Construction Of Sentinel Lymph Node Metastasis Prediction Model(PUMCH-SLN) For Breast Cancer And The Mechanism Of P53/AKT/JAK-STAT Regulatory Network Regulating Immune Escape Of Breast Cancer Cells

Objective:At present,sentinel lymph node biopsy can be performed in patients with suspected axillary lymph node(AlN)negative clinical physical examination,but there are few models to predict the condition of SLN by axillary lymph node ultrasound and tumor pathology.In this study,we compared the ALN status of patients,constructed and validated the predictive system of sentinel lymph node(PUMCH-SLN)metastasis in Peking Union Medical College Hospital(PUMCH).Methods:patients with the sentinel lymph node biopsies in PUMCH from January 1,2014 to December 31,2020 were analyzed retrospectively.The patients were divided into those with suspected ALN by ultrasonography,but the clinical physical examination was negative,and both the ultrasonography and clinical physical examination were negative.1.The ?2 and t tests were used to compare the sonographic and pathological features of lymph nodes.2.The highest efficiency of predicting the sentinel positive rate of non sentinel lymph node metastasis was obtained by ROC curve analysis.The relationship between sentinel lymph node metastasis and non sentinel axillary lymph node metastasis was compared by ?2.3.Using Cox proportional risk regression model,SLN metastasis prediction model was constructed.C statistic and calibration curve are used to evaluate the discrimination and calibration of nomogram.The clinical application was evaluated by decision curve analysis;4.The data of sentinel lymph node biopsy in PUMCH from January 1,2014 to December 31,2020 were used for validation.Results:A total of 2250 patients who underwent sentinel lymph node biopsy were included in the study.Among them,647 cases showed axillary lymph node metastasis by B-ultrasound and 1603 cases showed no axillary lymph node metastasis.The accuracy rate of B-ultrasonography in the diagnosis of axillary lymph node metastasis was 70.93%.Breast ultrasound showed axillary lymph node metastasis patients were divided into training group(n=472)and verification group(n=175).Multivariate analysis showed that histological type(P<0.001),axillary lymph node ultrasound(ALN-US)shape(P=0.034),ALN-US cortical medullary boundary(P<0.001),ALN-US blood flow(P=0.004),PR status(P=0.001)were independent risk factors of lymph node metastasis.Therefore,we put these five risk factors into the model and got the sentinel lymph node metastasis prediction model.The C index of the training group and the verification group were 0.714(95%CI:0.688-0.740),0.816(95%CI:0.784-0.849),respectively.Through ROC curve analysis,we found that when SLNR ratio is greater than 0.333,the diagnostic efficacy of predicting non sentinel axillary lymph node metastasis is the highest,the AUC value is 0.726,and the non sentinel axillary lymph node metastasis in patients with SLNR>0.333 is significantly higher than that in patients with SLNR?0.333(P<0.001).Conclusion:we have established a prediction system of PUMCH-SLN,including PUMCH-SLN nomogram and sentinel lymph node warning rate:sentinel lymph node positive rate is 0.333,which provides a direct and reliable tool for preoperative SLN state prediction and individual evaluation.PUMCH-SLN nomogram shows high net benefit,which can be used as a good supplementary reference for clinical diagnosis of SLN metastasis depending on pathological factors.Its transformative clinical utility and value are not only reflected in the convenience and practicability of preoperative prediction and evaluation,but also in the early warning of false negative SLN patients.At the same time,we found that when the sentinel lymph node positive rate(positive sentinel/total sentinel)was>0.333,the non sentinel axillary lymph node would be more likely to metastasize.This conclusion is helpful to judge whether ALND should be further performed and the precise adjuvant chemotherapy in the high-risk axillary lymph node metastasis patients with 1-2 sentinel lymph nodes metastasis.Objective:in previous studies,we found that the expression of TP53 was related to the prognosis of breast cancer patients.In order to further understand the mechanism of TP53 in breast cancer metastasis,we made a preliminary exploration through further experiments.We used bioinformatics analysis to explore the underlying mechanism and flow cytometry for preliminary verification.Methods:We used the SNP related data and the original mRNA expression data of breast cancer in TCGA database for bioinformatics analysis.The mutant gene was obtained from SNP data of hNSC samples downloaded.Survival analysis was carried out with R-package"survival" package.According to the median value of TP53 expression,patients were divided into high and low groups.Survival analysis was carried out with km method(P<0.05).Then we used flow cytometry to detect PD-L1 expression of p53 wild type(MCF-7 cells)and p53 mutant(MDA-MB231 cells).Results:the results of analysis showed that the high expression of TP53(wild-type p53)was related to the good prognosis,while the low expression of PD-L1 was related to wild-type p53.Flow cytometry showed that PD-L1 of wild-type p53(MCF-7 cells)was not expressed,and PD-L1 of mutant p53(MDA-MB231 cells)was highly expressed.Conclusion:TP53 gene(wild-type p53)may affect the metastasis of breast cancer cells by affecting the expression of PD-L1.Objective:In clinical trials,programmed cell death protein 1(PD-1)ligand(PD-L1)inhibitors have benefited selected patients.In breast cancer,circulating tumor cells(CTCs)are associated with a poor prognosis,but research concerning PD-L1 on CTCs in breast cancer is limited.Molecular targeted therapy requires information on biomarker response to PD-L1 checkpoint inhibitors.This study investigated an association between PD-L1 on CTCs and prognosis and clinicopathological features in breast cancer.Methods:Twenty patients with breast cancer were recruited,and one was excluded for confirmed lymphoma.The PD-L1 mRNA expression on CTCs was analyzed.The chi-squared test was used to determine associations between clinicopathological features and PD-L1 mRNA expression on CTCs.Kaplan-Meier and Cox proportional hazards model analyses were applied to compare the survival of patients and related factors.Results:The follow-up time was 48 months.Of the 19 patients,14 had>1 CTC/10 mL peripheral blood.Among these,each had?1 CTC showing PD-L1.There was no association between PD-L1 expression on CTCs and pathology.Patients with high PD-L1 expression on CTCs or higher T status had poor overall survival(P=0.034 and 0.003,respectively);and these were prognostic factors(P=0.029,0.010),based on a multivariate Cox proportional hazards model.Conclusion:High expression of PD-L1 on CTCs may be a prognostic factor for shorter survival in breast cancer.Objective:To further explore the regulatory mechanism of PD-L1 expression in breast cancer cells.Methods:using TCGA database(http://portal.gdc.cancer.gov/)GDA apps gdc.client-Windows*64.zip,under the guidance of manifest and under the environment of CMD DOS,analyze the clinical parameters of breast cancer patients.The selection of KEGG pathway and GSEA analysis in linkedomics online system were used.Results:the increase of Akt3 copy number in breast cancer was related to the abnormal amplification of PD-L1 gene.In conclusion,Akt may regulate JAK-STAT signaling pathway and affect the expression of PD-L1 on tumor cell surface.Akt3/JAK-STAT signal axis is the signal pathway regulating PD-L1.Conclusion:Akt3/JAK-STAT signal regulatory network may regulate the expression of PD-L1 on the surface of breast cancer cells,and thus mediate tumor immune escape.