Hugene 1.0 st

For Affymetrix Human Genome U133 Plus 2.0, 133A, and HuGene 1.0 ST arrays, probe sets were mapped to gene identifiers using annotations provided by Affymetrix version 35.
TCGA GEP are annotated with ENTREZ identifiers which were converted to HUGO symbols using Homo_sapiens.gene_info (ftp://ftp.ncbi.nih.gov/gene/DATA/GENE_INFO/Mammalia/Homo_sapiens.gene_info.gz; retrieved on 20 May 2015).
When assessing the reproducibility of the selection procedure across microenvironment series, mapping between features was performed as follows. Probesets that are shared between the Affymetrix Human Genome U133 Plus 2.0 and 133A platforms were mapped, while the others were ignored. As HuGene 1.0 ST and Human Genome U133 Plus 2.0 Affymetrix platforms do not share any probe set, probe sets of both platforms mapping to the same gene symbols were mapped between the two platforms.

To identify multi-markers in pancreatic cancer, we used mRNA and miRNA expression data from 104 PDAC patients and 17 normal pancreatic patients, following surgery for kidney stones and non-malignant pancreatic disease at Seoul National University Hospital (SNUH) (The detailed experiment and pre-processing steps are described in [15 ]). All human subjects studies were approved by the Institutional Review Board of Seoul National University Hospital. In this dataset, mRNA and miRNA expression levels were profiled on Affymetrix (Santa Clara, CA, USA) HuGene 1.0 ST (33,297 probes) arrays and Affymetrix GeneChip miRNA 3.0 (25,016 probes) arrays, respectively. We used 5,617 human miRNA probes, out of 25,016 probes, on the Affymetrix GeneChip miRNA 3.0 array.
For validation with independent datasets of selected multi-marker candidates, we collected expression datasets for PDAC (GSE32688 [23 (link)], GSE15471 [24 (link)], and GSE16515 [25 (link)]), lymphoma (LP; GSE14879 [26 (link)]), breast cancer (BC; GSE10780 [27 (link)]), hepatocellular carcinoma (HCC; GSE6764 [28 (link)]), and lung carcinoma (LC; GSE19188 [29 (link)]) from the Gene Expression Omnibus (GEO) [30 (link)]. All collected expressed data were performed using quantile normalization and RMA normalization by R package.