BACKGROUND: Extra-cellular microRNAs have been identified within blood and their profiles reflect various pathologies; therefore they have potential as disease biomarkers. Our aim was to investigate how circulating microRNA profiles change during cancer treatment. Our hypothesis was that tumour-related profiles are lost after tumour resection and therefore that comparison of profiles before and after surgery would allow identification of biomarker microRNAs. We aimed to examine whether these microRNAs were directly derived from tumours, and whether longitudinal expression monitoring could provide recurrence diagnoses. METHODS: Plasma was obtained from ten breast cancer patients before and at two time-points after resection. Tumour tissue was also obtained. Quantitative PCR were used to determine levels of 367 miRNAs. Relative expressions were determined after normalisation to miR-16, as is typical in the field, or to the mean microRNA level. RESULTS: 210 microRNAs were detected in at least one plasma sample. Using miR-16 normalisation, we found few consistent changes in circulating microRNAs after resection, and statistical analyses indicated that this normalisation was not justifiable. However, using data normalised to mean microRNA expression we found a significant bias for levels of individual circulating microRNAs to be reduced after resection. Potential biomarker microRNAs were identified, including let-7b, let-7g and miR-18b, with higher levels associated with tumours. These microRNAs were over-represented within the more highly expressed microRNAs in matched tumours, suggesting that circulating populations are tumour-derived in part. Longitudinal monitoring did not allow early recurrence detection. CONCLUSIONS: We concluded that specific circulating microRNAs may act as breast cancer biomarkers but methodological issues are critical.
BACKGROUND: Extra-cellular microRNAs have been identified within blood and their profiles reflect various pathologies; therefore they have potential as disease biomarkers. Our aim was to investigate how circulating microRNA profiles change during cancer treatment. Our hypothesis was that tumour-related profiles are lost after tumour resection and therefore that comparison of profiles before and after surgery would allow identification of biomarker microRNAs. We aimed to examine whether these microRNAs were directly derived from tumours, and whether longitudinal expression monitoring could provide recurrence diagnoses. METHODS: Plasma was obtained from ten breast cancerpatients before and at two time-points after resection. Tumour tissue was also obtained. Quantitative PCR were used to determine levels of 367 miRNAs. Relative expressions were determined after normalisation to miR-16, as is typical in the field, or to the mean microRNA level. RESULTS: 210 microRNAs were detected in at least one plasma sample. Using miR-16 normalisation, we found few consistent changes in circulating microRNAs after resection, and statistical analyses indicated that this normalisation was not justifiable. However, using data normalised to mean microRNA expression we found a significant bias for levels of individual circulating microRNAs to be reduced after resection. Potential biomarker microRNAs were identified, including let-7b, let-7g and miR-18b, with higher levels associated with tumours. These microRNAs were over-represented within the more highly expressed microRNAs in matched tumours, suggesting that circulating populations are tumour-derived in part. Longitudinal monitoring did not allow early recurrence detection. CONCLUSIONS: We concluded that specific circulating microRNAs may act as breast cancer biomarkers but methodological issues are critical.
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