GSE113863
An assessment of prognostic immunity markers in breast cancer
We used Targeted RNA-seq to generate a gene expression data set of the 72-gene panel (TARGETSEQ) including 483 targeted RNA-seq data of 225 breast cancer FFPE samples from Shanghai and 258 breast cancer FFPE samples from UNC at Chapel Hill. The identified gene panel and risk evaluation model iRDM were developed in training data set AFFY1951 (p<0.0001, n=1951) and further  validated in two other published gene expression datasets including Illumina beads array data METABRIC (p<0.0001, n=1997) and whole transcriptomic mRNA-seq data TCGA (p=0.00019, n=996) and in our own targeted RNA-seq data TARGETSEQ (p<0.0001, n=303) (of 483 RNA-seq samples, 303 with survival data). In conclusion, immunity gene expression were an important parameter for prognosis and therefore can be incorporated into current multi-gene assays to improve assessment of risk of distant metastasis in breast cancer. Overall design: Gene expression were detected using Targeted RNA-seq. The fastq files were mapped to know region of human genome and gene expression raw counts were obtained and further processed using edgeR and DWD software. The normalized expression data were used for breast cancer subtype classification and risk stratification.