Metastatic Tissue Proteomic Profiling Predicts 5-Year Outcomes in Patients with Colorectal Liver Metastases

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RECERCAT Home > Universitat de Barcelona > IDIBAPS: Institut d'investigacions Biomèdiques August Pi i Sunyer > Articles publicats en revistes (IDIBAPS: Institut d'investigacions Biomèdiques August Pi i Sunyer) > View document

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dc.contributor.author	Marfà Bruix, Santiago
dc.contributor.author	Martí, Josep
dc.contributor.author	Reyes, Adalquza
dc.contributor.author	Casals, Gregori
dc.contributor.author	Fernández Varo, Guillermo
dc.contributor.author	Carvajal Romero, Silvia
dc.contributor.author	García-Valdecasas Salgado, Juan Carlos
dc.contributor.author	Fuster Obregón, Josep
dc.contributor.author	Jiménez Povedano, Wladimiro
dc.date	2017-04-05T07:02:14Z
dc.date	2017-04-05T07:02:14Z
dc.date	2016-10-14
dc.date	2017-04-05T07:02:14Z
dc.identifier	1944-7124
dc.identifier	665919
dc.identifier	27751349
dc.identifier.uri	http://hdl.handle.net/2445/109383
dc.description	Colorectal cancer (CRC) is one of the most common cancers in the developed countries, and nearly 70% of patients with CRC develop colorectal liver metastases (CRLMs). During the last decades, several scores have been proposed to predict recurrence after CRLM resection. However, these risk scoring systems do not accurately reflect the prognosis of these patients. Therefore, this investigation was designed to identify a proteomic profile in human hepatic tumor samples to classify patients with CRLM as 'mild' or 'severe' based on the 5-year survival. The study was performed on 85 CRLM tumor samples. Firstly, to evaluate any distinct tumor proteomic signatures between mild and severe CRLM patients, a training group of 57 CRLM tumor samples was characterized by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry, and a classification and regression tree (CART) analysis was subsequently performed. Finally, 28 CRLM tumor samples were used to confirm and validate the results obtained. Based on all the protein peaks detected in the training group, the CART analysis was generated, and four peaks were considered to be the most relevant to construct a diagnostic algorithm. Indeed, the multivariate model yielded a sensitivity of 85.7% and a specificity of 86.1%, respectively. In addition, the receiver operating characteristic (ROC) curve showed an excellent diagnostic accuracy to discriminate mild from severe CRLM patients (area under the ROC: 0.903). Finally, the validation process yielded a sensitivity and specificity of 68.8% and 83.3%, respectively. We identified a proteomic profile potentially useful to determine the prognosis of CRLM patients based on the 5-year survival.
dc.format	8 p.
dc.format	application/pdf
dc.language	eng
dc.publisher	Elsevier
dc.relation	Reproducció del document publicat a: https://doi.org/10.1016/j.tranon.2016.08.002
dc.relation	Translational Oncology, 2016, vol. 9, num. 5, p. 445-452
dc.relation	https://doi.org/10.1016/j.tranon.2016.08.002
dc.rights	cc-by-nc-nd (c) Marfà, Santiago et al., 2016
dc.rights	http://creativecommons.org/licenses/by-nc-nd/3.0/es
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Càncer colorectal
dc.subject	Metàstasi
dc.subject	Càncer de fetge
dc.subject	Pronòstic mèdic
dc.subject	Colorectal cancer
dc.subject	Metastasis
dc.subject	Liver cancer
dc.subject	Prognosis
dc.title	Metastatic Tissue Proteomic Profiling Predicts 5-Year Outcomes in Patients with Colorectal Liver Metastases
dc.type	info:eu-repo/semantics/article
dc.type	info:eu-repo/semantics/publishedVersion

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