BACKGROUND: Octamer-binding transcription factor 4 (Oct-4) has been identified to participate in the tumorigenicity and malignancy of non-small cell lung cancer (NSCLC). However, its definite prognostic roles in NSCLC still remain a debate. Therefore, we conducted this meta-analysis to evaluate the prognostic value of Oct-4 expression in NSCLC and its relationship to some major clinicopathological characteristics. METHODS: A comprehensive literature retrieval was performed in PubMed, EMBASE and the Web of Science to identify the full-text articles that met our eligibility criteria. Odds ratio (OR) with 95% confidence interval (CI) severed as the summarized statistics for clinicopathological assessments, and hazard ratio (HR) with 95% CI served as the summarized statistics for prognostic assessments. Q-test and I(2)-statistic were used to evaluate the level of heterogeneity. Potential publication bias was detected by both Begg's test and Egger's test. RESULTS: There were 16 retried articles with 1,363 NSCLC cases included into this meta-analysis. Oct-4 expression was found to be significantly associated with the unfavorable outcomes for differentiation degree (OR: 3.065; 95% CI: 1.568-5.957; P=0.001), TNM stage (OR: 3.695; 95% CI: 2.252-6.063; P<0.001) and lymphatic metastasis (OR: 2.372; 95% CI: 1.504-3.742; P<0.001), but not associated with the histological subtypes, gender, age and smoking status. Oct-4 expression was also significantly associated with the poor prognosis of NSCLC (HR: 3.030; 95% CI: 2.283-4.021; P<0.001). The prognostic roles of Oct-4 expression in NSCLC still remained statistically reliable in the subgroups stratified by statistical analysis, patients' origins, positively-stained sites and histological subtypes. CONCLUSIONS: Our meta-analysis indicates that Oct-4 can serve as a strong biomarker predicting the poor clinicopathological and prognostic characteristics of NSCLC. More high-quality studies based on a large sample size will be very helpful to further validate and modify our findings in the future.
BACKGROUND:Octamer-binding transcription factor 4 (Oct-4) has been identified to participate in the tumorigenicity and malignancy of non-small cell lung cancer (NSCLC). However, its definite prognostic roles in NSCLC still remain a debate. Therefore, we conducted this meta-analysis to evaluate the prognostic value of Oct-4 expression in NSCLC and its relationship to some major clinicopathological characteristics. METHODS: A comprehensive literature retrieval was performed in PubMed, EMBASE and the Web of Science to identify the full-text articles that met our eligibility criteria. Odds ratio (OR) with 95% confidence interval (CI) severed as the summarized statistics for clinicopathological assessments, and hazard ratio (HR) with 95% CI served as the summarized statistics for prognostic assessments. Q-test and I(2)-statistic were used to evaluate the level of heterogeneity. Potential publication bias was detected by both Begg's test and Egger's test. RESULTS: There were 16 retried articles with 1,363 NSCLC cases included into this meta-analysis. Oct-4 expression was found to be significantly associated with the unfavorable outcomes for differentiation degree (OR: 3.065; 95% CI: 1.568-5.957; P=0.001), TNM stage (OR: 3.695; 95% CI: 2.252-6.063; P<0.001) and lymphatic metastasis (OR: 2.372; 95% CI: 1.504-3.742; P<0.001), but not associated with the histological subtypes, gender, age and smoking status. Oct-4 expression was also significantly associated with the poor prognosis of NSCLC (HR: 3.030; 95% CI: 2.283-4.021; P<0.001). The prognostic roles of Oct-4 expression in NSCLC still remained statistically reliable in the subgroups stratified by statistical analysis, patients' origins, positively-stained sites and histological subtypes. CONCLUSIONS: Our meta-analysis indicates that Oct-4 can serve as a strong biomarker predicting the poor clinicopathological and prognostic characteristics of NSCLC. More high-quality studies based on a large sample size will be very helpful to further validate and modify our findings in the future.
Authors: Laurie A Boyer; Tong Ihn Lee; Megan F Cole; Sarah E Johnstone; Stuart S Levine; Jacob P Zucker; Matthew G Guenther; Roshan M Kumar; Heather L Murray; Richard G Jenner; David K Gifford; Douglas A Melton; Rudolf Jaenisch; Richard A Young Journal: Cell Date: 2005-09-23 Impact factor: 41.582
Authors: Ariel A Avilion; Silvia K Nicolis; Larysa H Pevny; Lidia Perez; Nigel Vivian; Robin Lovell-Badge Journal: Genes Dev Date: 2003-01-01 Impact factor: 11.361