| Literature DB >> 30655697 |
Yang Yao1, Jie Su1, Lei Zhao2, Na Luo3, Lihui Long4, Xingmei Zhu5.
Abstract
OBJECTIVE: NIMA-related kinase 2 (NEK2) has been reported to be overexpressed in various types of cancer and correlated with poor prognosis. The role(s) of NEK2 in cancer, however, is still uncertain. The aim of this study was to evaluate the prognostic value of NEK2 in human tumors.Entities:
Keywords: NEK2; cancer; clinical characteristics; diagnosis; meta-analysis; prognosis
Year: 2019 PMID: 30655697 PMCID: PMC6322518 DOI: 10.2147/CMAR.S188347
Source DB: PubMed Journal: Cancer Manag Res ISSN: 1179-1322 Impact factor: 3.989
Figure 1Flow diagram of literature search and selection.
Characteristics of the included studies
| Study (first author) | Year | Country | Cancer type | No. of cases | Gender (M/F) | Follow-up (months) | Detection method | Outcome measurements | HR (95% CI) | NOS |
|---|---|---|---|---|---|---|---|---|---|---|
| Zeng et al | 2015 | PR China | PCa | 180 | NR/NR | 140 | qRT-PCR | OS | 1.76 (0.85–3.64) | 7 |
| Fu et al | 2017 | PR China | HCC | 310 | 252/59 | 40 | IHC | OS | 1.44 (0.96–2.17) | 8 |
| Ning et al | 2014 | PR China | PDA | 136 | 72/64 | 100 | qRT-PCR | OS | 0.84 (0.56–1.38) | 8 |
| Li et al | 2017 | PR China | HCC | 63 | 52/11 | 116 | qRT-PCR | OS | 1.15 (0.39–3.35) | 8 |
| Liu et al | 2017 | PR China | MG | 105 | 47/52 | 200 | IHC | OS | 4.177 (1.97–8.82) | 9 |
| Zhong et al | 2014 | PR China | NSCLC | 270 | 192/78 | 60 | IHC | OS | 3.810 (2.06–7.036) | 8 |
| Takahashi et al | 2014 | Japan | CRC | 180 | 104/76 | 180 | qRT-PCR | OS | 1.76 (0.87–3.59) | 7 |
| Zhong et al | 2014 | PR China | NSCLC | 270 | 192/78 | 10 | IHC | OS | 1.85 (1.20–2.83) | 8 |
| Lu et al | 2015 | PR China | CC | 60 | 32/28 | 100 | IHC | OS | 3.04 (1.12–8.29) | 7 |
| Wubetu et al | 2016 | Japan | HCC | 50 | 16/34 | 180 | qRT-PCR | OS | 2.76 (1.12–8.29) | 8 |
| Shi et al | 2017 | PR China | LC | 349 | 159/190 | 240 | qRT-PCR | OS/DFS | 1.749 (1.140–2.681)/1.738 (1.161–2.601) | 9 |
| Zhang et al | 2018 | PR China | HCC | 259 | 230/29 | 100 | qRT-PCR | OS | 1.72 (1.18–2.53) | 8 |
| Neal et al | 2014 | UK | CC | 103 | 57/46 | NR | IHC | OS/DFS | 1.654 (0.926–2.956)/2.393 (1.096–5.227) | 8 |
| Gu et al | 2017 | USA | MM | 351 | NR/NR | 80 | qRT-PCR | OS | 1.80 (0.95–3.42) | 6 |
| Marina and Saavedra | 2014 | USA | BC | 594 | NR/NR | 133 | qRT-PCR | DFS | 0.6 (0.5–0.9) | 6 |
Abbreviations: BC, breast cancer; CC, colon cancer; CRC, colorectal cancer; DFS, disease-free survival; F, female; HCC, hepatocellular carcinoma; IHC, immunohistochemistry; LC, lung cancer; M, male; MG, malignant glioma; MM, multiple myeloma; NOS, Newcastle-Ottawa Scale; NR, not reported; NSCLC, non-small cell lung cancer; OS, overall survival; PDA, pancreatic ductal adenocarcinoma; PCa, prostate cancer.
Figure 2Forest plot of HRs for the association between high NIMA-related kinase 2 (NEK2) expression and overall survival in cancer patients.
Figure 3Forest plot of HRs for the association between high NIMA-related kinase 2 (NEK2) expression and overall survival stratified by cancer type.
Figure 4Forest plot of the subgroup analyses evaluating HRs of NEK2 for overall survival by the factors of (A) sample size, (B) follow-up months, (C) region, and (D) HR estimation method.
Abbreviations: CC, colon cancer; HCC, hepatocellular carcinoma; LC, lung cancer; NEK2, NIMA-related kinase 2.
Subgroup analysis of the pooled HRs for OS
| Categories | Studies (n) | No. of patients | Fixed effects model
| Heterogeneity
| ||
|---|---|---|---|---|---|---|
| HR (95% CI) for OS | ||||||
|
| ||||||
| OS | 14 | 2,335 | 1.72 (1.49–2.00) | <0.00001 | 46 | 0.03 |
| DFS | 2 | 697 | 1.13 (0.29–4.38) | <0.00001 | 91 | 0.0007 |
| Cancer type | ||||||
| HCC | 4 | 682 | 1.62 (1.25–2.10) | 0.02 | 1 | 0.37 |
| CC | 2 | 163 | 1.82 (0.92–3.59) | 0.08 | 44 | 0.18 |
| LC | 3 | 889 | 2.18 (1.40–3.38) | 0.0005 | 58 | 0.09 |
| Sample size | ||||||
| ≤300 | 11 | 1,325 | 1.88 (1.43–2.46) | <0.00001 | 57 | 0.010 |
| >300 | 3 | 1,010 | 1.59 (1.20–2.10) | 0.001 | 0 | 0.78 |
| Follow-up | ||||||
| ≤100 months | 5 | 1,342 | 1.68 (1.09–2.59) | 0.02 | 73 | 0.005 |
| >100 months | 8 | 1,077 | 1.95 (1.56–2.44) | <0.00001 | 1 | 0.42 |
| HR estimation method | ||||||
| Indirect | 11 | 2,129 | 1.75 (1.37–2.23) | <0.00001 | 45 | 0.05 |
| Direct | 3 | 557 | 2.01 (1.18–3.42) | 0.01 | 66 | 0.05 |
| Country | ||||||
| Asian | 12 | 2,232 | 1.86 (1.45–2.38) | <0.0001 | 53 | 0.02 |
| Other | 2 | 451 | 1.55 (1.08–2.23) | 0.02 | 0 | 0.57 |
Abbreviations: CC, colon cancer; DFS, disease-free survival; HCC, hepatocellular carcinoma; LC, lung cancer; OS, overall survival.
Figure 5Forest plot of HRs for the association between high NIMA-related kinase 2 (NEK2) expression and disease-free survival in cancer patients by different cancer types.
Association between NEK2 expression and clinicopathological features
| Clinicopathological parameters | Studies (n) | Patients (n) | OR (95% CI) | Heterogeneity
| ||
|---|---|---|---|---|---|---|
|
| ||||||
| Age (≥65 vs <65 years) | 3 | 403 | 0.45 (0.11–1.84) | <0.00001 | 96 | 0.27 |
| Gender (male vs female) | 12 | 2,150 | 3.02 (1.30–7.02) | 0.01 | 97 | <0.00001 |
| Clinical stage (I–II vs III–IV) | 6 | 1,086 | 2.50 (0.78–8.03) | 0.13 | 97 | <0.00001 |
| Tumor differentiation (well/moderate vs poor) | 5 | 625 | 4.23 (1.30–13.77) | <0.00001 | 95 | <0.00001 |
| Tumor nodule number (solitary vs multiple) | 4 | 682 | 5.88 (2.19–5.80) | 0.0004 | 93 | <0.00001 |
| Tumor size (≥5 vs <5 cm) | 3 | 602 | 1.07 (0.16–7.31) | 0.95 | 98 | <0.00001 |
| Venous invasion (present vs absent) | 3 | 667 | 6.55 (0.86–49.59) | 0.07 | 98 | <0.00001 |
Abbreviation: NEK2, NIMA-related kinase 2.
Sensitivity analysis
| Study (first author) | HR (95% CI) | ||
|---|---|---|---|
|
| |||
| Neal et al | 1.76 (1.51–2.06) | <0.00001 | 49 |
| Li et al | 1.74 (1.50–2.01) | <0.00001 | 49 |
| Wubetu et al | 1.70 (1.47–1.97) | <0.00001 | 48 |
| Liu et al | 1.66 (1.43–1.93) | <0.00001 | 35 |
| Lu et al | 1.70 (1.47–1.97) | <0.00001 | 48 |
| Fu et al | 1.77 (1.51–2.07) | <0.00001 | 48 |
| Zhong et al | 1.71 (1.46–2.00) | <0.00001 | 50 |
| Zhong et al | 1.64 (1.41–1.91) | <0.00001 | 31 |
| Zeng et al | 1.72 (1.48–2.00) | <0.00001 | 50 |
| Zhang et al | 1.72 (1.47–2.02) | <0.00001 | 50 |
| Shi et al | 1.72 (1.48–2.01) | <0.00001 | 50 |
| Takahashi et al | 1.72 (1.48–2.00) | <0.00001 | 50 |
| Ning et al | 1.85 (1.58–2.15) | <0.00001 | 22 |
| Gu et al | 1.72 (1.48–2.00) | <0.00001 | 50 |
Figure 6Funnel plot analysis for the potential publication bias among included studies.