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Open Access

Peer-reviewed

Research Article

KRAS, NRAS, and BRAF mutation prevalence, clinicopathological association, and their application in a predictive model in Mexican patients with metastatic colorectal cancer: A retrospective cohort study

Hector Eduardo Sanchez-Ibarra,

Roles Conceptualization, Investigation, Methodology, Project administration, Writing – review & editing

Affiliation Genetics Laboratory, Vitagénesis SA de CV, Monterrey, Nuevo Leon, Mexico

http://orcid.org/0000-0002-9991-267X

⨯
Xianli Jiang,

Roles Data curation, Formal analysis, Writing – original draft

Affiliation Evolutionary Information Laboratory, Department of Biological Sciences, the University of Texas at Dallas, Richardson, Texas, United States of America
⨯
Elena Yareli Gallegos-Gonzalez,

Roles Methodology, Writing – original draft

Affiliation Genetics Laboratory, Vitagénesis SA de CV, Monterrey, Nuevo Leon, Mexico
⨯
Adriana Carolina Cavazos-González,

Roles Methodology

Affiliation Genetics Laboratory, Vitagénesis SA de CV, Monterrey, Nuevo Leon, Mexico
⨯
Yenho Chen,

Roles Data curation, Formal analysis

Affiliation Evolutionary Information Laboratory, Department of Biological Sciences, the University of Texas at Dallas, Richardson, Texas, United States of America
⨯
Faruck Morcos,

Roles Data curation, Formal analysis, Investigation

Affiliation Evolutionary Information Laboratory, Department of Biological Sciences, the University of Texas at Dallas, Richardson, Texas, United States of America
⨯
Hugo Alberto Barrera-Saldaña

Roles Supervision, Writing – review & editing

* E-mail: habarrera@gmail.com

Affiliation Genetics Laboratory, Vitagénesis SA de CV, Monterrey, Nuevo Leon, Mexico
⨯

KRAS, NRAS, and BRAF mutation prevalence, clinicopathological association, and their application in a predictive model in Mexican patients with metastatic colorectal cancer: A retrospective cohort study

Hector Eduardo Sanchez-Ibarra,
Xianli Jiang,
Elena Yareli Gallegos-Gonzalez,
Adriana Carolina Cavazos-González,
Yenho Chen,
Faruck Morcos,
Hugo Alberto Barrera-Saldaña

x

Published: July 6, 2020
https://doi.org/10.1371/journal.pone.0235490

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Histology
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Colon
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Colorectal cancer
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Mutation
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Forecasting
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Machine learning
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Rectum
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Neural networks
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