| Literature DB >> 27529629 |
Monica Molano1, Sepehr N Tabrizi1,2,3, Suzanne M Garland1,2,3, Jennifer M Roberts4, Dorothy A Machalek1,2, Samuel Phillips1,2, David Chandler5, Richard J Hillman6,7, Andrew E Grulich8, Fengyi Jin8, I Mary Poynten8, David J Templeton8,9, Alyssa M Cornall1,2.
Abstract
Incidence and mortality rates of anal cancer are increasing globally. More than 90% of anal squamous cell carcinomas (ASCC) are associated with human papillomavirus (HPV). Studies on HPV-related anogenital lesions have shown that patterns of methylation of viral and cellular DNA targets could potentially be developed as disease biomarkers. Lesion-specific DNA isolated from formalin-fixed paraffin-embedded (FFPE) tissues from existing or prospective patient cohorts may constitute a valuable resource for methylation analysis. However, low concentrations of DNA make these samples technically challenging to analyse using existing methods. We therefore set out to develop a sensitive and reproducible nested PCR-pyrosequencing based method to accurately quantify methylation at 10 CpG sites within the E2BS1, E2BS2,3,4 and Sp1 binding sites in the viral upstream regulatory region of HPV16 genome. Methylation analyses using primary and nested PCR-pyrosequencing on 52 FFPE tissue [26 paired whole tissue sections (WTS) and laser capture microdissected (LCM) tissues] from patients with anal squamous intraepithelial lesions was performed. Using nested PCR, methylation results were obtained for the E2BS1, E2BS2,3,4 and Sp1 binding sites in 86.4% of the WTS and 81.8% of the LCM samples. Methylation patterns were strongly correlated within median values of matched pairs of WTS and LCM sections, but overall methylation was higher in LCM samples at different CpG sites. High grade lesions showed low methylation levels in the E2BS1 and E2BS2 regions, with increased methylation detected in the E2BS,3,4/Sp1 regions, showing the highest methylation at CpG site 37. The method developed is highly sensitive in samples with low amounts of DNA and demonstrated to be suitable for archival samples. Our data shows a possible role of specific methylation in the HPV16 URR for detection of HSIL.Entities:
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Year: 2016 PMID: 27529629 PMCID: PMC4987059 DOI: 10.1371/journal.pone.0160673
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Schematic representation of the HPV16 URR including the 10 CpG sites studied and location of PCR primers.
Fig 2Detection limits for primary and nested PCRs.
Serial dilutions of SiHa were subjected to primary PCR using specific primers for (A) E2BS1 region and (B) E2BS2,3,4 region of HPV16 in triplicate reactions. The primary PCR reactions were then used as templates to conduct nested PCR.
Inter-assay reproducibility and intra-assay repeatability of methylation at 10 different CpG sites of HPV16 URR in CaSki and SiHa cells.
| E2BS1 | E2BS2 | E2BS3,4 | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 7459 CpG | 7453 CpG | 7432 CpG | 7426 CpG | 7860 CpG | 31 CpG | 37 CpG | 43 CpG | 52 CpG | 58 CpG | |||
| Mean | 65.3 | 68.8 | 42.0 | 48.3 | 21.0 | 92.0 | 93.0 | 99.3 | 97.8 | 99.5 | ||
| SD | 2.8 | 3.1 | 2.7 | 3.0 | 1.2 | 1.6 | 1.2 | 1.3 | 2.3 | 0.9 | ||
| CV (%) | 4.3 | 4.5 | 6.5 | 6.2 | 5.8 | 1.7 | 1.3 | 1.3 | 2.3 | 0.8 | ||
| Mean | 3.5 | 1.8 | 6.8 | 2.8 | 1.0 | 1.0 | 2.3 | 1.3 | 2.0 | 2.3 | ||
| SD | 1.1 | 0.4 | 0.8 | 1.1 | 0.0 | 0.0 | 0.43 | 0.43 | 0.7 | 0.4 | ||
| CV (%) | 3.1 | 2.4 | 1.2 | 3.9 | 0.0 | 0.0 | 1.9 | 3.4 | 3.5 | 1.9 | ||
| Mean | 65.3 | 67.3 | 40.3 | 46.36 | 21.36 | 93.0 | 93.7 | 100.0 | 97.3 | 100.0 | ||
| SD | 0.6 | 0.6 | 0.6 | 0.6 | 0.6 | 0.0 | 0.6 | 0.0 | 0.6 | 0.0 | ||
| CV (%) | 0.9 | 0.9 | 1.46 | 1.26 | 2.7 | 0.0 | 0.6 | 0.0 | 0.6 | 0.0 | ||
| Mean | 4.0 | 2.3 | 5.3 | 3.7 | 1.0 | 1.0 | 2.0 | 1.0 | 2.0 | 1.7 | ||
| SD | 0.0 | 0.6 | 0.6 | 0.6 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6 | ||
| CV (%) | 0.0 | 2.5 | 1.1 | 1.6 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3.5 | ||
Fig 3Comparison of methylation patterns by PCR type (Primary/nested) at 10 CpG sites of the URR of HPV 16 in (A) SiHa and (B) CaSki cells.
The percentage of methylation for each CpG site are mean (±S.D) of four sequencing reactions. Coefficient of correlation between primary and nested PCRs were 0.986 and 0.999 in SiHa and CaSki cells respectively. Error bars indicate standard deviation.
Fig 4Representative pyrograms showing methylation levels at 10 CpG sites within the E2BS1, E2BS2,3,4 and Sp1 binding sites of HPV16 URR in SiHa and CaSki cells using nested amplified products.
Percentage of amplification of the different regions using primary and nested PCRs in 44 samples.
| AMPLIFIED REGION | TISSUE | |||||||
|---|---|---|---|---|---|---|---|---|
| WTS | LCM | |||||||
| Primary | Nested | Primary | Nested | |||||
| n | % | n | % | n | % | n | % | |
| 9 | 40.9 | 19 | 86.4 | 4 | 18.2 | 18 | 81.8 | |
| 4 | 18.2 | 2 | 9.1 | 7 | 31.8 | 1 | 4.5 | |
| 1 | 4.5 | 1 | 4.5 | 2 | 9.1 | 3 | 13.7 | |
| 8 | 36.4 | 9 | 40.9 | |||||
| 22 | 100 | 22 | 100 | 22 | 100 | 22 | 100 | |
Fig 5Correlation of methylation between primary and nested PCR in (A) WTS and (B) LCM samples.
Correlations were determined using the Spearman rank correlation coefficient (rs). P ≤ 0.05 are considered significant.
Fig 6Pattern of methylation in 10 CpG sites of HPV16 URR using matched whole tissue sections (WTS) and laser capture microdissected (LCM) samples of patients with anal squamous intraepithelial lesions.
Methylation levels at each CpG site represent mean of 14 subjects. Error bars indicate SD.
Fig 7Analysis of methylation comparing median values between whole tissue section (WTS) and laser capture microdissected (LCM) tissue p value was derived from Wilcoxon matched pairs test comparisons.
The central mark of the boxplots indicate the median, the edges mark of the box indicate the 25th and 75th percentiles and the whiskers indicate the minimum and maximum values. Individual points (circles) represent outliers.