| Literature DB >> 29348895 |
Haihua Ruan1, Shuangyan Hu1, Hongyu Zhang1, Gang Du1, Xiaoting Li2, Xiaobo Li2, Xichuan Li1.
Abstract
It was recently reported that increased SOX9 expression drives tumor growth and promotes cancer invasion during human tumorigenicity and metastasis. However, the prognostic value of SOX9 for the survival of patients with solid tumors remains controversial. The present meta-analysis was thus performed to highlight the link between dysregulated SOX9 expression and prognosis in cancer patients. A systematic literature search was conducted using the electronic databases PubMed, Web of Science and Embase to identify eligible studies. A random-effects meta-analytical model was employed to correlate SOX9 expression with overall survival (OS), disease-free survival (DFS) and clinicopathological features. In total, 17 studies with 3307 patients were eligible for the final analysis. Combined hazard ratios (HRs) and 95% confidence intervals (CIs) suggested that high SOX9 expression has an unfavourable impact on OS (HR = 1.66, 95% CI 1.36-2.02, P < 0.001) and DFS (HR = 3.54, 95% CI 2.29-5.47, P = 0.008) in multivariate analysis. Additionally, the pooled odds ratios (ORs) indicated that SOX9 over-expression is associated with large tumor size, lymph node metastasis, distant metastasis and a higher clinical stage. Overall, these results indicated that SOX9 over-expression in patients with solid tumors might be related to poor prognosis and could serve as a potential predictive marker of poor clinicopathological prognosis factor.Entities:
Keywords: SOX9; meta-analysis; prognosis; solid tumors
Year: 2017 PMID: 29348895 PMCID: PMC5762580 DOI: 10.18632/oncotarget.22635
Source DB: PubMed Journal: Oncotarget ISSN: 1949-2553
Figure 1Flow diagram of the selection of eligible studies
Main characteristics of studies exploring the relationship between SOX9 expression and tumor prognosis
| Author | Year | Region | Cancer Type | Stage / Grade | No. of Patients | Follow-up Time Median (range) | Detection Method | Cut-off | NOS Score | Outcomes |
|---|---|---|---|---|---|---|---|---|---|---|
| Chen H [ | 2017 | USA | Chordoma | I-III | 50 | 4-250 m | IHC(Santa Cruz) | PS > 2 | 5 | OS, DFS |
| Qi J [ | 2017 | China | Osteosarcoma | I-III | 97 | 10-72 m | IHC(Santa Cruz) | IRS > 5 | 6 | OS |
| Yang Z [ | 2016 | Korea | Esophageal cancer | I-V | 127 | 1-120 m | IHC(Abnova) | NR | 6 | OS, DFS |
| Liu C [ | 2016 | China | Hepatocellular Carcinoma | I-III | 148 | 1-80 m | IHC(Millipore) | PS > 2 | 6 | OS |
| Hong Y [ | 2015 | China | Esophageal cancer | I-V | 155 | 1-100 m | IHC(Abcam) | IRS > 6 | 7 | OS |
| Matsushima H [ | 2015 | Japan | Intrahepatic cholangiocarcinoma | I-V | 43 | 1-150 m | IHC(Abcam) | NR | 5 | OS |
| Xia S [ | 2015 | China | Pancreatic ductal adenocarcinoma | I-V | 88 | 1-60 m | IHC(Millipore) | IRS > 6 | 6 | OS |
| Qin GQ [ | 2014 | China | Prostate cancer | T2A | 98 | 1-140 m | IHC(Santa Cruz) | PS > 1 | 7 | OS, DFS |
| Zhu H [ | 2013 | China | Osteosarcoma | II-III | 166 | 10–152 m | IHC(Santa Cruz) | IRS > 5 | 6 | OS, DFS |
| Yun JY [ | 2013 | Korea | Thyroid carcinoma | I-V | 158 | 47.5 m for median | IHC(Abnova) | PS > 1 | 7 | OS |
| Candy P [ | 2013 | Australia | Colorectal cancer | I-III | 1056 | 69.7 m for median | IHC(Santa Cruz) | > 50% | 8 | OS |
| Choi YJ [ | 2013 | Korea | Gastric cancers | NR | 185 | 1-60 m | IHC(Millipore) | > 30% | 7 | OS |
| Zhong WD [ | 2012 | China | Prostate cancer | T2A | 147 | 3-12 y | IHC(Santa Cruz) | IRS > 4 | 6 | DFS |
| Guo X [ | 2012 | China | Hepatocellular Carcinoma | I-V | 130 | 8.6 year for median | IHC(Santa Cruz) | IRS > 5 | 7 | OS, DFS |
| Zhou CH [ | 2012 | China | Non-small cell lung cancer | I-V | 89 | 1-60 m | IHC(Millipore) | IRS > 6 | 6 | OS |
| Sun M [ | 2012 | China | Gastric cancer | NR | 382 | 1-3000 d | IHC(Millipore) | IRS > 5 | 8 | OS |
| Lü B [ | 2008 | China | Colorectal Cancer | I-V | 188 | 1-12.5 y | IHC(Santa Cruz) | PS > 2 | 7 | OS |
NR: Not Reported; y: year; m: month; d: day; OS: Overall Survival; DFS: Disease-Free Survival. PS: Percentage Score; IRS: Immunoreactive Score.
Figure 2Forest plot describing the association between over-expressed SOX9 and OS
Associations between SOX9 expression and OS stratified according to the ethnics, case number, NOS score, follow-up time, antibody and cut-off value
| Categories | Subgroups | Ref | HR (95% CI) | Heterogeneity test (I2, |
|---|---|---|---|---|
| Ethnics | Asian Not Asian | [ | 1.98 (1.50–2.62) | 53.8%, 0.009 |
| 1.19 (0.96–1.48) | 60.7%, 0.111 | |||
| Case Number | ≥ 100 | [ | 1.60 (1.29–1.99) | 71.8%, 0.000 |
| [ | ||||
| < 100 | [ | 2.05 (1.30–3.23) | 0.0%, 0.770 | |
| NOS Score | ≥ 7 | [ | 1.41 (1.10–1.79) | 67.5%, 0.003 |
| < 7 | [ | 2.69 (1.99–3.62) | 46.4%, 0.071 | |
| Follow-up Time | ≥ 120 m | [ | 2.26 (1.46–3.50) | 78.0%, 0.001 |
| < 120 m | [ | 1.53 (1.23–1.91) | 67.1%, 0.001 | |
| Antibody | Santa Cruz | [ | 1.58 (1.28–1.95) | 74.0%, 0.001 |
| Millipore | [ | 1.54 (0.92–2.59) | 41.1%, 0.147 | |
| Abcam | [ | 3.54 (2.11–5.94) | 0.0%, 0.749 | |
| Abnova | [ | 1.63 (0.94–2.83) | 0.0%, 0.573 | |
| Cut-off Value | IRS | [ | 2.64 (1.67–4.17) | 30.3%, 0.197 |
| PS | [ | 1.47 (0.99–2.18) | 0.0%, 0.760 | |
| Percentage | [ | 1.13 (0.92–1.38) | 0.0%, 0.844 | |
| NR | [ | 2.08 (1.37–3.16) | 0.0%, 0.366 |
m: month; PS: Percentage Score; IRS: Immunoreactive Score; NR: Not Reported.
Figure 3Forest plot describing the association between over-expressed SOX9 and DFS
Meta-analysis results of the associations of increased SOX9 expression with clinicopathological parameters
| Clinicopathological parameter | Ref | Overall OR (95% CI) | Heterogeneity test (I2, |
|---|---|---|---|
| Gender (male vs female) | [ | 0.99 (0.85–1.15) | 0.0%, 0.439 |
| Tumor Differentiation (poor VS well) | [ | 1.13 (0.93–1.39) | 59.2%, 0.031 |
| Tumor Size (T3-4 vs T1-2) | [ | 1.58 (1.31–1.91) | 81.3%, 0.000 |
| Lymph Node Metastasis (yes vs no) | [ | 1.61 (1.30–1.99) | 84.9%, 0.000 |
| Distant Metastasis (yes vs no) | [ | 1.53 (1.25–1.87) | 27.3%, 0.230 |
| Clinical Stage (III-IV vs I-II) | [ | 1.68 (1.33–2.12) | 90.4%, 0.000 |
Results of meta−regression analysis exploring source of heterogeneity with OS and DFS
| Covariates | OS | DFS | ||||
|---|---|---|---|---|---|---|
| Coef. | S.E. | Coef. | S.E. | |||
| Country | −0.129 | .083 | 0.144 | −0.310 | 0.328 | 0.399 |
| Case Number | 0.263 | 0.261 | 0.331 | 0.227 | 0.576 | 0.713 |
| Antibody | 0.033 | 0.122 | 0.792 | −0.250 | 0.103 | 0.071 |
| Cut-off value | −0.065 | 0.121 | 0.599 | 0.310 | 0.123 | 0.065 |
Coef.: Coefficient; S.E.: Standard Error;
Figure 4Sensitivity analysis of the OS and DFS in the meta-analysis
Figure 5Funnel plot for the assessment of potential publication bias regarding OS and DFS in the meta-analysis