BACKGROUND: DNA methylation may be used a potential biomarker for detecting cervical cancer. The authors of this report used quantitative methylation analysis of 4 genes in a full spectrum of cervical lesions to test its potential clinical application. METHODS: This hospital-based, retrospective, case-control study was conducted in 185 patients and included patients who had a normal uterine cervix (n = 53), cervical intraepithelial neoplasm type 1 (CIN1) (n = 37), CIN2 (n = 22), CIN3 (n = 24), carcinoma in situ (CIS) (n = 22), squamous cell carcinoma (SCC, n = 20), and adenocarcinoma (AC) (n = 7). Methylation levels of the genes sex-determining region Y, box 1 (SOX1); paired box gene 1 (PAX1); LIM homeobox transcription factor 1α (LMX1A), and NK6 transcription factor-related locus 1 (NKX6-1) were determined by using real-time methylation-specific polymerase chain reaction (PCR) amplification. Cutoff values of the percentage of methylation reference (PMR) for different diagnoses were determined to test the sensitivity and specificity and to generate receiver operating characteristic (ROC) curves. Two-sided Mann-Whitney U tests were used to test differences in PMR between groups. RESULTS: The PMRs of the 4 genes were significantly higher in CIN3 and worse (CIN3+) lesions than the PMRs in specimens of normal cervix and CIN1 or CIN2 (P < .001). ROC curve analysis demonstrated that the sensitivity, specificity, and accuracy for detecting CIN3+ lesions were 0.88, 0.82, and 0.95, respectively, for SOX1; 0.78, 0.91, and 0.89, respectively, for PAX1; 0.77, 0.88, and 0.90, respectively, for LMX1A; and 0.93, 0.97, and 0.97, respectively, for NKX6-1. CONCLUSIONS: The current results indicated that quantitative PCR-based testing for DNA methylation of 4 genes holds great promise for cervical cancer screening and warrants further population-based studies using standardized DNA methylation testing.
BACKGROUND: DNA methylation may be used a potential biomarker for detecting cervical cancer. The authors of this report used quantitative methylation analysis of 4 genes in a full spectrum of cervical lesions to test its potential clinical application. METHODS: This hospital-based, retrospective, case-control study was conducted in 185 patients and included patients who had a normal uterine cervix (n = 53), cervical intraepithelial neoplasm type 1 (CIN1) (n = 37), CIN2 (n = 22), CIN3 (n = 24), carcinoma in situ (CIS) (n = 22), squamous cell carcinoma (SCC, n = 20), and adenocarcinoma (AC) (n = 7). Methylation levels of the genes sex-determining region Y, box 1 (SOX1); paired box gene 1 (PAX1); LIM homeobox transcription factor 1α (LMX1A), and NK6 transcription factor-related locus 1 (NKX6-1) were determined by using real-time methylation-specific polymerase chain reaction (PCR) amplification. Cutoff values of the percentage of methylation reference (PMR) for different diagnoses were determined to test the sensitivity and specificity and to generate receiver operating characteristic (ROC) curves. Two-sided Mann-Whitney U tests were used to test differences in PMR between groups. RESULTS: The PMRs of the 4 genes were significantly higher in CIN3 and worse (CIN3+) lesions than the PMRs in specimens of normal cervix and CIN1 or CIN2 (P < .001). ROC curve analysis demonstrated that the sensitivity, specificity, and accuracy for detecting CIN3+ lesions were 0.88, 0.82, and 0.95, respectively, for SOX1; 0.78, 0.91, and 0.89, respectively, for PAX1; 0.77, 0.88, and 0.90, respectively, for LMX1A; and 0.93, 0.97, and 0.97, respectively, for NKX6-1. CONCLUSIONS: The current results indicated that quantitative PCR-based testing for DNA methylation of 4 genes holds great promise for cervical cancer screening and warrants further population-based studies using standardized DNA methylation testing.
Authors: Divya A Patel; Laura S Rozek; Justin A Colacino; Adrienne Van Zomeren-Dohm; Mack T Ruffin; Elizabeth R Unger; Dana C Dolinoy; David C Swan; Juanita Onyekwuluje; Cecilia R DeGraffinreid; Electra D Paskett Journal: J Virol Methods Date: 2012-06-01 Impact factor: 2.014
Authors: Megan A Clarke; Patricia Luhn; Julia C Gage; Clara Bodelon; S Terence Dunn; Joan Walker; Rosemary Zuna; Stephen Hewitt; J Keith Killian; Liying Yan; Andrew Miller; Mark Schiffman; Nicolas Wentzensen Journal: Int J Cancer Date: 2017-05-26 Impact factor: 7.396
Authors: Renske D M Steenbergen; Peter J F Snijders; Daniëlle A M Heideman; Chris J L M Meijer Journal: Nat Rev Cancer Date: 2014-06 Impact factor: 60.716