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Identification of a biomarker panel for colorectal cancer diagnosis
by
Calvo, Begoña
, Inza, Iñaki
, García-Bilbao, Amaia
, Alonso-Varona, Ana
, López-Vivanco, Guillermo
, Suárez-Merino, Blanca
, Armañanzas, Rubén
, Ispizua, Ziortza
, Larrañaga, Pedro
, Betanzos, Mónica
in
Analysis of Variance
/ Bayes Theorem
/ Biological markers
/ Biomarkers
/ Biomedical and Life Sciences
/ Biomedicine
/ Cancer Research
/ Colon
/ Colorectal cancer
/ Colorectal Neoplasms - diagnosis
/ Colorectal Neoplasms - genetics
/ Computer science
/ Deoxyribonucleic acid
/ Diagnosis
/ Disease Progression
/ DNA
/ Gene Expression Profiling
/ Genetic aspects
/ Genetic Markers
/ Genetic Variation
/ Genomics
/ Health Promotion and Disease Prevention
/ Humans
/ Identification and classification
/ Medical research
/ Medicine/Public Health
/ Mortality
/ Oncology
/ Real-Time Polymerase Chain Reaction
/ Research Article
/ Surgical Oncology
/ Validation studies
2012
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Identification of a biomarker panel for colorectal cancer diagnosis
by
Calvo, Begoña
, Inza, Iñaki
, García-Bilbao, Amaia
, Alonso-Varona, Ana
, López-Vivanco, Guillermo
, Suárez-Merino, Blanca
, Armañanzas, Rubén
, Ispizua, Ziortza
, Larrañaga, Pedro
, Betanzos, Mónica
in
Analysis of Variance
/ Bayes Theorem
/ Biological markers
/ Biomarkers
/ Biomedical and Life Sciences
/ Biomedicine
/ Cancer Research
/ Colon
/ Colorectal cancer
/ Colorectal Neoplasms - diagnosis
/ Colorectal Neoplasms - genetics
/ Computer science
/ Deoxyribonucleic acid
/ Diagnosis
/ Disease Progression
/ DNA
/ Gene Expression Profiling
/ Genetic aspects
/ Genetic Markers
/ Genetic Variation
/ Genomics
/ Health Promotion and Disease Prevention
/ Humans
/ Identification and classification
/ Medical research
/ Medicine/Public Health
/ Mortality
/ Oncology
/ Real-Time Polymerase Chain Reaction
/ Research Article
/ Surgical Oncology
/ Validation studies
2012
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Identification of a biomarker panel for colorectal cancer diagnosis
by
Calvo, Begoña
, Inza, Iñaki
, García-Bilbao, Amaia
, Alonso-Varona, Ana
, López-Vivanco, Guillermo
, Suárez-Merino, Blanca
, Armañanzas, Rubén
, Ispizua, Ziortza
, Larrañaga, Pedro
, Betanzos, Mónica
in
Analysis of Variance
/ Bayes Theorem
/ Biological markers
/ Biomarkers
/ Biomedical and Life Sciences
/ Biomedicine
/ Cancer Research
/ Colon
/ Colorectal cancer
/ Colorectal Neoplasms - diagnosis
/ Colorectal Neoplasms - genetics
/ Computer science
/ Deoxyribonucleic acid
/ Diagnosis
/ Disease Progression
/ DNA
/ Gene Expression Profiling
/ Genetic aspects
/ Genetic Markers
/ Genetic Variation
/ Genomics
/ Health Promotion and Disease Prevention
/ Humans
/ Identification and classification
/ Medical research
/ Medicine/Public Health
/ Mortality
/ Oncology
/ Real-Time Polymerase Chain Reaction
/ Research Article
/ Surgical Oncology
/ Validation studies
2012
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Identification of a biomarker panel for colorectal cancer diagnosis
Journal Article
Identification of a biomarker panel for colorectal cancer diagnosis
2012
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Overview
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).
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
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