Division of Organ Pathology, Department of Microbiology and Pathology, Faculty of Medicine, Tottori University, and Tottori University Hospita, Yonago-city, Tottori 683-8503, Japan.
Oncol Rep. 2012 Sep;28(3):915-22. doi: 10.3892/or.2012.1894. Epub 2012 Jul 3.
Cell cycle-related molecules play crucial roles in maintaining genomic stability, and can also serve as biomarkers of cell cycle phase distribution at the same time. In this study, we used multiparameter analysis of various biomarkers to investigate their utility for the evaluation of tumor proliferation activities and the prognosis of patients with small-size lung adenocarcinoma. We performed immunohistochemical analysis using five cell cycle-related biomarkers (MCM7, Ki-67, Geminin, Aurora A and H3S10ph) for 102 surgically resected small-size lung adenocarcinomas. We classified them into three phenotypes based on the dominant cell cycle phase distribution of the tumor cell population, and evaluated whether these phenotypes were associated with clinicopathological factors and survival. Phenotype I (MCM7-negative tumors; n=56) was correlated with high or moderate differentiation and reduced local invasiveness (pleural and lymphovascular invasion) compared with phenotype II (MCM7-, Ki-67- and Geminin-positive tumors; n=23) and phenotype III (MCM7-, Aurora A- and H3S10ph-positive tumors; n=17). Five-year survival rates of phenotypes I, II and III were 89.8, 55.4 and 38.6%, respectively, with a significant difference between them (p<0.01). Multivariate analysis revealed that phenotypes II and III were independent prognostic factors in the 79 patients with stage I lung adenocarcinoma. Multiparameter analysis using cell cycle biomarkers for small-size lung adenocarcinoma provided novel insights into the cell cycle phase distribution of dynamic tumor cell populations in vivo; it may be possible to evaluate tumor proliferation activities and patient prognosis more precisely if this analytical procedure is used.
细胞周期相关分子在维持基因组稳定性方面发挥着关键作用，同时也可以作为细胞周期时相分布的生物标志物。本研究采用多参数分析各种细胞周期标志物，旨在探讨其在评估小尺寸肺腺癌肿瘤增殖活性和患者预后中的作用。我们使用五种细胞周期相关标志物（MCM7、Ki-67、Geminin、Aurora A 和 H3S10ph）对 102 例手术切除的小尺寸肺腺癌进行了免疫组织化学分析。根据肿瘤细胞群体的主导细胞周期时相分布，我们将其分为三种表型，并评估这些表型是否与临床病理因素和生存相关。表型 I（MCM7 阴性肿瘤；n=56）与高或中分化以及较低的局部侵袭性（胸膜和血管淋巴管侵犯）相关，与表型 II（MCM7-、Ki-67-和 Geminin-阳性肿瘤；n=23）和表型 III（MCM7-、Aurora A-和 H3S10ph-阳性肿瘤；n=17）相比。表型 I、II 和 III 的 5 年生存率分别为 89.8%、55.4%和 38.6%，差异具有统计学意义（p<0.01）。多因素分析显示，表型 II 和 III 是 I 期肺腺癌患者的独立预后因素。小尺寸肺腺癌的细胞周期标志物多参数分析为体内动态肿瘤细胞群体的细胞周期时相分布提供了新的见解；如果使用这种分析程序，可能能够更精确地评估肿瘤增殖活性和患者预后。
