Prognostic Of Early Breast Cancer And Predictive Factors Of Neoadjuvant Chemotherapy Efficacy

Background:The identification of biomarkers and clinical indicators for predicting the risk of recurrence and treatment response in breast cancer(BC)is critical for the determination of patients’ risk of metastasis and treatment sensitivity,as well as the identification of the optimal treatment regimen.The tumor microenvironment(TME)is composed of extracellular matrix with endothelial progenitor cells,immune cells,growth factors,and cytokines,and includes a wealth of information on tumor-related biomarkers.In particularly,attention has recently been directed to the stromal components and immune cells in the TME for biomarker identification,due to their associations with tumor progression and metastasis.Several immunomodulatory drugs have been proposed for the treatment of BC,and the value of multigene testing in decision-making for adjuvant chemotherapy for early BC patients has gained wide recognition in recent years.This suggests that genetic screening for prognostic markers based on immune and microenvironment-related genes in BC may have significant potential.On the other hand,chemotherapy itself can cause significant disruption and remodeling of the TME,especially in patients receiving neoadjuvant chemotherapy(NCT).NCT is systemic chemotherapy administered before surgery for patients with no distant metastases at the time of initial diagnosis.NCT has the advantages of "down-staging surgery","down-staging breast conservation","obtaining in vivo drug sensitivity information",and "guiding the adjustment of the subsequent treatment plan".The reprogramming of tumor cells and their TME caused by chemotherapy leads to doubt about the accuracy of biomarkers for predicting prognosis.Therefore,in patients treated with NCT,a stable clinical prognostic assessment index that can both guide the implementation of surgical protocols after NCT and retain the clinical efficacy of biomarkers would be valuable.The SENTINA,ACOSOG Z1071,and SN FNAC studies evaluated the safety and feasibility of sentinel lymph node biopsy(SLNB)in patients with positive axillary lymph nodes(c N+)who were down-staged to lymph node-negative(c N0)post-chemotherapy.Axillary lymph node dissection can be dispensed if the SLNB is negative,thus reducing the incidence of complications such as upper limb edema.However,because of the high risks of false-negative SLNB after chemotherapy and insufficient long-term survival data during the actual operation,the procedure of axillary preservation after chemotherapy is still controversial.Therefore,screening NCT-sensitive patients and reducing the risk of missed SLNB-positive lymph nodes after chemotherapy are important for the formulation of post-chemotherapy breast and axillary surgery and the adjustment of subsequent treatment plans.Therefore,in this study,we conducted a series of in-depth investigations of TME-related genetic prognostic markers,NCT outcome prediction,and surgical strategies for axillary lymph node management after chemotherapy,aiming to explore the most accurate and stable prognostic indicators for BC patients receiving different treatment regimens,leading ultimately to the practice of precision medicine.Purpose:I)To explore the prognostic significance of TME-related genes in early breast cancer;II)To explore the correlation between NLR and the efficacy of NCT in breast cancer;III)To explore the factors associated with pathologic complete response(p CR)of axillary lymph nodes after NCT in c N+ patients.Methods:The transcriptomic and clinicopathological data of BC patients were downloaded from The Cancer Genome Atlas(TCGA)and the ESTIMATE algorithm was used to assess the level of stromal and immune cell infiltration in the tumor tissue.To screen for genes expressed differentially(DEGs)between immune cells and stroma,we conducted a differential analysis of the m RNA expression profiles of patients with different immune/stromal scores using the "edge” package in R.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)analyses were used to identify the potential functions of the DEGs.Univariate Cox regression,using the R package “survival” was used to screen candidate DEGs for model construction and the candidate genes were optimized using least absolute shrinkage and selection operator(LASSO)regression analysis.After successful model construction,the prognostic risk score of patients was calculated using the following equation: Risk score = gene 1*β1 + gene 2*β2 +...Gene n*βn,where β represents the regression coefficient of each relevant gene calculated based on the training set.Further,CIBERSORT analysis,Principal Component Analysis(PCA),and Gene Set Enrichment Analysis(GSEA)were used to assess the differences in the lymphocyte subpopulations and gene expression in tumor samples from patients in different risk groups.The chi-square test was used for univariate analysis of categorical clinicopathological variables,binary logistic regression analysis was used for multivariate analysis of screened variables and model construction,and receiver operating characteristic(ROC)curves,concordance index(C-index),k-fold cross-validation,and bootstrapping validation were used to evaluate and validate the model.Survival analysis was performed using Kaplan-Meier curves and Cox regression.Results:Firstly,the identified DEGs were found to be closely associated with the tumor immune response,and the prognostic models successfully constructed by the 12 genes(ASCL1,BHLHE22,C1 S,CLEC9A,CST7,EEF1A2,FOLR2,KLRB1,MEOX1,PEX5 L,PLA2G2D,PPP1R16B)performed well.The immunological status and subpopulations of infiltrating lymphocytes differed significantly between the low-and high-risk patient groups.Secondly,we found higher peripheral blood neutrophil/lymphocyte ratio(NLR) values in young and premenopausal patients,and the NLR,tumor size,hormone receptor(HR)status,and Ki67 status were all found to be important factors influencing the efficacy of NCT.The p CR prediction model based on these four factors was stable and effective and is likely to have important potential clinical significance.Thirdly,this is the first analysis of the factors associated with p CR in lymph nodes after NCT for c N+ BC based on a large Asian sample.The results showed that initial lymph node staging,Ki67,molecular subtype,and breast p CR status were all independent correlates of node p CR.We also successfully developed and validated a predictive model for axillary p CR after chemotherapy in primary c N+ patients,demonstrating both the accuracy and efficiency of the model.Conclusion:The results provide new ideas for the study of TME-related genetic prognostic markers in BC,together with a method for the assessment of NCT-sensitive patients and the optimization of axillary surgery treatment after chemotherapy.