Groundbreaking advancements in biomarkers and algorithms promise to revolutionise diagnosis and improve patient outcomes, ultimately changing the landscape of ovarian cancer care.
Ovarian cancer (OC) is one of the most prevalent cancers and the fifth leading cause of cancer-related deaths in women worldwide. There were approximately 314,000 new cases reported in 2020. Studies suggest that OC was the fourth most prevalent cancer among women in the UAE in 2019, with 100 reported cases.
The UAE has revolutionised healthcare to control OC. Early detection is also effective in improving patient outcomes and can save lives.
Women with OC symptoms should undergo a full pelvic examination, including a rectovaginal examination. However, physical examinations have limited accuracy. Following a physical examination, individuals may undergo imaging tests, such as Transvaginal Ultrasound (TVUS), which is accurate in detecting abnormalities in ovarian volume and morphology but less reliable in differentiating benign from malignant tumours.
To define tumour extension, further imaging with a chest and pelvis computed tomography (CT) scan, pelvic magnetic resonance imaging (MRI), and positron emission tomography (PET) scan could be carried out.
If OC is suspected, a complete blood count, blood chemistry (including liver function tests as well as calcium), and serum cancer biomarkers should be obtained.
Cancer antigen (CA)-125 test: CA-125 levels in serum can be measured by electrochemiluminescence immunoassay. Research shows that most cases of epithelial OC have elevated CA-125 levels. This assay, despite being more accurate for postmenopausal women, is not a reliable method for OC detection due to increased CA-125 levels in other physiological or benign conditions like endometriosis, fibroids, and pelvic inflammatory disease. Therefore, researchers are exploring more effective ways to screen for OC. Additionally, serum biomarkers such as human epididymis protein 4 are primarily used to assess disease progression and monitor for recurrence. While imaging and blood tests may suggest that a woman has OC, surgery enables a conclusive diagnosis.
Surgery: For many women, procedures such as minimally invasive laparoscopy and robotic surgery are utilised to excise a sample of tissue to determine the presence of cancer. A tissue biopsy is the only approach that can confirm an OC diagnosis.
Genetic testing: Recognising a hereditary predisposition (BRCA mutation) to OC allows for genetically designed precision medicine for women with cancer diagnosis.
Globally, researchers are making efforts to develop accurate and non-invasive methods for OC diagnosis. Working in this direction, multiple serum tumour biomarkers, radiological imaging techniques, and risk stratification algorithms have been the focus for the early diagnosis of OC. The advent of AI technology has made a tremendous breakthrough in OC diagnosis.
With the enormous research on liquid biopsy, a novel sampling technique has been developed. This approach analyses distinctive tumour components discharged into the peripheral circulation, comprising circulating tumour DNA, circulating tumour cells, tumour-educated platelets, and exosomes. Increasing evidence indicates that liquid biopsy could enhance the clinical management of OC by improving early diagnosis. The main advantages of liquid biopsy are its non-invasive nature and feasibility, which allow for serial sampling and longitudinal monitoring of potent tumour modifications over time.
There is a commercially available liquid biopsy test that utilises a cell-free DNA methylation technique, an encouraging new way to detect early-stage high-grade serous ovarian carcinoma with 91 per cent accuracy. At specific nucleic acids, the test searches for methylated DNA circulating in the blood.
A study has shown cutting-edge technology that can collect stray ovarian cells from a simple blood test and successfully predict cancer. The study recognised nine gene transcripts and four biomarkers that were helpful for detecting cancer. They were used to design an algorithm known as MAGIC. The algorithm achieved 95 per cent sensitivity and 83 per cent accuracy for detecting OC.
This technique is widely used for the detection of epithelial OCs through haptoglobin, a prognostic biomarker found in ovarian cyst fluid. This assay is unique in that when haptoglobin is present, the assay reagent undergoes a biochemical reaction that results in product formation. The unique Raman signature of the output falls within the wavenumber region 1500–1700 cm-1 and can be detected using the single peak Raman system since its diagnostic performance has 100 per cent sensitivity and 85 per cent specificity.
Researchers have discovered a way to improve the standard of care and diagnostic precision for potentially cancerous lesions in the ovaries by combining functional biomarkers with photoacoustic imaging. This technique exposes tissue to specific wavelengths of near-infrared light, which are absorbed differently by oxygenated and deoxygenated haemoglobin. The results of this novel assessment may allow some individuals to avoid surgery, reducing health care expenses and potential complications from the procedure.
AI could play a significant role in predicting the pathological diagnosis of OC based on preoperative examinations. Studies conducted used five machine learning classifiers, including Support Vector Machines, Random forests, Naïve Bayes, Logistic Regression, and XGBoost, knowing that XGBoost had the highest precision at 0.8.
In medical research, the path from the laboratory bench to the patient's bedside is usually a long one. And when it comes to breakthroughs in specific testing for OC, it is an avenue that no one has yet traversed successfully.
To date, most studies evaluating liquid biopsy approaches are limited by small sample sizes.
Similarly, in the case of Raman spectroscopy, a small sample size needs further validation involving larger clinical cohorts to assess clinical utility.
Potential studies are warranted to validate a commercially available liquid biopsy platform for high-grade serous ovarian carcinoma and further develop it for non-HGSOC epithelial OC histotypes (any of a range of tissue types that arise during the growth of a tumour) in both symptomatic and asymptomatic females with adnexal masses.
Future studies require proper validation of the AI models to estimate unbiased generalisation performance. Additionally, we should investigate methods to expand the sample size by utilising large cohorts or gathering data from multiple sites.
OC is the leading cause of death among women diagnosed with gynaecological cancer. Currently, imaging tests, blood tests, and a biopsy are used to diagnose OC. A key aspect of successfully implementing OC screening will be to expand genetic testing further to accurately and efficiently identify risk populations. Liquid biopsy has emerged as a promising alternative to conventional tissue sampling methods for its potential utility in the early detection of OC. Further research on how AI can change the landscape of OC diagnosis is required.
References available on request.
Dr Hyo Jin Park, MD, Ph is a Consultant Physician at SEHA Hospitals - Tawam Hospital Laboratory, PureLab, and Dr Joowon Oh, MD, PhD is a Consultant Physician, Leading Genetic CoE, STMC, Purelab.
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