Ni Yun-Bi, Tsang Julia Y S, Chan Siu Ki, Tse Gary M
Department of Anatomical and Cellular Pathology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China.
Ann Surg Oncol. 2014 Sep;21(9):2928-33. doi: 10.1245/s10434-014-3691-9. Epub 2014 Apr 18.
Histologic grade, TNM stage, and Nottingham Prognostic Index are traditional prognostic tools for breast cancer. "IHC-molecular" classification of breast cancer can also identify patients at different recurrence risks and provides insight into cancer therapy. However, cancers in each group are heterogeneous. A model based on the comprehensive analysis of morphologic features and molecular subtype was constructed to predict recurrence and refine these traditional prognostic tools.
Morphologic features including histologic grade, fibrotic focus, extensive intraductal component, lymphocytic infiltrate, lymphovascular invasion, tumor necrosis, tumor margin and TNM stage, and molecular subtypes approximated by immunohistochemistry were analyzed in 633 patients with invasive breast carcinoma (excluding those with HER2 targeted therapy). Significant independent predictors for recurrence included: high histologic grade (p = 0.004), presence of lymphovascular invasion (p = 0.004), fibrotic focus (p = 0.020), mild lymphocytic infiltrate (p = 0.013), high TNM stage (p < 0.001), and HER2-overexpressing (p = 0.004) and basal-like (p < 0.001) molecular subtypes. A morphologic-molecular recurrence predictive model based on these features was useful in recurrence prediction, independent of treatment modalities, and was able to refine the traditional prognostic tools of histologic grade, TNM stage, and Nottingham prognostic index, particularly for intermediate-risk groups, and to refine the luminal group molecular subtypes. Such findings were reproducible with a validation cohort.
TNM stage, histologic grade, lymphovascular invasion, fibrotic focus, mild lymphocytic infiltrate, HER2-overexpressing and basal-like molecular subtypes were important independent recurrence risk factors for breast cancer. This morphologic-molecular model was robust in recurrence prediction and refined recurrence risk stratified by the traditional prognostic parameters, independent of treatment modalities.
组织学分级、TNM分期和诺丁汉预后指数是乳腺癌传统的预后评估工具。乳腺癌的“免疫组化-分子”分类也能够识别具有不同复发风险的患者,并为癌症治疗提供依据。然而,每组癌症都是异质性的。构建了一个基于形态学特征和分子亚型综合分析的模型,用于预测复发并优化这些传统的预后评估工具。
对633例浸润性乳腺癌患者(不包括接受HER2靶向治疗的患者)的形态学特征进行分析,包括组织学分级、纤维化灶、广泛导管内成分、淋巴细胞浸润、淋巴管浸润、肿瘤坏死、肿瘤边界和TNM分期,以及通过免疫组化评估的分子亚型。复发的重要独立预测因素包括:高组织学分级(p = 0.004)、淋巴管浸润(p = 0.004)、纤维化灶(p = 0.020)、轻度淋巴细胞浸润(p = 0.013)、高TNM分期(p < 0.001),以及HER2过表达(p = 0.004)和基底样(p < 0.001)分子亚型。基于这些特征的形态学-分子复发预测模型在复发预测中有效,独立于治疗方式,能够优化组织学分级、TNM分期和诺丁汉预后指数等传统预后评估工具,尤其是对中风险组,并细化管腔型分子亚型。这些结果在验证队列中具有可重复性。
TNM分期、组织学分级、淋巴管浸润、纤维化灶、轻度淋巴细胞浸润、HER2过表达和基底样分子亚型是乳腺癌重要的独立复发危险因素。这种形态学-分子模型在复发预测中表现稳健,优化了传统预后参数分层的复发风险,且独立于治疗方式。