Search Results - EGA European Genome-Phenome Archive

Whole genome sequencing of a breast cancer cohort with known functional homologous recombination status

Optimal patient selection for PARP inhibitors and double strand break (DSB) inducing chemotherapy is of great clinical importance. In principle, the use of these therapies can be extended beyond germline BRCA1/2 mutated cancers. Although several methods for detection of BRCA-like tumors have been developed, a golden standard is lacking. We have developed the RECAP test, a functional HR assay exploiting the formation of RAD51 foci in proliferating cells after ex vivo irradiation of fresh primary breast cancer (BrC) tissue. The RECAP test seems robust and has an advantage over genetic tests, due to its functional character for exploring the HR phenotype. Another type of HRD test is the BRCAness classifier, which is based on specific genomic patterns derived from copy number data of BRCA1/2 mutated BrCs that also occur in sporadic cancers. The BRCAness classifier is a robust test that is easily applicable in the clinic and has also been validated to predict in vivo response to high dose chemotherapy in clinical trials. More recently, a new HRD test based on genomic signatures which can be extracted from whole genome sequencing has been published, HRDetect. Studies comparing these different HRD tests within the same cohort of patients do not yet exist. Here, we have the unique opportunity to compare three HRD tests within the same cohort. We aim to compare three different HRD tests (RECAP, BRCAness classifier and HRDetect) within the same cohort of primary BrCs (n=41). As a secondary aim, we will analyze additional genetic alterations in HRD tumors (both BRCA-deficient and BRCA-proficient HRD tumors).

Study EGAS00001005572

Functional Mapping of AKT Signaling and Biomarkers of Response From the FAIRLANE Trial of Neoadjuvant Ipatasertib Plus Paclitaxel for Triple-Negative Breast Cancer

Purpose: Despite extensive genomic and transcriptomic profiling, it remains unknown how signaling pathways are differentially activated and how tumors are differentially sensitized to certain perturbations. Here, we aim to characterize AKT signaling activity and its association with other genomic or immunohistochemistry-based PI3K/AKT pathway biomarkers as well as the clinical activity of ipatasertib (AKT inhibitor) in the FAIRLANE trial. Experimental Design: In FAIRLANE, 151 patients with early triple-negative breast cancer were randomized 1:1 to receive paclitaxel with ipatasertib or placebo for 12 weeks prior to surgery. Adding ipatasertib did not increase pathologic complete response rate and numerically improved overall response rate by magnetic resonance imaging (MRI). We used reverse-phase protein microarrays (RPPA) to examine the total level and/or phosphorylation states of over 100 proteins in various signaling or cell processes including PI3K/AKT and mTOR signaling. 125 baseline and 127 on-treatment samples were evaluable by RPPA, with 110 paired samples at both time points. Results: Tumors with genomic/protein alterations in PIK3CA/AKT1/PTEN were associated with higher levels of AKT phosphorylation. In addition, phosphorylated(p)AKT levels exhibited a significant association with enriched clinical benefit of ipatasertib, and identified patients who received benefit in the absence of PIK3CA/AKT1/PTEN alterations. Ipatasertib treatment led to a down-regulation of AKT/mTORC1 signaling, which was more pronounced among the tumors with PIK3CA/AKT1/PTEN alterations or among the responders to the treatment. Conclusions: We showed that the high baseline pAKT levels are associated with the alterations of PI3K/AKT pathway components and enriched benefit of ipatasertib in TNBC.

Study EGAS00001005892

The University of Hong Kong Gastric Cancer Organoids RHO Signaling Study

Objective: Cell-cell (CC) and cell-matrix (CM) adhesions are essential for epithelial cell survival, yet dissociation-induced apoptosis is frequently circumvented in malignant cells. Design: We explored CC and CM dependence in 58 gastric cancer (GC) organoids by withdrawing either ROCK inhibitor, matrix, or both, to evaluate their tumorigenic potential in terms of apoptosis resistance, correlation with oncogenic driver mutations and clinical behaviour. We performed mechanistic studies to determine the role of diffuse-type GC drivers: ARHGAP fusions, RHOA, and CDH1, in modulating CC (CCi) or CM (CMi) adhesion independence. Results: 97% of the tumour organoids were CMi, 66% were CCi and 52% were resistant to double withdrawal (CCi/CMi), while normal organoids were neither CMi nor CCi. Clinically, the CCi/CMi phenotype was associated with an infiltrative tumour edge and advanced tumour stage. Moreover, the CCi/CMi transcriptome signature was associated with poor patient survival when applied to 3 public GC datasets. CCi/CMi and CCi phenotypes were enriched in diffuse-type GC organoids, especially in those with oncogenic driver perturbation of RHO signalling via RHOA mutation or ARHGAP fusions. Inducible knockout of ARHGAP fusions in CCi/CMi tumour organoids led to re-sensitization to CC/CM dissociation-induced apoptosis, upregulation of focal adhesion and tight junction genes, partial reversion to a more normal cystic phenotype, and inhibited xenograft formation. Normal gastric organoids engineered with CDH1 or RHOA mutations became CMi or CCi, respectively. Conclusions: The CCi/CMi phenotype has a critical role in malignant transformation and tumour progression, offering new mechanistic information on RHO-ROCK pathway inhibition that contributes to GC pathogenicity.

Study EGAS00001006252

Genome and gene analysis of gastrointestinal cancer and elucidation of its clinicopathological significance

<html>Cancer develops through the accumulation of genetic and epigenetic aberrations. To identify sequential molecular alterations that occur during the development of hepatocellular carcinoma (HCC), we molecularly compared 52 early and 108 overt HCC samples by genome sequencing. Gene mutations in the p53/RB1 pathway, WNT pathway, MLLs, SWI/SNF complexes, and AKT/PI3K pathway were common in HCC. In the early phase of all entities, TERT was the most frequently upregulated gene owing to diverse mechanisms. Despite frequent somatic mutations in driver genes, including CTNNB1 and TP53, early HCC was a separate molecular entity from overt HCC as each had a distinct expression profile. Notably, WNT target genes were not activated in early HCC, regardless of CTNNB1 mutation status, because ?-catenin did not translocate into the nucleus due to the E-Cadherin/?-catenin complex at the membrane. Conversely, WNT targets were definitively upregulated in overt HCC with CTNNB1 mutation associated with downregulation of CDH1 and hypomethylation of CpG islands in the target genes. Similarly, cell cycle genes downstream of the p53/RB pathway were upregulated only in overt HCC with TP53 and/or RB1 gene mutations associated with chromosomal deletion of 4q and/or 16q. Differing from the expression profile, HCC was epigenetically distinguished into four subclasses: normal-like methylation, global-hypomethylation (favorable prognosis), stem-like methylation (poor prognosis), and CpG island methylation. These methylation statuses were globally maintained through HCC progression. Taken together, additional molecular events besides driver gene mutations cooperatively contribute to transcriptional activation of downstream targets as HCC progresses, according to the methylation status of the associated genes.</html>

Study JGAS000233

Histone chaperone CHAF1A promotes proliferation and tumorigenicity in gastric cancer and impacts prognosis via context-depedent regulation of gene expression

The histone chaperone CHAF1A is associated with some tumors, but its mechanisms in tumor biology remain elusive. Gastric cancer (GC) has significant heterogeneity among patients, and novel prognostic markers and therapeutic targets may improve its outcomes. The role of CHAF1A in GC is unknown. In this study, we demonstrated that CHAF1A was overexpressed in GC tissues accompanied by low expression of wild-type P53 and high expression of the proliferation marker MKI67. In vitro, CHAF1A knockdown inhibited cell proliferation, induced cell cycle arrest and promoted apoptosis, while CHAF1A overexpression had contrary effects. In vivo, CHAF1A knockdown inhibited tumorigenicity of GC cells. A microarray assay with CHAF1A inhibition and a PathScan signaling antibody array with CHAF1A overexpression showed that CHAF1A inhibited the P53 pathway, activated stress response and induced glycolytic metabolism. In 665 patients, the expression level of CHAF1A protein was an independent predictor for overall survival and disease-free survival in non-cardia GC and also had survival associations in patients with small or perineural invasion-negative tumors. Tumor mRNA analyses based on next-generation sequencing in patients indicated that CHAF1A promoted the Warburg effect by depressing oxidative phosphorylation and increasing glycolysis. Furthermore, the heterogeneous clinical significance of CHAF1A among patient subgroups was associated with its differential regulation of gene expression involved with glycolysis and cell proliferation and survival, indicating that the role of CHAF1A is depended on patient characteristics. These results reveal critical roles and clinical values for CHAF1A in GC. CHAF1A may have context-dependent effects in GC, which increases understandings for GC heterogeneity.

Study EGAS00001003064

National Cancer Institute (NCI) Non-Hodgkin Lymphoma Genome-wide Association Study (GWAS)

Within the framework of the International Lymphoma Epidemiology Consortium (InterLymph) Consortium and NCI-sponsored Cohort Consortium, investigators from 22 studies came together to conduct a genome-wide association study (GWAS) of non-Hodgkin lymphoma (NHL). The goal of the study was to identify common genetic variants associated with the risk of NHL. As described previously (Berndt SI et al., Nature Genetics, 2013, PMID: 23770605 ), cases and controls from 22 studies, including nine prospective cohort studies, eight population-based case-control studies, and five clinic or hospital-based case-control studies were included in this effort. Cases of NHL were ascertained from cancer registries, clinics or hospitals, or through self-report verified by medical and pathology reports. The phenotype information for all NHL cases was reviewed centrally at the InterLymph Data Coordinating Center and harmonized according to the hierarchical classification proposed by the InterLymph Pathology Working Group based on the World Health Organization (WHO) classification (2008). Controls were frequency matched to cases on age and gender by study, and the study was limited to subjects of European ancestry. Participants were genotyped using the Illumina Omni Express. The NCI Non-Hodgkin Lymphoma GWAS is utilized in the following dbGaP sub-studies. To view genotypes 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 phs000801 NCI Non-Hodgkin Lymphoma GWAS. phs000802 NCI Non-Hodgkin Lymphoma GWAS: CLL phs000818 NCI Non-Hodgkin Lymphoma GWAS: Controls phs000889 NCI Non-Hodgkin Lymphoma GWAS: DLBCL phs000890 NCI Non-Hodgkin Lymphoma GWAS: FL phs000891 NCI Non-Hodgkin Lymphoma GWAS: MZL

Study phs000801

NHGRI GREGoR Consortium: Genomics Research to Elucidate the Genetics of Rare Disease

The NHGRI GREGoR (Genomics Research to Elucidate the Genetics of Rare Disease) Consortium was established in June 2021 with the goal of developing novel tools and approaches to advance the discovery of the genetic basis of rare conditions. Numerous types of molecular data are generated in GREGoR and available on the AnVIL cloud platform via dbGaP application, including short- and long-read genome and exome sequencing, transcriptomics, metabolomics, methylomics, and proteomics. De-identified clinical and demographic data is obtained, with a focus on standardized ontologies. The Consortium comprises five Research Centers (RCs - see below), a Data Coordinating Center (DCC), and various partner members and external collaborators. Baylor College of Medicine Research Center (BCM-GREGoR) The Baylor College of Medicine GREGoR program, which is part of the GREGoR consortium, enrolls individuals, families, and cohorts with suspected rare disease across a range of syndromic and non-syndromic phenotypes. Subjects are enrolled from national and international collaborating physician referrals. Subjects provide written informed consent for future re-contact. Data generated and shared include family structure, detailed phenotypes, exome or short-read genome data, and in some cases long-read genome or RNA-sequencing, and these are shared upon completion of standard quality control checks and annotation. Broad Institute (Broad) The Broad Center for Mendelian Genomics, part of the GREGoR consortium uses next-generation sequencing (exome, genome, transcriptome, and long read sequencing), computational approaches, and functional studies to discover the variants and genes that underlie Mendelian conditions with a particularly focus on neuromuscular, neurodevelopmental, and syndromic phenotypes. Samples come from collaborators and direct enrollment through the Rare Genomes Project and we are committed to rapid data sharing without an embargo period. Children's National Hospital / Invitae - Pediatric Mendelian Genomics (CNH/Invitae) The Pediatric Mendelian Genomics Research Center, a joint collaboration between Children's National Hospital Research Institute and Invitae, is part of the GREGoR consortium to discover disease-causing variants. Our center uses a combination of short-read and long-read next-generation sequencing technologies (genomes and transcriptomes), computational approaches, and protein-level functional modeling to discover novel gene-variant associations for Mendelian disease. Research participants, and often family members, were consented and enrolled directly into our research study. Most of our participants are single families with a wide range of likely genetic phenotypes including congenital malformations, neurodevelopmental features, or connective tissue differences who have had negative standard of care genetic testing such as panels or exomes. Several specific phenotype cohorts of interest include holoprosencephaly, leukodystrophies, cardiomyopathies, differences of sexual development, congenital renal disease, and epilepsy. De-identified clinical phenotype and sequence data are linked to all samples. GREGoR Stanford Site (GSS) The goal of the GREGoR Stanford Site (GSS) is to provide a platform for functional genomics research and validation to improve diagnosis in Mendelian disease. Participants included individuals with undiagnosed suspected Mendelian disease who had non-diagnostic exome sequencing and their immediate family members. Participants and their family members provided written, informed consent and biological samples from which DNA, RNA, plasma, fibroblasts, PBMCs and other cell types were generated and stored. Samples from research participants and their immediate family members may have undergone short and long-read genome sequencing, transcriptome sequencing, metabolomics and/or lipidomics profiling, methyl-capture-sequencing and ATAC-sequencing. De-identified clinical data extracted from participant medical records are linked to the samples. University of Washington Center for Rare Disease Research (UW-CRDR) The goals of the University of Washington Center for Rare Disease Research are to: (1) maximize novel gene discovery for Mendelian conditions by recruitment, short- and long-read whole genome sequencing, transcriptome sequencing and analysis of families with rare conditions for which the gene is either unknown or the gene is known but no pathogenic variant can be identified via clinical testing; (2) develop new strategies for gene discovery for Mendelian conditions caused by variants that are difficult to detect using conventional testing strategies, variants of unknown function effect (e.g., regulatory, structural variants) or have unusual modes of inheritance; and (3) implement high-throughput screening and targeted follow-up functional studies to prioritize and validate candidate non-coding variants. De-identified data and phenotypic information are shared via MyGene2, ClinVar, and AnViL.

Study phs003047

Genomic Data of Pediatric MDS

The dataset consists of - 126 whole exome sequencings (SAMD9/9Lmut: 64; GATA2mut 24, MDS wildtype 38/471) performed using SureSelect Human All Exon V6 enrichment (Agilent, cat# 5190-8863). The generated libraries were sequenced on the Illumina Hiseq 2500 with 150bp paired-end reads. FASTQ files were processed using SeqNext platform (JSI medical system, Germany), with gene-based alignment to a virtual panel of 300 genes (including 28 MDS-associated genes, SAMD9, and SAMD9L), consisting of genes relevant to bone marrow failure, MDS predisposition, and hematological cancers as per the Pan-Cancer studies with cohorts of >10,000 cancers. The respective BAM files are provided. - Custom panel targeting SAMD9, SAMD9L, and 22 single nucleotide polymorphisms (SNP) on chromosome 7q (allele frequency >35% in all ethnic sub-populations in gnomAD) (Ampliseq #IAD104171) were performed in 666/669 cases. And Custom panel targeting 28 MDS-associated genes (GATA2, RUNX1, HOXA9, CEBPA, GATA1, KRAS, NRAS, CBL, PTPN11, ASXL1, EZH2, SETBP1, FLT3, KIT, JAK2, JAK3, CSF3R, MPL, SH2, BCOR, BCORL1; RAD21, STAG2, CTCF, TP53, PTEN, CALR, VPS45) was performed in 544 cases (Ampliseq #IAD51150). Both custom panel libraries were prepared using NEBNext Ultra II DNA library prep kit (New England BioLabs, cat#E7645S/L) per manufacturer’s instruction and samples were sequenced on an Illumina Miseq 2000 with 2 x 150 bp reads. The respective BAM files are provided - 4 SAMD9/9L patients were subjected to MissionBio custom single-cell panel (CO-112) targeting 250 heterozygous gnomAD population polymorphisms on 7q arm and 69 amplicons in SAMD9/9L and other cancer genes. All libraries were sequenced on an Illumina NovaSeq6000 with 150 base-paired ending multiplexed runs. Fastq files were processed using the Tapestri Pipeline V2 and python-based Mosaic package (multi-omics analysis, data visualization). The derived BAM and loom files are provided.

Dataset EGAD00001007856

Whole-genome sequencing of gastric cancer 81 samples in the Japanese population.

Genomic DNA of 81 cases from Japanese gastric cancer was extracted from tumor and matched normal tissues, and libraries with an insert size of 350–550 bp were prepared. The libraries were sequenced on a HiSeq 2500 instrument (Illumina) with paired-end reads of 101 bp. The read data are stored as FASTQ formatted files.

Dataset EGAD00001008610

Somatic_mutation_profiling_of_intestinal_crypts_from_IBD

In this project we want to investigate the role that somatic mutations in intestinal stem cells play in IBD. We will use laser capture microdissection to ascertain epithelial cells from an individual crypts/vilus. We will extract DNA from these and use a new low-input material library prep methods to make accurate libraries for sequencing. In this pilot phase of the project we will perform 15X whole-genome sequencing of a small number of crypts biopsied from four patients. Biopsies have been taken from inflammed and noninflammed patches to compare mutation rates and mutational signatures. We will also test if crypts from inflammed patches of a single patient are clonal (either within a given inflammed patch or across inflammed patches). We will quantify the rate of cancer driver mutations in inflammed and non-inflammed crypts. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001002896

9296 results for "cancer rna-seq"

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