基于Logistic回归模型的弥漫性大B细胞淋巴瘤分型研究

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目的:在免疫组化分型的基础上,探讨弥漫性大B细胞淋巴瘤患者石蜡标本基因表达与免疫组化分型之间的关系。方法:收集弥漫性大B细胞淋巴瘤患者石蜡切片,常规免疫组化检测CD10、Bcl-6和MUM1,按Hans分类标准进行亚型分类。石蜡组织中提取RNA,real-time PCR法检测Bcl-2、CCND2、LMO2、FOXP1、Bcl-6、HGAL、FN1、CCL3、MME、MUM1和REL基因的表达。利用Logistic回归建立预测模型,并用ROC曲线对其应用价值进行评价。结果:免疫组化结果显示,CD10阳性率为17.07%,Bcl-6阳性率为78.05%,MUM1阳性率为60.98%,Hans标准分型GCB型24.39%,non-GCB型75.61%。Logistic回归模型单因素分析结果表明,MME、LMO2和Bcl-2基因与DLBCL的免疫分型有关,P<0.05;多因素逐步回归分析显示,MME、LMO2和Bcl-2有显著回归效果,建立预测模型公式P=e-3.946-0.687×Bcl-2+0.199×MME+0.421×LMO2/(1+e-3.946-0.687×Bcl-2+0.199×MME+0.421×LMO2)。ROC曲线显示,该模型的曲线下面积为0.970,灵敏度为0.900,特异度为0.968。该模型判断DLBCL分型与免疫组化的总符合率为95.1%。结论:从石蜡中提取RNA,real-time PCR检测基因表达,建立Logistic回归模型,利用该模型对DLBCL分型是可行的。 OBJECTIVE: To investigate the relationship between the gene expression of paraffin-embedded specimens and the immunohistochemical typing in patients with diffuse large B-cell lymphoma on the basis of immunohistochemical typing. Methods: Paraffin sections were collected from patients with diffuse large B-cell lymphoma. CD10, Bcl-6 and MUM1 were detected by routine immunohistochemistry and classified according to Hans classification criteria. RNA was extracted from paraffin tissues and the expression of Bcl-2, CCND2, LMO2, FOXP1, Bcl-6, HGAL, FN1, CCL3, MME, MUM1 and REL genes was detected by real-time PCR. Logistic regression was used to establish the prediction model, and its application value was evaluated by ROC curve. Results: The positive rate of CD10 was 17.07%, the positive rate of Bcl-6 was 78.05%, the positive rate of MUM1 was 60.98%. The positive rate of Hans was 24.39% for GCB and 75.61% for non-GCB. Logistic regression model of univariate analysis showed that, MME, LMO2 and Bcl-2 gene and DLBCL immune typing, P <0.05; stepwise regression analysis showed that the MME, LMO2 and Bcl-2 significant regression effect, the establishment of a prediction The model equation P = e-3.946-0.687 × Bcl-2 + 0.199 × MME + 0.421 × LMO2 / (1 + e-3.946-0.687 × Bcl-2 + 0.199 × MME + 0.421 × LMO2). The ROC curve shows that the area under the curve of this model is 0.970, the sensitivity is 0.900 and the specificity is 0.968. The model to determine the total coincidence rate of DLBCL typing and immunohistochemistry was 95.1%. Conclusion: RNA was extracted from paraffin and real-time PCR was used to detect gene expression. Logistic regression model was established. DLBCL typing was feasible.
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