Cluster Of Differentiation 36 And Vitamin D Receptor As Potential Diagnosis And Prognosis Biomarkers For Uterine Smooth Muscle Tumors

Objective:Uterine smooth muscle tumors(USMT)are classified into benign leiomyomas,smooth muscle tumors of uncertain malignant potential(STUMP),and leiomyosarcoma(LMS).Benign leiomyomas include usual-type leiomyoma(ULM)and a group of histopathological uterine leiomyoma variants.Pathomorphological examination remains key to the diagnosis of USMT.However,the overlapping morphologic features often cause diagnostic problems of LMS,especially when differentiating leiomyosarcoma from benign leiomyomas variants and STUMP.The immunohistochemistry(IHC)and molecular tests may become valuable tools to facilitate differential diagnosis.Some biomarkers,such as PR,Ki-67,and p53 have been used in differential diagnosis,but their diagnostic efficacy is limited.Because of this,it is reasonable to look for new IHC biomarkers with higher sensitivity and specificity and explore the useful diagnostic model.It has been reported that cluster of differentiation 36(CD36)and vitamin D receptor(VDR)may be related to the pathogenesis of USMT.The purpose of this study is to explore the application of CD36,VDR and their synergistic role with PR,Ki-67 and p53 in the diagnosis and prognosis of USMT,and to explore their potential relationship with tumor pathogenesis.Methods:We collected 164 cases diagnosed as USMT in the affiliated hospital of Qingdao university,including 30 cases of LMS,15 cases of STUMP,119 cases of benign USMT,including ULM and other variants.As controls,we used 20 myometrial tissue samples.The current classification system of USMT follows the WHO guidelines updated in 2020.Two senior pathologists diagnosed all cases with hematoxylin and eosin(H&E)staining slides.Patients without follow-up information were excluded,and the cut-off for follow-up was February 2022.The following IHC biomarkers were performed: CD36,VDR,Ki-67,PR,and p53.Sanger sequencing was performed on exon 2 of Mediator complex subunit 12(MED12).Statistical analyses were performed using SPSS 26.0.One-Way ANOVA,Kruskal-Wallis test,and Pearson’s chi-square test were used to analyze the difference of each marker between different USMT subtypes.Binary logistic regression was performed to analyze the independent diagnostic markers of LMS and benign USMT.The receiving operator characteristics(ROC)curve and Youden index were used to identify the optimal cut-off values to distinguish between benign and malignant(LMS)tumor types.Independent prognostic factors for LMS were identified using Cox regression analysis.P<0.05 was considered statistically significant.Results:1.There were significant differences in the expression levels of CD36,VDR,Ki-67,PR,and p53 between LMS and other USMT subtypes(P<0.05).There was no significant difference in mutation frequency of MED12 exon 2 between LMS and other USMT subtypes(P>0.05).2.Multivariate logistic regression analysis showed postmenopausal status(OR=5.667,95% confidence interval [CI]=1.154-27.830,P=0.033),low expression of CD36(OR=0.285,95% CI=0.096-0.847,P=0.024),high expression of VDR(OR=3.186,95% CI=1.074-9.452,P=0.037),high expression of Ki-67(OR=3.340,95%CI=1.262-8.838,P=0.015),low expression of PR(OR=0.293,95% CI=0.126-0.683,P=0.004),and high expression of p53(OR=2.559,95% CI=1.119-5.852,P=0.026)were independent predictors of LMS.The disease probability P estimated by this diagnostic model has high accuracy in judging whether it is LMS or not.The area under the curve(AUC)of the ROC curve was 0.972,the sensitivity was 93.3%,and the specificity was91.6%.The accuracy of the diagnostic model in diagnosing LMS is significantly higher than that of each variable(P<0.05): CD36(AUC=0.739),VDR(AUC=0.727),Ki-67(AUC=0.875),PR(AUC=0.756),and p53(AUC=0.774).3.In the Cox multivariable regression,the independent adverse prognostic factors were as follows: high FIGO stage(HR=4.102,95% CI=1.345-12.515,P=0.013),low expression of VDR(HR=0.391,95% CI=0.189-0.812,P=0.012),and PR negative expression(HR=0.124,95% CI=0.023-0.656,P=0.014).Conclusion:1.The results suggest that CD36 and VDR are potential biomarkers for USMT diagnosis and can be used as part of the diagnostic model.The diagnostic model combined with menopausal status,CD36,VDR,Ki-67,PR,and p53 has significantly higher accuracy in diagnosing LMS than each variable.2.The mutation in exon 2 of MED12 did not reach statistical significance in the differential diagnosis of LMS and benign USMT.3.In addition,the FIGO stage,VDR,and PR are the independent prognostic factors of LMS.High FIGO stage,low VDR expression,and PR negative expression are significantly associated with a shorter overall survival(OS)of LMS.