title: Multiparameter analysis using cell cycle biomarkers for small-size lung             adenocarcinoma: prognostic implications.
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.
authors: Division of Organ Pathology, Department of Microbiology and Pathology, Faculty of Medicine, Tottori University, and Tottori University Hospita, Yonago-city, Tottori 683-8503, Japan.
authors: Tomohiro
authors: T
authors: Haruki
authors: Kohei
authors: K
authors: Shomori
authors: Tatsushi
authors: T
authors: Shiomi
authors: Yuji
authors: Y
authors: Taniguchi
authors: Hiroshige
authors: H
authors: Nakamura
authors: Hisao
authors: H
authors: Ito
mesh_terms: D000230:Adenocarcinoma / Q000175:diagnosis / Q000378:metabolism* / Q000401:mortality; D000077192:Adenocarcinoma of Lung; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000378:metabolism*; D059447:Cell Cycle Checkpoints; D018797:Cell Cycle Proteins / Q000378:metabolism*; D049109:Cell Proliferation; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D008175:Lung Neoplasms / Q000175:diagnosis / Q000378:metabolism* / Q000401:mortality; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D010641:Phenotype; D011379:Prognosis; D016016:Proportional Hazards Models
chemical_list: D014408:Biomarkers, Tumor; D018797:Cell Cycle Proteins