Bacus J W, Bacus J V, Stoner G D, Moon R C, Kelloff G J, Boone C W
Bacus Laboratories, Inc., Elmhurst, Illinois 60126, USA.
J Cell Biochem Suppl. 1997;28-29:21-38.
An assay method that precisely quantitates the cellular and tissue changes associated with early, preinvasive neoplasia is much needed as a surrogate endpoint biomarker (SEB) in clinical trials to predict the potential efficacy of chemopreventive agents in bringing about cancer incidence reduction. Quantification of histological changes at the tissue level are potentially powerful SEB's since these visually apparent changes are common in all neoplastic development, regardless of tissue type or neoplastic cause. Currently, subjective inspection of the histological appearance of sectioned and stained material, or "grading," by experienced pathologists is used to evaluate neoplastic progression. This has well-known limitations of reproducibility, accuracy, and resolution of grading scale. Since neoplastic changes are visually apparent and morphologic in nature, quantification by image analysis is a measurement modality of choice. Image analysis was implemented through the use of high-resolution "tiled" images of complete tissue sections. A histological grading system, or "scale," was developed that could be expressed in terms of normal deviate units of multiple and different morphometric descriptors. Neoplastic growth was characterized quantitatively with multiple measurements on each tissue image tile, which were combined into a single number for each tile, i.e., a histologic grade per tile, and parameters from the distributions of these measurements were used to represent the histologic grade for the entire region considered. This concept provided a uniform final scale in similar units of measurement, regardless of which tissues were graded. Also, the grading scale automatically adjusted measurement variance for different tissues by using normal tissue for each different type to obtain the normalization to standard deviation (z) units. This further defined a uniform final scale and maintained standard references. Using this method, results from two well-known animal models of carcinogenesis, squamous cell carcinoma of SENCAR mouse skin induced by benzo(a)pyrene (B[a]P), and squamous cell carcinoma of the rat esophagus induced by N-nitrosomethylbenzylamine (NMBA), were compared to each other. Image analysis was performed on skin tissue sections from a total of 64 SENCAR mice, and esophagus tissue sections from 96 Fischer-344 rats. In both cases, a quantitative expression of the preinvasive neoplastic response to the carcinogen as a function of time of exposure was expressed along a continuous grading scale in standard deviation units (z). In the SENCAR mouse skin animal model, similar cohorts of 4 mice at 20 weeks showed significant modulation of B[a]P-induced neoplasia by treatment with the antiproliferative agent difluoromethylornithine, P < .05. In the rat esophagus animal model, similar cohorts of 6 rats at 10 and 15 weeks showed significant modulation of NMBA-induced neoplasia by treatment with the antimutagen phenethyl isothiocyanate, P < .05.
在临床试验中，迫切需要一种能够精确量化与早期、侵袭前肿瘤形成相关的细胞和组织变化的检测方法，作为替代终点生物标志物（SEB），以预测化学预防剂在降低癌症发病率方面的潜在疗效。组织水平上组织学变化的量化可能是强大的SEB，因为这些视觉上明显的变化在所有肿瘤发生过程中都很常见，无论组织类型或肿瘤病因如何。目前，由经验丰富的病理学家对切片和染色材料的组织学外观进行主观检查或“分级”，以评估肿瘤进展。这具有众所周知的局限性，包括分级的可重复性、准确性和分级尺度的分辨率。由于肿瘤变化在视觉上是明显的且本质上是形态学的，通过图像分析进行量化是一种首选的测量方式。通过使用完整组织切片的高分辨率“拼接”图像来实施图像分析。开发了一种组织学分级系统或“尺度”，可以用多个不同形态计量描述符的标准偏差单位来表示。对每个组织图像切片进行多次测量，以定量表征肿瘤生长，将这些测量结果组合成每个切片的单个数字，即每个切片的组织学分级，并使用这些测量分布的参数来表示所考虑的整个区域的组织学分级。这个概念提供了一个统一的最终尺度，使用相似的测量单位，无论分级的是哪些组织。此外，分级尺度通过使用每种不同类型的正常组织来自动调整不同组织的测量方差，以获得标准化到标准偏差（z）单位。这进一步定义了一个统一的最终尺度并维持了标准参考。使用这种方法，比较了两种著名的致癌动物模型的结果，即苯并（a）芘（B[a]P）诱导的SENCAR小鼠皮肤鳞状细胞癌和N-亚硝基甲基苄胺（NMBA）诱导的大鼠食管鳞状细胞癌。对总共64只SENCAR小鼠的皮肤组织切片和96只Fischer-344大鼠的食管组织切片进行了图像分析。在这两种情况下，侵袭前肿瘤对致癌物的反应随暴露时间的定量表达均以标准偏差单位（z）沿连续分级尺度表示。在SENCAR小鼠皮肤动物模型中，20周时每组4只小鼠的相似队列显示，用抗增殖剂二氟甲基鸟氨酸治疗可显著调节B[a]P诱导的肿瘤形成，P <.05。在大鼠食管动物模型中，10周和15周时每组6只大鼠的相似队列显示，用抗诱变剂苯乙基异硫氰酸酯治疗可显著调节NMBA诱导的肿瘤形成，P <.05。
