Project description:Genome-wide DNA methylation profiling of normal and lung adenocarcinoma fresh tissue samples. The Illumina Infinium MethylationEPIC BeadChip (850K) was used to obtain DNA methylation profiles across 860,000 CpGs in fresh tissue of lung adenocarcinoma and adjacent histological normal lung tissue samples. Samples included 30 paired tumor-normal driver gene-negative lung adenocarcinoma tissues and 35 paired tumor-normal EGFR-mutation positive lung adenocarcinoma tissues.
Project description:Ten arrays were performed on the RNA extracts from 10 patients' samples, each of them contained the paired samples tumor tissue/ normal adjacent tissue.
Project description:Purpose: Liver-specific MPC-knockout (Mpc1-/-, LivKO) mice develop less liver tumors than wild-type (Mpc1+/+) mice when given a DEN/CCl4 hepatocarcinogenesis protocol. The goals of this study are to compare transcriptome changes (RNA-seq) between liver tumor and normal-adjacent tissue in WT and Mpc1-/- mice. Methods: Total RNA was collected from tumor and paired normal-adjacent liver samples using the Qiagen miRNeasy kit. RNA from four samples each of wild-type tumor (WT-Tumor), paired wild-type normal-adjacent (WT normal adjacent), Mpc1-/- (MPC LivKO) tumor (MPC LivKO-Tumor), and paired MPC LivKO normal-adjacent (MPC LivKO normal adjacent) tissue was isolated. Each tumor and its paired normal-adjacent tissue were analyzed in a paired manner. Library preparation and sequencing were performed using the Illumina mRNA-Seq workflow. For data normalization, the raw number of reads for each transcript was converted to Fragments Per Kilobase of transcript per Million mapped reads (FPKM). FPKM values were log transformed, and unsupervised clustering was performed on samples based on normalized expression of genes with variation in Euclidean distance among samples of at least 2.5 standard deviations using Cluster 3 software. Results: Using an optimized data analysis workflow, we mapped about 50 million sequence reads per sample to the mouse genome (buildmm10) and identified 15,777 transcripts in the liver tissue samples of WT an Mpc1-/- (MPC LivKO) with Illumina workflow. FPKM values were log transformed, and unsupervised clustering was performed using Cluster 3 software. Unsupervised clustering analysis identified six gene expression groups: (1) increased gene expression in both WT and LivKO tumors, (2) increased gene expression in WT tumors, (3) increased gene expression in MPC LivKO tumors, (4) decreased gene expression down in both WT and LivKO tumors, (5) decreased gene expression in WT tumors, and (6) decreased gene expression in MPC LivKO tumors. Conclusions: Our study is the first on Mpc1-/- liver tumors. The HCC markers Alpha-fetoprotein (Afp) and Glypican-3 (Gpc3) were in the cluster of genes upregulated in both WT and MPC LivKO tumors. In the cluster of 14 genes up-regulated in only WT tumors were two GSTs: Gsta1 and Gstp2. In the cluster of 108 genes down-regulated in only MPC LivKO tumors were three GSTs: Gsta2, Gsta3, and Mgst1. That same cluster contained Gpx1, glutathione peroxidase (Gpx1). Thus, we concluded WT tumors increased but MPC LivKO tumors decreased expression of glutathione metabolizing genes.
Project description:Chronic inflammation promotes breast tumor growth and invasion by accelerating angiogenesis and tissue remodeling in the tumor microenvironment. The relationship between inflammation and estrogen, which drives the growth of 70 percent of breast tumors, is complex. Low levels of estrogen exposure stimulate macrophages and other inflammatory cell populations, but very high levels are immune suppressive. Breast tumor incidence is increased by obesity and age, which interact to influence inflammatory cell populations in normal breast tissue. The molecular impact of these factors on tumor initiation and growth is not well-understood. We modeled the difference in gene expression between 195 breast adenocarcinomas and 195 matched adjacent normal breast tissue samples, using age, body mass index (BMI), and tumor subtype as covariates. Age and BMI were independently associated with inflammation in normal tissue but not tumors. Older patients with ER-positive disease had tumors with higher levels of Estrogen Receptor (ER) signaling compared to adjacent normal tissue and had lower relative levels of tumor macrophage expression. We developed a novel statistic to quantify the rewiring of gene co-expression networks and demonstrate that in ER-positive tumors basal gene networks are rewired even though their expression levels of these genes are not significantly different from those in adjacent normal tissue. Patient age influences the molecular profile of ER-positive breast tumors. Our data support an immunosuppressive effect of estrogen signaling in the breast tumor microenvironment, suggesting this effect contributes to the greater presence of prognostic and therapeutically relevant immune cells in ER-negative tumors. 137 total samples: 43 mammaplastic reduction, 47 breast adenocarcinoma, 47 paired adjacent normal breast tissue
Project description:Chronic inflammation promotes breast tumor growth and invasion by accelerating angiogenesis and tissue remodeling in the tumor microenvironment. The relationship between inflammation and estrogen, which drives the growth of 70 percent of breast tumors, is complex. Low levels of estrogen exposure stimulate macrophages and other inflammatory cell populations, but very high levels are immune suppressive. Breast tumor incidence is increased by obesity and age, which interact to influence inflammatory cell populations in normal breast tissue. The molecular impact of these factors on tumor initiation and growth is not well-understood. We modeled the difference in gene expression between 195 breast adenocarcinomas and 195 matched adjacent normal breast tissue samples, using age, body mass index (BMI), and tumor subtype as covariates. Age and BMI were independently associated with inflammation in normal tissue but not tumors. Older patients with ER-positive disease had tumors with higher levels of Estrogen Receptor (ER) signaling compared to adjacent normal tissue and had lower relative levels of tumor macrophage expression. We developed a novel statistic to quantify the rewiring of gene co-expression networks and demonstrate that in ER-positive tumors basal gene networks are rewired even though their expression levels of these genes are not significantly different from those in adjacent normal tissue. Patient age influences the molecular profile of ER-positive breast tumors. Our data support an immunosuppressive effect of estrogen signaling in the breast tumor microenvironment, suggesting this effect contributes to the greater presence of prognostic and therapeutically relevant immune cells in ER-negative tumors. 296 total samples: 148 breast adenocarcinoma, 148 paired adjacent normal breast tissue
Project description:Genome wide DNA methylation profiling of paired adjacent and hepatocellular samples and 8 non-diseased liver samples. The Illumina Infinium 27k Human DNA methylation Beadchip v1.2 was used to obtain DNA methylation profiles across approximately 27,000 CpGs. Samples included 12 paired adjacent and 12 hepatocellular samples.
Project description:The main objective of the study was to identify potential diagnostic and follow up markers along with therapeutic targets for breast cancer. We performed gene expression studies using the microarray technology on 65 samples including 41 breast tumours [24 early stage, 17 locally advanced, 18 adjacent normal tissue [paired normal] and 6 apparently normal from breasts which had been operated for non-malignant conditions. All the samples had frozen section done – tumours needed to have 70% or more tumour cells; paired normal and apparently normal had to be morphologically normal with no tumour cells.