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宫颈癌中的血清蛋白质组学特征:现状与未来方向

Serum Proteomic Signatures in Cervical Cancer: Current Status and Future Directions.

作者信息

Weaver Chaston, Nam Alisha, Settle Caitlin, Overton Madelyn, Giddens Maya, Richardson Katherine P, Piver Rachael, Mysona David P, Rungruang Bunja, Ghamande Sharad, McIndoe Richard, Purohit Sharad

机构信息

Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.

Department of Undergraduate Health Professions, College of Allied Health Sciences, Augusta University, Augusta, GA 30912, USA.

出版信息

Cancers (Basel). 2024 Apr 24;16(9):1629. doi: 10.3390/cancers16091629.

Abstract

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.

摘要

2020年,世界卫生组织(WHO)报告称,全球有60.4万例宫颈癌(CC)新诊断病例,以及超过30万例与CC相关的死亡病例。绝大多数CC病例是由持续性人乳头瘤病毒(HPV)感染引起的。由于HPV疫苗接种增加以及采用巴氏试验(PAP试验)进行CC筛查,全球范围内与HPV相关的CC发病率和死亡率有所下降。尽管取得了这些显著进展,但发展中国家在实施这些计划时面临困难,而发达国家则在识别非HPV相关病例方面面临挑战。从血液或肿瘤样本中获得的分子和蛋白质组学信息极有可能提供有关CC恶性进展和对治疗反应的信息。有大量已发表的与CC相关的生物标志物数据,但缺乏FDA批准临床使用所需的广泛验证。研究人员利用从临床研究中获得的大数据并从这些数据中得出有意义关系的能力是在临床实践中实施必须克服的两个障碍。我们报告了过去5年中CC血清蛋白质组学研究中确定的多标志物组合、现代计算生物学研究的潜力,以及利用全国生物样本库弥合多变量蛋白质特征开发与预测临床相关CC患者结局之间的差距。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7060/11083044/0bda4c9bc042/cancers-16-01629-g001.jpg

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