Project description:Chronic obstructive pulmonary disease (COPD) is an inflammatory lung disorder characterized by the progressive obstruction of airflow and is currently the fourth leading cause of death in the world. The pathogenesis of COPD is thought to involve bacterial infections and inflammations. Owing to advancement in sequencing technology, evidence is emerging that supports an association between the lung microbiome and COPD. However, few studies have looked into the expression profile of the bacterial communities in the COPD lungs. In this study, we analyzed the sputum microbiome of four moderate and four severe COPD male patients both at the DNA and RNA level, using next generation sequencing technology. We found that bacterial composition determined by 16S rRNA gene sequencing may not directly translate to the set of actively expressing bacteria as defined by transcriptome sequencing. The two sequencing data agreed on Prevotella, Rothia, Neisseria, Porphyromonas, Veillonella, Fusobacterium and Streptococcus being among the most differentially abundant genera between the moderate and severe COPD samples, supporting their association with COPD severity. However, the two sequencing analyses disagreed on the relative abundance of these bacteria in the two COPD groups, implicating the importance of studying the actively expressing bacteria for enriching our understanding of COPD. Though we have described the metatranscriptome profiles of the lung microbiome in moderate and severe COPD, further investigations are required to determine the functional basis underlying the relationship between the microbial species in the lungs and pathogenesis of COPD.
Project description:The interplay between copy number variation (CNV) and differential gene expression may be able to shed light on molecular process underlying breast cancer and lead to the discovery of cancer-related genes. In the current study, genes concurrently identified in array comparative genomic hybridization (CGH) and gene expression microarrays were used to derive gene signatures for Han Chinese breast cancers. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival. Distributions of signature genes were strongly associated with chromosomal location: chromosome 16 for ER and 17 for HER2. A breast cancer risk predictive model was built based on the first supervised principal component from 16 genes (RCAN3, MCOLN2, DENND2D, RWDD3, ZMYM6, CAPZA1, GPR18, WARS2, TRIM45, SCRN1, CSNK1E, HBXIP, CSDE1, MRPL20, IKZF1, and COL20A1), and distinct survival patterns were observed between the high- and low-risk groups from the combined dataset of 408 microarrays. The risk score was significantly higher in breast cancer patients with recurrence, metastasis, or mortality than in relapse-free individuals (0.241 versus 0, P<0.001). The concurrent gene risk predictive model remained discriminative across distinct clinical ER and HER2 statuses in subgroup analysis. We conclude that parallel analysis of CGH and microarray data, in conjunction with known gene expression patterns, can be used to identify biomarkers with prognostic values in breast cancer. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival.
Project description:The interplay between copy number variation (CNV) and differential gene expression may be able to shed light on molecular process underlying breast cancer and lead to the discovery of cancer-related genes. In the current study, genes concurrently identified in array comparative genomic hybridization (CGH) and gene expression microarrays were used to derive gene signatures for Han Chinese breast cancers. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival. Distributions of signature genes were strongly associated with chromosomal location: chromosome 16 for ER and 17 for HER2. A breast cancer risk predictive model was built based on the first supervised principal component from 16 genes (RCAN3, MCOLN2, DENND2D, RWDD3, ZMYM6, CAPZA1, GPR18, WARS2, TRIM45, SCRN1, CSNK1E, HBXIP, CSDE1, MRPL20, IKZF1, and COL20A1), and distinct survival patterns were observed between the high- and low-risk groups from the combined dataset of 408 microarrays. The risk score was significantly higher in breast cancer patients with recurrence, metastasis, or mortality than in relapse-free individuals (0.241 versus 0, P<0.001). The concurrent gene risk predictive model remained discriminative across distinct clinical ER and HER2 statuses in subgroup analysis. We conclude that parallel analysis of CGH and microarray data, in conjunction with known gene expression patterns, can be used to identify biomarkers with prognostic values in breast cancer. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival.
Project description:Affymetrix SNP array analysis was performed on DNA extracted from whole blood samples of 7 Taiwanese patients with hyperlipidemia. Three copy number variant (CNV) regions associated significantly with hyperlipidemia were identified through genomic segmentation analysis (P<0.001). 7 male Taiwanese hyperlipidemia patients.
Project description:'Precision medicine' is a concept that by utilizing modern molecular diagnostics, an effective therapy is accurately applied for each cancer patient to improve their survival rates. The aim of this study was to compare the molecular subtypes of triple negative breast cancer (TNBC) between Taiwanese and other datasets.
Project description:Han:SPRD rats carry a missense mutation in Anks6 (also called Pkdr1), leading to an R823W substitution in SamCystin, a protein that contains ankyrin repeats and a sterile alpha motif (SAM). Han:SPRD Cy/+ rats develop a slowly progressing form of PKD which resembles phenotypically human ADPKD. We used microarrays to examine alterations in the renal gene expression in a rodent model of PKD, namely the Han:SPRD rat.
Project description:The research included a cohort of 11 patients who were diagnosed with mild or moderate COPD, as well as a control group of 7 individuals who were matched for age.
Project description:Microcalcification is one of the most common radiological and pathological features of breast ductal carcinoma in situ (DCIS), and to a lesser extent, invasive ductal carcinoma. We evaluated transcriptional profiles associated with ectopic mammary mineralization. We evaluated the transcriptional profiles associated with breast cancer microcalcification for Taiwanese breast cancer and a gene expression signature was derived.
Project description:We analyzed tumor and adjacent non-tumor tissues from 62 Taiwanese HCC cases using Illumina HumanMethylation 27 chips. After Bonferroni adjustment, a total of 2,324 CpG sites significantly differed in methylation level, with 684 CpG sites significantly hypermethylated and 1,640 hypomethylated in tumor compared to non-tumor tissues. Array data were validated with pyrosequencing in a subset of 5 of these genes; correlation coefficients ranged from 0.92 to 0.97.