How Colposcopy Misses Invasive Cervical Cancer: A Case Report from the IMPROVE-COLPO Study

From Diagnosis to Treatment: Exploring the Latest Management Trends in Cervical Intraepithelial Neoplasia

Cervical intraepithelial neoplasia (CIN) stands as a precancerous condition with the potential to progress to invasive cervical cancer. This comprehensive review explores the intricacies of CIN management, beginning with its definition, classification, and etiology. It emphasizes the significance of early detection and outlines the latest trends in diagnosis, including Pap smears, human papillomavirus (HPV) testing, and colposcopy. Grading and staging, pivotal in treatment selection, are elucidated. Current management approaches, encompassing watchful waiting, surgical interventions, emerging minimally invasive techniques, and immunotherapy, are detailed. The factors influencing treatment decisions, informed consent, and patient education are discussed. Potential complications following treatment, the importance of long-term follow-up, and the role of HPV vaccination in prevention are underscored. Finally, the review looks to the future, discussing advances in detection, novel treatments, and the promise of precision medicine. In conclusion, early detection and management remain the cornerstone of CIN care, offering hope for a future where cervical cancer is a preventable and treatable condition.

Pap Smear miR-92a-5p and miR-155-5p as potential diagnostic biomarkers of squamous intraepithelial cervical cancer

BACKGROUND

one of the female-specific diseases with a high incidence and mortality is cervical cancer. The main cause of cervical cancer is infection with Human papilloma virus (HPV). Low-grade squamous intraepithelial lesions (LSIL) and High-grade squamous intraepithelial lesions (HSIL) usually is caused by an HPV infection. Considering the role of microRNAs (miRNAs) as diagnostic biomarkers for a variety of cancers, the aim of this study was to determine miR-92a-5p and miR-155-5p expression levels in LSIL and HSIL Pap Smear samples.

METHODS

After initial bioinformatic studies, A total of 75 samples (25 samples of patients with LSIL, 25 patients with HSIL and 25 healthy individuals) were subjected to RNA extraction and cDNA synthesis. The expressions levels of confirmed miRNAs in samples of patients with LSIL, HSIL and healthy individuals were evaluated by Real time PCR analysis. To demonstration the role of predicted miRNAs as novel biomarkers in diagnosis of LSIL and HSIL, ROC curve analysis was done.

RESULTS

Bioinformatics results showed that miR-92a-5p and miR-155-5p target the HPV E6 and E7 genes. The expression levels of these miRNAs were strikingly higher in Pap smear of patients with LSIL than in the healthy individuals (35.36, P = 0.001) (62.23, P = 0.001). Similarity, expression levels of miR-92a-5p and miR-155-5p were amazingly higher in patients with HSIL than in the healthy individuals (33.62, P= 0.001) (69.07, P= 0.001). Although, the levels of miR-92a-5p (0.95, P = 0. 85) and miR-155-5p (1.11, P = 0.84) exhibited no statistical differences between patients with LSIL and HSIL. Also, ROC curve analyses verified that miR-92a-5p and miR-155-5p are specific and sensitive and may serve as new biomarkers for the early detection of cervical cancer.

CONCLUSION

These data suggest miR-92a-5p and miR-155-5p, which are upregulated in LSIL and HSIL, can be consider as predictive biomarkers for the prognosis of cervical cancer patients.
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Optimization of Classification Strategies of Acetowhite Temporal Patterns towards Improving Diagnostic Performance of Colposcopy

Efforts have been being made to improve the diagnostic performance of colposcopy, trying to help better diagnose cervical cancer, particularly in developing countries. However, improvements in a number of areas are still necessary, such as the time it takes to process the full digital image of the cervix, the performance of the computing systems used to identify different kinds of tissues, and biopsy sampling. In this paper, we explore three different, well-known automatic classification methods (k-Nearest Neighbors, Naïve Bayes, and C4.5), in addition to different data models that take full advantage of this information and improve the diagnostic performance of colposcopy based on acetowhite temporal patterns. Based on the ROC and PRC area scores, the k-Nearest Neighbors and discrete PLA representation performed better than other methods. The values of sensitivity, specificity, and accuracy reached using this method were 60% (95% CI 50–70), 79% (95% CI 71–86), and 70% (95% CI 60–80), respectively. The acetowhitening phenomenon is not exclusive to high-grade lesions, and we have found acetowhite temporal patterns of epithelial changes that are not precancerous lesions but that are similar to positive ones. These findings need to be considered when developing more robust computing systems in the future.