背景:SWI/SNF复合物亚基的异常表达与肿瘤发生密切相关。在胃腺癌中,SMARCA2和SMARCA4亚基改变的临床病理和预后意义尚未得到很好的评估。
方法:我们收集了1271例胃腺癌术后病例,然后构建了组织微阵列(TMA),从中获得SMARCA2和SMARCA4的免疫组化表达。接下来,通过单因素相关分析和多因素logistic回归分析筛选与SMARCA2和SMARCA4丢失相关的变量。然后,我们通过单因素和多因素Cox回归分析确定了与预后相关的变量.最后,我们构建了一个列线图预测模型并对其进行了评估。
结果:SMARCA2和SMARCA4的丢失分别发生在236例(18.57%)和86例(6.77%),分别,包括26例共同损失。经过多变量逻辑回归,与SMARCA2丢失相关的独立变量是T期,分化状态,WHO组织学分类,和EBER。与SMARCA4丢失独立相关的变量是分化状态,WHO组织学分类,PD-L1和MMR。生存分析显示,SMARCA2和SMARCA4丢失组的生存情况比相应的现有组差(分别为P=0.032和P=0.0048)。单变量和多变量Cox分析确定了独立的预后因素,包括年龄,T级,N级,M阶段,SMARCA2和化疗。
结论:SMARCA2和SMARCA4的缺失与分化差相关,导致更糟糕的预后。SMARCA2作为独立的预后因素,结合其他临床病理变量,建立了一个新的列线图预测模型,其性能优于AJCCTNM模型。
BACKGROUND: Aberrant expression of SWI/SNF complex subunits is closely associated with tumorigenesis. The clinicopathological and prognostic significance of altered
SMARCA2 and SMARCA4 subunits has not been well evaluated in gastric adenocarcinoma.
METHODS: We collected 1271 postoperative cases of gastric adenocarcinoma and then constructed tissue microarrays (TMA), from which we obtained the immunohistochemistry expression of
SMARCA2 and SMARCA4. Next, we screened the variables related to the loss of
SMARCA2 and SMARCA4 by univariate correlation analysis and multivariate logistic regression analysis. Then, we identified the variables related to prognosis by univariate and multivariate Cox regression analysis. Finally, we constructed a nomogram prognostic model and evaluated it.
RESULTS: The loss of SMARCA2 and SMARCA4 occurred in 236 (18.57%) and 86 (6.77%) cases, respectively, including 26 cases of co-loss. After multivariate logistic regression, variables independently associated with
SMARCA2 loss were T stage, differentiation status, WHO histological classification, and EBER. Variables independently associated with SMARCA4 loss were differentiation status, WHO histological classification, PD-L1, and MMR. Survival analysis revealed that the SMARCA2 and SMARCA4 lost groups showed worse survival than the corresponding present groups (P = 0.032 and P = 0.0048, respectively). Univariate and multivariate Cox analyses identified independent prognostic factors, including age, T stage, N stage, M stage, SMARCA2, and chemotherapy.
CONCLUSIONS: The loss of
SMARCA2 and SMARCA4 correlated with poor differentiation, leading to a worse prognosis. SMARCA2, as an independent prognostic factor, combined with other clinicopathological variables, established a novel nomogram prognostic model, which outperformed the AJCC TNM model.