Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/113588
Title: A novel epigenetic signature for early diagnosis in lung cancer
Author: Diaz-Lagares, Angel
Mendez-Gonzalez, Jesus
Hervas, David
Saigi, Maria
Pajares, Maria J.
Garcia, Diana
Crujeiras, Ana B.
Pio, Ruben
Montuenga, Luis M.
Zulueta, Javier
Nadal, Ernest
Rosell, Antoni, 1963-
Esteller, Manel
Sandoval, Juan
Keywords: Epigènesi
Diagnòstic
Marcadors bioquímics
Metilació
ADN
Càncer de pulmó
Epigenesis
Diagnosis
Biochemical markers
Methylation
DNA
Lung cancer
Issue Date: 1-Jul-2016
Publisher: American Association for Cancer Research
Abstract: Purpose: lung cancer remains as the leading cause of cancer-related death worldwide, mainly due to late diagnosis. Cytology is the gold-standard method for lung cancer diagnosis in minimally invasive respiratory samples, despite its low sensitivity. We aimed to identify epigenetic biomarkers with clinical utility for cancer diagnosis in minimally/noninvasive specimens to improve accuracy of current technologies. Experimental design: the identification of novel epigenetic biomarkers in stage I lung tumors was accomplished using an integrative genome-wide restrictive analysis of two different large public databases. DNA methylation levels for the selected biomarkers were validated by pyrosequencing in paraffin-embedded tissues and minimally invasive and noninvasive respiratory samples in independent cohorts. Results: we identified nine cancer-specific hypermethylated genes in early-stage lung primary tumors. Four of these genes presented consistent CpG island hypermethylation compared with nonmalignant lung and were associated with transcriptional silencing. A diagnostic signature was built using multivariate logistic regression model based on the combination of four genes: BCAT1, CDO1, TRIM58, and ZNF177. Clinical diagnostic value was also validated in multiple independent cohorts and yielded a remarkable diagnostic accuracy in all cohorts tested. Calibrated and cross-validated epigenetic model predicts with high accuracy the probability to detect cancer in minimally and noninvasive samples. We demonstrated that this epigenetic signature achieved higher diagnostic efficacy in bronchial fluids as compared with conventional cytology for lung cancer diagnosis. Conclusions: minimally invasive epigenetic biomarkers have emerged as promising tools for cancer diagnosis. The herein obtained epigenetic model in combination with current diagnostic protocols may improve early diagnosis and outcome of lung cancer patients.
Note: Versió postprint del document publicat a: https://doi.org/10.1158/1078-0432.CCR-15-2346
It is part of: Clinical Cancer Research, 2016, vol. 22, num. 13, p. 3361-3371
Related resource: https://doi.org/10.1158/1078-0432.CCR-15-2346
URI: http://hdl.handle.net/2445/113588
ISSN: 1078-0432
Appears in Collections:Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))
Articles publicats en revistes (Medicina)
Articles publicats en revistes (Ciències Fisiològiques)

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