| Background: Dysfunction of cellular transport machinery is often observed in caner.The shuttling of proteins between the cytoplasm and the nucleus is mediated by karyopherins.Karyopherin ?2(KPNA2)is one of seven described members of the karyopherin? family,which is also known as importin?-1 or RAG cohort 1.KPNA2 weighs around 58 k Da and is composed of a N-terminal hydrophilicimportinb-binding domain,a central hydrophobic region,and a short acidic C-terminus.KPNA2 may participate in carcinogenesis through regulating the subcellular translocation of cancer-associated cargo proteins.KPNA2 overexpression was shown to promote G1/S cell cycle transition via upregulating c-Myc.KPNA2 could also enhance transcriptional activity of c-Myc,activate Akt,and suppress FOXO3 a in various cancer cells.Meanwhile,downregulation of cyclin-dependent kinase(CDK)inhibitor p21 and p27,as well as upregulation of CDK regulator cyclin D1 were seen in KPNA2-over-expresssed cells.Forced expression of KPNA2 could increase proliferation of breast cancer cells.On the other hand,knockdown of KPNA2 was shown to inhibit proliferation of cancer cells.Growth evidences have also proposed the potential role of KPNA2 in multiple cancerous behaviors,including cell proliferation,differentiation,cell-matrix adhesion,colony formation and migration.Existing evidences have shown that KPNA2 was over-expressed in multiple malignancies.Meanwhile,it has been suggested that elevated KPNA2 could be associated with poor prognosis in a variety of solid tumors.However,the association between KPNA2 expression and prognosis in cancer remains controversial.So we performed this meta-analysis to evaluate whether expression of KPNA2 was associated with prognosis in patients with solid tumors.Methods/Findings: 24 published eligible studies,including 6164 cases,were identified and included in this meta-analysis through searching of Pub Med,EMBASE and Web of Science.This meta-analysis of KPNA2 expression was based on the following outcome endpoints: primary outcome(OS)and secondary outcomes [time to recurrence(TTR),recurrence free survival(RFS),progression free survival(PFS)and disease free survival(DFS)].According to the inclusion and exclusion criterias,the following items were extracted from each study: the first author's surname,year of publication,country of origin,number of cases,type of cancer,method of detection,score for KPNA2 assessment and cut-off value to determine KPNA2 positivity,Hazard ratio(HR)of KPNA2 expression for OS,TTR,RFS,PFS and DFS with the 95% CI and P-value.If only Kaplan-Meier curves were presented in the studies,we utilized Engauge Digitizer version 4.3 to obtain the survival data,and Tierney's method to calculate the HRs and 95%CIs.Subgroup analysis was performed when there were at least three studies in each subgroup.The methodological quality assessment of each study was performed using the Newcastle–Ottawa Scale(NOS),which scored studies with 8 items.Studies with an NOS score ?6 were considered as high-quality ones.In order to evaluate the relationship between KPNA2 expression and solid tumor prognosis,we applied HRs with their corresponding 95% CIs from each eligible paper to calculate the pooled HR for outcome endpoints(OS,DFS,RFS,PFS and TTR).The overall HR was >1,and the 95% CI did not overlap in the forest plot,suggesting a poor prognosis in patients with high expression of KPNA2.Heterogeneity assumption among the included studies was checked using Cochran's Q test and Higgins' s I2 statistic,P value >0.10 and I2 <50% suggesteda lack of heterogeneity among studies.In absence of heterogeneity,a fixed-effects model was applied.Otherwise,the random-effects model was employed.Funnel plots and the Egger's test were utilized to evaluate the possible publication bias.If a publication bias did exist,its influence on the overall effect was assessed by the Duval and Tweedie's trim and fill method.Sensitivity analysis was also performed by omitting each study or specific studies to find potential outliers.All P values for comparisons were two-sided and statistical significance was defined as P<0.05,except those for heterogeneity.The current meta-analysis was based on primary outcome(OS)and secondary outcomes(TTR,RFS,PFS and DFS).Twenty studies were included in the meta-analysis of OS.A random-effects model was applied to calculate the pooled hazard ratio(HR)and 95% confidence interval(CI).The heterogeneity test reported the P value of 0.011 and I2 values of 46.4%.These results showed an evidence of significant association between KPNA2 overexpression and poor OS(pooled HR=1.767,95% CI=1.503-2.077,P<0.001).A random-effects model was utilized to calculate the pooled HR and 95% CI in 5 studies which focused on DFS,as the heterogeneity test reported the P value <0.001 and I2 value of 81.0%.The pooled result showed the association between KPNA2 overexpression and DFS was not significant(pooled HR=1.653,95% CI=0.903-3.029,P=0.104).The TTR was derived from only one dataset and showed significant association with KPNA2 overexpression(HR=1.464,95% CI=1.023-2.096,P=0.037).The pooled results from five datasets for RFS and three datasets for PFS indicated that KPNA2 overexpression was associated with poor RFS and poor PFS(HR=1.835,95% CI=1.530-2.200,P<0.001;HR=2.921,95% CI=1.493-5.715,P=0.002,respectively).In the subgroup stratified by origin of patients,the pooled HR was 1.962(95% CI=1.525-2.525,P<0.001)in East-Asian populations from 12 included studies.The pooled HR was 1.562(95% CI=1.407-1.734,P<0.001)for European group from the other 8 studies.Both of the two overall outcomes indicated the significant relationship between KPNA2 overexpression and poor OS.For the analysis stratified by cancer type,significant association between KPNA2 overexpression and poor OS was observed in patients with gastric cancer(HR= 2.353,95% CI=1.048-5.284,P=0.038)and colorectal cancer(HR=3.252,95%CI=1.82-5.811,P<0.001),but not in patients with breast cancer(HR= 1.588,95% CI=0.996-2.531,P=0.052).Begg's funnel plot and Egger's test were applied to evaluate the publication bias of the literatures.The funnel plot was asymmetrical.The P value calculated from Egger's test pointed outthe presence of publication bias(P<0.001)among these studies.Therefore,we performed trim and fill method to make pooled HR more reliable,and the P value was less than 0.01.Furthermore,sensitivity analysis was conducted to assess the influence of individual study on the summary effects for the OS.None of the each single study dominated this meta-analysis,and the removal of each study had no significant effect on the overall conclusion.Removal of studyusing Quantitative Real Time Polymerase Chain Reaction(q RT-PCR)to assess the expression of KPNA2 obtained similar results of OS(HR=1.773,95% CI=1.495-2.102,P<0.001,I2=48.4%).There were 4 studies with the number of cases less than 100,elimination of these studieshad no substantial impact on the outcome of OS(HR=1.583,95% CI=1.372-1.826,P<0.001,I2=30.7%).Conclusion: KPNA2 expression may be a useful prognostic biomarker to monitor cancer prognosis.Further prospective studies with larger sample sizes are required to confirm our findings. |
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