Jones Blake, Thomas Georgia, Westreich Jared, Nofech-Mozes Sharon, Vitkin Alex, Khorasani Mohammadali
Department of Medical Biophysics, University of Toronto, 101 College St, Toronto, ON M5G 1L7, Canada.
Authors contributed equally.
Biomed Opt Express. 2020 May 21;11(6):3246-3262. doi: 10.1364/BOE.392722. eCollection 2020 Jun 1.
As a leading cause of death in women, breast cancer is a global health concern for which personalized therapy remains largely unrealized, resulting in over- or under-treatment. Recently, tumor stroma has been shown to carry important prognostic information, both in its relative abundance and morphology, but its current assessment methods are few and suboptimal. Herein, we present a novel stromal architecture signature (SAS) methodology based on polarized light imaging that quantifies patterns of tumor connective tissue. We demonstrate its ability to differentiate between myxoid and sclerotic stroma, two pathology-derived categories associated with significantly different patient outcomes. The results demonstrate a 97% sensitivity and 88% specificity for myxoid stroma identification in a pilot study of 102 regions of interest from human invasive ductal carcinoma breast cancer surgical specimens (20 patients). Additionally, the SAS numerical score is indicative of the wide range of stromal characteristics within these binary classes and highlights ambiguous mixed-morphology regions prone to misclassification. The enabling polarized light microscopy technique is inexpensive, fast, fully automatable, applicable to fresh or embedded tissue without the need for staining and thus potentially translatable into research and/or clinical settings. The SAS metric yields quantifiable and objective stromal characterization with promise for prognosis in many types of cancers beyond breast carcinoma, enabling researchers and clinicians to further investigate the emerging and important role of stromal architectural patterns in solid tumors.
作为女性主要死因之一,乳腺癌是一个全球健康问题,其个性化治疗在很大程度上仍未实现,导致治疗过度或不足。最近,肿瘤基质已被证明在其相对丰度和形态方面都携带重要的预后信息,但其目前的评估方法较少且不够理想。在此,我们提出一种基于偏振光成像的新型基质结构特征(SAS)方法,该方法可量化肿瘤结缔组织的模式。我们展示了它区分黏液样和硬化性基质的能力,这是两种与患者预后显著不同相关的病理学衍生类别。在一项对来自人类浸润性导管癌乳腺癌手术标本(20例患者)的102个感兴趣区域的初步研究中,结果显示识别黏液样基质的敏感性为97%,特异性为88%。此外,SAS数值评分表明了这些二元类别内广泛的基质特征,并突出了易于误分类的模糊混合形态区域。所采用的偏振光显微镜技术价格低廉、速度快、完全可自动化,适用于新鲜或包埋组织,无需染色,因此有可能转化为研究和/或临床应用。SAS指标产生可量化和客观的基质特征,有望用于乳腺癌以外的多种癌症的预后评估,使研究人员和临床医生能够进一步研究基质结构模式在实体瘤中新兴的重要作用。