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BMC Cancer. 2012; 12: 43.
Published online Jan 26, 2012. doi:  10.1186/1471-2407-12-43
PMCID: PMC3323359
Identification of a biomarker panel for colorectal cancer diagnosis
Amaia García-Bilbao,#1 Rubén Armañanzas,#2 Ziortza Ispizua,1 Begoña Calvo,3 Ana Alonso-Varona,4 Iñaki Inza,5 Pedro Larrañaga,2 Guillermo López-Vivanco,3 Blanca Suárez-Merino,1 and Mónica Betanzoscorresponding author1
1GAIKER Technology Centre, Parque Tecnológico, Edificio 202, 48170 Zamudio, (Bizkaia), Spain
2Computational Intelligence Group, Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Campus de Montegancedo, 28660 Boadilla del Monte, Spain
3Medical Oncology Service, Hospital de Cruces, Plaza de Cruces s/n, 48903 Barakaldo, (Bizkaia), Spain
4Department of Cell Biology and Histology, School of Medicine and Dentistry, University of the Basque Country, 48940 Leioa, (Bizkaia), Spain
5Department of Computer Science and Artificial Intelligence, Computer Science Faculty, University of the Basque Country, 20018 San Sebastián, (Gipuzkoa), Spain
corresponding authorCorresponding author.
#Contributed equally.
Amaia García-Bilbao: garciaam/at/gaiker.es; Rubén Armañanzas: r.armananzas/at/upm.es; Ziortza Ispizua: zispizua/at/owlmetabolomics.com; Begoña Calvo: begona.calvomartinez/at/osakidetza.net; Ana Alonso-Varona: ana.alonsovarona/at/ehu.es; Iñaki Inza: inaki.inza/at/ehu.es; Pedro Larrañaga: pedro.larranaga/at/fi.upm.es; Guillermo López-Vivanco: guillermo.lopezvivanco/at/osakidetza.net; Blanca Suárez-Merino: suarezb/at/gaiker.es; Mónica Betanzos: betanzos/at/gaiker.es
Received August 26, 2011; Accepted January 26, 2012.
Abstract
Background
Malignancies arising in the large bowel cause the second largest number of deaths from cancer in the Western World. Despite progresses made during the last decades, colorectal cancer remains one of the most frequent and deadly neoplasias in the western countries.
Methods
A genomic study of human colorectal cancer has been carried out on a total of 31 tumoral samples, corresponding to different stages of the disease, and 33 non-tumoral samples. The study was carried out by hybridisation of the tumour samples against a reference pool of non-tumoral samples using Agilent Human 1A 60-mer oligo microarrays. The results obtained were validated by qRT-PCR. In the subsequent bioinformatics analysis, gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling were built. The consensus among all the induced models produced a hierarchy of dependences and, thus, of variables.
Results
After an exhaustive process of pre-processing to ensure data quality--lost values imputation, probes quality, data smoothing and intraclass variability filtering--the final dataset comprised a total of 8, 104 probes. Next, a supervised classification approach and data analysis was carried out to obtain the most relevant genes. Two of them are directly involved in cancer progression and in particular in colorectal cancer. Finally, a supervised classifier was induced to classify new unseen samples.
Conclusions
We have developed a tentative model for the diagnosis of colorectal cancer based on a biomarker panel. Our results indicate that the gene profile described herein can discriminate between non-cancerous and cancerous samples with 94.45% accuracy using different supervised classifiers (AUC values in the range of 0.997 and 0.955).
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