Candidate RNA biomarkers in biofluids for early diagnosis of ovarian cancer: A systematic review

Ovarian cancer is often diagnosed in an advanced stage and is associated with a high mortality rate. It is assumed that early detection of ovarian cancer could improve patient outcomes. Unfortunately, effective screening methods for early diagnosis of ovarian cancer are still lacking. Extracellular RNAs circulating in human biofluids can reliably be measured and are emerging as potential biomarkers in cancer. In this systematic review, we present 75 RNA biomarkers detectable in human biofluids that have been studied for early diagnosis of ovarian cancer. The majority of these markers are microRNAs identified using RT-qPCR or microarrays in blood-based fluids. A handful of studies used RNA-sequencing and explored alternative fluids, such as urine and ascites. Candidate RNA biomarkers that were more abundant in biofluids of ovarian cancer patients compared to controls in at least two independent studies include miR-21, the miR-200 family, miR-205, miR-10a and miR-346. Amongst the markers confirmed to be lower in at least two studies are miR-122, miR-193a, miR-223, miR-126 and miR-106b. While these biomarkers show promising diagnostic potential, further validation is required before implementation in routine clinical care. Challenges related to biomarker validation and reflections on future perspectives to accelerate progress in this field are discussed. (c) 2020 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

This systematic review presents 75 RNA biomarkers detectable in human biofluids for early diagnosis of ovarian cancer, with the majority identified using RT-qPCR or microarrays in blood-based fluids. Some studies utilized RNA-sequencing and looked into alternative fluids like urine and ascites. Promising biomarkers include miR-21, the miR-200 family, miR-205, miR-10a, and miR-346, while validation and further research are needed before clinical implementation. Challenges in biomarker validation and future perspectives are discussed to accelerate progress in this field.