Search Results - EGA European Genome-Phenome Archive

Changes in alternative splicing and associated neo-antigens due to therapy

Recent studies have identified alternative splicing (AS) as a novel source of neoantigens for immunotherapy. Surprisingly little is known about the AS milieu in recurrent glioblastoma (GBM), despite this being the venue for most clinical trials. We profiled 29 primary-recurrent paired human GBM specimens via RNA sequencing and re-analyzed RNA-sequencing data from non-malignant human brain tissues. From these data, we reconstructed the landscape of AS in GBM through recurrence and contrasted that to isoforms observed in non-malignant brain. The AS events we identified were cross-referenced with single-cell GBM atlases to determine cell-type specific splicing patterns. From this we identified novel splicing events in cell-surface proteins that are suitable targets for engineered T-cell therapies. We found recurrent-specific isoforms of mitogen-activated kinase pathway genes which are expressed exclusively by GBM stem-like cells that enhance invasiveness. These studies shed light on the effect of therapy on AS and identify novel targets for emerging immunotherapies.

Study EGAS00001004524

Full blood mRNA sequencing of myotonic dystrophy type 1 patients after cognitive behavioural therapy

Myotonic dystrophy type 1 (DM1) is an incurable multisystem disease caused by a CTG-repeat expansion in the DM1 protein kinase (DMPK) gene. The OPTIMISTIC clinical trial demonstrated positive and heterogenous effects of cognitive behavioral therapy (CBT) on the capacity for activity and social participations in DM1 patients. Here, we performed mRNA sequencing of full blood for 27 patients of the OPTIMISTIC cohort before and after the CBT intervention. We identified 608 genes for which their expression was significantly associated with the disease causing CTG-repeat expansion, as well as with 1176 genes significantly associated with the average clinical response towards the intervention. Remarkably, all 97 genes significantly associated with both returned to more normal levels in patients who benefited most from CBT. This trend was consistent with the difference observed between DM1 patients and controls in an earlier study of blood mRNA expression levels, singling these genes out as candidate biomarkers for therapy response. Together these results highlight the ability to find disease relevant information in full blood of DM1 patients and open new avenues to monitor therapy effects.

Study EGAS00001005830

MECOM represses myeloid differentiation through CEBPA downregulation in AML

Transcription factor MECOM, located at 3q26, is essential for hematopoietic stem cells (HSCs) in healthy individuals. Enhancer translocations, due to 3q26 rearrangements, drive out-of-context MECOM expression in an aggressive subtype of leukemia (AML). Aberrantly expressed MECOM is essential for the survival and immature phenotype of these leukemia cells. Direct depletion of MECOM using an endogenous auxin-inducible degron rapidly upregulates expression of myeloid differentiation factor CEBPA. MECOM depletion is also accompanied by a severe loss of CD34 expression and gain of mature myeloid cell surface marker CD15. MECOM exerts its inhibitory effect on differentiation by binding to the +42kb CEBPA enhancer, which is essential for neutrophil development. This is partially dependent on the interaction between MECOM and its essential co-repressor CTBP2, a potential target in this type of AML. We demonstrate that CEBPA overexpression can bypass the MECOM-mediated block of differentiation. In addition, AML patients with MECOM overexpression through enhancer hijacking show significantly reduced CEBPA. Our study provides insight into the mechanism by which MECOM maintains the stem cell state in AML. Furthermore, CEBPA levels are an important read-out for successful targeting of MECOM in 3q26-rearranged AML.

Study EGAS00001008005

Robust detection of translocations in lymphoma FFPE samples using Targeted Locus Capture-based sequencing

Chromosomal translocations with immunoglobin (IG) loci are the classic drivers in a large subset of B-cell lymphomas. Detection of these translocations is important for confirmation of diagnosis and for prognosis and therapy decisions. Currently, molecular diagnosis of translocations in lymphomas is not addressed well by Next Generation Sequencing (NGS). The standard method for detection of translocations is Fluorescence In Situ Hybridization (FISH), which is labor-intensive, and can be difficult to interpret. There is a need for a robust technology that can be standardized. Targeted Locus Capture (TLC) selectively enriches and sequences entire genes based on the crosslinking of physically proximal sequences, and thereby enables complete sequencing of genes of interest, including detection of large structural variants. Because the technology is based on the crosslinking and fragmenting of DNA, it has particular advantages in the analysis of Formalin-Fixed, Paraffin-Embedded (FFPE) samples, in which DNA is inherently crosslinked and fragmented. In order to validate the FFPE-TLC technology as a novel approach for translocation detection in lymphoma samples, we have developed a panel assay containing genes with frequent translocations (MYC, BCL2, BCL6, IG loci). With this assay we have analyzed >140 lymphoma and control FFPE samples of variable input amounts and qualities that had previously been analyzed with FISH, and a subset also with standard targeted NGS. Good concordance with FISH results was observed for both translocation positive and negative samples. In 10 cases for which FFPE-TLC detected a relevant fusion and FISH had been called negative, discordance could be explained by higher sensitivity of FFPE-TLC or by inconclusive FISH results. In a specific case, FFPE-TLC detected a small-distance rearrangement on chromosome 3 that caused a BCL6 fusion but led to insufficient and therefore undetectable break-apart with FISH. Secondly, the FFPE-TLC approach was tested on a set of 19 B-cell lymphoma FFPE samples that had previously been analyzed using standard targeted NGS and FISH and was enriched for discordant results between these methods. FFPE-TLC-based NGS enables more robust translocation calling as the detection relies on broad sequencing coverage across the translocation partner rather than on breakpoint sequences only. In 3 cases, FFPE-TLC could proof false negative calls in standard targeted NGS due to breakpoints located in regions difficult to capture or to sequence. In 1 case, standard targeted NGS had made a false positive call on a breakpoint sequence that was shown to be caused by a small insertion rather than a genuine translocation. This study shows that FFPE-TLC promises to be a robust alternative for FISH analysis and standard targeted NGS procedures in lymphoma diagnostics and possibly in other cancers with frequent structural variants. The FFPE-TLC approach enables a single, DNA-based NGS test detecting both small mutations and translocations.

Study EGAS00001004760

Institut Curie Neuroblastoma Whole Genome Sequencing Diagnosis Relapse

Neuroblastoma, a clinically heterogeneous pediatric cancer, is characterized by distinct genomic profiles but few recurrent mutations. As neuroblastoma is expected to have high degree of genetic heterogeneity, study of neuroblastoma's clonal evolution with deep coverage whole-genome sequencing of diagnosis and relapse samples will lead to a better understanding of the molecular events associated with relapse. Samples were included in this study if sufficient DNA from constitutional, diagnosis and relapse tumors was available for WGS. Whole genome sequencing was performed on trios (constitutional, diagnose and relapse DNA) from eight patients using Illumina Hi-seq2500 leading to paired-ends (PE) 90x90 for 6 of them and 100x100 for two. Expected coverage for sample NB0175 100x100bp was 30X for tumor and constitutional samples. For the seven other patients expected coverage was 80X for tumor samples with PE 100x100, 100X in the other tumor samples and 50X for all constitutional samples (see table 1). Following alignment with BWA (Li et al., Oxford J, 2009 Jul) allowing up to 4% of mismatches, bam files were cleaned up according to the Genome Analysis Toolkit (GATK) recommendations (Van der Auwera et al., Current Protocols in Bioinformatics, 2013, picard-1.45, GenomeAnalysisTK-2.2-16). Variant calling was performed in parallel using 3 variant callers: GenomeAnalysisTK-2.2-16, Samtools-0.1.18 and MuTect-1.1.4 (McKenna et al., Genome Res, 2010; Li et al., Oxford J, 2009 Aug; Cibulskis et al., Nature, 2013). Annovar-v2012-10-23 with cosmic-v64 and dbsnp-v137 were used for the annotation and RefSeq for the structural annotation. For GATK and Samtools, single nucleotide variants (SNVs) with a quality under 30, a depth of coverage under 6 or with less than 2 reads supporting the variant were filter out. MuTect with parameters following GATK and Samtools thresholds have been used to filter our irrelevant variants. .SNVs within and around exons of coding genes overlapping splice sites.. Then,variants reported in more than 1% of the population in the 1000 genomes (1000gAprl_2012) or Exome Sequencing Project (ESP6500) have been discarded in order to filter polymorphisms. Finally, synonymous variants were filtered out. MuTect focuses on somatic by filtering with constitutional sample. Mpileup comparison between constitutional and somatic DNAs allowed us to focus also on tumor specific SNVs with GATK and Samtools. Finally, every SNV called by our pipeline and also supported in any constitutional samples were filtered our in order to prevent putative constitutional DNA coverage deficiency. Then we analyzed CNVs (copy number variants) with HMMcopy-v0.1.1 (Gavin et al., Genome Res, 2012) and control-FREEC-v6.7 (Boeva et al., Bioinformatics 2011) with a respective window of 2000bp and 1000 bp, and auto-correction of normal contamination of tumor samples for Control-FREEC. Finally we explored Structural variants (SVs) including deletions, inversions, tandem duplications and translocations using DELLY-v0.5.5 with standard parameters (Rausch et al., Oxford J, 2012). In tumors, at least 10 supporting reads were required to make a call and 5 supporting reads for the sample NB0175 with a coverage of only 40X (see table 2). To predict SVs in constitutional samples for subsequent somatic filtering, only 2 supporting reads were required in order not to miss one. To identify somatic events, all the SVs in each normal sample were first flanked by 500 bp in both directions and any SVs called in a tumor sample which was in the combined flanked regions of respective normal sample was removed (see graph 1). Deletions with more than 5 genes impacted or larger than 1Mb and inversions or tandem duplications covering more than 4 genes, were removed. We focused on exonic and splicing events for deletions, inversions, and tandem duplications. For translocation, we keep all SVs that occurred in intronic, exonic, 5'UTR, upstream or splicing regions. Bioinformatics detection of variations with Deep sequencing approach Once PE reads merged and adaptors trimmed by SeqPrep with default parameters, merged reads were aligned via the BWA (Li H. and Durbin R. 2009 PMID 19451168) allowing up to 1 differences in the 22-base-long seeds and reporting only unique alignments. Only reads having a mapping quality 20 or more have been further analysed. Variant calling software was not used, since we aimed to predict variations at low frequencies, observed in less than 1% of reads. Such variants require a custom approach. Using DepthOfCoverage functions of the Genome Analysis Toolkit (GATK) v2.13.2 (McKenna A, et al., 2010 Genome Research PMID: 20644199), we focused on high quality coverage of bases A, C, G and T at the targeted variant position. Depth of coverage of each base following a mapping quality higher than 20 and a base quality higher than 10 have been taken into account in order to focus only on high quality data. Aiming to determine the background level of variability at the studied regions, 10 control samples were included in the analysis. The same approach and filtering criteria have been applied as introduced above over the entire amplicons. In order to highlight variants, for each sample the frequencies of each bases at each amplicon position were then compared to those observed in the set of controls. Statistical analyses were performed with the R statistical software (http://www.R-project.org). Fisher’s exact two-sided tests with a Bonferroni correction were performed to compare percentages of bases between the data sets, i.e. for a given base between a case and the controls. Finally, significant variations were filtered-in once (i) a significant increase in the percentage of avariant base and (ii) a significant decrease in the percentage of it's reference base following our p.values criteria was observed (p.val < 0.05).

Dataset EGAD00001001356

Immune Checkpoint Blockade for Relapsed Hematologic Malignancy Post-HSCT

Relapse after allogeneic hematopoietic stem cell transplantation (HSCT) is characterized by poor outcomes and novel therapeutic options are urgently needed. Immune checkpoint blockade using CTLA-4 and PD-1 blocking antibodies are a potential concept for reinstating a dormant graft-versus-leukemia (Gvl) effect. This study investigated transcriptomic changes in biopsies obtained from patients who received immune checkpoint blockade for relapsed hematologic malignancy post-HSCT and elucidated transcriptional programs associated with successful reinvigoration of GvL. Differential gene expression analysis showed evidence of increased T cell infiltration in biopsies of responders to ipilimumab treatment and demonstrated shared gene programs between GvL and GvHD.

Study phs003291

Development of molecular targeted therapy for small cell lung cancer by comprehensive genome analysis

Aims: Identifying new therapeutic targets of small cell lung cancer (SCLC), genome-wide mutation analysis has been performed. Methods: Genomic DNA was extracted from formalin-fixed or methanol-fixed tissue samples. 71 Mb of DNA fragments containing whole coding exons were concentrated using SureSelect Human All Exon V4+UTRs Kit (Agilent Technologies) followed by 100-bp paired end sequencing by HiSeq 2000 (Illumina). Participants/Materials: 51 of 1042 cases of pathologically diagnosed small seen lung cancer that were registered to National Cancer Hospital East Lung Cancer Database in 1992-2012, and which surgically resected or biopsy samples were suitable for DNA extraction for further analyses.

Study JGAS000037

Genomic DNA analysis for malignant mesothelioma from the patients of Japan and USA.

Malignant mesotheliomas (MMs) are highly aggressive adult malignancies and exposure to asbestos is the major factor involved in MM pathogenesis. It is desirable for a better understanding of the molecular pathogenesis of MM will lead to more specific and effective targeted therapies. In addition it is reported that germline mutation in a specific gene (ex. BAP1) associates familial MMs, and new candidate markers to determine a subject?s predisposition to MM and for early detection need to be identified. Analysis of genomic DNA from MM tumors and reference peripheral blood from Japan and USA are ongoing to find the common genomic characters beyond race.

Study JGAS000108

Diversity of U1 small nuclear RNAs and Evaluation of Diagnostic Methods for their Mutations

U1 small nuclear RNA (snRNA) mutations are recurrent non-coding alterations found in various malignancies, including medulloblastoma, yet their identification has proven challenging due to their repetitive nature. To establish a robust DNA-based, and RNA-based method for detecting U1 snRNA mutations, we performed targeted DNA sequencing using our original gene panel for medulloblastoma and RNA-sequencing. As an RNA-based method, we developed a random forest classifier employing splicing patterns which were massively altered as a result of U1 snRNA mutations. By using both methods, we successfully detected U1 snRNA mutation in five DNA samples and four RNA samples.

Study EGAS50000000693

Exome array analysis of adverse reactions to fluoropyrimidine-based therapy for gastrointestinal cancer

Fluoropyrimidines, including 5-fluororacil (5FU) and its pro-drug Capecitabine, are the common treatment for colorectal, breast, neck and head cancers – either as monotherapy or in combination therapy. Adverse reactions (ADRs) to the treatment are common and often result in treatment discontinuation or dose reduction. Factors contributing to ADRs, including genetic variation, are poorly characterized. We performed exome array analysis to identify genetic variants that contribute to adverse reactions.Our final dataset consisted of 504 European ancestry individuals undergoing fluoropyrimidine-based therapy for gastrointestinal cancer. A subset of 254 of these were treated with Capecitabine. All individuals were genotyped on the Illumina HumanExome Array.

Study EGAS00001002763

Partner independent fusion gene detection by multiplexed CRISPR Cas9 enrichment and long read Nanopore sequencing (FUDGE)

Targeted long-read nanopore sequencing. Abstract: Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment. Fusion gene partner choice and breakpoint-position promiscuity restricts diagnostic detection, even for known and recurrent configurations. To accurately and impartially identify fusions, we developed FUDGE: FUsion Detection from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for fusion gene driver enrichment - without prior knowledge of fusion partner or breakpoint-location – to long-read Nanopore sequencing with the bioinformatics pipeline NanoFG. FUDGE has flexible target-loci choices and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in one sequencing run. We observe on-average 665 fold breakpoint-site enrichment and identify nucleotide resolution fusion breakpoints - within two days. The assay identifies cancer cell line and tumor sample fusions irrespective of partner gene or breakpoint-position. FUDGE is a rapid and versatile fusion detection assay, providing unparalleled opportunity for diagnostic pan-cancer fusion detection.

Dataset EGAD00001006111

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

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

Study phs000211

Molecular Etiology of Early-Onset Dystonia

Primary torsin dystonias (PTD) are a group of movement disorders characterized by twisting muscle contractures, where dystonia is the only clinical sign (except for tremor) and there is no evidence of neuronal degeneration or an acquired cause. Eleven genes have been mapped for primary dystonia including DYT1 (TOR1A), DYT2, DYT4 (TUBB4A), DYT6 (THAP1), DYT7, DYT13,, DYT17, DYT21, CIZ1, DYT24 (ANO3), and DYT25 (GNAL); however, only 3 genes (TOR1A, THAP1, and GNAL) have mutations in early onset dystonia patients. Each is inherited as an autosomal dominant trait but with reduced penetrance, meaning that individuals can carry the mutation but do not show clinical symptoms. The most common form of PTD is adult onset focal accounting for about 90% of all cases of dystonia with a prevalence estimated at 30/100,000 in the general population. A small percentage of focal cases are due to mutations in CIZ1, ANO3, THAP1, TUBB4A, and GNAL, but the vast majority is unaccounted for and is most likely multigenic or multifactorial. In this grant, focusing on early onset PTD, we will uncover genes that influence the penetrance of DYT1 (TOR1A) dystonia through GWAS and exome sequencing studies. We will identify other genes for early onset PTD using exome sequencing and determine whether variants within the identified early onset PTD genes or the pathways associated with these genes contribute to susceptibility in the most prevalent form of PTD, focal dystonia, using a case:control association study. The proposed research will identify novel PTD risk factors and genes, which in turn should reveal shared and intersecting pathways leading to a better understanding of the molecular basis of PTD and provide the underpinnings for developing new treatments. Additionally, insight into the factors that modulate disease penetrance would be a first step in determine whether these could be modified leading to a reduced incidence of the disease.

Study phs001733

Prediction of Trastuzumab Benefit in Adjuvant Breast Cancer: Gene Expression Profiling in NSABP B31

Background National Surgical Adjuvant Breast and Bowel Project (NSABP) trial B-31 suggested the efficacy of adjuvant trastuzumab, even in HER2-negative breast cancer. This finding prompted us to develop a predictive model for degree of benefit from trastuzumab using archived tumor blocks from B-31. Methods Case subjects with tumor blocks were randomly divided into discovery (n = 588) and confirmation cohorts (n = 991). A predictive model was built from the discovery cohort through gene expression profiling of 462 genes with nCounter assay. A predefined cut point for the predictive model was tested in the confirmation cohort. Gene-by-treatment interaction was tested with Cox models, and correlations between variables were assessed with Spearman correlation. Principal component analysis was performed on the final set of selected genes. All statistical tests were two-sided. Results Eight predictive genes associated with HER2 (ERBB2, c17orf37, GRB7) or ER (ESR1, NAT1, GATA3, CA12, IGF1R) were selected for model building. Three-dimensional subset treatment effect pattern plot using two principal components of these genes was used to identify a subset with no benefit from trastuzumab, characterized by intermediate-level ERBB2 and high-level ESR1 mRNA expression. In the confirmation set, the predefined cut points for this model classified patients into three subsets with differential benefit from trastuzumab with hazard ratios of 1.58 (95% confidence interval [CI] = 0.67 to 3.69; P = .29; n = 100), 0.60 (95% CI = 0.41 to 0.89; P = .01; n = 449), and 0.28 (95% CI = 0.20 to 0.41; P < .001; n = 442; P interaction between the model and trastuzumab < .001). Conclusions We developed a gene expression-based predictive model for degree of benefit from trastuzumab and demostrated that HER2-negative tumors belong to the moderate benefit group, thus providing justification for testing trastuzumab in HER2-negative patients (NSABP B-47). ** Reprinted from J Natl Cancer Inst;2013;105:1782-1788 with permission from Oxford University Press.

Study phs000826

A Genome-Wide Association Study of Lung Cancer Risk

Three genetic loci for lung cancer risk have been identified by genome-wide association studies (GWAS), but inherited susceptibility to specific histologic types of lung cancer is not well established. We conducted a GWAS of lung cancer and its major histologic types genotyping 515,922 single nucleotide polymorphisms (SNPs) in 5,739 incident lung cancer cases and 5,848 controls from one population-based case-control study and three cohort studies. Results were combined with summary data from 10 additional studies for a total of 13,300 cases and 19,666 controls of European descent. Four studies also provided histology data for replication resulting in 3,333 adenocarcinomas (AD), 2,589 squamous cell carcinomas (SQ), and 1,418 small cell carcinomas (SC). In analyses by histology, rs2736100 (TERT) on chromosome 5p15.33, was associated with risk of adenocarcinoma (OR=1.23, 95%CI=1.13-1.33, P=3.02x10-7), but not other histologic types (OR=1.01, P=0.84, and OR=1.00, P=0.93, for SQ and SC, respectively). This finding was confirmed in each replication study and overall meta-analysis (OR=1.24, 95%CI=1.17-1.31, P=3.74x10-14 for AD and OR=0.99, P=0.69 and OR=0.97, P=0.48, for SQ and SC, respectively). Other previously reported association signals on 15q25 and 6p21 were also refined, but no additional loci reached genome-wide significance. In conclusion, a lung cancer GWAS identified a distinct hereditary contribution to adenocarcinoma. Note: The lung study dataset to be released to dbGaP and caBIG excludes 47 individuals from the PLCO cohort who consented to participate only in cancer research projects and 22 individuals because of updated QC. Thus, the released dataset is derived from 11517 subjects, 5699 cases and 5818 controls. After the updated QC, the dataset to be released to dbGaP and caBIG includes 506062 SNPs.

Study phs000336

Next-Generation Sequencing of RNA and DNA Isolated from Paired Fresh-Frozen and Formalin-Fixed Paraffin-Embedded Samples of Human Cancer and Normal Tissue

Formalin-fixed, paraffin-embedded (FFPE) tissues are an invaluable resource for clinical research. However, nucleic acids extracted from FFPE tissues are fragmented and chemically modified making them challenging to use in molecular studies. We analysed 23 fresh-frozen (FF), 35 FFPE and 38 paired FF/FFPE specimens, representing six different human tissue types (bladder, prostate and colon carcinoma; liver and colon normal tissue; reactive tonsil) in order to examine the potential use of FFPE samples in next-generation sequencing (NGS) based retrospective and prospective clinical studies. Two methods for DNA and three methods for RNA extraction from FFPE tissues were compared and were found to affect nucleic acid quantity and quality. DNA and RNA from selected FFPE and paired FF/FFPE specimens were used for exome and transcriptome analysis. Preparations of DNA Exome-Seq libraries was more challenging (29.5 % success) than that of RNA-Seq libraries, presumably because of modifications to FFPE tissue-derived DNA. Libraries could still be prepared from RNA isolated from two-decade old FFPE tissues. Data were analysed using the CLC Bio Genomics Workbench and revealed systematic differences between FF and FFPE tissue-derived nucleic acid libraries. In spite of this, pairwise analysis of DNA Exome-Seq data showed concordance for 70-80 % of variants in FF and FFPE samples stored for fewer than three years. RNA-Seq data showed high correlation of expression profiles in FF/FFPE pairs (Pearson Correlations of 0.90 +/- 0.05), irrespective of storage time (up to 244 months) and tissue type. A common set of 1,494 genes was identified with expression profiles that were significantly different between paired FF and FFPE samples irrespective of tissue type. Our results are promising and suggest that NGS can be used to study FFPE specimens in both prospective and retrospective archive-based studies in which FF specimens are not available.

Study EGAS00001000737

Characterization of genetic intratumor heterogeneity in colorectal cancer and matching patient-derived spheroid cultures.

Patient-derived in vitro cultures of colorectal cancer (CRC) may help guide treatment strategies prior to patient treatment. However, most previous studies have been performed on a single biopsy per tumor. The purpose of this study was to analyze multiple spatially distinct biopsies from CRCs and see how well intratumor heterogeneity (ITH) was recapitulated in matching patient-derived spheroids. Three to five biopsies were collected from six CRC tumors. Each biopsy was split in two; one half was used for spheroid culturing, the other half was used for direct DNA and RNA purification. For two of the patients, lymph node metastases were analyzed. Somatic mutations were called from whole exome sequencing data. Each tumor contained multiple mutations shared across all biopsies and spheroids, including major CRC drivers such as APC, KRAS, and TP53. At the same time, all tumors exhibited ITH on both mutation and copy number level. The concordance between biopsies and spheroids ranged between 40-70% for coding mutations. For three of the patients the biopsy and spheroid from matching areas clustered together, meaning that the spheroid resembled the area of origin more than the other areas. However, all biopsies and spheroids contained private mutations. Thereby, multiple cultures from spatially distinct sites of the tumor increase the insight into the genetic profile of the entire tumor. RNA sequencing based molecular subtyping was stable and seemed independent of genetic ITH. In conclusion, all examined CRC tumors contained genetic ITH on mutation and copy number level. Spheroid cultures partly reflected this ITH, meaning that multiple cultures from distinct sites of the tumor improved the representation of the different genetic subclones in the primary tumor. This should be taken in to account when establishing patient-derived models for drug screening.

Study EGAS00001002684

Nala GSI GSAv3 PGx Study

Background: Microarrays are a well-established and widely adopted technology capable of interrogating hundreds of thousands of loci across the human genome. Combined with imputation to cover common variants not included in the chip design, they offer a cost-effective solution for large-scale genetic studies. Beyond research applications, this technology can be applied for testing pharmacogenomics, nutrigenetics, and complex disease risk prediction. However, establishing clinical reporting workflows requires a thorough evaluation of the assay's performance, which is achieved through validation studies. In this study, we performed pre-clinical validation of a genetic testing workflow based on the Illumina Global Screening Array for 25 pharmacogenomic-related genes. Methods: To evaluate the accuracy of our workflow, we conducted multiple pre-clinical validation studies. Here, we present the results of accuracy and precision assessments, involving a total of 73 cell lines. These assessments encompass reference materials from the Genome-In-A-Bottle (GIAB), the Genetic Testing Reference Material Coordination Program (GeT-RM) projects, as well as additional samples from the 1000 Genomes project (1KGP). We conducted an accuracy assessment of genotype calls for target loci in each indication against established truth sets. Results: In our per-sample analysis, we observed a mean analytical sensitivity of 99.39% and specificity 99.98%. We further assessed the accuracy of star-allele calls by relying on established diplotypes in the GeT-RM catalogue or calls made based on 1KGP genotyping. On average, we detected a diplotype concordance rate of 96.47% across 14 pharmacogenomic-related genes with star allele-calls. Lastly, we evaluated the reproducibility of our findings across replicates and observed 99.48% diplotype and 100 % phenotype inter-run concordance. Conclusion: Our comprehensive validation study demonstrates the robustness and reliability of the developed workflow, supporting its readiness for further development for applied testing.

Study EGAS00001007710

Proteomic Analysis of Non-Muscle Invasive and Muscle Invasive Bladder Cancer Highlights Distinct Subgroups With Metabolic, Matrisomal, and Immune Hallmarks

We present the proteome biology of bladder cancer based on a cohort comprising treatment-naïve non-muscle invasive (NMIBC, N=17) and treatment-naïve muscle-invasive bladder cancer (MIBC, N=51), as well as neoadjuvant-treated MIBC (N=11); using formalin-fixed, paraffin-embedded samples and data-independent acquisition yielding >8,000 protein identifications. The NMIBC proteome reveals two subgroups that represent cell adhesion or lipid metabolism biology. MIBC, compared to NMIBC, shows an altered metabolic proteome together with enrichment of extracellular matrix (ECM), immune response, and complement proteins; in line with three proteomic MIBC subgroups that represent ECM, metabolic, or immune signatures. The ECM and immune subgroups are enriched for markers of M2-like tumor-associated macrophages and dendritic cells, while markers for natural killer cells are exclusive for the ECM subgroup, and markers for cytotoxic T-cells are a hallmark of the immune subgroup. Infiltration of CD8+ PD1+ positive cytotoxic T cells correlated with PD-L1 expression of MIBC, as demonstrated by multiplex immunofluorescence analysis. The metabolic subgroup presents a comparably immune-depleted microenvironment. YAP1 signaling is particularly prominent in the ECM subgroup. The protein BSCL2 emerges as a prognostic marker for MIBC. We highlight increased endogenous proteolysis in MIBC alongside the upregulation of matrix metalloproteases exceeding the upregulation of their endogenous inhibitors. Genomic panel sequencing underlines prevalent FGFR3 mutations in NMIBC and prevalent TP53 mutations in MIBC, but a genomic underpinning of the MIBC subgroups remains elusive. Proteogenomic analysis yields protein-level evidence for more than 1,300 single amino acid variants. The proteomes of neoadjuvant-treated MIBC resembled treatment-naïve MIBC. Tumor-stroma interaction of MIBC was further investigated by proteomic analysis of patient-derived xenografts of MIBC. Our study adds to the proteome-level understanding of bladder cancer.

Study EGAS00001007290

DAC for EGA study: "ctDNA residual disease analyses during perioperative nivolumab or nivolumab plus ipilimumab in resectable diffuse pleural mesothelioma"

This DAC regulates access to the whole-exome sequence data for the study "ctDNA residual disease analyses during perioperative nivolumab or nivolumab plus ipilimumab in resectable diffuse pleural mesothelioma".

Dac EGAC50000000706

Genetic analysis in an inherited cardiac arrhythmia

To identify a causative gene for an inherited cardiac arrhythmia, exome sequence analysis was conducted in 6 patients and 5 controls.

Study JGAS000041

Clinical and ctDNA data for IMpassion031

Clinical and ctDNA data for IMpassion031, including survival, response, and ctDNA data from baseline through post-surgery time points. 222 samples run on Signatera assay. File type is csv.

Dataset EGAD50000001420

Central Africa whole genome sequencing (rainforest hunter-gatherers and neighboring populations)

High-coverage (>30X) whole genome data (FASTQ) for 29 central African rainforest hunter-gatherer individuals (from five populations) and for 20 central African rainforest hunter-gatherer neighbor individuals (from four populations).

Dataset EGAD50000001560

Framome cancer samples

Cancer samples for neo-open reading frame peptides that comprise the tumor framome are a rich source of neoantigens for cancer immunotherapy.

Dataset EGAD50000000420

vaccgene_1000G_MKK_hla

VaccGene HLA imputation panel variants and HLA allele calls for all individuals across all tested sequence platforms and countries, and the high quality direct genotypes for these individuals (with genotype data available) across the MHC in PLINK format

Dataset EGAD00010002577

GBM-ZEB1: RNA sequencing of parental tumors used for cell line generation

This dataset contains RNA sequencing raw data from four parental tumors that were used for classification of gene expression subtypes (Verhaak, Cancer Cell 2010) using ssGSEA.

Dataset EGAD00001001627

McGill EMC Release 4 for assay "ATAC-seq"

McGill EMC Release 4 for assay "ATAC-seq": Sequencing of transposase-accessible chromatin as described by Buenrostro et al. (Nature Methods 10, 1213?1218 (2013) doi:10.1038/nmeth.2688)

Dataset EGAD00001001300

BLUEPRINT: WGBS-seq for monocytes and neutrophils

WGBS-seq for monocytes and neutrophils

Dataset EGAD00001000673

WGS DATA FILES FOR SJPhLike

Dataset EGAD00001000976

Dataset for whole exome sequencing of 113 pairs of tumor and normal DNA samples along with 8 cell lines

Dataset for whole exome sequencing of 113 pairs of tumor and normal DNA samples along with 8 cell lines.

Dataset EGAD00001001006

ICGC Benchmark 1 (CLL)

Raw fastq files from WGS sequencing of CLL and matching blood normal for the ICGC Techval Benchmark1 study. Sequence data was provided to multiple centers for independent analysis and comparison.

Dataset EGAD00001001858

Utility of ctDNA to support patient selection for early phase clinical trials: The TARGET Study

The TARGET Study consists of 200 BAM files, for the 100 patients discussed in the publication. Each patient has a normal control BAM file and a ctDNA BAM file.

Dataset EGAD00001004796

Single Cell RNA Seq GBM

Single Cell RNA sequencing for 4 high grade glioma samples. NovaSeq6000 was used for snRNA Seq. The files uploaded are bam files created with grch38 reference.

Dataset EGAD00001005369

Single Cell RNA Seq LGG

Single Cell RNA sequencing for 5 low grade glioma samples. NovaSeq6000 was used for scRNA Seq. The files uploaded are bam files created with grch38 reference.

Dataset EGAD00001005368

WGS files for Mullighan_GL_reALL

WGS files for Mullighan_GL_reALL paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

Dataset EGAD00001005506

WXS files for Mullighan_GL_reALL

WXS files for Mullighan_GL_reALL paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

Dataset EGAD00001005509

Hospital for Sick Children 2020 Pediatric Low-Grade Glioma RNA and Targeted DNA Sequencing

Whole transcriptome and targeted dna sequencing (Ampliseq) of pediatric low-grade glioma samples at the Hospital for Sick Children

Dataset EGAD00001005987

sWGS for genome-wide copy number profiling

Shallow whole-genome sequencing (sWGS) data for the identification of somatic copy number alterations (SCNA) and the estimation of tumor fractions in plasma DNA of metastatic colorectal cancer patients (mCRC).

Dataset EGAD00001006384

RNA data for Glioblastoma (EGAS00001003953, H016)

RNA data for human glioblastoma patients, EGAS00001003953. 64 human samples, 2 cell lines (LN229, ZH487).

Dataset EGAD00001006547

RNA-seq data from paired tumour and germline samples from mesothelioma patients for study EGAS00001005196

Dataset EGAD00001007874

Hi-C for Junvenile Pilocytic Astrocytomas

5 Hi-C datasets (4 JPA and 1 LGG). Hi-C data for the remaining 5 JPAs used in our paper as well as all controls have been uploaded to EGA under EGAS00001005476.

Dataset EGAD00001009044

Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer

Dataset EGAD00001011123

Amplicon Sequencing for 'Early evolutionary branching across spatial domains predisposes to clonal replacement under chemotherapy in neuroblastoma'

BAMs from deep sequencing using a custom panel for the study 'Early evolutionary branching across spatial domains predisposes to clonal replacement under chemotherapy in neuroblastoma'

Dataset EGAD00001015012

WGS files for paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

WGS files for Klco paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

Dataset EGAD00001015490

WXS files for paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

WXS files for Klco paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

Dataset EGAD00001015491

RNASeq files for paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

RNASeq files for Klco paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

Dataset EGAD00001015492

MissionBio files for paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

MissionBio files for Klco paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

Dataset EGAD00001015493

Dataset for transcriptome sequencing of forebrain organoids from Lissencephaly patients

This dataset contains transcriptome sequencing for 16 samples of forebrain organoids from Lissencephaly patients. The sequencing was performed on Illumina NextSeq 6000 . The sequencing was always paired.

Dataset EGAD00001015688

Co culture scRNAseq PARSE

Fastq files are divided into 2 groups (WT and Mini). For alignment please use their respective loading table to run splitpipe from PARSE

Study EGAS50000001918

Center for Common Disease Genomics [CCDG] - Autoimmune: Inflammatory Bowel Disease (IBD) Exomes and Genomes

The National Human Genome Research Institute (NHGRI) has funded a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Called the Centers for Common Disease Genomics (CCDG), this initiative will explore a range of diseases with the ultimate goal of: undertaking variant discovery for enough different examples of disease architectures and study designs to better understand the general principles of the genomic architecture underlying common, complex inherited diseases; understanding how best to design rare variant studies for common disease; developing resources, informatics tools, and innovative approaches and technologies for multiple disease research communities and the wider biomedical research community. The initial focus of the CCDGs will be in cardiovascular disease (early-onset coronary artery disease, atrial fibrillation, hemorrhagic stroke), neuropsychiatric disease (epilepsy, autism), and autoimmune/inflammatory disease (type 1 diabetes, inflammatory bowel disease). The Broad Institute is one of four selected CCDG project centers. The overarching aim of the Inflammatory Bowel Disease (IBD) program is to define the full allelic spectrum of protein-altering variation in genes associated to IBD, and assess their role in both Crohn's Disease (CD) and Ulcerative Colitis (UC) risk. The whole genome sequencing data generated here is comprised of samples from US-based diverse populations including African American, Puerto-Rican, Caribean and Cuban origins.

Study phs001642

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