Study On The Correlation Between Peripheral Serological Indexes And The Efficacy Of Neoadjuvant Chemotherapy In Breast Cancer

Objective:The data of breast cancer patients who received neoadjuvant chemotherapy(NAC)before surgery were collected for retrospective analysis,and bioinformatics analysis was carried out in conjunction with public databases to screen markers that have predictive value for achieving pathological complete response(pCR)after NAC,and further analyze the mechanism of its impact on the efficacy of NAC.Methods:The data of breast cancer patients who received NAC before surgery in Shanxi Bethune Hospital and Shanxi Provincial Cancer Hospital from January 2014 to July 2022 were collected.According to the pathological examination results,they were divided into five subtypes: HER2 positive,Luminal A type,Luminal B type(HER2 positive),Luminal B type(HER2 negative),and three negative.The different subtypes were analyzed separately;According to the judgment of postoperative pathology on the efficacy of NAC,the patients were divided into pCR group and non pathological complete remission(non pCR)group.The differences of various serological indicators between the two groups were compared,and the indicators that could predict the achievement of pCR after NAC in breast cancer were analyzed.All data were analyzed using the statistical software SPSS 26.0.The statistically significant indicators were analyzed by Logistic regression to explore the independent predictors of reaching pCR after influencing the NAC of breast cancer.Search and select the appropriate data set related to the NAC efficacy of breast cancer from the Gene Expression Omnibus(GEO)database,use R language Limma package to screen differential genes,and draw the heat map and volcano map of differential expression genes.The differently expressed genes construct a Protein-Protein interaction(PPI)network.The PPI network is visualized through Cytascape software,and the dominant differentially expressed genes with the highest interaction relationship are further screened through Cytascape software.The selected dominant differentially expressed genes are used for survival analysis on the GEPIA2(Gene Expression Profiling Interactive Analysis)website,Further screening out genes related to overall survival(OS)and disease-free survival(DFS)of breast cancer.Results:1.All collected breast cancer cases were analyzed.The markers of reaching pCR after influencing breast cancer NAC were: Targeted therapy,Body mass index,neutrophil number,lymphocyte number,Eosinophil,platelet distribution width,platelet to lymphocyte ratio,systemic immune inflammation index,systemic inflammatory response index,lymphocyte to Monocyte ratio,preoperative Ki67,including Targeted therapy,neutrophil number The platelet distribution width and preoperative Ki67 have independent predictive value.2.The pCR rate of patients with different subtypes of breast cancer after receiving NAC was different.Serological markers affecting NAC and reaching pCR were not found in HER2 positive and Luminal A breast cancer.3.The markers that affect the pCR of triple negative breast cancer NAC are: Body mass index,white blood cell count,neutrophil number,neutrophil percentage,Monocyte number,platelet count,platelet distribution width,neutrophil to lymphocyte ratio,derived granulocyte ratio,platelet to lymphocyte ratio,systemic immune inflammation index,and universal immune inflammation value.Among them,Body mass index has independent predictive value.4.The markers affecting the pCR of Luminal B type(HER2 positive)breast cancer NAC are: Targeted therapy,white blood cell count,neutrophil number,neutrophil percentage,lymphocyte number,Monocyte number,average platelet volume,neutrophil to lymphocyte ratio,derived granulocyte ratio,platelet to lymphocyte ratio,systemic immune inflammation index,systemic inflammatory response index,lymphocyte to Monocyte ratio Pan immune inflammation value,among which Targeted therapy has independent predictive value.5.The markers that affect Luminal B type(HER2 negative)breast cancer NAC to reach pCR include white blood cell count and lymphocyte number,which have no independent predictive value.6.The GSE140494 dataset was finally screened from the GEO database,and was divided into pCR group and non pCR group according to whether the pCR of breast cancer was reached after NAC.By analyzing the data of the two groups,64 differential genes were obtained,34 of which were up-regulated genes and 30 were down-regulated genes.7.Three dominant differential genes with high interaction relationship were screened out by Mc Creeght(MCC)algorithm in Cytoscape,namely CCL18,CXCL9 and CXCL10.Patients with high expression of these genes in breast cancer are more likely to reach pCR after NAC.8.Through the survival analysis in GEPIA2 website,we analyzed the correlation between the above three dominant differential genes and prognosis,and found that breast cancer patients with CXCL9 overexpression also had better DFS and OS.Conclusions:There are significant differences in the pCR rate of different subtypes of breast cancer after NAC.The serological markers that predict the pCR rate of different subtypes of breast cancer after NAC are different.Through bioinformatics analysis,new biomarkers can also be found.