Abstract
Circulating microRNAs are non-invasive biomarkers that can be used for breast cancer diagnosis. However, differences in cancer tissue microRNA expression are observed in populations with different genetic/environmental backgrounds. This work aims at checking if a previously identified diagnostic circulating microRNA signature is efficient in other genetic and environmental contexts, and if a universal circulating signature might be possible. Two populations are used: women recruited in Belgium and Rwanda. Breast cancer patients and healthy controls were recruited in both populations (Belgium: 143 primary breast cancers and 136 healthy controls; Rwanda: 82 primary breast cancers and 73 healthy controls; Ntot = 434), and cohorts with matched age and cancer subtypes were compared. Plasmatic microRNA profiling was performed by RT-qPCR. Random Forest was used to (1) evaluate the performances of the previously described breast cancer diagnostic tool identified in Belgian-recruited cohorts on Rwandan-recruited cohorts and vice versa; (2) define new diagnostic signatures common to both recruitment sites; (3) define new diagnostic signatures efficient in the Rwandan population. None of the circulating microRNA signatures identified is accurate enough to be used as a diagnostic test in both populations. However, accurate circulating microRNA signatures can be found for each specific population, when taken separately.
Highlights
Breast cancer is the most commonly diagnosed and deadly malignancy in women in both developed and developing countries, with about 2.1 million cases and 627,000 deaths registered in 2018
The random forest algorithm is a supervised machine learning classification method based on an ensemble of decision trees, that was first described by Breiman et al.[26]
Circulating microRNAs have been identified in serum and plasma, and are increasingly recognized as powerful disease biomarkers for breast cancers[30,31]
Summary
Breast cancer is the most commonly diagnosed and deadly malignancy in women in both developed and developing countries, with about 2.1 million cases and 627,000 deaths registered in 2018. It causes 25.1% of all cancer deaths each year in developed countries and is the leading cause of mortality among women in developing countries, with 14.3% of all deaths a nnually[1]. It has some limitations; (a) exposure to X-ray radiation, (b) low sensitivity and specificity in young women or women with a high breast density[6]. Blood biomarkers such as carbohydrate antigen (CA 15.3) and carcino-embryogenic antigen (CEA) are useful for monitoring breast cancer treatment but lacks sensitivity for the detection of primary breast cancers[7]
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