14970 results for "cancer studies using rna-seq"

in 38.75 milliseconds.

• A CCG expansion in ABCD3 causes oculopharyngodistal myopathy in individuals of European ancestry

  In this study we describe the identification of CCG expansions in ABCD3 in affected individuals across eight unrelated OPDM families of European ancestry. In two large Australian OPDM families, using a combination of linkage studies, short-read WGS and targeted ONT sequencing, we identified CCG expansions in the 5’UTR of ABCD3. Independently, the ABCD3 CCG expansion was identified through the 100,000 Genomics England Genome Project in three individuals from two unrelated UK families diagnosed with OPDM.

  Study EGAS50000000298

• South African Blood Regulatory (SABR) Resource

  Functional genomics resources are critical for interpreting human genetic studies, however they are predominantly from European-ancestry individuals. Here we present the South African Blood Regulatory (SABR) resource, a map of blood regulatory variation that includes three South Eastern Bantu-speaking groups. Using paired whole genome and blood transcriptome data from over 600 individuals, we map the genetic architecture of 40 blood cell traits derived from deconvolution analysis, as well as expression, splice, and cell type interaction quantitative trait loci (QTL).

  Study EGAS50000001008

• Relapse CHL study

  Classical Hodgkin Lymphoma (CHL) is characterized by a complex tumor microenvironment (TME) that supports disease progression. While immune cell recruitment by Hodgkin and Reed–Sternberg (HRS) cells is well-documented, the role of non-malignant B cells in relapse remains unclear. Using single-cell RNA sequencing (scRNA-seq) on paired diagnostic and relapsed CHL samples, we identified distinct shifts in B cell populations, particularly an enrichment of naïve B cells and a reduction of memory B cells in early-relapse compared to late-relapse and newly diagnosed CHL. The enrichment of naïve B cells in early relapse biopsies was confirmed in independent validation cohorts using scRNA-seq and immunohistochemistry. Notably, naïve B cells in early-relapse samples exhibited high expression of LGALS9, an immunosuppressive molecule known to interact with T cell immunoglobulin and mucin domain 3 (TIM-3) on regulatory T cells (Tregs). Cell-cell interaction analysis revealed the importance of interactions between LGALS9+ naïve B cells and TIM-3+ Tregs in the early-relapse setting. Spatial analysis by imaging mass cytometry confirmed close proximity of LGALS9+ naïve B cells with TIM-3⁺ CD4⁺ T cells and HRS cells, pointing to their role in shaping an immunosuppressive niche. Our findings highlight a previously unrecognized population of LGALS9⁺ naïve B cells with immunoregulatory potential in early-relapse CHL and provide new insights into the spatial and transcriptional architecture of the relapsed TME in CHL.

  Study EGAS00001008222

• DS-ALL RNA-Seq DAC

  Dac EGAC00001002866

• Melanoma RNA Seq Data commitee

  Dac EGAC00001002928

• Single cell RNA-seq aging

  Dac EGAC00001001502

• Whole genome and RNA sequencing of paediatric glioblastoma in the ICGC PedBrain project

  Paediatric glioblastoma (pedGBM) is characterised by substantial intertumoural heterogeneity. In order to identify the genetic lesions underlying tumourigenesis, we analysed whole genomes and transcriptomes of pedGBMs and in vitro model systems by next generation sequencing. Novel fusions of the receptor tyrosine kinase MET lead us to investigate targeted therapy using MET inhibitors. This study is part of the International Cancer Genome Consortium PedBrain Tumor Project (ICGC PedBrain, http://www.pedbraintumor.org/).

  Study EGAS00001001139

• NextGen Consortium: The iPSCORE (iPSC Collection for Omic Research) Resource for Studying the Impact of Genetic Variation on Molecular Phenotypes

  The iPSC Collection for Omic Research (iPSCORE) Resource was created as part of the Next-Gen Consortium funded by NHLBI. The overarching purpose of the resource is to provide a large collection of human induced pluripotent stem cells (iPSCs) for use in studying the impact of genetic variation on molecular and physiological phenotypes. The resource has been used in a number of studies in the Dr. Kelly A. Frazer's Lab examining both the characteristics of human iPSCs and a variety of iPSC-derived cell types including cardiovascular progenitor cells (iPSC-CVPCs), pancreatic precursor cells (iPSC-PPCs), and retina pigment epithelium cells (iPSC-RPEs). We have shown that the iPSCs, CVPCs, and PPCs are suitable surrogate models to identify genetic factors active in early developmental processes because they exhibit fetal-like molecular properties. A total of 273 individuals have participated in the study, of which 222 have had iPSCs generated from fibroblasts. Of the 273 individuals, 181 are part of 55 families that include 24 monozygotic twin pairs and 5 dizygotic twin pairs, allowing for the incorporation of familial relationships into genetic analyses. Germline DNA has been sequenced from blood or fibroblast samples for all 273 individuals (available through dbGaP phs001325) and other genomic data (RNA-seq, DNA methylation, genotype arrays, ATAC-seq, H3K27ac ChIP-seq, HiC-seq) have been generated from the 222 iPSCs as well as derived cell types (available through dbGaP phs000924). QTL analyses were conducted for multiple omics data types and summary statistics are available through dbGaP phs0001325. Important note: Of the 273 individuals, 268 are consented for general research use and 5 are consented for cardiac research only. For detailed information about iPSCORE Collection including samples, methods used to generate the data, and how to access the datasets visit the Frazer lab website.The 222 well characterized iPSC lines that constitute the iPSCORE resource are available, please contact Dr. Kelly A. Frazer (kafrazer@health.ucsd.edu) if you are interested in obtaining the collection.

  Study phs000924

• NextGen Consortium: The iPSCORE (iPSC Collection for Omic Research) Resource for Studying the Impact of Genetic Variation on Molecular and Physiological Phenotypes - Whole Genome Sequence

  The iPSC Collection for Omic Research (iPSCORE) Resource was created as part of the Next-Gen Consortium funded by NHLBI. The overarching purpose of the resource is to provide a large collection of human induced pluripotent stem cells (iPSCs) for use in studying the impact of genetic variation on molecular and physiological phenotypes. The resource has been used in a number of studies in the Dr. Kelly A. Frazer's Lab examining both the characteristics of human iPSCs and a variety of iPSC-derived cell types including cardiovascular progenitor cells (iPSC-CVPCs), pancreatic precursor cells (iPSC-PPCs), and retina pigment epithelium cells (iPSC-RPEs). We have shown that the iPSCs, CVPCs, and PPCs are suitable surrogate models to identify genetic factors active in early developmental processes because they exhibit fetal-like molecular properties.A total of 273 individuals have participated in the study, of which 222 have had iPSCs generated from fibroblasts. Of the 273 individuals, 181 are part of 55 families that include 24 monozygotic twin pairs and 5 dizygotic twin pairs, allowing for the incorporation of familial relationships into genetic analyses.Germline DNA has been sequenced from blood or fibroblast samples for all 273 individuals (available through dbGaP phs001325) and other genomic data (RNA-seq, DNA methylation, genotype arrays, ATAC-seq, H3K27ac ChIP-seq, HiC-seq) have been generated from the 222 iPSCs as well as derived cell types (available through dbGaP phs000924).QTL analyses were conducted for multiple omics data types and summary statistics are available through dbGaP phs0001325.Important note: Of the 273 individuals, 268 are consented for general research use and 5 are consented for cardiac research only.For detailed information about iPSCORE Collection including samples, methods used to generate the data, and how to access the datasets visit the Frazer lab website.The 222 well characterized iPSC lines that constitute the iPSCORE resource are available, please contact Dr. Kelly A. Frazer (kafrazer@health.ucsd.edu) if you are interested in obtaining the collection.

  Study phs001325

• A novel TP53-KPNA3 translocation defines a de novo treatment-resistant clone in osteosarcoma

  Osteosarcoma is the most common primary bone cancer. It can be cured by aggressive surgery and chemotherapy, but outcomes for metastatic or chemoresistant disease remain dismal. Cancer sequencing studies have shown that the p53 pathway is dysregulated in nearly every case, often by translocation; however, no studies of osteosarcoma evolution or intratumor heterogeneity have been done to date. We studied a patient with chemoresistant, metastatic disease over the course of three years. We performed exome sequencing on germline DNA and DNA collected from tumor at three separate timepoints. We compared variant calls and variant allele frequencies between different samples. We identified subclonal driver mutations in several different genes in the primary tumor sample and found that one particular subclone dominated subsequent tumor samples at relapse. This clone was marked by a novel TP53-KPNA3 translocation and loss of the opposite-strand wild-type TP53 allele. Future research must focus on functional significance of such clones and strategies to eliminate them.

  Study EGAS00001001805

• Germline Genomic Analyses of Breast Cancer in Latinas

  In this case-control study of breast cancer among Hispanic/Latina (H/L) women, the goals were to identify breast cancer susceptibility genes and genetic variants for risk of developing breast cancer in H/L women. There were two phases with whole exome sequencing (WES) done in a discovery phase and targeted sequencing of candidate genes in the replication phase. The candidate genes selected for replication came from the first phase and from genes known to affect breast cancer risk in prior studies. Cases and controls were drawn from several studies. Breast cancer cases for discovery phase included women from the City of Hope (COH) Clinical Cancer Genomics Community Research Network (CCGCRN), UCSF Cancer Genetics Clinic and USC Cancer Genetics clinic. Controls for discovery phase included women who did not have breast and were recruited through City of Hope community fairs. A separate group of controls included women from the California Teachers Study. Additional controls for discovery were obtained from WES already generated by the Multi-ethnic cohort (MEC) study. The discovery/WES results of known breast cancer genes were published (PMID 31206626). In the replication phase, we included cases and controls from the Cancer de Mama (CAMA) study which is a case-control study of breast cancer in Mexico, MEC for those not included in the discovery dataset, the San Francisco Bay Area Cancer study (phs000912), the Northern California Breast Cancer Registry, and the California Pacific Medical Center Research Institute Women's Cohort (phs000395). Cases from the PATHWAYS study who were recruited from Northern California Kaiser Permanente were also included. Results from the combined discovery and replication analyses are reported in PMID 36747679.

  Study phs003144

• The Molecular Landscape of Asian Breast Cancers Reveals Clinically Relevant Population-Specific Differences

  Molecular profiles of breast cancer have contributed to an improved understanding of the disease, enabled development of molecular prognostic signatures to guide treatment decisions and unveiled new or more accurate therapeutic options for breast cancer patients. However, the extent to which differences in genetic, environmental and lifestyle factors influence molecular profiles in different populations remains poorly characterised, as relatively few large-scale molecular studies of breast tumours in non-Caucasian populations have hitherto been reported. Here, we present the molecular profiles of 560 Asian breast tumours and a comparative analysis of breast cancers arising in Asian and Caucasian women. Compared to the breast tumours in predominantly Caucasian women reported in TCGA and METABRIC, we show an increased prevalence of Her2-enriched molecular subtypes and higher prevalence of TP53 somatic mutations in ER+ Asian breast tumours. Using gene expression and immunohistochemistry, we observed elevated immune scores in Asian breast tumours, suggesting potential clinical response to immune checkpoint inhibitors. Whilst Her2-subtype and enriched immune score are associated with improved survival, presence of TP53 somatic mutations is associated with poorer survival in ER+ tumours. Taken together, these population differences unveil new opportunities to improve the understanding of this disease and lay the foundation for precision medicine in different populations.

  Study EGAS00001004518

• CARE iSGS single nucleus RNA-seq

  This study contains single nucleus RNA-sequencing data from healthy controls, iSGS, and traumatic subglottic stenosis patients.

  Study EGAS50000000878

• RNA-seq study of human long-term and short-term hematopoietic stem cells from umblical cord blood with lentiviral overexpression of S1PR3

  To investigate the molecular and biological pathways altered by S1PR3OE in human hematopoietic stem cells (HSC), we performed RNA-sequencing (RNA-seq) of LT- and ST-HSC 3 days after transduction with control or S1PR3 overexpression (OE) lentiviral vectors. LT-HSC and ST-HSC from 3 pool of CB lin- were FACS-purified, cells were prestimulated for 4 hours and transduced with lentiviral vectors. At day 3, 2000-5300 BFP+ cells were FACS-purified for RNA isolation with a PicoPure kit. We were able to isolate only 1600-1800 BFP+ cells from LT-HSC control samples as opposed to 4000-5400 BFP+ cells from S1PR3OE samples. Thus, we pooled all control BFP+ LT-HSC cells into one sample for RNA-seq analysis. BFP- LT-HSC from control vector transduction were purified from CB1 as an additional LT-HSC control. Nextera libraries generated from 10 ng RNA from 5 LT-HSC samples (2 controls, 3 S1PR3OE) and 6 ST-HSC samples (3 controls, 3 S1PR3OE) were subjected to 125 bp, paired-end RNA-sequencing on the Illumina HiSeq 2500 with an average of 50 million reads/sample at the Center for Applied Genomics, Sick Kids Hospital.

  Study EGAS00001004798

• Genomic Translation for ALS Care (GTAC) - WGS

  To look for genetic correlates of disease progression, the GTAC study recruited patients with motor neuron disease from 13 academic medical center clinics and followed them longitudinally for up to 5 years. Participants were regularly assessed for changes in respiratory function, the ALS Functional Rating Scale, and the ALS Cognitive Behavioral Scale. Participants underwent PCR-free whole genome sequencing on the Illumina NovaSeq, as well as repeat-prime PCR assessment of the C9ORF72 repeat expansion. Participants had PBMCs and whole blood RNA banked for future correlative studies.

  Study phs002973

• An epigenetic single-cell atlas of IDH-mutant glioma reveals the role of ATRX in shaping tumor composition

  Recent single-cell RNA-sequencing studies have identified a hierarchy of cell types that is common to all isocitrate dehydrogenase (IDH) -mutant gliomas. This finding is somewhat paradoxical since the genetic differences between IDH-mutant astrocytomas and IDH-mutant oligodendrogliomas are prognostic, predictive of therapeutic response, and correlated with differences in immune infiltrates. To integrate these disparate findings, we constructed a single-cell atlas of 22 human IDH-mutant primary untreated grade-II/III gliomas.

  Study EGAS00001004523

• Discovery of new fusion transcripts in a cohort of pediatric solid cancers at relapse

  This study aims to dissect further the complexity of fusion landscape in recurrent pediatric cancers. A retrospective study on RNA-sequencing data of 48 pediatric patients at relapse with different malignancies was conducted in order to detect and validate several fusions and predict their probable oncogenic potential and targetability. We obtained a high validation rate of 90% of selected candidates which will serve both clinical and research needs to detect and prioritize experimental validation studies leading to the development of new therapeutic options.

  Study EGAS00001003236

• The endometrial transcription landscape of MRKH syndrome

  The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome (OMIM 277000) is characterized by agenesis of the uterus and upper part of the vagina in females with normal ovarian function. While genetic causes have been identified for a small subset of patients and epigenetic mechanisms presumably contribute to the pathogenic unfolding, too, the etiology of the syndrome has remained largely enigmatic. A comprehensive understanding of gene activity in the context of the disease is crucial to identify etiological components and their potential interplay. So far, this understanding is lacking, primarily due to the scarcity of samples and suitable tissue. In order to close this gap, we profiled endometrial tissue of uterus rudiments in a large cohort of MRKH patients using RNA-seq and thereby provide a genome-wide view on the altered transcription landscape of the MRKH syndrome.

  Study EGAS00001004601

• Cancer-associated fibroblasts promote drug resistance in ALK-driven lung adenocarcinoma cells by upregulating lipid biosynthesis

  Targeted therapy interventions using tyrosine kinase inhibitors (TKIs) provide encouraging treatment responses in ALK-rearranged lung adenocarcinomas, yet resistances occur almost inevitably. Apart from tumor cell-intrinsic resistance mechanisms, accumulating evidence supports a role of cancer-associated fibroblasts (CAFs) in affecting the therapeutic vulnerability of lung cancer cells. Here, we aimed to investigate underlying molecular networks shaping the therapeutic susceptibility of ALK-driven lung adenocarcinoma cells via tumor microenvironmental cues using three-dimensional (3D) spheroid co-culture settings. We show that CAFs promote therapy resistance of lung tumor cells against ALK inhibition by reducing apoptotic cell death and increasing cell proliferation. Using single-cell RNA-sequencing analysis, we show that genes involved in lipogenesis constitute the major transcriptional difference between TKI-treated homo- and heterotypic lung tumor spheroids. CAF-conditioned medium and CAF-secreted factors HGF and NRG1 were both able to promote resistance of 3D-cultured ALK-rearranged lung tumor cells via AKT signaling, which was accompanied by enhanced de novo lipogenesis and supression of lipid peroxidation. Notably, simultaneous targeting of ALK and SREBP-1 was able to overcome the established CAF-driven lipid metabolic-supportive niche of TKI-resistant lung tumor spheroids. Our findings highlight a crucial role of CAFs in mediating ALK-TKI resistance via lipid metabolic reprogramming and suggest new ways to overcome resistance towards molecular directed drugs by targeting vulnerabilities downstream of oncogenic signaling.

  Study EGAS50000000135

• Chromatin accessibility (ATAC-seq) and transcriptome (RNA-seq) data from immune cells for healthy young and healthy old subjects

  Dataset consisting of: (1) N=234 genome-wide chromatin accessibility (ATAC-seq) profiles for distinct N=21 healthy old and N=28 healthy young subjects. ATAC-seq biological samples provided for the following tissues: PBMC (N=24), CD14+ monocytes (N=18), CD8+ memory T cells (N=7), CD8+ naive T cells (N=7), CD4+ memory T cells (N=7), CD4+ naive T cells (N=7), and naive B cells (N=7). (2) N=39 genome-wide transcription (RNA-seq) data for distinct N=15 healthy old and N=24 healthy young subjects' PBMCs.

  Dataset EGAD00001003602

• 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

• Dataset for breast_cancer-RNA

  Rare cancer sequencing data of 59 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008850

• Dataset for bone_cancer-RNA

  Rare cancer sequencing data of 55 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008848

• Dataset for GIST-RNA

  Rare cancer sequencing data of 50 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008852

• RNA-seq data of 370 high grade ovarian tumors from the ICON7 trial

  Collection of RNA-seq, Illumina, paired-end fastq files for 370 archival tissues from a subset of patients with high grade serous ovarian carcinoma enrolled in the phase 3 ICON7 trial. Clinical data and digital pathology information for CD8 is also available.

  Dataset EGAD00001004988

• BLUEPRINT release August 2016, RNA-Seq for monocyte - T=0days, on genome GRCh38

  RNA-Seq data for 4 monocyte - T=0days sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002360

• BLUEPRINT release August 2015, RNA-Seq for plasma cell, on genome GRCh38

  RNA-Seq data for 4 plasma cell sample(s). 4 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001523

• BLUEPRINT release August 2015, RNA-Seq for monocyte - None, on genome GRCh38

  RNA-Seq data for 4 monocyte - None sample(s). 4 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001532

• Chronic lymphocytic leukemia patient-derived xenografts recapitulate clonal evolution to Richter transformation

  Whole-genome sequencing (WGS) and RNA-seq data from patient-derived xenografts (PDXs) obtained from CLL and RT primary samples as described in Playa-Albinyana et al.

  Study EGAS00001006965

• RNA-seq on neuroblastoma PDX model COG-N-519 treated with control miR-1283 and test miR-99b-5p mimics

  RNA-sequencing on neuroblastoma PDX model COG-N-519 treated with control miR-1283 and test miR-99b-5p mimics. Three samples from each of the treatment condition were analysed. Next-Seq platform was used for sequencing.

  Dataset EGAD00001007754

• PPGL RNA-Seq dataset

  Dataset includes fastq files for RNA-Seq experiments for tumor samples of PPGL patients. Single end reads fastq files are available for 102 different samples

  Dataset EGAD00001008578

• Paired RNA-Seq of Tumor Organoids from glioblastoma, 2 patients, treated with different small molecule inhibitors

  Tumor Organoids from glioblastoma, 2 patients, treated with different small molecule inhibitors. Paired RNA-Seq was done on NovaSeq 6000 with the Illumina TruSeq stranded mRNA Kit. The small inhibitors GW2580, BLZ945 and PLX3397 were used. DMSO was used as control.

  Dataset EGAD00001011274

• bulk RNA-Seq samples of CRC patients

  The dataset contains samples of 30 CRC patients (3 samples for each patient, tumor and 2 normal adjacent tissue sites, 90 samples in total). Dataset is composed by fastq file (paired end) type from bulk RNA-Seq.

  Dataset EGAD00001009635

• Single-cell RNA-seq and spatial transcriptomics data of patients with sarcoidosis

  Single-cell RNA-seq and spatial transcriptomics data for 12 patients with sarcoidosis. From each patient, we analyzed skin biopsies of both lesional and non-lesional skin and we performed spatial transcriptomics for lesional skin samples. The data are provided as aligned BAM files.

  Dataset EGAD00001010020

• BLUEPRINT release August 2016, RNA-Seq for monocyte - None, on genome GRCh38

  RNA-Seq data for 4 monocyte - None sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002338

• Long-read data (PacBio)

  The goal of this project was to perform long-read RNA sequencing (LR-seq, PacBio) in combination with short-read RNA-seq for systematic characterization of the isoform diversity in primary breast tumor samples. We sequenced the full-length transcriptomes of 26 breast tumors and 4 normal breast samples.

  Dataset EGAD00001006597

• RNA-seq data from DMD patients and healthy controls

  This dataset comprises RNA-seq expression profiles from 57 subjects, of which 39 are DMD patients and 18 healthy controls. The data are described in the following article: Signorelli, Ebrahimpoor et al. (in review). Peripheral blood transcriptome profiling enables monitoring disease progression in dystrophic mice and patients.

  Dataset EGAD00001006826

• Processed RNA-seq data for clinical efficacy and biomarker analysis of neoadjuvant atezolizumab in operable urothelial carcinoma in the ABACUS trial

  ABACUS is a single arm phase 2 study that investigated 2 cycles of atezolizumab (1200mg Q3) prior to cystectomy in 95 patients with muscle invasive transitional cell cancer (T2-4N0M0). Pathological complete response (pCR) occurring in ≥20% of patients was the primary endpoint. Biomarker analysis on sequential tissue was a co-primary endpoint. This dataset includes the TPM and raw counts tables.

  Dataset EGAD00001006199

• ScRNA-seq of 6 human FL

  Follicular lymphoma (FL) is an indolent cancer of mature B-cells but carries increased risk of transformation to a more aggressive histology over time. We present here comprehensive profiling both tumor and immune compartments in 6 diagnostic FL biopsies by single-cell RNA sequencing. This confirmed results from 155 FL tumors characterized by mass cytometry (CyTOF) which revealed two distinct evolutionary trajectories with disparate risk of transformation and alternate biologies.

  Dataset EGAD00001007691

• Processed bam files for the whole exome sequencing of primary lung adenocarcinoma samples

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

  Dataset EGAD00001010320

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - Ribo-Seq

  This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

  Dataset EGAD00001011193

• South Asia Rheumatic Heart Disease Genetics Network

  Rheumatic heart disease (RHD) is a major cause of cardiovascular death and disability amongst young adults. Building on a sample collection established for and genotyped in several earlier successful candidate gene studies, this case-control study investigated host genetic susceptibility to RHD using a genome-wide approach. The current dataset comprises over 850 individuals recruited in Uttar Pradesh, India, including cases of RHD based on echocardiographic diagnosis and controls recruited on the basis of normal echocardiograms. For this analysis all available samples were genotyped using the Illumina HumanCore-24 BeadChip platform. Efforts are now underway to establish new sample collections in other areas of India as well as Pakistan and later other neighbouring countries.

  Study EGAS00001003565

• Genomics_of_acral_lentiginous_melanoma

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico.

  Study EGAS00001003740

• Adult-type Granulosa Cell Tumour of the Ovary RNA Sequencing

  We analyzed 34 AGCTs (19 primary and 15 recurrent) and the KGN cell line by RNA-Seq. Our cohort comprised of 3 AGCTs WT for FOXL2, 28 heterozygous and 3 homo/hemizygous for the pathogenic variant. Fresh-frozen AGCTs were selected from OVCARE’s Gynecological Tissue Bank in Vancouver, Canada for bulk RNA-seq. RNA was extracted from frozen tissue and sections adjacent to the scrolls submitted for RNA-seq were stained with hematoxylin and eosin (H&E) to evaluate tumour cell purity. Cases with >80% tumour cell purity were selected for sequencing with the majority of cases (29 of 34 patients) containing >90% tumour cells. Ribodepleted RNA libraries were constructed and paired-end sequencing (125 base pair reads) was performed.

  Dataset EGAD00001007812

• Diagnostic utility of whole genome sequencing in adults with B-other acute lymphoblastic leukemia

  Genomic profiling at diagnosis of B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL) in adults is used to guide disease classification, risk stratification and treatment decisions. Patients for which diagnostic screening fails to identify disease defining or risk stratifying lesions are classified as B-other ALL. We screened a cohort of 652 BCP-ALL cases enrolled in UKALL14 to identify and perform whole genome sequencing (WGS) on paired tumor-normal samples. For 52 B-other patients we compared WGS findings to data from clinical and research cytogenetics. WGS identifies a cancer associated event in 51/52 cases, this includes an established subtype defining genetic alteration in 5/52 that were previously missed by standard-of-care genetics. Of the 47 true B-other ALL we identified a recurrent driver in 87% (41).  Complex karyotype by cytogenetics emerges as a heterogeneous group, underlied by distinct genetic alterations associated with either favorable (DUX4-r) or poor outcomes (MEF2D-r, IGK::BCL2). For a subset of 31 cases, we integrate findings from RNA-sequencing (RNA-seq) analysis to include fusion gene detection, and classification by gene expression. Compared to RNA-seq, WGS was sufficient to detect and resolve recurrent genetic subtypes, however RNA-seq can provide orthogonal validation of findings. In conclusion, we demonstrate that WGS can identify clinically relevant genetic abnormalities missed by standard-of-care testing and identify leukemia driver events in virtually all cases of B-other ALL.

  Dataset EGAD00001009304

• Identifying Novel Small RNA Biomarkers Unique to Patients with Gastric Cancer

  The biomarker development study consisted of two parts: discovery and validation. The first part was the discovery and verification phase of biomarkers using two different platforms: transcriptomic and miRNA. The salivary transcriptomes of 63 GC samples and 31 non-GC controls were profiled using Affymetrix HG U133+2.0 microarrays (Affymetrix, Santa Clara, CA). The identified exRNA candidates were verified by quantitative real-time PCR (RT-qPCR) using all 94 of the original samples. In the discovery phase for the miRNA biomarkers, 10 early-stage GC samples and 10 non-GC controls were selected. The salivary miRNAs of these samples (n=20) were profiled using the TaqMan MicroRNA Array (Applied Biosystems, Foster City, CA). MicroRNA candidates were verified using TaqMan miRNA Assay (Thermo Scientific, Grand Island, NY). The second part of the study was to validate these verified exRNA biomarker candidates with exRNA samples extracted from an independent cohort of 100 GC and 100 non-GC saliva samples. The cohort was not balanced for demographics on gender and smoking history but more accurately reflected the diagnostic setting where our proposed final model could be implemented. Reprinted from "Li F, Yoshizawa MJ, Kim K, Kanjanapangka J, Grogan T, Wang X, Elashoff D, Ishikawa S, Chia D, Liao W, Akin D, Yan X, Lee M, Choi R, Kim S, Kang S, Bae J, Sohn T, Lee J, Choi M, Min B, Lee J, Kim J, Kim Y, Kim S, Wong D. (2018) Development and Validation of Salivary Extracellular RNA Biomarkers for Noninvasive Detection of Gastric Cancer. Clin Chem. PMID: 30097497 DOI: 10.1373/clinchem.2018.290569", with permission from American Association for Clinical Chemistry (United States).

  Study phs001767

• Oxford Nanopore RNA sequencing for HLA typing

  A targeted RNA-based method for typing of 12 classical HLA genes using Oxford Nanopore sequencing. In the method, were enriched HLA genes from cDNA of 50 individuals using gene-specific reverse primers. The library molecules were then barcoded, pooled into 2 separate gene pools, and sequenced on MinION R9.4 SpotON flow cells.

  Study EGAS00001004918

• Direct Detection of Early-stage Cancers Using Circulating Tumor DNA

  Early detection and intervention are likely to be the most effective means for reducing morbidity and mortality of human cancer. However, development of methods for noninvasive detection of early-stage tumors has remained a challenge. We have developed an approach called targeted error correction sequencing (TEC-Seq) that allows ultrasensitive direct evaluation of sequence changes in circulating cell-free DNA using massively parallel sequencing. We have used this approach to examine 58 cancer-related genes encompassing 81 kb. Analysis of plasma from 44 healthy individuals identified genomic changes related to clonal hematopoiesis in 16% of asymptomatic individuals but no alterations in driver genes related to solid cancers. Evaluation of 200 patients with colorectal, breast, lung, or ovarian cancer detected somatic mutations in the plasma of 71, 59, 59, and 68%, respectively, of patients with stage I or II disease. Analyses of mutations in the circulation revealed high concordance with alterations in the tumors of these patients. In patients with resectable colorectal cancers, higher amounts of preoperative circulating tumor DNA were associated with disease recurrence and decreased overall survival. These analyses provide a broadly applicable approach for noninvasive detection of early-stage tumors that may be useful for screening and management of patients with cancer.

  Study EGAS00001002577

• MDS-HSC-RNA-SEQ

  Dac EGAC00001000185

• utero-tubal lavage RNA seq DAC

  Dac EGAC00001002241

• GLASS-NL RNA-seq Data access committee

  Dac EGAC00001003470

• RNA sequencing in primary inflammatory (TPP) macrophages following deletion of a disease-associated gene desert at chr21q22, disruption of ETS2, or treatment of ETS2-edited macrophages with a HIF1α stabiliser.

  GWAS studies in five different inflammatory diseases have identified a strong genetic association at a gene desert at the chr21q22 locus. We have shown that this locus contains a monocyte/macrophage-specific enhancer that regulates ETS2 - a gene whose role in primary human monocytes/macrophages is incompletely understood. We therefore used a CRISPR-Cas9-based approach to delete the enhancer region or to disrupt ETS2, and performed RNA-sequencing to examine the transcriptional consequences. One effect of ETS2 disruption was upregulation of genes involved in aerobic respiration and oxidative phosphorylation. We therefore treated ETS2-edited inflammatory macrophages with roxadustat, a HIF1α stabiliser that can promote glycolysis via HIF1α-mediated metabolic reprogramming, and performed RNA-sequencing to determine whether this drug might rescue the transcriptional effects of ETS2 disruption.

  Study EGAS00001007553

• Tenk10k Phase 1: Whole Genome Sequencing

  TenK10K Phase 1 is a dataset of matched human whole-genome sequencing (WGS) from 1,925 individuals, and single-cell RNA sequencing (scRNA-seq) from over 5 million peripheral blood mononuclear cells across 28 immune cell types. Single-cell ATAC sequencing was additionally performed on a subset of 922 individuals. This EGA study consists of the WGS data from 1,925 individuals while a separate EGA study comprises the scRNA-seq and scATAC-seq data.

  Study EGAS50000001654

• Genome-Wide Association Studies in Upper Gastrointestinal Cancers (Asian)

  This project aims to conduct genome-wide association studies (GWAS) in two anatomically different upper gastrointestinal (UGI) cancer sites in two populations with distinctly different disease rates and genetic profiles. One population has very high rates for both esophageal squamous cell carcinomas (ESCCs) and gastric cancers (GCs) and is comprised of Asians (the "Asian UGI GWAS"), while the other population has low rates of ESCC and GC and includes non-Asians from the Americas, Europe, and Australia (the "Non-Asian UGI GWAS"). Study participants for the Asian UGI GWAS reported here (Illumina 660W Quad chip) were drawn from 2 studies, the Shanxi Upper Gastrointestinal Cancer Genetics Project (Shanxi) and the Linxian Nutrition Intervention Trial (NIT), a prospective cohort, and included a total of 1898 ESCCs, 1625 GCs, and 2100 controls. For the 2nd phase (8 TaqMan SNPs), additional subjects from Shanxi and NIT as well as subjects from the Shanghai Men's Health Study (SMHS), the Shanghai Women's Health Study (SWHS), and the Singapore Chinese Health Study (SCHS) were also included (217 ESCCs, 615 GCs, 1202 controls). Altogether 2115 ESCCs, 2240 GCs, and 3302 controls were genotyped in this study.

  Study phs000361

• Organoid BulkRNAseq

  Here, we aim to understand early determinants of brain organoid quality and generated a set of brain organoids from 12 different hPSC lines using an adaptation of the unguided Lancaster protocol (Lancaster & Knoblich, 2014). All cell lines were obtained from healthy donors. 12 donor hPSC lines were differentiated into brain organoids and a set of 72 individual organoids (6 per line) were randomly selected morphologically diverse organoids and subjected to bulk RNA sequencing for gene expression analysis. RNA was extracted using the RNeasy kit (Qiagen, Germany) according to the manufacturer’s instructions. A total of 1000 ng per sample was sent for RNA sequencing to Azenta Life Sciences (Genewiz Leipzig, Germany) for sequencing. Library preparation was performed using the NEBNext Ultra II RNA Library Prep Kit for Illumina following manufacturer’s instructions (NEB, Ipswich, MA, USA). mRNAs were first enriched with Oligo(dT) beads. The samples were sequenced using a 2x150 Pair-End (PE) configuration v1.5 at a depth of >20 million reads in each sample. Raw sequence data (.bcl files) generated from Illumina NovaSeq6000 was converted into fastq files and de-multiplexed using Illumina bcl2fastq program version 2.20. The raw sequence reads were aligned to the human reference genome GRCh38 using the STAR aligner (Dobin et al., 2013). Gene expression levels were quantified using the FeatureCounts tool (Liao et al., 2014).

  Study EGAS50000000659

• single-cell RNA-seq Case-Control study of children progressing to Type1 diabetes

  Single-cell RNA sequencing was carried out on four selected PBMC samples of Finnish children at risk of developing Type 1 diabetes and their gender age and HLA matched control children using 10X genomic platform. All four Case children were positive for multiple islet specific autoantibodies and two of them also progressed to clinical disease during the follow up whereas the control children remain negative for all autoantibodies. Age at seroconversion for Case 2, 3, 5, and 9 children is 12, 18, 24, and 18 months, respectively. Age at sampling, in months, for the pairs was as follows (Case/Control): pair 2:24/24; pair 3: 12/18; pair 5: 12/12; pair 9:24/18.

  Study EGAS00001004070

• Pathogenic Neurofibromatosis type 1 (NF1) RNA splicing resolved by targeted RNAseq

  Neurofibromatosis type 1 (NF1) is caused by loss-of-function variants in the NF1 gene. Approximately 10% of these variants affect RNA splicing and are either missed by conventional DNA diagnostics or are misinterpreted by in silico splicing predictions. Therefore, a targeted RNAseq-based approach was designed to detect pathogenic RNA splicing and associated pathogenic DNA variants. an in-house developed tool (QURNAS) was used to calculate the enrichment score (ERS) for each splicing event. RNA enrichment of NF1 and SPRED1 was done using SPET (NUGEN - NF1 only) and using SureSelect (Agilent - NF1 and SPRED1).

  Study EGAS00001005530

• RIP-seq of SF3B4 binding RNA fragments

  Project aims to characterize SF3B4 binding RNA fragments within liver organoids to understand its role in splicing regulation

  Study EGAS50000000850

• RNA-sequencing of adult T-cell leukemia/lymphoma sample

  This dataset includes 10 RNA-sequencing (RNA-seq) data for 9 primary tumors and 1 cell line from adult T-cell leukemia/lymphoma (ATL).

  Dataset EGAD00001004937

• Illumina RNA sequencing data

  RNA sequence data for HKCI-2, HKCI-C1, HKCI-C2, HKCI-C3 and MIHA. RNA-seq data of all the 5 samples were stored in compressed fastq format.

  Dataset EGAD00001004476

• DMET Genes, Nicotine Metabolism and Prospective Abstinence

  This study (DA033813; PI: Andrew W Bergen; PMID:26132489) includes samples from two laboratory studies of nicotine metabolism. The Pharmacokinetics of Nicotine Metabolism in Twins study (PKTWIN; PI: Gary E Swan; PMID: 15527659) was based on recruitment from a twin registry (PMID: 23084148). The Integrated Research Project on Tobacco Use and Dependence (IRP; PI: Gary E Swan; PMID: 14578134) was based on recruitment from a pedigree-based longitudinal study of risk factors for substance use, the Smoking in Families study (SMOFAM; DA03706; PI: Hy Hops). These two laboratory studies (PKTWIN and IRP/SMOFAM) served as the Stage I dataset to interrogate Drug Metabolizing Enzyme and Transporter genes with a targeted SNP array for association with the Nicotine Metabolite Ratio (NMR, ratio of trans-3'-hydroxycotinine and cotinine), an established biomarker of nicotine metabolism. In addition to the laboratory studies, samples from eight RCTs (PMID: 23249876) with the NMR and smoking-related measures used to test SNPs identified in Stage I (PMID: 26132489). In a third stage, a lung cancer meta-analysis database (PMID: 24880342) was used to assess association of SNPs identified in Stage II with lung cancer. The objectives of the study were to identify novel genes and SNPs contributing to nicotine metabolism (Stage I), and to validate PK SNPs associated with the NMR from individuals participating in a clinical laboratory protocol with the NMR obtained from treatment-seeking smokers, and then to investigate association with prospective smoking cessation (Stage II). This study built upon existing studies of nicotine metabolism and randomized trials of smoking cessation therapies. Enhanced knowledge of the genes influencing nicotine metabolism and prospective abstinence may help personalize smoking cessation treatment and risk assessment for smoking-related diseases. For Stage I, both subject [fixed-dose NMR, covariates (age, BMI, ethnicity, sex, smoking status, and hormone use), and pedigree relationships] and sample (common DMET SNP genotype, genotyping quality control) data are available in this accession. The analysis protocol, quality control summaries, summary genotype, summary phenotype, and analysis results are available for Stage I, II and III samples (PMID: 26132489). Extensive discussion of the prior CYP2A6 association literature with the NMR, abstinence, smoking heaviness and lung cancer risk is available (PMID: 26132489). The NMR has previously been associated with CYP2A6 activity, response to smoking cessation treatments, and cigarette consumption. We searched for drug metabolizing enzyme and transporter (DMET) gene variation associated with the NMR and prospective abstinence in 2,946 participants of laboratory studies of nicotine metabolism and of clinical trials of smoking cessation therapies. Stage I was a meta-analysis of the association of 507 common single nucleotide polymorphisms (SNPs) at 173 DMET genes with the NMR in 449 participants of two laboratory studies. Nominally significant associations were identified in ten genes after adjustment for intragenic SNPs; CYP2A6 and two CYP2A6 SNPs attained experiment-wide significance adjusted for correlated SNPs (CYP2A6 PACT=4.1E-7, rs4803381 PACT=4.5E-5, rs1137115, PACT=1.2E-3). Stage II was mega-regression analyses of 10 DMET SNPs with pretreatment NMR and prospective abstinence in up to 2,497 participants from eight trials. rs4803381 and rs1137115 SNPs were associated with pretreatment NMR at genome-wide significance. In post-hoc analyses of CYP2A6 SNPs, we observed nominally significant association with: abstinence in one pharmacotherapy arm; cigarette consumption among all trial participants; and lung cancer in four case:control studies. CYP2A6 minor alleles were associated with reduced NMR, CPD, and lung cancer risk. We confirmed the major role that CYP2A6 plays in nicotine metabolism, and made novel findings with respect to genome-wide significance and associations with CPD, abstinence and lung cancer risk. Additional multivariate analyses with patient variables and genetic modeling will improve prediction of nicotine metabolism, disease risk and smoking cessation treatment prognosis.

  Study phs000931

• Upcycling and merging data to challenge the dogma and identify new therapeutic targets for Glioblastoma

  Glioblastoma is the most common brain tumour. Characterised by a poor prognosis and its recurrence after multimodal treatments, the search for preventable risk factors has been mainly inconclusive up to date. Recently, the data merge from datasetsdeposited at the EGA allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. Challenges in glioblastoma research As for virtually all cancer types, many efforts have been made to unveil the molecular features responsible of the disease, and several cellular pathways have indeed been identified as being frequently mutated in glioblastoma. Nonetheless, targeted therapies based on identified genes have so far failed to improve outcome, thus survival mostly relies on a standard treatment unchanged since 2005. This is a frustrating situation for both the scientific and medical communities, and above all for the patients, still facing a dreadful path. Some researchers hypothesised that this may be due to the inability to efficiently target cancer stem cells, the originators of the other cell types, thus inducing cancer relapse. In 2019 Charles P. Couturier and colleagues sequenced RNA from single cells of freshly excised glioblastomas of 16 patients, and demonstrated that glioblastoma cells replicate normal brain cell development with a conserved neural cancer cell hierarchy centered around glial progenitor-like cells. In this way, they helped identify the possible target cells to improve efficacy and durability of treatment. Data upcycling at the EGA: the glioblastoma case study Single cell RNA sequencing is generated with a laborious and expensive protocol. The quality of the starting material is crucial (cells sample freshly extracted from the patients) and often several attempts are needed before producing reliable quality sequencing results. Collecting big numbers of patients is also challenging. The sequencing data produced by Kevin Petrecca’s group in Montreal, Canada and deposited at the EGA (EGAS00001004422) was recently upcycled by Lin Wang in San Francisco, California and pooled with their freshly produced ones, and then deposited at the EGA as Dataset EGAS00001004909 The data merge allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. They profiled 86 primary-recurrent patient-matched paired glioblastoma samples with single-nucleus RNA, among other techniques. These very comprehensive results lead the team to challenge the findings from several other cancer fields where chemotherapy standard chemo-radiation therapy selection pressure at the level of genomic alterations; this is indeed not the case for glioblastoma, where the pressure results in phenotypic transition between cellular states. Several technical controls were made to ensure that the merge of the data was not introducing a bias in the results, and an Inter-table analysis demonstrated nearly equal contribution to overall variance from each of the studies included, indicating that the findings were not due to inter-laboratory technical effect. A novel principal-component analysis showed that the largest contribution to variation in primary glioblastoma neoplastic cells was an axis between MES (mesenchymal) and proneural expression programs. In summary, treating glioblastoma often makes a MES, as commented by Lucy Stead about this remarkable work. Check Aaron Diaz’s team Nature Cancer paper, with strong technical tools, state of the art analysis and data from different sources converging to the same outcomes that made possible a significant step toward a better handling of a frightful cancer. References Couturier, C.P., Ayyadhury, S., Le, P.U. et al. Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. Nat Commun 11, 3406 (2020). Stead, L.F. Treating glioblastoma often makes a MES. Nat Cancer 3, 1446–1448 (2022). Wang, L., Jung, J., Babikir, H. et al. A single-cell atlas of glioblastoma evolution under therapy reveals cell-intrinsic and cell-extrinsic therapeutic targets. Nat Cancer 3, 1534–1552 (2022). Related links: Kevin Petrecca’s group dataset deposited at the EGA: EGAS00001004422 Lin Wang dataset deposited at the EGA: EGAS00001004909

  Blog upcycling-and-merging-data-to-challenge-glioblastoma

• RNA-seq of STIC lesions and adjacent normal samples

  In this study, we characterize premalignant lesions of the fallopian tube (serous tubal intraepithelial carcinomas) to explore the earliest events of tumorigenesis following mutation of the TP53 tumor suppressor gene. We conduct laser capture microdissection to isolate premalignant cells from adjacent normal cells, and subject isolated tissues to RNA-seq. Our findings reveal the earliest transcriptional changes established during premalignancy within the fallopian tube.

  Study EGAS50000000200

• Genetic Epidemiology of COPD (COPDGene) Funded by the National Heart, Lung, and Blood Institute

  Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project will establish a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,000 subjects will be recruited, including control smokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 or GOLD-Unclassified). This cohort will be used for cross-sectional analysis, although long-term longitudinal follow-up will be a future goal. The primary focus of the study will be genome-wide association analysis to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease. The initial phase of genome-wide association analysis included 500 COPD cases and 500 control subjects (all non-Hispanic White) genotyped with the Illumina Omni-1 chip. The second phase genotyped the entire study cohort using the Illumina Omni-Express chip. Unique aspects of the study include: 1) Inclusion of large numbers of African American subjects (approximately 1/3 of the cohort); 2) Obtaining chest CT scans (including inspiratory and expiratory images); and 3) Inclusion of the full range of disease severity. The COPDGene_v6 Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000179 COPDGene_v6 Cohort. phs000296 ESP LungGO COPDGene phs000765 COPDGene_Geno

  Study phs000179

• Genomic Analysis of Low Grade B-Cell Lymphoma

  We included tumors from 64 newly diagnosed or untreated Low Grade B-Cell Lymphoma (LGBCL) patients, consisting of SMZL (n = 48), NMZL (n = 6), EMZL (n = 2), LPL (n = 5), and B-NOS (n = 3) in this study. Samples were selected from cases consented to the Molecular Epidemiology Resource (MER) of the University of Iowa and Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE). RNA or DNA were extracted from 64 frozen LGBCLs tumors (with available matched germline DNA for N=61. For RNA sequencing, library preparation was done using the Illumina TruSeq RNA Exome Kit and sequenced with 100 nucleotide paired-end reads using the HiSeq 4000. For WES, library preparation was done using the Agilent SureSelect XT kit and sequenced with 100 nucleotide paired-end reads using the Illumina HiSeq 4000.

  Study phs002552

• RNA-seq data of HGG PDOX study

  Study EGAS00001004633

• Data Access Commitee Hidradenitis suppurativa RNA-Seq

  Dac EGAC00001002270

• Pheochromocytoma and paraganglioma single nuclei RNA-seq

  Dac EGAC00001002657

• COVID-19 RNA-seq Data Access Commitee

  Dac EGAC00001002979

• Gene expression analysis for nasal polyps

  The aim of the study is to identify the gene expression profile and biomarkers related with chronic rhinosinusitis with nasal polyps (CRSwNP). RNA-sequencing was performed to identify differentially expressed genes between nasal polyps (NP) and inferior turbinate mucosa from 6 patients with CRSwNP. We validated the RNA-seq results by quantitative real-time PCR.

  Study JGAS000153

• 10X single-cell Multiome (RNA+ATAC) and single-cell RNAseq of xenograft-derived HSPC, progenitors and myeloid progeny

  10X genomics chromium single-cell ATAC+RNA (Multiome) was use to prepare single-nucleus RNA- and ATAC-seq libraries for human HSPC sorted from xenografts recovered from inflammatory challenge. 10X genomics 3' kits were used to prepare single-cell RNA-seq libraries for committed progenitors and myeloid cells from the same xenografts. These were sequenced on an Illumina NovaSea 6000 platform; BAM files are provided. Samples from 3 conditions were sequenced for each cell type; 3 chromatin accessibility runs and 9 gene expression runs are provided.

  Dataset EGAD50000002328

• A Phase 2 Study of Lamivudine in Patients with p53 Mutant Metastatic Colorectal Cancer

  This was an open-label, single-arm Phase II study of lamivudine in patients who had progressed on systemic therapy for advanced colorectal cancer with TP53 mutations. The phase II study had a two-stage design, with a target accrual of 20 evaluable patients for the first stage and a total of 32 patients for the whole study. The first 9 patients were treated with lamivudine at 150 mg PO bid continuously for 28-day cycles. Subsequent patients (10-32) received a higher dose of 600 mg PO bid continuously for 28-day cycles. Tumor assessments were performed every 8 weeks until documented disease progression by Response Evaluation Criteria in Solid Tumors (RECIST) or drug intolerance. Whole genome sequencing (WGS) and total RNA-seq were performed on pre- and post- treatment biopsies on this trial.

  Study phs002833

• RNA sequencing

  For RNA sequencing: All sample numbers starting with 6717 are tumor samples which has been sequenced using transcriptomics (see BAM files). It concerns biopsies of metastatic lesions from patients with BRAFV600 mutated melanoma, obtained before, during and after the study treatment (see samples metadata). RNA sequencing is performed using the Illumina Novaseq 6000 system.

  Dataset EGAD50000000383

• WTS data of patients diagnosed with angiosarcoma

  Whole-transcriptome sequencing (WTS) of 6 tumor-normal and 6 tumor-only samples from patients diagnosed with angiosarcoma. Total RNA from snap frozen EITL tumor samples was extracted using TRIzol (Invitrogen) and purified with RNeasy Mini Kit (Qiagen) according to manufacturer’s instructions. The integrity of RNA was determined by electrophoresis using 2100 Bioanalyzer (Agilent Technologies). 500 ng of total RNA was reverse transcribed with iScript cDNA Synthesis Kit (Bio-Rad, Hercules, CA, USA). Quantification was performed using SsoFast EvaGreen Supermix and CFX96 Real-Time PCR System (both Bio-Rad). Sequencing libraries were prepared using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero (Illumina) and WTS was performed on HiSeq 2500 and HiSeq 3000 (Illumina) with 2x101 bp and 2x151 bp read length, respectively.

  Dataset EGAD00001005367

• WTS data of patients diagnosed with NKTL

  Whole-transcriptome sequencing (WTS) of 36 samples from patients diagnosed with NKTL. Total RNA from snap frozen EITL tumor samples was extracted using TRIzol (Invitrogen) and purified with RNeasy Mini Kit (Qiagen) according to manufacturer’s instructions. The integrity of RNA was determined by electrophoresis using 2100 Bioanalyzer (Agilent Technologies). 500 ng of total RNA was reverse transcribed with iScript cDNA Synthesis Kit (Bio-Rad, Hercules, CA, USA). Quantification was performed using SsoFast EvaGreen Supermix and CFX96 Real-Time PCR System (both Bio-Rad). Sequencing libraries were prepared using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero (Illumina) and WTS was performed on HiSeq 2500 and HiSeq 3000 (Illumina) with 2x101 bp and 2x151 bp read length, respectively.

  Dataset EGAD00001005230

• Clinical Sequencing Exploratory Research Consortium: Incorporation of Genomic Sequencing into Pediatric Cancer Care

  This project includes data derived from subjects enrolled in the BASIC3 (Baylor College of Medicine Advancing Sequencing in Childhood Cancer Care) study. BASIC3 is a National Genome Human Research Institute (NHGRI) and National Cancer Institute-funded Clinical Sequencing Exploratory Research (CSER) consortium project that focused on prospective implementation of clinical whole exome sequencing in the pediatric oncology clinic. The primary study objective were to integrate information from CLIA-certified germline and tumor exome sequencing into the care of newly diagnosed solid tumor patients at Texas Children's Cancer Center, and to perform parallel evaluation of the impact of tumor and germline exomes on families and physicians. Blood and frozen tumor (if available) samples were collected from children undergoing surgery or biopsy of newly diagnosed solid tumors and subjected to exome sequencing in a CLIA-certified laboratory. Germline and tumor (if applicable) exome sequencing reports were generated and submitted into the electronic health record and returned to each patient/family by their primary oncologist. In addition to the clinical exome sequencing, specific (optional) consent was requested for research sequencing studies. If this consent was obtained then research studies of some of the children and parents participating in the BASIC3 study (including tumor transcriptome and whole genome sequencing of blood and/or tumor) are performed. The Clinical Sequencing Exploratory Research Consortium 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-studies below or in the "Sub-study" section of this top-level study page phs001383 Clinical Sequencing Exploratory Research Consortium Cohort. phs001026 BASIC3 phs001878 GMKF BASIC3

  Study phs001683

• RNA sequencing of high-risk paediatric cancers for identifying T-cell infiltration signatures

  Transcriptome profiling of 121 high-risk paediatric cancer samples for identifying T-cell infiltration signatures using poly-A capture by Truseq and sequenced on NextSeq 500

  Dataset EGAD00001010920

• RNA-sequencing on thyroid samples from fetuses with Down syndrome and fetuses with no genetic/developmental abnormality

  The current data pertains RNA-sequencing reads obtained from thyroid samples acquired from fetuses with Down syndrome and fetuses with no genetic/developmental abnormality. Total RNA was isolated from left lobe from thyroid samples using a hand-held homogenizer and the Promega ReliaPrep RNA Miniprep System (Thermo Fisher Scientific). RNA yield was determined with the NanoDrop Microvolume Spectrophotometer (Thermo Fisher Scientific). Fragmentation and mRNA library preparation was performed using the Kapa mRNA Hyperprep Kit (Roche, Basel, Switzerland). Libraries were equimolar pooled and quality was checked on a TapeStation system using the DNA1000 ScreenTape (Agilent Technologies, Santa Clara, CA, USA). Libraries were sequenced with poly(A) selection to sequence all messenger RNA for gene expression analysis on the NovaSeq6000 PE150 (Illumina, San Diego, CA, USA), producing at least 40M 150-bp paired-end reads per library.

  Dataset EGAD50000000387

• RNA sequencing from patient-derived intestinal organoids

  uman duodenal tissues for establishing organoid cultures used in this study were sourced from de-identified surgical specimens (n = 3) of the duodenum obtained from patients who had undergone biopsy procedures unrelated to CeD at Tampere University Hospital. The protocol was approved by the Ethics Committee of Tampere University Hospital, Tampere, Finland (ETL code R18082). RNA from the duodenal organoids was isolated using an RNeasy Kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. RNA purity and concentration were measured using a NanoDrop One spectrophotometer (NanoDrop Technologies, Wilmington, Delaware, USA). Preparation of the RNA library and transcriptome sequencing was conducted by Novogene Co., LTD (Cambridge, UK). Messenger RNA was purified from total RNA using polyA selection and subjected to library construction. Sequencing was performed on an Illumina platform, and 150 bp paired-end reads were generated.

  Dataset EGAD50000000492

• Genentech gastric tumor sequencing

  Exome-seq, RNA-Seq, SNP array profiling of gastric tumor samples.

  Dataset EGAD00001000815

• Single-cell Analysis of Neoplastic Plasma Cells Identifies Myeloma Pathobiology Mediators and Potential Targets

  Multiple myeloma is a clonal plasma cell (PC) dyscrasia that arises from precursors and has been studied utilizing approaches focused on CD138+ cells. By combining single-cell (sc)RNA- with scB-cell receptor (BCR)-sequencing, we differentiate monoclonal/neoplastic from polyclonal/normal PCs, and find more dysregulated genes, especially in precursor patients, than by analyzing bulk PCs. To determine if this approach can identify oncogenes that contribute to disease pathobiology, MAD2L1 and MAT2A are validated as targets with drug-like molecules that suppress myeloma growth in pre-clinical models. Moreover, functional studies show a role of LAMP5, which is uniquely expressed in neoplastic PCs, in tumor progression and aggressiveness via interactions with c-MYC. Finally, a monoclonal antibody recognizing cell-surface LAMP5 shows efficacy as an antibody-drug conjugate and in a chimeric antigen receptor-guided T-cell format. These studies provide additional insights into myeloma biology and identify potential targeted therapeutic approaches that can be applied to reverse myeloma progression.

  Study EGAS50000000802

• Exploration of neuroblastoma xenograft models for tumor extracellular RNA profiling in murine blood plasma

  Total RNA sequencing (SMARTer Stranded Total RNA-Seq Kit v2) data of extracellular RNA (exRNA) from liquid biopsies of neuroblastoma xenograft models.

  Dataset EGAD00001010905

• PE-CGS: Optimizing Engagement of Hispanic Colorectal Cancer Patients in Cancer Genomic Characterization Studies

  Colorectal Cancer (CRC) is the second leading cause of cancer death in the US. Hispanic/Latinos (H/L) are the largest and fasting growing ethnic group in the US, and cancer is the leading cause of death among H/L in the US. Therefore, we need to fully understand the full complexity of the molecular etiology of cancer in this ethnic group. For instance, although incidence rates of CRC are lower among Latinos as compared to Whites or African Americans, Hispanics with metastatic disease have shorter overall survival when adjusted for health care setting, demographics, disease characteristics and treatment factors. H/L also tend to be diagnosed at a younger age and with higher stage, and we have previously reported that Mexican H/L in California have the greatest proportion of young (The Cancer Genome Atlas has provided a deep overview of the molecular taxonomy of CRC in 594 cases, however, less than 1% of the cases (n=5) were H/L. Therefore, it is imperative for us to take more detailed assessment of the molecular genomic landscape of CRC in H/L. One of the major issues likely limiting our ability to perform these large genomic initiatives in minority patients is that Patient or Participant Engagement practices may not be investigated to identify best practices for accruing and consenting patients into clinical translational biomedical research studies. This concept of Participant Engagement is critically important for both the patients and the translational cancer research community. Optimizing and improving our approaches for directly engaging patients at initial contact, throughout the course of a translational genomic study, and during the time of return of results is likely to lead to stronger relationships between the medical community and patients, but could also lead to significant improvement in outcomes for patients and for the cancer care community as a whole. As such, we propose the creation of the USC Center for Optimization of Participant Engagement in Cancer Characterization (COPECC) with a focus on optimizing the engagement of Latinos in CRC Genomic Characterization research studies. USC COPECC would serve as a member of the NCI U2C Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network. Our investigative team includes experts in all relevant areas of research for genomic characterization, participant engagement, and engagement optimization. We have an established platform for consenting patients into cancer genomics studies that will serve as a standard process. The overall goal of USC COPECC is to generate results on participant engagement optimization and CRC genomic research that will be shared with the broader community to distribute best practices for engaging Latinos in hopes of improving overall outcomes for CRC in this underserved population.

  Study phs003985

• single cell RNA-seq of peripheral blood from analysis in infants with MLL-rearranged Acute Lymphoblastic Leukemia

  This dataset contains two experiments. 1) Single cell RNA-seq of peripheral blood diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not), sequenced with SORT-seq (see cell systems, 2016, doi:10.1016/j.cels.2016.09.002). For some of the patients, multiple indipendent plates were produced (each plate is a sample). Barcode-well correspondence can be found here: https://bitbucket.org/princessmaximacenter/sharq/src/master/data/celseq2_bc384-v4.csv . 2) Single cell RNA-seq of peripheral blood diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not), sequenced with10x Genomics Version 2.

  Dataset EGAD00001007752

• Unraveling the transcriptomic profile of utero-tubal lavage fluid of ovarian cancer patients

  The majority of ovarian cancers are diagnosed at an advanced stage and have a high mortality rate. Current screening strategies fail to improve prognosis because markers of early stage disease are lacking. This medical need justifies the search for biomarkers enabling early detection of ovarian cancer. In this study, we explore the extracellular transcriptome of utero-tubal lavage fluid obtained from 26 ovarian cancer patients and 48 controls using messenger RNA (mRNA) capture and small RNA sequencing. Because of its contact with the fallopian tube and the ovaries, collection of utero-tubal lavage might be the preferred non-invasive method to identify localized lesions compared with analyses based on peripheral blood samples. We observed an enrichment of ovarian and fallopian tube specific messenger RNAs in utero-tubal lavage fluid compared to other human biofluids. Over 300 mRNAs and 41 miRNAs were upregulated in ovarian cancer samples compared with controls. Upregulated genes were enriched for genes involved in cell cycle activation and proliferation, hinting at a tumor derived signal. In conclusion, we provide proof-of-principle that mRNA capture sequencing of utero-tubal lavage fluid is technically feasible, and that the extracellular transcriptome of utero-tubal lavage should be further explored in larger cohorts to assess the diagnostic value of the biomarkers identified in this study.

  Study EGAS00001005498

• Dissecting intratumor heterogeneity of nodal B cell lymphoma on the transcriptional, genetic, and drug response level

  Tumor heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is well-known to affect the efficacy of anti-cancer, most personalized treatment approaches do not account for intratumor heterogeneity. We addressed this issue by studying the heterogeneity of lymph node-derived B cell non-Hodgkin lymphoma (B-NHL) by single cell RNA-sequencing (scRNA-seq) and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subclones and compared their drug response and genomic profiles. Malignant subclones of the same patient responded strikingly different to anti-cancer drugs ex vivo, which recapitulated subclone-specific drug sensitivity during in vivo treatment. Tumor infiltrating T cells represented the majority of non-malignant cells, whose gene expression signatures were similar across all donors, whereas the frequencies of T cell subsets varied significantly between the donors. Our data provide new insights into the heterogeneity of B-NHL and highlight the relevance of intratumor heterogeneity for personalized cancer therapies.

  Study EGAS00001004335

• Immunotesting cohort with RNA-seq data of melanoma samples

  This dataset contains RNA-seq raw data in fastq format from 9 melanoma samples. The samples are formalin-fixed paraffin-embedded (FFPE) treated. For target enrichment SureSelect XT Human All Exon V6 was used. The libraries were sequenced in paired-end mode (2 x 50 nt) on a NovaSeq6000 S2 flow cell.

  Dataset EGAD00001006783

• RNA-seq dataset of lung adenocarcinomas

  This dataset includes the RNA-seq data from a study entitled "Tracing Oncogene Rearrangements in the Mutational History of Lung Adenocarcinoma". PolyA tails were captured by Oligo-dT beads, and sequencing run was made in HiSeq 2500 machines. Paired-end FASTQ files are provided in our dataset.

  Dataset EGAD00001004794

• BLUEPRINT release August 2016, RNA-Seq for macrophage - T=6days untreated, on genome GRCh38

  RNA-Seq data for 4 macrophage - T=6days untreated sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002457

• He et al. RNA-seq data

  This dataset are the bam files of RNA-seq data from the paper by He et al.

  Dataset EGAD00001007135

• BLUEPRINT release August 2016, RNA-Seq for macrophage - T=6days LPS, on genome GRCh38

  RNA-Seq data for 4 macrophage - T=6days LPS sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002337

• Integrative multi-omic analyses of malignant pleural mesothelioma

  Multi-omic data (whole-genome sequencing, RNA-seq, EPIC 850K methylation arrays) for 123 samples from the MESOMICS project, the French project of molecular characterization of malignant pleural mesothelioma

  Study EGAS00001004812

• Chromatin landscape of medulloblastoma reveals context dependent driver

  In this study, we defined subgroup specific chromatin landscape (H3K27ac, H3K27me3, RNA-Seq, 27ac hichip, WGS) of medulloblastoma to identify pathogenic epigenetic alterations that regulate expression of a context dependent driver gene.

  Study EGAS00001006741

• RNA-Seq data for manuscript titled: Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy

  RNA-Seq data for manuscript titled: Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy

  Dataset EGAD00001008656

• RNA-seq on neuroblastoma PDX model COG-N-519 treated with control miR-1283 and test miR-99b-5p mimics

  RNA-sequencing on neuroblastoma PDX model COG-N-519 treated with control miR-1283 and test miR-99b-5p mimics. Three samples from each of the treatment condition were analysed. Next-Seq platform was used for sequencing.

  Dataset EGAD00001008035

• single-cell RNA-Seq samples of CRC patients

  The dataset contains samples of 11 CRC patients (2 samples for each patient, tumor and normal adjacent tissue site, 22 samples in total). Dataset is composed by fastq file (paired end) type from 10x single-cell RNA-Seq.

  Dataset EGAD00001009634

• BLUEPRINT release August 2016, RNA-Seq for macrophage - T=6days B-glucan, on genome GRCh38

  RNA-Seq data for 4 macrophage - T=6days B-glucan sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002522

• RNA-seq from PDAC samples

  Bam and fastq files from RNA-seq of PDAC samples used in the PCSI mismatch repair study

  Dataset EGAD00001006261

• snRNA-seq of subcortical MS

  Single-nuclei RNA-sequencing (snRNA-seq) from subcortical white matter controls and MS lesions, specifically chronic active (CA) and chronic inactive (CI), that paired with the spatial transcriptomics from the same samples, was used to identify spatial niches and key cell interactions driving inflammation and disease progression.

  Study EGAS50000000354

• Single-cell RNA-seq data of bronchoalveolar lavage fluid and extramedullary relapse of a multiple myeloma patient with sarcoidosis-like reactions after anti-BCMA CAR T-cell therapy

  We performed single-cell RNA-sequencing (scRNA-seq) of cells in the bronchoalveolar lavage (BAL) fluid at 3-month follow-up of a multiple myeloma patient experiencing sarcoidosis-like pulmonary reactions after anti-BCMA CAR T-cell therapy (Sample alias: A8_3, A9_3; technical replicates). In addition we performed scRNA-seq of a extramedullary relapse lesion at 6-month follow-up (Sample alias: B10_3).

  Dataset EGAD00001008649

• Tam-Seq of HGSOC samples for fixative comparison study

  Targeted amplicon sequencing of samples as part of the study "Methanol-based fixation is superior to buffered formalin for next-generation sequencing of DNA from clinical cancer samples. The amplicon panel consists of 48 amplicons in TP53, PTEN, EGFR, PIK3CA, KRAS and BRAF genes as described previously [Forshew, STM 2012]. All libraries were pooled and quantify using DNA 1000 kit on Agilent 2100 Bioanalyzer and KAPA SYBR FAST ABI Prism qPCR Kit (KAPA Biosystems) on 7900HT Fast Real-Time PCR System (Applied Biosystems) according to the supplier's recommendations. Reads were aligned using bwa-mem v0.7.12-r1039 to the 1000 genomes version of human genome build GRCh37, retaining duplicate reads.

  Dataset EGAD00001001937

• Genetic architecture of microRNA expression and its link to complex diseases in the Japanese population

  We mapped microRNA expression quantitative trait loci by quantifying microRNA expression using small RNA sequencing.

  Study JGAS000504

• Leiden University Medical Center Adipose tissue RNA-seq

  Dac EGAC00001000503

• Board considering access to BELOB RNA-seq data

  Dac EGAC00001001686

• RNA-seq data from 27 glioblastoma samples

  Study EGAS00001005807

• RNA-sequencing of Non-muscle Invasive Bladder cancer (NMIBC)

  This RNA-sequencing cohort includes 78 Non-muscle Invasive Bladder cancer (NMIBC) samples and 7 Muscle Invasive Bladder cancer (MIBC) samples.

  Study EGAS00001004358

• Genetic Studies of Homologous Recombination Deficiency in Hispanic Gastric Cancer

  Approximately 10% of gastric cancer cases show familial clustering and a hereditary cause is likely, however, only 1-3% cases result from known hereditary syndromes – which are predominantly associated with CDH1 and CTNNA1 genes. Hispanics are > 2 times more likely to be diagnosed and to die from gastric cancer compared to non-Hispanic whites. Not only does gastric cancer precision medicine lag behind other cancers – there is an urgent need to understand its etiology. Germline mutations in homologous recombination genes have been implicated as important risk factors for gastric cancer. The purpose of this study is to continue to generate knowledge to improve gastric cancer outcomes and disparities by 1) characterizing prevalence of germline mutations in homologous recombination genes and identify new genes associated with gastric cancer 2) perform molecular characterization of gastric tumors in Hispanic patients. Participants for germline analysis were enrolled from Chile, Colombia, Mexico, Portugal, Spain, Uruguay.Whole exome sequence capture was performed for all germline and somatic samples using Agilent SureSelect Human All Exon v7 Kit. All sequencing was performed on an Illumina NovaSeq 6000. Germline Analysis: Whole exome sequencing was performed on 536 Hispanic patients (290 males, 246 female)

  Study phs003251

• Single Cell ATAC-Seq of MELAS

  This dataset includes combined single Assay for Transposase-Accessible Chromatin, using sequencing (ATAC-seq), and mitochondrial DNA sequencing of peripheral blood mononuclear cells from three individuals with m.3243A>G associated MELAS (Mitochondrial Encephalopathy, Lactic Acidosis, and Stroke-like episodes).

  Study phs002217

• Blood Gene Signatures Associated with Stiffness After TKA

  In this study, we used PAXgene Blood RNA tubes collected from patients undergoing total knee arthroplasty (TKA) for osteoarthritis. Samples were collected with IRB approval and patient consent. We identified 8 patients with knee stiffness after TKA (cases) and 10 patients without post-TKA stiffness (controls). We isolated RNA from cases and controls for RNA-seq analyses, comparing samples collected the day of surgery and samples collected at 24 hours after surgery.

  Study phs002927

• Association studies using the Metabochip array - Samples analysed by the WTCCC (1958 British Birth Cohort (58BC), Hypertension cohort (HT), Type 2 Diabetes Cohort (T2D) and Coronary Artery Disease (CAD) cohort)

  Genomewide association studies (GWAS) have proven a powerful hypothesis-free method to identify common disease-associated variants. Even quite large GWAS, however, have only at best identified moderate proportions of the genetic variants contributing to disease heritability. To provide cost-effective genotyping of common and rare variants to map the remaining heritability and to fine-map established loci, the Metabochip Consortium has developed a 200,000 SNP chip that has been produced in very large numbers for a fraction of the cost of GWAS chips. This chip provides a powerful tool for genetic studies of metabolic, cardiovascular and anthropometric traits (Voight et al., in press PLoS Genetics).

  Study EGAS00000000115

• Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

  Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via "mapping" procedures to existing data. However, the manual interpretation required in the former case scales poorly to large datasets, which are also often prone to batch effects, while existing data for purified cell types must be available for the latter. Furthermore, unsupervised clustering can be error-prone, leading to under- and over- clustering of the cell types of interest. To overcome these issues we present CellAssign, a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined and de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while simultaneously controlling for batch and patient effects. We demonstrate the analytical advantages of CellAssign through extensive simulations and exemplify real-world utility to profile the spatial dynamics of high-grade serous ovarian cancer and the temporal dynamics of follicular lymphoma. Our analysis reveals subclonal malignant phenotypes and points towards an evolutionary interplay between immune and cancer cell populations with cancer cells escaping immune recognition.

  Study EGAS00001003452

• Human and rat skeletal muscle multi-omic profiling

  Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. Here, we optimize single-nucleus ATAC-seq (snATAC-seq) to map skeletal muscle cell-specific chromatin accessibility landscapes in frozen human and rat samples, and single-nucleus RNA-seq (snRNA-seq) to map cell-specific transcriptomes in human. We additionally perform multi-omics profiling (gene expression and chromatin accessibility) on human and rat muscle samples.

  Study EGAS00001005730

• fibroblast RNAseq from a GINS3 patient and two parents

  RNA-seq was performed from 3 separate GINS3 patient fibroblast cultures and 1 replicate of fibroblasts derived from each of the two parents. RNA-seq libraries were generated with NEBNext Ultra II Directional RNA library prep for Illumina with NEBNext Poly(A) mRNA Magnetic Isolation Module (New England Biolabs) and sequenced on Illumina NextSeq500 with paired-end 150 bp read length. SIRV Set 3 (Lexogen) spike-ins were added. Two fastq files are provided for each RNAseq sample.

  Dataset EGAD00001008571

• Analysis of T-cell receptor clonotypes in tumor micro-environment identifies shared cancer type-specific signatures

  Despite the conventional view that a truly random V(D)J recombination process should generate a highly diverse immune repertoire, emerging reports suggest that there is a certain bias towards the generation of shared/public immune receptor chains. These studies were performed in viral diseases where public T-cell receptors (TCR) appear to confer better protective responses. Selective pressures generating common TCR clonotypes are currently not well understood but it is believed that they confer a growth advantage. As very little is known about public TCR clonotypes in cancer, here we set out to determine the extent of shared TCR clonotypes in the intra-tumor microenvironments of virus- and non-virus- driven head and neck cancers using TCR sequencing. We report that tumor-infiltrating T-cell clonotypes were indeed shared across individuals with the same cancer type, where the majority of shared sequences were specific to the cancer type (ie viral versus non-viral). These shared clonotypes were not particularly enriched in EBV-associated nasopharynx cancer, but in both cancers, exhibited distinct characteristics, namely shorter CDR3 lengths, restricted V- and J-gene usages and also demonstrated convergent V(D)J recombination. Many of these shared TCRs were expressed in patients with a shared HLA background. Pattern recognition of CDR3 amino acid sequences revealed strong convergence to specific motifs that were unique to each cancer type, suggesting they may be enriched for specificity to common antigens found in the tumor microenvironment. The identification of shared TCRs in infiltrating tumor T-cells not only adds to our understanding of the tumor adaptive immune recognition but could also serve as disease-specific biomarkers and guide the development of future immunotherapies.

  Study EGAS00001005480

• WGBS data of solid liver tumor DNA, and WGBS data of cell-free DNA derived from human blood, for CancerDetector study

  The blood samples of four liver cancer patients and four healthy people, and the solid liver tumor samples of two liver cancer patients are collected for this dataset. Blood samples were centrifuged first at 1,600 × g for 10 minutes, and then the plasma was transferred into new micro tubes and centrifuged at 16,000 × g for another 10 minutes. The plasma was collected and stored at -80⁰C. CfDNA was extracted from 5 ml plasma using the Qiagen QIAamp Circulating Nucleic Acids Kit and quantified by Qubit 3.0 Fluoromter (Thermo Fisher Scientific). Bisulfite conversion of cfDNA was performed by using EZ-DNA-Methylation-GOLD kit (Zymo Research). After that, Accel-NGS Methy-Seq DNA library kit (Swift Bioscience) was used to prepare the sequencing libraries. The DNA libraries were then sequenced with 150bp paired-end reads.

  Dataset EGAD00001004317

• Single-cell omics data for COVID-19 patients

  Single-cell RNA-seq, single-cell ATAC-seq, and genotypes used in the analysis for the study "Altered and allele-specific open chromatin landscape reveal epigenetic and genetic regulators of innate immunity in COVID-19". The RNA-seq and ATAC-seq are raw data in FASTQ format while the genotypes are in the VCF format which was filtered and imputed (more details are available in the main text of the study).

  Dataset EGAD00001009331

• Single cell RNA-seq, TCR-seq and bulk TCR-seq on HNSCC patients treated with ICB

  We performed single cell RNA- and TCR-sequencing (10x Genomics) on immune infiltrates (CD45+ cells) from 18 HNSCC patients enrolled in the IMCISION trial (Vos et al. 2021). Viable immune cells were isolated from pre-treatment and post-treatment primary tumor biopsies of 10 patients responding (1 partial pathological response and 9 major pathological responses) and 7 patients non-responding to anti-PD-1 and anti-CTLA4 combination immunotherapy. One patient treated with anti-PD-1 monotherapy (1 major pathological response) was included in the dataset. Bulk TCR-seq was performed on the PBMCs of responding patients, pre- and post-treatment.

  Dataset EGAD00001011311

• RNA-Seq Pair End

  RNA analysis of two patients 11 and 15 with WGS done on Illumina HiSeq2000. For research purpose and authorised user only.

  Dataset EGAD00001003429

• Genomic Sequencing of Lung Adenocarcinoma

  Lung carcinoma is the leading cause of cancer death in the United States and world-wide; lung adenocarcinoma is the most common cause of lung cancer. Pilot studies of lung adenocarcinoma with hybrid-capture based whole exome sequencing will enable us to identify new targets for therapy and improve diagnosis. We will analyze a blend of whole exome and whole genome sequencing data as well as copy number and somatic mutation calls for 200 tumor and matched normal controls. When completed this study will represent the most comprehensive lung adenocarcinoma genome dataset to date.

  Study phs000488

• ALCHEMIST Study

  The ALCHEMIST study will accrue patients that are potentially eligible for the Intergroup adjuvant studies and perform central EGFR and ALK genotyping using a central reference laboratory certified by the Clinical Laboratory Improvement Amendments of 1988 (CLIA). Patients may either present prior to surgery with resectable NSCLC, may present following complete resection (before or after adjuvant chemotherapy). Eligibility is limited to those with NSCLC of a non-squamous histological subtype and those with adequate performance status and organ function for future trial eligibility. All subjects must submit tissue for central EGFR and ALK genotyping, as well as additional tissue for advanced genomics at the CCG. Subjects may have had local genotyping done prior to registration, however if these results shows no targetable EGFR or ALK alterations (or if it shows a KRAS mutation) then the patient will not be eligible for this screening protocol given the primary aim is to facilitate accrual to the adjuvant studies. All subjects will provide peripheral blood for matched normal DNA. All subjects (including those known to have EGFR or ALK alterations with local genotyping) will have formalin-fixed tissue collected for central genotyping. The testing will be performed at Response Genetics (Los Angeles, CA), a commercial CLIA-certified laboratory. ALK FISH will be performed using the Vysis break-apart probe and EGFR sequencing will be performed of exons 18-21. It is preferred that a full tumor block be submitted, but if unavailable, 15 unstained slides can be submitted. Genotyping results are expected to be provided to the treating clinician within 14 business days of submission so they can be used to determine eligibility for the randomized adjuvant studies, or to confirm the local results. Results will also be reported at intervals to the study team for update into the Alliance database. In addition to the commercial genotyping at Response Genetics, tissue will be collected for research genomics by CCG. For those patients with a block available, this will be forwarded to the CCG after clinical testing at Response Genetics. For patients without a block available, 15 unstained slides should be submitted to the CCG BCR for exploratory analysis. A peripheral blood specimen will also be collected and sent to the CCG BCR to use as matched normal. Specimens will be coded. Over the course of the study, the CCG will perform advanced genomic analysis of the resected lung cancer specimens in a research, non-CLIA environment. Following completion of the genomic analysis, the results can be matched with the clinical follow-up results using a link between the samples codes and the patient identifiers for correlative analyses. Subjects participating in the follow-up portion of the ALCHEMIST study, as well as those participating in the adjuvant therapeutic studies, are expected to undergo a standard-of-care diagnostic biopsy to confirm recurrence. At least two core biopsies, minimum, should be obtained as part of this recurrence biopsy. Paraffin embedded tissue from this biopsy will be used for confirmation of recurrence, for CLIA genomics to plan subsequent clinical trials, and for additional research genomics by the CCG. Plasma will additionally be collected at recurrence and sent to CCG for study of circulating free DNA (cfDNA). Data for the ALCHEMIST study is not yet available to be accessed by the public at this time; when ready it will be made available at the GDC Data Portal.

  Study phs001140

• DAC for RNA-Seq Transcriptomic CD4+ T data from EGAS00001004152

  Dac EGAC00001001462

• FIMM AML Single-Cell RNA-seq Data Access Committee

  Dac EGAC00001001709

• RNA-Seq of clonal endocrine therapy resistant cell lines

  Study EGAS00001007123

• Comparison of 133/144bp dominant phenotype vs 166bp dominant phenotype.

  Background: Previous studies found that cell-free DNA (cfDNA) generated from tumors was shorter than that from healthy cells, and selecting short cfDNA could enrich for tumor cfDNA and improve its usage in early cancer diagnosis and treatment monitoring; however, the underlying mechanism of shortened tumor cfDNA was still unknown, which potentially limits its further clinical application.Results: Using targeted sequencing of cfDNA in a large cohort of solid tumor patient, sequencing reads harboring tumor-specific somatic mutations were isolated to examine the exact size distribution of tumor cfDNA. For the majority of studied cases, 166bp remained as the peak size of tumor cfDNA, with tumor cfDNA showing an increased proportion of short fragments (100-150bp). Less than 1% of cfDNA samples were found to be peaked at 134/144bp and independent of tumor cfDNA purity. Using whole-genome sequencing of cfDNA, we discovered a positive correlation between cfDNA shortening and the magnitude of chromatin inaccessibility, as measured by transcription, DNase I hypersensitivity, and histone modifications. Tumor cfDNA shortening occurred simultaneously at both 5’ and 3’ ends of the DNA wrapped around nucleosomes. Conclusions: Tumor cfDNA shortening exhibited two distinctive modes. Tumor cfDNA purity and chromatin inaccessibility were contributing factors but insufficient to trigger a global transition from 166bp dominant to 134/144bp dominant phenotype.

  Study EGAS00001004135

• Inferring expressed genes by whole-genome sequencing of plasma DNA

  The analysis of cell-free DNA (cfDNA) in plasma represents a rapidly advancing field in medicine. cfDNA consists predominantly of nucleosome-protected DNA shed into the bloodstream by cells undergoing apoptosis. We performed whole-genome sequencing (WGS) of plasma DNA and identified two discrete regions at transcription start sites (TSS) where the nucleosome occupancy results in different read-depth coverage patterns in expressed and silent genes. By employing machine learning for gene classification we found that the plasma DNA read depth patterns from healthy donors reflected the expression signature of hematopoietic cells. In cancer patients with metastatic disease, we were able to classify expressed cancer driver genes in regions with somatic copy number gains with high accuracy. We could even determine the expressed isoform of genes with several TSSs as confirmed by RNA-Seq of the matching primary tumor. Our analyses provide functional information about the cells releasing their DNA into the circulation.

  Study EGAS00001001754

• Genomic Characterization CS-MATCH-0007 Arm B

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing, RNA sequencing and if possible, whole-genome, methylation and miRNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH clinical trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm B is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with HER2- activating mutations are treated with Afatinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002028

• Genomic Characterization CS-MATCH-0007 Arm Z1I

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm Z1I is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with BRCA1, BRCA2 mutations are treated with AZD1775. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002058

• PDAC Prognosis Biomarkers in Genomic and Transcriptomic Molecular Data

  Our study was designed to identify biomarkers related to the prognosis of Pancreatic Ductal AdenoCarcinoma (PDAC) patients using genomic variants and gene expression in coding regions of the human genome (exome). PDAC is the 7th cause of cancer deaths and is among types of cancer having the poorest prognosis. To improve treatment outcomes of PDAC, biomarkers related to PDAC prognosis are needed. The goals of our study are to find genomic and transcriptomic biomarkers, which can classify prognosis subtype of PDAC patients, and eventually to predict subtypes or prognosis for each patient. In this study, we generated Whole Exome Sequencing (WES) and exome capture RNA sequencing data of 450 tumor and matched normal samples from 150 PDAC patients. Our data may be useful for understanding genomic and transcriptomic features, prognosis prediction, and precision medicine for PDAC.

  Study phs002347

• Genomic Characterization CS-MATCH-0007 Arm Z1A

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm Z1A is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with NRAS mutations are treated with Binimetinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs001973

• Genomic Characterization CS-MATCH-0007 Arm W

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm W is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with FGFR fusions, mutations, amplifications are treated with AZD4547. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including tumor tissue and whole blood.

  Study phs001948

• Genomic Characterization CS-MATCH-0007 Arm S2

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm S2 is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with GNAQ or GNA11 mutations are treated with Trametinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002178

• Genomic Characterization CS-MATCH-0007 Arm R

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm R is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with BRAF fusions, non-V600K or non-V600E mutations, are treated with Trametinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002029

• Genomic Characterization CS-MATCH-0007 Arm S1

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm S1 is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with NF1 mutations are treated with Trametinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002153

• Genomic Characterization CS-MATCH-0007 Arm I

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm I is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with PIK3CA mutations (without KRAS Mutation or PTEN Loss) are treated with Taselisib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002181