Next Generation Sequencing of the transcriptomes of prostate cancer cells with or without ectopic expression of miR-5100
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE267128 | GEO | 2024/05/14
REPOSITORIES: GEO
Similar Datasets
Project description:MicroRNAs (miRNAs) function as regulators of cancer progression as they modulate different cellular processes. The objective of this study is to demonstrate a multi-dimensional function of miR-30e through regulating genes involved in various signaling pathways including androgen receptor signaling. miR-30e targets androgen receptor mRNA and functions as a tumor suppressor. We noted loss of miR-30e expression in prostate tumors and restored expression of miR-30e led to cell cycle arrest, induction of apoptosis, improved drug sensitivity in prostate cancer cells, and reduced tumor progression in prostate cancer xenograft models. To understand the tumor suppressor function of miR-30e on a global scale, we performed total RNA-sequence analysis upon overexpression of miR-30e in a prostate cancer cell line 22Rv-1, which expresses a splice variant of androgen receptor and represents an androgen-independent and drug-resistant form of prostate cancer.qRT-PCR validation of RNA-sequencing data supports our in vitro study showeing differential expression of genes involved in cell cycle progression, apoptosis and ubiquitination upon expression of miR-30e in prostate cancer cells.
2022-08-31 | GSE188345 | GEO
Project description:Transcriptome analysis was performed to determine the effect of overexpression of LINC00888 on global gene expression in prostate cancer cells.
2021-03-09 | GSE158953 | GEO
Project description:Next-generation sequencing of the transcriptomes of prostate cancer cells with or without ectopic expression of LINC00888
| PRJNA667086 | ENA
Project description:Gene expression profilings for prostate cancer cells after olaparib treatment
2022-03-31 | GSE189186 | GEO
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:BACKGROUND: Organelle genomes of Geraniaceae exhibit several unusual evolutionary phenomena compared to other angiosperm families including accelerated nucleotide substitution rates, widespread gene loss, reduced RNA editing, and extensive genomic rearrangements. Since most organelle-encoded proteins function in multi-subunit complexes that also contain nuclear-encoded proteins, it is likely that the atypical organellar phenomena affect the evolution of nuclear genes encoding organellar proteins. To begin to unravel the complex co-evolutionary interplay between organellar and nuclear genomes in this family, we sequenced nuclear transcriptomes of two species, Geranium maderense and Pelargonium x hortorum. RESULTS: Normalized cDNA libraries of G. maderense and P. x hortorum were used for transcriptome sequencing. Five assemblers (MIRA, Newbler, SOAPdenovo, SOAPdenovo-trans [SOAPtrans], Trinity) and two next-generation technologies (454 and Illumina) were compared to determine the optimal transcriptome sequencing approach. Trinity provided the highest quality assembly of Illumina data with the deepest transcriptome coverage. An analysis to determine the amount of sequencing needed for de novo assembly revealed diminishing returns of coverage and quality with data sets larger than sixty million Illumina paired end reads for both species. The G. maderense and P. x hortorum transcriptomes contained fewer transcripts encoding the PLS subclass of PPR proteins relative to other angiosperms, consistent with reduced mitochondrial RNA editing activity in Geraniaceae. In addition, transcripts for all six plastid targeted sigma factors were identified in both transcriptomes, suggesting that one of the highly divergent rpoA-like ORFs in the P. x hortorum plastid genome is functional. CONCLUSIONS: The findings support the use of the Illumina platform and assemblers optimized for transcriptome assembly, such as Trinity or SOAPtrans, to generate high-quality de novo transcriptomes with broad coverage. In addition, results indicated no major improvements in breadth of coverage with data sets larger than six billion nucleotides or when sampling RNA from four tissue types rather than from a single tissue. Finally, this work demonstrates the power of cross-compartmental genomic analyses to deepen our understanding of the correlated evolution of the nuclear, plastid, and mitochondrial genomes in plants.
| S-EPMC3880972 | biostudies-literature
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: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