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.
2020年，世界卫生组织（WHO）报告全球新增宫颈癌（CC）确诊病例604,000例，相关死亡病例超过300,000例。绝大多数宫颈癌病例由持续的人乳头瘤病毒（HPV）感染引起。随着HPV疫苗接种和巴氏涂片（PAP test）宫颈癌筛查的普及，全球范围内HPV相关宫颈癌的发病率和死亡率均呈下降趋势。尽管取得这些显著进展，发展中国家在实施这些项目时仍面临困难，而发达国家则面临识别非HPV依赖性病例的挑战。从血液或肿瘤样本中获取的分子和蛋白质组学信息，在揭示宫颈癌恶性进展及治疗反应方面具有巨大潜力。目前已有大量已发表的宫颈癌相关生物标志物数据，但缺乏美国食品药品监督管理局（FDA）批准临床使用所需的大规模验证。研究人员如何有效利用临床研究获得的大数据，并从中提取有意义的关联，是实现临床转化必须克服的两大障碍。本文报告了过去五年中已确定的宫颈癌血清蛋白质组学研究多标志物组合，探讨了现代计算生物学技术的应用潜力，以及如何利用国家生物样本库来弥合多变量蛋白质特征开发与临床相关宫颈癌患者预后预测之间的鸿沟。
Serum Proteomic Signatures in Cervical Cancer: Current Status and Future Directions
肿瘤(癌症)患者之家