| Background: Currently,the cancer with the highest incidence in women is breast cancer,which has become increasingly common and increasing in mortality worldwide over the past decade.According to the latest statistics,the number of patients diagnosed with cancer in 2020 reached 19.3 million,of which 10 million died of cancer,of which breast cancer patients accounted for 11.7% of cases,so breast cancer is also considered to be the cancer with the highest mortality rate among women.Breast microcalcification is an important feature in the diagnosis of early-stage breast cancer and may be the only indication for early-stage breast cancer.In recent years,there has been some research evidence that the formation of calcifications in breast cancer is closely related to epithelial interstitial transformation.At present,with the continuous development of bioinformatics and medicine,medical research at the molecular level is also improving.However,the relationship between microcalcification-related genes and breast cancer has been poorly studied.Objective: In this study,this study explores the correlation between microcalcification-related genes and breast cancer prognosis through bioinformatics technology,and provides a new and more valuable target for the future study of breast cancer screening,prevention and treatment from the field of genetics.Methods: R was used to screen the selected GEO dataset(GSE146558)with significant up-regulated genes and significantly down-regulated differentially expressed genes(DEGs),and the main enrichment pathways of the selected DEGs were obtained by GO and KEGG enrichment analysis.The obtained DEGs were clinically analyzed using the TCGA database,genes related to breast cancer prognosis were obtained,and a risk model was constructed,and the prognosis of breast cancer patients could be predicted according to the risk score.Results: Four significant upregulated genes were preliminarily screened,namely CAPN8(Calpain 8,calpain 8),SYT4(Synaptotagmin 4,synaptic binding protein 4),MALRD1(MAM and LDL receptor class A domains containing 1)and CHGB(Chromogranin B,pheochromogranin b).There were 15 genes significantly downregulated,namely FAM3B(FAM3 metabolic regulatory signaling molecule B),TSPAN5(Tetraspanin 5,transmembrane tetraprotein 5),LAPTM4B(lysosomal protein transmembrane 4 β),APOD(apolipoprotein D),ALOX15B(arachidonic acid15-lipoxygenase type B),FMO1(flavin-containing dimethylaniline monooxygenase 1),PNMA8A(PNMA family member 8A),INAVA(innate immune activator),NETO2(Neuropilin and Tolloid Like 2),CXCL6(C-X-C motif chemokine ligand 6),TENM2(Teneurin Transmembrane Protein 2,tendon neuroprotein transmembrane protein 2),THRSP(thyroid hormone response),HPGD(15-hydroxyprostaglandin dehydrogenase),MUCL1(mucin-like 1),POU2AF1(POU Class 2 Homeobox associated Factor 1,POU Class Homologous Box Correlation Factor 1).Through enrichment analysis,it was found that the upregulated genes were mainly enriched in the Signaling pathways regulating pluripotency of stem cells,Insulin secretion,Cytokine-cytokine receptor interaction,Signaling pathways such as Adrenergic signaling in cardiomyocytes.The downregulated genes were mainly enriched in Cytokine-cytokine receptor interaction,PI3K/Akt signaling pathway,and Viral protein interaction with cytokine and cytokine receptor(interaction of viral proteins with cytokines and cytokine receptors,Neuroactive ligand-receptor interaction),Human papillomavirus infection and other signaling pathways.Further studies on differential expression and survival analysis screened three genes that were clearly associated with breast cancer prognosis,namely CXCL6,APOD and LAPTM4 B.The risk model was constructed,and the results showed that the expression of APOD,the age of patients,and the N and M stages could be used as independent influencing factors to predict the prognosis of patients.Conclusion: According to the results of enrichment analysis and the existing research results,it is believed that the PI3K/Akt signaling pathway and the signaling pathway regulating stem cell pluripotency(TGF-β signaling pathway are closely related to the signaling pathway formed by microcalcification.The results of the prognostic model showed that the expression of APOD,the age of the patient,and the NM stage were independent influencing factors of breast cancer,which could predict the prognosis of breast cancer patients. |
