Next Generation Sequencing Facilitates Differential Expression Analysis of miRNA Expression In the Whole Blood Samples Obtained From Prostate Cancer Patients vs. Controls
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE97901 | GEO | 2017/04/18
SECONDARY ACCESSION(S): PRJNA383159
REPOSITORIES: GEO
Similar Datasets
Project description:Beginning with precursor lesions, aberrant DNA methylation marks the entire spectrum of prostate cancer progression. We mapped the global DNA methylation patterns in selected prostate tissues and cell lines using Methylplex-Next Generation Sequencing (M-NGS). Hidden Markov Model based next generation sequence analysis identified ~68,000 methylated regions per sample. While global CpG Island (CGI) methylation was not differential between benign adjacent and cancer samples, overall promoter CGI methylation increased from ~12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues, respectively. We found distinct patterns of promoter methylation around transcription start sites, where methylation occurred not only on the CGIs, but also on flanking regions and CGI sparse promoters. Among the 6,691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer specific, including numerous novel DMRs. A novel cancer specific DMR in WFDC2 promoter showed heavy methylation in cancer (17/22 tissues, 6/6 cell lines), but not in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested an epigenetic mechanism for alternate transcription start site utilization and these modifications segregated into distinct regions when present on the same promoter. Finally, we observed differences in repeat element methylation, particularly LINE-1, between ERG gene fusion positive and negative cancers. This comprehensive methylome map will further our understanding of epigenetic regulation in prostate cancer progression. Next generation Sequencing for Gene expression using the RNA-Seq methodology from LNCaP and PrEC cell lines
2011-05-09 | E-GEOD-29155 | biostudies-arrayexpress
Project description:Beginning with precursor lesions, aberrant DNA methylation marks the entire spectrum of prostate cancer progression. We mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2) from fifty nanograms of genomic DNA using Methylplex-Next Generation Sequencing (M-NGS). A Hidden Markov Model (HMM)-based algorithm previously used for Chip-Seq data analysis(http://www.sph.umich.edu/csg/qin/HPeak) was used to locate peaks from mapped reads obtained in each sequencing run. The total methylation events in intergenic/intronic regions between benign adjacent and cancer tissues were comparable. While approximately 20% of all CpG islands (CGIs) (68,508) were methylated in tissues, promoter CGI methylation gradually increased from ~12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues. We found distinct patterns in promoter methylation around transcription start sites, where methylation occurred directly on the CGIs, flanking regions and on CGI sparse promoters. Among the 6,691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer specific and several previously studied targets were among them. A novel cancer specific DMR in WFDC2 promoter showed 77% methylation in cancer (17/22), 100% methylation in transformed prostate cell lines (6/6), none in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested a role for DNA methylation in alternate transcription start site utilization. While methylated promoters containing CGIs had mutually exclusive H3K4me3 modification, the histone mark was absent in CGI sparse promoters. Finally, we observed difference in methylation of LINE-1 elements between transcription factor ERG positive and negative cancers. The comprehensive methylome map presented here will further our understanding of epigenetic regulation of the prostate cancer genome. We mapped the global DNA methylation patterns in prostate tissues (n=17; data not available in GEO - being deposited in dbGaP for controlled access) and cells (n=2) from fifty nanograms of genomic DNA using Methylplex-Next Generation Sequencing (M-NGS). For replicate analysis in cell lines, a total of 4 runs were completed for PrEC prostate normal cell line, and 5 runs were completed for LNCaP prostate cancer cell line. For tissue samples, 2 benign prostate samples were ran twice on illumina next generation sequencing platform to access overall repeatability of M-NGS.
2011-05-09 | E-GEOD-27618 | biostudies-arrayexpress
Project description:Purpose: Prostate cancer most frequently metastasizes to bone and is incurable. Metastatic prostate cancer cells thrive in bone through molecular regulation of surrounding bone stroma; however, it is unclear how non-metastatic vs. metastatic cancer differentially alter the bone cells. Since neutrophils are the most abundant stromal cell in bone, the goal of this study was to identify prostate cancer-induced transcriptomic changes in bone marrow neutrophils for comparison to non-metastatic prostate cancer cells.
2022-08-03 | GSE193468 | GEO
Project description:iRNAs have been demonstrated to play crucial roles in cancer development by directing the post-transcriptional regulation of target gene expression. We analyzed the expression profile of piRNAs in 3 of the prostate cancer tissues and matched normal adjacent tissues by piRNA sequencing. The aim of this analyse was to find the different expressed piRNAs in prostate cancer.
2022-01-01 | GSE143389 | GEO
Project description:Neurodegenerative diseases encompass a wide variety of pathological conditions caused by a loss of neurons in the central nervous system (CNS) and are severely debilitating. Exosome contains bio-signatures of great diagnostic and therapeutic value. There is proof that exosomal proteins can be biomarkers for Alzheimer's disease (AD) and Parkinson's disease (PD). MicroRNAs in exosome has potential to be an important source of biomarkers for neurodegenerative diseases. Here, we report exosomal microRNA performance of human plasma in neurodegenerative diseases by small RNA sequencing. A wide range of altered exo-miRNA expression levels were detected in both AD and PD patients. Down-regulated miRNAs in AD samples were enriched in ECM-receptor interaction pathway and both up-/down-regulated miRNAs in PD samples were enriched in fatty acid biosynthesis pathway. Compared to the control, 8 miRNAs were found to be significantly elevated/declined in AD and PD samples, of which 4 miRNAs were newly identified. Additionally, two exosome isolating methods were compared and the reproducibility of plasma exo-miRNA expression was confirmed, suggesting the feasibility of large-scale clinical application of this method. This study revealed exo-miRNA expression levels in neurodegenerative diseases, proposed new biomarkers and their potential functional pathway for AD and PD, confirmed the reproductivity of exo-miRNA profiles by using a different exosome isolating method, and compared the results with plasma miRNA expression. Therefore, this study also provides a precedent for identifying exosomal biomarkers of neurodegenerative diseases in plasma by high-throughput sequencing and it could extend the therapeutic repertoire of exosomal biomarkers.
| S-EPMC7227778 | biostudies-literature
Project description:Next-generation sequencing technologies enable the rapid cost-effective production of sequence data. To evaluate the performance of these sequencing technologies, investigation of the quality of sequence reads obtained from these methods is important. In this study, we analyzed the quality of sequence reads and SNP detection performance using three commercially available next-generation sequencers, i.e., Roche Genome Sequencer FLX System (FLX), Illumina Genome Analyzer (GA), and Applied Biosystems SOLiD system (SOLiD). A common genomic DNA sample obtained from Escherichia coli strain DH1 was applied to these sequencers. The obtained sequence reads were aligned to the complete genome sequence of E. coli DH1, to evaluate the accuracy and sequence bias of these sequence methods. We found that the fraction of "junk" data, which could not be aligned to the reference genome, was largest in the data set of SOLiD, in which about half of reads could not be aligned. Among data sets after alignment to the reference, sequence accuracy was poorest in GA data sets, suggesting relatively low fidelity of the elongation reaction in the GA method. Furthermore, by aligning the sequence reads to the E. coli strain W3110, we screened sequence differences between two E. coli strains using data sets of three different next-generation platforms. The results revealed that the detected sequence differences were similar among these three methods, while the sequence coverage required for the detection was significantly small in the FLX data set. These results provided valuable information on the quality of short sequence reads and the performance of SNP detection in three next-generation sequencing platforms.
| S-EPMC3096631 | biostudies-literature
Project description: Not available
| S-EPMC11022476 | biostudies-literature
Project description:A cross-species analysis identified MELK as a potential therapeutic target in prostate cancer. To further elucidate the functional role of MELK in prostate cancer cells, we aimed to identify MELK-regulated genes. C4-2b cells were either treated with a small-molecule MELK inhibitor (OTSSP167), or transfected with siRNAs targeting MELK. Differentially expressed genes were identified using next-generation sequencing. Our results demonstrate that MELK promotes the expression of genes associated with tumour progression in prostate cancer cells.
2018-02-05 | GSE94570 | GEO
Project description:We established a protocol of the SuperSAGE technology combined with next-generation sequencing, coined "High-Throughput (HT-) SuperSAGE". SuperSAGE is a method of digital gene expression profiling that allows isolation of 26-bp tag fragments from expressed transcripts. In the present protocol, index (barcode) sequences are employed to discriminate tags from different samples. Such barcodes allow researchers to analyze digital tags from transcriptomes of many samples in a single sequencing run by simply pooling the libraries. Here, we demonstrated that HT-SuperSAGE provided highly sensitive, reproducible and accurate digital gene expression data. By increasing throughput for analysis in HT-SuperSAGE, various applications are foreseen and several examples are provided in the present study, including analyses of laser-microdissected cells, biological replicates and tag extraction using different anchoring enzymes.
| S-EPMC2917361 | biostudies-literature
Project description:Alternative cleavage and polyadenylation (APA) is a form of transcriptional regulation via shifts in how frequently multiple polyadenylation (polyA) sites within genes are used across biological conditions. APA can result in transcripts with varying length and information content, and has been linked to gene regulation in both cancer and development. To provide a reference for investigating APA in the context of prostate cancer, we performed a genome-wide quantification of polyA site usage using a next generation sequencing technique. By priming the polyA-tails of an RNA library, we mapped cleavage sites and abundances with base-pair resolution across the genomes of one normal prostate and two prostate cancer cell lines. This data can be used to detect APA events among these cell line models, and integration of these data with APA events from clinical prostate cancer samples can lead to candidate genes for future mechanistic studies of the regulation and function of APA in cancer.
2022-12-29 | GSE86180 | GEO