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Xenograft assessment of predictive biomarkers for standard head and neck cancer therapies

Head and neck squamous cell carcinoma (HNSCC) remains a challenging cancer to treat with overall 5-year survival on the order of 50–60%. Therefore, predictive biomarkers for this disease would be valuable to provide more effective and individualized therapeutic approaches for these patients. While p...

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Autores principales: Stein, Andrew P, Swick, Adam D, Smith, Molly A, Blitzer, Grace C, Yang, Robert Z, Saha, Sandeep, Harari, Paul M, Lambert, Paul F, Liu, Cheng Z, Kimple, Randall J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BlackWell Publishing Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4430263/
https://www.ncbi.nlm.nih.gov/pubmed/25619980
http://dx.doi.org/10.1002/cam4.387
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author Stein, Andrew P
Swick, Adam D
Smith, Molly A
Blitzer, Grace C
Yang, Robert Z
Saha, Sandeep
Harari, Paul M
Lambert, Paul F
Liu, Cheng Z
Kimple, Randall J
author_facet Stein, Andrew P
Swick, Adam D
Smith, Molly A
Blitzer, Grace C
Yang, Robert Z
Saha, Sandeep
Harari, Paul M
Lambert, Paul F
Liu, Cheng Z
Kimple, Randall J
author_sort Stein, Andrew P
collection PubMed
description Head and neck squamous cell carcinoma (HNSCC) remains a challenging cancer to treat with overall 5-year survival on the order of 50–60%. Therefore, predictive biomarkers for this disease would be valuable to provide more effective and individualized therapeutic approaches for these patients. While prognostic biomarkers such as p16 expression correlate with outcome; to date, no predictive biomarkers have been clinically validated for HNSCC. We generated xenografts in immunocompromised mice from six established HNSCC cell lines and evaluated response to cisplatin, cetuximab, and radiation. Tissue microarrays were constructed from pre- and posttreatment tumor samples derived from each xenograft experiment. Quantitative immunohistochemistry was performed using a semiautomated imaging and analysis platform to determine the relative expression of five potential predictive biomarkers: epidermal growth factor receptor (EGFR), phospho-EGFR, phospho-Akt, phospho-ERK, and excision repair cross-complementation group 1 (ERCC1). Biomarker levels were compared between xenografts that were sensitive versus resistant to a specific therapy utilizing a two-sample t-test with equal standard deviations. Indeed the xenografts displayed heterogeneous responses to each treatment, and we linked a number of baseline biomarker levels to response. This included low ERCC1 being associated with cisplatin sensitivity, low phospho-Akt correlated with cetuximab sensitivity, and high total EGFR was related to radiation resistance. Overall, we developed a systematic approach to identifying predictive biomarkers and demonstrated several connections between biomarker levels and treatment response. Despite these promising initial results, this work requires additional preclinical validation, likely involving the use of patient-derived xenografts, prior to moving into the clinical realm for confirmation among patients with HNSCC.
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spelling pubmed-44302632015-05-18 Xenograft assessment of predictive biomarkers for standard head and neck cancer therapies Stein, Andrew P Swick, Adam D Smith, Molly A Blitzer, Grace C Yang, Robert Z Saha, Sandeep Harari, Paul M Lambert, Paul F Liu, Cheng Z Kimple, Randall J Cancer Med Cancer Research Head and neck squamous cell carcinoma (HNSCC) remains a challenging cancer to treat with overall 5-year survival on the order of 50–60%. Therefore, predictive biomarkers for this disease would be valuable to provide more effective and individualized therapeutic approaches for these patients. While prognostic biomarkers such as p16 expression correlate with outcome; to date, no predictive biomarkers have been clinically validated for HNSCC. We generated xenografts in immunocompromised mice from six established HNSCC cell lines and evaluated response to cisplatin, cetuximab, and radiation. Tissue microarrays were constructed from pre- and posttreatment tumor samples derived from each xenograft experiment. Quantitative immunohistochemistry was performed using a semiautomated imaging and analysis platform to determine the relative expression of five potential predictive biomarkers: epidermal growth factor receptor (EGFR), phospho-EGFR, phospho-Akt, phospho-ERK, and excision repair cross-complementation group 1 (ERCC1). Biomarker levels were compared between xenografts that were sensitive versus resistant to a specific therapy utilizing a two-sample t-test with equal standard deviations. Indeed the xenografts displayed heterogeneous responses to each treatment, and we linked a number of baseline biomarker levels to response. This included low ERCC1 being associated with cisplatin sensitivity, low phospho-Akt correlated with cetuximab sensitivity, and high total EGFR was related to radiation resistance. Overall, we developed a systematic approach to identifying predictive biomarkers and demonstrated several connections between biomarker levels and treatment response. Despite these promising initial results, this work requires additional preclinical validation, likely involving the use of patient-derived xenografts, prior to moving into the clinical realm for confirmation among patients with HNSCC. BlackWell Publishing Ltd 2015-05 2015-01-26 /pmc/articles/PMC4430263/ /pubmed/25619980 http://dx.doi.org/10.1002/cam4.387 Text en © 2014 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Cancer Research
Stein, Andrew P
Swick, Adam D
Smith, Molly A
Blitzer, Grace C
Yang, Robert Z
Saha, Sandeep
Harari, Paul M
Lambert, Paul F
Liu, Cheng Z
Kimple, Randall J
Xenograft assessment of predictive biomarkers for standard head and neck cancer therapies
title Xenograft assessment of predictive biomarkers for standard head and neck cancer therapies
title_full Xenograft assessment of predictive biomarkers for standard head and neck cancer therapies
title_fullStr Xenograft assessment of predictive biomarkers for standard head and neck cancer therapies
title_full_unstemmed Xenograft assessment of predictive biomarkers for standard head and neck cancer therapies
title_short Xenograft assessment of predictive biomarkers for standard head and neck cancer therapies
title_sort xenograft assessment of predictive biomarkers for standard head and neck cancer therapies
topic Cancer Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4430263/
https://www.ncbi.nlm.nih.gov/pubmed/25619980
http://dx.doi.org/10.1002/cam4.387
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