Multiparameter analysis using cell cycle biomarkers for small-size lung adenocarcinoma: prognostic implications.
نویسندگان
چکیده
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.
منابع مشابه
Identification of microRNAs as potential biomarkers for lung adenocarcinoma using integrating genomics analysis
Lung adenocarcinoma (LUAD) is the most common histological subtype of non-small cell lung cancer, but novel biomarkers for early diagnosis are lacking. Extensive effort has been exerted to identify miRNA biomarkers in LUAD. Unfortunately, high inter-lab variability and small sample sizes have produced inconsistent conclusions in this field. To resolve the above-mentioned limitations, we perform...
متن کاملRobust Prognostic Gene Expression Signatures in Bladder Cancer and Lung Adenocarcinoma Depend on Cell Cycle Related Genes
Few prognostic biomarkers are approved for clinical use primarily because their initial performance cannot be repeated in independent datasets. We posited that robust biomarkers could be obtained by identifying deregulated biological processes shared among tumor types having a common etiology. We performed a gene set enrichment analysis in 20 publicly available gene expression datasets comprisi...
متن کاملExpression of Epidermal Growth Factor Receptor and the association with Demographic and Prognostic Factors in Patients with Non-small Cell Lung Cancer
Introduction: Growth, proliferation, survival, and differentiation are the prominent characteristics of cells, which are affected by cancer. Epidermal growth factor receptor (EGFR) plays a pivotal role in the effective control of these features. Given the significance of EGFR signaling pathway in non-small cell lung cancer (NSCLC), EGFR expression is influential on these cell characteristics. I...
متن کاملPrognostic and predictive values of CDK1 and MAD2L1 in lung adenocarcinoma
Lung cancer remains as the leading cause of cancer-related death worldwide, and lung adenocarcinoma (LUAD) is the most common histological subtype. This study aims to investigate biomarkers associated with cancer progression and prognosis of LUAD. We integrated expression profiles of 668 lung cancer patients in five datasets from the Gene Expression Omnibus (GEO) and identified a panel of diffe...
متن کاملThe Effect of Time-dependent Prognostic Factors on Survival of Non-Small Cell Lung Cancer using Bayesian Extended Cox Model
Abstract Background: Lung cancer is one of the most common cancers around the world. The aim of this study was to use Extended Cox Model (ECM) with Bayesian approach to survey the behavior of potential time-varying prognostic factors of Non-small cell lung cancer. Materials and Methods: Survival status of all 190 patients diagnosed with Non-Small Cell lung cancer referring to hospitals in ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Oncology reports
دوره 28 3 شماره
صفحات -
تاریخ انتشار 2012