Project description:Serous borderline tumours (SBOT) are a challenging group of ovarian tumours positioned between benign and malignant disease. We have profiled the DNA methylomes of 12 low grade serous carcinoma (LGSC), 19 SBOT and 16 benign serous tumours (BST) across 27,578 CpG sites to further characterise the epigenomic relationship between these subtypes of ovarian tumours. Unsupervised hierarchical clustering of DNA methylation levels showed that LGSC differ distinctly from BST, however, not from SBOT. Gene ontology analysis of genes showing differential methylation at linked CpG sites between LGSC and BST revealed significant enrichment of gene groups associated with cell adhesion, cell-cell signalling and the extracellular region consistent with a more invasive phenotype of LGSC as compared to BST. Consensus clustering highlighted differences between SBOT methylomes and returned subgroups with malignant-like or benign-like methylation profiles. Furthermore, a two loci DNA methylation signature can distinguish between these SBOT subgroups with benign-like and malignant-like methylation characteristics. Our findings indicate striking similarities between SBOT and LGSC methylomes which supports a common origin and the view that LGSC may arise from SBOT. A subgroup of SBOT can be classified into tumours with a benign-like or a malignant-like methylation profile which may help in identifying tumours more likely to progress into LGSC.
Project description:DNA methylation is increasingly used for tumour classification and has expanded upon the > 100 currently known brain tumour entities. A correct diagnosis is the basis for suitable treatment for patients with brain tumours, which is the leading cause of cancer-related death in children. DNA methylation profiling is required for diagnosis of certain tumours, and used clinically for paediatric brain tumours in several countries. We therefore evaluated if the methylation-based classification is robust in different locations of the same tumour, and determined how the methylation pattern changed over time to relapse.
Project description:Diagnosis of malignant pleural mesothelioma (MPM) is a challenging task because of its overlap with other neoplasms or even reactive conditions. Recently, DNA methylation analysis proved to be an effective tool for tumor diagnosis. We thus set out to test this approach for MPM diagnosis. A discovery (n=33) and an independent validation cohort (n=46) of MPM samples were subjected to array-based DNA methylation analyses and their DNA methylation patterns were compared to a representative set of both malignant and benign diagnostic mimics. By both unsupervised hierarchical clustering and t-distributed stochastic neighbor embedding analysis, MPM samples of the discovery cohort exhibited a distinct DNA methylation profile, different from that of other neoplastic and reactive mimics.
Project description:Serous borderline tumours (SBOT) are a challenging group of ovarian tumours positioned between benign and malignant disease. We have profiled the DNA methylomes of 12 low grade serous carcinoma (LGSC), 19 SBOT and 16 benign serous tumours (BST) across 27,578 CpG sites to further characterise the epigenomic relationship between these subtypes of ovarian tumours. Unsupervised hierarchical clustering of DNA methylation levels showed that LGSC differ distinctly from BST, however, not from SBOT. Gene ontology analysis of genes showing differential methylation at linked CpG sites between LGSC and BST revealed significant enrichment of gene groups associated with cell adhesion, cell-cell signalling and the extracellular region consistent with a more invasive phenotype of LGSC as compared to BST. Consensus clustering highlighted differences between SBOT methylomes and returned subgroups with malignant-like or benign-like methylation profiles. Furthermore, a two loci DNA methylation signature can distinguish between these SBOT subgroups with benign-like and malignant-like methylation characteristics. Our findings indicate striking similarities between SBOT and LGSC methylomes which supports a common origin and the view that LGSC may arise from SBOT. A subgroup of SBOT can be classified into tumours with a benign-like or a malignant-like methylation profile which may help in identifying tumours more likely to progress into LGSC. Array-based methylation profiling was performed using the Infinium HumanMethylation27 BeadChip in 12 low grade serous carcinoma, 19 serous borderline tumours and 16 benign serous tumours. The reproducibility of the Infinium HumanMethylation27 BeadChips was evaluated using four biological replicates of the high grade serous ovarian cancer cell line PEO1. Differential methylation cutoff was estimated from four biological replicates by bootstrap resampling and set at Δβ ≥ 0.25 corresponding to a FDR ≤ 0.09.
Project description:Non-diagnostic findings in Transbronchial Lung Biopsy (TBLB) and Endobronchial Ultrasound-guided Transbronchial Lung Biopsy (EBUS-TBLB) are not uncommon. A challenge is to improve lung cancer detection by TBLB/EBUS-TBLB. In order to improve the diagnostic yield of bronchoscopy, we used 850K methylation chip to identify methylation sites that distinguish malignant from benign lung nodules.We found that the combination of HOXA7, SHOX2,and SCT methylation analysis has the best diagnostic yield in 123 bronchial washing (sensitivity: 74·1%; AUC: 0·851) and 172 brushing samples (sensitivity: 86·1%; AUC: 0·915). We developed a kit comprising these three genes and validated the kit in 329 unique bronchial washing samples, 397 unique brushing samples, and 179 unique patients with both washing and brushing samples. The diagnostic accuracy of the panel alone in lung cancer diagnosis was 86·9%, 91·2% and 95% in bronchial washing, brushing, and washing+brushing samples, respectively. The panel's sensitivity in combination with cytology, rapid on-site evaluation (ROSE), and histology in lung cancer diagnosis was 90·8% and 95.8% in bronchial washing and brushing samples, respectively, and 100% in washing+brushing samples. Quantitative analysis of the three-gene panel improves lung cancer diagnosis by bronchoscopy.
Project description:Embryonal tumours of the central nervous system (CNS) represent a heterogeneous group of tumours about which little is known biologically, and whose diagnosis, on the basis of morphologic appearance alone, is controversial. Medulloblastomas, for example, are the most common malignant brain tumour of childhood, but their pathogenesis is unknown, their relationship to other embryonal CNS tumours is debated, and patients' response to therapy is difficult to predict. We approached these problems by developing a classification system based on DNA microarray gene expression data derived from 99 patient samples. Here we demonstrate that medulloblastomas are molecularly distinct from other brain tumours including primitive neuroectodermal tumours (PNETs), atypical teratoid/rhabdoid tumours (AT/RTs) and malignant gliomas. Previously unrecognized evidence supporting the derivation of medulloblastomas from cerebellar granule cells through activation of the Sonic Hedgehog (SHH) pathway was also revealed. We show further that the clinical outcome of children with medulloblastomas is highly predictable on the basis of the gene expression profiles of their tumours at diagnosis.
Project description:mRNA expression was assayed from bronchial epithelial cells collected via bronchoscopy and nasal epithelial cells collected by brushing the inferior turbinate from healthy current and never smoker volunteers in order to determine the relationship between smoking-related gene expression changes in bronchial and nasal epithelium within the same individual.
Project description:Embryonal tumours of the central nervous system (CNS) represent a heterogeneous group of tumours about which little is known biologically, and whose diagnosis, on the basis of morphologic appearance alone, is controversial. Medulloblastomas, for example, are the most common malignant brain tumour of childhood, but their pathogenesis is unknown, their relationship to other embryonal CNS tumours is debated, and patients' response to therapy is difficult to predict. We approached these problems by developing a classification system based on DNA microarray gene expression data derived from 99 patient samples. Here we demonstrate that medulloblastomas are molecularly distinct from other brain tumours including primitive neuroectodermal tumours (PNETs), atypical teratoid/rhabdoid tumours (AT/RTs) and malignant gliomas. Previously unrecognized evidence supporting the derivation of medulloblastomas from cerebellar granule cells through activation of the Sonic Hedgehog (SHH) pathway was also revealed. We show further that the clinical outcome of children with medulloblastomas is highly predictable on the basis of the gene expression profiles of their tumours at diagnosis. golub-00460 Assay Type: Gene Expression Provider: Affymetrix Array Designs: Hu6800 Organism: Homo sapiens (ncbitax) Material Types: synthetic_RNA, organism_part, whole_organism, total_RNA Disease States: synthetic_RNA, organism_part, whole_orMedulloblastoma, renal rhabdoid tumor, Atypical Teratoid/Rhabdoid Tumor, Supratentorial PNET, Supratentorial PNET (pineoblastoma), Normal, Malignant Glioma, Extrarenal Rhabdoid Tumorganism, total_RNA
Project description:mRNA expression was assayed from bronchial epithelial cells collected via bronchoscopy and nasal epithelial cells collected by brushing the inferior turbinate from healthy current and never smoker volunteers in order to determine the relationship between smoking-related gene expression changes in bronchial and nasal epithelium within the same individual. Bronchial epithelial cells were collected from current and never smokers via bronchoscopy, and nasal epithelial cells were collected by brushing the inferior turbinate during the same clinic visit. 1ug of RNA was isolated and hybridized to Affymetrix Human Exon 1.0 ST microarrays to obtain mRNA expression. The genome build upon which transcript assignments are based is hg18 (HuEx-1_0-st-v2.na27.hg18.transcript.csv).