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 Méndez González, Jesús Hervas, David Saigí, Maria Pajares, María José Garcia, Diana Crujeiras, Ana B. Pio, Ruben Montuenga, Luis M. Zulueta, Javier J. 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 |
URI: | http://hdl.handle.net/2445/113588 |
Related resource: | https://doi.org/10.1158/1078-0432.CCR-15-2346 |
ISSN: | 1078-0432 |
Appears in Collections: | Articles publicats en revistes (Medicina) Articles publicats en revistes (Ciències Fisiològiques) Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL)) |
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