| Background Breast cancer(BC)is the most common cancer among women in the world.As an aggressive subgroup of breast cancer,the incidence rate and mortality of triple negative breast cancer(TNBC)continue rising all around the world,reflecting the strong invasive and metastatic characteristics of the cancer.So far,chemotherapy is still the main treatment option for TNBC.In view of the lack of treatment methods for TNBC,it is urgent to explore new targets to improve the prognosis of TNBC,and it is necessary to establish effective models to make targeted treatment more feasible.With the rapid development of second-generation sequencing technology,more and more previously unknown transcripts have been identified.Non-coding RNA(nc RNA)is one of the transcripts mentioned above,which cannot be translated into protein due to the lack of open reading frame(ORF),and has been proved to play a crucial role in regulating tumorigenesis and malignant behavior.Circular RNA(circ RNA)is a kind of non-coding RNA with covalent closed loop structure,although existing reports have confirmed that circ RNA is translatable.Compared with linear RNA,circ RNA has no 5 ’cap or 3’ tail,which is characterized by longer half-life,higher evolutionary conservatism and stronger resistance to ribonuclease R(RNase R).More and more evidences emphasize the indispensable regulatory role of circ RNA in carcinogenesis and development,especially through sponge function acting on micro RNAs(mi RNAs)to regulate downstream genes.Circ RNA is expected to become a potential diagnostic biomarker and therapeutic target for various malignant tumors.Combined with bioinformatics,the analysis of circ RNA and downstream target genes may play a role in promoting the diagnosis and treatment of TNBC.MethodsDownload the original gene expression data(n=1226)of breast cancer from the database of the Cancer Genome Atlas(TCGA),process the data in R language and conduct normalization,select patients whose estrogen receptor(ER),progesterone receptor(PR)and the epidermal growth factor receptor-2(HER-2)receptor column are negative.According to clinical information,116 TNBCs and 11 paracancerous samples were screened,and 60660 m RNA expression matrices were obtained.2577 differentially expressed m RNA were obtained by differential analysis of R language "edge" R package(| log FC |>1,P<0.05).GSE165884 was obtained from GEO database.The data set includes cancer tissue samples from 4 BC patients and adjacent non-tumor tissue samples.1913 differentially expressed circ RNAs were obtained from13617 circ RNAs,of which 812 were up-regulated and 1101 were down-regulated(log FC |>1,P<0.05).Among the differentially expressed circ RNAs,4 up-regulated and4 down-regulated circ RNAs with the highest difference multiple and the lowest P value were selected for further study.118 mi RNAs targeted by 8 circ RNAs were obtained from the Circinteracome database.According to the Mirwalk database,850 m RNAs targeted by 118 mi RNA were obtained.By crossing 2577 differentially expressed m RNA and 850 targeted m RNA through Venn,60 TNBC prognostication-related circ RNA-targeted m RNA were obtained,and the TNBC prognostication-related circ RNA-mi RNA-m RNA ce RNA network was constructed and visualized using Cytoscape software.The String database was used to mine the interaction relationship of m RNAs in the ce RNA network,and the protein-protein interaction networks(PPI)were constructed,The Kyoto Encyclopedia of Genes and Genomes(KEGG)and Gene Ontology(GO)were used to analyze the pathways and functions of m RNAs.The target genes were obtained by single factor cox,multiple factor cox and Lasso regression analysis,and the risk model related to the prognosis of TNBC was constructed according to the target genes.Subsequently,the prediction ability of the model is evaluated through the Receiver Operating Characteristic Curve(ROC).ResultsThe circRNA-miRNA-mRNA ceRNA network composed by 6 circRNAs,8 mi RNAs and 31 m RNA was obtained through analysis.A prediction model consisting of three target m RNA was constructed by single-factor cox,multi-factor cox and lasso regression analysis of differentially expressed m RNA.The AUC values of three and five years were 0.757 and 0.848,respectively,indicating its sensitivity and specificity in the prognosis of TNBC.ConclusionsThis study has established a TNBC-related ceRNA regulatory network of circ RNAmi RNA-m RNA,and found that circ RNA-targeted genes affect tumor progression by regulating cell migration,forming plasma membrane,synthesizing protein and phosphatidylinositol 3 kinase-protein kinase B(PI3K-AKT)signal pathway.The survival prediction model based on SLC4A4,ADAM19,TMEM26 and proved that it is significantly related to the prognosis of TNBC,and can be used as a biomarker for predicting the prognosis of patients with TNBC,thus contributing to the individualized diagnosis and treatment of patients with different risks. |
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