Exploration of biomarkers for the diagnosis, treatment and prognosis of cervical cancer: a review

被引:0
作者
Masita Arip
Lee Fang Tan
Rama Jayaraj
Maha Abdullah
Mogana Rajagopal
Malarvili Selvaraja
机构
[1] Institute for Medical Research,Allergy & Immunology Research Centre
[2] National Institute of Health,Department of Pharmaceutical Biology, Faculty of Pharmaceutical Sciences
[3] UCSI University,Immunology Unit, Department of Pathology, Faculty of Medicine and Health Sciences
[4] Universiti Putra Malaysia,undefined
[5] Charles Darwin University,undefined
来源
Discover Oncology | / 13卷
关键词
Biomarker; Cervical cancer; Omics; Genomics; Transcriptomics; Proteomics; Metabolomics; High throughput;
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摘要
As the fourth most diagnosed cancer, cervical cancer (CC) is one of the major causes of cancer-related mortality affecting females globally, particularly when diagnosed at advanced stage. Discoveries of CC biomarkers pave the road to precision medicine for better patient outcomes. High throughput omics technologies, characterized by big data production further accelerate the process. To date, various CC biomarkers have been discovered through the advancement in technologies. Despite, very few have successfully translated into clinical practice due to the paucity of validation through large scale clinical studies. While vast amounts of data are generated by the omics technologies, challenges arise in identifying the clinically relevant data for translational research as analyses of single-level omics approaches rarely provide causal relations. Integrative multi-omics approaches across different levels of cellular function enable better comprehension of the fundamental biology of CC by highlighting the interrelationships of the involved biomolecules and their function, aiding in identification of novel integrated biomarker profile for precision medicine. Establishment of a worldwide Early Detection Research Network (EDRN) system helps accelerating the pace of biomarker translation. To fill the research gap, we review the recent research progress on CC biomarker development from the application of high throughput omics technologies with sections covering genomics, transcriptomics, proteomics, and metabolomics.
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