014850 whole human genome microarray

Gene expression data set E-MTAB-2325 was downloaded from EBI ArrayExpress database, which was annotated using the platform of GPL6480 (Agilent-014850 Whole Human Genome Microarray 4 × 44 K G4112F). A total of 40 samples were selected out, including 10 normal and 30 SALS motor cortex samples. Raw signal values were thresholded to 1, log2 transformed, normalized to the 50th percentile, and baselined to the median of all samples using GeneSpringGX v.14.5 (Agilent Technologies, Italy). Fold change (FC) values were calculated between SALS patients and individual controls. Positive FC meant over-expression, whereas negative FC indicated under-expression. Probes not corresponding to an ENTREZ ID were removed. In cases where several probes corresponded to one ENTREZ ID, the probe showing the highest variance over all samples was chosen for further analysis. Genes that showed a significant P value < 0.05 (one-way ANOVA followed by the Benjamini and Hochberg False Discovery Rate and the Tukey’s Post Hoc test) and FC ≥ ± 1.5 were considered differentially expressed and were taken for further analysis.

GSEA is a computational method that determines whether an a priori defined gene set shows statistically significant and concordant differences between two biological states [25 (link), 26 (link)]. GSEA computes biological information from different perspectives and further elucidates relevant biological events. The GSE47911 dataset, based on the GPL6480 platform (Agilent-014850 Whole Human Genome Microarray 4 × 44 K G4112F), was also downloaded from the GEO database. This dataset has 15 gastric GIST samples [27 (link)]. Based on the key gene expression level, GIST samples were divided into two groups, after which GSEA was subsequently performed. Annotated gene sets (c2. cp.kegg.v7.2.symbols.gmt [Curated], c2.cp.ractome.v7.2.symbols.gmt [Curated], and c5.bp.v7.2.symbols.gmt. [Gene Oncology]) were chosen as the reference gene sets. Gene size > 20, FDR < 0.05 and normalized enrichment score (NES) > 2.00 were set as the cutoff criteria.

We first downloaded RNA sequencing data of localized prostate cancer and metastatic CRPC in the microarray dataset GSE35988 from two platforms. One is Agilent-012391 Whole Human Genome Oligo Microarray, GPL6848, and the other is Agilent-014850 Whole Human Genome Microarray, GPL6480. As results, 59 samples of localized prostate cancer and 35 samples of CRPC were merged for analysis of DEGs [5 (link)]. Besides, RNA sequencing data of prostate cancer and paracancerous normal tissue from the Illumina HiSeq RNA sequencing platform correlated with the clinical information of The Cancer Genome Atlas (TCGA) database was also downloaded for analysis.
We first performed different expressed analysis using the online tool GEO2R. We set the adjusted p value <0.05 and 2-fold change (|log2FC| ≥ 1) as thresholds for differential expression. We downloaded gene clusters of both drivers and suppressors for ferroptosis from FerrDb V2 and constructed a Venn diagram to extract DEGs correlated with ferroptosis [6 (link)].