Observatorio de I+D+i UPM

Memorias de investigación
Research Publications in journals:
Identification of a biomarker panel for colorectal cancer diagnosis
Year:2012
Research Areas
  • Artificial intelligence,
  • Biomedicine,
  • Computational biology
Information
Abstract
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. 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. 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. 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).
International
Si
JCR
Si
Title
Bmc Cancer
ISBN
1471-2407
Impact factor JCR
3,153
Impact info
Datos JCR del año 2010
Volume
12
doi:10.1186/1471-2407-12-43
Journal number
43
From page
1
To page
13
Month
SIN MES
Ranking
Participants
  • Autor: Amaia García-Bilbao (Fundación GAIKER)
  • Autor: Ruben Armañanzas Arnedillo (UPM)
  • Autor: Ziortza Ispizua (Fundación GAIKER)
  • Autor: Begoña Calvo (Hospital de Cruces)
  • Autor: Ana Alonso-Varona (Universidad del País Vasco)
  • Autor: Iñaki Inza Cano (Universidad del País Vasco)
  • Autor: Pedro Maria Larrañaga Mugica (UPM)
  • Autor: Guillermo López-Vivanco (Hospital de Cruces)
  • Autor: Blanca Suárez-Merino (Fundación GAIKER)
  • Autor: Mónica Betanzos (Fundación GAIKER)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: COMPUTATIONAL INTELLIGENCE GROUP
  • Departamento: Inteligencia Artificial
S2i 2020 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)