Transcriptomics,Genomics

Dataset Information

46

Microarray gene-expression data to validate a 17-gene biomarker obtained from excessive meta-analysis to test its PDAC specificity in the presence of pancreatitis tissues.


ABSTRACT: Clinical signs and radiographic findings of PDAC and pancreatitis are often indistinguishable, highlighting the need of a PDAC biomarker to be insensitive to pancreatitis. Therefore we validated a biomarker signature of 17-genes in this gene expression data containing PDAC, non-tumor pancreatic and pancreatitis of fresh-frozen and formalin-fixed paraffin-embedded tissues. Overall design: Total RNA was obtained from 3 FF and 1 FFPE non-tumor pancreatic, 3 FF and 3 FFPE PDAC, 4 FFPE non-tumor pancreatic, and 10 FFPE pancreatitis tissues. Data was quantile normalized and manufactor IDs were matched to unique Entrez IDs using the probe with the largest interquartile range. Subsequently, classification performance of the biomarker genes were tested by distinguishing between PDAC and non-tumor (adjacent pancreas and pancreatitis) tissues.

INSTRUMENT(S): Illumina HumanHT-12 V4.0 expression beadchip

SUBMITTER: Hauke Busch  

PROVIDER: GSE101462 | GEO | 2018-05-11

REPOSITORIES: GEO

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Publications

Identification and Validation of a Diagnostic and Prognostic Multi-Gene Biomarker Panel for Pancreatic Ductal Adenocarcinoma.

Klett Hagen H   Fuellgraf Hannah H   Levit-Zerdoun Ella E   Hussung Saskia S   Kowar Silke S   Küsters Simon S   Bronsert Peter P   Werner Martin M   Wittel Uwe U   Fritsch Ralph R   Busch Hauke H   Boerries Melanie M  

Frontiers in genetics 20180405


Late diagnosis and systemic dissemination essentially contribute to the invariably poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Therefore, the development of diagnostic biomarkers for PDAC are urgently needed to improve patient stratification and outcome in the clinic. By studying the transcriptomes of independent PDAC patient cohorts of tumor and non-tumor tissues, we identified 81 robustly regulated genes, through a novel, generally applicable meta-analysis. Using consensus clust  ...[more]

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