Identification And Initial Validation Of Prognostic-related Hub Genes For Breast Cancer

Breast cancer is the most prevalent malignancy with a high mortality rate among women worldwide.The molecular mechanisms of breast cancer are still needs further elucidation,and effective biomarkers for diagnosis,prognosis and molecular typing are also lacking clinically.Identificaton of tumor-associated hub genes can not only provide candidate molecules for disease molecular mechanism studies,but also facilitate the discovery of potential biomarkers.Therefore,this paper aims to use the rich transcriptomic data to screen the potential hub genes of breast cancer by integrating a variety of bioinformatics analysis methods.On the one hand,the biological function analysis and verification of hub gene were conducted,and on the other hand,the hubs genes were exploited to carry out the research of breast cancer diagnosis,prognosis and molecular typing.The experimental data are as follows:1.First,a total of 512 robust differentially expressed genes were identified from integrated analysis of eight breast cancer datasets in the GEO database.The breast cancer hub gene EZH2 was identified based on the protein interaction network.Five hub genes,namely,CENPL,ISG20L2,LSM4,MRPL3 and CCDC69,were identified based on the weighted gene co-expression network for the subsequent analysis.2.Four genes,CENPL,ISG20L2,LSM4 and MRPL3,were significantly upregulated in breast cancer tumor cells and tissues,and were closely associated with multiple clinicopathological variables.The ROC analysis and prognostic analysis showed that the four genes are potential diagnostic and prognostic biomarkers for breast cancer.Biological functional analysis revealed that all these four genes are involved in the tumor cell proliferation process.3.MRPL3 knockdown suppresses cell biological behaviors such as cell proliferation and cell migration,and its molecular mechanisms are involved in the p38 MAPK signaling pathway.4.CCDC69 was significantly downregulated in breast cancer and was strongly associated with clinicopathological variables and prognosis.Biological function analysis showed that CCDC69 was associated with anti-tumor immunity in breast cancer.A total of 2123 breast cancer samples were divided into two subtypes based on tumor microenvironment immune status and immune checkpoint expression characteristics.ROC analysis shows that CCDC69 can distinguish the two subtypes samples well(AUC ＞ 0.8),suggesting that the CCDC69 is a valid biomarker to evaluate the immune status and immune checkpoint characteristics of breast cancer.Based on cold-and-hot tumor analysis,it also showed that CCDC69 enhanced anti-immunotherapy.Finally,CCDC69-overexpressing cell lines were constructed and transcriptome sequencing indicate that CCDC69 is an important driver gene for immune regulation in breast cancer.5.A prognostic markers of breast cancer were constructed based on five hub genes(SORBS1,CCDC69,ERCC6 L,RACGAP1 and CCNB1).The results showed that the prognostic markers could well classify breast cancer samples into high-risk and low-risk groups with significant differences in survival.This risk marker is associated with the PAM50 molecular typing of breast cancer.We build a prognostic nomogram that can be used to predict the prognosis of breast cancer patients at 1,3,5 and 10 years based on prognostic markers and clinical variables.The prognostic nomogram shows a satisfactory prediction value of patient outcomes.In conclusion,five breast cancer hub genes were identified by integrating transcriptomic data from multiple breast cancer datasets.On one hand,it provides a theoretical basis for studying the molecular mechanism of breast cancer.On the other hand,it provides candidate biomarkers for breast cancer.Importantly,CCDC69 was identified as an important driver gene of immune regulation in breast cancer,and can it can be used as an effective biomarker to evaluate the immune microenvironment status and immune checkpoint features of breast cancer.In addition,the risk score and the nomogram constructed based on breast cancer hub genes that are used to evaluate breast cancer prognosis may have important guiding significance for the clinical precision treatments of breast cancer.