부산대학교 도서관

Simple Summary: In this literature review, we delve into the emerging prospects of of leveraging proteomic signatures and additional molecular data to enhance the clinical care and management of cervical cancer (CC) patients. By critical evaluation of existing research findings and elucidating recent advancements, we aim to provide an understanding of how proteomic signatures and molecular information on diagnostic, prognostic, and therapeutic strategies for CC. This review underscores the importance of integrating proteomic analysis into clinical practice, offering insights into its role in enhancing personalized treatment approaches and improving patient outcomes in the realm of cervical cancer management. Through a critical examination of current literature, we highlight the promising avenues for leveraging proteomic data to address the multifaceted challenges associated with CC diagnosis, treatment, and monitoring. In 2020, the World Health Organization (WHO) reported 604,000 new diagnoses of cervical cancer (CC) worldwide, and over 300,000 CC-related fatalities. The vast majority of CC cases are caused by persistent human papillomavirus (HPV) infections. HPV-related CC incidence and mortality rates have declined worldwide because of increased HPV vaccination and CC screening with the Papanicolaou test (PAP test). Despite these significant improvements, developing countries face difficulty implementing these programs, while developed nations are challenged with identifying HPV-independent cases. Molecular and proteomic information obtained from blood or tumor samples have a strong potential to provide information on malignancy progression and response to therapy in CC. There is a large amount of published biomarker data related to CC available but the extensive validation required by the FDA approval for clinical use is lacking. The ability of researchers to use the big data obtained from clinical studies and to draw meaningful relationships from these data are two obstacles that must be overcome for implementation into clinical practice. We report on identified multimarker panels of serum proteomic studies in CC for the past 5 years, the potential for modern computational biology efforts, and the utilization of nationwide biobanks to bridge the gap between multivariate protein signature development and the prediction of clinically relevant CC patient outcomes. [ABSTRACT FROM AUTHOR]