Page 216 - Strategies for non-invasive managementof high-grade cervical intraepithelial neoplasia - prognostic biomarkers and immunotherapy Margot Maria Koeneman

Chapter 12
Human Leucocyte Antigens (HLA) alleles were identified a candidate prognostic biomarker for spontaneous regression of high-grade CIN. An individuals’ HLA repertoire determines the immune capacity, potentially influencing the capability of CIN clearance. In chapter 3, we assessed HLA-A, -B, -C, -DRB1 and -DQB1 alleles as prognostic biomarkers in a cohort of 32 women with high-grade CIN, who were followed for a median of 112 days before LLETZ was performed. We found no association was between any HLA allele and spontaneous regression of high-grade CIN. We did find a significant association between the HLA-DRB1*13/14 alleles and HPV status: all patients with these alleles were HPV16-negative, while HPV16 positive lesions did occur in patients without an HLA-DRB1*13/14 allele. HLA-DRB1*13/14 may therefore be protective against the development of HPV16-induced high-grade CIN. This indicates an early and HPV16-specific protective effect of an HLA- DRB1*13/14 epitope.
Gain of the human telomerase RNA gene (hTERC) was also identified as a promising biomarker for disease outcome in high-grade CIN. Overexpression of hTERC allows cells to avoid apoptosis, and thus contributes to carcinogenesis. In chapter 4, we assessed whether gain of the chromosomal 3q26 region – which contains the hTERC gene –, can predict the natural prognosis of high-grade CIN. To this aim, we first performed a review of the currently available literature. Eight studies were identified, most of which were performed in women with low-grade lesions. All studies found an association between 3q26 gain and disease prognosis. Positive predictive values (PPV) ranged from 50-93%, negative predictive values (NPV) ranged from 75-100%. Next, we performed a pilot study in 19 women with high-grade CIN who were followed for a mean of 115 days before LLETZ was performed. 3q26 gain was found in 15 lesions, of whom 10 showed disease persistence and 5 showed disease regression. Four lesions showed no 3q26 gain, all these lesions regressed. This resulted in a positive predictive value of 3q26 gain for disease persistence of 67%, and a negative predictive value of 100%. As such, the absence of 3q26 gain is an indicator of disease regression, but the test characteristics of 3q26 gain are insufficient for implementation as an individual prognostic biomarker. Further studies could focus on 3q26 gain as part of a prognostic biomarker profile, to improve test characteristics.
Treatment guidelines advice upon observational management of CIN2 lesions in younger women. However, adherence to this recommendation is not optimal. In the era of personalized medicine and shared decision making, a prediction model for spontaneous regression of CIN2 could improve the counseling of women with CIN2 for observational or invasive treatment. In Chapter 5, we developed such a prediction model. Analysis of 129 women with CIN 2 who were managed by watchful waiting for 6–24 months resulted in a prediction model that consisted of four simple clinical parameters: (1) smoking status, (2) PAP smear result, (3) concomitant CIN 1 in the same biopsy and (4) amount of biopsies containing CIN 2. The area under the curve of the model was 69.2% [95% confidence interval (CI), 58.5–79.9%], indicating a moderate-to-good discriminative ability of the model. The model proved to be more accurate in prediction of disease regression than disease persistence. The model can thus be applied to reassure patients that observational management is a good option when the model indicates a high probability of regression. As such, this prediction model for spontaneous regression of CIN 2 may aid physicians in the personalized management of these lesions.
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