unprecedented views of the human epigenetic landscape and its variation across cell states, which offer fundamental insight into the functions and interrelationships of epigenetic marks, and provide a framework for future studies of normal and diseased epigenomes. The Roadmap Epigenomics Broad cohort is utilized in the following dbGaP sub-study. To view molecular data and derived variables collected in this sub-study, please click on the following sub-study below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000700 the Roadmap Epigenomics Broad cohort. phs000610 RM_Epigenomics_Broad_Alz

  Study phs000700

• Human Pilocytic Astrocytoma Single Cell RNA Sequencing

  Pilocytic astrocytoma (PA), the most common childhood brain tumor, is a low-grade glioma with a single driver BRAF rearrangement. Here, we perform scRNAseq in six PAs using methods that enabled detection of the rearrangement. When compared to higher-grade gliomas, a strikingly higher proportion of the PA cancer cells exhibit a differentiated, astrocyte-like phenotype. A smaller proportion of cells exhibit a progenitor-like phenotype with evidence of proliferation. These express a mitogen-activated protein kinase (MAPK) program that was absent from higher-grade gliomas. Immune cells, especially microglia, comprise 40% of all cells in the PAs and account for differences in bulk expression profiles between tumor locations and subtypes. These data indicate that MAPK signaling is restricted to relatively undifferentiated cancer cells in PA, with implications for investigational therapies directed at this pathway. Note that 931 out of 1234 samples in the Sequence Read Archive (SRA) passed QC and have transcript count data available from the Broad Institute Single Cell Portal. The transcript count data can be found at https://singlecell.broadinstitute.org/single_cell/study/SCP271/pilocytic-astrocytoma-single-cell-rna-seq#study-download

  Study phs001854

• VA APOLLO Project - Research for Precision Oncology (RePOP)

  The Research for Precision Oncology Program (RePOP) is a research activity that establishes a cohort of Veterans diagnosed with cancer and who have had genomic analyses performed on their tumor tissue as part of standard of care. All data relevant to a patient's cancer and cancer care will be collected under RePOP, including patient demographics, co-morbidities, genomic analysis, treatments, medications, lab values, imaging studies, and outcomes. All RePOP participants will have signed/verbal informed consent and signed HIPAA authorization to have their data stored and shared from RePOP's Precision Oncology Program Data Repository (PODR). The Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) network is a collaboration between NCI, the Department of Defense (DoD), and the Department of Veterans Affairs (VA) to incorporate proteogenomics into patient care as a way of looking beyond the genome, to the activity and expression of the proteins that the genome encodes. The emerging field of proteogenomics aims to better predict how patients will respond to therapy by screening their tumors for both genetic abnormalities and protein information, an approach that has been made possible in recent years due to advances in proteomic technology.

  Study phs001374

• Pharmacogenomic Interactions in Glioblastoma Cell Line Models

  Glioblastoma (GBM) is a lethal disease without effective treatments. To advance toward effective therapeutic approaches that are biomarker-driven, there is a need for new targeted agents and to develop accurate preclinical models that encompass its cellular and molecular diversity. Historical cell line models poorly represent molecular diversity of GBMs, so we developed a living tissue bank encompassing 103 patient-derived GBM cell lines (PDGCLs) as a platform for preclinical pharmacogenomic investigation at scale. Thirty-four PDGCLs were submitted to a comprehensive molecular characterization of copy number alterations and mutations using whole exome sequencing (WES) and gene expression (microarrays), and tested against a panel of 390 small molecules at sixteen different duplicated concentrations. After integrating and systematically correlating molecular alterations with drug sensitivities, we yielded 8,083,140 pharmacogenomic interactions, and discovered novel drug and biomarker combinations which help to prioritize highly effective novel candidate treatments in GBM. Our findings demonstrate the utility of deep characterization of large numbers of models from a single disease to detect complex predictors of compound sensitivity, and indicate novel therapeutic approaches for a large fraction of patients with GBM.

  Study phs001793