Qian Xu, Xiao Feng, Chen Yuan-Yuan, Yuan Jing-Ping, Liu Xiao-Hong, Wang Lin-Wei, Xiong Bin
Hubei Key Laboratory of Tumor Biological Behaviors, Hubei Cancer Clinical Study Center, Wuhan, China, 430071.
Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China, 430071.
J Cancer. 2021 Apr 19;12(12):3427-3438. doi: 10.7150/jca.55750. eCollection 2021.
Various studies have verified the prognostic significance of the tumor-stromal ratio (TSR) in several types of carcinomas using manually assessed H&E stained histologic sections. This study aimed to establish a computerized method to assess the TSR in invasive breast cancer (BC) using immunohistochemistry (IHC)-stained tissue microarrays (TMAs), and integrate the TSR into a novel nomogram for predicting survival. IHC-staining of cytokeratin (CK) was performed in 7 prepared TMAs containing 240 patients with 480 invasive BC specimens. The ratio of tumor areas and stromal areas was determined by the computerized method, and categorized as stroma-low and stroma-high groups using the X-tile software. The prognostic value of the TSR at 5-year disease free survival (5-DFS) in each subgroup was analyzed. Univariate and multivariate analyses were performed and a novel nomogram for predicting survival in invasive breast cancer was established and assessed. The newly developed computerized method could accurately recognize CK-labeled tumor areas and non-labeled stromal areas, and automatically calculate the TSR. Stroma-low and stroma-high accounted for 38.8% (n = 93) and 61.2% (n = 147) of the cases, according to the cut-off value of 55.5% for stroma ratio. The Kaplan-Meier analysis showed that patients in the stroma-high group had a worse 5-DFS compared to patients in the stroma-low group ( = 0.031). Multivariable analysis indicated that the T stage, N status, histological grade, ER status, HER-2 gene, and the TSR were potential risk factors of invasive BC patients, which were included into the nomogram ( < 0.10 for all). The nomogram was well calibrated to predict the probability of 5-DFS and the C-index was 0.817, which was higher than any single predictor. A dynamic nomogram was built for convenient use. The area under the curve (AUC) of the nomogram was 0.870, while that of the TNM staging system was 0.723. The Kaplan-Meier analysis showed that the nomogram had a better risk stratification for invasive BC patients than the TNM staging system. Based on IHC staining of CK on TMAs, this study successfully developed a computerized method for TSR assessment and established a novel nomogram for predicting survival in invasive BC patients.
多项研究已通过手动评估苏木精-伊红(H&E)染色的组织学切片,证实了肿瘤-基质比(TSR)在几种类型癌症中的预后意义。本研究旨在建立一种计算机化方法,用于通过免疫组织化学(IHC)染色的组织微阵列(TMA)评估浸润性乳腺癌(BC)中的TSR,并将TSR整合到一个用于预测生存的新型列线图中。对7个制备好的TMA进行细胞角蛋白(CK)免疫组化染色,这些TMA包含240例患者的480个浸润性BC标本。通过计算机化方法确定肿瘤面积与基质面积的比值,并使用X-tile软件将其分为基质低和基质高两组。分析了每个亚组中TSR对5年无病生存期(5-DFS)的预后价值。进行了单因素和多因素分析,并建立和评估了一个用于预测浸润性乳腺癌生存的新型列线图。新开发的计算机化方法能够准确识别CK标记的肿瘤区域和未标记的基质区域,并自动计算TSR。根据基质比55.5%的临界值,基质低和基质高的病例分别占38.8%(n = 93)和61.2%(n = 147)。Kaplan-Meier分析显示,基质高组患者的5-DFS比基质低组患者更差(P = 0.031)。多变量分析表明,T分期、N状态、组织学分级、ER状态、HER-2基因和TSR是浸润性BC患者的潜在危险因素,这些因素被纳入列线图(所有P < 0.10)。该列线图校准良好,可预测5-DFS的概率,C指数为0.817,高于任何单一预测指标。构建了一个动态列线图以便于使用。列线图的曲线下面积(AUC)为0.870,而TNM分期系统的AUC为0.723。Kaplan-Meier分析表明,该列线图对浸润性BC患者的风险分层比TNM分期系统更好。基于TMA上CK的免疫组化染色,本研究成功开发了一种用于TSR评估的计算机化方法,并建立了一个用于预测浸润性BC患者生存的新型列线图。