Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer
Abstract 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 pr...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-01-01
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| Series: | npj Breast Cancer |
| Online Access: | https://doi.org/10.1038/s41523-022-00502-1 |
| _version_ | 1797422073380864000 |
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| author | Gloria V. Echeverria Shirong Cai Yizheng Tu Jiansu Shao Emily Powell Abena B. Redwood Yan Jiang Aaron McCoy Amanda L. Rinkenbaugh Rosanna Lau Alexander J. Trevarton Chunxiao Fu Rebekah Gould Elizabeth E. Ravenberg Lei Huo Rosalind Candelaria Lumarie Santiago Beatriz E. Adrada Deanna L. Lane Gaiane M. Rauch Wei T. Yang Jason B. White Jeffrey T. Chang Stacy L. Moulder W. Fraser Symmans Susan G. Hilsenbeck Helen Piwnica-Worms |
| author_facet | Gloria V. Echeverria Shirong Cai Yizheng Tu Jiansu Shao Emily Powell Abena B. Redwood Yan Jiang Aaron McCoy Amanda L. Rinkenbaugh Rosanna Lau Alexander J. Trevarton Chunxiao Fu Rebekah Gould Elizabeth E. Ravenberg Lei Huo Rosalind Candelaria Lumarie Santiago Beatriz E. Adrada Deanna L. Lane Gaiane M. Rauch Wei T. Yang Jason B. White Jeffrey T. Chang Stacy L. Moulder W. Fraser Symmans Susan G. Hilsenbeck Helen Piwnica-Worms |
| author_sort | Gloria V. Echeverria |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-03-09T07:26:51Z |
| format | Article |
| id | doaj.art-1aeaec90b47b427c8b0d10b0dad9ddf6 |
| institution | Directory Open Access Journal |
| issn | 2374-4677 |
| language | English |
| last_indexed | 2024-03-09T07:26:51Z |
| publishDate | 2023-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Breast Cancer |
| spelling | doaj.art-1aeaec90b47b427c8b0d10b0dad9ddf62023-12-03T06:52:40ZengNature Portfolionpj Breast Cancer2374-46772023-01-01911910.1038/s41523-022-00502-1Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancerGloria V. Echeverria0Shirong Cai1Yizheng Tu2Jiansu Shao3Emily Powell4Abena B. Redwood5Yan Jiang6Aaron McCoy7Amanda L. Rinkenbaugh8Rosanna Lau9Alexander J. Trevarton10Chunxiao Fu11Rebekah Gould12Elizabeth E. Ravenberg13Lei Huo14Rosalind Candelaria15Lumarie Santiago16Beatriz E. Adrada17Deanna L. Lane18Gaiane M. Rauch19Wei T. Yang20Jason B. White21Jeffrey T. Chang22Stacy L. Moulder23W. Fraser Symmans24Susan G. Hilsenbeck25Helen Piwnica-Worms26Department of Experimental Radiation Oncology, University of Texas MD Anderson Cancer CenterDepartment of Experimental Radiation Oncology, University of Texas MD Anderson Cancer CenterDepartment of Experimental Radiation Oncology, University of Texas MD Anderson Cancer CenterDepartment of Experimental Radiation Oncology, University of Texas MD Anderson Cancer CenterDepartment of Experimental Radiation Oncology, University of Texas MD Anderson Cancer CenterDepartment of Experimental Radiation Oncology, University of Texas MD Anderson Cancer CenterDepartment of Experimental Radiation Oncology, University of Texas MD Anderson Cancer CenterDepartment of Experimental Radiation Oncology, University of Texas MD Anderson Cancer CenterDepartment of Experimental Radiation Oncology, University of Texas MD Anderson Cancer CenterDepartment of Pathology, University of Texas MD Anderson Cancer CenterDepartment of Pathology, University of Texas MD Anderson Cancer CenterDepartment of Pathology, University of Texas MD Anderson Cancer CenterDepartment of Pathology, University of Texas MD Anderson Cancer CenterDepartment of Breast Medical Oncology, University of Texas MD Anderson Cancer CenterDepartment of Pathology, University of Texas MD Anderson Cancer CenterDepartment of Breast Imaging, University of Texas MD Anderson Cancer CenterDepartment of Breast Imaging, University of Texas MD Anderson Cancer CenterDepartment of Breast Imaging, University of Texas MD Anderson Cancer CenterDepartment of Breast Medical Oncology, University of Texas MD Anderson Cancer CenterDepartment of Abdominal Imaging, University of Texas MD Anderson Cancer CenterDepartment of Breast Medical Oncology, University of Texas MD Anderson Cancer CenterDepartment of Breast Medical Oncology, University of Texas MD Anderson Cancer CenterDepartment of Integrative Biology and Pharmacology, University of Texas Health Science CenterDepartment of Breast Medical Oncology, University of Texas MD Anderson Cancer CenterDepartment of Pathology, University of Texas MD Anderson Cancer CenterLester and Sue Smith Breast Center, Baylor College of MedicineDepartment of Experimental Radiation Oncology, University of Texas MD Anderson Cancer CenterAbstract 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.https://doi.org/10.1038/s41523-022-00502-1 |
| spellingShingle | Gloria V. Echeverria Shirong Cai Yizheng Tu Jiansu Shao Emily Powell Abena B. Redwood Yan Jiang Aaron McCoy Amanda L. Rinkenbaugh Rosanna Lau Alexander J. Trevarton Chunxiao Fu Rebekah Gould Elizabeth E. Ravenberg Lei Huo Rosalind Candelaria Lumarie Santiago Beatriz E. Adrada Deanna L. Lane Gaiane M. Rauch Wei T. Yang Jason B. White Jeffrey T. Chang Stacy L. Moulder W. Fraser Symmans Susan G. Hilsenbeck Helen Piwnica-Worms Predictors of success in establishing orthotopic patient-derived xenograft models of triple negative breast cancer npj 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 |
| url | https://doi.org/10.1038/s41523-022-00502-1 |
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