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

Abstract

Abstract. 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.

High proliferation index, as determined by immunohistochemical expression of Aurora kinase B and geminin, indicates poor prognosis in neuroblastomas

“…There are two possible explanations for the difference. Firstly, while GMNN expression occurs throughout the S phase, AURKB expression (similar to AURKA) starts in mid-S phase [16]. Secondly, the fact that GMNN plays an important role in neurogenesis [17] might explain why it is expressed more frequently.…”