H3.3G34W、p63及SATB2免疫组织化学染色联合应用对骨巨细胞瘤的诊断价值

Diagnostic value of H3.3G34W,p63 and SATB2 immunohistochemical staining combined in giant cell tumor of bone

目的探讨H3.3G34W、p63及SATB2在骨巨细胞瘤(giant cell tumor of bone,GCTB)中的表达情况及其联合应用对GCTB的诊断作用和价值。方法收集西安交通大学附属红会医院病理科2020年至2022年诊断的54例GCTB、83例非骨巨细胞瘤(non-giant cell tumor of bone,NGCTB)(包含14例动脉瘤样骨囊肿、16例软骨母细胞瘤和53例非骨化性纤维瘤)患者的样本和病历资料,采用免疫组织化学EliVision法检测H3.3G34W、p63及SATB2的表达情况。通过χ^(2)检验判断H3.3G34W、p63及SATB2的阳性率在各组间是否存在统计学差异;通过Logistic回归分析建立包括H3.3G34W、p63及SATB2的联合诊断模型,通过受试者工作特征(ROC)曲线分析评价模型的诊断价值。结果H3.3G34W、p63及SATB2在GCTB组中阳性率分别为81.5%、90.7%、92.6%;在NGCTB组中阳性率分别为2.4%、28.9%、62.7%。与NGCTB组相比,GCTB组患者年龄显著较大[(41.222±14.849)vs.(16.566±9.439);P<0.001],女性比男性患病率更高(51.9%vs.48.1%,P<0.001)。与NGCTB组相比,GCTB组中H3.3G34W(81.5%vs.2.4%,P<0.001);p63(90.7%vs.28.9%,P<0.001)和SATB2(92.6%vs.62.7%,P<0.001)的阳性率更高。单因素Logistic回归分析构建单因素预测模型,同时行ROC曲线分析,表明年龄(AUC=92.9%,P<0.001)、性别(AUC=64.5%,P=0.004)、H3.3G34W阳性率(AUC=89.5%,P<0.001)、p63阳性率(AUC=80.9%,P<0.001)、SATB2阳性率(AUC=65.0%,P=0.003)是GCTB诊断的独立预测因素。进一步的多因素Logistic回归分析构建混合预测模型,并行ROC曲线分析,发现混合模型展现出比单因素模型更好的预测价值(AUC=98.4%,P<0.001)。结论H3.3G34W、p63及SATB2是有效诊断GCTB的分子标记物,且三者联合应用更能提高GCTB的诊断预测效能。

Objective To investigate the expressions of H3.3G34W,p63 and SATB2 in giant cell tumor of bone(GCTB)and the effect and value of their combined application in the diagnosis of GCTB.Methods We collected the samples and medical records of 54 cases of GCTB and 83 cases of non-giant cell tumor of bone(14 cases of aneurysmal bone cyst,16 cases of chondroblastoma and 53 cases of non-ossifying fibroma)diagnosed between 2020 and 2022 in the Department of Pathology of Honghui Hospital Affiliated to Xi'an Jiaotong University.The expressions of H3.3G34W,p63 and SATB2 were detected by EliVision immunohistochemical method.χ^(2)test was used to determine whether there are significant differences in the positive rates of H3.3G34W,p63 and SATB2 among all the groups.The combined diagnostic model including H3.3G34W,p63 and SATB2 was established by Logistic regression analysis,and the diagnostic value of the model was evaluated by ROC curve analysis.Results The positive rates of H3.3G34W,p63 and SATB2 in GCTB group were 81.5%,90.7%and 92.6%,respectively;the positive rates in NGCTB group were 2.4%,28.9%and 62.7%.Compared with NGCTB group,the age of GCTB group was significantly older[(41.222±14.849)vs.(16.566±9.439),P<0.001],and the prevalence was higher in women than in men(51.9%vs.48.1%,P<0.001).In addition,compared with the NGCTB group,the positive rates of H3.3G34W(81.5%vs.2.4%,P<0.001),p63(90.7%vs.28.9%,P<0.001)and SATB2(92.6%vs.62.7%,P<0.001)were significantly higher in the GCTB group.Univariate regression analysis built a univariate prediction model and ROC curve analysis showed that age(AUC=92.9%,P<0.001),sex(AUC=64.5%,P=0.004),H3.3G34W positive rate(AUC=89.5%,P<0.001),p63 positive rate(AUC=80.9%,P<0.001)and SATB2 positive rate(AUC=65.0%,P=0.003)were independent predictors of diagnosis of giant cell tumor of bone.Multivariate regression analysis(Logistic)constructed a hybrid prediction model.ROC curve analysis suggested that the hybrid model showed better prediction value than the single factor model(AUC=98.4%,P<0.001).Conclusion H3.3G34W,p63 and SATB2 are effective molecular markers for the diagnosis of GCTB,and their combined application can improve the prediction efficiency of the diagnosis of GCTB.