Excavating the pathogenic gene of breast cancer based on high throughput data of tumor and somatic reprogramming

基于肿瘤和体细胞重编程高通量数据挖掘乳腺癌致病基因

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Abstract

Breast cancer (BC) is one of the most common malignancies in female, and has a high mortality rate. The mechanisms of tumorigenesis and reprogramming of somatic cells have a certain degree of similarity. Here, we focus on the relationship between gene expression, signaling pathways and functions in BC compared to induced pluripotent stem cells (iPSCs). We first identified differentially expressed genes (DEGs) common to BC and iPSCs in datasets from GEO and TCGA. We found 22 DEGs that were significantly associated with clinicopathological features and prognosis by performing Kaplan-Meier survival analysis and one-way ANOVA. The results of protein mass spectrometry of tumor stem cells (Mcfips) demonstrated that the proteins encoded by 8 of these DEGs were also differentially expressed. The functional enrichment analysis showed that most of the 30 DEGs were related to collagen and chromatin functions. Our results might offer targets for future studies into the mechanisms underlying tumor occurrence and progression, and our studies could provide valuable data for both basic research and clinical applications of BC.

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