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Krushkal J, Zhao Y, Roney K, Zhu W, Brooks A, Wilsker D, Parchment RE, McShane LM, Doroshow JH. Association of changes in expression of HDAC and SIRT genes after drug treatment with cancer cell line sensitivity to kinase inhibitors. Epigenetics 2024; 19:2309824. [PMID: 38369747 PMCID: PMC10878021 DOI: 10.1080/15592294.2024.2309824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 01/14/2024] [Indexed: 02/20/2024] Open
Abstract
Histone deacetylases (HDACs) and sirtuins (SIRTs) are important epigenetic regulators of cancer pathways. There is a limited understanding of how transcriptional regulation of their genes is affected by chemotherapeutic agents, and how such transcriptional changes affect tumour sensitivity to drug treatment. We investigated the concerted transcriptional response of HDAC and SIRT genes to 15 approved antitumor agents in the NCI-60 cancer cell line panel. Antitumor agents with diverse mechanisms of action induced upregulation or downregulation of multiple HDAC and SIRT genes. HDAC5 was upregulated by dasatinib and erlotinib in the majority of the cell lines. Tumour cell line sensitivity to kinase inhibitors was associated with upregulation of HDAC5, HDAC1, and several SIRT genes. We confirmed changes in HDAC and SIRT expression in independent datasets. We also experimentally validated the upregulation of HDAC5 mRNA and protein expression by dasatinib in the highly sensitive IGROV1 cell line. HDAC5 was not upregulated in the UACC-257 cell line resistant to dasatinib. The effects of cancer drug treatment on expression of HDAC and SIRT genes may influence chemosensitivity and may need to be considered during chemotherapy.
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Affiliation(s)
- Julia Krushkal
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, USA
| | - Yingdong Zhao
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, USA
| | - Kyle Roney
- Department of Biostatistics and Bioinformatics, George Washington University, Washington, DC, USA
| | - Weimin Zhu
- Clinical Pharmacodynamic Biomarkers Program, Applied/Developmental Research Directorate, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Alan Brooks
- Clinical Pharmacodynamic Biomarkers Program, Applied/Developmental Research Directorate, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Deborah Wilsker
- Clinical Pharmacodynamic Biomarkers Program, Applied/Developmental Research Directorate, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Ralph E. Parchment
- Clinical Pharmacodynamic Biomarkers Program, Applied/Developmental Research Directorate, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Lisa M. McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, USA
| | - James H. Doroshow
- Division of Cancer Treatment and Diagnosis and Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
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2
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Gong J, Mita AC, Wei Z, Cheng HH, Mitchell EP, Wright JJ, Ivy SP, Wang V, Gray RC, McShane LM, Rubinstein LV, Patton DR, Williams PM, Hamilton SR, Tricoli JV, Conley BA, Arteaga CL, Harris LN, O'Dwyer PJ, Chen AP, Flaherty KT. Phase II Study of Erdafitinib in Patients With Tumors With Fibroblast Growth Factor Receptor Mutations or Fusions: Results From the NCI-MATCH ECOG-ACRIN Trial (EAY131) Subprotocol K2. JCO Precis Oncol 2024; 8:e2300407. [PMID: 38603650 DOI: 10.1200/po.23.00407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 11/14/2023] [Accepted: 02/28/2024] [Indexed: 04/13/2024] Open
Abstract
PURPOSE Subprotocol K2 (EAY131-K2) of the NCI-MATCH platform trial was an open-label, single-arm, phase II study designed to evaluate the antitumor efficacy of the oral FGFR1-4 inhibitor, erdafitinib, in patients with tumors harboring FGFR1-4 mutations or fusions. METHODS Central confirmation of tumor FGFR1-4 mutations or fusions was required for outcome analysis. Patients with urothelial carcinoma were excluded. Enrolled subjects received oral erdafitinib at a starting dose of 8 mg daily continuously until intolerable toxicity or disease progression. The primary end point was objective response rate (ORR) with key secondary end points of safety, progression-free survival (PFS), and overall survival (OS). RESULTS Thirty-five patients were enrolled, and 25 patients were included in the primary efficacy analysis as prespecified in the protocol. The median age was 61 years, and 52% of subjects had received ≥3 previous lines of therapy. The confirmed ORR was 16% (4 of 25 [90% CI, 5.7 to 33.0], P = .034 against the null rate of 5%). An additional seven patients experienced stable disease as best-confirmed response. Four patients had a prolonged PFS including two with recurrent WHO grade IV, IDH1-/2-wildtype glioblastoma. The median PFS and OS were 3.6 months and 11.0 months, respectively. Erdafitinib was manageable with no new safety signals. CONCLUSION This study met its primary end point in patients with several pretreated solid tumor types harboring FGFR1-3 mutations or fusions. These findings support advancement of erdafitinib for patients with fibroblast growth factor receptor-altered tumors outside of currently approved indications in a potentially tumor-agnostic manner.
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Affiliation(s)
- Jun Gong
- Cedars-Sinai Medical Center, Los Angeles, CA
| | | | - Zihan Wei
- Dana Farber Cancer Institute-ECOG-ACRIN Biostatistics Center, Boston, MA
| | | | - Edith P Mitchell
- Sidney Kimmel Cancer Center at Thomas Jefferson University, Philadelphia, PA
| | - John J Wright
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - S Percy Ivy
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Victoria Wang
- Dana Farber Cancer Institute-ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Robert C Gray
- Dana Farber Cancer Institute-ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Lisa M McShane
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Larry V Rubinstein
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - David R Patton
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | | | - James V Tricoli
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Barbara A Conley
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Lyndsay N Harris
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Alice P Chen
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
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3
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Chen MF, Song Z, Yu HA, Sequist LV, Lovly CM, Mitchell EP, Moscow JA, Gray RJ, Wang V, McShane LM, Rubinstein LV, Patton DR, Williams PM, Hamilton SR, Umemura Y, Tricoli JV, Conley BA, Arteaga CL, Harris LN, O'Dwyer PJ, Chen AP, Flaherty KT. Phase II Study of Osimertinib in Patients With Epidermal Growth Factor Receptor Mutations: Results From the NCI-MATCH ECOG-ACRIN (EAY131) Trial Subprotocol E. JCO Precis Oncol 2024; 8:e2300454. [PMID: 38591867 PMCID: PMC10896470 DOI: 10.1200/po.23.00454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 09/29/2023] [Accepted: 11/20/2023] [Indexed: 04/10/2024] Open
Abstract
PURPOSE The National Cancer Institute Molecular Analysis for Therapy Choice trial is a signal-finding genomically driven platform trial that assigns patients with any advanced refractory solid tumor, lymphoma, or myeloma to targeted therapies on the basis of next-generation sequencing results. Subprotocol E evaluated osimertinib, an epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor, in patients with EGFR mutations. METHODS Eligible patients had EGFR mutations (T790M or rare activating) and received osimertinib 80 mg once daily. Patients with lung cancer with EGFR T790M were excluded. The primary end point was objective response rate (ORR), and the secondary end points were 6-month progression-free survival (PFS), overall survival, and toxicity. RESULTS A total of 19 patients were enrolled: 17 were evaluable for toxicity and 13 for efficacy. The median age of the 13 included in the efficacy analysis was 63 years, 62% had Eastern Cooperative Oncology Group performance status 1, and 31% received >three previous systemic therapies. The most common tumor type was brain cancers (54%). The ORR was 15.4% (n = 2 of 13; 90% CI, 2.8 to 41.0) and 6-month PFS was 16.7% (90% CI, 0 to 34.4). The two confirmed RECIST responses were observed in a patient with neuroendocrine carcinoma not otherwise specified (EGFR exon 20 S768T and exon 18 G719C mutation) and a patient with low-grade epithelial carcinoma of the paranasal sinus (EGFR D770_N771insSVD). The most common (>20%) treatment-related adverse events were diarrhea, thrombocytopenia, and maculopapular rash. CONCLUSION In this pretreated cohort, osimertinib did not meet the prespecified end point threshold for efficacy, but responses were seen in a neuroendocrine carcinoma with an EGFR exon 20 S768T and exon 18 G719C mutation and an epithelial carcinoma with an EGFR D770_N771insSVD mutation. Osimertinib was well tolerated and had a safety profile consistent with previous studies.
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Affiliation(s)
| | - Zihe Song
- Dana Farber Cancer Institute—ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Helena A. Yu
- Memorial Sloan Kettering Cancer Center, New York, NY
| | | | | | - Edith P. Mitchell
- Sidney Kimmel Cancer Center at Thomas Jefferson University, Philadelphia, PA
| | - Jeffrey A. Moscow
- Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Robert J. Gray
- Dana Farber Cancer Institute—ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Victoria Wang
- Dana Farber Cancer Institute—ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Lisa M. McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Larry V. Rubinstein
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - David R. Patton
- Center for Biomedical Informatics & Information Technology, National Cancer Institute, Bethesda, MD
| | | | | | - Yoshie Umemura
- University of Michigan Comprehensive Cancer Center, Ann Arbor, MI
| | - James V. Tricoli
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Barbara A. Conley
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Lyndsay N. Harris
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Alice P. Chen
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
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4
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Gong J, Mita AC, Wei Z, Cheng HH, Mitchell EP, Wright JJ, Ivy SP, Wang V, Gray RC, McShane LM, Rubinstein LV, Patton DR, Williams PM, Hamilton SR, Alva AS, Tricoli JV, Conley BA, Arteaga CL, Harris LN, O'Dwyer PJ, Chen AP, Flaherty KT. Phase II Study of Erdafitinib in Patients With Tumors With FGFR Amplifications: Results From the NCI-MATCH ECOG-ACRIN Trial (EAY131) Subprotocol K1. JCO Precis Oncol 2024; 8:e2300406. [PMID: 38603651 DOI: 10.1200/po.23.00406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 11/14/2023] [Accepted: 02/08/2024] [Indexed: 04/13/2024] Open
Abstract
PURPOSE Despite fibroblast growth factor receptor (FGFR) inhibitors being approved in tumor types with select FGFR rearrangements or gene mutations, amplifications of FGFR represent the most common FGFR alteration across malignancies. Subprotocol K1 (EAY131-K1) of the National Cancer Institute-MATCH platform trial was designed to evaluate the antitumor efficacy of the oral FGFR1-4 inhibitor, erdafitinib, in patients with tumors harboring FGFR1-4 amplification. METHODS EAY131-K1 was an open-label, single-arm, phase II study with central confirmation of presence of FGFR1-4 amplification in tumors. Patients with urothelial carcinoma were excluded. Enrolled patients received oral erdafitinib at a starting dose of 8 mg once daily continuously with escalation to 9 mg once daily continuously, on the basis of predefined time point assessments of phosphate levels, until disease progression or intolerable toxicity. The primary end point was centrally assessed objective response rate (ORR), with key secondary end points being 6-month progression-free survival (PFS6), PFS, overall survival (OS), and safety. RESULTS Thirty-five patients were enrolled into this study with 18 included in the prespecified primary efficacy analysis. The median age of the 18 patients was 60 years, and 78% had received ≥3 previous lines of therapy. There were no confirmed responses to erdafitinib; however, five patients experienced stable disease (SD) as best response. One patient with an FGFR1-amplified breast cancer had a prolonged PFS >168 days (5.5 months). The median PFS was 1.7 months (90% CI, 1.1 to 1.8 months) and the median OS was 4.2 months (90% CI, 2.3 to 9.3 months). The estimated PFS6 rate was 13.8% (90% CI, 3.3 to 31.6). The majority of toxicities were grade 1 to 2 in nature, although there was one grade 5 treatment-related adverse event. CONCLUSION Erdafitinib did not meet its primary end point of efficacy as determined by ORR in treatment-refractory solid tumors harboring FGFR1-4 amplifications. Our findings support that rearrangements and gene mutations, but not amplifications, of FGFR remain the established FGFR alterations with approved indications for FGFR inhibition.
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Affiliation(s)
- Jun Gong
- Cedars-Sinai Medical Center, Los Angeles, CA
| | | | - Zihan Wei
- Dana Farber Cancer Institute-ECOG-ACRIN Biostatistics Center, Boston, MA
| | | | - Edith P Mitchell
- Sidney Kimmel Cancer Center at Thomas Jefferson University, Philadelphia, PA
| | - John J Wright
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - S Percy Ivy
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Victoria Wang
- Dana Farber Cancer Institute-ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Robert C Gray
- Dana Farber Cancer Institute-ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Lisa M McShane
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Larry V Rubinstein
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - David R Patton
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | | | - Ajjai S Alva
- University of Michigan Comprehensive Cancer Center, Ann Arbor, MI
| | - James V Tricoli
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Barbara A Conley
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Lyndsay N Harris
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Alice P Chen
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
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5
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Connolly RM, Wang V, Hyman DM, Grivas P, Mitchell EP, Wright JJ, Sharon E, Gray RJ, McShane LM, Rubinstein LV, Patton DR, Williams PM, Hamilton SR, Wang J, Wisinski KB, Tricoli JV, Conley BA, Harris LN, Arteaga CL, O'Dwyer PJ, Chen AP, Flaherty KT. Trastuzumab and Pertuzumab in Patients with Non-Breast/Gastroesophageal HER2-Amplified Tumors: Results from the NCI-MATCH ECOG-ACRIN Trial (EAY131) Subprotocol J. Clin Cancer Res 2024; 30:1273-1280. [PMID: 38433347 PMCID: PMC10984755 DOI: 10.1158/1078-0432.ccr-23-0633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 07/05/2023] [Accepted: 01/22/2024] [Indexed: 03/05/2024]
Abstract
PURPOSE NCI-MATCH assigned patients with advanced cancer and progression on prior treatment, based on genomic alterations in pretreatment tumor tissue. Arm J (EAY131-J) evaluated the combination of trastuzumab/pertuzumab (HP) across HER2-amplified tumors. PATIENTS AND METHODS Eligible patients had high levels of HER2 amplification [copy number (CN) ≥7] detected by central next-generation sequencing (NGS) or through NCI-designated laboratories. Patients with breast/gastroesophageal adenocarcinoma and those who received prior HER2-directed therapy were excluded. Enrollment of patients with colorectal cancer was capped at 4 based on emerging data. Patients received HP IV Q3 weeks until progression or unacceptable toxicity. Primary endpoint was objective response rate (ORR); secondary endpoints included progression-free survival (PFS) and overall survival (OS). RESULTS Thirty-five patients were enrolled, with 25 included in the primary efficacy analysis (CN ≥7 confirmed by a central lab, median CN = 28). Median age was 66 (range, 31-80), and half of all patients had ≥3 prior therapies (range, 1-11). The confirmed ORR was 12% [3/25 partial responses (colorectal, cholangiocarcinoma, urothelial cancers), 90% confidence interval (CI) 3.4%-28.2%]. There was one additional partial response (urothelial cancer) in a patient with an unconfirmed ERBB2 copy number. Median PFS was 3.3 months (90% CI 2.0-4.1), and median OS 9.4 months (90% CI 5.0-18.9). Treatment-emergent adverse events were consistent with prior studies. There was no association between HER2 CN and response. CONCLUSIONS HP was active in a selection of HER2-amplified tumors (non-breast/gastroesophageal) but did not meet the predefined efficacy benchmark. Additional strategies targeting HER2 and potential resistance pathways are warranted, especially in rare tumors.
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Affiliation(s)
- Roisin M Connolly
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University, Baltimore, Maryland
- Cancer Research @UCC, College of Medicine and Health, University College Cork, Ireland
| | - Victoria Wang
- Dana Farber Cancer Institute, ECOG-ACRIN Biostatistics Center, Boston, Massachusetts
| | - David M Hyman
- Memorial Sloan Kettering Cancer Center, New York, New York
| | - Petros Grivas
- University of Washington, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Edith P Mitchell
- Sidney Kimmel Cancer Center at Thomas Jefferson University Hospital, Philadelphia, Pennsylvania
| | - John J Wright
- Investigational Drug Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - Elad Sharon
- Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - Robert J Gray
- Dana Farber Cancer Institute, ECOG-ACRIN Biostatistics Center, Boston, Massachusetts
| | - Lisa M McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - Larry V Rubinstein
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - David R Patton
- Center for Biomedical Informatics and Information Technology, National Cancer Institute, Bethesda, Maryland
| | - P Mickey Williams
- Frederick National Laboratory for Cancer Research, Frederick, Maryland
| | | | - Jue Wang
- UT Southwestern Simmons Comprehensive Cancer Center, Dallas, Texas
| | - Kari B Wisinski
- University of Wisconsin Carbone Cancer Center, Madison, Wisconsin
| | - James V Tricoli
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - Barbara A Conley
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - Lyndsay N Harris
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - Carlos L Arteaga
- UT Southwestern Simmons Comprehensive Cancer Center, Dallas, Texas
| | | | - Alice P Chen
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - Keith T Flaherty
- Massachusetts General Hospital Cancer Center, Boston, Massachusetts
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6
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Vega DM, Yee LM, McShane LM, Williams PM, Chen L, Vilimas T, Fabrizio D, Funari V, Newberg J, Bruce LK, Chen SJ, Baden J, Carl Barrett J, Beer P, Butler M, Cheng JH, Conroy J, Cyanam D, Eyring K, Garcia E, Green G, Gregersen VR, Hellmann MD, Keefer LA, Lasiter L, Lazar AJ, Li MC, MacConaill LE, Meier K, Mellert H, Pabla S, Pallavajjalla A, Pestano G, Salgado R, Samara R, Sokol ES, Stafford P, Budczies J, Stenzinger A, Tom W, Valkenburg KC, Wang XZ, Weigman V, Xie M, Xie Q, Zehir A, Zhao C, Zhao Y, Stewart MD, Allen J. Erratum to "Aligning tumor mutational burden (TMB) quantification across diagnostic platforms: phase II of the Friends of Cancer Research TMB Harmonization Project": [Annals of Oncology 32 (2021) 1626-1636]. Ann Oncol 2024; 35:145. [PMID: 37558578 DOI: 10.1016/j.annonc.2023.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/11/2023] Open
Affiliation(s)
- D M Vega
- Friends of Cancer Research, Washington
| | - L M Yee
- National Cancer Institute, Bethesda
| | | | - P M Williams
- Molecular Characterization Laboratory, Frederick National Lab for Cancer Research, Leidos Biomedical Research Inc., Frederick
| | - L Chen
- Molecular Characterization Laboratory, Frederick National Lab for Cancer Research, Leidos Biomedical Research Inc., Frederick
| | - T Vilimas
- Molecular Characterization Laboratory, Frederick National Lab for Cancer Research, Leidos Biomedical Research Inc., Frederick
| | | | - V Funari
- NeoGenomics Laboratories, Aliso Viejo, USA
| | | | - L K Bruce
- NeoGenomics Laboratories, Aliso Viejo, USA
| | | | - J Baden
- Bristol Myers Squibb Co., Princeton
| | | | - P Beer
- European Organisation for Research and Treatment of Cancer, Brussels, Belgium
| | - M Butler
- LGC Clinical Diagnostics, Gaithersburg
| | | | | | - D Cyanam
- Clinical Sequencing Division, Thermo Fisher Scientific, Ann Arbor
| | - K Eyring
- Intermountain Precision Genomics, St. George
| | - E Garcia
- Brigham and Women's Hospital, Boston, USA
| | - G Green
- Bristol Myers Squibb Co., Princeton
| | | | - M D Hellmann
- Memorial Sloan Kettering Cancer Center, New York
| | | | - L Lasiter
- Friends of Cancer Research, Washington
| | - A J Lazar
- The University of Texas MD Anderson Cancer Center, Houston
| | - M-C Li
- National Cancer Institute, Bethesda
| | | | - K Meier
- Illumina Inc, Clinical Genomics, San Diego
| | | | | | | | | | - R Salgado
- European Organisation for Research and Treatment of Cancer, Brussels, Belgium
| | | | | | - P Stafford
- Caris Life Sciences Inc, Phoenix, Arizona, USA
| | - J Budczies
- Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany
| | - A Stenzinger
- Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany
| | - W Tom
- Clinical Sequencing Division, Thermo Fisher Scientific, Ann Arbor
| | | | - X Z Wang
- EMD Serono Research and Development Institute, Inc., Billerica
| | | | - M Xie
- AstraZeneca Pharmaceuticals LP, Waltham, USA
| | - Q Xie
- General Dynamics Information Technology, Inc., Columbia, USA
| | - A Zehir
- Memorial Sloan Kettering Cancer Center, New York
| | - C Zhao
- Illumina Inc, Clinical Genomics, San Diego
| | - Y Zhao
- National Cancer Institute, Bethesda
| | | | - J Allen
- Friends of Cancer Research, Washington
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7
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Harris LN, Blanke CD, Erba HP, Ford JM, Gray RJ, LeBlanc ML, Hu-Lieskovan S, Litzow MR, Luger SM, Meric-Bernstam F, O'Dwyer PJ, Othus MK, Politi K, Shepherd LE, Allegra CJ, Chen HX, Ivy SP, Korde LA, Little RF, McShane LM, Moscow JA, Patton DR, Thurin M, Yee LM, Doroshow JH. The New NCI Precision Medicine Trials. Clin Cancer Res 2023; 29:4728-4732. [PMID: 37531248 PMCID: PMC10690084 DOI: 10.1158/1078-0432.ccr-23-0917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 06/06/2023] [Accepted: 07/20/2023] [Indexed: 08/04/2023]
Abstract
Basket, umbrella, and platform trial designs (master protocols) have emerged over the last decade to study precision medicine approaches in oncology. First-generation trials like NCI-MATCH (Molecular Analysis for Therapy Choice) have proven the principle that studying targeted therapies on a large scale is feasible both from the laboratory and clinical perspectives. However, single-agent targeted therapies have shown limited ability to control metastatic disease, despite careful matching of drug to target. As such, newer approaches employing combinations of targeted therapy, or targeted therapy with standard therapies, need to be considered. The NCI has recently embarked on three second-generation precision medicine trials to address this need: ComboMATCH, iMATCH, and myeloMATCH. The design of these trials and necessary infrastructure are discussed in the following perspective.
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Affiliation(s)
| | - Charles D. Blanke
- SWOG Cancer Research Network, OHSU Knight Cancer Center, Portland, Oregon
| | - Harry P. Erba
- Department of Medicine, Duke Cancer Center, Durham, North Carolina
| | - James M. Ford
- Division of Oncology, Stanford University School of Medicine, Stanford, California
| | - Robert J. Gray
- Department of Data Science, Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Michael L. LeBlanc
- SWOG Statistics and Data Management Center, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Siwen Hu-Lieskovan
- Department of Medicine, University of Utah School of Medicine, Salt Lake City, Utah
| | - Mark R. Litzow
- Division of Hematology, Mayo Clinic, Rochester, Minnesota
| | - Selina M. Luger
- Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Funda Meric-Bernstam
- Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Peter J. O'Dwyer
- ECOG-ACRIN Cancer Research Group, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Megan K.D. Othus
- Biostatistics, Public Health Division, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Katerina Politi
- Section of Medical Oncology, Yale School of Medicine, New Haven, Connecticut
| | - Lois E. Shepherd
- Canadian Cancer Trials Group, Queen's University, Kingston, Ontario, Canada
| | | | - Helen X. Chen
- Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | - S. Percy Ivy
- Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | - Larissa A. Korde
- Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | | | - Lisa M. McShane
- Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | | | - David R. Patton
- Clinical and Translational Research Branch, Center for Biomedical Informatics and Information Technology, NCI, Rockville, Maryland
| | - Magdalena Thurin
- Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | - Laura M. Yee
- Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
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8
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Wolff AC, Somerfield MR, Dowsett M, Hammond MEH, Hayes DF, McShane LM, Saphner TJ, Spears PA, Allison KH. Human Epidermal Growth Factor Receptor 2 Testing in Breast Cancer. Arch Pathol Lab Med 2023; 147:993-1000. [PMID: 37303228 DOI: 10.5858/arpa.2023-0950-sa] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/29/2023] [Indexed: 06/13/2023]
Abstract
PURPOSE.— To update the American Society of Clinical Oncology-College of American Pathologists (ASCO-CAP) recommendations for human epidermal growth factor receptor 2 (HER2) testing in breast cancer. An Update Panel is aware that a new generation of antibody-drug conjugates targeting the HER2 protein is active against breast cancers that lack protein overexpression or gene amplification. METHODS.— The Update Panel conducted a systematic literature review to identify signals for updating recommendations. RESULTS.— The search identified 173 abstracts. Of 5 potential publications reviewed, none constituted a signal for revising existing recommendations. RECOMMENDATIONS.— The 2018 ASCO-CAP recommendations for HER2 testing are affirmed. DISCUSSION.— HER2 testing guidelines have focused on identifying HER2 protein overexpression or gene amplification in breast cancer to identify patients for therapies that disrupt HER2 signaling. This update acknowledges a new indication for trastuzumab deruxtecan when HER2 is not overexpressed or amplified but is immunohistochemistry (IHC) 1+ or 2+ without amplification by in situ hybridization. Clinical trial data on tumors that tested IHC 0 are limited (excluded from DESTINY-Breast04), and evidence is lacking that these cancers behave differently or do not respond similarly to newer HER2 antibody-drug conjugates. Although current data do not support a new IHC 0 versus 1+ prognostic or predictive threshold for response to trastuzumab deruxtecan, this threshold is now relevant because of the trial entry criteria that supported its new regulatory approval. Therefore, although it is premature to create new result categories of HER2 expression (eg, HER2-Low, HER2-Ultra-Low), best practices to distinguish IHC 0 from 1+ are now clinically relevant. This update affirms prior HER2 reporting recommendations and offers a new HER2 testing reporting comment to highlight the current relevance of IHC 0 versus 1+ results and best practice recommendations to distinguish these often subtle differences. Additional information is available at www.asco.org/breast-cancer-guidelines.
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Affiliation(s)
- Antonio C Wolff
- From the Johns Hopkins Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland (Wolff)
- The Stanford University School of Medicine, Stanford, California (Allison)
| | - Mark R Somerfield
- The American Society of Clinical Oncology, Alexandria, Virginia (Somerfield)
| | - Mitchell Dowsett
- The Royal Marsden NHS Foundation Trust, London, United Kingdom (Dowsett)
| | - M Elizabeth H Hammond
- Intermountain Healthcare and the University of Utah School of Medicine, Salt Lake City (Hammond)
| | | | - Lisa M McShane
- The National Cancer Institute, Bethesda, Maryland (McShane)
| | - Thomas J Saphner
- The Vince Lombardi Cancer Clinic, Two Rivers, Wisconsin (Saphner)
| | | | - Kimberly H Allison
- The Stanford University School of Medicine, Stanford, California (Allison)
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Wolff AC, Somerfield MR, Dowsett M, Hammond MEH, Hayes DF, McShane LM, Saphner TJ, Spears PA, Allison KH. Human Epidermal Growth Factor Receptor 2 Testing in Breast Cancer: ASCO-College of American Pathologists Guideline Update. J Clin Oncol 2023:JCO2202864. [PMID: 37284804 DOI: 10.1200/jco.22.02864] [Citation(s) in RCA: 52] [Impact Index Per Article: 52.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023] Open
Abstract
PURPOSE To update ASCO-College of American Pathologists (CAP) recommendations for human epidermal growth factor receptor 2 (HER2) testing in breast cancer. The Panel is aware that a new generation of antibody-drug conjugates (ADCs) targeting the HER2 protein is active against breast cancers that lack protein overexpression or gene amplification. METHODS An Update Panel conducted a systematic literature review to identify signals for updating recommendations. RESULTS The search identified 173 abstracts. Of five potential publications reviewed, none constituted a signal for revising existing recommendations. RECOMMENDATIONS The 2018 ASCO-CAP recommendations for HER2 testing are affirmed. DISCUSSION HER2 testing guidelines have focused on identifying HER2 protein overexpression or gene amplification in breast cancer to identify patients for therapies that disrupt HER2 signaling. This update acknowledges a new indication for trastuzumab deruxtecan when HER2 is not overexpressed or amplified but is immunohistochemistry (IHC) 1+ or 2+ without amplification by in situ hybridization. Clinical trial data on tumors that tested IHC 0 are limited (excluded from DESTINY-Breast04), and evidence is lacking that these cancers behave differently or do not respond similarly to newer HER2 ADCs. Although current data do not support a new IHC 0 versus 1+ prognostic or predictive threshold for response to trastuzumab deruxtecan, this threshold is now relevant because of the trial entry criteria that supported its new regulatory approval. Therefore, while it is premature to create new result categories of HER2 expression (eg, HER2-Low, HER2-Ultra-Low), best practices to distinguish IHC 0 from 1+ are now clinically relevant. This Update affirms prior HER2 reporting recommendations and offers a new HER2 testing reporting comment to highlight the current relevance of IHC 0 versus 1+ results and best practice recommendations to distinguish these often subtle differences.Additional information is available at www.asco.org/breast-cancer-guidelines.
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Affiliation(s)
- Antonio C Wolff
- Johns Hopkins Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD
| | | | | | - M Elizabeth H Hammond
- Intermountain Healthcare and University of Utah School of Medicine, Salt Lake City, UT
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10
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O'Dwyer PJ, Gray RJ, Flaherty KT, Chen AP, Li S, Wang V, McShane LM, Patton DR, Tricoli JV, Williams PM, Iafrate AJ, Sklar J, Mitchell EP, Takebe N, Sims DJ, Coffey B, Fu T, Routbort M, Rubinstein LV, Little RF, Arteaga CL, Marinucci D, Hamilton SR, Conley BA, Harris LN, Doroshow JH. The NCI-MATCH trial: lessons for precision oncology. Nat Med 2023; 29:1349-1357. [PMID: 37322121 PMCID: PMC10612141 DOI: 10.1038/s41591-023-02379-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 04/28/2023] [Indexed: 06/17/2023]
Abstract
The NCI-MATCH (Molecular Analysis for Therapy Choice) trial ( NCT02465060 ) was launched in 2015 as a genomically driven, signal-seeking precision medicine platform trial-largely for patients with treatment-refractory, malignant solid tumors. Having completed in 2023, it remains one of the largest tumor-agnostic, precision oncology trials undertaken to date. Nearly 6,000 patients underwent screening and molecular testing, with a total of 1,593 patients (inclusive of continued accrual from standard next-generation sequencing) being assigned to one of 38 substudies. Each substudy was a phase 2 trial of a therapy matched to a genomic alteration, with a primary endpoint of objective tumor response by RECIST criteria. In this Perspective, we summarize the outcomes of the initial 27 substudies in NCI-MATCH, which met its signal-seeking objective with 7/27 positive substudies (25.9%). We discuss key aspects of the design and operational conduct of the trial, highlighting important lessons for future precision medicine studies.
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Affiliation(s)
| | - Robert J Gray
- Dana-Farber Cancer Institute - ECOG-ACRIN Biostatistics Center, Boston, MA, USA
| | | | - Alice P Chen
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Shuli Li
- Dana-Farber Cancer Institute - ECOG-ACRIN Biostatistics Center, Boston, MA, USA
| | - Victoria Wang
- Dana-Farber Cancer Institute - ECOG-ACRIN Biostatistics Center, Boston, MA, USA
| | - Lisa M McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - David R Patton
- Center for Biomedical Informatics & Information Technology, National Cancer Institute, Bethesda, MD, USA
| | - James V Tricoli
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - P Mickey Williams
- Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - A John Iafrate
- Massachusetts General Hospital Cancer Center, Boston, MA, USA
| | | | | | - Naoko Takebe
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - David J Sims
- Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Brent Coffey
- Center for Biomedical Informatics & Information Technology, National Cancer Institute, Bethesda, MD, USA
| | - Tony Fu
- Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Mark Routbort
- University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Larry V Rubinstein
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Richard F Little
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Carlos L Arteaga
- UT Southwestern Simmons Comprehensive Cancer Center, Dallas, TX, USA
| | | | | | - Barbara A Conley
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Lyndsay N Harris
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - James H Doroshow
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
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11
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Meric-Bernstam F, Ford JM, O'Dwyer PJ, Shapiro GI, McShane LM, Freidlin B, O'Cearbhaill RE, George S, Glade-Bender J, Lyman GH, Tricoli JV, Patton D, Hamilton SR, Gray RJ, Hawkins DS, Ramineni B, Flaherty KT, Grivas P, Yap TA, Berlin J, Doroshow JH, Harris LN, Moscow JA. National Cancer Institute Combination Therapy Platform Trial with Molecular Analysis for Therapy Choice (ComboMATCH). Clin Cancer Res 2023; 29:1412-1422. [PMID: 36662819 PMCID: PMC10102840 DOI: 10.1158/1078-0432.ccr-22-3334] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 01/09/2023] [Accepted: 01/17/2023] [Indexed: 01/21/2023]
Abstract
Over the past decade, multiple trials, including the precision medicine trial National Cancer Institute-Molecular Analysis for Therapy Choice (NCI-MATCH, EAY131, NCT02465060) have sought to determine if treating cancer based on specific genomic alterations is effective, irrespective of the cancer histology. Although many therapies are now approved for the treatment of cancers harboring specific genomic alterations, most patients do not respond to therapies targeting a single alteration. Further, when antitumor responses do occur, they are often not durable due to the development of drug resistance. Therefore, there is a great need to identify rational combination therapies that may be more effective. To address this need, the NCI and National Clinical Trials Network have developed NCI-ComboMATCH, the successor to NCI-MATCH. Like the original trial, NCI-ComboMATCH is a signal-seeking study. The goal of ComboMATCH is to overcome drug resistance to single-agent therapy and/or utilize novel synergies to increase efficacy by developing genomically-directed combination therapies, supported by strong preclinical in vivo evidence. Although NCI-MATCH was mainly comprised of multiple single-arm studies, NCI-ComboMATCH tests combination therapy, evaluating both combination of targeted agents as well as combinations of targeted therapy with chemotherapy. Although NCI-MATCH was histology agnostic with selected tumor exclusions, ComboMATCH has histology-specific and histology-agnostic arms. Although NCI-MATCH consisted of single-arm studies, ComboMATCH utilizes single-arm as well as randomized designs. NCI-MATCH had a separate, parallel Pediatric MATCH trial, whereas ComboMATCH will include children within the same trial. We present rationale, scientific principles, study design, and logistics supporting the ComboMATCH study.
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Affiliation(s)
- Funda Meric-Bernstam
- Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - James M. Ford
- Department of Medicine – Oncology, Stanford University, Stanford, California
| | - Peter J. O'Dwyer
- Division of Hematology-Oncology, Department of Medicine, Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Geoffrey I. Shapiro
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Lisa M. McShane
- Biometric Research Program, DCTD, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Boris Freidlin
- Biometric Research Program, DCTD, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Roisin E. O'Cearbhaill
- Department of Medicine, Memorial Sloan Kettering Cancer Center; Weill Cornell Medical College, New York, New York
| | - Suzanne George
- Sarcoma and Bone Oncology Division, Medical Oncology Department, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Julia Glade-Bender
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Gary H. Lyman
- Clinical Research Division, Fred Hutchinson Cancer Research Center and the University of Washington, Seattle, Washington
| | - James V. Tricoli
- Diagnostic Biomarkers and Technology Branch, Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, Maryland
| | - David Patton
- Center for Biomedical Informatics and Information Technology, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Stanley R. Hamilton
- Department of Pathology, City of Hope National Medical Center, Duarte, California
| | - Robert J. Gray
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Douglas S. Hawkins
- Department of Pediatrics, Seattle Children's Hospital, University of Washington, Seattle, Washington
| | - Bhanumati Ramineni
- Cancer Therapy Evaluation Program, Regulatory Affairs Branch, DCTD, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Keith T. Flaherty
- Division of Medical Oncology, Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, Massachusetts
| | - Petros Grivas
- Department of Medicine, Division of Medical Oncology, University of Washington, Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle Cancer Care Alliance, Seattle, Washington
| | - Timothy A. Yap
- Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jordan Berlin
- Division of Hematology and Oncology, Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
| | - James H. Doroshow
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - Lyndsay N. Harris
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - Jeffrey A. Moscow
- Investigational Drug Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
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12
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Clark AS, Hong F, Finn RS, DeMichele AM, Mitchell EP, Zwiebel J, Arnaldez FI, Gray RJ, Wang V, McShane LM, Rubinstein LV, Patton D, Williams PM, Hamilton SR, Copur MS, Kasbari SS, Thind R, Conley BA, Arteaga CL, O'Dwyer PJ, Harris LN, Chen AP, Flaherty KT. Phase II Study of Palbociclib (PD-0332991) in CCND1, 2, or 3 Amplification: Results from the NCI-MATCH ECOG-ACRIN Trial (EAY131) Subprotocol Z1B. Clin Cancer Res 2023; 29:1477-1483. [PMID: 36853016 PMCID: PMC10102836 DOI: 10.1158/1078-0432.ccr-22-2150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 10/07/2022] [Accepted: 02/07/2023] [Indexed: 03/01/2023]
Abstract
PURPOSE Cyclin D/CDK4/6 is critical in controlling the G1 to S checkpoint. CCND, the gene encoding cyclin D, is known to be amplified in a variety of solid tumors. Palbociclib is an oral CDK4/6 inhibitor, approved in advanced breast cancer in combination with endocrine therapy. We explored the efficacy of palbociclib in patients with nonbreast solid tumors containing an amplification in CCND1, 2, or 3. PATIENTS AND METHODS Patients with tumors containing a CCND1, 2, or 3 amplification and expression of the retinoblastoma protein were assigned to subprotocol Z1B and received palbociclib 125 mg once daily for 21 days of a 28-day cycle. Tumor response was assessed every two cycles. RESULTS Forty patients were assigned to subprotocol Z1B; 4 patients had outside assays identifying the CCND1, 2, or 3 amplification and were not confirmed centrally; 3 were ineligible and 2 were not treated (1 untreated patient was also ineligible), leaving 32 evaluable patients for this analysis. There were no partial responses; 12 patients (37.5%) had stable disease as best response. There were seven deaths on study, all during cycle 1 and attributable to disease progression. Median progression-free survival was 1.8 months. The most common toxicities were leukopenia (n = 21, 55%) and neutropenia (n = 19, 50%); neutropenia was the most common grade 3/4 event (n = 12, 32%). CONCLUSIONS Palbociclib was not effective at treating nonbreast solid tumors with a CCND1, 2, or 3 amplification in this cohort. These data do not support further investigation of single-agent palbociclib in tumors with CCND1, 2, or 3 amplification.
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Affiliation(s)
- Amy S. Clark
- University of Pennsylvania, Philadelphia, Pennsylvania
| | - Fangxin Hong
- Dana Farber Cancer Institute – ECOG-ACRIN Biostatistics Center, Boston, Massachusetts
| | - Richard S. Finn
- University of California, Los Angeles, Los Angeles, California
| | | | - Edith P. Mitchell
- Sidney Kimmel Cancer Center at Thomas Jefferson University Hospital, Philadelphia, Pennsylvania
| | - James Zwiebel
- Investigational Drug Branch, Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | - Fernanda I. Arnaldez
- Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | - Robert J. Gray
- Dana Farber Cancer Institute – ECOG-ACRIN Biostatistics Center, Boston, Massachusetts
| | - Victoria Wang
- Dana Farber Cancer Institute – ECOG-ACRIN Biostatistics Center, Boston, Massachusetts
| | - Lisa M. McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | - Larry V. Rubinstein
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | - David Patton
- Center for Biomedical Informatics and Information Technology, NCI, Bethesda, Maryland
| | | | | | | | | | | | | | | | | | | | - Alice P. Chen
- Early Clinical Trials Development Program, Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
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13
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Wisinski KB, Flamand Y, Wilson MA, Luke JJ, Tawbi HA, Hong F, Mitchell EP, Zwiebel JA, Chen H, Gray RJ, Li S, McShane LM, Rubinstein LV, Patton D, Williams PM, Hamilton SR, Behrens RJ, Pennington KP, Conley BA, Arteaga CL, Harris LN, O'Dwyer PJ, Chen AP, Flaherty KT. Trametinib in Patients With NF1-, GNAQ-, or GNA11-Mutant Tumors: Results From the NCI-MATCH ECOG-ACRIN Trial (EAY131) Subprotocols S1 and S2. JCO Precis Oncol 2023; 7:e2200421. [PMID: 37053535 PMCID: PMC10309549 DOI: 10.1200/po.22.00421] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 02/13/2023] [Indexed: 04/15/2023] Open
Abstract
PURPOSE NCI-MATCH is a precision medicine trial using genomic testing to allocate patients with advanced malignancies to targeted treatment subprotocols. This report combines two subprotocols evaluating trametinib, a MEK1/2 inhibitor, in patients with Neurofibromatosis 1 (NF1[S1] or GNA11/Q [S2]) altered tumors. METHODS Eligible patients had tumors with deleterious inactivating NF1 or GNA11/Q mutations by the customized Oncomine AmpliSeq panel. Prior MEK inhibitor treatment was excluded. Glioblastomas (GBMs) were permitted, including malignancies associated with germline NF1 mutations (S1 only). Trametinib was administered at 2 mg once daily over 28-day cycles until toxicity or disease progression. Primary end point was objective response rate (ORR). Secondary end points included progression-free survival (PFS) at 6 months, PFS, and overall survival. Exploratory analyses included co-occurring genomic alterations and PTEN loss. RESULTS Fifty patients were eligible and started therapy: 46 with NF1 mutations (S1) and four with GNA11 mutations (S2). In the NF1 cohort, nonsense single-nucleotide variants were identified in 29 and frameshift deletions in 17 tumors. All in S2 had nonuveal melanoma and GNA11 Q209L variant. Two partial responses (PR) were noted in S1, one patient each with advanced lung cancer and GBM for an ORR of 4.3% (90% CI, 0.8 to 13.1). One patient with melanoma in S2 had a PR (ORR, 25%; 90% CI, 1.3 to 75.1). Prolonged stable disease (SD) was also noted in five patients (four in S1 and one in S2) with additional rare histologies. Adverse events were as previously described with trametinib. Comutations in TP53 and PIK3CA were common. CONCLUSION Although these subprotocols did not meet the primary end point for ORR, significant responses or prolonged SD noted in some disease subtypes warrants further investigation.
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Affiliation(s)
- Kari B. Wisinski
- Department of Medicine, University of Wisconsin Carbone Cancer Center, Madison, WI
| | - Yael Flamand
- Dana Farber Cancer Institute—ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Melissa A. Wilson
- Department of Oncology, Division of Hematology/Medical Oncology, St Luke's University Health Network, Easton, PA
| | - Jason J. Luke
- Division of Hematology/Oncology, University of Pittsburgh Medical Center, Hillman Cancer Center, Pittsburgh, PA
| | | | - Fangxin Hong
- Dana Farber Cancer Institute—ECOG-ACRIN Biostatistics Center, Boston, MA
| | | | - James A. Zwiebel
- Investigational Drug Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Helen Chen
- Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Robert J. Gray
- Dana Farber Cancer Institute—ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Shuli Li
- Dana Farber Cancer Institute—ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Lisa M. McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Lawrence V. Rubinstein
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - David Patton
- Center for Biomedical Informatics & Information Technology, National Cancer Institute, Bethesda, MD
| | | | | | | | | | - Barbara A. Conley
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Lyndsay N. Harris
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Alice P. Chen
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
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Sankaran H, Finnigan SR, McShane LM, Best AF, Seibel NL. Enrollment of adolescent and young adult patients newly diagnosed with cancer in NCI CTEP-sponsored clinical trials before and after launch of the NCI National Clinical Trials Network. Cancer 2022; 128:3843-3849. [PMID: 36089859 PMCID: PMC9826149 DOI: 10.1002/cncr.34402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 06/27/2022] [Accepted: 06/30/2022] [Indexed: 01/11/2023]
Abstract
BACKGROUND Participation of adolescents and young adults (AYAs) in oncology clinical trials is important to ensure adequate opportunities for AYA patients to contribute to, and benefit from, advances in cancer treatment. METHODS Accrual data for National Cancer Institute (NCI) Cancer Therapy Evaluation Program (CTEP) cooperative group-led treatment trials were examined to assess enrollment of newly diagnosed AYA patients (15-39 years) during the period 2004-2019, with particular interest in comparing enrollment before launch of the NCI National Clinical Trials Network (NCTN) to after. All phase 2, 2/3, and 3 trials activated during the period between January 1, 2004, and December 31, 2019, were identified (n = 1568) and reduced to a set of 304 that met predetermined criteria to focus on cooperative group-led trials that involved therapy for newly diagnosed cancer and had age eligibility overlapping the AYA range. The proportion of AYA patients relative to total accrual, along with 95% bootstrapped CI was calculated for patients enrolled pre-NCTN and post-NCTN. RESULTS AYA accrual comprised 9.5% (95% CI, 7.6-11.8) pre-NCTN compared with 14.0% (95% CI, 9.9-18.3) post-NCTN. The mean difference in proportions post-NCTN compared with pre-NCTN was 4.4% (0.7%-8.3%). CONCLUSIONS These results indicate an increase in AYA participation in trials conducted within the NCTN relative to the pre-NCTN period. This suggests an awareness and utilization of NCTN trials for AYAs with cancer.
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Affiliation(s)
- Hari Sankaran
- Biometric Research Program, Division of Cancer Treatment and DiagnosisNational Cancer InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Shanda R. Finnigan
- Clinical Investigations Branch, Cancer Therapy Evaluation Program, Division of Cancer Treatment and DiagnosisNational Cancer InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Lisa M. McShane
- Biometric Research Program, Division of Cancer Treatment and DiagnosisNational Cancer InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Ana F. Best
- Biometric Research Program, Division of Cancer Treatment and DiagnosisNational Cancer InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Nita L. Seibel
- Clinical Investigations Branch, Cancer Therapy Evaluation Program, Division of Cancer Treatment and DiagnosisNational Cancer InstituteNational Institutes of HealthBethesdaMarylandUSA
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15
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Hayes DF, Herbst RS, Myles JL, Topalian SL, Yohe SL, Aronson N, Bellizzi AM, Basu Roy U, Bradshaw G, Edwards RH, El-Gabry EA, Elvin J, Gajewski TF, McShane LM, Oberley M, Philip R, Rimm DL, Rosenbaum JN, Rubin EH, Schlager L, Sherwood SW, Stewart M, Taube JM, Thurin M, Vasalos P, Laser J. Proceedings From the ASCO/College of American Pathologists Immune Checkpoint Inhibitor Predictive Biomarker Summit. JCO Precis Oncol 2022; 6:e2200454. [PMID: 36446042 PMCID: PMC10530621 DOI: 10.1200/po.22.00454] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 09/29/2022] [Accepted: 10/11/2022] [Indexed: 09/29/2023] Open
Abstract
PURPOSE Immune checkpoint inhibition (ICI) therapy represents one of the great advances in the field of oncology, highlighted by the Nobel Prize in 2018. Multiple predictive biomarkers for ICI benefit have been proposed. These include assessment of programmed death ligand-1 expression by immunohistochemistry, and determination of mutational genotype (microsatellite instability or mismatch repair deficiency or tumor mutational burden) as a reflection of neoantigen expression. However, deployment of these assays has been challenging for oncologists and pathologists alike. METHODS To address these issues, ASCO and the College of American Pathologists convened a virtual Predictive Factor Summit from September 14 to 15, 2021. Representatives from the academic community, US Food and Drug Administration, Centers for Medicare and Medicaid Services, National Institutes of Health, health insurance organizations, pharmaceutical companies, in vitro diagnostics manufacturers, and patient advocate organizations presented state-of-the-art predictive factors for ICI, associated problems, and possible solutions. RESULTS The Summit provided an overview of the challenges and opportunities for improvement in assay execution, interpretation, and clinical applications of programmed death ligand-1, microsatellite instability-high or mismatch repair deficient, and tumor mutational burden-high for ICI therapies, as well as issues related to regulation, reimbursement, and next-generation ICI biomarker development. CONCLUSION The Summit concluded with a plan to generate a joint ASCO/College of American Pathologists strategy for consideration of future research in each of these areas to improve tumor biomarker tests for ICI therapy.
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Affiliation(s)
| | | | | | - Suzanne L. Topalian
- Johns Hopkins Bloomberg-Kimmel Institute for Cancer Immunotherapy, Baltimore, MD
| | | | | | | | | | | | - Robin H. Edwards
- Bristol-Myers Squibb, New York, NY (at time of summit)
- Daiichi Sankyo Inc, Baskin Ridge, NJ
| | - Ehab A. El-Gabry
- Roche Tissue Diagnostics, Indianapolis, IN
- Akoya Biosciences, Marlborough, MA
| | | | | | - Lisa M. McShane
- National Institutes of Health/National Cancer Institute, Bethesda, MD
| | | | - Reena Philip
- United States Food and Drug Administration, Silver Spring, MD
| | | | - Jason N. Rosenbaum
- Kaiser Permanente Northern California Regional Genetics Laboratory, San Jose, CA
| | | | - Lisa Schlager
- FORCE: Facing Our Risk of Cancer Empowered, Tampa, FL
| | | | | | - Janis M. Taube
- Johns Hopkins Bloomberg-Kimmel Institute for Cancer Immunotherapy, Baltimore, MD
| | - Magdalena Thurin
- National Institutes of Health/National Cancer Institute, Bethesda, MD
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16
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Olaku O, Conley BA, Ivy SP, McShane LM, Staudt LM, King SM, Sansevere M, Kim B, White JD. Survey of Lifestyle, Past Medical History and Complementary and Alternative Medicine Use Among Adult Patients Participating in the National Cancer Institute's Exceptional Responders Initiative. Transl Oncol 2022; 25:101484. [PMID: 35944413 PMCID: PMC9365974 DOI: 10.1016/j.tranon.2022.101484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 07/01/2022] [Accepted: 07/06/2022] [Indexed: 11/28/2022] Open
Abstract
Fifty percent of exceptional responders changed diet after cancer diagnosis. Forty percent of exceptional responders changed level of physical activity after cancer diagnosis Sixty percent of subjects reported using complementary and alternative approaches during exceptional response period Complementary and alternative medicine users generally used multiple interventions
Introduction The Exceptional Responders Initiative (ERI) at the National Cancer Institute attempts to correlate unusually good outcomes in patients with cancer with genetic targets in tumors and the therapies the patients received. It is not known if other factors might contribute to exceptional responses or outcomes. We explored aspects of the medical history, lifestyle changes, complementary and alternative medicine (CAM) use and communication between health care practitioners and patients who experienced an exceptional response following cancer treatment. Methods All subjects whose case was submitted to the ERI were eligible to participate in the survey. A 121-question survey questionnaire was developed to assess aspects of the subject's past medical history, lifestyle (e.g., diet, exercise, spirituality) and use of CAM. Results Thirty subjects completed and returned the questionnaire from approximately 88 patients invited to participate (approximate response rate = 34%). Approximately 68% were female and 32% were male. Fifty percent of subjects changed their diet after their cancer diagnosis. Eighteen patients (60%) reported using a CAM therapy (not including oral vitamins/minerals or spiritual practices) during their Exceptional Response (ER). Conclusion Multiple factors, including features of the tumor itself, the patient, or the environment, could affect tumor response or patient survival, either solely or in combination with the treatments received. Many patients use other medications, change their diet or physical activity or use CAM interventions after their cancer diagnosis. Investigators attempting to understand the exceptional response phenomenon should acquire rich data sets of their subjects that include information about these factors.
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Affiliation(s)
- Oluwadamilola Olaku
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, 9609 Medical Center Drive, Bethesda, MD 20892, USA.
| | - Barbara A Conley
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, 9609 Medical Center Drive, Bethesda, MD 20892, USA.
| | - S Percy Ivy
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, 9609 Medical Center Drive, Bethesda, MD 20892, USA.
| | - Lisa M McShane
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, 9609 Medical Center Drive, Bethesda, MD 20892, USA.
| | - Louis M Staudt
- Center for Cancer Genomics, National Cancer Institute, NIH, 31 Center Drive, Bethesda, MD 20892, USA.
| | - Sophie M King
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, 9609 Medical Center Drive, Bethesda, MD 20892, USA.
| | - Megan Sansevere
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, 9609 Medical Center Drive, Bethesda, MD 20892, USA.
| | - Benjamin Kim
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, 9609 Medical Center Drive, Bethesda, MD 20892, USA.
| | - Jeffrey D White
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, 9609 Medical Center Drive, Bethesda, MD 20892, USA.
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17
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Bedard PL, Li S, Wisinski KB, Yang ES, Limaye SA, Mitchell EP, Zwiebel JA, Moscow JA, Gray RJ, Wang V, McShane LM, Rubinstein LV, Patton DR, Williams PM, Hamilton SR, Conley BA, Arteaga CL, Harris LN, O'Dwyer PJ, Chen AP, Flaherty KT. Phase II Study of Afatinib in Patients With Tumors With Human Epidermal Growth Factor Receptor 2-Activating Mutations: Results From the National Cancer Institute-Molecular Analysis for Therapy Choice ECOG-ACRIN Trial (EAY131) Subprotocol EAY131-B. JCO Precis Oncol 2022; 6:e2200165. [PMID: 35939768 PMCID: PMC9384949 DOI: 10.1200/po.22.00165] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 03/31/2022] [Accepted: 06/14/2022] [Indexed: 01/14/2023] Open
Abstract
PURPOSE National Cancer Institute-Molecular Analysis for Therapy Choice is a multicohort trial that assigns patients with advanced cancers to targeted therapies on the basis of central tumor genomic testing. Arm B evaluated afatinib, an ErbB family tyrosine kinase inhibitor, in patients with ERBB2-activating mutations. METHODS Eligible patients had selected ERBB2 single-nucleotide variants or insertions/deletions detected by the National Cancer Institute-Molecular Analysis for Therapy Choice next-generation sequencing assay. Patients had performance status ≤ 1, left ventricular ejection fraction > 50%, grade ≤ 1 diarrhea, and no prior human epidermal growth factor receptor 2 (HER2) therapy. Patients received afatinib 40 mg once daily in 28-day cycles. The primary end point was objective response rate (ORR). Secondary end points were 6-month progression-free survival, overall survival, toxicity, and molecular correlates. RESULTS A total of 59 patients were assigned and 40 were enrolled. The median age was 62 years, 78% were female, 68% had performance status = 1, and 58% had received > 3 prior therapies. The confirmed ORR was 2.7% (n = 1 of 37; 90% CI, 0.14 to 12.2), and 6-month progression-free survival was 12.0% (90% CI, 5.6 to 25.8). A confirmed partial response occurred in a patient with adenocarcinoma of extra-mammary Paget disease of skin who progressed after cycle 6. Two unconfirmed partial responses were observed (low-grade serous gynecological tract and estrogen receptor-positive/HER2-negative immunohistochemistry breast ductal carcinoma). Of 12 patients with breast cancer, 1 additional patient with lobular carcinoma (estrogen receptor-positive/HER2 fluorescent in situ hybridization) had a 51% reduction in target lesions but progressed because of a new lesion at cycle 6. The most common (> 20%) treatment-related adverse events were diarrhea (68%), mucositis (43%), fatigue (40%), acneiform rash (30%), dehydration (27%), vomiting (27%), nausea (27%), anemia (27%), and anorexia (22%). Four patients (11%) discontinued because of adverse events. CONCLUSION Although afatinib did not meet the prespecified threshold for antitumor activity in this heavily pretreated cohort, the response in a rare tumor type is notable. The safety profile of afatinib was consistent with prior studies.
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Affiliation(s)
| | - Shuli Li
- E-A Biostatistical Center, Boston, MA
| | | | - Eddy S. Yang
- University of Alabama-Birmingham, Birmingham, AL
| | | | | | - James A. Zwiebel
- Investigational Drug Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Jeffrey A. Moscow
- Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Robert J. Gray
- Dana Farber Cancer Institute—ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Victoria Wang
- Dana Farber Cancer Institute—ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Lisa M. McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Larry V. Rubinstein
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - David R. Patton
- Center for Biomedical Informatics & Information Technology, National Cancer Institute, Bethesda, MD
| | | | | | - Barbara A. Conley
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Lyndsay N. Harris
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Alice P. Chen
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
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18
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Henry NL, Somerfield MR, Dayao Z, Elias A, Kalinsky K, McShane LM, Moy B, Park BH, Shanahan KM, Sharma P, Shatsky R, Stringer-Reasor E, Telli M, Turner NC, DeMichele A. Biomarkers for Systemic Therapy in Metastatic Breast Cancer: ASCO Guideline Update. J Clin Oncol 2022; 40:3205-3221. [PMID: 35759724 DOI: 10.1200/jco.22.01063] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
PURPOSE To update the ASCO biomarkers to guide systemic therapy for metastatic breast cancer (MBC) guideline. METHODS An Expert Panel conducted a systematic review to identify randomized clinical trials and prospective-retrospective studies from January 2015 to January 2022. RESULTS The search identified 19 studies informing the evidence base. RECOMMENDATIONS Candidates for a regimen with a phosphatidylinositol 3-kinase inhibitor and hormonal therapy should undergo testing for PIK3CA mutations using next-generation sequencing of tumor tissue or circulating tumor DNA (ctDNA) in plasma to determine eligibility for alpelisib plus fulvestrant. If no mutation is found in ctDNA, testing in tumor tissue, if available, should be used. Patients who are candidates for poly (ADP-ribose) polymerase (PARP) inhibitor therapy should undergo testing for germline BRCA1 and BRCA2 pathogenic or likely pathogenic mutations to determine eligibility for a PARP inhibitor. There is insufficient evidence for or against testing for a germline PALB2 pathogenic variant to determine eligibility for PARP inhibitor therapy in the metastatic setting. Candidates for immune checkpoint inhibitor therapy should undergo testing for expression of programmed cell death ligand-1 in the tumor and immune cells to determine eligibility for treatment with pembrolizumab plus chemotherapy. Candidates for an immune checkpoint inhibitor should also undergo testing for deficient mismatch repair/microsatellite instability-high to determine eligibility for dostarlimab-gxly or pembrolizumab, as well as testing for tumor mutational burden. Clinicians may test for NTRK fusions to determine eligibility for TRK inhibitors. There are insufficient data to recommend routine testing of tumors for ESR1 mutations, for homologous recombination deficiency, or for TROP2 expression to guide MBC therapy selection. There are insufficient data to recommend routine use of ctDNA or circulating tumor cells to monitor response to therapy among patients with MBC.Additional information can be found at www.asco.org/breast-cancer-guidelines.
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Affiliation(s)
| | | | | | | | - Kevin Kalinsky
- Winship Cancer Institute at Emory University, Atlanta, GA
| | | | | | - Ben Ho Park
- Vanderbilt-Ingram Cancer Center, Nashville, TN
| | | | | | - Rebecca Shatsky
- University of California, San Diego School of Medicine, La Jolla, CA
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Subbiah V, Fengmin F, Kudchadkar R, Sullivan RJ, Mitchell EP, Wright JJ, Chen HX, Gray RJ, Wang XV, McShane LM, Rubinstein LV, Patton D, Williams PM, Sundaresan TK, Conley BA, Arteaga CL, Harris LN, O'Dwyer PJ, Chen AP, Flaherty KT. Abstract CT160: BVD-523FB (Ulixertinib) in Patients with Tumors with BRAF Fusions, or with Non-V600E, Non-V600K BRAF Mutations: Results from the NCI-MATCH ECOG-ACRIN Trial (EAY131) Sub-protocol EAY131-Z1L. Cancer Res 2022. [DOI: 10.1158/1538-7445.am2022-ct160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Purpose: Mutations in BRAF at codons other than V600 (non-V600) and BRAF fusions confer dependence on RAF-MEK-ERK pathway. BVD-523FB (ulixertinib) is a small molecule that potently inhibits both ERK1 and ERK2 protein kinases in the sub-nanomolar range. Based on the reports of early clinical activity in the phase 1 trial, including in non-V600 BRAF mutations, subprotocol Z1L (EAY131-Z1L) sought to investigate the clinical activity of ulixertinib in patients with tumors harboring these alterations. Methods: In this single-arm study, patients with BRAF non-V600 mutation or BRAF fusion were given ulixertinib orally at a dose of 600 mg twice daily, continuously for each 28-day cycle until progression or intolerability. The primary endpoint was objective response rate (ORR). Secondary endpoints included progression-free survival (PFS), 6-month PFS, and overall survival (OS). BRAF mutation status was determined by an analytically validated assay in a CLIA-certified laboratory for all patients. Results: From August 2019 to July 2020, 35 patients were enrolled and received protocol treatment on the trial. Among the 34 patients who were eligible, median age was 66.5; 50% were female, 88% were white, 9% black, 1% Asian. Performance status was ECOG PS 1 in 74% of patients, with remaining PS 0. Median number of prior therapies was >3.Tumor types included multiple gastrointestinal malignancies (N=16), lung cancer (N=3), and melanoma (N=3), among others. Mutations were centrally confirmed in 26 patients who were deemed analyzable per protocol. Twenty-two patients had a single nucleotide variant (SNV) in BRAF; one patient had an insertion/deletion (indel) in BRAF, and three patients harbored BRAF fusions. No patients achieved CR or PR, resulting in ORR = 0%. Stable disease was the best response in 7/26 centrally confirmed cases. Median PFS was 1.8 months (90% CI: 1.6, 2.2), 6-month PFS rate was 11% (90% CI: 4%, 22%), and median OS was 4.0 months (90% CI: 2.8, 7.4). Twenty patients (57%) had grade 3 toxicities, and one patient (3%) had grade 4 toxicity; there were no grade 5 toxicities. Most common toxicities include anemia (n=11), diarrhea (n=16), nausea (n=16), vomiting (n=11), fatigue (n=16), increased creatinine (n=12), and acneiform rash (n=14). Conclusion: BVD-523FB (ulixertinib) had no demonstrable evidence of clinical activity in this small, heavily pre-treated population of patients with tumors harboring BRAF fusions, or with non-V600E, non-V600K BRAF mutations
Citation Format: Vivek Subbiah, Fengmin Fengmin, Ragini Kudchadkar, Ryan J. Sullivan, Edith P. Mitchell, John J. Wright, Helen X. Chen, Robert J. Gray, Xin Victoria Wang, Lisa M. McShane, Larry V. Rubinstein, David Patton, P. Mickey Williams, Tilak K. Sundaresan, Barbara A. Conley, Carlos L. Arteaga, Lyndsay N. Harris, Peter J. O'Dwyer, Alice P. Chen, Keith T. Flaherty. BVD-523FB (Ulixertinib) in Patients with Tumors with BRAF Fusions, or with Non-V600E, Non-V600K BRAF Mutations: Results from the NCI-MATCH ECOG-ACRIN Trial (EAY131) Sub-protocol EAY131-Z1L [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr CT160.
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Affiliation(s)
| | | | | | | | | | | | | | - Robert J. Gray
- 8Dana Farber Cancer Institute – ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Xin Victoria Wang
- 8Dana Farber Cancer Institute – ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Lisa M. McShane
- 9Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Houston, TX
| | - Larry V. Rubinstein
- 10Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Besthesda, MD
| | - David Patton
- 11Center for Biomedical Informatics & Information Technology, National Cancer Institute, Bethesda, MD
| | | | | | - Barbara A. Conley
- 14Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Lyndsay N. Harris
- 14Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Alice P. Chen
- 17Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
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20
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Damodaran S, Zhao F, Deming DA, Mitchell EP, Wright JJ, Gray RJ, Wang V, McShane LM, Rubinstein LV, Patton DR, Williams PM, Hamilton SR, Suga JM, Conley BA, Arteaga CL, Harris LN, O'Dwyer PJ, Chen AP, Flaherty KT. Phase II Study of Copanlisib in Patients With Tumors With PIK3CA Mutations: Results From the NCI-MATCH ECOG-ACRIN Trial (EAY131) Subprotocol Z1F. J Clin Oncol 2022; 40:1552-1561. [PMID: 35133871 PMCID: PMC9084438 DOI: 10.1200/jco.21.01648] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 11/15/2021] [Accepted: 01/06/2022] [Indexed: 01/14/2023] Open
Abstract
PURPOSE Activating mutations in PIK3CA are observed across multiple tumor types. The NCI-MATCH (EAY131) is a tumor-agnostic platform trial that enrolls patients to targeted therapies on the basis of matching genomic alterations. Arm Z1F evaluated copanlisib, an α and δ isoform-specific phosphoinositide 3-kinase (PI3K) inhibitor, in patients with PIK3CA mutations (with or without PTEN loss). PATIENTS AND METHODS Patients received copanlisib (60 mg intravenous) once weekly on days 1, 8, and 15 in 28-day cycles until progression or toxicity. Patients with KRAS mutations, human epidermal growth factor receptor 2-positive breast cancers, and lymphomas were excluded. The primary end point was centrally assessed objective response rate (ORR); secondary end points included progression-free survival, 6-month progression-free survival, and overall survival. RESULTS Thirty-five patients were enrolled, and 25 patients were included in the primary efficacy analysis as prespecified in the Protocol. Multiple histologies were enrolled, with gynecologic (n = 6) and gastrointestinal (n = 6) being the most common. Sixty-eight percent of patients had ≥ 3 lines of prior therapy. The ORR was 16% (4 of 25, 90% CI, 6 to 33) with P = .0341 against a null rate of 5%. The most common reason for protocol discontinuation was disease progression (n = 17, 68%). Grade 3/4 toxicities observed were consistent with reported toxicities for PI3K pathway inhibition. Sixteen patients (53%) had grade 3 toxicities, and one patient (3%) had grade 4 toxicity (CTCAE v5.0). Most common toxicities include hyperglycemia (n = 19), fatigue (n = 12), diarrhea (n = 11), hypertension (n = 10), and nausea (n = 10). CONCLUSION The study met its primary end point with an ORR of 16% (P = .0341) with copanlisib showing clinical activity in select tumors with PIK3CA mutation in the refractory setting.
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Affiliation(s)
| | - Fengmin Zhao
- Dana-Farber Cancer Institute-ECOG-ACRIN Biostatistics Center, Boston, MA
| | | | - Edith P. Mitchell
- Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA
| | - John J. Wright
- Investigational Drug Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Robert J. Gray
- Dana-Farber Cancer Institute-ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Victoria Wang
- Dana-Farber Cancer Institute-ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Lisa M. McShane
- Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Larry V. Rubinstein
- Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - David R. Patton
- National Cancer Institute/Center for Biomedical Informatics & Information Technology, Rockville, MD
| | - P. Mickey Williams
- Molecular Characterization Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD
| | | | | | - Barbara A. Conley
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Lyndsay N. Harris
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Peter J. O'Dwyer
- University of Pennsylvania Abramson Cancer Center, Division of Medical Oncology, Philadelphia, PA
| | - Alice P. Chen
- Developmental Therapeutics Clinic/Early Clinical Trials Development Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Keith T. Flaherty
- Dana-Farber Cancer Institute/Harvard Medical School/Massachusetts General Hospital, Boston, MA
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21
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Sankaran H, Negi S, McShane LM, Zhao Y, Krushkal J. Pharmacogenomics of in vitro response of the NCI-60 cancer cell line panel to Indian natural products. BMC Cancer 2022; 22:512. [PMID: 35525914 PMCID: PMC9077913 DOI: 10.1186/s12885-022-09580-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 04/20/2022] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Indian natural products have been anecdotally used for cancer treatment but with limited efficacy. To better understand their mechanism, we examined the publicly available data for the activity of Indian natural products in the NCI-60 cell line panel. METHODS We examined associations of molecular genomic features in the well-characterized NCI-60 cancer cell line panel with in vitro response to treatment with 75 compounds derived from Indian plant-based natural products. We analyzed expression measures for annotated transcripts, lncRNAs, and miRNAs, and protein-changing single nucleotide variants in cancer-related genes. We also examined the similarities between cancer cell line response to Indian natural products and response to reference anti-tumor compounds recorded in a U.S. National Cancer Institute (NCI) Developmental Therapeutics Program database. RESULTS Hierarchical clustering based on cell line response measures identified clustering of Phyllanthus and cucurbitacin products with known anti-tumor agents with anti-mitotic mechanisms of action. Curcumin and curcuminoids mostly clustered together. We found associations of response to Indian natural products with expression of multiple genes, notably including SLC7A11 involved in solute transport and ATAD3A and ATAD3B encoding mitochondrial ATPase proteins, as well as significant associations with functional single nucleotide variants, including BRAF V600E. CONCLUSION These findings suggest potential mechanisms of action and novel associations of in vitro response with gene expression and some cancer-related mutations that increase our understanding of these Indian natural products.
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Affiliation(s)
- Hari Sankaran
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, MD, 20850, USA.
| | - Simarjeet Negi
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, MD, 20850, USA
| | - Lisa M McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, MD, 20850, USA
| | - Yingdong Zhao
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, MD, 20850, USA
| | - Julia Krushkal
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, MD, 20850, USA.
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22
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Dobbin KK, McShane LM. Sample size methods for evaluation of predictive biomarkers. Stat Med 2022; 41:3199-3210. [DOI: 10.1002/sim.9412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 03/24/2022] [Accepted: 04/02/2022] [Indexed: 11/09/2022]
Affiliation(s)
- Kevin K. Dobbin
- Department of Epidemiology and Biostatistics University of Georgia Athens Georgia USA
| | - Lisa M. McShane
- Biometric Research Program National Cancer Institute Bethesda Maryland USA
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Affiliation(s)
- Daniel L Hertz
- Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, MI
| | - Lisa M McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Daniel F Hayes
- Stuart B. Padnos Professor of Breast Cancer Research, University of Michigan Rogel Cancer Center, Ann Arbor, MI
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Krop IE, Jegede OA, Grilley-Olson JE, Lauring JD, Mitchell EP, Zwiebel JA, Gray RJ, Wang V, McShane LM, Rubinstein LV, Patton D, Williams PM, Hamilton SR, Kono SA, Ford JM, Garcia AA, Sui XD, Siegel RD, Slomovitz BM, Conley BA, Arteaga CL, Harris LN, O'Dwyer PJ, Chen AP, Flaherty KT. Phase II Study of Taselisib in PIK3CA-Mutated Solid Tumors Other Than Breast and Squamous Lung Cancer: Results From the NCI-MATCH ECOG-ACRIN Trial (EAY131) Subprotocol I. JCO Precis Oncol 2022; 6:e2100424. [PMID: 35138919 PMCID: PMC8865530 DOI: 10.1200/po.21.00424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 11/12/2021] [Accepted: 01/05/2022] [Indexed: 01/14/2023] Open
Abstract
PURPOSE PIK3CA mutations frequently contribute to oncogenesis in solid tumors. Taselisib, a potent and selective inhibitor of phosphoinositide 3-kinase, has demonstrated clinical activity in PIK3CA-mutant breast cancer. Whether PIK3CA mutations predict sensitivity to taselisib in other cancer types is unknown. National Cancer Institute-Molecular Analysis for Therapy Choice Arm EAY131-I is a single-arm, phase II study of the safety and efficacy of taselisib in patients with advanced cancers. METHODS Eligible patients had tumors with an activating PIK3CA mutation. Patients with breast or squamous cell lung carcinoma, or whose cancer had KRAS or PTEN mutations, were excluded. Patients received taselisib 4 mg, orally once daily continuously, until disease progression or unacceptable toxicity. The primary end point was objective response rate. Secondary end points included progression-free survival (PFS), 6-month PFS, overall survival (OS), and identification of predictive biomarkers. RESULTS Seventy patients were enrolled, and 61 were eligible and initiated protocol therapy. Types of PIK3CA mutations included helical 41 of 61 (67%), kinase 11 of 61 (18%), and other 9 of 61 (15%). With a median follow-up of 35.7 months, there were no complete or partial responses. Six-month PFS was 19.9% (90% CI, 12.0 to 29.3) and median PFS was 3.1 months (90% CI, 1.8 to 3.7). Six-month OS was 60.7% (90% CI, 49.6 to 70.0) and median OS was 7.2 months (90% CI, 5.9 to 10.0). Individual comutations were too heterogeneous to correlate with clinical outcome. Fatigue, diarrhea, nausea, and hyperglycemia were the most common toxicities, and most were grade 1 and 2. CONCLUSION In this study, taselisib monotherapy had very limited activity in a heterogeneous cohort of heavily pretreated cancer patients with PIK3CA-mutated tumors; the presence of a PIK3CA mutation alone does not appear to be a sufficient predictor of taselisib activity.
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Affiliation(s)
- Ian E. Krop
- Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Opeyemi A. Jegede
- Dana-Farber Cancer Institute, ECOG-ACRIN Biostatistics Center, Boston, MA
| | | | | | | | | | - Robert J. Gray
- Dana-Farber Cancer Institute, ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Victoria Wang
- Dana-Farber Cancer Institute, ECOG-ACRIN Biostatistics Center, Boston, MA
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Vega DM, Yee LM, McShane LM, Williams PM, Chen L, Vilimas T, Fabrizio D, Funari V, Newberg J, Bruce LK, Chen SJ, Baden J, Carl Barrett J, Beer P, Butler M, Cheng JH, Conroy J, Cyanam D, Eyring K, Garcia E, Green G, Gregersen VR, Hellmann MD, Keefer LA, Lasiter L, Lazar AJ, Li MC, MacConaill LE, Meier K, Mellert H, Pabla S, Pallavajjalla A, Pestano G, Salgado R, Samara R, Sokol ES, Stafford P, Budczies J, Stenzinger A, Tom W, Valkenburg KC, Wang XZ, Weigman V, Xie M, Xie Q, Zehir A, Zhao C, Zhao Y, Stewart MD, Allen J. Aligning tumor mutational burden (TMB) quantification across diagnostic platforms: phase II of the Friends of Cancer Research TMB Harmonization Project. Ann Oncol 2021; 32:1626-1636. [PMID: 34606929 DOI: 10.1016/j.annonc.2021.09.016] [Citation(s) in RCA: 72] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Revised: 09/21/2021] [Accepted: 09/26/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Tumor mutational burden (TMB) measurements aid in identifying patients who are likely to benefit from immunotherapy; however, there is empirical variability across panel assays and factors contributing to this variability have not been comprehensively investigated. Identifying sources of variability can help facilitate comparability across different panel assays, which may aid in broader adoption of panel assays and development of clinical applications. MATERIALS AND METHODS Twenty-nine tumor samples and 10 human-derived cell lines were processed and distributed to 16 laboratories; each used their own bioinformatics pipelines to calculate TMB and compare to whole exome results. Additionally, theoretical positive percent agreement (PPA) and negative percent agreement (NPA) of TMB were estimated. The impact of filtering pathogenic and germline variants on TMB estimates was assessed. Calibration curves specific to each panel assay were developed to facilitate translation of panel TMB values to whole exome sequencing (WES) TMB values. RESULTS Panel sizes >667 Kb are necessary to maintain adequate PPA and NPA for calling TMB high versus TMB low across the range of cut-offs used in practice. Failure to filter out pathogenic variants when estimating panel TMB resulted in overestimating TMB relative to WES for all assays. Filtering out potential germline variants at >0% population minor allele frequency resulted in the strongest correlation to WES TMB. Application of a calibration approach derived from The Cancer Genome Atlas data, tailored to each panel assay, reduced the spread of panel TMB values around the WES TMB as reflected in lower root mean squared error (RMSE) for 26/29 (90%) of the clinical samples. CONCLUSIONS Estimation of TMB varies across different panels, with panel size, gene content, and bioinformatics pipelines contributing to empirical variability. Statistical calibration can achieve more consistent results across panels and allows for comparison of TMB values across various panel assays. To promote reproducibility and comparability across assays, a software tool was developed and made publicly available.
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Affiliation(s)
- D M Vega
- Friends of Cancer Research, Washington, USA
| | - L M Yee
- National Cancer Institute, Bethesda, USA
| | | | - P M Williams
- Molecular Characterization Laboratory, Frederick National Lab for Cancer Research, Leidos Biomedical Research Inc., Frederick, USA
| | - L Chen
- Molecular Characterization Laboratory, Frederick National Lab for Cancer Research, Leidos Biomedical Research Inc., Frederick, USA
| | - T Vilimas
- Molecular Characterization Laboratory, Frederick National Lab for Cancer Research, Leidos Biomedical Research Inc., Frederick, USA
| | - D Fabrizio
- Foundation Medicine Inc., Cambridge, USA
| | - V Funari
- NeoGenomics Laboratories, Aliso Viejo, USA
| | - J Newberg
- Foundation Medicine Inc., Cambridge, USA
| | - L K Bruce
- NeoGenomics Laboratories, Aliso Viejo, USA
| | | | - J Baden
- Bristol Myers Squibb Co., Princeton, USA
| | | | - P Beer
- European Organisation for Research and Treatment of Cancer, Brussels, Belgium
| | - M Butler
- LGC Clinical Diagnostics, Gaithersburg, USA
| | | | | | - D Cyanam
- Clinical Sequencing Division, Thermo Fisher Scientific, Ann Arbor, USA
| | - K Eyring
- Intermountain Precision Genomics, St. George, USA
| | - E Garcia
- Brigham and Women's Hospital, Boston, USA
| | - G Green
- Bristol Myers Squibb Co., Princeton, USA
| | | | - M D Hellmann
- Memorial Sloan Kettering Cancer Center, New York, USA
| | - L A Keefer
- Personal Genome Diagnostics, Baltimore, USA
| | - L Lasiter
- Friends of Cancer Research, Washington, USA
| | - A J Lazar
- The University of Texas MD Anderson Cancer Center, Houston, USA
| | - M-C Li
- National Cancer Institute, Bethesda, USA
| | | | - K Meier
- Illumina Inc, Clinical Genomics, San Diego, USA
| | | | | | | | | | - R Salgado
- European Organisation for Research and Treatment of Cancer, Brussels, Belgium
| | | | - E S Sokol
- Foundation Medicine Inc., Cambridge, USA
| | | | - J Budczies
- Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany
| | - A Stenzinger
- Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany
| | - W Tom
- Clinical Sequencing Division, Thermo Fisher Scientific, Ann Arbor, USA
| | | | - X Z Wang
- EMD Serono Research and Development Institute, Inc., Billerica, USA
| | | | - M Xie
- AstraZeneca Pharmaceuticals LP, Waltham, USA
| | - Q Xie
- General Dynamics Information Technology, Inc., Columbia, USA
| | - A Zehir
- Memorial Sloan Kettering Cancer Center, New York, USA
| | - C Zhao
- Illumina Inc, Clinical Genomics, San Diego, USA
| | - Y Zhao
- National Cancer Institute, Bethesda, USA
| | - M D Stewart
- Friends of Cancer Research, Washington, USA.
| | - J Allen
- Friends of Cancer Research, Washington, USA
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Mita AC, Wei Z, Mayer IA, Cheng H, Mitchell EP, Wright JJ, Ivy P, Gray RJ, Wang V, McShane LM, Rubinstein LV, Patton DR, Williams M, Hamilton SR, Conley BA, Arteaga CL, Harris LN, O'Dwyer PJ, Chen AP, Flaherty KT. Abstract LBA003: Erdafitinib in patients with tumors harboring FGFR gene mutations or fusions: Results from the NCI-MATCH ECOG-ACRIN Trial (EAY131) Sub-protocol K2. Mol Cancer Ther 2021. [DOI: 10.1158/1535-7163.targ-21-lba003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: The NCI-MATCH precision medicine trial assigns patients (pts) with solid tumors, lymphoma, or multiple myeloma whose cancers have progressed on prior treatment to a targeted therapy based on genetic alterations identified in pre-treatment biopsies. Arm K2 (EAY131-K2) evaluated the pan-FGFR inhibitor erdafitinib (E) in pts with FGFR mutations or fusions. Patients and methods: Pts with bladder or urothelial cancers were excluded. Pts received E 8 mg PO daily (28-day cycle) until disease progression or unacceptable toxicity; dose reduction for toxicities was allowed; imaging was performed every 2 cycles. The primary endpoint was objective response rate (ORR); secondary endpoints included progression-free survival (PFS), 6-month PFS, and overall survival (OS). Results: A total of 35 pts were enrolled to this arm from 07/2018-07/2019; one was ineligible and one did not receive treatment. Nine distinct tumor histologies were represented, most common being pancreatobiliary (11), CNS (7) and gynecological tumors (5). 73% of pts were female, with median age of 59y (range 26-83y), 70% were Caucasian, and 61% of pts had received at least 3 prior therapies (range 0-22). Alterations in FGFR1, FGFR2 and FGFR3 were recorded in 6, 18, and 9 evaluable pts, respectively. 18 pt tumors had fusions and 15 had mutations in an FGFR gene. The confirmed ORR was 12% (90% CI 4%, 26%), with a median duration of response (DoR) of 7.3 months (mo), range 4.2-11.7 mo. Responses were seen in cholangiocarcinoma (2 pts), Brenner ovarian tumor and adenoid cystic carcinoma (1 pt each). Two (50%) of these 4 tumors harbored FGFR fusions and 2 FGFR mutations. 13 pts had stable disease (SD). Median PFS was 3.9 mo, and 6-mo PFS was 32.8% (90% CI 21.2%, 50.6%). Median OS was 11.0 mo. Of the 6 pts with intrahepatic cholangiocarcinoma, 2 had PR and 2 SD. The most frequent grade 3 treatment-related AEs were oral mucositis/pain (5 pts), paronychia, electrolyte disorders, and anemia/lymphopenia (2 pts each). There were no treatment-related grade 4-5 toxicities. Toxicities were reversible and manageable with E dose interruptions and/or dose reduction. Conclusions: In this pre-treated, mixed histology cohort with tumors harboring FGFR somatic alterations, E showed activity with durable responses and disease stabilizations outside of currently approved FDA indications, although the pre-specified criterion that the primary endpoint, ORR, be significantly greater than 16% was not reached. Toxicities were consistent with E safety profile. Responses were observed in tumors harboring FGFR fusions as well as in those with mutations of FGFR; further correlative analyses are planned.
Citation Format: Alain C Mita, Zihan Wei, Ingrid A Mayer, Heather Cheng, Edith P Mitchell, John J Wright, Percy Ivy, Robert J Gray, Victoria Wang, Lisa M McShane, Larry V Rubinstein, David R Patton, Mickey Williams, Stanley R Hamilton, Barbara A Conley, Carlos L Arteaga, Lyndsay N Harris, Peter J O'Dwyer, Alice P Chen, Keith T Flaherty. Erdafitinib in patients with tumors harboring FGFR gene mutations or fusions: Results from the NCI-MATCH ECOG-ACRIN Trial (EAY131) Sub-protocol K2 [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr LBA003.
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Affiliation(s)
| | - Zihan Wei
- 2Dana-Farber Cancer Institute, Boston, MA,
| | - Ingrid A Mayer
- 3Vanderbilt University Medical Center/Vanderbilt-Ingram Cancer Center, Nashville, TN,
| | | | | | | | - Percy Ivy
- 6National Cancer Institute, Bethesda, MD,
| | | | | | | | | | | | | | | | | | | | | | - Peter J O'Dwyer
- 10University of Pennsylvania Medical Center, Philadelphia, PA,
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27
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Merino DM, McShane LM, Fabrizio D, Funari V, Chen SJ, White JR, Wenz P, Baden J, Barrett JC, Chaudhary R, Chen L, Chen WS, Cheng JH, Cyanam D, Dickey JS, Gupta V, Hellmann M, Helman E, Li Y, Maas J, Papin A, Patidar R, Quinn KJ, Rizvi N, Tae H, Ward C, Xie M, Zehir A, Zhao C, Dietel M, Stenzinger A, Stewart M, Allen J. Establishing guidelines to harmonize tumor mutational burden (TMB): in silico assessment of variation in TMB quantification across diagnostic platforms: phase I of the Friends of Cancer Research TMB Harmonization Project. J Immunother Cancer 2021; 8:jitc-2019-000147. [PMID: 32217756 PMCID: PMC7174078 DOI: 10.1136/jitc-2019-000147] [Citation(s) in RCA: 281] [Impact Index Per Article: 93.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/11/2020] [Indexed: 12/13/2022] Open
Abstract
Background Tumor mutational burden (TMB), defined as the number of somatic mutations per megabase of interrogated genomic sequence, demonstrates predictive biomarker potential for the identification of patients with cancer most likely to respond to immune checkpoint inhibitors. TMB is optimally calculated by whole exome sequencing (WES), but next-generation sequencing targeted panels provide TMB estimates in a time-effective and cost-effective manner. However, differences in panel size and gene coverage, in addition to the underlying bioinformatics pipelines, are known drivers of variability in TMB estimates across laboratories. By directly comparing panel-based TMB estimates from participating laboratories, this study aims to characterize the theoretical variability of panel-based TMB estimates, and provides guidelines on TMB reporting, analytic validation requirements and reference standard alignment in order to maintain consistency of TMB estimation across platforms. Methods Eleven laboratories used WES data from The Cancer Genome Atlas Multi-Center Mutation calling in Multiple Cancers (MC3) samples and calculated TMB from the subset of the exome restricted to the genes covered by their targeted panel using their own bioinformatics pipeline (panel TMB). A reference TMB value was calculated from the entire exome using a uniform bioinformatics pipeline all members agreed on (WES TMB). Linear regression analyses were performed to investigate the relationship between WES and panel TMB for all 32 cancer types combined and separately. Variability in panel TMB values at various WES TMB values was also quantified using 95% prediction limits. Results Study results demonstrated that variability within and between panel TMB values increases as the WES TMB values increase. For each panel, prediction limits based on linear regression analyses that modeled panel TMB as a function of WES TMB were calculated and found to approximately capture the intended 95% of observed panel TMB values. Certain cancer types, such as uterine, bladder and colon cancers exhibited greater variability in panel TMB values, compared with lung and head and neck cancers. Conclusions Increasing uptake of TMB as a predictive biomarker in the clinic creates an urgent need to bring stakeholders together to agree on the harmonization of key aspects of panel-based TMB estimation, such as the standardization of TMB reporting, standardization of analytical validation studies and the alignment of panel-based TMB values with a reference standard. These harmonization efforts should improve consistency and reliability of panel TMB estimates and aid in clinical decision-making.
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Affiliation(s)
| | | | | | | | | | | | - Paul Wenz
- Clinical Genomics, Illumina Inc, San Diego, California, USA
| | | | - J Carl Barrett
- Translational Medicine, Oncology Research and Early Development, AstraZeneca Pharmaceuticals LP, Boston, Massachusetts, USA
| | - Ruchi Chaudhary
- Clinical Sequencing Division, Thermo Fisher Scientific, Ann Arbor, Michigan, USA
| | - Li Chen
- Molecular Characterization Laboratory, Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA
| | | | | | - Dinesh Cyanam
- Clinical Sequencing Division, Thermo Fisher Scientific, Ann Arbor, Michigan, USA
| | | | | | | | - Elena Helman
- Bioinformatics, Guardant Health Inc, Redwood City, California, USA
| | - Yali Li
- Foundation Medicine Inc, Cambridge, Massachusetts, USA
| | - Joerg Maas
- Quality in Pathology (QuIP), Berlin, Germany
| | | | - Rajesh Patidar
- Molecular Characterization Laboratory, Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA
| | - Katie J Quinn
- Bioinformatics, Guardant Health Inc, Redwood City, California, USA
| | - Naiyer Rizvi
- Division of Hematology/Oncology, Department of Medicine, Columbia University, New York, New York, USA
| | | | | | - Mingchao Xie
- AstraZeneca Pharmaceuticals LP, Waltham, Massachusetts, USA
| | - Ahmet Zehir
- Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Chen Zhao
- Clinical Genomics, Illumina Inc, San Diego, California, USA
| | | | - Albrecht Stenzinger
- Institute of Pathology, University Hospital Heidelberg, Heidelberg, Baden-Württemberg, Germany
| | | | - Jeff Allen
- Friends of Cancer Research, Washington, DC, USA
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28
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Li D, Ha MJ, Evrard YA, Chen H, McShane LM, Grover J, Wang J, Fang B, DiPeri T, Lewis MT, Rubinstein L, Roth JA, Chuang JH, Doroshow JH, Moscow JA, Meric-Bernstam F. Abstract 3009: A systematic review of the tumor growth metrics of patient-derived xenograft (PDX) models in the literature and in NCI PDXNet centers. Cancer Res 2021. [DOI: 10.1158/1538-7445.am2021-3009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: Despite increasing utilization of patient-derived xenografts (PDXs) in early drug development, there are no agreed upon metrics for assessment of PDX growth inhibition for agents given alone or in combination. In the present study, we aim to investigate what metrics are being used in the literature, as well as among the National Cancer Institute PDX Development and Trial Centers Research Network (PDXNet) investigators.
Methods: Relevant PDX literature was identified and retrieved using an information retrieval tool, RetriLite, to search for articles that met following criteria: 1) Published between 01/2018 through 12/2019; 2) Published in a journal with impact factor of 10 or above; 3) Search terms included: Cancer, PDX(s), patient derived xenograft(s), and patient-derived xenograft(s). Exclusion criteria included: 1) Brain tumors; 2) Immune-oncology/non-solid tumors; 3) Studies with no detailed information; 4) studies from PDXNet investigators. In addition, a questionnaire regarding PDX analysis practices was distributed to NCI PDXNet investigators and responses were analyzed.
Results: Sixty-five studies with relevant information were included in this systematic literature review and 15 NCI PDXNet PIs from all six centers responded to the survey representing the general practice in the network. The most commonly used tumor growth assessment metric was comparisons in tumor volumes in different treatment arms, used by 33 (51%) of 65 PDX papers and 13 (87%) of 15 PDXNet investigators. Thirteen different growth metrics were reported in the PDX literature and ten different metrics were used by PDXNet investigators. PDXNet investigators were more likely to use growth metrics analogous to clinical endpoints compared to the PDX literature, including percent change of tumor volume (80% vs 17%), event-free survival (EFS: 40% vs 11%), and overall survival (33% vs 8%). PDXNet investigators were also more likely to assess objective response rate (ORR) compared to the PDX literature (60% vs 12%); several different cutoffs were used for defining response and progression. For combination therapy, most investigators and literature compared tumor volumes across treatment arms, with few looking at measures of synergy or dynamic effects and with variable utilization of other metrics such as OR and EFS. In PDX literature, of the 40 papers with combination therapies presented, at least one monotherapy control arm was missing in 7 (18%), and four (10%) only compared growth with the no treatment control arm.
Conclusions: In summary, there is great variability in growth metrics used in the PDX community. To better use PDXs as preclinical models and increase the reproducibility of treatment effect on PDXs, a joint effort is needed to harmonize approaches in PDX growth assessment.
Citation Format: Dali Li, Min Jin Ha, Yvonne A. Evrard, Huiqin Chen, Lisa M. McShane, Jeffrey Grover, Jing Wang, Bingliang Fang, Timothy DiPeri, Michael T. Lewis, Lawrence Rubinstein, Jack A. Roth, Jeffrey H. Chuang, James H. Doroshow, Jeffrey A. Moscow, Funda Meric-Bernstam. A systematic review of the tumor growth metrics of patient-derived xenograft (PDX) models in the literature and in NCI PDXNet centers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3009.
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Affiliation(s)
- Dali Li
- 1MD Anderson Cancer Center, Houston, TX
| | | | | | | | | | | | - Jing Wang
- 1MD Anderson Cancer Center, Houston, TX
| | | | | | | | | | | | - Jeffrey H. Chuang
- 6The Jackson Laboratory for Genomic Medicine, University of Connecticut Health Center, Farmington, CT
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29
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Zhao Y, Li MC, Konaté MM, Chen L, Das B, Karlovich C, Williams PM, Evrard YA, Doroshow JH, McShane LM. TPM, FPKM, or Normalized Counts? A Comparative Study of Quantification Measures for the Analysis of RNA-seq Data from the NCI Patient-Derived Models Repository. J Transl Med 2021; 19:269. [PMID: 34158060 PMCID: PMC8220791 DOI: 10.1186/s12967-021-02936-w] [Citation(s) in RCA: 110] [Impact Index Per Article: 36.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 06/10/2021] [Indexed: 12/18/2022] Open
Abstract
Background In order to correctly decode phenotypic information from RNA-sequencing (RNA-seq) data, careful selection of the RNA-seq quantification measure is critical for inter-sample comparisons and for downstream analyses, such as differential gene expression between two or more conditions. Several methods have been proposed and continue to be used. However, a consensus has not been reached regarding the best gene expression quantification method for RNA-seq data analysis. Methods In the present study, we used replicate samples from each of 20 patient-derived xenograft (PDX) models spanning 15 tumor types, for a total of 61 human tumor xenograft samples available through the NCI patient-derived model repository (PDMR). We compared the reproducibility across replicate samples based on TPM (transcripts per million), FPKM (fragments per kilobase of transcript per million fragments mapped), and normalized counts using coefficient of variation, intraclass correlation coefficient, and cluster analysis. Results Our results revealed that hierarchical clustering on normalized count data tended to group replicate samples from the same PDX model together more accurately than TPM and FPKM data. Furthermore, normalized count data were observed to have the lowest median coefficient of variation (CV), and highest intraclass correlation (ICC) values across all replicate samples from the same model and for the same gene across all PDX models compared to TPM and FPKM data. Conclusion We provided compelling evidence for a preferred quantification measure to conduct downstream analyses of PDX RNA-seq data. To our knowledge, this is the first comparative study of RNA-seq data quantification measures conducted on PDX models, which are known to be inherently more variable than cell line models. Our findings are consistent with what others have shown for human tumors and cell lines and add further support to the thesis that normalized counts are the best choice for the analysis of RNA-seq data across samples. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-021-02936-w.
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Affiliation(s)
- Yingdong Zhao
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, USA
| | - Ming-Chung Li
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, USA
| | - Mariam M Konaté
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, USA
| | - Li Chen
- Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Biswajit Das
- Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Chris Karlovich
- Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - P Mickey Williams
- Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Yvonne A Evrard
- Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - James H Doroshow
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Lisa M McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, USA.
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30
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Jhaveri KL, Wang XV, Makker V, Luoh SW, Mitchell EP, Zwiebel JA, Sharon E, Gray RJ, Li S, McShane LM, Rubinstein LV, Patton D, Williams PM, Hamilton SR, Conley BA, Arteaga CL, Harris LN, O'Dwyer PJ, Chen AP, Flaherty KT. Corrigendum to 'Ado-trastuzumab emtansine (T-DM1) in patients with HER2-amplified tumors excluding breast and gastric/gastroesophageal junction (GEJ) adenocarcinomas: results from the NCI-MATCH trial (EAY131) subprotocol Q': [Annals of Oncology 30 (2019) 1821-1830]. Ann Oncol 2021; 32:1068. [PMID: 34099371 PMCID: PMC8929237 DOI: 10.1016/j.annonc.2021.05.797] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
Affiliation(s)
- K L Jhaveri
- Department of Medicine, Memorial Sloan-Kettering Center, New York, USA.
| | - X V Wang
- Biostatistics, E-A Biostatistical Center, Boston, USA
| | - V Makker
- Gynecologic Medical Oncology Service, Memorial Sloan-Kettering Cancer Center, New York, USA
| | - S-W Luoh
- Knight Cancer Institute, Oregon Health Science University, Portland, USA
| | - E P Mitchell
- Medical Oncology, Thomas Jefferson University, Philadelphia, USA
| | - J A Zwiebel
- Investigational Drug Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, USA
| | - E Sharon
- Medical Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, USA
| | - R J Gray
- Department of Biostatistics, Dana Farber Cancer Institutes, Boston, USA
| | - S Li
- Department of Biostatistics, Dana Farber Cancer Institutes, Boston, USA
| | - L M McShane
- Biometric Research Branch, National Cancer Institute, Bethesda, USA
| | - L V Rubinstein
- Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institute of Health, Bethesda, USA
| | - D Patton
- Center for Biomedical, Informatics & Information Technology, National Cancer Institute, Bethesda, USA
| | - P M Williams
- Molecular Characterization Laboratory, Frederick National Laboratory for Cancer Research, Frederick, USA
| | - S R Hamilton
- Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, USA
| | - B A Conley
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, USA
| | - C L Arteaga
- Department of Internal Medicine, University of Texas Southwestern, Dallas, USA
| | - L N Harris
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, USA
| | - P J O'Dwyer
- University of Pennsylvania, Philadelphia, USA
| | - A P Chen
- CTEP, National Cancer Institute, Bethesda, USA
| | - K T Flaherty
- Cancer Center, Massachusetts General Hospital, Boston, USA
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31
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Cleary JM, Wang V, Heist RS, Kopetz ES, Mitchell EP, Zwiebel JA, Kapner KS, Chen HX, Li S, Gray RJ, McShane LM, Rubinstein LV, Patton DR, Meric-Bernstam F, Dillmon MS, Williams PM, Hamilton SR, Conley BA, Aguirre AJ, O'Dwyer PJ, Harris LN, Arteaga CL, Chen AP, Flaherty KT. Differential Outcomes in Codon 12/13 and Codon 61 NRAS-Mutated Cancers in the Phase II NCI-MATCH Trial of Binimetinib in Patients with NRAS-Mutated Tumors. Clin Cancer Res 2021; 27:2996-3004. [PMID: 33637626 PMCID: PMC8542423 DOI: 10.1158/1078-0432.ccr-21-0066] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 01/11/2021] [Accepted: 02/18/2021] [Indexed: 01/02/2023]
Abstract
PURPOSE Preclinical and clinical data suggest that downstream inhibition with an MEK inhibitor, such as binimetinib, might be efficacious for NRAS-mutated cancers. PATIENTS AND METHODS Patients enrolled in the NCI-MATCH trial master protocol underwent tumor biopsy and molecular profiling by targeted next-generation sequencing. Patients with NRAS-mutated tumors, except melanoma, were enrolled in subprotocol Z1A, a single-arm study evaluating binimetinib 45 mg twice daily. The primary endpoint was objective response rate (ORR). Secondary endpoints included progression-free survival (PFS) and overall survival (OS). A post hoc analysis examined the association of NRAS mutation type with outcome. RESULTS In total, 47 eligible patients with a refractory solid tumor harboring a codon 12, 13, or 61 NRAS mutation were treated. Observed toxicity was moderate, and 30% of patients discontinued treatment because of binimetinib-associated toxicity. The ORR was 2.1% (1/47 patients). A patient with malignant ameloblastoma harboring a codon 61 NRAS mutation achieved a durable partial response (PR). A patient with NRAS codon 61-mutated colorectal cancer had an unconfirmed PR, and two other patients with NRAS codon 61-mutated colorectal had stable disease for at least 12 months. In an exploratory analysis, patients with colorectal cancer bearing a NRAS codon 61 mutation (n = 8) had a significantly longer OS (P = 0.03) and PFS (P = 0.007) than those with codon 12 or 13 mutations (n = 16). CONCLUSIONS Single-agent binimetinib did not show promising efficacy in NRAS-mutated cancers. The observation of increased OS and PFS in patients with codon 61 NRAS-mutated colorectal cancer merits further investigation.
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Affiliation(s)
- James M Cleary
- Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts.
| | | | - Rebecca S Heist
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, Massachusetts
| | - E Scott Kopetz
- University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Edith P Mitchell
- Thomas Jefferson University Hospital, Philadelphia, Pennsylvania
| | - James A Zwiebel
- Investigational Drug Branch, Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | - Kevin S Kapner
- Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - Helen X Chen
- Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | - Shuli Li
- Dana-Farber Cancer Institute, Boston, Massachusetts
| | | | - Lisa M McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | - Larry V Rubinstein
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | - David R Patton
- Center for Biomedical Informatics and Information Technology, NCI, Bethesda, Maryland
| | - Funda Meric-Bernstam
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, Massachusetts
| | | | - P Mickey Williams
- Frederick National Laboratory for Cancer Research, Frederick, Maryland
| | | | - Barbara A Conley
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | - Andrew J Aguirre
- Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | | | - Lyndsay N Harris
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | | | - Alice P Chen
- Division of Cancer Treatment and Diagnosis, NCI, Bethesda, Maryland
| | - Keith T Flaherty
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, Massachusetts
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Hendrix SB, Mogg R, Wang SJ, Chakravarty A, Romero K, Dickson SP, Sauer JM, McShane LM. Perspectives on statistical strategies for the regulatory biomarker qualification process. Biomark Med 2021; 15:669-684. [PMID: 34037457 PMCID: PMC8293027 DOI: 10.2217/bmm-2020-0523] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Qualification of a biomarker for use in a medical product development program requires a statistical strategy that aligns available evidence with the proposed context of use (COU), identifies any data gaps to be filled and plans any additional research required to support the qualification. Accumulating, interpreting and analyzing available data is outlined, step-by-step, illustrated by a qualified enrichment biomarker example and a safety biomarker in the process of qualification. The detailed steps aid requestors seeking qualification of biomarkers, allowing them to organize the available evidence and identify potential gaps. This provides a statistical perspective for assessing evidence that parallels clinical considerations and is intended to guide the overall evaluation of evidentiary criteria to support a specific biomarker COU.
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Affiliation(s)
| | - Robin Mogg
- Bill & Melinda Gates Medical Research Institute, MA 02139, USA
| | - Sue Jane Wang
- Office of Biostatistics, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food & Drug Administration, MD 20993, USA
| | - Aloka Chakravarty
- Office of the Commissioner, US Food & Drug Administration, MD 20993, USA
| | - Klaus Romero
- Translational and Safety Sciences Program, Critical Path Institute, AZ 85718, USA
| | | | - John-Michael Sauer
- Translational and Safety Sciences Program, Critical Path Institute, AZ 85718, USA
| | - Lisa M McShane
- Biometric Research Program, Division of Cancer Treament and Diagnosis, National Cancer Institute, National Institutes of Health, MD 20892, USA
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Nielsen TO, Leung SCY, McShane LM, Dowsett M, Hayes DF. Response to Zhang and Yang. J Natl Cancer Inst 2021; 113:1597-1598. [PMID: 34003287 DOI: 10.1093/jnci/djab094] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 05/12/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Torsten O Nielsen
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Samuel C Y Leung
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Lisa M McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Mitch Dowsett
- Breast Cancer Now Toby Robins Research Centre, Institute of Cancer Research, London, UK
| | - Daniel F Hayes
- University of Michigan Rogel Cancer Center, Ann Arbor, MI, USA
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Flaherty KT, Gray R, Chen A, Li S, Patton D, Hamilton SR, Williams PM, Mitchell EP, Iafrate AJ, Sklar J, Harris LN, McShane LM, Rubinstein LV, Sims DJ, Routbort M, Coffey B, Fu T, Zwiebel JA, Little RF, Marinucci D, Catalano R, Magnan R, Kibbe W, Weil C, Tricoli JV, Alexander B, Kumar S, Schwartz GK, Meric-Bernstam F, Lih CJ, McCaskill-Stevens W, Caimi P, Takebe N, Datta V, Arteaga CL, Abrams JS, Comis R, O'Dwyer PJ, Conley BA. The Molecular Analysis for Therapy Choice (NCI-MATCH) Trial: Lessons for Genomic Trial Design. J Natl Cancer Inst 2021; 112:1021-1029. [PMID: 31922567 PMCID: PMC7566320 DOI: 10.1093/jnci/djz245] [Citation(s) in RCA: 118] [Impact Index Per Article: 39.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 12/02/2019] [Accepted: 12/26/2019] [Indexed: 12/22/2022] Open
Abstract
Background The proportion of tumors of various histologies that may respond to drugs targeted to molecular alterations is unknown. NCI-MATCH, a collaboration between ECOG-ACRIN Cancer Research Group and the National Cancer Institute, was initiated to find efficacy signals by matching patients with refractory malignancies to treatment targeted to potential tumor molecular drivers regardless of cancer histology. Methods Trial development required assumptions about molecular target prevalence, accrual rates, treatment eligibility, and enrollment rates as well as consideration of logistical requirements. Central tumor profiling was performed with an investigational next-generation DNA–targeted sequencing assay of alterations in 143 genes, and protein expression of protein expression of phosphatase and tensin homolog, mutL homolog 1, mutS homolog 2, and RB transcriptional corepressor 1. Treatments were allocated with a validated computational platform (MATCHBOX). A preplanned interim analysis evaluated assumptions and feasibility in this novel trial. Results At interim analysis, accrual was robust, tumor biopsies were safe (<1% severe events), and profiling success was 87.3%. Actionable molecular alteration frequency met expectations, but assignment and enrollment lagged due to histology exclusions and mismatch of resources to demand. To address this lag, we revised estimates of mutation frequencies, increased screening sample size, added treatments, and improved assay throughput and efficiency (93.9% completion and 14-day turnaround). Conclusions The experiences in the design and implementation of the NCI-MATCH trial suggest that profiling from fresh tumor biopsies and assigning treatment can be performed efficiently in a large national network trial. The success of such trials necessitates a broad screening approach and many treatment options easily accessible to patients.
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Affiliation(s)
| | - Robert Gray
- Dana Farber Cancer Institute ECOG-ACRIN Biostatistics Center, Boston, MA, USA
| | - Alice Chen
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Shuli Li
- Dana Farber Cancer Institute ECOG-ACRIN Biostatistics Center, Boston, MA, USA
| | - David Patton
- Center for Biomedical Informatics and Information Technology, National Cancer Institute, NIH, Bethesda, MD, USA
| | | | - Paul M Williams
- Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | | | - A John Iafrate
- Massachusetts General Hospital, Harvard University, Boston, MA, USA
| | | | - Lyndsay N Harris
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Lisa M McShane
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Larry V Rubinstein
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Bethesda, MD, USA
| | - David J Sims
- Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Mark Routbort
- University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Brent Coffey
- Center for Biomedical Informatics and Information Technology, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Tony Fu
- Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - James A Zwiebel
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Richard F Little
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Bethesda, MD, USA
| | | | | | - Rick Magnan
- ECOG-ACRIN Cancer Research Group, Boston, MA, USA
| | - Warren Kibbe
- Center for Biomedical Informatics and Information Technology, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Carol Weil
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Bethesda, MD, USA
| | - James V Tricoli
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Brian Alexander
- Radiation Oncology, Dana Farber Cancer Institute, Boston, MA, USA
| | | | - Gary K Schwartz
- Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, USA
| | | | - Chih-Jian Lih
- Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | | | - Paolo Caimi
- Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, USA
| | - Naoko Takebe
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Vivekananda Datta
- Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Carlos L Arteaga
- University of Texas Southwestern Simmons Cancer Center, Dallas, TX, USA
| | - Jeffrey S Abrams
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Robert Comis
- ECOG-ACRIN Cancer Research Group, Philadelphia, PA, USA
| | | | - Barbara A Conley
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Bethesda, MD, USA
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Krushkal J, Negi S, Yee LM, Evans JR, Grkovic T, Palmisano A, Fang J, Sankaran H, McShane LM, Zhao Y, O'Keefe BR. Molecular genomic features associated with in vitro response of the NCI-60 cancer cell line panel to natural products. Mol Oncol 2021; 15:381-406. [PMID: 33169510 PMCID: PMC7858122 DOI: 10.1002/1878-0261.12849] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 09/29/2020] [Accepted: 11/06/2020] [Indexed: 12/17/2022] Open
Abstract
Natural products remain a significant source of anticancer chemotherapeutics. The search for targeted drugs for cancer treatment includes consideration of natural products, which may provide new opportunities for antitumor cytotoxicity as single agents or in combination therapy. We examined the association of molecular genomic features in the well-characterized NCI-60 cancer cell line panel with in vitro response to treatment with 1302 small molecules which included natural products, semisynthetic natural product derivatives, and synthetic compounds based on a natural product pharmacophore from the Developmental Therapeutics Program of the US National Cancer Institute's database. These compounds were obtained from a variety of plant, marine, and microbial species. Molecular information utilized for the analysis included expression measures for 23059 annotated transcripts, lncRNAs, and miRNAs, and data on protein-changing single nucleotide variants in 211 cancer-related genes. We found associations of expression of multiple genes including SLFN11, CYP2J2, EPHX1, GPC1, ELF3, and MGMT involved in DNA damage repair, NOTCH family members, ABC and SLC transporters, and both mutations in tyrosine kinases and BRAF V600E with NCI-60 responses to specific categories of natural products. Hierarchical clustering identified groups of natural products, which correlated with a specific mechanism of action. Specifically, several natural product clusters were associated with SLFN11 gene expression, suggesting that potential action of these compounds may involve DNA damage. The associations between gene expression or genome alterations of functionally relevant genes with the response of cancer cells to natural products provide new information about potential mechanisms of action of these identified clusters of compounds with potentially similar biological effects. This information will assist in future drug discovery and in design of new targeted cancer chemotherapy agents.
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Affiliation(s)
- Julia Krushkal
- Biometric Research ProgramDivision of Cancer Treatment and DiagnosisNational Cancer InstituteNIHRockvilleMDUSA
| | - Simarjeet Negi
- Biometric Research ProgramDivision of Cancer Treatment and DiagnosisNational Cancer InstituteNIHRockvilleMDUSA
| | - Laura M. Yee
- Biometric Research ProgramDivision of Cancer Treatment and DiagnosisNational Cancer InstituteNIHRockvilleMDUSA
| | - Jason R. Evans
- Natural Products BranchDevelopmental Therapeutics ProgramDivision of Cancer Treatment and DiagnosisNational Cancer InstituteFrederickMDUSA
| | - Tanja Grkovic
- Natural Products Support GroupFrederick National Laboratory for Cancer ResearchFrederickMDUSA
| | - Alida Palmisano
- Biometric Research ProgramDivision of Cancer Treatment and DiagnosisNational Cancer InstituteNIHRockvilleMDUSA
- General Dynamics Information Technology (GDIT)Falls ChurchVAUSA
| | - Jianwen Fang
- Biometric Research ProgramDivision of Cancer Treatment and DiagnosisNational Cancer InstituteNIHRockvilleMDUSA
| | - Hari Sankaran
- Biometric Research ProgramDivision of Cancer Treatment and DiagnosisNational Cancer InstituteNIHRockvilleMDUSA
| | - Lisa M. McShane
- Biometric Research ProgramDivision of Cancer Treatment and DiagnosisNational Cancer InstituteNIHRockvilleMDUSA
| | - Yingdong Zhao
- Biometric Research ProgramDivision of Cancer Treatment and DiagnosisNational Cancer InstituteNIHRockvilleMDUSA
| | - Barry R. O'Keefe
- Natural Products BranchDevelopmental Therapeutics ProgramDivision of Cancer Treatment and DiagnosisNational Cancer InstituteFrederickMDUSA
- Molecular Targets ProgramCenter for Cancer ResearchNational Cancer InstituteFrederickMDUSA
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36
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Kalinsky K, Hong F, McCourt CK, Sachdev JC, Mitchell EP, Zwiebel JA, Doyle LA, McShane LM, Li S, Gray RJ, Rubinstein LV, Patton D, Williams PM, Hamilton SR, Conley BA, O’Dwyer PJ, Harris LN, Arteaga CL, Chen AP, Flaherty KT. Effect of Capivasertib in Patients With an AKT1 E17K-Mutated Tumor: NCI-MATCH Subprotocol EAY131-Y Nonrandomized Trial. JAMA Oncol 2021; 7:271-278. [PMID: 33377972 PMCID: PMC7774047 DOI: 10.1001/jamaoncol.2020.6741] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 09/30/2020] [Indexed: 01/15/2023]
Abstract
Importance In the National Cancer Institute Molecular Analysis for Therapy Choice (NCI-MATCH) trial, agents targeting genetic tumor abnormalities are administered to patients. In the NCI-MATCH subprotocol EAY131-Y trial, patients with an AKT1 E17K-mutated metastatic tumor received the pan-AKT inhibitor capivasertib. Objective To assess the objective response rate (ORR) of capivasertib in patients with an AKT1 E17K-mutated tumor. Design, Setting, and Participants Between July 13, 2016, and August 10, 2017, patients in the NCI-MATCH trial were enrolled and assigned to the subprotocol EAY131-Y nonrandomized trial. Patients included adults with an AKT1 E17K-mutated metastatic tumor that had progressed with standard treatment, and these patients were assigned to receive capivasertib. Tumor assessments were repeated every 2 cycles. Data analysis of this evaluable population was performed from November 8, 2019, to March 12, 2020. Interventions The study treatment was capivasertib, 480 mg, orally twice daily for 4 days on and 3 days off weekly in 28-day cycles until disease progression or unacceptable toxic effect. If patients continued hormone therapy for metastatic breast cancer, the capivasertib dose was 400 mg. Main Outcomes and Measures The primary end point was the ORR (ie, complete response [CR] and partial response) according to the Response Evaluation Criteria in Solid Tumors criteria, version 1.1. Secondary end points included progression-free survival (PFS), 6-month PFS, overall survival, and safety. Results In total, 35 evaluable and analyzable patients were included, of whom 30 were women (86%), and the median (range) age was 61 (32-73) years. The most prevalent cancers were breast (18 [51%]), including 15 patients with hormone receptor (HR)-positive/ERBB2-negative and 3 with triple-negative disease, and gynecologic (11 [31%]) cancers. The ORR rate was 28.6% (95% CI, 15%-46%). One patient with endometrioid endometrial adenocarcinoma achieved a CR and remained on therapy at 35.6 months. Patients with confirmed partial response had the following tumor types: 7 had HR-positive/ERBB2-negative breast cancer, 1 had uterine leiomyosarcoma, and 1 had oncocytic parotid gland carcinoma and continued receiving treatment at 28.8 months. Sixteen patients (46%) had stable disease as the best response, 2 (6%) had progressive disease, and 7 (20%) were not evaluable. With a median follow-up of 28.4 months, the overall 6-month PFS rate was 50% (95% CI, 35%-71%). Capivasertib was discontinued because of adverse events in 11 of 35 patients (31%). Grade 3 treatment-related adverse events included hyperglycemia (8 [23%]) and rash (4 [11%]). One grade 4 hyperglycemic adverse event was reported. Conclusions and Relevance This nonrandomized trial found that, in patients with an AKT1 E17K-mutated tumor treated with capivasertib, a clinically significant ORR was achieved, including 1 CR. Clinically meaningful activity with single-agent capivasertib was demonstrated in refractory malignant neoplasms, including rare cancers. Trial Registration ClinicalTrials.gov Identifier: NCT00700882.
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Affiliation(s)
- Kevin Kalinsky
- Department of Medicine, Columbia University Irving Medical Center, New York, New York
- Now with Winship Cancer Institute at Emory University, Atlanta, Georgia
| | - Fangxin Hong
- Department of Biostatistics, Dana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Carolyn K. McCourt
- Department of Obstetrics and Gynecology, Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Jasgit C. Sachdev
- Department of Medicine, TGen/HonorHealth Research Institute, Scottsdale, Arizona
| | - Edith P. Mitchell
- Department of Medicine, Thomas Jefferson University Health, Philadelphia, Pennsylvania
| | - James A. Zwiebel
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - L. Austin Doyle
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - Lisa M. McShane
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - Shuli Li
- Department of Biostatistics, Dana-Farber Cancer Institute–ECOG (Eastern Cooperative Oncology Group)–ACRIN (American College of Radiology Imaging Network) Biostatistics Center, Boston, Massachusetts
| | - Robert J. Gray
- Department of Biostatistics, Dana-Farber Cancer Institute–ECOG (Eastern Cooperative Oncology Group)–ACRIN (American College of Radiology Imaging Network) Biostatistics Center, Boston, Massachusetts
| | - Larry V. Rubinstein
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - David Patton
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - Paul M. Williams
- Division of Cancer Therapeutics and Diagnosis, Molecular Characterization and Assay Development Laboratory, Leidos, Frederick, Maryland
| | - Stanley R. Hamilton
- Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston
- Department of Pathology, City of Hope National Medical Center, Duarte, California
| | - Barbara A. Conley
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - Peter J. O’Dwyer
- Department of Medicine, University of Pennsylvania, Philadelphia
| | - Lyndsay N. Harris
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - Carlos L. Arteaga
- Department of Medicine, University of Texas Southwestern Simmons Cancer Center, Dallas
| | - Alice P. Chen
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
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Wheeler DA, Takebe N, Hinoue T, Hoadley KA, Cardenas MF, Hamilton AM, Laird PW, Wang L, Johnson A, Dewal N, Miller V, Piñeyro D, Castro de Moura M, Esteller M, Shen H, Zenklusen JC, Tarnuzzer R, McShane LM, Tricoli JV, Williams PM, Lubensky I, O'Sullivan-Coyne G, Kohn EC, Little RF, White J, Malik S, Harris L, Weil C, Chen AP, Karlovich C, Rodgers B, Shankar L, Jacobs P, Nolan T, Hu J, Muzny DM, Doddapaneni H, Korchina V, Gastier-Foster J, Bowen J, Leraas K, Edmondson EF, Doroshow JH, Conley BA, Ivy SP, Staudt LM. Molecular Features of Cancers Exhibiting Exceptional Responses to Treatment. Cancer Cell 2021; 39:38-53.e7. [PMID: 33217343 PMCID: PMC8478080 DOI: 10.1016/j.ccell.2020.10.015] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 08/23/2020] [Accepted: 10/13/2020] [Indexed: 12/21/2022]
Abstract
A small fraction of cancer patients with advanced disease survive significantly longer than patients with clinically comparable tumors. Molecular mechanisms for exceptional responses to therapy have been identified by genomic analysis of tumor biopsies from individual patients. Here, we analyzed tumor biopsies from an unbiased cohort of 111 exceptional responder patients using multiple platforms to profile genetic and epigenetic aberrations as well as the tumor microenvironment. Integrative analysis uncovered plausible mechanisms for the therapeutic response in nearly a quarter of the patients. The mechanisms were assigned to four broad categories-DNA damage response, intracellular signaling, immune engagement, and genetic alterations characteristic of favorable prognosis-with many tumors falling into multiple categories. These analyses revealed synthetic lethal relationships that may be exploited therapeutically and rare genetic lesions that favor therapeutic success, while also providing a wealth of testable hypotheses regarding oncogenic mechanisms that may influence the response to cancer therapy.
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Affiliation(s)
- David A Wheeler
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA; Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Naoko Takebe
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | | | - Katherine A Hoadley
- Department of Genetics, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Maria F Cardenas
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA; Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Alina M Hamilton
- Department of Genetics, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | | | - Linghua Wang
- Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | | | - Ninad Dewal
- Foundation Medicine Inc, Cambridge, MA 02141, USA
| | | | - David Piñeyro
- Josep Carreras Leukaemia Research Institute, Badalona, 08916 Barcelona, Catalonia, Spain; Institucio Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Catalonia, Spain
| | - Manuel Castro de Moura
- Josep Carreras Leukaemia Research Institute, Badalona, 08916 Barcelona, Catalonia, Spain
| | - Manel Esteller
- Josep Carreras Leukaemia Research Institute, Badalona, 08916 Barcelona, Catalonia, Spain; Centro de Investigacion Biomedica en Red Cancer (CIBERONC), 28029 Madrid, Spain; Institucio Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Catalonia, Spain; Physiological Sciences Department, School of Medicine and Health Sciences, University of Barcelona (UB), 08007 Barcelona, Catalonia, Spain
| | - Hui Shen
- Van Andel Institute, Grand Rapids, MI 49503, USA
| | | | - Roy Tarnuzzer
- Center for Cancer Genomics, National Cancer Institute, Bethesda, MD 20892, USA
| | - Lisa M McShane
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - James V Tricoli
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Paul M Williams
- Frederick National Laboratory for Cancer Research, Frederick, MD 21701, USA
| | - Irina Lubensky
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | | | - Elise C Kohn
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Richard F Little
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Jeffrey White
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Shakun Malik
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Lyndsay Harris
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Carol Weil
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Alice P Chen
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Chris Karlovich
- Frederick National Laboratory for Cancer Research, Frederick, MD 21701, USA
| | - Brian Rodgers
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Lalitha Shankar
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Paula Jacobs
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Tracy Nolan
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
| | - Jianhong Hu
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Donna M Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | | | - Viktoriya Korchina
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | | | - Jay Bowen
- Nationwide Children's Hospital, Columbus, OH 43205, USA
| | | | - Elijah F Edmondson
- Pathology and Histology Laboratory, Frederick National Laboratory for Cancer Research, National Cancer Institute, NIH, Frederick, MD 21701, USA
| | - James H Doroshow
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Barbara A Conley
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - S Percy Ivy
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Louis M Staudt
- Center for Cancer Genomics, National Cancer Institute, Bethesda, MD 20892, USA.
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Conley BA, Staudt L, Takebe N, Wheeler DA, Wang L, Cardenas MF, Korchina V, Zenklusen JC, McShane LM, Tricoli JV, Williams PM, Lubensky I, O’Sullivan-Coyne G, Kohn E, Little RF, White J, Malik S, Harris LN, Mann B, Weil C, Tarnuzzer R, Karlovich C, Rodgers B, Shankar L, Jacobs PM, Nolan T, Berryman SM, Gastier-Foster J, Bowen J, Leraas K, Shen H, Laird PW, Esteller M, Miller V, Johnson A, Edmondson EF, Giordano TJ, Kim B, Ivy SP. The Exceptional Responders Initiative: Feasibility of a National Cancer Institute Pilot Study. J Natl Cancer Inst 2021; 113:27-37. [PMID: 32339229 PMCID: PMC7781457 DOI: 10.1093/jnci/djaa061] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Revised: 02/27/2020] [Accepted: 04/20/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Tumor molecular profiling from patients experiencing exceptional responses to systemic therapy may provide insights into cancer biology and improve treatment tailoring. This pilot study evaluates the feasibility of identifying exceptional responders retrospectively, obtaining pre-exceptional response treatment tumor tissues, and analyzing them with state-of-the-art molecular analysis tools to identify potential molecular explanations for responses. METHODS Exceptional response was defined as partial (PR) or complete (CR) response to a systemic treatment with population PR or CR rate less than 10% or an unusually long response (eg, duration >3 times published median). Cases proposed by patients' clinicians were reviewed by clinical and translational experts. Tumor and normal tissue (if possible) were profiled with whole exome sequencing and, if possible, targeted deep sequencing, RNA sequencing, methylation arrays, and immunohistochemistry. Potential germline mutations were tracked for relevance to disease. RESULTS Cases reflected a variety of tumors and standard and investigational treatments. Of 520 cases, 476 (91.5%) were accepted for further review, and 222 of 476 (46.6%) proposed cases met requirements as exceptional responders. Clinical data were obtained from 168 of 222 cases (75.7%). Tumor was provided from 130 of 168 cases (77.4%). Of 117 of the 130 (90.0%) cases with sufficient nucleic acids, 109 (93.2%) were successfully analyzed; 6 patients had potentially actionable germline mutations. CONCLUSION Exceptional responses occur with standard and investigational treatment. Retrospective identification of exceptional responders, accessioning, and sequencing of pretreatment archived tissue is feasible. Data from molecular analyses of tumors, particularly when combining results from patients who received similar treatments, may elucidate molecular bases for exceptional responses.
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Affiliation(s)
- Barbara A Conley
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Lou Staudt
- Center for Cancer Genomics, National Cancer Institute, Bethesda, MD, USA
| | - Naoko Takebe
- Developmental Therapeutics Clinic, National Cancer Institute, Bethesda, MD, USA
| | - David A Wheeler
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Linghua Wang
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Maria F Cardenas
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Viktoriya Korchina
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | | | - Lisa M McShane
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - James V Tricoli
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Paul M Williams
- Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Irina Lubensky
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | | | - Elise Kohn
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Richard F Little
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Jeffrey White
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Shakun Malik
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Lyndsay N Harris
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Bhupinder Mann
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Carol Weil
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Roy Tarnuzzer
- Center for Cancer Genomics, National Cancer Institute, Bethesda, MD, USA
| | - Chris Karlovich
- Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Brian Rodgers
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Lalitha Shankar
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Paula M Jacobs
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Tracy Nolan
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Sean M Berryman
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Julie Gastier-Foster
- Nationwide Children’s Hospital, Columbus, OH, USA; Van Andel Research Institute, Grand Rapids, MI, USA
| | - Jay Bowen
- Nationwide Children’s Hospital, Columbus, OH, USA; Van Andel Research Institute, Grand Rapids, MI, USA
| | - Kristen Leraas
- Nationwide Children’s Hospital, Columbus, OH, USA; Van Andel Research Institute, Grand Rapids, MI, USA
| | - Hui Shen
- Van Andel Research Institute, Grand Rapids, MI, USA
| | | | - Manel Esteller
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Catalonia, Spain
| | | | | | - Elijah F Edmondson
- Pathology and Histology Laboratory, Leidos Biomedical Research, Inc, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | | | - Benjamin Kim
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - S Percy Ivy
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
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Nielsen TO, Leung SCY, Rimm DL, Dodson A, Acs B, Badve S, Denkert C, Ellis MJ, Fineberg S, Flowers M, Kreipe HH, Laenkholm AV, Pan H, Penault-Llorca FM, Polley MY, Salgado R, Smith IE, Sugie T, Bartlett JMS, McShane LM, Dowsett M, Hayes DF. Assessment of Ki67 in Breast Cancer: Updated Recommendations From the International Ki67 in Breast Cancer Working Group. J Natl Cancer Inst 2020; 113:808-819. [PMID: 33369635 PMCID: PMC8487652 DOI: 10.1093/jnci/djaa201] [Citation(s) in RCA: 261] [Impact Index Per Article: 65.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 10/14/2020] [Accepted: 11/30/2020] [Indexed: 12/17/2022] Open
Abstract
Ki67 immunohistochemistry (IHC), commonly used as a proliferation marker in breast cancer, has limited value for treatment decisions due to questionable analytical validity. The International Ki67 in Breast Cancer Working Group (IKWG) consensus meeting, held in October 2019, assessed the current evidence for Ki67 IHC analytical validity and clinical utility in breast cancer, including the series of scoring studies the IKWG conducted on centrally stained tissues. Consensus observations and recommendations are: 1) as for estrogen receptor and HER2 testing, preanalytical handling considerations are critical; 2) a standardized visual scoring method has been established and is recommended for adoption; 3) participation in and evaluation of quality assurance and quality control programs is recommended to maintain analytical validity; and 4) the IKWG accepted that Ki67 IHC as a prognostic marker in breast cancer has clinical validity but concluded that clinical utility is evident only for prognosis estimation in anatomically favorable estrogen receptor–positive and HER2-negative patients to identify those who do not need adjuvant chemotherapy. In this T1-2, N0-1 patient group, the IKWG consensus is that Ki67 5% or less, or 30% or more, can be used to estimate prognosis. In conclusion, analytical validity of Ki67 IHC can be reached with careful attention to preanalytical issues and calibrated standardized visual scoring. Currently, clinical utility of Ki67 IHC in breast cancer care remains limited to prognosis assessment in stage I or II breast cancer. Further development of automated scoring might help to overcome some current limitations.
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Affiliation(s)
- Torsten O Nielsen
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Samuel C Y Leung
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - David L Rimm
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
| | - Andrew Dodson
- The UK National External Quality Assessment Scheme for Immunocytochemistry and In-Situ Hybridisation, London, UK
| | - Balazs Acs
- Department of Oncology and Pathology, Cancer Centre Karolinska (CCK), Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Pathology and Cytology, Karolinska University Laboratory, Stockholm, Sweden
| | - Sunil Badve
- Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, USA
| | - Carsten Denkert
- Philipps University Marburg and University Hospital Marburg, Marburg, Germany
| | - Matthew J Ellis
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, USA
| | - Susan Fineberg
- Montefiore Medical Center and the Albert Einstein College of Medicine, Bronx, NY, USA
| | | | - Hans H Kreipe
- Medical School Hannover, Institute of Pathology, Hannover, Germany
| | | | - Hongchao Pan
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | - Mei-Yin Polley
- Department of Public Health Sciences, University of Chicago Biological Sciences, Chicago, IL, USA
| | - Roberto Salgado
- Department of Pathology, GasthuisZusters Antwerpen / Hospital Network Antwerp (GZA-ZNA), Antwerp, Belgium.,Division of Research, Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Ian E Smith
- Breast Unit, Royal Marsden Hospital, London, UK
| | - Tomoharu Sugie
- Department of Surgery, Kansai Medical University, Shinmachi, Hirakata City, Osaka Prefecture, Japan
| | - John M S Bartlett
- Diagnostic Development Program, Ontario Institute for Cancer Research, Toronto, ON, Canada.,Edinburgh Cancer Research Centre, University of Edinburgh, Edinburgh, UK
| | - Lisa M McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA
| | - Mitch Dowsett
- Breast Cancer Now Toby Robins Research Centre, Institute of Cancer Research, London, UK
| | - Daniel F Hayes
- University of Michigan Rogel Cancer Center, Ann Arbor, MI, USA
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Flaherty KT, Gray RJ, Chen AP, Li S, McShane LM, Patton D, Hamilton SR, Williams PM, Iafrate AJ, Sklar J, Mitchell EP, Harris LN, Takebe N, Sims DJ, Coffey B, Fu T, Routbort M, Zwiebel JA, Rubinstein LV, Little RF, Arteaga CL, Comis R, Abrams JS, O'Dwyer PJ, Conley BA. Molecular Landscape and Actionable Alterations in a Genomically Guided Cancer Clinical Trial: National Cancer Institute Molecular Analysis for Therapy Choice (NCI-MATCH). J Clin Oncol 2020; 38:3883-3894. [PMID: 33048619 PMCID: PMC7676882 DOI: 10.1200/jco.19.03010] [Citation(s) in RCA: 149] [Impact Index Per Article: 37.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Therapeutically actionable molecular alterations are widely distributed across cancer types. The National Cancer Institute Molecular Analysis for Therapy Choice (NCI-MATCH) trial was designed to evaluate targeted therapy antitumor activity in underexplored cancer types. Tumor biopsy specimens were analyzed centrally with next-generation sequencing (NGS) in a master screening protocol. Patients with a tumor molecular alteration addressed by a targeted treatment lacking established efficacy in that tumor type were assigned to 1 of 30 treatments in parallel, single-arm, phase II subprotocols.
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Affiliation(s)
| | - Robert J Gray
- ECOG-ACRIN Cancer Research Group Biostatistics Center, Dana Farber Cancer Institute Boston, MA
| | - Alice P Chen
- Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD
| | - Shuli Li
- ECOG-ACRIN Cancer Research Group Biostatistics Center, Dana Farber Cancer Institute Boston, MA
| | - Lisa M McShane
- Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD
| | - David Patton
- Center for Biomedical Informatics and Information Technology, NCI, NIH, Bethesda, MD
| | | | | | - A John Iafrate
- Massachusetts General Hospital, Boston, MA.,Harvard University, Boston, MA
| | | | | | - Lyndsay N Harris
- Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD
| | - Naoko Takebe
- Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD
| | - David J Sims
- Frederick National Laboratory for Cancer Research, Frederick, MD
| | - Brent Coffey
- Center for Biomedical Informatics and Information Technology, Frederick National Laboratory for Cancer Research, Frederick, MD
| | - Tony Fu
- Frederick National Laboratory for Cancer Research, Frederick, MD
| | - Mark Routbort
- University of Texas MD Anderson Cancer Center, Houston, TX
| | - James A Zwiebel
- Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD
| | - Larry V Rubinstein
- Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD
| | - Richard F Little
- Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD
| | - Carlos L Arteaga
- University of Texas Southwestern Simmons Cancer Center, Dallas, TX
| | - Robert Comis
- ECOG-ACRIN Cancer Research Group, Philadelphia, PA.,Deceased
| | - Jeffrey S Abrams
- Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD
| | - Peter J O'Dwyer
- Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD
| | - Barbara A Conley
- Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD
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MERINO DM, Yee LM, McShane LM, Williams PM, Vilimas T, Patidar R, Barrett JC, Chen SJ, Cheng JH, Conroy JM, Cyanam D, Eyring KR, Fabrizio DA, Funari V, Garcia EP, Glenn ST, Gocke CD, Gupta V, Haley LM, Hellmann MD, Keefer L, Keeler LR, Kennedy B, Lazar AJ, MacConaill LE, Meier KL, Papin A, Rizvi NA, Sokol E, Stafford P, Thompson JF, Tom W, Weigman VJ, Xie M, Zhao C, Stewart MD, Allen J. Abstract 5671: Alignment of TMB measured on clinical samples: Phase IIB of the Friends of Cancer Research TMB Harmonization Project. Cancer Res 2020. [DOI: 10.1158/1538-7445.am2020-5671] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Introduction:
Tumor mutational burden (TMB) is the number of somatic mutations per megabase in a tumor's genome and has shown promise as a predictive biomarker of response to immune checkpoint inhibitors across several cancers. TMB is typically measured by whole exome sequencing (WES TMB) or by targeted next-generation sequencing gene panels (panel TMB). As more assays are developed to estimate TMB, harmonization is emerging as an unmet need and is a key goal of the Friends of Cancer Research (Friends) TMB Harmonization Project. Phase I of the Harmonization Project demonstrated correlation between panel TMB and WES TMB using TCGA data and defined theoretical sources of variability across panels. In phase IIA, sustainable TMB reference standard materials generated from human derived cell lines were used to characterize variability in TMB measurements across panels and assessed for utility in TMB alignment. Phase IIB aims to characterize variability in TMB measurements in clinical samples and to establish best practices for estimating and aligning TMB in order to improve consistency across panels.
Methods:
Fifteen laboratories (16 targeted gene panels) at different stages of development participated in phase IIB. Thirty formalin-fixed paraffin-embedded (FFPE) samples with >30% tumor content were acquired; tumor DNA was isolated by a single reference lab. TMB values were calculated for DNA extracted from lung (N=10), bladder (N=10), and gastric tumors (N=10) using WES and a uniform bioinformatics pipeline agreed upon by all Consortium members. DNA samples were also sent to all laboratories, and each used their own sequencing and bioinformatics pipelines to estimate TMB from the genes represented in their respective panels. For each tumor sample, a median across panel TMB estimates was calculated; individual panel TMB estimates were translated to fold-changes relative to the sample median to quantify variability. Association between WES TMB (reference) and panel TMB will be assessed by regression analysis; dependence of association on cancer type was investigated.
Results:
A subset of tumor samples (9 bladder, 7 lung, and 5 gastric) was analyzed using 11 panels at the time of abstract submission. Median panel TMB values ranged 0.60 - 40.26 across samples, with median of median values of 5.35. Fold-change from sample-level medians ranged 0x - 6.67x. Assessment of these clinical samples by WES and all 16 gene panels, as well as regression analysis results, are forthcoming.
Conclusions:
The Friends TMB Harmonization Project has made substantial progress in characterization of TMB measurement variability and association between WES TMB and panel TMB. These are important steps toward alignment of TMB estimates generated by different gene panels which may improve the interpretation of findings within clinical development programs and ultimately enhance the usefulness of this predictive biomarker in clinical decision making.
Citation Format: Diana M. MERINO, Laura M. Yee, Lisa M. McShane, P. Mickey Williams, Tomas Vilimas, Rajesh Patidar, J. Carl Barrett, Shu-Jen Chen, Jen-Hao Cheng, Jeffrey M. Conroy, Dinesh Cyanam, Kenneth R. Eyring, David A. Fabrizio, Vincent Funari, Elizabeth P. Garcia, Sean T. Glenn, Christopher D. Gocke, Vikas Gupta, Lisa M. Haley, Matthew D. Hellmann, Laurel Keefer, Lauryn R. Keeler, Brett Kennedy, Alexander J. Lazar, Laura E. MacConaill, Kristen L. Meier, Arnaud Papin, Naiyer A. Rizvi, Ethan Sokol, Phillip Stafford, John F. Thompson, Warren Tom, Victor J. Weigman, Mingchao Xie, Chen Zhao, Mark D. Stewart, Jeff Allen. Alignment of TMB measured on clinical samples: Phase IIB of the Friends of Cancer Research TMB Harmonization Project [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5671.
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Affiliation(s)
| | | | | | - P. Mickey Williams
- 3Molecular Characterization Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Frederick, MD
| | - Tomas Vilimas
- 3Molecular Characterization Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Frederick, MD
| | - Rajesh Patidar
- 3Molecular Characterization Laboratory, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research Inc, Frederick, MD
| | | | | | | | | | | | | | | | | | | | | | | | | | - Lisa M. Haley
- 12Johns Hopkins University School of Medicine, Baltimore, MD
| | | | | | | | - Brett Kennedy
- 8Intermountain Precision Genomics, Salt Lake City, UT
| | | | | | | | | | | | | | | | | | - Warren Tom
- 22Thermo Fisher Scientific, South San Francisco, CA
| | | | | | | | | | - Jeff Allen
- 1Friends of Cancer Research, Washington, DC
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Salama AKS, Li S, Macrae ER, Park JI, Mitchell EP, Zwiebel JA, Chen HX, Gray RJ, McShane LM, Rubinstein LV, Patton D, Williams PM, Hamilton SR, Armstrong DK, Conley BA, Arteaga CL, Harris LN, O'Dwyer PJ, Chen AP, Flaherty KT. Dabrafenib and Trametinib in Patients With Tumors With BRAFV600E Mutations: Results of the NCI-MATCH Trial Subprotocol H. J Clin Oncol 2020; 38:3895-3904. [PMID: 32758030 DOI: 10.1200/jco.20.00762] [Citation(s) in RCA: 122] [Impact Index Per Article: 30.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
PURPOSE BRAFV600 mutations are commonly found in melanoma and thyroid cancers and to a lesser degree in other tumor types. Subprotocol H (EAY131-H) of the NCI-MATCH platform trial sought to investigate the selective BRAF inhibitor dabrafenib and the MEK1/2 inhibitor trametinib in patients with solid tumors, lymphomas, or multiple myeloma whose tumors harbored a BRAFV600 mutation. PATIENTS AND METHODS EAY131-H is an open-label, single-arm study. Patients with melanoma, thyroid, or colorectal cancer were excluded; patients with non-small-cell lung cancer were later excluded in an amendment. Patients received dabrafenib 150 mg twice per day and trametinib 2 mg per day continuously until disease progression or intolerable toxicity. The primary end point was centrally assessed objective response rate (ORR); secondary end points included progression-free survival (PFS), 6-month PFS, and overall survival. RESULTS Thirty-five patients were enrolled, and 29 were included in the primary efficacy analysis as prespecified in the protocol. Median age was 59 years, and 45% of the patients had received ≥ 3 lines of therapy. The confirmed ORR was 38% (90% CI, 22.9% to 54.9%) with P < .0001 against a null rate of 5%, and PFS was 11.4 months (90% CI, 8.4 to 16.3 months); responses were seen in 7 distinct tumor types. Seven patients had a duration of response of > 12 months, including 4 patients with a duration of response of > 24 months. An additional 8 patients had a PFS > 6 months. The median overall survival was 28.6 months. Reported adverse events were comparable to those noted in previously reported profiles of dabrafenib and trametinib. CONCLUSION This study met its primary end point, with an ORR of 38% (P < .0001) in this mixed histology, pretreated cohort. This promising activity warrants additional investigations in BRAFV600-mutated tumors outside of currently approved indications.
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Affiliation(s)
| | - Shuli Li
- ECOG-ACRIN Biostatistical Center, Boston, MA
| | - Erin R Macrae
- Columbus Oncology and Hematology Associates, Columbus, OH
| | | | | | - James A Zwiebel
- Investigational Drug Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Helen X Chen
- Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Lisa M McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Larry V Rubinstein
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - David Patton
- Center for Biomedical Informatics and Information Technology, National Cancer Institute, Bethesda, MD
| | | | | | | | - Barbara A Conley
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Lyndsay N Harris
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Alice P Chen
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
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Abstract
Oncology clinical trials are undergoing transformation to evaluate targeted therapies addressing a wider variety of biologically defined cancer subgroups. Multiarm basket and umbrella trials conducted under master protocols have become more prominent mechanisms for the clinical evaluation of promising new biologically driven anticancer therapies that are integral to precision oncology medicine. These new trial designs permit efficient clinical evaluation of multiple therapies in a variety of histologically and biologically defined cancers. These complex trials require extensive planning and attention to many factors, including choice of biomarker assay platform, mechanism for processing clinicopathologic and biomarker data to assign patients to substudies, and statistical design, monitoring, and analysis of substudies. Trial teams have expanded to include expertise in the interface between biology, clinical oncology, bioinformatics, and statistics. Strategies for the design, conduct, and analysis of these complex trials will continue to evolve to meet new challenges and opportunities in precision oncology medicine.
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Affiliation(s)
- Laura M. Yee
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Lisa M. McShane
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Boris Freidlin
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Margaret M. Mooney
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Edward L. Korn
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
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Chae YK, Hong F, Vaklavas C, Cheng HH, Hammerman P, Mitchell EP, Zwiebel JA, Ivy SP, Gray RJ, Li S, McShane LM, Rubinstein LV, Patton D, Williams PM, Hamilton SR, Mansfield A, Conley BA, Arteaga CL, Harris LN, O'Dwyer PJ, Chen AP, Flaherty KT. Phase II Study of AZD4547 in Patients With Tumors Harboring Aberrations in the FGFR Pathway: Results From the NCI-MATCH Trial (EAY131) Subprotocol W. J Clin Oncol 2020; 38:2407-2417. [PMID: 32463741 DOI: 10.1200/jco.19.02630] [Citation(s) in RCA: 89] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
PURPOSE NCI-MATCH is a nationwide, histology-agnostic, signal-finding, molecular profile-driven trial for patients with refractory cancers, lymphomas, or myelomas. Patients with tumors harboring actionable aberration(s) in fibroblast growth factor receptor (FGFR) 1-3 were treated with AZD4547, an oral FGFR1-3 inhibitor. METHODS Patients' tumors were screened by next-generation sequencing for predefined FGFR amplification, activating mutations, or fusions. Patients were treated with AZD4547, 80 mg orally twice daily until progression of disease or drug intolerance. A response rate of 16% was considered promising. RESULTS Between July 2016 and June 2017, 70 patients were assigned and 48 received protocol therapy and are eligible for analysis. Patients' tumors harbored FGFR1 or FGFR2 amplification (n = 20), FGFR2 or FGFR3 single-nucleotide variants (n = 19), or FGFR1 or FGFR3 fusions (n = 9). The most common primary tumors were breast (33.3%), urothelial (12.5%), and cervical cancer (10.4%).Grade 3 adverse events were consistent with those described in previous clinical trials. Confirmed partial responses were seen in 8% (90% CI, 3% to 18%) and were observed only in patients whose tumors harbored FGFR1-3 point mutations or fusions. Stable disease was observed in 37.5% (90% CI, 25.8% to 50.4%). The median progression-free survival (PFS) was 3.4 months, and the 6-month PFS rate was 15% (90% CI, 8% to 31%). For patients with tumors harboring FGFR fusions, the response rate was 22% (90% CI, 4.1% to 55%), and 6-month PFS rate was 56% (90% CI, 31% to 100%). CONCLUSION Preliminary signals of activity appeared to be limited to cancers harboring FGFR activating mutations and fusions, although AZD4547 did not meet the primary end point. Different FGFR somatic alterations may confer different levels of signaling potency and/or oncogene dependence.
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Affiliation(s)
| | - Fangxin Hong
- Dana Farber Cancer Institute-ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Christos Vaklavas
- University of Alabama at Birmingham, Birmingham, AL.,Huntsman Cancer Institute of the University of Utah, Salt Lake City, UT
| | | | | | | | - James A Zwiebel
- Investigational Drug Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - S Percy Ivy
- Cancer Therapy Evaluation Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Robert J Gray
- Dana Farber Cancer Institute-ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Shuli Li
- Dana Farber Cancer Institute-ECOG-ACRIN Biostatistics Center, Boston, MA
| | - Lisa M McShane
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - Larry V Rubinstein
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | - David Patton
- Center for Biomedical Informatics & Information Technology, National Cancer Institute, Bethesda, MD
| | | | | | | | - Barbara A Conley
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Lyndsay N Harris
- Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
| | | | - Alice P Chen
- Investigational Drug Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD
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Allison KH, Hammond MEH, Dowsett M, McKernin SE, Carey LA, Fitzgibbons PL, Hayes DF, Lakhani SR, Chavez-MacGregor M, Perlmutter J, Perou CM, Regan MM, Rimm DL, Symmans WF, Torlakovic EE, Varella L, Viale G, Weisberg TF, McShane LM, Wolff AC. Estrogen and Progesterone Receptor Testing in Breast Cancer: American Society of Clinical Oncology/College of American Pathologists Guideline Update. Arch Pathol Lab Med 2020; 144:545-563. [PMID: 31928354 DOI: 10.5858/arpa.2019-0904-sa] [Citation(s) in RCA: 164] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
PURPOSE.— To update key recommendations of the American Society of Clinical Oncology/College of American Pathologists estrogen receptor (ER) and progesterone receptor (PgR) testing in breast cancer guideline. METHODS.— A multidisciplinary international Expert Panel was convened to update the clinical practice guideline recommendations informed by a systematic review of the medical literature. RECOMMENDATIONS.— The Expert Panel continues to recommend ER testing of invasive breast cancers by validated immunohistochemistry as the standard for predicting which patients may benefit from endocrine therapy, and no other assays are recommended for this purpose. Breast cancer samples with 1% to 100% of tumor nuclei positive should be interpreted as ER positive. However, the Expert Panel acknowledges that there are limited data on endocrine therapy benefit for cancers with 1% to 10% of cells staining ER positive. Samples with these results should be reported using a new reporting category, ER Low Positive, with a recommended comment. A sample is considered ER negative if < 1% or 0% of tumor cell nuclei are immunoreactive. Additional strategies recommended to promote optimal performance, interpretation, and reporting of cases with an initial low to no ER staining result include establishing a laboratory-specific standard operating procedure describing additional steps used by the laboratory to confirm/adjudicate results. The status of controls should be reported for cases with 0% to 10% staining. Similar principles apply to PgR testing, which is used primarily for prognostic purposes in the setting of an ER-positive cancer. Testing of ductal carcinoma in situ (DCIS) for ER is recommended to determine potential benefit of endocrine therapies to reduce risk of future breast cancer, while testing DCIS for PgR is considered optional. Additional information can be found at www.asco.org/breast-cancer-guidelines .
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Affiliation(s)
| | | | | | | | | | | | | | - Sunil R Lakhani
- University of Queensland, Brisbane, Queensland, Australia
- Pathology Queensland, Brisbane, Queensland, Australia
| | | | | | | | - Meredith M Regan
- Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA
| | | | | | - Emina E Torlakovic
- Saskatchewan Health Authority, Saskatoon, Saskatchewan, Canada
- University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | | | - Giuseppe Viale
- IEO, European Institute of Oncology, Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy
- University of Milan, Milan, Italy
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Allison KH, Hammond MEH, Dowsett M, McKernin SE, Carey LA, Fitzgibbons PL, Hayes DF, Lakhani SR, Chavez-MacGregor M, Perlmutter J, Perou CM, Regan MM, Rimm DL, Symmans WF, Torlakovic EE, Varella L, Viale G, Weisberg TF, McShane LM, Wolff AC. Estrogen and Progesterone Receptor Testing in Breast Cancer: ASCO/CAP Guideline Update. J Clin Oncol 2020; 38:1346-1366. [PMID: 31928404 DOI: 10.1200/jco.19.02309] [Citation(s) in RCA: 579] [Impact Index Per Article: 144.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/03/2019] [Indexed: 12/13/2022] Open
Abstract
PURPOSE To update key recommendations of the American Society of Clinical Oncology/College of American Pathologists estrogen (ER) and progesterone receptor (PgR) testing in breast cancer guideline. METHODS A multidisciplinary international Expert Panel was convened to update the clinical practice guideline recommendations informed by a systematic review of the medical literature. RECOMMENDATIONS The Expert Panel continues to recommend ER testing of invasive breast cancers by validated immunohistochemistry as the standard for predicting which patients may benefit from endocrine therapy, and no other assays are recommended for this purpose. Breast cancer samples with 1% to 100% of tumor nuclei positive should be interpreted as ER positive. However, the Expert Panel acknowledges that there are limited data on endocrine therapy benefit for cancers with 1% to 10% of cells staining ER positive. Samples with these results should be reported using a new reporting category, ER Low Positive, with a recommended comment. A sample is considered ER negative if < 1% or 0% of tumor cell nuclei are immunoreactive. Additional strategies recommended to promote optimal performance, interpretation, and reporting of cases with an initial low to no ER staining result include establishing a laboratory-specific standard operating procedure describing additional steps used by the laboratory to confirm/adjudicate results. The status of controls should be reported for cases with 0% to 10% staining. Similar principles apply to PgR testing, which is used primarily for prognostic purposes in the setting of an ER-positive cancer. Testing of ductal carcinoma in situ (DCIS) for ER is recommended to determine potential benefit of endocrine therapies to reduce risk of future breast cancer, while testing DCIS for PgR is considered optional. Additional information can be found at www.asco.org/breast-cancer-guidelines.
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Affiliation(s)
| | | | | | | | | | | | | | - Sunil R Lakhani
- University of Queensland, Brisbane, Queensland, Australia
- Pathology Queensland, Brisbane, Queensland, Australia
| | | | | | | | - Meredith M Regan
- Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA
| | | | | | - Emina E Torlakovic
- Saskatchewan Health Authority, Saskatoon, Saskatchewan, Canada
- University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | | | - Giuseppe Viale
- IEO, European Institute of Oncology, Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy
- University of Milan, Milan, Italy
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Johnson DB, Zhao F, Noel M, Riely GJ, Mitchell EP, Wright JJ, Chen HX, Gray RJ, Li S, McShane LM, Rubinstein LV, Patton D, Williams PM, Hamilton SR, Conley BA, Arteaga CL, Harris LN, O'Dwyer PJ, Chen AP, Flaherty KT. Trametinib Activity in Patients with Solid Tumors and Lymphomas Harboring BRAF Non-V600 Mutations or Fusions: Results from NCI-MATCH (EAY131). Clin Cancer Res 2020; 26:1812-1819. [PMID: 31924734 PMCID: PMC7165046 DOI: 10.1158/1078-0432.ccr-19-3443] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 12/16/2019] [Accepted: 01/07/2020] [Indexed: 11/16/2022]
Abstract
PURPOSE Substantial preclinical evidence and case reports suggest that MEK inhibition is an active approach in tumors with BRAF mutations outside the V600 locus, and in BRAF fusions. Thus, Subprotocol R of the NCI-MATCH study tested the MEK inhibitor trametinib in this population. PATIENTS AND METHODS The NCI-MATCH study performed genomic profiling on tumor samples from patients with solid tumors and lymphomas progressing on standard therapies or with no standard treatments. Patients with prespecified fusions and non-V600 mutations in BRAF were assigned to Subprotocol R using the NCI-MATCHBOX algorithm. The primary endpoint was objective response rate (ORR). RESULTS Among 50 patients assigned, 32 were eligible and received therapy with trametinib. Of these, 1 had a BRAF fusion and 31 had BRAF mutations (13 and 19 with class 2 and 3 mutations, respectively). There were no complete responses; 1 patient (3%) had a confirmed partial response (patient with breast ductal adenocarcinoma with BRAF G469E mutation) and 10 patients had stable disease as best response (clinical benefit rate 34%). Median progression-free survival (PFS) was 1.8 months, and median overall survival was 5.7 months. Exploratory subgroup analyses showed that patients with colorectal adenocarcinoma (n = 8) had particularly poor PFS. No new toxicity signals were identified. CONCLUSIONS Trametinib did not show promising clinical activity in patients with tumors harboring non-V600 BRAF mutations, and the subprotocol did not meet its primary endpoint.
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Affiliation(s)
| | - Fengmin Zhao
- Dana-Farber Cancer Institute-ECOG-ACRIN Biostatistics Center, Boston, Massachusetts
| | - Marcus Noel
- University of Rochester, Rochester, New York
| | | | - Edith P Mitchell
- Thomas Jefferson University Hospital, Philadelphia, Pennsylvania
| | | | | | - Robert J Gray
- Dana-Farber Cancer Institute-ECOG-ACRIN Biostatistics Center, Boston, Massachusetts
| | - Shuli Li
- Dana-Farber Cancer Institute-ECOG-ACRIN Biostatistics Center, Boston, Massachusetts
| | | | | | | | - P Mickey Williams
- Frederick National Laboratory for Cancer Research, Bethesda, Maryland
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Azad NS, Gray RJ, Overman MJ, Schoenfeld JD, Mitchell EP, Zwiebel JA, Sharon E, Streicher H, Li S, McShane LM, Rubinstein L, Patton DR, Williams PM, Coffey B, Hamilton SR, Bahary N, Suga JM, Hatoum H, Abrams JS, Conley BA, Arteaga CL, Harris L, O'Dwyer PJ, Chen AP, Flaherty KT. Nivolumab Is Effective in Mismatch Repair-Deficient Noncolorectal Cancers: Results From Arm Z1D-A Subprotocol of the NCI-MATCH (EAY131) Study. J Clin Oncol 2020; 38:214-222. [PMID: 31765263 PMCID: PMC6968795 DOI: 10.1200/jco.19.00818] [Citation(s) in RCA: 93] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/07/2019] [Indexed: 01/08/2023] Open
Abstract
PURPOSE The National Cancer Institute Molecular Analysis for Therapy Choice (NCI-MATCH) trial, the largest national precision oncology study to date (> 1,100 sites) of patients with relapsed or refractory malignancies, assigned patients to targeted therapy in parallel phase II studies based on tumor molecular alterations. The anti-programmed death receptor 1 inhibitor nivolumab previously showed activity in mismatch repair (MMR)-deficient colon cancer. We hypothesized that nivolumab would have activity in patients with MMR-deficient, noncolorectal tumors. PATIENTS AND METHODS Eligible patients with relapsed or refractory tumors, good end-organ function, and Eastern Cooperative Oncology Group performance status of ≤ 1 underwent tumor biopsy for centralized screening of molecular alterations. MMR deficiency was defined by complete loss of nuclear expression of MLH1 or MSH2 MMR gene products by immunohistochemistry (IHC). Patients with MMR-deficient colorectal cancer were excluded. Nivolumab, 3 mg/kg every 2 weeks (28-day cycles) and 480 mg every 4 weeks after cycle 4, was administered intravenously. Disease reassessment was performed every 2 cycles. The primary end point was RECIST 1.1 objective response rate (ORR). RESULTS Two percent of 4,902 screened patients had an MMR-deficient cancer by IHC. Forty-two evaluable patients were enrolled, with a median age of 60 years and a median of 3 prior therapies. The most common histologies were endometrioid endometrial adenocarcinoma (n = 13), prostate adenocarcinoma (n = 5), and uterine carcinosarcoma (n = 4). ORR was 36% (15 of 42 patients). An additional 21% of patients had stable disease. The estimated 6-, 12-, and 18-month progression-free survival rates were 51.3% (90% CI, 38.2% to 64.5%), 46.2% (90% CI, 33.1% to 59.3%), and 31.4% (90% CI, 18.7% to 44.2%), respectively. Median overall survival was 17.3 months. Toxicity was predominantly low grade. CONCLUSION A variety of refractory cancers (2.0% of those screened) had MMR deficiency as defined in NCI-MATCH. Nivolumab has promising activity in MMR-deficient noncolorectal cancers of a wide variety of histopathologic types.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Shuli Li
- Dana-Farber Cancer Institute, Boston, MA
| | | | | | | | | | - Brent Coffey
- Frederick National Laboratory for Cancer Research, Frederick, MD
| | | | | | - J. Marie Suga
- Kaiser Permanente Vallejo Medical Center, San Diego, CA
| | - Hassan Hatoum
- University of Oklahoma Health Sciences Center, Oklahoma City, OK
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Chen AP, Li S, Coffey B, Tricoli JV, Hamilton SR, Williams MP, Mitchell EP, Patton D, Gray RJ, McShane LM, Rubinstein LV, Arteaga CL, O'Dwyer PJ, Harris LN, Conley BA, Flaherty KT. Abstract A089: Adolescent and young adult (AYA) cohort of the NCI MATCH clinical trial (EAY131). Mol Cancer Ther 2019. [DOI: 10.1158/1535-7163.targ-19-a089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: Over the last 30 years, adolescent and young adult (AYA, 15-39 years of age) patients (pts) with cancer have experienced smaller improvements in 5-year survival compared to younger and older pts. One reason is their historically lower rate of participation in clinical trials (~3% AYA vs. 10% in pts > 40 years of age in adult cancer centers). A histology-agnostic trial provides greater opportunity for the AYA population and may improve accrual. The National Cancer Institute-Molecular Analysis for Therapy Choice (NCI-MATCH; NCT0246506), a phase II precision medicine trial evaluating targeted therapy in adult pts (3 18 years old) based on molecular abnormalities in a tumor-agnostic fashion, has been open since 2015. Jointly developed and coordinated by NCI and ECOG-ACRIN and open through the NCI National Clinical Trials Network and the NCI Community Oncology Research Program at more than 1100 academic and community sites, this trial screened 6801 pts for 39 independently-accruing targeted treatment subprotocols. We reviewed the AYA data from the NCI-MATCH trial, which, due to eligibility criteria, does not include pts age 15-17. Materials and Methods: AYA pts age 18-39 with treatment-refractory malignancies (solid tumor, lymphoma, or myeloma) who were (a) eligible for a screening biopsy on the NCI-MATCH trial (screening cohort [SC]) or (b) had an actionable mutation previously identified through clinically indicated sequencing at a CLIA-approved and NCI-MATCH–accepted laboratory (outside assay cohort [OAC]) were eligible for MATCH AYA analysis. Results: Of the 6801 pts screened for NCI-MATCH, 373 were AYA pts age 18-39 (5.5%). Within the SC, 93.5% (300/321) of AYA pts were successfully biopsied, vs. 92.9% of those age 40+ (5240/5640); 35.7% of the SC AYA vs. 39.6% of the 40+ pts had a study-eligible actionable mutation, and 17% (51/300) of AYA pts vs. 17.8% (934/5240) of those 40+ were subsequently assigned to treatment. Of the 401 pts in the OAC, 30 (7.1%) were AYA; 24/30 (80.0%) of AYA OAC pts were assigned to treatment vs. 87.6% (332/379) of OAC pts age 40+. Screening enrollment data show that at Lead Academic Participating Sites (LAPS), a higher percentage of AYA pts were enrolled compared to pts age 40+ (32.8% [113/344] vs. 24.3% [1472/6047], respectively). In contrast, at NCORP sites, a higher percentage of 40+ pts was enrolled relative to AYA pts (43.8% [2647/6047] vs. 35.8% [123/344], respectively). Among the top histologies enrolled (aside from colon, breast, ovarian) were soft tissue sarcoma other than rhabdomyosarcoma, primary CNS tumors, and liver and hepatobiliary, cervical, and neuroendocrine cancers. Conclusions: There were no statistically significant differences between AYA and older (40+) pts in the number who underwent successful biopsies, the prevalence of tumor actionable mutations, or the number of pts assigned to or who received study treatment. AYA pts were more likely to have been enrolled at a LAPS than a NCORP site, consistent with the AYA population being referred to LAPS upon progression from first-line treatment. Enrollment of the AYA in adult cancer centers in the NCI-MATCH trial was higher than the historical 3%: 5.5% in the SC and 7.1% in the OAC. As more tissue-agnostic studies become available in nationwide trials, AYA participation in clinical trials may increase.
Citation Format: Alice P Chen, Shuli Li, Brent Coffey, James V Tricoli, Stanley R Hamilton, Mickey P Williams, Edith P Mitchell, David Patton, Robert J Gray, Lisa M McShane, Lawrence V Rubinstein, Carlos L Arteaga, Peter J O'Dwyer, Lyndsay N Harris, Barbara A Conley, Keith T Flaherty. Adolescent and young adult (AYA) cohort of the NCI MATCH clinical trial (EAY131) [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr A089. doi:10.1158/1535-7163.TARG-19-A089
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Affiliation(s)
| | - Shuli Li
- 2Dana Faber Cancer Institute, Boston, MA
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50
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Harris LN, Gray RJ, Conley BA, Chen AP, Flaherty KT, Hamilton SR, Williams PM, Karlovich C, Patton D, Li S, McShane LM, Rubinstein LV, Mitchell EP, Tricoli JV, Little RF, Arteaga CL, O'Dwyer PJ. Abstract A079: National Cancer Institute Molecular Analysis for Therapy Choice (NCI-MATCH): A successful precision medicine signal-seeking trial in patients (pts) with rare variants and refractory malignancies. Mol Cancer Ther 2019. [DOI: 10.1158/1535-7163.targ-19-a079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Introduction: NCI-MATCH, developed by ECOG-ACRIN & NCI, is the largest precision medicine study for pts with refractory malignancy. Over 1100 clinical sites in the National Clinical Trials Network enrolled pts. The purpose of the study is to identify potentially beneficial targeted treatments across tumor types with similar molecular abnormalities. Methods: The NCI Central IRB approved NCI-MATCH. Pts with refractory/no treatment available solid tumors, lymphomas or myelomas had a fresh biopsy profiled by next generation sequencing (143 genes, > 4000 single nucleotide variants, indels, amplifications & targeted fusions). Pts are assigned by a defined algorithm to treatments with evidence of activity against tumors with the relevant molecular alteration. Pts are excluded if a treatment is FDA approved or known to be ineffective for their malignancy. After successfully sequencing fresh biopsies from 5540 pts, subprotocols with extremely rare variants lacked sufficient accrual. To address actionable variants with a prevalence of < 1.5%, we decided to accept clinical sequencing results from 30 commercial and academic laboratories vetted by NCI-MATCH to address relevant variants. These labs notify clinicians participating in NCI-MATCH if their pt’s tumor contains an actionable variant. Treatment continues until tumors became refractory, pt intolerance or withdrawal of consent. An objective response rate (ORR by RECIST) of > 16% among 31 eligible patients is considered a positive signal. Results: After screening 5540 pts, 37.6% had an actionable variant. After histology and treatment-specific exclusions, 17.8% were assigned and 69.5% enrolled on the assigned subprotocol. 11 of the initial 30 subprotocols reached completion with adequate follow-up. Of the first 11 evaluable subprotocols, 3 addressing rare variants had a positive signal: Nivolumab in pts with loss of expression of MLH1 or MSH2 (ORR 36%), capivasertib in pts with AKT mutations (ORR 23%), and dabrafenib + trametinib in pts with BRAF V600 mutations (ORR 33%). These molecular variants were found in 2%, 1.2% and 1.9% respectively, of screened pts. Two other subprotcocols (afatinib in ERBB2 mutations and AZD4547 in FGFR abnormalities) showed responses in rare tumors or specific variant subsets, respectively. As of July 15, 2019, an additional 378 of 432 (88%) pts have been assigned to a treatment with a clinical sequencing assay; 83% of these pts enrolled to 1 of 24 subprotocols, allowing completion of an additional 9 of the original 30 subprotocols and complete accrual to 2 of 5 recently added subprotocols. Four of 35 subprotocols closed for lack of accrual, 10 continue accruing and 4 are planned. Conclusions: Platform precision medicine trials can identify potentially useful targeted treatments for diverse malignancies in pts with uncommon tumors & rare actionable variants, an unmet need. In a population of pts with refractory cancers, lymphomas and myelomas, 30-40% will have an actionable variant for targeted treatment (investigational or standard). Of the first 11 subprotocols with adequate follow-up, 3 (27%) showed a positive signal and an additional 2 showed responses in rare tumors or in a molecular subset, suggesting that the NCI-MATCH trial approach identifies useful targets for further exploration.
Citation Format: Lyndsay N Harris, Robert J Gray, Barbara A Conley, Alice P Chen, Keith T Flaherty, Stanley R Hamilton, Paul M Williams, Chris Karlovich, David Patton, Shuli Li, Lisa M McShane, Larry V Rubinstein, Edith P Mitchell, James V Tricoli, Richard F Little, Carlos L Arteaga, Peter J O'Dwyer, NCI-MATCH team. National Cancer Institute Molecular Analysis for Therapy Choice (NCI-MATCH): A successful precision medicine signal-seeking trial in patients (pts) with rare variants and refractory malignancies [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr A079. doi:10.1158/1535-7163.TARG-19-A079
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Affiliation(s)
| | | | | | | | | | | | - Paul M Williams
- 5Frederick National Laboratory for Cancer Research, Frederick, MD
| | - Chris Karlovich
- 5Frederick National Laboratory for Cancer Research, Frederick, MD
| | | | - Shuli Li
- 2Dana Farber Cancer Institute, Boston, MA
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