Dataset Information

The CpG island methylator phenotype increases the risk of high-grade squamous intraepithelial lesions and cervical cancer.

ABSTRACT:

Background

High-risk human papillomavirus (HR-HPV) infection is the main cause of cervical cancer, but additional alterations are necessary for its development. Abnormal DNA methylation has an important role in the origin and dissemination of cervical cancer and other human tumors. In this work, we analyzed the methylation of eight genes (AJAP1, CDH1, CDH13, MAGI2, MGMT, MYOD1, RASSF1A and SOX17) that participate in several biological processes for the maintenance of cell normality. We analyzed DNA methylation by methylation-specific PCR (MSP) and HPV infection using the INNO‑LiPA genotyping kit in 59 samples diagnostic of normal cervical tissue (non-SIL), 107 low-grade squamous intraepithelial lesions (LSILs), 29 high-grade squamous intraepithelial lesions (HSILs) and 51 cervical cancers (CCs).

Results

We found that all samples of LSIL, HSIL, and CC were HPV-positive, and the genotypes with higher frequencies were 16, 18, 51 and 56. In general, the genes analyzed displayed a significant tendency toward an increase in methylation levels according to increasing cervical lesion severity, except for the CDH13 gene. High CpG island methylator phenotype (CIMP) was associated with a 50.6-fold (95% CI 4.72-2267.3)-increased risk of HSIL and a 122-fold risk of CC (95% CI 10.04-5349.7).

Conclusions

We found that CIMP high was significantly associated with HSIL and CC risk. These results could indicate that CIMP together with HR-HPV infection and other factors participates in the development of HSIL and CC.

SUBMITTER: Loaeza-Loaeza J

PROVIDER: S-EPMC8740093 | biostudies-literature |

REPOSITORIES: biostudies-literature

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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.