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Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer
Patient-derived xenograft (PDX) models of breast cancer are an effective discovery platform and tool for preclinical pharmacologic testing and biomarker identification. We established orthotopic PDX models of triple negative breast cancer (TNBC) from the primary breast tumors of patients prior to an...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9831981/ https://www.ncbi.nlm.nih.gov/pubmed/36627285 http://dx.doi.org/10.1038/s41523-022-00502-1 |
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author | Echeverria, Gloria V. Cai, Shirong Tu, Yizheng Shao, Jiansu Powell, Emily Redwood, Abena B. Jiang, Yan McCoy, Aaron Rinkenbaugh, Amanda L. Lau, Rosanna Trevarton, Alexander J. Fu, Chunxiao Gould, Rebekah Ravenberg, Elizabeth E. Huo, Lei Candelaria, Rosalind Santiago, Lumarie Adrada, Beatriz E. Lane, Deanna L. Rauch, Gaiane M. Yang, Wei T. White, Jason B. Chang, Jeffrey T. Moulder, Stacy L. Symmans, W. Fraser Hilsenbeck, Susan G. Piwnica-Worms, Helen |
author_facet | Echeverria, Gloria V. Cai, Shirong Tu, Yizheng Shao, Jiansu Powell, Emily Redwood, Abena B. Jiang, Yan McCoy, Aaron Rinkenbaugh, Amanda L. Lau, Rosanna Trevarton, Alexander J. Fu, Chunxiao Gould, Rebekah Ravenberg, Elizabeth E. Huo, Lei Candelaria, Rosalind Santiago, Lumarie Adrada, Beatriz E. Lane, Deanna L. Rauch, Gaiane M. Yang, Wei T. White, Jason B. Chang, Jeffrey T. Moulder, Stacy L. Symmans, W. Fraser Hilsenbeck, Susan G. Piwnica-Worms, Helen |
author_sort | Echeverria, Gloria V. |
collection | PubMed |
description | Patient-derived xenograft (PDX) models of breast cancer are an effective discovery platform and tool for preclinical pharmacologic testing and biomarker identification. We established orthotopic PDX models of triple negative breast cancer (TNBC) from the primary breast tumors of patients prior to and following neoadjuvant chemotherapy (NACT) while they were enrolled in the ARTEMIS trial (NCT02276443). Serial biopsies were obtained from patients prior to treatment (pre-NACT), from poorly responsive disease after four cycles of Adriamycin and cyclophosphamide (AC, mid-NACT), and in cases of AC-resistance, after a 3-month course of different experimental therapies and/or additional chemotherapy (post-NACT). Our study cohort includes a total of 269 fine needle aspirates (FNAs) from 217 women, generating a total of 62 PDX models (overall success-rate = 23%). Success of PDX engraftment was generally higher from those cancers that proved to be treatment-resistant, whether poorly responsive to AC as determined by ultrasound measurements mid-NACT (p = 0.063), RCB II/III status after NACT (p = 0.046), or metastatic relapse within 2 years of surgery (p = 0.008). TNBC molecular subtype determined from gene expression microarrays of pre-NACT tumors revealed no significant association with PDX engraftment rate (p = 0.877). Finally, we developed a statistical model predictive of PDX engraftment using percent Ki67 positive cells in the patient’s diagnostic biopsy, positive lymph node status at diagnosis, and low volumetric reduction of the patient’s tumor following AC treatment. This novel bank of 62 PDX models of TNBC provides a valuable resource for biomarker discovery and preclinical therapeutic trials aimed at improving neoadjuvant response rates for patients with TNBC. |
format | Online Article Text |
id | pubmed-9831981 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-98319812023-01-12 Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer Echeverria, Gloria V. Cai, Shirong Tu, Yizheng Shao, Jiansu Powell, Emily Redwood, Abena B. Jiang, Yan McCoy, Aaron Rinkenbaugh, Amanda L. Lau, Rosanna Trevarton, Alexander J. Fu, Chunxiao Gould, Rebekah Ravenberg, Elizabeth E. Huo, Lei Candelaria, Rosalind Santiago, Lumarie Adrada, Beatriz E. Lane, Deanna L. Rauch, Gaiane M. Yang, Wei T. White, Jason B. Chang, Jeffrey T. Moulder, Stacy L. Symmans, W. Fraser Hilsenbeck, Susan G. Piwnica-Worms, Helen NPJ Breast Cancer Article Patient-derived xenograft (PDX) models of breast cancer are an effective discovery platform and tool for preclinical pharmacologic testing and biomarker identification. We established orthotopic PDX models of triple negative breast cancer (TNBC) from the primary breast tumors of patients prior to and following neoadjuvant chemotherapy (NACT) while they were enrolled in the ARTEMIS trial (NCT02276443). Serial biopsies were obtained from patients prior to treatment (pre-NACT), from poorly responsive disease after four cycles of Adriamycin and cyclophosphamide (AC, mid-NACT), and in cases of AC-resistance, after a 3-month course of different experimental therapies and/or additional chemotherapy (post-NACT). Our study cohort includes a total of 269 fine needle aspirates (FNAs) from 217 women, generating a total of 62 PDX models (overall success-rate = 23%). Success of PDX engraftment was generally higher from those cancers that proved to be treatment-resistant, whether poorly responsive to AC as determined by ultrasound measurements mid-NACT (p = 0.063), RCB II/III status after NACT (p = 0.046), or metastatic relapse within 2 years of surgery (p = 0.008). TNBC molecular subtype determined from gene expression microarrays of pre-NACT tumors revealed no significant association with PDX engraftment rate (p = 0.877). Finally, we developed a statistical model predictive of PDX engraftment using percent Ki67 positive cells in the patient’s diagnostic biopsy, positive lymph node status at diagnosis, and low volumetric reduction of the patient’s tumor following AC treatment. This novel bank of 62 PDX models of TNBC provides a valuable resource for biomarker discovery and preclinical therapeutic trials aimed at improving neoadjuvant response rates for patients with TNBC. Nature Publishing Group UK 2023-01-10 /pmc/articles/PMC9831981/ /pubmed/36627285 http://dx.doi.org/10.1038/s41523-022-00502-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Echeverria, Gloria V. Cai, Shirong Tu, Yizheng Shao, Jiansu Powell, Emily Redwood, Abena B. Jiang, Yan McCoy, Aaron Rinkenbaugh, Amanda L. Lau, Rosanna Trevarton, Alexander J. Fu, Chunxiao Gould, Rebekah Ravenberg, Elizabeth E. Huo, Lei Candelaria, Rosalind Santiago, Lumarie Adrada, Beatriz E. Lane, Deanna L. Rauch, Gaiane M. Yang, Wei T. White, Jason B. Chang, Jeffrey T. Moulder, Stacy L. Symmans, W. Fraser Hilsenbeck, Susan G. Piwnica-Worms, Helen Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer |
title | Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer |
title_full | Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer |
title_fullStr | Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer |
title_full_unstemmed | Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer |
title_short | Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer |
title_sort | predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9831981/ https://www.ncbi.nlm.nih.gov/pubmed/36627285 http://dx.doi.org/10.1038/s41523-022-00502-1 |
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