Objective To construct a risk score model for basement membrane-related genes(BMRGs)in triple-negative breast cancer(TNBC).Methods The TNBC risk score model based on BMRGs was established in the cancer genome atlas(TCGA)cohort by the LASSO-COX regression machine learning method,and verified in the Yau-2010 cohort and the molecular taxonomy of breast cancer international consortium(METABRIC)cohort.A nomogram containing BMRG risk score and clinical factors was constructed to predict the survival prognosis of TNBC patients.Based on the functional annotations of gene ontology(GO)and the Kyoto encyclopedia of genes and genomes,KEGG and Gene Set Enrichment Analysis(GSEA)were used to explore differences in protein functional enrichment in risk subgroups.The Immuno-Oncology Biological Research(IOBR)package was used to explore differences in immune infiltration based on risk subgroups.The Mutation Annotation Format Tools(Maltools)package was used to explore genomic changes.Finally,based on the cancer therapeutics response portal(CTRP)and the cancer single-cell expression map(CSEP)to explore differences in drug sensitivity and single-cell expression status in risk score subgroups.Results Six BMRGS-constructed risk subgroups were identified by Kaplan-Meier(KM)survival analysis and LASSO-COX regression analysis and were closely related to the prognosis of TNBC patients(all P<0.001).Among them,SDC1 and ADAM9 were poor prognostic factors,HAPLN1,FREM1,FBLN5 and ITGB4 were protective prognostic factors.The combination of BMRGs risk score and TNM tumor stage has excellent predictive ability for the prognosis of TNBC patients.Protein function analysis showed that the up-regulated genes in the high-risk group were enriched in the pathways and biological functions of neuroactive ligand-receptor interactions,synthesis of various biological complexes,and participation in immune defense responses.Compared with the high-risk group,the infiltration degree of mast cells and cytotoxic lymphocytes was higher in the low-risk group.The genetic map revealed that the most frequently mutated genes in the high-low-risk subgroups were not identical Drug sensitivity analysis showed that patients in the high-risk group had higher sensitivity to bortezomib,fluvastatin,and ouabain(all P<0.05).Patients in the low-risk group had higher sensitivity to nintedanib,BRD-A86708339,and vandetanib(all P<0.05).Single-cell analysis showed that the above six genes were highly expressed in TNBC tumor cells.Conclusion The risk score based on BMRGs was constructed and validated to provide effective biological indicators for predicting the survival and prognosis of TNBC patients.

Objective To construct a risk score model for basement membrane-related genes(BMRGs)in triple-negative breast cancer(TNBC).Methods The TNBC risk score model based on BMRGs was established in the cancer genome atlas(TCGA)cohort by the LASSO-COX regression machine learning method,and verified in the Yau-2010 cohort and the molecular taxonomy of breast cancer international consortium(METABRIC)cohort.A nomogram containing BMRG risk score and clinical factors was constructed to predict the survival prognosis of TNBC patients.Based on the functional annotations of gene ontology(GO)and the Kyoto encyclopedia of genes and genomes,KEGG and Gene Set Enrichment Analysis(GSEA)were used to explore differences in protein functional enrichment in risk subgroups.The Immuno-Oncology Biological Research(IOBR)package was used to explore differences in immune infiltration based on risk subgroups.The Mutation Annotation Format Tools(Maltools)package was used to explore genomic changes.Finally,based on the cancer therapeutics response portal(CTRP)and the cancer single-cell expression map(CSEP)to explore differences in drug sensitivity and single-cell expression status in risk score subgroups.Results Six BMRGS-constructed risk subgroups were identified by Kaplan-Meier(KM)survival analysis and LASSO-COX regression analysis and were closely related to the prognosis of TNBC patients(all P<0.001).Among them,SDC1 and ADAM9 were poor prognostic factors,HAPLN1,FREM1,FBLN5 and ITGB4 were protective prognostic factors.The combination of BMRGs risk score and TNM tumor stage has excellent predictive ability for the prognosis of TNBC patients.Protein function analysis showed that the up-regulated genes in the high-risk group were enriched in the pathways and biological functions of neuroactive ligand-receptor interactions,synthesis of various biological complexes,and participation in immune defense responses.Compared with the high-risk group,the infiltration degree of mast cells and cytotoxic lymphocytes was higher in the low-risk group.The genetic map revealed that the most frequently mutated genes in the high-low-risk subgroups were not identical Drug sensitivity analysis showed that patients in the high-risk group had higher sensitivity to bortezomib,fluvastatin,and ouabain(all P<0.05).Patients in the low-risk group had higher sensitivity to nintedanib,BRD-A86708339,and vandetanib(all P<0.05).Single-cell analysis showed that the above six genes were highly expressed in TNBC tumor cells.Conclusion The risk score based on BMRGs was constructed and validated to provide effective biological indicators for predicting the survival and prognosis of TNBC patients.