Transcriptomics,Genomics

Dataset Information

45

Gene expression and alternative splicing in pancreatic ductal adenocarcinoma (PDAC) [gene level]


ABSTRACT: Alternative splicing is a key event to human transcriptome and proteome diversity and complexity. Recent evidence suggests that pancreatic cancer might possess particular patterns of splice variation that influence the function of individual genes contributing to tumour progression in this disease. The identification of new pancreatic cancer-associated splice variants would offer opportunities for novel diagnostics and potentially also represent novel therapeutic targets. In this dataset, we investigated the alterations in the splicing machinery in pancreatic adenocarcinoma (PDAC) specimens with full clinicopathological details, in comparisons to adjacent pancreatic tissues and normal tissues from donors. Overall design: We extracted total RNA from 28 PDAC specimens, 4 adjacent tissues and 2 normal pancreatic tissues from donors, and hybridized them to Affymetrix exon arrays. Affymetrix GeneChip® Human Exon 1.0 ST Arrays (Affymetrix, Santa Clara, CA, USA) were used for gene expression and alternative splicing analysis. Labelling and hybridization were performed according to the manufacturer's instructions. After scanning, .CEL files were checked for quality and analysed following the pipeline based on aroma.affymetrix R package, to produce transcript, probeset and probe-level intensities. This was followed by intensity filtering as recommended by Affymetrix. This submission includes the gene-level analysis.

INSTRUMENT(S): [HuEx-1_0-st] Affymetrix Human Exon 1.0 ST Array [transcript (gene) version]

SUBMITTER: Jun Wang  

PROVIDER: GSE56560 | GEO | 2014-11-10

SECONDARY ACCESSION(S): PRJNA243910

REPOSITORIES: GEO

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Publications


Improved usage of the repertoires of pancreatic ductal adenocarcinoma (PDAC) profiles is crucially needed to guide the development of predictive and prognostic tools that could inform the selection of treatment options.Using publicly available mRNA abundance datasets, we performed a large retrospective meta-analysis on 466 PDAC patients to discover prognostic gene signatures. These signatures were trained on two clinical cohorts (n = 70), and validated on four independent clinical cohorts (n = 2  ...[more]

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