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Microarray gene-expression profiles of 69 pancreatic tumors and 61 adjacent non-tumor tissue from patients with pancreatic ductal adenocarcinoma

ABSTRACT: In order to identify biologically relevant tumor markers , we analyzed gene expression profiling of tumor and adjacent non-tumor tissues from PDAC cases. We compared the microarray gene-expression profiles of MIF-high and MIF low expressing tumors as detrmined by qRT-PCR. Affymetrix gene-expression analysis was done in two sets. Affymetrix data from sample number 1-90 were earlier submited by us as GEO accession#: GSE28735. The batch effect between the two sets of data was removed using Partek Genomic Suite and this normalized data was submitted to GEO in this submission. All the analysis was performed using the merged data set. We compared gene expression profile of 69 pancreatic tumor and adjacent non-tumor tissues using Affymetrix GeneChip Human Gene 1.0 ST arrays to identify microRNA targets associated with MIF signaling. Using Partek, we peformed ANOVA and Cox-regression analysis to identify differentially expressed genes that were also associated with survival. The list of genes was then subjected to pathway and biomarker analyses using Ingenuity Pathways Analysis (IPA).

ORGANISM(S): Homo sapiens

SUBMITTER: Perwez Hussain

PROVIDER: E-GEOD-62452 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Microarray gene-expression profiles of 69 pancreatic tumors and 61 adjacent non-tumor tissue from patients with pancreatic ductal adenocarcinoma

Project description:In order to identify biologically relevant tumor markers , we analyzed gene expression profiling of tumor and adjacent non-tumor tissues from PDAC cases. We compared the microarray gene-expression profiles of MIF-high and MIF low expressing tumors as detrmined by qRT-PCR. Affymetrix gene-expression analysis was done in two sets. Affymetrix data from sample number 1-90 were earlier submited by us as GEO accession#: GSE28735. The batch effect between the two sets of data was removed using Partek Genomic Suite and this normalized data was submitted to GEO in this submission. All the analysis was performed using the merged data set.

2016-07-01 | GSE62452 | GEO

microRNA Expression Profiling of MIF-high and MIF-low Pancreatic Ductal Adenocarcinoma using Nanostring nCounter Platform

Project description:We identified differentially expressed microRNAs between MIF-high and MIF-low tumor groups. These microRNAs were then investigated for their potential downstream targets using an integrative strategy, which combines miR-Walk target prediction module and mRNA expression array data to identify key MIF-induced signalling pathways driving tumor progresion and disease aggressiveness. Genes that associated with prognostic significance was then subjected to mechanistic study. miRNA expression profiling of 69 pancreatic ductual adenocarcinoma was performed in two sets. The batch effect between the two sets of data was removed using Partek Genomic Suite

2016-06-01 | E-GEOD-62498 | biostudies-arrayexpress

Microarray gene-expression profiles of 45 matching pairs of pancreatic tumor and adjacent non-tumor tissues from 45 patients with pancreatic ductal adenocarcinoma

Project description:In order to identify biologically relevant tumor markers with prognostic significance, we set out to analyze gene expression profiling of tumor and adjacent non-tumor tissues from PDAC cases. We compared the microarray gene-expression profiles of 45 matching pairs of pancreatic tumor and adjacent non-tumor tissues. This data set were used to obtained genes that were differentially expressed and associated with survival. 51 genes were selected for further validation. 90 total samples were analyzed. We compared gene expression profile of 45 pairs of pancreatic tumor and adjacent non-tumor tissues using Affymetrix GeneChip Human Gene 1.0 ST arrays. Tumor gene expression profiles were distinctly different from non-tumor profiles. Using ANOVA in Partek®, 7352 independent genes were found to be differentially expressed in tumors (P<0.01). We next performed Cox-regression analysis and identified 928 of the differentially expressed genes that were associated with survival (P<0.1). The list of genes was then subjected to pathway and biomarker analyses using Ingenuity Pathways Analysis (IPA). Based on literatures supporting their roles in cancer, 51 genes were selected for further analyses

2012-07-08 | E-GEOD-28735 | biostudies-arrayexpress

Microarray gene-expression profiles of 139 pancreatic tumor,102 adjacent non-tumor tissue from patients with pancreatic ductal adenocarcinoma and 3 normal pancreas from donors.

Project description:In order to identify key pathways associated with disease aggressiveness and therapeutics resistance in the most agrressive subset of PDAC, we analyzed gene expression profiling of tumor and adjacent non-tumor tissues from PDAC cases. Non-negative matrix factorization (NMF) clustering, using gene expression profile form PDAC tumors, revealed three patient subsets. A 142-gene signature specific to the subset with the worst patient survival, predicted prognosis and stratified patients with significantly different survival. Mechanistic and functional analyses of most aggressive subset revealed a HNF1B/Clusterin Axis negatively regulate pancreatic cancer progression and potentially be useful in designing novel strategies to attenuate disease progression. Affymetrix data from from these dataset were partially earlier submited by us as GEO accession#: GSE28735 and GSE 62452. The batch effect between the different sets of data was removed using Partek Genomic Suite and this normalized data was submitted to GEO in this submission.

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microRNA Expression Profiling of MIF-high and MIF-low Pancreatic Ductal Adenocarcinoma using Nanostring nCounter Platform

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MIF promotes cell invasion by LRP1-uPAR interaction in pancreatic cancer cells

Project description:To investigate the role of MIF in the regulation of malignant phenotype of pancreatic cancer , MIF gene has been knocked down by shRNA in PANC-1 cells. We then performed gene expression profiling analysis using data obtained from RNA-seq of shMIF (MIF knockdown) and shNTC (non-targeting control) cells at normoxia and hypoxia.

2022-12-31 | GSE212201 | GEO

Role of Macrophage migration inhibitory factor (MIF) in pancreatic stellate cells (PSCs)

Project description:The presence of activated pancreatic stellate cells (PSCs) in the pancreatic ductal adenocarcinoma (PDAC) microenvironment plays a significant role in cancer progression. Macrophage migration inhibitory factor (MIF) is overexpressed in PDAC tissues and expressed by both cancer and stromal cells. The expression status of MIF and its receptors in PDAC- associated fibroblasts or PSCs and its pathophysiological roles are yet to be elucidated. The next-generation sequencing technique was adapted to check the effect of MIF absence on the expression of other genes in mice (mPSCs).

2022-09-28 | E-MTAB-9392 | biostudies-arrayexpress

Genome-wide analysis of differentially expressed genes and splicing isoforms in clear cell Renal Cell Carcinoma

Project description:In this study we performed a genome wide analysis of the entire complement of mRNAs in clear cell renal cell carcinomas (ccRCC) by means of the Affymetrix Exon Array platform. The analyses were performed both at gene and exon level. Under our parameters over 2,000 genes resulted differentially expressed, and about 250 genes resulted alternative spliced showing differential inclusion of specific cassette exons comparing tumor and non tumoral tissues. 20 total samples were used for exon array analysis: 10 ccRCC tumor sample (T) and their matched non-tumor (NT) kidney tissues samples. All exon array data were analyzed using Partek Genomic Suite 6.4 software (Partek). The robust multi-array average (RMA) algorithm was used for the gene- and exon-level intensity analyses. Data were M-oM-,M-^Altered to consider only those probe sets included in the M-bM-^@M-^\Core Meta-ProbesetM-bM-^@M-^]. Lists of genes and exons with significant variation of the expression levels were generated by using a 0.01 FDR criterion as a significant cutoff. Partek list of significant exon-level probesets (FDR corrected p-value < 0.01) and exon level ANOVA test list were used to create - by an ad hoc Python script - a database of significant probesets from Exon Array experiments. To make more stringent the analysis criteria we excluded from the final exon lists all those cases in which Exon Array revealed a significant change at gene-level. This database we created has been used to explore simple exon skipping events using as reference ASPicDB single exon skipping splicing events after mapping Affymetrix probesets on ASPicDB .gtf files. A single exon from the Partek list was defined significantly skipped only if its adjacent exons were not, by using 0.01 and 0.05 p-value criterions as a significant cutoff for the M-bM-^@M-^\skippedM-bM-^@M-^] and adjacent exons, respectively.

2013-09-06 | E-GEOD-47032 | biostudies-arrayexpress

Macrophage migration inhibitory factor - a therapeutic target in gallbladder cancer

Project description:Poor prognosis in gallbladder cancer is due to late presentation of the disease, lack of reliable biomarkers for early diagnosis and limited targeted therapies. Early diagnostic markers and novel therapeutic targets can significantly improve clinical management of GBC. We carried out quantitative proteomic analysis using a panel of gallbladder cancer cell lines using isobaric tags for relative and absolute quantitation (iTRAQ). We identified 3,655 proteins among which 654 were found to be overexpressed and 387 were downregulated in the invasive cell lines (OCUG-1, NOZ and GB-d1) compared to the non-invasive cell line, TGBC24TKB. Among these, macrophage inhibitory factor (MIF) was observed to be >3-fold overexpressed. MIF is a pleiotropic proinflammatory cytokine that plays a causative role in multiple diseases including cancer. MIF has been reported to play a central role in tumor cell proliferation and invasion in several cancers. Immunohistochemical staining confirmed our findings showing overexpression of MIF in 21 of 29 gallbladder adenocarcinoma cases. A significant decrease in cell viability, colony forming ability and invasive property of the gallbladder cancer cells was observed upon MIF inhibition using MIF siRNA and MIF antagonists. Our findings support the role of MIF in tumor aggressiveness and suggest its potential application as a therapeutic target for gallbladder cancer.

2015-10-02 | PXD001566 | Pride

Gene expression analysis of pancreatic cancer associated fibroblasts

Project description:Gene expression analysis of pancreatic cancer associated fibroblasts and control fibroblasts To identify signaling pathways important in tumor-stromal cell interactions, we performed gene expression profiling on pancreatic cancer associated fibroblast cultures and control fibroblast cultures using Affymetrix Exon arrays. We analyzed 3 control fibroblast cultures and 9 pancreatic cancer associated fibroblast cultures using the Affymetrix Human Exon 1.0 ST platform. Gene expression levels were compared using Partek (version 6.3beta).

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