Similar Datasets
Project description:We performed RNA-seq using 23 human surgically-resected gastric adenocarcinomas.
2022-01-31 | GSE152040 | GEO
Project description:We performed RNA-seq using 19 human surgically-resected lung adenocarcinomas to investigate of difference between EGFR-mutated and wild-type lung adenocarcinomas.
2020-02-25 | GSE141569 | GEO
Project description:PURPOSE: Non-small cell lung cancers (NSCLC) comprise multiple distinct biological groups with different prognoses. For example, patients with epithelial-like (EL) tumors have a better prognosis and exhibit greater sensitivity to inhibitors of the epidermal growth factor receptor (EGFR) pathway than patients with mesenchymal-like (ML) tumors. Here we test the hypothesis that EL NSCLCs can be distinguished from ML NSCLCs on the basis of global DNA methylation patterns. EXPERIMENTAL DESIGN: To determine whether phenotypic subsets of NSCLC can be defined based on their DNA methylation patterns, we combined microfluidics-based gene expression analysis and genome-wide methylation profiling. We derived robust classifiers for both gene expression and methylation in cell lines and tested these classifiers in surgically resected NSCLC tumors. We validate our approach using quantitative RT-PCR and methylation specific PCR in formalin-fixed biopsies from NSCLC patients who went on to fail front-line chemotherapy. RESULTS: We show that patterns of methylation divide NSCLCs into EL and ML subsets as defined by gene expression and that these signatures are similarly correlated in NSCLC cell lines and tumors. We identify multiple DMRs, including ERBB2 and ZEB2, whose methylation status is strongly associated with an epithelial phenotype in NSCLC cell lines, surgically resected tumors, and formalin-fixed biopsies from NSCLC patients who went on to fail front-line chemotherapy. CONCLUSIONS: Our data demonstrate that patterns of DNA methylation can divide NSCLCs into two phenotypically distinct subtypes of tumors and provide proof of principle that differences in DNA methylation can be used for predictive biomarker discovery and development. To determine whether phenotypic subsets of NSCLC can be defined based on their DNA methylation patterns, we combined microfluidics-based gene expression analysis and genome-wide methylation profiling. We derived robust classifiers for both gene expression and methylation in cell lines and tested these classifiers in surgically resected NSCLC tumors. We validate our approach using quantitative RT-PCR and methylation specific PCR in formalin-fixed biopsies from NSCLC patients who went on to fail front-line chemotherapy.
2012-03-03 | E-GEOD-36216 | biostudies-arrayexpress
Project description:The single-cell transcriptomes were performed from paired uninflamed and inflamed mucosal biopsies obtained from surgically resected colonic samples from 3 CD patients.
2024-09-01 | GSE236459 | GEO
Project description:PURPOSE: Non-small cell lung cancers (NSCLC) comprise multiple distinct biological groups with different prognoses. For example, patients with epithelial-like (EL) tumors have a better prognosis and exhibit greater sensitivity to inhibitors of the epidermal growth factor receptor (EGFR) pathway than patients with mesenchymal-like (ML) tumors. Here we test the hypothesis that EL NSCLCs can be distinguished from ML NSCLCs on the basis of global DNA methylation patterns. EXPERIMENTAL DESIGN: To determine whether phenotypic subsets of NSCLC can be defined based on their DNA methylation patterns, we combined microfluidics-based gene expression analysis and genome-wide methylation profiling. We derived robust classifiers for both gene expression and methylation in cell lines and tested these classifiers in surgically resected NSCLC tumors. We validate our approach using quantitative RT-PCR and methylation specific PCR in formalin-fixed biopsies from NSCLC patients who went on to fail front-line chemotherapy. RESULTS: We show that patterns of methylation divide NSCLCs into EL and ML subsets as defined by gene expression and that these signatures are similarly correlated in NSCLC cell lines and tumors. We identify multiple DMRs, including ERBB2 and ZEB2, whose methylation status is strongly associated with an epithelial phenotype in NSCLC cell lines, surgically resected tumors, and formalin-fixed biopsies from NSCLC patients who went on to fail front-line chemotherapy. CONCLUSIONS: Our data demonstrate that patterns of DNA methylation can divide NSCLCs into two phenotypically distinct subtypes of tumors and provide proof of principle that differences in DNA methylation can be used for predictive biomarker discovery and development.
2012-03-03 | GSE36216 | GEO
Project description:Altering cancer transcriptomes using epigenomic inhibitors [RNA-Seq]
2025-01-24 | E-GEOD-63776 | ExpressionAtlas
Project description:Transcriptome analysis of human brain microvascular endothelial cells response to Neisseria meningitidis and its antigen MafA using RNA-seq
2025-01-23 | E-MTAB-8008 | ExpressionAtlas
Project description:A chondroblastic osteosarcoma was surgically resected. We performed small RNA sequencing to quantify the microRNAs/ small RNAs expression in the resulting library.
2021-08-13 | GSE98014 | GEO
Project description:Transcriptome analysis of human brain microvascular endothelial cells response to Streptococcus pneumoniae and its antigen Adhesion lipoprotein using RNA-seq
2025-01-16 | E-MTAB-8054 | ExpressionAtlas
Project description:RNA-seq of coding RNA performed on the root tips of Arabidopsis rtel1 mutants and Col-1
2016-10-17 | E-MTAB-2943 | ExpressionAtlas