| Literature DB >> 21747645 |
Aris Spathis1, Evaggelia Aga, Maria Alepaki, Aikaterini Chranioti, Christos Meristoudis, Ioannis Panayiotides, Dimitrios Kassanos, Petros Karakitsos.
Abstract
Cervical cancer is a common cancer inflicting women worldwide. Even though, persistent infection with oncogenic Human Papillomavirus (HPV) types is considered the most important risk factor for cervical cancer development, less than 5% of women with HPV will eventually develop cervical cancer supporting that other molecular events, like methylation-dependent inactivation of tumor suppressor genes, may cocontribute in cervical carcinogenesis. We analyzed promoter methylation of three candidate genes (p16, MGMT, and hMLH1) in 403 liquid-based cytology samples. Methylation was commonly identified in both benign and pathologic samples and correlated with higher lesion grade determined by cytological, colposcopical, or histological findings, with HPV DNA and mRNA positivity of specific HPV types and p16(INK4A) protein expression. Overall accuracy of methylation is much lower than traditional diagnostic tests ranking it as an ancillary technique with more data needed to identify the exact value of methylation status in cervical carcinogenesis.Entities:
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Year: 2011 PMID: 21747645 PMCID: PMC3124238 DOI: 10.1155/2011/927861
Source DB: PubMed Journal: Infect Dis Obstet Gynecol ISSN: 1064-7449
Figure 1Agarose gel electrophoresis of PCR products of gene promoter methylation of (a) MGMT, (b) hMLH1, and (c) p16INK4A. L: DNA ladder 50 bp, +ctl: DNA treated with SssI, −ctl: unmethylated DNA control, s1,s2: clinical samples negative for methylation for MGMT and hMLH1. s2 is positive for p16 methylation.
Promoter methylation results.
| MGMT | hMLH1 | p16INK4A | Any gene | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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| (%) |
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| (%) |
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| (%) |
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| (%) |
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| Cytology | WNL | 22 | 22.7 | 97 | *** | 5 | 5.7 | 88 | * | 7 | 13.5 | 52 | 31 | 32.0 | 97 | *** | |
| ASCUS | 26 | 40.7 | 64 | 4 | 7.0 | 57 | 9 | 18.4 | 49 | 33 | 51.6 | 64 | |||||
| LgSIL | 51 | 38.6 | 132 | 22 | 17.9 | 123 | 18 | 17.5 | 103 | 75 | 56.8 | 132 | |||||
| ASC-H | 3 | 37.5 | 8 | 1 | 14.3 | 7 | 1 | 33.3 | 3 | 4 | 50.0 | 8 | |||||
| HgSIL | 43 | 47.3 | 91 | 13 | 14.8 | 88 | 15 | 19.7 | 76 | 54 | 59.3 | 91 | |||||
| SCC | 5 | 80.0 | 6 | 0 | 0 | 5 | 1 | 33.3 | 3 | 5 | 83.3 | 6 | |||||
| AdenoCa | 5 | 100 | 5 | 2 | 50.0 | 4 | 3 | 75.0 | 4 | 5 | 100 | 5 | |||||
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| Colposcopy | NSF | 3 | 42.9 | 7 | *** | 0 | 0 | 7 | * | 0 | 0 | 5 | 3 | 42.9 | 7 | *** | |
| Negative | 25 | 27.2 | 93 | 6 | 7.3 | 82 | 11 | 21.2 | 52 | 35 | 38.0 | 93 | |||||
| LGSIL | 74 | 38.7 | 191 | 24 | 13.6 | 177 | 25 | 17.6 | 142 | 100 | 52.4 | 191 | |||||
| HGSIL | 40 | 40.8 | 98 | 15 | 16.1 | 93 | 15 | 18.5 | 81 | 56 | 57.1 | 98 | |||||
| SCC | 9 | 81.8 | 11 | 1 | 10.0 | 10 | 1 | 14.3 | 7 | 9 | 81.8 | 11 | |||||
| AdenoCa | 4 | 100 | 4 | 1 | 33.3 | 3 | 2 | 66.7 | 3 | 4 | 100 | 4 | |||||
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| Histology | Negative | 13 | 22.8 | 57 | *** | 8 | 15.1 | 53 | 5 | 12.2 | 41 | 21 | 36.8 | 57 | ** | ||
| LSIL | 70 | 42.7 | 164 | 21 | 13.5 | 155 | 25 | 20.7 | 121 | 95 | 57.9 | 164 | |||||
| HSIL | 43 | 42.6 | 101 | 14 | 14.6 | 96 | 15 | 17.6 | 85 | 57 | 56.4 | 101 | |||||
| SCC | 8 | 66.7 | 12 | 1 | 9.1 | 11 | 1 | 12.5 | 8 | 8 | 66.7 | 12 | |||||
| AdenoCa | 6 | 100 | 6 | 2 | 40.0 | 5 | 3 | 75.0 | 4 | 6 | 100 | 6 | |||||
M: Methylated, N: Number of cases, NSF: Nonsatisfactory, χ 2 for trend P: *P < .05, **P < .005, ***P < .001.
Figure 2ROC curve analysis. Diagonal segments are produced by ties.