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Published on: March 30, 2019
Multiparameter analysis using cell cycle biomarkers for small-size lung adenocarcinoma: prognostic implications
Tomohiro Haruki1, Kohei Shomori, Tatsushi Shiomi
1Division of Organ Pathology, Department of Microbiology and Pathology, Faculty of Medicine, Tottori University, and Tottori University Hospita, Yonago-city, Tottori 683-8503, Japan.
Oncology Reports
|July 7, 2012
Summary
Multiparameter analysis of cell cycle biomarkers in small lung adenocarcinoma revealed distinct phenotypes. These phenotypes significantly correlate with tumor proliferation, invasiveness, and patient survival, offering improved prognostic evaluation.
Area of Science:
- Oncology
- Molecular Biology
- Genomics
Background:
- Cell cycle molecules are vital for genomic stability and serve as biomarkers for cell cycle distribution.
- Understanding tumor proliferation and patient prognosis in small lung adenocarcinoma is critical for effective treatment strategies.
Purpose of the Study:
- To investigate the utility of multiparameter analysis of cell cycle biomarkers for evaluating tumor proliferation and prognosis in small lung adenocarcinoma.
- To classify tumors into phenotypes based on cell cycle phase distribution and assess their association with clinicopathological factors and survival.
Main Methods:
- Immunohistochemical analysis of five cell cycle-related biomarkers (MCM7, Ki-67, Geminin, Aurora A, H3S10ph) in 102 surgically resected small lung adenocarcinomas.
- Classification of tumors into three phenotypes based on dominant cell cycle phase distribution.
- Evaluation of phenotype association with clinicopathological factors and survival rates.
Main Results:
- Phenotype I (MCM7-negative) showed high differentiation and reduced invasiveness compared to Phenotype II (MCM7-, Ki-67-, Geminin-positive) and Phenotype III (MCM7-, Aurora A-, H3S10ph-positive).
- Five-year survival rates were significantly different across phenotypes: 89.8% (Phenotype I), 55.4% (Phenotype II), and 38.6% (Phenotype III).
- Phenotypes II and III were identified as independent prognostic factors for stage I lung adenocarcinoma.
Conclusions:
- Multiparameter analysis of cell cycle biomarkers provides novel insights into dynamic tumor cell populations in vivo.
- This approach allows for more precise evaluation of tumor proliferation activities and patient prognosis in small lung adenocarcinoma.