Dataset Information

TMEM45A, SERPINB5 and p16INK4A transcript levels are predictive for development of high-grade cervical lesions.

ABSTRACT: Women persistently infected with human papillomavirus (HPV) type 16 are at high risk for development of cervical intraepithelial neoplasia grade 3 or cervical cancer (CIN3+). We aimed to identify biomarkers for progression to CIN3+ in women with persistent HPV16 infection. In this prospective study, 11,088 women aged 20-29 years were enrolled during 1991-1993, and re-invited for a second visit two years later. Cervical cytology samples obtained at both visits were tested for HPV DNA by Hybrid Capture 2 (HC2), and HC2-positive samples were genotyped by INNO-LiPA. The cohort was followed for up to 19 years via a national pathology register. To identify markers for progression to CIN3+, we performed microarray analysis on RNA extracted from cervical swabs of 30 women with persistent HPV16-infection and 11 HPV-negative women. Six genes were selected and validated by quantitative PCR. Three genes were subsequently validated within a different and large group of women from the same cohort. Secondly, Kaplan-Meier and Cox-regression analyses were used to investigate whether expression levels of those three genes predict progression to CIN3+. We found that high transcript levels of TMEM45A, SERPINB5 and p16INK4a at baseline were associated with increased risk of CIN3+ during follow-up. The hazard ratios of CIN3+ per 10-fold increase in baseline expression level were 1.6 (95% CI: 1.1-2.3) for TMEM45A, 1.6 (95% CI: 1.1-2.5) for p16INK4a, and 1.8 (95% CI: 1.2-2.7) for SERPINB5. In conclusion, high mRNA expression levels of TMEM45A, SERPINB5 and p16INK4a were associated with increased risk of CIN3+ in persistently HPV16-infected women.

SUBMITTER: Manawapat-Klopfer A

PROVIDER: S-EPMC4969401 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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TMEM45A, SERPINB5 and p16INK4A transcript levels are predictive for development of high-grade cervical lesions.

Manawapat-Klopfer Anna A Thomsen Louise T LT Martus Peter P Munk Christian C Russ Rainer R Gmuender Hans H Frederiksen Kirsten K Haedicke-Jarboui Juliane J Stubenrauch Frank F Kjaer Susanne K SK Iftner Thomas T

American journal of cancer research 20160701 7

Women persistently infected with human papillomavirus (HPV) type 16 are at high risk for development of cervical intraepithelial neoplasia grade 3 or cervical cancer (CIN3+). We aimed to identify biomarkers for progression to CIN3+ in women with persistent HPV16 infection. In this prospective study, 11,088 women aged 20-29 years were enrolled during 1991-1993, and re-invited for a second visit two years later. Cervical cytology samples obtained at both visits were tested for HPV DNA by Hybrid Ca ...[more]

PMID: 27508094

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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:Background. MicroRNAs (miRNAs) are short (~22 nt) non-coding regulatory RNAs that control gene expression at the translational level. Deregulation of miRNA expression has been discovered in a wide variety of tumours and it is now clear that they contribute to cancer development and progression. This prompted the development of miRNA-chips for cancer diagnosis or prognosis, opening a new door to understand carcinogenesis. Cervical cancer is one of the most common cancers in women worldwide. Therefore, there is a strong need for a non-invasive, fast and efficient method to diagnose the disease. We investigated miRNA expression profiles in cervical cancer using a microarray platform developed in house containing probes for mature miRNAs. Results. We have evaluated miRNA expression profiles of a heterogeneous set of cervical tissues from 25 different patients. This set included 19 normal cervical tissues, 4 squamous cell carcinoma, 5 high-grade squamous intraepithelial lesion (HSIL) and 9 low-grade squamous intraepithelial lesion (LSIL) samples. We observed high variability in miRNA expression especially among normal cervical samples, which prevented us from obtaining a unique miRNA expression signature for this tumour type. However, miRNAs deregulation in malignant and pre-malignant cervical tissues was detected after tackling the high variability observed. We were also able to identify putative targets of relevant candidate miRNAs. Conclusions. Our results show that miRNA deregulation may play an important role in the malignant transformation of cervical squamous cells. In addition, deregulated miRNAs highlight new candidate targets allowing a better understanding of the molecular mechanism of this tumour type. In this study we used a common reference design experiment where the common reference used was a commercial RNA from normal cervix (Ambion) and the test samples were 4 pre-treatment squamous cell cervical carcinoma, 7 high-grade Squamous Intraepithelial Lesion (CINII, n=2 and CIN III, n=5) sample, 9 low-grade Squamous Intraepithelial Lesion (CIN I) samples, 19 normal cervix samples and 4 pools of normal cervix samples.

Dataset Information

TMEM45A, SERPINB5 and p16INK4A transcript levels are predictive for development of high-grade cervical lesions.

Publications

TMEM45A, SERPINB5 and p16INK4A transcript levels are predictive for development of high-grade cervical lesions.

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