Modern emerging biosensing methodologies for the early diagnosis and screening of ovarian cancer

Ovarian cancer (OC) is one of the leading causes of gynecological cancer-related death worldwide. Late diagnosis at advanced stages of OC is the reason for a higher mortality rate. Earlier diagnosis and proper treatment are important for improving the prognosis of OC patients. Biosensors offer accurate, low-cost, rapid, and user-friendly devices that can be employed for the detection of OC-specific biomarkers in the early stage. Therefore, it is important to consider the potential biomarkers in the biological fluids to confirm the OC prognosis. Out of many biomarkers, the most commonly tested clinically is cancer antigen 125 (CA-125). However, CA-125 is considered to be a poor biomarker for OC diagnosis. Several biosensing methods were developed for the sensitive and quantitative detection of each biomarker. In abnormal expression in OC patients, nucleic acids, enzymes, cells, and exosomes are used as target biomarkers for the construction of biosensors. This review focuses on the development for the detection of various biomarkers using multiple biosensing methods. Here, we describe the origin and the significance of OC-associated biomarkers, the working principle of biosensors, and the classification of biosensors based on their recognition elements and signal transducers. The modes of detection and sensitivity of the sensors are discussed. Finally, the challenges in the fabrication, obstacles in the clinical application, and future prospects are discussed.

Publication Details

Journal
Strathprints: The University of Strathclyde institutional repository (University of Strathclyde)
Published
2025-03-21
Primary Topic
Diverse Scientific and Economic Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modern emerging biosensing methodologies for the early diagnosis and screening of ovarian cancer

Strathprints: The University of Strathclyde institutional repository (University of Strathclyde)
Diverse Scientific and Economic Studies
article

Modern emerging biosensing methodologies for the early diagnosis and screening of ovarian cancer

article en

Abstract

Ovarian cancer (OC) is one of the leading causes of gynecological cancer-related death worldwide. Late diagnosis at advanced stages of OC is the reason for a higher mortality rate. Earlier diagnosis and proper treatment are important for improving the prognosis of OC patients. Biosensors offer accurate, low-cost, rapid, and user-friendly devices that can be employed for the detection of OC-specific biomarkers in the early stage. Therefore, it is important to consider the potential biomarkers in the biological fluids to confirm the OC prognosis. Out of many biomarkers, the most commonly tested clinically is cancer antigen 125 (CA-125). However, CA-125 is considered to be a poor biomarker for OC diagnosis. Several biosensing methods were developed for the sensitive and quantitative detection of each biomarker. In abnormal expression in OC patients, nucleic acids, enzymes, cells, and exosomes are used as target biomarkers for the construction of biosensors. This review focuses on the development for the detection of various biomarkers using multiple biosensing methods. Here, we describe the origin and the significance of OC-associated biomarkers, the working principle of biosensors, and the classification of biosensors based on their recognition elements and signal transducers. The modes of detection and sensitivity of the sensors are discussed. Finally, the challenges in the fabrication, obstacles in the clinical application, and future prospects are discussed.

Strathprints: The University of Strathclyde institutional repository (University of Strathclyde)
Good health and well-being
Openalex Percentile: Top 37%
Diverse Scientific and Economic Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.