Objective To screen the lapatinib resistance-related hub genes of breast cancer by bioinformatics initially in order to lay the foundation for further study. Methods We screened and downloaded the gene expression profile data of GSE16179 and GSE38376 from the gene expression omnibus (GEO), and used the limma package of R software to identify the differential expressed genes (DEGs) in breast cancer cells. Then we used the DAVID online website for pathway and function enrichment. With the usage of STRING and Cytoscape, the protein-protein interaction network (PPI) was constructed, and the plug-in app MCODE in Cytoscape was applied to screen hub genes. Then we performed the function enrichment and co-expression analysis of hub genes by DAVID and GeneMANIA. Kaplan-Meier Plotter was used to conduct survival analysis of hub genes. Results A total of 206 kinds of DEGs were screened, and there were 126 kinds of up-regulated genes and 80 kinds of down-regulated genes. DAVID results showed that DEGs were mainly enriched in the biological processes of extracellular space and extracellular region, including extracellular matrix organization, oxygen binding, integrin binding, cell adhesion, positive regulation of angiogenesis, Hippo signaling pathway, transforming growth factor-β signaling pathway and so on. PPI network visualized 74 nodes, the top 10 kinds of hub genes with high connectivity in the gene expression network were screened by MCODE. The Kaplan-Meier Plotter analysis confirmed that 6 of the 10 kinds of hub genes, including peroxisome proliferator activated receptor gamma, transforming growth factor beta receptor 2, tissue inhibitor of metalloproteinase 1, transforming growth factor beta induced, serpin family E member 1, and thrombospondin 1, were correlated with the prognosis of breast cancer patients. Conclusion This 6 kinds of genes may play a significant role in lapatinib resistance of breast cancer.
Objective To explore the relationship between the metastatic sites and prognosis in newly diagnosed stage Ⅳ breast cancer. Methods The data of newly diagnosed female patients with stage Ⅳ invasive breast cancer with complete follow-up data from SEER database from 2010 to 2015 were grouped according to different metastatic sites, and the differences of breast cancer-specific survival (BCSS) in different metastatic sites were analyzed by univariate and multivariate Cox. Kaplan-Meier method was used to draw the survival curve, and log-rank test was used to analyze the prognostic factors of BCSS in newly diagnosed stage ⅳ breast cancer. Results A total of 8 407 patients were included in the final analysis. Among them, 5 619 (66.84%) patients were confirmed with bone metastasis only, 1 483 (17.64%) patients with lung metastasis only, 1 096 (13.04%) patients with liver metastasis only, and 209 (2.49%) patients with brain metastasis only. The median follow-up time was 22 months, with 4 180 (49.72%) breast cancer-related deaths and a median BCSS of 39 months in those patients. The location of metastasis in newly diagnosed stage Ⅳ invasive breast cancer was significantly correlated with BCSS (χ2=151.07, P<0.001). Multivariate Cox model analysis showed that the BCSS was worse in patients with liver metastasis [HR=1.34, 95%CI (1.21, 1.49), P<0.001], lung metastasis [HR=1.09, 95%CI (1.04, 1.14), P<0.001] and brain metastases [HR=1.28, 95%CI (1.20, 1.36), P<0.001] than in patients with bone metastases. Further subgroup analysis showed that the BCSS of breast cancer patients with different molecular subtypes and different metastatic sites were also significantly different (P<0.05). Patients with brain and liver metastases in the HR+/HER2– subtype had worse BCSS than those with bone metastases (P<0.001). Patients with brain metastases in the HR+/HER2+ subtype had worse BCSS than those with bone metastases (P=0.001). In HR–/HER2+ subtype, the BCSS of patients with liver metastasis, lung metastasis and brain metastasis were worse than that of patients with bone metastasis (P<0.05). In HR–/HER2– subtype, the BCSS of patients with brain metastasis and liver metastasis were worse than that of patients with bone metastasis (P<0.05) . Conclusion The prognosis of newly diagnosed stage ⅳ breast cancer patients with different metastatic sites is different, and the prognosis of different molecular subtypes and different metastatic sites is also different.