Introduction: microRNAs (miRNAs) are small non-coding RNAs involved in the development of various cancers. Quantitative real-time PCR (qPCR) is the assay commonly used to investigate miRNA expression and qPCR-low-density arrays are the most used technique for both identification and validation of modulated miRNAs. One crucial pre-processing step for miRNA analysis is data normalization, aimed at reducing nonbiological sources of variation [1]. This process would allow to identify a small set of miRNAs to be used for data normalization in subsequent validation studies [2]. Materials and methods: we analyzed the expression levels of 381 human miRNAs on TaqMan Array MicroRNA Card A v.2 (Applied Biosystems), on a cohort of 60 plasma samples (38 precancerous lesions/cancer and 22 without lesion) from individuals enrolled in the CRC screening program of the Milan Local Health Authority that underwent colonoscopy at our Institute (INT) after a positive fecal occult blood test (FIT+). Starting from these data, we developed and applied a data-driven normalization method able to identify a small set of reference miRNAs to use for data normalization in the subsequent validation studies [2,3]. Briefly, by considering the miRNAs expressed in all the samples, the relative expression of each miRNA was first computed according to their mean expression value [4] and the best subset of miRNAs that resemble this value was selected [2,3]. Results and discussion: we identified 4 housekeeping miRNAs suitable for data normalization and 7 miRNAs significantly different in subjects with precancerous/cancerous lesions versus subjects without lesions. We also identified 4 miRNAs related to presence of initial adenoma, one linked to advanced adenoma and 8 to presence of cancerous lesion. We are now constructing of a Custom TaqMan Array Cards including the identified miRNAs and some other miRNAs of interest, i.e those haemolysis-related and miR-378 [5], with the aim of validating these biomarkers on a prospective cohort of 120 FIT+ subjects that underwent colonoscopy at INT. Conclusion: the adopted strategy allowed the identification of reference miRNAs to be used for data normalization and the identification of modulated miRNAs that will be validated in larger prospective series. Acknowledgements: This work was supported by grants from Associazione Italiana per la Ricerca sul Cancro (AIRC) (Grants No.10529 and No. 12162 to MA Pierotti).

Identification of microRNAs for the early diagnosis of colorectal cancer (CRC) / C.M. Ciniselli, S. Pizzamiglio, S. Bottelli, S. Zanutto, C. Bertan, M. Gariboldi, M.A. Pierotti, P. Verderio. ((Intervento presentato al 4. convegno Biomarker Conference tenutosi a Munich nel 2014.

Identification of microRNAs for the early diagnosis of colorectal cancer (CRC)

C.M. Ciniselli
Primo
;
2014

Abstract

Introduction: microRNAs (miRNAs) are small non-coding RNAs involved in the development of various cancers. Quantitative real-time PCR (qPCR) is the assay commonly used to investigate miRNA expression and qPCR-low-density arrays are the most used technique for both identification and validation of modulated miRNAs. One crucial pre-processing step for miRNA analysis is data normalization, aimed at reducing nonbiological sources of variation [1]. This process would allow to identify a small set of miRNAs to be used for data normalization in subsequent validation studies [2]. Materials and methods: we analyzed the expression levels of 381 human miRNAs on TaqMan Array MicroRNA Card A v.2 (Applied Biosystems), on a cohort of 60 plasma samples (38 precancerous lesions/cancer and 22 without lesion) from individuals enrolled in the CRC screening program of the Milan Local Health Authority that underwent colonoscopy at our Institute (INT) after a positive fecal occult blood test (FIT+). Starting from these data, we developed and applied a data-driven normalization method able to identify a small set of reference miRNAs to use for data normalization in the subsequent validation studies [2,3]. Briefly, by considering the miRNAs expressed in all the samples, the relative expression of each miRNA was first computed according to their mean expression value [4] and the best subset of miRNAs that resemble this value was selected [2,3]. Results and discussion: we identified 4 housekeeping miRNAs suitable for data normalization and 7 miRNAs significantly different in subjects with precancerous/cancerous lesions versus subjects without lesions. We also identified 4 miRNAs related to presence of initial adenoma, one linked to advanced adenoma and 8 to presence of cancerous lesion. We are now constructing of a Custom TaqMan Array Cards including the identified miRNAs and some other miRNAs of interest, i.e those haemolysis-related and miR-378 [5], with the aim of validating these biomarkers on a prospective cohort of 120 FIT+ subjects that underwent colonoscopy at INT. Conclusion: the adopted strategy allowed the identification of reference miRNAs to be used for data normalization and the identification of modulated miRNAs that will be validated in larger prospective series. Acknowledgements: This work was supported by grants from Associazione Italiana per la Ricerca sul Cancro (AIRC) (Grants No.10529 and No. 12162 to MA Pierotti).
nov-2014
Settore MED/01 - Statistica Medica
Identification of microRNAs for the early diagnosis of colorectal cancer (CRC) / C.M. Ciniselli, S. Pizzamiglio, S. Bottelli, S. Zanutto, C. Bertan, M. Gariboldi, M.A. Pierotti, P. Verderio. ((Intervento presentato al 4. convegno Biomarker Conference tenutosi a Munich nel 2014.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/470769
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