Dataset Information

DNA methylation in human papillomavirus-infected cervical cells is elevated in high-grade squamous intraepithelial lesions and cancer.

ABSTRACT:

Objective

DNA methylation has been shown to be a potential biomarker for early cancer detection. The aim of this study was to evaluate DNA methylation profiles according to liquid-based Pap (LBP) test results and to assess their diagnostic value in a Korean population.

Methods

A total of 205 patients with various Papanicolaou test results were enrolled to this study (negative, 26; atypical squamous cells of undetermined significance, 39; low grade squamous intraepithelial lesion, 44; high grade squamous intraepithelial lesion (HSIL), 48; and cancer, 48). DNA methylation analysis of four genes, ADCYAP1, PAX1, MAL, and CADM1, was performed on residual cervical cells from LBP samples using a quantitative bisulfite pyrosequencing method. To evaluate the diagnostic performance of the four methylated genes for cancer detection, receiver operating characteristic (ROC) curves were drawn. Sensitivities and specificities were also tested at cutoffs determined from the ROC curves.

Results

Cervical cancer cells showed dramatically increased methylation levels for the four genes analyzed. ADCYAP1 and PAX1 also trended toward elevated methylation levels in HSIL samples, although the levels were much lower than those in cancer cells. The sensitivities of methylated ADCYAP1, PAX1, MAL, and CADM1 for the detection of cancer were 79.2%, 75.0%, 70.8%, and 52.1%, and the specificities were 92.0%, 94.0%, 94.7%, and 94.0%, respectively. Methylated ADCYAP1 and PAX1 demonstrated relatively better discriminatory ability than did methylated MAL and CADM1 (area under the curves 0.911 and 0.916 vs. 0.854 and 0.756, respectively).

Conclusion

DNA methylation status, especially in the ADCYAP1 and PAX1 genes, showed relatively good specificity, ranging from 90% to 94%. The possible additive and complementary roles of DNA methylation testing with respect to conventional cervical cancer screening programs will need to be validated in prospective population-based studies.

SUBMITTER: Kim MK

PROVIDER: S-EPMC4717219 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Publications

DNA methylation in human papillomavirus-infected cervical cells is elevated in high-grade squamous intraepithelial lesions and cancer.

Kim Mi-Kyung MK Lee In-Ho IH Lee Ki-Heon KH Lee Yoo Kyung YK So Kyeong A KA Hong Sung Ran SR Hwang Chang-Sun CS Kee Mee-Kyung MK Rhee Jee Eun JE Kang Chun C Hur Soo Young SY Park Jong Sup JS Kim Tae-Jin TJ

Journal of gynecologic oncology 20160301 2

<h4>Objective</h4>DNA methylation has been shown to be a potential biomarker for early cancer detection. The aim of this study was to evaluate DNA methylation profiles according to liquid-based Pap (LBP) test results and to assess their diagnostic value in a Korean population.<h4>Methods</h4>A total of 205 patients with various Papanicolaou test results were enrolled to this study (negative, 26; atypical squamous cells of undetermined significance, 39; low grade squamous intraepithelial lesion, ...[more]

PMID: 26768780

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Project description:It is crucial to classify cervical lesions into high-grade squamous intraepithelial lesions (HSILs) and low-grade SILs (LSILs), as LSILs are conservatively treated by observation, based on an expectation of natural regression, whereas HSILs usually require electrosurgical excision. In the present study, peripheral blood gene expression profiles were analyzed to identify transcriptomic biomarkers distinguishing HSILs from LSILs. A total of 102 blood samples were collected from women with cervical SILs (66 HSIL and 36 LSIL) for microarray hybridization. Candidate gene signatures were identified using AdaBoost algorithms, and a predictive model was constructed using logistic regression to differentiate HSILs from LSILs. To correct for possible bias as a result of the limited sample size and to verify the stability of the predictive model, a two-fold cross validation and null set analysis was conducted over 1,000 iterations. The functions of the transcriptomic biomarkers were then analyzed to elucidate the pathogenesis of cervical SIL. A total of 10 transcriptomic genes (STMN3, TRPC4AP, DYRK2, AGK, KIAA0319L, GRPEL1, ZFC3H1, LYL1, ITGB1 and ARHGAP18) were identified. The predictive model based on the 10-gene panel exhibited well-discriminated power. A cross validation process using known disease status exhibited almost the same performance as that of the predictive model, whereas null-set analysis with randomly reassigned disease status exhibited much lower predictive performance for distinguishing HSILs from LSILs. These biomarkers were involved in the 'Rho GTPase cycle', 'mitochondrial protein import', 'oncogenic MAPK signaling', 'integrin cell surface interaction' and 'signaling by BRAF and RAF fusions'. In conclusion, peripheral blood gene expression analysis is a promising method for distinguishing HSILs from LSILs. The present study proposes 10 candidate genes that could be used in the future as diagnostic biomarkers and potential therapeutic targets for cervical SILs. A simple, non-invasive blood test would be clinically useful in the diagnosis and classification of patients with cervical SILs.

Project description:BackgroundThe complete response rate of cervical high-grade squamous intraepithelial lesion (cHSIL) patients to imiquimod immunotherapy is approximately 60%. Consequently, many patients are exposed to unnecessary adverse effects of imiquimod. On the other hand, conventional surgical large loop excision therapy is associated with increased risk of premature births in subsequent pregnancies. An in-depth analysis of the cHSIL immune microenvironment was performed in order to identify and develop a predictive biomarker for response to imiquimod, to maximize therapy efficacy and to avoid adverse effects in patients unlikely to respond.MethodsBiopsies of 35 cHSIL patients, before and 10 weeks on imiquimod treatment, were analyzed by two multispectral seven-color immunofluorescence panels for T cell and myeloid cell composition in relation to treatment response. Based on these results a simplified immunohistochemical detection protocol was developed. Samples were scanned with the Vectra multispectral imaging system and cells were automatically identified using machine learning.ResultsThe immune microenvironment of complete responders (CR) is characterized by a strong and coordinated infiltration by T helper cells (activated PD1+/type 1 Tbet+), M1-like macrophages (CD68+CD163-) and dendritic cells (CD11c+) prior to imiquimod. The lesions of non-responders (NRs) displayed a high infiltration by CD3+FOXP3+ regulatory T cells. At 10 weeks on imiquimod, a strong influx of intraepithelial and stromal CD4+ T cells was observed in CR but not NR patients. A steep decrease in macrophages occurred both in CR and NR patients, leveling the pre-existing differences in myeloid cell composition between the two groups. Based on the pre-existing immune composition differences, the sum of intraepithelial CD4 T cell, macrophage and dendritic cell counts was used to develop a quantitative simplified one color immunohistochemical biomarker, the CHSIL immune biomarker for imiquimod (CIBI), which can be automatically and unbiasedly quantified and has an excellent predictive capacity (receiver operating characteristic area under the curve 0.95, p<0.0001).ConclusionThe capacity of cHSIL patients to respond to imiquimod is associated with a pre-existing coordinated local immune process, fostering an imiquimod-mediated increase in local T cell infiltration. The CIBI immunohistochemical biomarker has strong potential to select cHSIL patients with a high likelihood to experience a complete response to imiquimod immunotherapy.

Dataset Information

DNA methylation in human papillomavirus-infected cervical cells is elevated in high-grade squamous intraepithelial lesions and cancer.

Objective

Methods

Results

Conclusion

Publications

DNA methylation in human papillomavirus-infected cervical cells is elevated in high-grade squamous intraepithelial lesions and cancer.

Similar Datasets

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