Department of Pathology, Yokohama City University Graduate School of Medicine, 3-9, Fukuura, Kanazawa-ku, 236-0004, Yokohama, Japan.
Am J Surg Pathol. 2010 Feb;34(2):243-55. doi: 10.1097/PAS.0b013e3181c79a6f.
The traditional histologic classification of lung cancer is not satisfactory to describe the morphologic characteristics of individual tumors, because it does not fully cover cytologic features. This paper describes a novel typing system using morphometric profiling that covers a variety of morphologic features including histologic architecture, cell type, cytoplasmic color and internal structure, nuclear outline, chromatin pattern, nucleoli count and remarkableness, and average and deviation of nuclear size and circularity. In all, 201 cases of lung tumors (whose sizes are <20 mm) were examined. Results of a hierarchical clustering analysis were used to draw a dendrogram. We here tentatively focused on 8 morphometric clusters and analyzed their potential association with a variety of clinicopathologic and molecular genetic features. Significant differences in postoperative recurrent risk, growth activity, oncogenic mutation (EGFR or KRAS), impairments of tumor suppressors (p53 and p16), sex predisposition, and smoking status were found among the 8 clusters. The system has the potential to improve histopathologic diagnosis and our understanding of carcinogenesis in the lung.
传统的肺癌组织学分类不能令人满意地描述个别肿瘤的形态特征，因为它不能充分涵盖细胞学特征。本文描述了一种使用形态计量学分析的新型分型系统，它涵盖了多种形态特征，包括组织学结构、细胞类型、细胞质颜色和内部结构、核轮廓、染色质模式、核仁计数和显著程度，以及核大小和圆形度的平均值和偏差。总共检查了 201 例肺癌肿瘤（<20 毫米）。层次聚类分析的结果用于绘制树状图。我们在这里暂时关注 8 个形态计量学簇，并分析它们与各种临床病理和分子遗传学特征的潜在关联。在 8 个簇中发现了术后复发风险、生长活性、致癌突变（EGFR 或 KRAS）、肿瘤抑制因子（p53 和 p16）的损伤、性别倾向和吸烟状态的显著差异。该系统有可能改善组织病理学诊断，并加深我们对肺癌发生的认识。
