CK19 Combined With Contrast-enhanced Ultrasound:A Prediction System Of Axillary Lymph Node Metastasis In Breast Cancer

BACKGROUND:Axillary lymph node metastasis is an independent prognostic factor for breast cancer.Therefore,it is very important to determine the statues of axillary lymph nodes before the treatment.The preoperative accurate diagnosis of axillary lymph node metastasis can help neoadjuvant therapy decision,surgical incision design,sentinel lymph node biopsy indication,lymphatic local treatment and postoperative systematic therapy.The evaluation of the axillary lymph node status mainly depends on physical examination,imaging and puncture biopsy,with unsatisfying predicting accuracy.Currently,the prediction model of lymph node metastasis has been reported mainly for sentinel lymph node(SLN)or non-sentinel lymph node(nSLN).But some respective studies reported high false negative rate,larg bias and lack of high-level clinical evidences.At the same time,the prediction model shows a common feature,namely,commonly using clinical examination and immmohistochemical index as parameters,leading to insufficient objective and standards.The liquid biopsy and gene level index were reported effect in small sample basic researches but failed to get a better clinical verification results.CK19 were belong to the type I keratin,almost all expression in breast cancer primary focal organization,but not expression of CK19 were normal lymph nodes,so it is possible that CK19 is to determine whether breast cancer lymph node metastasis a suitable test object.Existing studies prove CK19 mRNA in normal population or not expression in breast benign disease peripheral blood samples in the control group,and in cases of invasive breast cancer,CK19 level in blood has significant correlation with lymph node metastasis and pathological staging.On the other hand,contrast-enhanced ultrasound sonography(CEUS)as a new technology of ultrasonic imaging,can get more information helping the differential diagnosis of benign versus malignant lymph node perfusion,with higher diagnostic sensitivity(84%),specificity(79%)and accuracy(80%)than doppler and usual ultrasound,also better than CT(sensitivity 76.9%)and MR(sensitivity 84%but worse specificity and limited examine range due to the breast coils).These studies provide the basis for us to predict the lymph node metastasis by peripheral blood CK19 and CEUS.This research assumes that the CK19mRNA in peripheral blood combined with CEUS based on clinical data can significantly improve the effect of predicting SLN/nSLN metastasis by establishing a prediction system,which also is comparing with the prediction nomogram of Memorial Sloan Kettering Cancer Center(MSKCC).OBJECTIVE:To combining CK19 mRNA in blood and CEUS score for establish a prediction model system to improve the effect and efficiency of predicting SLN/nSLN metastasis,guiding intraoperative and postoperative axillary processing more accurately.METHODS:1.Validate the feasibility of the detecting peripheral blood CK19 mRNA level by reverse transcription-polymerase chain reaction(RT-PCR),using the biological sample library specimens;To establish CK19 mRNA detection technology standard,and to preliminarily assess the prediction effect of predicting SLN/nSLN metastasis.According to the results,the cut-off value of copies results should be adjusted to establish the scoring standard of CK19.2.According to the guideline and researches previous,to establish CEUS examination standard and score systems for predicting lymph nodes,preliminarily exploring the feasibility of the prediction effect.3.Operable invasive breast cancer patients with cN0 are recruited for stabling the predictiong model(training set).The model is established basing on CK19 and CEUS score using binary Logistic regression(Forward the method to estimate the maximum likelihood ratio),setting up the pathological results of SLN and nSLNs(when SLN+)as golden standard.Preliminarily evaluating the predictive effect of this model.4.Operable invasive breast cancer patients with cN0 are further recuited for a validation set(verification).The probabilities of SLN and nSLN involvement are calculated by our model and MSKCC nomogram,which are compared for validating the effect and efficiency of predicting lymph node involvement of our model.RESULTS:1.There were 120 cases included from specimens library and CK19 mRNA in peripheral blood were seccussessfuly detected in all specimens.Statuses of lymph node metastasis were divided into three groups,SLN-,SLN+/nSLN-,and SLN+/nSLN+.CK19 mRNA copy number level were significantly higher in SLN+/nSLN+ group than other two goups,which is also validated in multifactor analysis.Based on the actual test results,the definition of CK19 were adjusted for grading more accurately:copy number<500 was defined as negative(0),?500 and<1000 was defined as a weak positive(1),1000 or higher was defined as a strong positive(2 points).With the adjusted CK19 criterion,for SLN prediction the AUC is 0.708(95%CI 0.614?0.803),and for nSLN(when SLN+)the AUC is 0.882(95%CI 0.795?0.968).2.According to the guide and researches previous,the CEUS examination and grading standard were established,random consistency inspection result reported coincidence rate was 93.33%.For SLN prediction the AUC was 0,939(95%CI 0.891?0.986),and for nSLN the AUC was 0.805(95%CI 0.699?0.912).3.From October,2015 to November,2016,a total of 359 cases were included for establishing the model(training set),single factor analysis and multifactor regression analysis showed that age,tumor size,CK19 and CEUS were significant factors influencing lymph node metastasis for the predicting model.For predicting the SLN statues,the sensitivity was 91.36%,false negative rate was 8.64%,specificity was 94.92%,false positive rate was 5.08%,positive predicted value 93.67%,negative predicted value 93.03%;AUC=0.979(95%CI 0.968?0.990,p=0.006).For predicting nSLN(when SLN+),sensitivity was 91.04%,false negative rate was 8.96%,specificity was 90.53%,false positive rate of 9.47%,positive predicted value 87.14%,negative predicted value 93.48%;AUC=0.932(95%CI 0.891?0.973,p=0.000).4.From December,2016 to July,2017,continuous 219 eligible cases were included in the research for model and MSKCC nomogram validation(validation set);For predicting SLN statue:sensitivity was 91.84%,false negative rate was 8.16%,specificity was 96.69%,false positive rate was 3.31%,the AUC of our model was 0.979(95%CI 0.965?0.994),superior to the AUC of MSKCC 0.739(95%CI 0.671?0.806).For predicting nSLN(when SLN+),sensitivity was 95.35%,false negative rate was 4.65%,specificity was 92.73%,false positive rate was 7.27%,positive predicted value was 91.11%,the AUC of our model was 0.945(95%CI 0.896?0.994),superior to the AUC of MSKCC 0.873(95%CI 0.803?0.944).CONCLUSION:This study established a predicting model for SLN and nSLN metastasis based on peripheral blood CK19 and CEUS in operable cN0 breast cancer patients.This model has satisfying sensitivity,false negative rate and AUC in both traing and validating sets,also better than the MSKCC model.It can accurately predict SLN and nSLN statues,with guiding axillary precision processing of clinical practice value.In the later stage,we need to adjust the parameters and enlarge the sample size for further study.