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Dataset Information

Expression data from peripheral blood mononuclear cells of subjects supplemented with vitamin C [qPCR array analysis]

ABSTRACT: A role of vitamin C(ascorbic acid) as an antioxidant molecule has been recognized, largely based on in vitro studies. However, more recently, the concept of M-bM-^@M-^\antioxidant moleculeM-bM-^@M-^] has been reconsidered and its biological function is no longer considered to be simply due to its ability to act as M-bM-^@M-^\electron donorsM-bM-^@M-^], rather, it appears to act by modulating signaling and gene expression. In order to gain a better understanding of the effects of vitamin C supplementation on gene expression in both physiological and pro-inflammatory conditions, we performed a pilot explorative intervention study based on the utilization of microarray and qPCR technologies, designed on a M-bM-^@M-^\in vivo-ex vivoM-bM-^@M-^] structure Five healthy subjects (three males and 2 females, aged 25-40) were recruited for a short term (five days) intervention study. Subjects were asked to assume one tablet of RedoxonM-BM-. (Bayer), a day (containing 1 gr of ascorbate), for 5 days. A baseline blood withdrawal was performed in fasting condition, just before the first vitamin C tablet. Tablets were provided to the volunteers, every morning at the same hour for the following 4 days of the study. The last tablet was supplemented about 1,5 hour before the second and last blood withdrawal, performed again in fasting condition. Plasma and peripheral blood mononuclear cells (PBMNC) were obtained . PBMNC from each subject were splitted in three aliquots: one was stored in lysis buffer at -80M-BM-0C and utilized to isolate RNA for the Affymetrix gene array analysis. The other two aliquots were resuspended in RPMI 1640 w/o phenol red containing 10% of autologous plasma: one was incubated with 10 ug/ml lipopolysaccharides (LPS) for 5 hours at 37M-BM-0C. At the end of the incubation time, the medium was collected and stored at -80M-BM-0C for the assessment of cytokine release in response to the inflammatory stimuli. RNA was extracted from the pelleted cells for gene expression analysis, using the Human NFkB Signaling 96 StellARrayM-bM-^DM-" qPCR array (Lonza). The results obtained with PBMNC isolated after vitamin C supplementation (supplemented PBMNC) were compared to those obtained with PBMNC isolated before the supplementation (baseline PBMNC), for each subject.

ORGANISM(S): Homo sapiens

SUBMITTER: Guido Leoni

PROVIDER: E-GEOD-54476 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Vitamin C supplementation modulates gene expression in peripheral blood mononuclear cells specifically upon an inflammatory stimulus: a pilot study in healthy subjects.

Canali Raffaella R Natarelli Lucia L Leoni Guido G Azzini Elena E Comitato Raffaella R Sancak Oezgur O Barella Luca L Virgili Fabio F

Genes & nutrition 20140307 3

In order to study the effects of vitamin C supplementation on gene expression and compare its action between physiological and inflammatory conditions, a pilot study was set up utilizing microarray and qPCR technologies. Five healthy volunteers were supplemented with 1 g vitamin C (Redoxon(®)) per day for five consecutive days. Peripheral blood mononuclear cells (PBMNC) were isolated before and just after the last supplementation, and RNA was isolated for the Affymetrix gene 1.0 ST chip analysis ...[more]

PMID: 24604612

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Project description:A role of vitamin C (ascorbic acid) as an antioxidant molecule has been recognized, largely based on in vitro studies. However, more recently, the concept of M-bM-^@M-^\antioxidant moleculeM-bM-^@M-^] has been reconsidered and its biological function is no longer considered to be simply due to its ability to act as M-bM-^@M-^\electron donorsM-bM-^@M-^], rather, it appears to act by modulating signaling and gene expression. In order to gain a better understanding of the effects of vitamin C supplementation on gene expression in both physiological and pro-inflammatory conditions, we performed a pilot explorative intervention study based on the utilization of microarray and qPCR technologies, designed on a M-bM-^@M-^\in vivo-ex vivoM-bM-^@M-^] structure Five healthy subjects (three males and 2 females, aged 25-40) were recruited for a short term (five days) intervention study. Subjects were asked to assume one tablet of RedoxonM-BM-. (Bayer), a day (containing 1 gr of ascorbate), for 5 days. A baseline blood withdrawal was performed in fasting condition, just before the first vitamin C tablet. Tablets were provided to the volunteers, every morning at the same hour for the following 4 days of the study. The last tablet was supplemented about 1,5 hour before the second and last blood withdrawal, performed again in fasting condition. Plasma and peripheral blood mononuclear cells (PBMNC) were obtained . PBMNC from each subject were splitted in three aliquots: one was stored in lysis buffer at -80M-BM-0C and utilized to isolate RNA for the Affymetrix gene array analysis. The other two aliquots were resuspended in RPMI 1640 w/o phenol red containing 10% of autologous plasma: one was incubated with 10 ug/ml lipopolysaccharides (LPS) for 5 hours at 37M-BM-0C. At the end of the incubation time, the medium was collected and stored at -80M-BM-0C for the assessment of cytokine release in response to the inflammatory stimuli. RNA was extracted from the pelleted cells for gene expression analysis, using the Human NFkB Signaling 96 StellARrayM-bM-^DM-" qPCR array (Lonza). The results obtained with PBMNC isolated after vitamin C supplementation (supplemented PBMNC) were compared to those obtained with PBMNC isolated before the supplementation (baseline PBMNC), for each subject.

Project description:Purpose: To identify tissue microRNAs predictive of sunitinib activity in patients with metastatic renal-cell carcinoma (MRCC) and to validate them in a cellular model. Selected microRNAs were studied in serum from MRCC patients and healthy individuals. Methods: We screened 673 microRNAs using TaqMan Low-density Arrays (TLDAs) in tumors from MRCC patients with extreme phenotypes of marked efficacy and resistance to sunitinib, selected from an identification cohort (n=41). Differentially expressed microRNAs were selected using bioinformatics-based target prediction analysis and quantified by qRT-PCR in tumors from patients presenting similar phenoytpes selected from an independent cohort (n=117). Results were validated in a cellular model of sunitinib resistance and studied in serum from healthy individuals and MRCC patients. Results: TLDAs identified 64 microRNAs differentially expressed in the identification cohort. Seven candidates were quantified by qRT-PCR in the independent series. MiR-942 was the most accurate predictor of sunitinib efficacy (p=0.0074). High expression of miR-942, miR-133a, miR484, and miR-628-5p was significantly associated with decreased time-to-progression and overall survival. These microRNAs were overexpressed in the sunitinib resistant cell line Caki-2 in comparison with the sensitive parental cell line. Serum levels of miR-942, miR-133a, miR-484, miR-146a-5p, miR-374a and miR-486-5p were significantly reduced in MRCC patients compared to healthy controls. Conclusions: Our strategy identified differentially expressed microRNAs in MRCC patients presenting marked sensitivity and resistance to sunitinib. Mir-942 was the best predictor of efficacy. Results were confirmed in a cellular model of sunitinib resistance. We also identified exosome derived serum microRNAs differentially expressed in MRCC patients and healthy individuals. Taqman Low Density Array for 6 FFPE tissues obtained from extreme phenotype MRCC patients, (n=3 marked resistance to sunitinib treatment patients and n=3 marked sensitivity to sunitinib treatment patients), was performanced to screen 667 microRNAs.

Project description:We previously demonstrated that the osteopontin-c (OPNc) splice variant activates several aspects of the progression of prostate cancers. The goal of the present study was to develop cell line model to determine the impact of OPNc overexpression on main cancer signaling pathways and thus obtain insights into the mechanisms of OPNc pro-tumorigenic roles. Methods: PC-3 cells were stably transfected to overexpress OPNc. Transcriptomic profiling was performed on these cells and compared to controls, to identify OPNc overexpression-dependent changes in gene expression levels and pathways by qRT-PCR analyses; Results: Of 84 genes tested by using a multiplex real-time PCR Cancer Pathway Array approach, among then 16 were differentially expressed between PC-3 OPNc-overexpressing cells in relation to control clones. Differentially expressed genes are included in all main hallmarks of cancer, and several interacting proteins have been identified using an interactome network analysis. Conclusions: Overall, the present study elucidated transcriptional changes of prostate cancer cells in response to OPNc overexpression, which provides an assessment for predicting the molecular mechanisms by which this splice variant promotes tumor progression features. Cell Culture, OPN Plasmids and Transfection; As a model to examine the signaling pathways modulated by OPNc overexpression in prostate carcinoma, we used PC-3 cell line, which were provided by ATCC. The open reading frame of OPNc was cloned into the pCR3.1 mammalian expression vector as previously described [Tilli et al., 2012]. Transfections were performed using LipofectamineTM 2000 (Invitrogen, CA). Our previous data demonstrated that PC-3 stably transfected cells contain higher levels of protein and the mRNA OPNc splicing isoform in relation to their endogenous levels in empty vector-transfected cells. PC-3 transfected with empty vector (EV) were used as a negative control in these assays. Human Cancer Pathway Finder PCR Array The Human Cancer Pathway Finder SuperArray (PAHS-033A; Qiagen) was used to determine changes in the specific genes encoding proteins related to the main hallmarks of cancer in response to OPNc overexpression. The assay design criteria ensure that each qPCR reaction will generate single, gene-specific amplicons and prevent the co-amplification of non-specific products. The qPCR Assays used in PCR Arrays are optimized to work under standard conditions enabling a large number of genes to be assayed simultaneously. Their specificity is guaranteed by SABiosciences when RT2 SYBR Green qPCR Master Mixes are used as part of the complete PCR Array System protocol. Simultaneous gene expression analyses require similar qPCR efficiencies for accurate comparison among genes. RT2 qPCR Primer Assays are designed with an amplicon size ranging from 100 to 250 bp and with PCR efficiencies uniformly greater than 90%. Overall, more than 10 thermodynamic criteria are included in the design of each RT2 qPCR Primer Assay to ensure the most reliable and accurate results for pathway-based gene expression analysis in the PCR Array System. We analyzed mRNA levels of 84 genes related to cell cycle control, apoptosis and cell senescence, signal transduction molecules and transcription factors, adhesion, angiogenesis, invasion and metastasis; and also 5 housekeeping genes and genomic DNA contamination controls. The PCR plates were run using the CFX96 Real-Time System cycler (BioRad, Hercules, CA), following a superarray two-step cycling PCR protocol, in which each plate ran one cycle for 10 minutes at 95M-BM-0C, as well as 40 cycles of 95M-BM-0C for 15 seconds and 60M-BM-0C for 1 minute. After the superarray protocol was run for each plate, RT-PCR data analysis was performed using the website:http://www.SABiosciences.com/pcrarraydataanalysis.php, in order to compare gene expression of OPNc-overexpressing cells and empty vector transfected cells. Total RNA quality control, cDNA synthesis and the quantitative real-time RT-PCR (qRT-PCR) array were performed as recommended by the manufacturer (Qiagen). Data analysis of gene expression was performed using Excel-based PCR Array Data Analysis Software provided by manufacturer (Qiagen). Fold-changes in gene expression were calculated using the M-NM-^TM-NM-^TCT method, and five stably expressed housekeeping genes (M-NM-22 microglobulin, hypoxanthine phosphoribosyltransferase 1, ribosomal protein L13a, GAPDH and M-NM-2-actin) were used to normalize the level of expression. The statistical analysis was performed to compare the gene expression values for the OPNc-overexpressing cells and those transfected with empty vector. P<0.05 was considered statistically significant. Only genes showing a 1.5-fold or greater change were considered for further analysis.

Project description:We previously demonstrated that the osteopontin-c (OPNc) splice variant activates several aspects of the progression of ovarian cancers. The goal of the present study was to develop cell line model to determine the impact of OPNc overexpression on main cancer signaling pathways and thus obtain insights into the mechanisms of OPNc pro-tumorigenic roles. Methods: OvCar-3 cells were stably transfected to overexpress OPNc. Transcriptomic profiling was performed on these cells and compared to controls, to identify OPNc overexpression-dependent changes in gene expression levels and pathways by qRT-PCR analyses; Results: Of 84 genes tested by using a multiplex real-time PCR Cancer Pathway Array approach, 34, were differentially expressed between OvCar-3 OPNc-overexpressing cells in relation to control clones. Differentially expressed genes are included in all main hallmarks of cancer, and several interacting proteins have been identified using an interactome network analysis. Conclusions: Overall, the present study elucidated transcriptional changes of ovarian cancer cells in response to OPNc overexpression, which provides an assessment for predicting the molecular mechanisms by which this splice variant promotes tumor progression features. Cell Culture, OPN Plasmids and Transfection; As a model to examine the signaling pathways modulated by OPNc overexpression in ovarian carcinoma, we used OvCar-3 cell line, which were provided by ATCC. The open reading frame of OPNc was cloned into the pCR3.1 mammalian expression vector as previously described [Tilli et al., 2012]. Transfections were performed using LipofectamineTM 2000 (Invitrogen, CA). Our previous data demonstrated that OvCar-3 stably transfected cells contain higher levels of protein and the mRNA OPNc splicing isoform in relation to their endogenous levels in empty vector-transfected cells. OvCar-3 transfected with empty vector (EV) were used as a negative control in these assays. Human Cancer Pathway Finder PCR Array The Human Cancer Pathway Finder SuperArray (PAHS-033A; Qiagen) was used to determine changes in the specific genes encoding proteins related to the main hallmarks of cancer in response to OPNc overexpression. The assay design criteria ensure that each qPCR reaction will generate single, gene-specific amplicons and prevent the co-amplification of non-specific products. The qPCR Assays used in PCR Arrays are optimized to work under standard conditions enabling a large number of genes to be assayed simultaneously. Their specificity is guaranteed by SABiosciences when RT2 SYBR Green qPCR Master Mixes are used as part of the complete PCR Array System protocol. Simultaneous gene expression analyses require similar qPCR efficiencies for accurate comparison among genes. RT2 qPCR Primer Assays are designed with an amplicon size ranging from 100 to 250 bp and with PCR efficiencies uniformly greater than 90%. Overall, more than 10 thermodynamic criteria are included in the design of each RT2 qPCR Primer Assay to ensure the most reliable and accurate results for pathway-based gene expression analysis in the PCR Array System. We analyzed mRNA levels of 84 genes related to cell cycle control, apoptosis and cell senescence, signal transduction molecules and transcription factors, adhesion, angiogenesis, invasion and metastasis; and also 5 housekeeping genes and genomic DNA contamination controls. The PCR plates were run using the CFX96 Real-Time System cycler (BioRad, Hercules, CA), following a superarray two-step cycling PCR protocol, in which each plate ran one cycle for 10 minutes at 95M-BM-0C, as well as 40 cycles of 95M-BM-0C for 15 seconds and 60M-BM-0C for 1 minute. After the superarray protocol was run for each plate, RT-PCR data analysis was performed using the website:http://www.SABiosciences.com/pcrarraydataanalysis.php, in order to compare gene expression of OPNc-overexpressing cells and empty vector transfected cells. Total RNA quality control, cDNA synthesis and the quantitative real-time RT-PCR (qRT-PCR) array were performed as recommended by the manufacturer (Qiagen). Data analysis of gene expression was performed using Excel-based PCR Array Data Analysis Software provided by manufacturer (Qiagen). Fold-changes in gene expression were calculated using the M-NM-^TM-NM-^TCT method, and five stably expressed housekeeping genes (M-NM-22 microglobulin, hypoxanthine phosphoribosyltransferase 1, ribosomal protein L13a, GAPDH and M-NM-2-actin) were used to normalize the level of expression. The statistical analysis was performed to compare the gene expression values for the OPNc-overexpressing cells and those transfected with empty vector. P<0.05 was considered statistically significant. Only genes showing a 1.5-fold or greater change were considered for further analysis.

Project description:CD8+ and CD4+ T cells from HIV infected patients with HIV-RNA viremia of >50 copies/ml and CD8+ and CD4+ T cells from healthy controls were isolated by negative selection (Miltenyi Biotech, Auburn, CA). Cell sorting of the CD4 and CD8 T cell subsets were performed based on surface staining of CD3+CD8+ or CD3+CD4+ and na ve CD45RA+CD27+CD127highHLA-DRlow, and CD3+CD8+ or CD3+CD4+ and memory CD45RA-CD27+CD127highHLA-DRlow. Sorted cell populations were spun down and stored as dry pellets at -80M-BM-0C. Samples analyzed by transcript levels of genes related to cytokine signaling were determined by the JAK/STAT Signaling Pathway microarray. CD8+ and CD4+ T cells from HIV infected patients with HIV-RNA viremia of >50 copies/ml and CD8+ and CD4+ T cells from healthy controls were isolated by negative selection (Miltenyi Biotech, Auburn, CA). Cell sorting of the CD4 and CD8 T cell subsets were performed based on surface staining of CD3+CD8+ or CD3+CD4+ and naM-CM-/ve CD45RA+CD27+CD127highHLA-DRlow, and CD3+CD8+ or CD3+CD4+ and memory CD45RA-CD27+CD127highHLA-DRlow. Sorted cell populations were spun down and stored as dry pellets at -80M-BM-0C. Samples analyzed by transcript levels of genes related to cytokine signaling were determined by the JAK/STAT Signaling Pathway microarray (http://www.sabiosciences.com/rt_pcr_product/HTML/PAHS-039A.html, SABiosciences Frederick, MD). Briefly, total RNA was harvested from each individual T cell subset from each patient or healthy control and contaminating DNA was digested with DNase. Messenger RNA was converted to cDNA and loaded onto PCR array plates for quantitative real-time PCR. Quantification of transcript levels was determined by normalizing to 5 housekeeping genes from each individual sample. Relative gene expression levels for each subset were averaged and compared between cell populations from the patient group and healthy controls. Because of the multiple comparisons only p values M-bM-^IM-$ 0.01 were considered significant.

Dataset Information

Expression data from peripheral blood mononuclear cells of subjects supplemented with vitamin C [qPCR array analysis]

Publications

Vitamin C supplementation modulates gene expression in peripheral blood mononuclear cells specifically upon an inflammatory stimulus: a pilot study in healthy subjects.

Similar Datasets

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