INTRODUCTION: Neoadjuvant chemoradiation therapy has been shown to improve the outcome in patients with rectal cancer and is generally accepted as standard care; however, only selected patients would benefit from this treatment. We aimed to identify predictors of response to neoadjuvant chemoradiation therapy in colorectal cancer using formalin-fixed paraffin-embedded (FFPE) tissues as source of genetic materials and microarray analysis as investigation tool. METHODS: After optimization of RNA extraction methods from FFPE, microarray analysis was carried out on total RNA extracted from 12 pre-treatment FFPE rectal tissues using Megaplex pool A. Microarray data were analysed using an artificial neural network algorithm. Statistical analysis and correlation with clinicopathological data was performed using SPSS software. RESULTS: A distinct miRNA expression signature predictive of response to neoadjuvant CRT in 12 FFPE pre-treatment rectal cancer tissue samples was identified. These signatures consisted of three miRNA transcripts (miR-16, miR-590-5p and miR-153) to predict complete vs. incomplete response and two miRNA transcript (miR-519c-3p and miR-561) to predict good vs. poor response with a median accuracy of 100 %. CONCLUSION: Using microarray analysis of pretreatment FFPE rectal cancer tissues, we identified for the first time a group of miRNA predictors of response to neoadjuvant CRT. This, indeed, can lead to a significant improvement in patient selection criteria and personalized rectal cancer management.
INTRODUCTION: Neoadjuvant chemoradiation therapy has been shown to improve the outcome in patients with rectal cancer and is generally accepted as standard care; however, only selected patients would benefit from this treatment. We aimed to identify predictors of response to neoadjuvant chemoradiation therapy in colorectal cancer using formalin-fixed paraffin-embedded (FFPE) tissues as source of genetic materials and microarray analysis as investigation tool. METHODS: After optimization of RNA extraction methods from FFPE, microarray analysis was carried out on total RNA extracted from 12 pre-treatment FFPE rectal tissues using Megaplex pool A. Microarray data were analysed using an artificial neural network algorithm. Statistical analysis and correlation with clinicopathological data was performed using SPSS software. RESULTS: A distinct miRNA expression signature predictive of response to neoadjuvant CRT in 12 FFPE pre-treatment rectal cancer tissue samples was identified. These signatures consisted of three miRNA transcripts (miR-16, miR-590-5p and miR-153) to predict complete vs. incomplete response and two miRNA transcript (miR-519c-3p and miR-561) to predict good vs. poor response with a median accuracy of 100 %. CONCLUSION: Using microarray analysis of pretreatment FFPE rectal cancer tissues, we identified for the first time a group of miRNA predictors of response to neoadjuvant CRT. This, indeed, can lead to a significant improvement in patient selection criteria and personalized rectal cancer management.
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