| Literature DB >> 30009173 |
Lin Cheng1,2, Yan Guo3, Shipeng Zhan2, Peiyuan Xia2.
Abstract
Objective. We aimed to derive a more precise estimation of the associations between human leukocyte antigens DP (HLA-DP) gene polymorphisms and cervical cancer risk by meta-analysis. Methods. PubMed, EMBASE, ScienceDirect, Web of Science, Chinese National Knowledge Infrastructure (CNKI), and Wanfang databases were systematically searched to identify studies investigating the relationship between HLA-DP gene polymorphisms and cervical cancer. The associations between them were evaluated by pooled OR and 95% CI. Results. A total of 11 studies including 5008 cases and 9322 controls with 11 HLA-DP alleles were included in the current meta-analysis. Results. The results showed that HLA-DPB1⁎03:01 was significantly associated with an increased risk of cervical cancer (OR=1.252, 95%CI: 1.116-1.403, Pz=0.001), while HLA-DPB1⁎04:02 and HLA-DP rs3117027 G allele were significantly associated with a decreased risk of cervical cancer (OR=0.744, 95%CI: 0.652-0.848, Pz=0.001; OR=0.790, 95%CI: 0.745-0.837, Pz=0.001), and HLA-DP rs9277535 G allele was significantly associated with a decreased risk of cervical cancer in Asia (OR=0.802, 95%CI: 0.753-0.855, Pz=0.001). Subgroup analyses based on race system showed that HLA-DPB1⁎13:01 was significantly associated with an increased risk of cervical cancer in Asia (OR=1.834, 95%CI: 1.107-3.039, Pz=0.019). No significant association was established for the HLA-DP following alleles: DPB1⁎02:01, DPB1⁎02:02, DPB1⁎04:01, DPB1⁎05:01, rs4282438, and rs3077. Conclusion. HLA-DP gene polymorphisms (HLA-DPB1⁎03:01, DPB1⁎04:02, DPB1⁎13:01, rs9277535, and rs3117027) were significantly associated with cervical cancer.Entities:
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Year: 2018 PMID: 30009173 PMCID: PMC6020657 DOI: 10.1155/2018/7301595
Source DB: PubMed Journal: Biomed Res Int Impact factor: 3.411
Figure 1Flow chart of study selection in the meta-analysis.
Main characteristics of all studies included in the meta-analysis.
| First author | Year | Country | Case | Control | Genotyping method | Polymorphisms |
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| Miura K [ | 2016 | Japan | 214 | 288 | PCR-SBT | DPB1 |
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| Jia M [ | 2016 | China | 593 | 4074 | TaqMan assay | rs4282438, rs9277535, rs3117027, rs3077 |
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| Yang YC [ | 2015 | Taiwan | 473 | 676 | PCR, sequencing | DPB1 |
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| Chen D [ | 2014 | Sweden | 1034 | 3948 | PCR, sequencing | DPB1 |
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| Chen D [ | 2013 | Sweden | 2215 | 5072 | GENios Pro platform | rs3117027 |
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| Jiang J [ | 2013 | China | 2317 | 2109 | TaqMan assay | rs9277535, rs3077 |
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| Shi Y [ | 2013 | China | 5531 | 10224 | Affymetrix Axiom Genome-Wide CHB1 Array | rs4282438 |
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| Zhang K [ | 2013 | China | 831 | 573 | TaqMan assay | rs9277535, rs3077 |
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| Ivansson EL [ | 2011 | Sweden | 1076 | 1426 | Affymetrix Genome-Wide Human SNP Array | DPB1 |
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| Liang J [ | 2008 | China | 126 | 88 | PCR-SBT | DPB1 |
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| Wu Y [ | 2007 | China | 133 | 98 | PCR-SBT | DPB1 |
PCR-SBT: polymerase chain reaction sequence-based typing; SNP: single nucleotide polymorphisms.
Meta-analysis of associations between HLA-DP alleles and cervical cancer.
| Alleles | No. of studies | Case (2n) | Control (2n) | Heterogeneity P value | I2 value (%) for heterogeneity test | Model | OR (95%CI) | P value | Z | P value for Egger's (Begg's) bias test |
|---|---|---|---|---|---|---|---|---|---|---|
| DPB1 | 6 | 743/5916 | 1397/10888 | 0.006 | 69.1 | R | 0.915 (0.741-1.130) | 0.409 | 0.82 | 0.981 (1.000) |
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| DPB1 | 4 | 103/1764 | 132/2300 | 0.071 | 57.4 | R | 1.261 (0.740-2.418) | 0.394 | 0.85 | 0.107 (0.089) |
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| DPB1 | 6 | 652/5878 | 1032/10888 | 0.080 | 49.1 | F | 1.252 (1.116-1.403) | 0.001 | 3.84 | 0.853 (1.000) |
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| DPB1 | 6 | 2015/5892 | 4215/10878 | 0.210 | 30.1 | F | 1.009 (0.932-1.092) | 0.821 | 0.23 | 0.240 (0.133) |
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| DPB1 | 4 | 412/4734 | 1075/9372 | 0.994 | 0.0 | F | 0.744 (0.652-0.848) | 0.001 | 4.41 | 0.781 (1.000) |
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| DPB1 | 5 | 744/3916 | 1031/3248 | 0.007 | 71.4 | R | 0.953 (0.728-1.248) | 0.727 | 0.35 | 0.129 (0.086) |
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| DPB1 | 5 | 177/3840 | 244/10166 | 0.015 | 67.7 | R | 1.518 (0.954-2.416) | 0.078 | 1.76 | 0.531 (0.806) |
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| rs4282438-T allele | 4 | 5309/10016 | 12197/18038 | 0.001 | 90.3 | R | 0.914 (0.688-1.213) | 0.533 | 0.62 | 0.382 (0.734) |
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| rs9277535 G allele | 4 | 4268/8266 | 4297/7402 | 0.509 | 0.0 | F | 0.802 (0.753-0.855) | 0.001 | 6.76 | 0.602 (1.000) |
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| rs3117027-G allele | 3 | 4994/7588 | 13159/18644 | 0.759 | 0.0 | F | 0.790 (0.745-0.837) | 0.001 | 7.92 | 0.055 (0.296) |
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| rs3077-C allele | 3 | 3494/5613 | 3374/5022 | 0.001 | 94.7 | R | 0.816 (0.560-1.189) | 0.290 | 1.06 | 0.957 (1.000) |
The HLA-DP rs9277535 and rs3077 were just studied among Asian population.
Meta-analysis of associations between HLA-DP alleles and cervical cancer in Asian.
| Alleles | No. of studies | Case (2n) | Control (2n) | Heterogeneity P value | I2 value (%) for heterogeneity test | Model | OR (95%CI) | P value | Z | P value for Egger's (Begg's) bias test |
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| DPB1 | 4 | 310/1764 | 369/2300 | 0.088 | 54.1 | R | 1.031 (0.781-1.362) | 0.829 | 0.22 | 0.109 (0.308) |
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| DPB1 | 4 | 98/1764 | 98/2300 | 0.228 | 30.7 | F | 1.317 (0.987-1.757) | 0.061 | 1.87 | 0.570 (0.734) |
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| DPB1 | 4 | 112/1764 | 158/2300 | 0.080 | 55.7 | R | 0.829 (0.524-1.314) | 0.426 | 0.80 | 0.277 (0.308) |
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| DPB1 | 4 | 679/1764 | 1012/2300 | 0.034 | 65.4 | R | 0.874 (0.680-1.123) | 0.291 | 1.06 | 0.358 (0.308) |
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| DPB1 | 4 | 150/1764 | 126/2300 | 0.099 | 52.1 | R | 1.834 (1.107-3.039) | 0.019 | 2.36 | 0.495 (0.734) |
Subgroup meta-analysis of associations between HLA-DP alleles and cervical cancer based on genotyping method.
| Alleles | No. of studies | Genotyping | Case (2n) | Control (2n) | Heterogeneity P value | I2 value (%) for heterogeneity test | Model | OR (95%CI) | P value | Z | P value for Egger's (Begg's) bias test |
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| DPB1 | 5 | PCR | 506/3764 | 1263/9940 | 0.011 | 69.2 | R | 0.960 (0.749-1.231) | 0.750 | -0.24 | 0.996 (1.000) |
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| DPB1 | 5 | PCR | 372/3726 | 908/9940 | 0.355 | 9.0 | F | 1.354 (1.144-1.604) | 0.001 | 0.24 | 0.804 (0.806) |
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| DPB1 | 5 | PCR | 1068/3740 | 3798/9930 | 0.129 | 43.9 | F | 0.951 (0.748-1.210) | 0.685 | 1.71 | 0.319 (0.086) |
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| DPB1 | 3 | PCR | 218/2582 | 961/8424 | 0.989 | 0.0 | F | 0.750 (0.642-0.877) | 0.001 | 1.02 | 0.640 (1.000) |
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| DPB1 | 4 | PCR | 679/1764 | 1012/2300 | 0.034 | 65.4 | R | 0.874 (0.680-1.123) | 0.291 | 0.00 | 0.358 (0.308) |
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| rs4282438 | 2 | PCR | 2244/2496 | 8012/8470 | 0.159 | 49.6 | F | 0.842 (0.653-1.087) | 0.186 | 0.00 | - (1.000) |
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| Rs9277535 | 3 | TaqMan | 3666/7320 | 3370/6050 | 0.313 | 13.8 | F | 0.800 (0.740-0.865) | 0.001 | 0.00 | 0.695 (1.000) |
Figure 2Forest plot of effect estimates for DPB1∗03:01 polymorphism and cervical cancer risk.
Figure 3Forest plot of effect estimates for DPB1∗04:02 polymorphism and cervical cancer risk.
Figure 4Forest plot of effect estimates for rs9277535 G allele and cervical cancer risk.
Figure 5Forest plot of effect estimates for DPB1∗13:01 polymorphism and cervical cancer risk.
Figure 6Sensitivity analysis of the pooled ORs and 95%CIs for DPB1∗03:01 polymorphism.
Figure 7Sensitivity analysis of the pooled ORs and 95%CIs for DPB1∗04:02 polymorphism.
Figure 8Sensitivity analysis of the pooled ORs and 95%CIs for rs9277535 G allele.
Figure 9Sensitivity analysis of the pooled ORs and 95%CIs for DPB1∗13:01 polymorphism.