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Prediction of Drug Efficacy in Colon Cancer Preclinical Models Using a Novel Ranking Method of Gene Expression

The presence of stromal cells in tumors is altering the significance of molecular profiling when using standard methods of gene expression quantification. We developed a novel normalization method to rank target gene expression in tumor samples by comparisons with reference samples representing the...

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Detalles Bibliográficos
Autores principales: Fritz, Justine, Lefebvre, Olivier, Fernandez, Aurore, Schmidt, Jordane, Bagnard, Dominique
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7016638/
https://www.ncbi.nlm.nih.gov/pubmed/31936310
http://dx.doi.org/10.3390/cancers12010149
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author Fritz, Justine
Lefebvre, Olivier
Fernandez, Aurore
Schmidt, Jordane
Bagnard, Dominique
author_facet Fritz, Justine
Lefebvre, Olivier
Fernandez, Aurore
Schmidt, Jordane
Bagnard, Dominique
author_sort Fritz, Justine
collection PubMed
description The presence of stromal cells in tumors is altering the significance of molecular profiling when using standard methods of gene expression quantification. We developed a novel normalization method to rank target gene expression in tumor samples by comparisons with reference samples representing the different cell types found in a tumor. The score for each target gene obtained after normalization, is aimed to be predictive of targeted therapies efficiency. We performed this qPCR analysis on human colorectal cancers to demonstrate the importance of reference samples to obtain accurate data and on a collection of patient-derived xenografted (PDX) colon tumors treated with Cetuximab (anti-EGFR) to demonstrate that the calculated EGFR score is predictive of Cetuximab efficacy. Interestingly, the score allowed to select an efficient treatment in a PDX model refractory to standard of care. This method is opening a novel way to predict targeted therapy efficiency which could be extended to several tumor types, and to unlimited target genes.
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spelling pubmed-70166382020-03-04 Prediction of Drug Efficacy in Colon Cancer Preclinical Models Using a Novel Ranking Method of Gene Expression Fritz, Justine Lefebvre, Olivier Fernandez, Aurore Schmidt, Jordane Bagnard, Dominique Cancers (Basel) Article The presence of stromal cells in tumors is altering the significance of molecular profiling when using standard methods of gene expression quantification. We developed a novel normalization method to rank target gene expression in tumor samples by comparisons with reference samples representing the different cell types found in a tumor. The score for each target gene obtained after normalization, is aimed to be predictive of targeted therapies efficiency. We performed this qPCR analysis on human colorectal cancers to demonstrate the importance of reference samples to obtain accurate data and on a collection of patient-derived xenografted (PDX) colon tumors treated with Cetuximab (anti-EGFR) to demonstrate that the calculated EGFR score is predictive of Cetuximab efficacy. Interestingly, the score allowed to select an efficient treatment in a PDX model refractory to standard of care. This method is opening a novel way to predict targeted therapy efficiency which could be extended to several tumor types, and to unlimited target genes. MDPI 2020-01-08 /pmc/articles/PMC7016638/ /pubmed/31936310 http://dx.doi.org/10.3390/cancers12010149 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Fritz, Justine
Lefebvre, Olivier
Fernandez, Aurore
Schmidt, Jordane
Bagnard, Dominique
Prediction of Drug Efficacy in Colon Cancer Preclinical Models Using a Novel Ranking Method of Gene Expression
title Prediction of Drug Efficacy in Colon Cancer Preclinical Models Using a Novel Ranking Method of Gene Expression
title_full Prediction of Drug Efficacy in Colon Cancer Preclinical Models Using a Novel Ranking Method of Gene Expression
title_fullStr Prediction of Drug Efficacy in Colon Cancer Preclinical Models Using a Novel Ranking Method of Gene Expression
title_full_unstemmed Prediction of Drug Efficacy in Colon Cancer Preclinical Models Using a Novel Ranking Method of Gene Expression
title_short Prediction of Drug Efficacy in Colon Cancer Preclinical Models Using a Novel Ranking Method of Gene Expression
title_sort prediction of drug efficacy in colon cancer preclinical models using a novel ranking method of gene expression
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7016638/
https://www.ncbi.nlm.nih.gov/pubmed/31936310
http://dx.doi.org/10.3390/cancers12010149
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