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: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: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:An FGF23-producing phosphaturic mesenchymal tumour was surgically resected. We performed small RNA sequencing to quantify the microRNAs/ small RNAs expression in the resulting library.
2017-09-22 | GSE97957 | GEO
Project description:Spatial transcriptomics of six surgically-resected human brain metastasis samples
2021-08-04 | GSE179572 | GEO
Project description:RNA-seq from human PDX derived from radiographically resectable pancreatic adenocarcinoma patients. All surgically resected tumors were obtained after written patient consent and according to the institutional review board-approved protocols of the University of Texas M.D. Anderson Cancer Center.
2021-09-06 | E-MTAB-10116 | biostudies-arrayexpress
Project description:Samples were taken from surgically resected tumor specimens/metastases from patients with colorectal cancer. The expression profiles were determined using the Affymetrix GeneChip Human Exon 1.0 ST Array version 2.
2017-09-24 | GSE90814 | GEO
Project description:Specimens were obtained from non-neoplastic colorectal mucosa for RNA ayalysis. Samples were obtained either from surgically resected specimens or during surveillance coloscopy. The expression profiles were determined using Affymetrix Human Genome U133 Plus 2.0 arrays.The correlation between mtDNA CNV and mitochondria-related gene expressions were investigated.
2017-07-12 | GSE74265 | GEO