Shanshan Li¹ , Mingzi Huang² , Chunyan Ji¹

1 Prenatal Diagnosis Center, Department of the gynecology and obstetrics, The Sixth Medical Center of PLA General Hospital, Beijing, 100048, Beijing, China
2 Liuliqiao Outpatient Department, Jingnan Medical Area of PLA General Hospital, Beijing, 100161, Beijing, China
Author    Correspondence author
International Journal of Molecular Medical Science, 2024, Vol. 14, No. 5   
Received: 16 Jul., 2024    Accepted: 24 Aug., 2024    Published: 06 Sep., 2024

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Cervical cancer remains a significant public health issue, especially in low- and middle-income countries. While traditional screening methods such as Pap smears and HPV DNA testing have reduced the incidence and mortality of cervical cancer, they are limited in sensitivity, specificity, and the ability to differentiate between transient and persistent high-risk infections. This study reviews the current status of cervical cancer screening and prevention, with a focus on the role of genetic markers in enhancing early screening accuracy and guiding personalized prevention strategies. The paper also addresses challenges associated with implementing these advanced methods, including cost, accessibility, ethical considerations, and the need for healthcare system adaptation. Recent advancements in genetic marker-based screening, such as next-generation sequencing (NGS), DNA methylation panels, and emerging biomarkers like microRNAs (miRNAs), have opened up new avenues for early detection and more precise risk stratification. Embracing these advancements can enable healthcare systems to enhance early detection and prevention of cervical cancer, ultimately reducing its global burden.

Cervical cancer; Genetic markers; Early screening; DNA methylation; Next-generation sequencing (NGS); Artificial intelligence (AI)