Search Results - EGA European Genome-Phenome Archive

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

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

A Phase I Study With a Personalized Neoantigen Cancer Vaccine in Glioblastoma Multiforme

Neoantigens, which are derived from tumor-specific protein-coding gene mutations, are exempt from central tolerance, can generate robust immune responses and function as bona fide antigens that facilitate tumor rejection. A strategy of using multi-epitope and personalized neoantigen vaccination has previously been tested in patients with high-risk melanoma. We demonstrated that this strategy is feasible for glioblastoma (GBM) which typically has a relatively low mutation load and an immunologically 'cold' tumor microenvironment. We conducted whole exome sequencing (WES) of tumor and normal cells from individual GBM patients to identify tumor-specific mutations. We assessed the expression of mutated alleles by RNA-sequencing of tumor, and used personalized neoantigen-targeting vaccines to immunize newly diagnosed GBM patients following surgical resection and conventional radiotherapy in a phase I/Ib study. Patients who did not receive dexamethasone, a highly potent corticosteroid that is frequently prescribed to treat cerebral oedema in GBM patients, generated circulating polyfunctional neoantigen-specific CD4+ and CD8+ T cell responses that were enriched in a memory phenotype and showed an increase in the number of tumor-infiltrating T cells. Using single-cell T cell receptor analysis, we provided an evidence that neoantigen-specific T cells from the peripheral blood can migrate into an intracranial GBM tumor. Neoantigen-targeting vaccines thus have the potential to favorably alter the immune environment of GBM.In order to discover cancer antigens derived from annotated and unannotated protein-coding regions of the genome, we carried out matched ribosome profiling (Ribo-Seq) on two GBM samples. We discovered novel or unannotated open reading frames (nuORFs) and their expression levels as well as somatic mutations within the nuORFs, which could be used to predict potential neoantigens.

Study phs001519

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

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.

Study JGAS000233

Genomic platform specific polygenic risk scores impact breast cancer risk stratification

Background: At present, there is no consensus on which genotyping platform should serve as the standard for clinical polygenic risk score (PRS) implementation. Previous studies have compared the overall performance and concordance of different genotyping and sequencing technologies; however, these analyses have generally averaged the results over the whole genome. We evaluated differences in a 313-variant breast cancer PRS (PRS313) across genomic platforms and their impact on risk stratification. Methods: We compare PRS313 derived from genotyping arrays (Global Screening Array [GSA], OncoArray-500K [OncoArray], Global Diversity Array [GDA], custom Axiom_PrecipV1 array [ThermoFisher]) and low-coverage genome sequencing (lc-WGS) in 2 cell lines and 92 individuals. Probes are designed for all variants on ThermoFisher (success rate: 259/313). Sanger sequencing profiles indels. Concordance of high-risk classification (PRS313scoresum > 0.6) across platforms is assessed using Kappa statistics. Results: In saliva samples, indel concordance with Sanger sequencing varies widely (Kappa: 0.007-1.000). PRS313-ThermoFisher is predictable from other platforms using linear models, despite systematic differences. Greater agreement is observed between arrays with high imputation overlap (e.g., GDA ~ GSA slope=0.986). Agreement in high-risk classification before mean correction is moderate (Fleiss's Kappa=0.552) and improves after mean correction (Kappa=0.650). Arrays with similar designs show higher agreement before mean correction (Kappa=0.745). Mean correction narrows high-risk proportions from 4-45% to 15-21%. Overall, 26 of 92 samples are classified as high risk on at least one platform, but only 7 are high risk across all. When restricting to identical variants across all platforms for PRS313 calculation, the corresponding number of high-risk individuals are 24 and 11. Conclusion: Our findings demonstrate that platform-specific variability can influence PRS313 estimates to potentially reclassify individuals around clinically relevant thresholds.

Study EGAS00001008439

Circulating Tumor DNA in Checkpoint Inhibitor treated Lung Cancer

BackgroundImmune checkpoint inhibitors (ICI) are increasingly used to treat non-small cell lung cancer (NSCLC) and there is a critical need for novel predictive/prognostic biomarkers. We evaluated whether dynamics of circulating tumor (ctDNA) can identify NSCLC patients who benefit from single agent ICI.MethodsCirculating cell-free DNA (cfDNA) from 177 patients was analyzed prior ICI and at first treatment evaluation using a Commercial 77-gene panel. We performed de novo mutation calling and corrected for variants related clonal hematopoiesis. ctDNA changes were evaluated as predictors of tumor response estimated with PET/diagnostic CT and survival.ResultsMutations were detected in 159 of 174 (91.4%) analyzable patients. Most responders presented decreasing ctDNA levels, while non-responders had mixed molecular responses. Patients with a >50% molecular ctDNA decrease or no detectable ctDNA demonstrated improved PFS (5.9 versus 1.8 months; HR 0.49, 95%CI, 0.35-0.67, P < .001), and OS (18.9 versus 9.9 months; HR 0.41, 95%CI, 0.30-0.57, P < .001) compared to patients not achieving these endpoints. Clearance of mutations (and no detected ctDNA) had a similar effect (PFS HR 0.45, 95%CI, 0.32-0.61, P < .001; OS 0.37,95%CI, 0.27-0.52, P < .001) compared to patients having stable or additional mutations. After adjusting for clinical factors both >50% ctDNA decrease (HR 0.4, 95% CI, 0.3-0.6, P < .001) and clearance of mutations (HR 0.42, 95% CI, 0.3-0.6, P < .001) remained independent predictors for PFS and OS.ConclusionsctDNA testing reveals significant prognostic albeit not predictive information in ICI treated advanced NSCLC. This relevant information can be obtained with a commercial easy-to-implement ctDNA test that will facilitate extensive testing.

Study EGAS00001004847

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

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

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

Study EGAS50000001102

Enhancer profiling identifies epigenetic markers of endocrine resistance and reveals therapeutic options for metastatic castration-resistant prostate cancer patients (LuCaP cell line data)

Androgen Receptor (AR) signaling inhibitors, including enzalutamide, are treatment options for patients with metastatic castration-resistant prostate cancer (mCRPC), but resistance inevitably develops. Using metastatic samples from a prospective phase II clinical trial, we epigenetically profiled enhancer/promoter activities with H3K27ac chromatin immunoprecipitation followed by sequencing, before and after AR-targeted therapy. We identified a distinct subset of H3K27ac-differentially marked regions that associated with treatment responsiveness. These data were successfully validated in mCRPC patient-derived xenograft models (PDX). In silico analyses revealed HDAC3 as a critical factor that can drive resistance to hormonal interventions, which we validated in vitro. Critically, we identified the pan-HDAC inhibitor, vorinostat to be effective in decreasing tumor cell proliferation both in vitro and in vivo. Moreover, we uncovered evidence for HDAC3 working together with Glucocorticoid Receptor (GR) as a potential mechanism for this therapeutic effect. These findings demonstrate rationale for new therapeutic strategies including HDAC inhibitors to improve patient outcome in advanced stages of mCRPC. Project Goal: We identified H3K27ac regions associated with resistance in patient samples. Extensive analysis of these regions suggested that HDAC3 may play a role in resistance. To test this, we analyzed ChIP-seq and RNA-seq from cell lines generated from PDX LuCaP samples (recapitulating resistant and non-resistant) to validate findings in patient samples. ChIP-seq samples were used to verify the signals identified from specific factors, such as H3K27ac, AR, FOXA1, GR and HDAC3, their association with resistance and possible mechanisms of action. RNA-seq samples were analyzed to determine the effect of AR signaling in these samples in specific genes in the H3K27ac resistance-associated regions.

Study EGAS50000000917

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

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