Identification of novel androgen-regulated pathways and mRNA isoforms through genome-wide exon-specific profiling of the LNCaP transcriptome. by Prabhakar Rajan, Caroline Dalgliesh, Phillippa J Carling, Thomas Buist, Chaolin Zhang, Sushma N Grellscheid, Kelly Armstrong, Jacqueline Stockley, Cedric Simillion, Luke Gaughan, Gabriela Kalna, Michael Q Zhang, Craig N Robson, Hing Y Leung, David J Elliott

“…Androgens drive the onset and progression of prostate cancer (PCa) by modulating androgen receptor (AR) transcriptional activity. Although several microarray-based studies have identified androgen-regulated genes, here we identify in-parallel global androgen-dependent changes in both gene and alternative mRNA isoform expression by exon-level analyses of the LNCaP transcriptome. …”
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Exploring the predictive values of SERP4 and FRZB in dilated cardiomyopathy based on an integrated analysis by Bin Qi, Hai-Yan Wang, Xiao Ma, Yu-Feng Chi, Chun Gui

“…Methods Five DCM-related microarray datasets were downloaded from the Gene Expression Omnibus (GEO). …”
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Examination of the functions and mechanism of KCP in mediating paclitaxel resistance in cervical squamous carcinoma cells by Yue He, Jian-Qing Xu, Jing-Jing Zhang, Zhen-You Liu, Chen Ji, Yang Liu, Yun-Fan Wang, Ming Wang, Yu-Mei Wu, Yan Wang

“…Key cell functions were assessed by colony formation assay, measurement of cell proliferation by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, and FACS-based detection of apoptosis. The downstream mechanism of KCP-mediated resistance to paclitaxel was then examined using human gene chip detection and IPA bioinformatics analysis, and qPCR analysis was used to validate its downstream genes.Results①Functional studies of SiHa cells showed that KCP knockout (sgRNA) inhibited colony formation and proliferation of SiHa cells in the presence of paclitaxel (p<0.05). ②Using a whole human genome microarray, a total of 491 differentially expressed genes were identified in KCP knockout versus the NC SiHa cells. …”
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Identification of Novel Biomarkers in Huntington’s Disease Based on Differential Gene Expression Meta-Analysis and Machine Learning Approach by Nayan Dash, Md Abul Bashar, Jeonghan Lee, Raju Dash

“…Therefore, to discover the key biomarkers associated with the progression of HD, we employed bioinformatics and machine learning (ML) to create a robust pipeline that integrated differentially expressed gene (DEG) analysis with ML to select potential biomarkers. We performed a meta-analysis to identify DEGs using three Gene Expression Omnibus (GEO) microarray datasets from different platforms related to HD-affected brain tissue, applying both relaxed and strict criteria to identify differentially expressed genes. …”
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Circulating exosomal microRNAs as biomarkers of colon cancer. by Hiroko Ogata-Kawata, Masashi Izumiya, Daisuke Kurioka, Yoshitaka Honma, Yasuhide Yamada, Koh Furuta, Toshiaki Gunji, Hideki Ohta, Hiroyuki Okamoto, Hikaru Sonoda, Masatoshi Watanabe, Hitoshi Nakagama, Jun Yokota, Takashi Kohno, Naoto Tsuchiya

“…<h4>Experimental design</h4>Microarray analyses of miRNAs in exosome-enriched fractions of serum samples from 88 primary CRC patients and 11 healthy controls were performed. …”
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Integrated bioinformatic analysis of the shared molecular mechanisms between ANCA-associated vasculitis and atherosclerosis by Xun Hu, Inmaculada Xu Lou, Qilan Chen

“…This study aims to explore the mechanisms underlying the concurrent occurrence of ANCA and AS. Methods Microarray data of AAV and AS were examined in a comprehensive gene expression database. …”
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Comparison of monocyte gene expression among patients with neurocysticercosis-associated epilepsy, Idiopathic Epilepsy and idiopathic headaches in India. by Vasudevan Prabhakaran, Douglas A Drevets, Govindan Ramajayam, Josephine J Manoj, Michael P Anderson, Jay S Hanas, Vedantam Rajshekhar, Anna Oommen, Hélène Carabin

“…Fifteen genes up-regulated in NCC patients compared with other groups were selected based on possible relevance to NCC, and analyzed by qPCR in all patients' samples. …”
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Research on the diagnosis model of osteoarthritis based on methylation-related genes using machine learning algorithms by Xu Cui, Houlin Ji, Shengyang Guo, Ju Liu, Linyuan Zhang, Yongwei Jia, Yin Cui, Xiaoxiao Zhou

“…Genes were selected through SVM-RFE analysis and LASSO regression model, and a diagnostic model for OA was established. …”
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An Immune-Related Prognostic Classifier Is Associated with Diffuse Large B Cell Lymphoma Microenvironment by Xiao-Jie Liang, Rui-ying Fu, He-nan Wang, Jing Yang, Na Yao, Xin-di Liu, Liang Wang

“…We systematically searched for DLBCL gene expression microarray datasets from the GEO database. Immune-related genes (IRGs) were obtained from the ImmPort database, and 318 transcription factor (TF) targets in cancer were retrieved from the Cistrome Cancer database. …”
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MiR-25-3p regulates pulmonary arteriovenous malformation after Glenn procedure in patients with univentricular heart via the PHLPP2-HIF-1α axis by Junpei Kawamura, Munekazu Yamakuchi, Kentaro Ueno, Teruto Hashiguchi, Yasuhiro Okamoto

“…Abstract The detailed mechanism of pulmonary arteriovenous malformations after Glenn surgery (G-PAVMs) in cyanotic congenital heart disease (CHD) remains unclear. Microarray in situ hybridization was performed to assess the miRNA (miRNA) profiles of serum from pediatric patients (0–6 years of age) with G-PAVMs and after the Fontan procedure without G-PAVMs. …”
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Stromal expression of decorin, Semaphorin6D, SPARC, Sprouty1 and Tsukushi in developing prostate and decreased levels of decorin in prostate cancer. by Alexander Henke, O Cathal Grace, George R Ashley, Grant D Stewart, Antony C P Riddick, Henry Yeun, Marie O'Donnell, Richard A Anderson, Axel A Thomson

“…<h4>Methodology and principal findings</h4>Five candidate molecules identified by transcript profiling of developmental prostate mesenchyme were selected using a wholemount in situ hybridisation screen and studied Decorin (Dcn), Semaphorin6D (Sema6D), SPARC/Osteonectin (SPARC), Sprouty1 (Spry-1) and Tsukushi (Tsku). …”
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Temporal Expression of Peripheral Blood Leukocyte Biomarkers in a Macaca fascicularis Infection Model of Tuberculosis; Comparison with Human Datasets and Analysis with Parametric/N... by Sajid Javed, Leanne Marsay, Alice Wareham, Kuiama S Lewandowski, Ann Williams, Michael J Dennis, Sally Sharpe, Richard Vipond, Nigel Silman, Graham Ball, Karen E Kempsell

“…Further data refinements identified groups of key markers showing group-specific expression patterns, with a substantial reprogramming event evident at the four to six week interval. Selected statistically-significant gene entities from this study and other immune and apoptotic markers were validated using qPCR, which confirmed many of the results obtained using microarray hybridisation. …”
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RTP4, a Biomarker Associated with Diagnosing Pulmonary Tuberculosis and Pan-Cancer Analysis by Hao Li, Qin Zhou, ZhiXiang Ding, QingHai Wang

“…Pulmonary tuberculosis (PTB) is a global epidemic of infectious disease; the purpose of our study was to explore new potential biomarkers for the diagnosis of pulmonary tuberculosis and to use the biomarkers for further pan-cancer analysis. Methods. Four microarray gene expression sets were downloaded from the GEO public databases and conducted for further analysis. …”
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Citrus flavonoids for overcoming breast cancer resistance to methotrexate: identification of potential targets of nobiletin and sinensetin by Adam Hermawan, Naufa Hanif, Dyaningtyas Dewi Pamungkas Putri, Nurul Fatimah, Heri Himawan Prasetio

“…Protein targets of citrus flavonoids were identified from multiple databases and were collected using Venny 2.1. Microarray data of MCF-7 and MCF-7/MTX cells were acquired from the Gene Expression Omnibus. …”
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A retrospective analysis of prenatal genetic results in fetal hydronephrosis. by Keqin Jin, Xiayuan Xu, Yue Qian, Liping Zhang, Min Hu, Jianfeng Luo

“…<h4>Objective</h4>To discuss the application value of technologies such as chromosome microarray analysis (CMA) in fetuses with hydronephrosis and pyelectasis.…”
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Bioinformatic analyses reveal lysosomal-associated protein transmembrane 5 as a potential therapeutic target in lipotoxicity-induced injury in diabetic kidney disease by Xin Chen, Shenglong Zhu, Ciyou Huang, Jiayi Liu, Jinbang Wang, Siyuan Cui

“…Here, we analyzed the GSE 30529 microarray datasets of human tubulointerstitial tissue samples from the Gene Expression Omnibus database (GEO). …”
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Multiple-omics analysis of aggrephagy-related cellular patterns and development of an aggrephagy-related signature for hepatocellular carcinoma by Jiafen Xie, Xiaoming Wang

“…Abstract Background Protein aggrephagy, a selected autophagy process response for degrading protein aggregates, plays a critical role in various cancers. …”
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Screening and identification of potential target of 1′-acetoxychavicol acetate (ACA) in acquired lapatinib-resistant breast cancer by Febri Wulandari, Ahmad Fauzi, Muhammad Da'i, Mahmoud Mirzaei, Maryati, Kun Harismah

“…We identified differentially expressed genes (DEGs) using GSE16179 microarray data. DEGs from ACA-treated and lapatinib-resistant cells were analyses using Panther DB, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and protein-protein interaction (PPI) network analysis. …”
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HDAC1 Mediates Immunosuppression of the Tumor Microenvironment in Non-Small Cell Lung Cancer by Fan Y, Ji X, Yuan K, Wu Q, Lou M

“…However, there are no studies on the immunological aspects of HDAC1 in non-small cell lung cancer (NSCLC).Methods: In this research, we used the Cancer Genome Atlas (TCGA) public database combined with tissue microarray (TMA) to investigate HDAC1 expression and prognosis in NSCLC. …”
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Bayesian inference towards the resolution of molecular evolution: application to the “Trichoderma harzianum sensu lato” clade by Druzhinina I S, Kubicek C P

“…The clade containing the ex-neotype strain of T. harzianum included exclusively clonally propagating isolates from temperate climates, and was clearly distinguished from all other “H. lixii/T. harzianum” lineages by multivariate analysis of phenotype microarray data. We propose that only this lineage should be regarded as T. harzianum sensu stricto, and that the other lineages be regarded as T. harzianum sensu lato until phenetic characters have been defined which allow their description as separate taxa.…”
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