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Cell cycle-related molecules play crucial roles in maintaining genomic stability,and can also serve as biomarkers of cell cycle phase distribution at the sametime. In this study, we used multiparameter analysis of various biomarkers toinvestigate their utility for the evaluation of tumor proliferation activitiesand the prognosis of patients with small-size lung adenocarcinoma. We performedimmunohistochemical 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 phasedistribution of the tumor cell population, and evaluated whether these phenotypeswere associated with clinicopathological factors and survival. Phenotype I (MCM7-negativetumors; n=56) was correlated with high or moderate differentiation and reducedlocal invasiveness (pleural and lymphovascular invasion) compared with phenotypeII (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 phenotypesI, II and III were 89.8, 55.4 and 38.6%, respectively, with a significant differencebetween them (p&lt;0.01). Multivariate analysis revealed that phenotypes II andIII were independent prognostic factors in the 79 patients with stage I lung adenocarcinoma.Multiparameter analysis using cell cycle biomarkers for small-size lung adenocarcinomaprovided novel insights into the cell cycle phase distribution of dynamic tumorcell populations in vivo; it may be possible to evaluate tumor proliferation activitiesand patient prognosis more precisely if this analytical procedure is used.

Multiparameter analysis using cell cycle biomarkers for small-size lung adenocarcinoma: prognostic implications