Abstract
Recent advances in cervical cancer diagnostics have transformed traditional screening approaches by integrating molecular, imaging, and digital innovations to enhance early detection, accuracy, and accessibility. High-risk HPV DNA testing has surpassed cytology in sensitivity, while emerging assays such as HPV mRNA detection, genotyping, and DNA methylation biomarkers (e.g., FAM19A4/miR124-2, CADM1/MAL) offer refined risk stratification and triage for HPV-positive women. Self-sampling and point-of-care molecular platforms improve screening reach, particularly in low-resource settings. Liquid biopsy techniques using circulating tumor DNA (ctDNA) and HPV-ctDNA hold promise for noninvasive disease monitoring and recurrence detection. Artificial intelligence (AI) and deep-learning systems enhance cytology and Colposcopic interpretation, addressing workforce shortages and improving diagnostic consistency. Additionally, radiomics, radiogenomics, and next-generation sequencing (NGS) contribute to personalized treatment planning and precision oncology. Despite these advances, barriers such as cost, infrastructure gaps, and limited large-scale validation persist. Standardization of molecular and AI tools and robust implementation research are needed to ensure global applicability. The integration of self-sampling, molecular triage, and AI-assisted diagnostics offers a scalable, equitable framework for cervical cancer control, particularly in resource-constrained environments.progress toward elimination.

Key Words:Cervical cancer, HPV testing, DNA methylation, Self-sampling, Liquid biopsy, Artificial intelligence, Next-generation sequencing, Molecular diagnostics, Screening, Radiogenomics
Citation:Pattnaik A, Acharya S (2025) Current Maternal Awareness, Knowledge, and Practices on Cervical Cancer Prevention. Journal of Cancer Cervix Eradication. 9(1):9-14