Department of Cellular Pathology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Headley Way, Headington, Oxford, OX3 9DU, UK.
Present Address: Institute of Cancer Research, London and Royal Free London NHS Foundation Trust, London, UK.
Breast Cancer Res. 2018 Feb 5;20(1):11. doi: 10.1186/s13058-018-0934-x.
As only a minor portion of the information present in histological sections is accessible by eye, recognition and quantification of complex patterns and relationships among constituents relies on digital image analysis. In this study, our working hypothesis was that, with the application of digital image analysis technology, visually unquantifiable breast cancer microarchitectural features can be rigorously assessed and tested as prognostic parameters for invasive breast carcinoma of no special type.
Digital image analysis was performed using public domain software (ImageJ) on tissue microarrays from a cohort of 696 patients, and validated with a commercial platform (Visiopharm). Quantified features included elements defining tumour microarchitecture, with emphasis on the extent of tumour-stroma interface. The differential prognostic impact of tumour nest microarchitecture in the four immunohistochemical surrogates for molecular classification was analysed. Prognostic parameters included axillary lymph node status, breast cancer-specific survival, and time to distant metastasis. Associations of each feature with prognostic parameters were assessed using logistic regression and Cox proportional models adjusting for age at diagnosis, grade, and tumour size.
An arrangement in numerous small nests was associated with axillary lymph node involvement. The association was stronger in luminal tumours (odds ratio (OR) = 1.39, p = 0.003 for a 1-SD increase in nest number, OR = 0.75, p = 0.006 for mean nest area). Nest number was also associated with survival (hazard ratio (HR) = 1.15, p = 0.027), but total nest perimeter was the parameter most significantly associated with survival in luminal tumours (HR = 1.26, p = 0.005). In the relatively small cohort of triple-negative tumours, mean circularity showed association with time to distant metastasis (HR = 1.71, p = 0.027) and survival (HR = 1.8, p = 0.02).
We propose that tumour arrangement in few large nests indicates a decreased metastatic potential. By contrast, organisation in numerous small nests provides the tumour with increased metastatic potential to regional lymph nodes. An outstretched pattern in small nests bestows tumours with a tendency for decreased breast cancer-specific survival. Although further validation studies are required before the argument for routine quantification of microarchitectural features is established, our approach is consistent with the demand for cost-effective methods for triaging breast cancer patients that are more likely to benefit from chemotherapy.
由于组织切片中只有一小部分信息是肉眼可识别的，因此识别和量化成分之间的复杂模式和关系依赖于数字图像分析。在这项研究中，我们的工作假设是，通过应用数字图像分析技术，可以严格评估和测试肉眼无法量化的乳腺癌微观结构特征，作为非特殊类型浸润性乳腺癌的预后参数。
使用公共领域软件（ImageJ）对 696 例患者的组织微阵列进行数字图像分析，并使用商业平台（Visiopharm）进行验证。定量特征包括定义肿瘤微结构的元素，重点是肿瘤-基质界面的程度。分析了四种免疫组织化学替代物分子分类中肿瘤巢微观结构的差异预后影响。预后参数包括腋窝淋巴结状态、乳腺癌特异性生存和远处转移时间。使用逻辑回归和 Cox 比例模型评估每个特征与预后参数的关联，该模型调整了诊断时的年龄、分级和肿瘤大小。
大量小巢的排列与腋窝淋巴结受累有关。这种关联在 luminal 肿瘤中更强（巢数每增加 1 个标准差的优势比（OR）=1.39，p=0.003；OR=0.75，p=0.006，用于平均巢面积）。巢数也与生存相关（风险比（HR）=1.15，p=0.027），但在 luminal 肿瘤中与生存最显著相关的是总巢周长参数（HR=1.26，p=0.005）。在相对较小的三阴性肿瘤队列中，平均圆度与远处转移时间（HR=1.71，p=0.027）和生存（HR=1.8，p=0.02）相关。
我们提出，肿瘤在少数大巢中的排列表明转移潜力降低。相比之下，在许多小巢中的组织表明肿瘤具有增加的向区域淋巴结转移的潜力。小巢中伸展的模式赋予肿瘤降低乳腺癌特异性生存的趋势。虽然在常规量化微观结构特征的论点得到确立之前需要进一步的验证研究，但我们的方法符合对化疗获益可能性更高的乳腺癌患者进行成本效益高的分类方法的需求。
