Aspirin antitumoral effect on pituitary adenoma
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ABSTRACT:
PROVIDER: PRJNA837778 | ENA |
REPOSITORIES: ENA
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Project description:Aspirin, is a commonly used non-steroidal anti-inflammatory drug with antipyretic, analgesic, anti-inflammatory, and anti-thrombotic effect. Its antitumoral effect was also demonstrated in several cancer types. In this study our aim was to investigate the genomic effects of ASA in pituitary adenomas using high-throughput profiling approaches and validate our findings by targeted methodologies, using in vitro functional assays. Whole transcriptome profile of RC4-B/C and GH3 pituitary cell lines upon Aspirin treatment was investigated.
2022-06-19 | GSE202934 | GEO
Project description:Data from 12 fresh-frozen somatotropinomas and their corresponding blood samples. Details are given in Valimaki et al. Whole-genome sequencing of Growth Hormone (GH) -secreting Pituitary Adenoma. Provisionally accepted, 2015.
| EGAS00001001293 | EGA
Project description:Pituitary adenomas are benign tumors originating from the endocrine cells of the pituitary gland, but some pathological subtypes are highly invasive, known as invasive pituitary adenomas. Invasive pituitary adenomas are relatively rare, progress rapidly, easily invade surrounding tissues, have a high risk of recurrence, and have poor response to standard treatments. This study collected tumor specimens from 17 patients with non-invasive pituitary adenomas (FSH type) and 15 patients with invasive pituitary adenomas (ACTH-silent type), and performed transcriptome sequencing, aiming to explore the genetic differences between invasive and non-invasive pituitary adenomas.
2024-03-04 | GSE260487 | GEO
Project description:Aspirin is a non-steroidal anti-inflammatory drug. Till date there is no information on the molecular mechanism of aspirin on oral cancer cells. In this study, treated oral cancer cells were compared with untreated ones for gene expression for finding the effect of aspirin on biological process and significant pathways involved. Aspirin plays an important role in inducing apoptotic effect by activating regulators and further inhibits cell cycle progression.
2014-11-22 | GSE58162 | GEO
Project description:This series includes the four major subtypes of pituitary adenomas and normal post-mortem pituitary tissue; Data Transformation; Using Affymetrix Microarray Suite 5.0 global scaling was applied to the quantification data to adjust the average recorded to a target intensity of 100. Data were then exported into the bioinformatics software GeneSpring 6.0 (Silicon Genetics, Redwood City, CA) for further analysis. Data normalization was performed to scale the data so that the average intensity value on each array was 1 by dividing each expression value by the median of the expression levels on each chip. The individual gene expression levels for each of the 4 pituitary adenoma subtype arrays was divided by the expression level in the normal pituitary array. Thus, the data are presented as relative to the expression in normal pituitary tissue. Filtering was then performed to identify genes over-expressed or under-expressed at least 2.0 fold in tumours compared to normal pituitary. TABLE 1:; The genes / ESTs differentially overexpressed >= 2-fold in at least one pituitary adenoma subtype compared to normal pituitary. Negative values represent underexpression. Where genes are represented by more than one probe set, individual probe data sets are given. TABLE 2:; The genes / ESTs differentially underexpressed >= 2-fold in at least one pituitary adenoma subtype compared to normal pituitary. Negative values represent underexpression. Where genes are represented by more than one probe set, individual probe data sets are given.
2008-06-12 | E-GEOD-2175 | biostudies-arrayexpress
Project description:Background: Circulating miRNAs in pituitary adenoma would help patient care especially in non-functioning adenoma cases as minimally invasive biomarkers of tumor recurrence and progression. Aim: Our aim was to investigate plasma miRNA profile in patients with pituitary adenoma. Materials and Methods: 149 plasma and extracellular vesicle (preoperative, early- and late postoperative) samples were collected from 45 pituitary adenoma patients. Adenomas were characterized based on anterior pituitary hormones and transcription factors by immunostaining. MiRNA next generation sequencing was performed on 36 samples (discovery set). Individual TaqMan assay was used for validation on extended sample set. PA tissue miRNAs were evaluated by TaqMan array and literature data. Results: Global downregulation of miRNA expression was observed in plasma samples of pituitary adenoma patients compared to normal samples. Expression of 29 miRNAs and isomiR variants were able to distinguish preoperative plasma samples and normal controls. MiRNAs with altered expression in both plasma and different adenoma tissues were identified. 3, 7 and 66 miRNAs expressed differentially between preoperative and postoperative plasma samples in growth hormone secreting, FSH/LH+ and hormone-immunonegative groups, respectively. MiR-143-3p was downregulated in late- but not in early postoperative plasma samples compared to preoperative ones exclusively in FSH/LH+ adenomas. Plasma level of miR-143-3p discriminated these samples with 81.8% sensitivity and 72.3% specificity (AUC=0.79; p=0.02). Conclusions: Differentially expressed miRNAs in pituitary adenoma tissues have low abundance in plasma minimizing their role as biomarkers. Plasma miR-143-3p decreases in patients with FSH/LH+ adenoma indicated successful surgery, but its application for evaluating tumor recurrence needs further investigation.
2019-05-21 | GSE131483 | GEO
Project description:This series includes the four major subtypes of pituitary adenomas and normal post-mortem pituitary tissue Data Transformation Using Affymetrix Microarray Suite 5.0 global scaling was applied to the quantification data to adjust the average recorded to a target intensity of 100. Data were then exported into the bioinformatics software GeneSpring 6.0 (Silicon Genetics, Redwood City, CA) for further analysis. Data normalization was performed to scale the data so that the average intensity value on each array was 1 by dividing each expression value by the median of the expression levels on each chip. The individual gene expression levels for each of the 4 pituitary adenoma subtype arrays was divided by the expression level in the normal pituitary array. Thus, the data are presented as relative to the expression in normal pituitary tissue. Filtering was then performed to identify genes over-expressed or under-expressed at least 2.0 fold in tumours compared to normal pituitary. TABLE 1: The genes / ESTs differentially overexpressed >= 2-fold in at least one pituitary adenoma subtype compared to normal pituitary. Negative values represent underexpression. Where genes are represented by more than one probe set, individual probe data sets are given. TABLE 2: The genes / ESTs differentially underexpressed >= 2-fold in at least one pituitary adenoma subtype compared to normal pituitary. Negative values represent underexpression. Where genes are represented by more than one probe set, individual probe data sets are given. Keywords = pituitary tumor Keywords: other
2005-05-23 | GSE2175 | GEO
Project description:We profiled the somatic landscape of 21 growth hormone (GH) -secreting pituitary adenomas using somatic copy-number alteration (SCNA), whole-genome sequencing (WGS), bisulfate sequencing, and transcriptome approaches. See details in Valimaki et al. Genetic and epigenetic characterization of growth hormone (GH) - secreting pituitary tumors. Manuscript in preparation, 2019.
| EGAS00001003488 | EGA
Project description:Chronic inflammation plays important role in lung cancer development. Recently, we found that anti-inflammation drugs aspirin and triptolide when combined showed synergistic effect in suppressing lung cancer development. In this study, we aim to use gene microarray to define the genes and pathways that are affected by aspirin, triptolide individually or in combination.
2017-06-01 | GSE99514 | GEO
Project description:To further identify microenvironment-related genes in Non-functioning pituitary adenoma (NFPAs) and assess their prognostic value, we collected 73 NFPA tumor samples and transcriptional expression profiles were obtained through microarray analysis. The immune and stromal scores of each sample were calculated through the ESTIMATE algorithm, and the patients were divided into high and low immune/stromal score groups. Intersection differentially expressed genes (DEGs) were then obtained to construct a protein-protein interaction (PPI) network. Potential functions and pathways of intersection DEGs were then analyzed through Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. The prognostic value of these genes was evaluated. Quantitative The quantitative real-time polymerase chain reaction in another set of NFPA samples was used to confirm the credibility of the bioinformatics analysis. The immune/stromal scores were significantly correlated with cavernous sinus (CS) invasion.
2021-03-30 | GSE169498 | GEO