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201 results on '"Rebecca J. Nagy"'

1. NSABP FB-10: a phase Ib/II trial evaluating ado-trastuzumab emtansine (T-DM1) with neratinib in women with metastatic HER2-positive breast cancer

Author

Samuel A. Jacobs, Ying Wang, Jame Abraham, Huichen Feng, Alberto J. Montero, Corey Lipchik, Melanie Finnigan, Rachel C. Jankowitz, Mohamad A. Salkeni, Sai K. Maley, Shannon L. Puhalla, Fanny Piette, Katie Quinn, Kyle Chang, Rebecca J. Nagy, Carmen J. Allegra, Kelly Vehec, Norman Wolmark, Peter C. Lucas, Ashok Srinivasan, and Katherine L. Pogue-Geile

Subjects
Metastatic breast cancer, ctDNA HER2 amplification, Clinical trial, Neratinib + t-DM1, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background We previously reported our phase Ib trial, testing the safety, tolerability, and efficacy of T-DM1 + neratinib in HER2-positive metastatic breast cancer patients. Patients with ERBB2 amplification in ctDNA had deeper and more durable responses. This study extends these observations with in-depth analysis of molecular markers and mechanisms of resistance in additional patients. Methods Forty-nine HER2-positive patients (determined locally) who progressed on-treatment with trastuzumab + pertuzumab were enrolled in this phase Ib/II study. Mutations and HER2 amplifications were assessed in ctDNA before (C1D1) and on-treatment (C2D1) with the Guardant360 assay. Archived tissue (TP0) and study entry biopsies (TP1) were assayed for whole transcriptome, HER2 copy number, and mutations, with Ampli-Seq, and centrally for HER2 with CLIA assays. Patient responses were assessed with RECIST v1.1, and Molecular Response with the Guardant360 Response algorithm. Results The ORR in phase II was 7/22 (32%), which included all patients who had at least one dose of study therapy. In phase I, the ORR was 12/19 (63%), which included only patients who were considered evaluable, having received their first scan at 6 weeks. Central confirmation of HER2-positivity was found in 83% (30/36) of the TP0 samples. HER2-amplified ctDNA was found at C1D1 in 48% (20/42) of samples. Patients with ctHER2-amp versus non-amplified HER2 ctDNA determined in C1D1 ctDNA had a longer median progression-free survival (PFS): 480 days versus 60 days (P = 0.015). Molecular Response scores were significantly associated with both PFS (HR 0.28, 95% CI 0.09–0.90, P = 0.033) and best response (P = 0.037). All five of the patients with ctHER2-amp at C1D1 who had undetectable ctDNA after study therapy had an objective response. Patients whose ctHER2-amp decreased on-treatment had better outcomes than patients whose ctHER2-amp remained unchanged. HER2 RNA levels show a correlation to HER2 CLIA IHC status and were significantly higher in patients with clinically documented responses compared to patients with progressive disease (P = 0.03). Conclusions The following biomarkers were associated with better outcomes for patients treated with T-DM1 + neratinib: (1) ctHER2-amp (C1D1) or in TP1; (2) Molecular Response scores; (3) loss of detectable ctDNA; (4) RNA levels of HER2; and (5) on-treatment loss of detectable ctHER2-amp. HER2 transcriptional and IHC/FISH status identify HER2-low cases (IHC 1+ or IHC 2+ and FISH negative) in these heavily anti-HER2 treated patients. Due to the small number of patients and samples in this study, the associations we have shown are for hypothesis generation only and remain to be validated in future studies. Clinical Trials registration NCT02236000

Published
2024
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2. Correction: NSABP FB-10: a phase Ib/II trial evaluating ado-trastuzumab emtansine (T-DM1) with neratinib in women with metastatic HER2-positive breast cancer

Author

Samuel A. Jacobs, Ying Wang, Jame Abraham, Huichen Feng, Alberto J. Montero, Corey Lipchik, Melanie Finnigan, Rachel C. Jankowitz, Mohamad A. Salkeni, Sai K. Maley, Shannon L. Puhalla, Fanny Piette, Katie Quinn, Kyle Chang, Rebecca J. Nagy, Carmen J. Allegra, Kelly Vehec, Norman Wolmark, Peter C. Lucas, Ashok Srinivasan, and Katherine L. Pogue-Geile

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Published
2024
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3. Identification of osimertinib-resistant EGFR L792 mutations by cfDNA sequencing: oncogenic activity assessment and prevalence in large cfDNA cohort

Author

Stephen R. Fairclough, Lesli A. Kiedrowski, Jessica J. Lin, Ori Zelichov, Gabi Tarcic, Thomas E. Stinchcombe, Justin I. Odegaard, Richard B. Lanman, Alice T. Shaw, and Rebecca J. Nagy

Subjects
Cell-free DNA, cfDNA, Genomic evolution, Acquired resistance, Osimertinib, Guardant360, Diseases of the blood and blood-forming organs, RC633-647.5, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Cell-free DNA (cfDNA) next-generation sequencing has the potential to capture tumor heterogeneity and genomic evolution under treatment pressure in a non-invasive manner. Here, we report the detection of EGFR L792 mutations, a non-covalent mechanism of osimertinib resistance, using Guardant360 cfDNA testing in a patient with metastatic EGFR-mutant non-small cell lung cancer (NSCLC) whose disease progressed on osimertinib. We subsequently analyzed a large cohort of over 1800 additional patient samples harboring an EGFR T790M mutation and identified a concomitant L792 mutation in a total of 22 (1.2%) cases. In vitro functional assays demonstrated that the EGFR L858R/T790M/L792F/H mutations conferred intermediate-level resistance to osimertinib. Further understanding of potential acquired resistance mechanisms to targeted therapy may help inform treatment strategy in EGFR-mutant NSCLC.

Published
2019
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4. Aberrant FGFR signaling mediates resistance to CDK4/6 inhibitors in ER+ breast cancer

Author

Luigi Formisano, Yao Lu, Alberto Servetto, Ariella B. Hanker, Valerie M. Jansen, Joshua A. Bauer, Dhivya R. Sudhan, Angel L. Guerrero-Zotano, Sarah Croessmann, Yan Guo, Paula Gonzalez Ericsson, Kyung-min Lee, Mellissa J. Nixon, Luis J. Schwarz, Melinda E. Sanders, Teresa C. Dugger, Marcelo Rocha Cruz, Amir Behdad, Massimo Cristofanilli, Aditya Bardia, Joyce O’Shaughnessy, Rebecca J. Nagy, Richard B. Lanman, Nadia Solovieff, Wei He, Michelle Miller, Fei Su, Yu Shyr, Ingrid A. Mayer, Justin M. Balko, and Carlos L. Arteaga

Subjects
Science
Abstract

Era+ breast cancer patients often develop resistance to endocrine therapy. Here, the authors show that FGFR1 amplification is a resistance mechanism to CDK4/6 inhibitor and endocrine therapy and that combined treatment with FGFR, CDK4/6, and anti-estrogens is a potential therapeutic strategy in Era+ breast cancer tumors.

Published
2019
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5. Cell-Free DNA Profiling to Discover Mechanisms of Exceptional Response to Cabozantinib Plus Panitumumab in a Patient With Treatment Refractory Metastatic Colorectal Cancer

Author

Jingquan Jia, Michael A. Morse, Rebecca J. Nagy, Richard B. Lanman, and John H. Strickler

Subjects
MET amplification, metastatic colorectal cancer, cabozantinib, cell-free DNA, ctDNA, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

MET amplification is rare in treatment-naïve metastatic colorectal cancer (CRC) tumors, but can emerge as a mechanism of resistance to anti-EGFR therapies. Preclinical and clinical data suggest that patients with MET amplified tumors benefit from MET-targeted therapy. Cabozantinib is an inhibitor of multiple tyrosine kinases, included c-MET. Panitumumab is an inhibitor of EGFR. This report describes a patient with KRAS, NRAS, and BRAF wild-type metastatic CRC who experienced disease progression on all standard chemotherapy and anti-EGFR antibody therapy. The patient was enrolled in a clinical trial evaluating the combination of cabozantinib plus panitumumab. After only 6 weeks of treatment, the patient experienced a significant anti-tumor response. Although tumor tissue was negative for MET amplification, molecular profiling of cell-free DNA (cfDNA) revealed MET amplification. This case represents the first report showing the activity of cabozantinib in combination with panitumumab in a patient with metastatic CRC, and suggests that MET amplification in cfDNA may be a biomarker of response. A clinical trial targeting MET amplified metastatic CRC is currently underway.

Published
2018
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6. BRAF Mutations Classes I, II, and III in NSCLC Patients Included in the SLLIP Trial: The Need for a New Pre-Clinical Treatment Rationale

Author

Jillian Wilhelmina Paulina Bracht, Niki Karachaliou, Trever Bivona, Richard B. Lanman, Iris Faull, Rebecca J. Nagy, Ana Drozdowskyj, Jordi Berenguer, Manuel Fernandez-Bruno, Miguel Angel Molina-Vila, and Rafael Rosell

Subjects
BRAF, NSCLC, SHP2, PTPN11, MEK, MAPK, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

BRAF V600 mutations have been found in 1−2% of non-small-cell lung cancer (NSCLC) patients, with Food and Drug Administration (FDA) approved treatment of dabrafenib plus trametinib and progression free survival (PFS) of 10.9 months. However, 50−80% of BRAF mutations in lung cancer are non-V600, and can be class II, with intermediate to high kinase activity and RAS independence, or class III, with impaired kinase activity, upstream signaling dependence, and consequently, sensitivity to receptor tyrosine kinase (RTK) inhibitors. Plasma cell-free DNA (cfDNA) of 185 newly diagnosed advanced lung adenocarcinoma patients (Spanish Lung Liquid versus Invasive Biopsy Program, SLLIP, NCT03248089) was examined for BRAF and other alterations with a targeted cfDNA next-generation sequencing (NGS) assay (Guardant360®, Guardant Health Inc., CA, USA), and results were correlated with patient outcome. Cell viability with single or combined RAF, MEK, and SHP2 inhibitors was assessed in cell lines with BRAF class I, II, and III mutations. Out of 185 patients, 22 had BRAF alterations (12%) of which seven patients harbored amplifications (32%) and 17 had BRAF mutations (77%). Of the BRAF mutations, four out of 22 (18%) were V600E and 18/22 (82%) were non-V600. In vitro results confirmed sensitivity of class III and resistance of class I and II BRAF mutations, and BRAF wild type cells to SHP2 inhibition. Concomitant MEK or RAF and SHP2 inhibition showed synergistic effects, especially in the class III BRAF-mutant cell line. Our study indicates that the class of the BRAF mutation may have clinical implications and therefore should be defined in the clinical practice and used to guide therapeutic decisions.

Published
2019
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7. MAF file for CNVs from Real-time Genomic Characterization of Advanced Pancreatic Cancer to Enable Precision Medicine

Author

Brian M. Wolpin, Scott L. Carter, Ryan B. Corcoran, William C. Hahn, Jen Jen Yeh, Nikhil Wagle, David A. Tuveson, Paul B. Shyn, Jeffrey W. Miller, Robert J. Mayer, Matthew H. Kulke, Bruce E. Johnson, Jason L. Hornick, Gad Getz, Levi A. Garraway, Charles S. Fuchs, Matthew B. Yurgelun, Dean J. Welsch, Deborah Knoerzer, Richard B. Lanman, Rebecca J. Nagy, Stuart G. Silverman, Ewa Sicinska, Geoffrey I. Shapiro, Marvin Ryou, Douglas A. Rubinson, Michael H. Rosenthal, Kimberly Perez, Anuj K. Patel, Kimmie Ng, Janet E. Murphy, Jeffrey A. Meyerhardt, Nadine J. McCleary, Kunal Jajoo, Leona A. Doyle, James M. Cleary, Thomas Clancy, Kelly P. Burke, Joseph P. St. Pierre, Heather A. Shahzade, Emily E. Van Seventer, Brandon Nadres, Annacarolina Da Silva, Ana Babic, Nelly Oliver, Karla Helvie, Kristin Anderka, Lori Marini, Devin McCabe, Emma Reilly, Marisa W. Welch, Dorisanne Ragon, Lauren K. Brais, Jaegil Kim, Srivatsan Raghavan, Mehlika Hazar-Rethinam, Arezou A. Ghazani, Richard A. Moffitt, Nicholas D. Camarda, Jonathan A. Nowak, and Andrew J. Aguirre

Abstract

MAF file for copy number variations identified in the cohort

Published
2023

8. Supplementary Figures 1-4 from Genomic Heterogeneity as a Barrier to Precision Medicine in Gastroesophageal Adenocarcinoma

Author

Daniel V. Catenacci, Adam J. Bass, Jeeyun Lee, Viktor Adalsteinsson, Yu Imamura, Jon Davison, Denisse Rotem, Greg Gydush, Sarah Reed, Justin Rhoades, Samuel S. Freeman, Gavin Ha, Andres Gelrud, Uzma Siddiqui, Kyle Hogarth, Paul Chang, Kiran Turaga, Kevin Roggin, Mitchell C. Posner, Yuan Ji, Haley A. Coleman, Bruce M. Wollison, Matthew D. Ducar, Aaron R. Thorner, Andrew Dunford, David J. Oh, Agoston T. Agoston, Rick Lanman, Hideo Baba, Masayuki Watanabe, Lea O'Keefe, Katie S. Nason, Byung-Hoon Min, Min-Gew Choi, Kyoung-Mee Kim, Rebecca J. Nagy, John Hart, Shu-Yuan Xiao, Namrata Setia, Christopher Weber, Carrie Fitzpatrick, Rajani Kanteti, Melissa Maranto, Samantha Lomnicki, Emily O'Day, Kenisha Allen, Manish R. Sharma, Blase Polite, Hedy Kindler, Heewon Kwak, Lindsay Alpert, Mirazul Islam, Steven Maron, Yang Liu, Sarah Derks, Matthew D. Stachler, and Eirini Pectasides

Abstract

Supplementary Fig. 1: Mutation rate and ploidy for each individual patient's primary and metastatic sample (cohort 1);Supplementary Fig. 2: Validation of genomic heterogeneity within primary tumor and between primary tumor and lymph node (LN) metastases detected by next generation sequencing (NGS) with fluorescent in situ hybridization (FISH) and immunohistochemistry (IHC);Supplementary Fig. 3: PANGEA: Platform clinical trial of molecularly driven therapies in patients with previously untreated GEA;Supplementary Fig. 4: Biomarker profiling of PANGEA where the biomarker profiling of the metastatic tumor did not lead to treatment reassignment relative to treatments assigned based upon the primary tumor

Published
2023

9. Figure S1 from EGFR and MET Amplifications Determine Response to HER2 Inhibition in ERBB2-Amplified Esophagogastric Cancer

Author

Yelena Y. Janjigian, Nikolaus Schultz, Maurizio Scaltriti, Jorge A. Carrasquillo, David B. Solit, Jason S. Lewis, Barry S. Taylor, Elisa de Stanchina, Michael F. Berger, Wolfgang A. Weber, David H. Ilson, Christine A. Iacobuzio-Donahue, Heiko Schöder, Neeta Pandit-Taskar, Steven M. Larson, Richard B. Lanman, Rebecca J. Nagy, Todd Hembrough, Yuan Tian, Fabiola Cecchi, Besnik Qeriqi, Marissa Mattar, Marinela Capanu, Mario E. Lacouture, Karen Brown, Robert A. Lefkowitz, David P. Kelsen, Mark Schattner, Efsevia Vakiani, Joanne Soong, Gouri J. Nanjangud, Nancy Bouvier, Christopher J. Fong, Helen Won, Yaelle Tuvy, Geoffrey Y. Ku, Pau Castel, Jaclyn F. Hechtman, and Francisco Sanchez-Vega

Abstract

Additional results for dual probe EGFR and ERBB2 FISH from Patients 9, 30 and 32.

Published
2023

10. Data from Genomic Heterogeneity as a Barrier to Precision Medicine in Gastroesophageal Adenocarcinoma

Author

Daniel V. Catenacci, Adam J. Bass, Jeeyun Lee, Viktor Adalsteinsson, Yu Imamura, Jon Davison, Denisse Rotem, Greg Gydush, Sarah Reed, Justin Rhoades, Samuel S. Freeman, Gavin Ha, Andres Gelrud, Uzma Siddiqui, Kyle Hogarth, Paul Chang, Kiran Turaga, Kevin Roggin, Mitchell C. Posner, Yuan Ji, Haley A. Coleman, Bruce M. Wollison, Matthew D. Ducar, Aaron R. Thorner, Andrew Dunford, David J. Oh, Agoston T. Agoston, Rick Lanman, Hideo Baba, Masayuki Watanabe, Lea O'Keefe, Katie S. Nason, Byung-Hoon Min, Min-Gew Choi, Kyoung-Mee Kim, Rebecca J. Nagy, John Hart, Shu-Yuan Xiao, Namrata Setia, Christopher Weber, Carrie Fitzpatrick, Rajani Kanteti, Melissa Maranto, Samantha Lomnicki, Emily O'Day, Kenisha Allen, Manish R. Sharma, Blase Polite, Hedy Kindler, Heewon Kwak, Lindsay Alpert, Mirazul Islam, Steven Maron, Yang Liu, Sarah Derks, Matthew D. Stachler, and Eirini Pectasides

Abstract

Gastroesophageal adenocarcinoma (GEA) is a lethal disease where targeted therapies, even when guided by genomic biomarkers, have had limited efficacy. A potential reason for the failure of such therapies is that genomic profiling results could commonly differ between the primary and metastatic tumors. To evaluate genomic heterogeneity, we sequenced paired primary GEA and synchronous metastatic lesions across multiple cohorts, finding extensive differences in genomic alterations, including discrepancies in potentially clinically relevant alterations. Multiregion sequencing showed significant discrepancy within the primary tumor (PT) and between the PT and disseminated disease, with oncogene amplification profiles commonly discordant. In addition, a pilot analysis of cell-free DNA (cfDNA) sequencing demonstrated the feasibility of detecting genomic amplifications not detected in PT sampling. Lastly, we profiled paired primary tumors, metastatic tumors, and cfDNA from patients enrolled in the personalized antibodies for GEA (PANGEA) trial of targeted therapies in GEA and found that genomic biomarkers were recurrently discrepant between the PT and untreated metastases. Divergent primary and metastatic tissue profiling led to treatment reassignment in 32% (9/28) of patients. In discordant primary and metastatic lesions, we found 87.5% concordance for targetable alterations in metastatic tissue and cfDNA, suggesting the potential for cfDNA profiling to enhance selection of therapy.Significance: We demonstrate frequent baseline heterogeneity in targetable genomic alterations in GEA, indicating that current tissue sampling practices for biomarker testing do not effectively guide precision medicine in this disease and that routine profiling of metastatic lesions and/or cfDNA should be systematically evaluated. Cancer Discov; 8(1); 37–48. ©2017 AACR.See related commentary by Sundar and Tan, p. 14.See related article by Janjigian et al., p. 49.This article is highlighted in the In This Issue feature, p. 1

Published
2023

11. Supplementary Figure S2 from Efficacy and Determinants of Response to HER Kinase Inhibition in HER2-Mutant Metastatic Breast Cancer

Author

David M. Hyman, Funda Meric-Bernstam, David B. Solit, Barry S. Taylor, José Baselga, Richard Bryce, Alshad S. Lalani, Melanie Dujka, Lisa D. Eli, Feng Xu, Grace Mann, Maurizio Scaltriti, Yanyan Cai, Aliaksandra Samoila, Myra Melcer, S. Duygu Selcuklu, Catherine Zimel, Elena I. Gavrila, Komal Jhaveri, Sarat Chandarlapaty, Gary A. Ulaner, Rebecca J. Nagy, Richard B. Lanman, Alexander N. Gorelick, François-Clement Bidard, Andrés Cervantes, Xavier Gonzàlez-Farré, Lee S. Schwartzberg, Joohyuk Sohn, Valentina Boni, Victor Moreno, Monica Arnedos, Morten Mau-Sørensen, Iben Spanggaard, Adam M. Brufksy, Macarena I. de la Fuente, Carlos L. Arteaga, Ingrid A. Mayer, Dejan Juric, Geoffrey I. Shapiro, Janice Lu, Sherene Loi, Cristina Saura, Alison M. Schram, Helen H. Won, Sarina A. Piha-Paul, and Lillian M. Smyth

Abstract

Overall sequencing CONSORT diagram. Flow diagram of study patients and analyzed biospecimens processed through and selected for central sequencing using MSK-IMPACT and Guardant360. cfDNA, cell-free DNA; FFPE, formalin-fixed paraffin-embedded; MSK-IMPACT, Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets; QC, quality control.

Published
2023

12. Supplemental Data File from Targeted Therapies for Targeted Populations: Anti-EGFR Treatment for EGFR-Amplified Gastroesophageal Adenocarcinoma

Author

Daniel V.T. Catenacci, Namrata Setia, Shu-Yuan Xiao, John Hart, Alexa Schrock, Todd Hembrough, Fabiola Cecchi, Richard B. Lanman, Rebecca J. Nagy, Emily O'Day, David Xu, Leah Chase, Samantha Lomnicki, Heewon A. Kwak, Lindsay Alpert, and Steven B. Maron

Abstract

Detailed patient information who were treated with anti-EGFR therapy

Published
2023

14. Supplementary Table S4 from Real-time Genomic Characterization of Advanced Pancreatic Cancer to Enable Precision Medicine

Author

Brian M. Wolpin, Scott L. Carter, Ryan B. Corcoran, William C. Hahn, Jen Jen Yeh, Nikhil Wagle, David A. Tuveson, Paul B. Shyn, Jeffrey W. Miller, Robert J. Mayer, Matthew H. Kulke, Bruce E. Johnson, Jason L. Hornick, Gad Getz, Levi A. Garraway, Charles S. Fuchs, Matthew B. Yurgelun, Dean J. Welsch, Deborah Knoerzer, Richard B. Lanman, Rebecca J. Nagy, Stuart G. Silverman, Ewa Sicinska, Geoffrey I. Shapiro, Marvin Ryou, Douglas A. Rubinson, Michael H. Rosenthal, Kimberly Perez, Anuj K. Patel, Kimmie Ng, Janet E. Murphy, Jeffrey A. Meyerhardt, Nadine J. McCleary, Kunal Jajoo, Leona A. Doyle, James M. Cleary, Thomas Clancy, Kelly P. Burke, Joseph P. St. Pierre, Heather A. Shahzade, Emily E. Van Seventer, Brandon Nadres, Annacarolina Da Silva, Ana Babic, Nelly Oliver, Karla Helvie, Kristin Anderka, Lori Marini, Devin McCabe, Emma Reilly, Marisa W. Welch, Dorisanne Ragon, Lauren K. Brais, Jaegil Kim, Srivatsan Raghavan, Mehlika Hazar-Rethinam, Arezou A. Ghazani, Richard A. Moffitt, Nicholas D. Camarda, Jonathan A. Nowak, and Andrew J. Aguirre

Abstract

Treatment history for patients enrolled on the PancSeq protocol.

Published
2023

15. Data from Efficacy and Determinants of Response to HER Kinase Inhibition in HER2-Mutant Metastatic Breast Cancer

Author

David M. Hyman, Funda Meric-Bernstam, David B. Solit, Barry S. Taylor, José Baselga, Richard Bryce, Alshad S. Lalani, Melanie Dujka, Lisa D. Eli, Feng Xu, Grace Mann, Maurizio Scaltriti, Yanyan Cai, Aliaksandra Samoila, Myra Melcer, S. Duygu Selcuklu, Catherine Zimel, Elena I. Gavrila, Komal Jhaveri, Sarat Chandarlapaty, Gary A. Ulaner, Rebecca J. Nagy, Richard B. Lanman, Alexander N. Gorelick, François-Clement Bidard, Andrés Cervantes, Xavier Gonzàlez-Farré, Lee S. Schwartzberg, Joohyuk Sohn, Valentina Boni, Victor Moreno, Monica Arnedos, Morten Mau-Sørensen, Iben Spanggaard, Adam M. Brufksy, Macarena I. de la Fuente, Carlos L. Arteaga, Ingrid A. Mayer, Dejan Juric, Geoffrey I. Shapiro, Janice Lu, Sherene Loi, Cristina Saura, Alison M. Schram, Helen H. Won, Sarina A. Piha-Paul, and Lillian M. Smyth

Abstract

HER2 mutations define a subset of metastatic breast cancers with a unique mechanism of oncogenic addiction to HER2 signaling. We explored activity of the irreversible pan-HER kinase inhibitor neratinib, alone or with fulvestrant, in 81 patients with HER2-mutant metastatic breast cancer. Overall response rate was similar with or without estrogen receptor (ER) blockade. By comparison, progression-free survival and duration of response appeared longer in ER+ patients receiving combination therapy, although the study was not designed for direct comparison. Preexistent concurrent activating HER2 or HER3 alterations were associated with poor treatment outcome. Similarly, acquisition of multiple HER2-activating events, as well as gatekeeper alterations, were observed at disease progression in a high proportion of patients deriving clinical benefit from neratinib. Collectively, these data define HER2 mutations as a therapeutic target in breast cancer and suggest that coexistence of additional HER signaling alterations may promote both de novo and acquired resistance to neratinib.Significance:HER2 mutations define a targetable breast cancer subset, although sensitivity to irreversible HER kinase inhibition appears to be modified by the presence of concurrent activating genomic events in the pathway. These findings have implications for potential future combinatorial approaches and broader therapeutic development for this genomically defined subset of breast cancer.This article is highlighted in the In This Issue feature, p. 161

Published
2023

16. Supplementary Figures from Real-time Genomic Characterization of Advanced Pancreatic Cancer to Enable Precision Medicine

Author

Brian M. Wolpin, Scott L. Carter, Ryan B. Corcoran, William C. Hahn, Jen Jen Yeh, Nikhil Wagle, David A. Tuveson, Paul B. Shyn, Jeffrey W. Miller, Robert J. Mayer, Matthew H. Kulke, Bruce E. Johnson, Jason L. Hornick, Gad Getz, Levi A. Garraway, Charles S. Fuchs, Matthew B. Yurgelun, Dean J. Welsch, Deborah Knoerzer, Richard B. Lanman, Rebecca J. Nagy, Stuart G. Silverman, Ewa Sicinska, Geoffrey I. Shapiro, Marvin Ryou, Douglas A. Rubinson, Michael H. Rosenthal, Kimberly Perez, Anuj K. Patel, Kimmie Ng, Janet E. Murphy, Jeffrey A. Meyerhardt, Nadine J. McCleary, Kunal Jajoo, Leona A. Doyle, James M. Cleary, Thomas Clancy, Kelly P. Burke, Joseph P. St. Pierre, Heather A. Shahzade, Emily E. Van Seventer, Brandon Nadres, Annacarolina Da Silva, Ana Babic, Nelly Oliver, Karla Helvie, Kristin Anderka, Lori Marini, Devin McCabe, Emma Reilly, Marisa W. Welch, Dorisanne Ragon, Lauren K. Brais, Jaegil Kim, Srivatsan Raghavan, Mehlika Hazar-Rethinam, Arezou A. Ghazani, Richard A. Moffitt, Nicholas D. Camarda, Jonathan A. Nowak, and Andrew J. Aguirre

Abstract

Supplementary Figure S1: Overview of workflow and data generation. Supplementary Figure S2: Analysis of neoplastic cellularity. Supplementary Figure S3: Recurrent copy number alterations. Supplementary Figure S4: Mutational signature analysis. Supplementary Figure S5: Analysis of PDAC gene expression signatures. Supplementary Figure S6: Clinically relevant alterations in the cohort.

Published
2023

17. Supplementary Figure Legends from Genomic Heterogeneity as a Barrier to Precision Medicine in Gastroesophageal Adenocarcinoma

Author

Daniel V. Catenacci, Adam J. Bass, Jeeyun Lee, Viktor Adalsteinsson, Yu Imamura, Jon Davison, Denisse Rotem, Greg Gydush, Sarah Reed, Justin Rhoades, Samuel S. Freeman, Gavin Ha, Andres Gelrud, Uzma Siddiqui, Kyle Hogarth, Paul Chang, Kiran Turaga, Kevin Roggin, Mitchell C. Posner, Yuan Ji, Haley A. Coleman, Bruce M. Wollison, Matthew D. Ducar, Aaron R. Thorner, Andrew Dunford, David J. Oh, Agoston T. Agoston, Rick Lanman, Hideo Baba, Masayuki Watanabe, Lea O'Keefe, Katie S. Nason, Byung-Hoon Min, Min-Gew Choi, Kyoung-Mee Kim, Rebecca J. Nagy, John Hart, Shu-Yuan Xiao, Namrata Setia, Christopher Weber, Carrie Fitzpatrick, Rajani Kanteti, Melissa Maranto, Samantha Lomnicki, Emily O'Day, Kenisha Allen, Manish R. Sharma, Blase Polite, Hedy Kindler, Heewon Kwak, Lindsay Alpert, Mirazul Islam, Steven Maron, Yang Liu, Sarah Derks, Matthew D. Stachler, and Eirini Pectasides

Abstract

Supplementary Figure Legends

Published
2023

18. Supplementary Data from Efficacy and Determinants of Response to HER Kinase Inhibition in HER2-Mutant Metastatic Breast Cancer

Author

David M. Hyman, Funda Meric-Bernstam, David B. Solit, Barry S. Taylor, José Baselga, Richard Bryce, Alshad S. Lalani, Melanie Dujka, Lisa D. Eli, Feng Xu, Grace Mann, Maurizio Scaltriti, Yanyan Cai, Aliaksandra Samoila, Myra Melcer, S. Duygu Selcuklu, Catherine Zimel, Elena I. Gavrila, Komal Jhaveri, Sarat Chandarlapaty, Gary A. Ulaner, Rebecca J. Nagy, Richard B. Lanman, Alexander N. Gorelick, François-Clement Bidard, Andrés Cervantes, Xavier Gonzàlez-Farré, Lee S. Schwartzberg, Joohyuk Sohn, Valentina Boni, Victor Moreno, Monica Arnedos, Morten Mau-Sørensen, Iben Spanggaard, Adam M. Brufksy, Macarena I. de la Fuente, Carlos L. Arteaga, Ingrid A. Mayer, Dejan Juric, Geoffrey I. Shapiro, Janice Lu, Sherene Loi, Cristina Saura, Alison M. Schram, Helen H. Won, Sarina A. Piha-Paul, and Lillian M. Smyth

Abstract

Supplementary data

Published
2023

19. Supplementary Experimental Methods from Real-time Genomic Characterization of Advanced Pancreatic Cancer to Enable Precision Medicine

Author

Brian M. Wolpin, Scott L. Carter, Ryan B. Corcoran, William C. Hahn, Jen Jen Yeh, Nikhil Wagle, David A. Tuveson, Paul B. Shyn, Jeffrey W. Miller, Robert J. Mayer, Matthew H. Kulke, Bruce E. Johnson, Jason L. Hornick, Gad Getz, Levi A. Garraway, Charles S. Fuchs, Matthew B. Yurgelun, Dean J. Welsch, Deborah Knoerzer, Richard B. Lanman, Rebecca J. Nagy, Stuart G. Silverman, Ewa Sicinska, Geoffrey I. Shapiro, Marvin Ryou, Douglas A. Rubinson, Michael H. Rosenthal, Kimberly Perez, Anuj K. Patel, Kimmie Ng, Janet E. Murphy, Jeffrey A. Meyerhardt, Nadine J. McCleary, Kunal Jajoo, Leona A. Doyle, James M. Cleary, Thomas Clancy, Kelly P. Burke, Joseph P. St. Pierre, Heather A. Shahzade, Emily E. Van Seventer, Brandon Nadres, Annacarolina Da Silva, Ana Babic, Nelly Oliver, Karla Helvie, Kristin Anderka, Lori Marini, Devin McCabe, Emma Reilly, Marisa W. Welch, Dorisanne Ragon, Lauren K. Brais, Jaegil Kim, Srivatsan Raghavan, Mehlika Hazar-Rethinam, Arezou A. Ghazani, Richard A. Moffitt, Nicholas D. Camarda, Jonathan A. Nowak, and Andrew J. Aguirre

Abstract

Supplementary Experimental Methods

Published
2023

20. Supplementary Data from Landscape of Acquired Resistance to Osimertinib in EGFR-Mutant NSCLC and Clinical Validation of Combined EGFR and RET Inhibition with Osimertinib and BLU-667 for Acquired RET Fusion

Author

Lecia V. Sequist, Aaron N. Hata, Beni Wolf, Sai-Hong I. Ou, Corinne Clifford, Erica K. Evans, Alice T. Shaw, Rebecca S. Heist, A. John Iafrate, Mari Mino-Kenudson, Dora Dias-Santagata, Richard B. Lanman, Rebecca J. Nagy, Jessica J. Lin, Varuna Nangia, Amanda K. Riley, Satoshi Yoda, Wenjia Su, Subba R. Digumarthy, Mandeep K. Banwait, Nicolas Marcoux, Viola W. Zhu, Inga T. Lennes, Justin F. Gainor, Jochen K. Lennerz, Hideko Isozaki, and Zofia Piotrowska

Abstract

Supplementary Data and Methods

Published
2023

21. MAF file for mutations from Real-time Genomic Characterization of Advanced Pancreatic Cancer to Enable Precision Medicine

Author

Brian M. Wolpin, Scott L. Carter, Ryan B. Corcoran, William C. Hahn, Jen Jen Yeh, Nikhil Wagle, David A. Tuveson, Paul B. Shyn, Jeffrey W. Miller, Robert J. Mayer, Matthew H. Kulke, Bruce E. Johnson, Jason L. Hornick, Gad Getz, Levi A. Garraway, Charles S. Fuchs, Matthew B. Yurgelun, Dean J. Welsch, Deborah Knoerzer, Richard B. Lanman, Rebecca J. Nagy, Stuart G. Silverman, Ewa Sicinska, Geoffrey I. Shapiro, Marvin Ryou, Douglas A. Rubinson, Michael H. Rosenthal, Kimberly Perez, Anuj K. Patel, Kimmie Ng, Janet E. Murphy, Jeffrey A. Meyerhardt, Nadine J. McCleary, Kunal Jajoo, Leona A. Doyle, James M. Cleary, Thomas Clancy, Kelly P. Burke, Joseph P. St. Pierre, Heather A. Shahzade, Emily E. Van Seventer, Brandon Nadres, Annacarolina Da Silva, Ana Babic, Nelly Oliver, Karla Helvie, Kristin Anderka, Lori Marini, Devin McCabe, Emma Reilly, Marisa W. Welch, Dorisanne Ragon, Lauren K. Brais, Jaegil Kim, Srivatsan Raghavan, Mehlika Hazar-Rethinam, Arezou A. Ghazani, Richard A. Moffitt, Nicholas D. Camarda, Jonathan A. Nowak, and Andrew J. Aguirre

Abstract

MAF file for mutations identified in the cohort

Published
2023

22. Supplementary Data from Genomic Landscape of Cell-Free DNA in Patients with Colorectal Cancer

Author

Scott Kopetz, Ryan B. Corcoran, Igor F. Tsigelny, AmirAli Talasaz, Richard B. Lanman, Funda Meric-Bernstam, Rebecca J. Nagy, Kimberly C. Banks, Chloe E. Atreya, W. Michael Korn, Matthew McKinney, Allan Andresson Lima Pereira, Donna Niedzwiecki, Aparna R. Parikh, Leanne G. Ahronian, Jonathan M. Loree, and John H. Strickler

Abstract

Suppementary Table S1: Gene lists and exon coverage; Supplementary Table S2: Patient Demographics; Supplementary Table S3. Mutational landscape in cfDNA; Supplementary Figure S1: Schema for identification of unique patient cases for analysis; Supplementary Figure S2. Impact of the number of mechanisms of resistance to anti-EGFR therapy on clonality and relative mutant allele frequency; Supplementary Figure S3: Clonal dynamics during anti-EGFR therapy in patient #18.

Published
2023

23. Supplementary Methods from Genomic Heterogeneity as a Barrier to Precision Medicine in Gastroesophageal Adenocarcinoma

Author

Daniel V. Catenacci, Adam J. Bass, Jeeyun Lee, Viktor Adalsteinsson, Yu Imamura, Jon Davison, Denisse Rotem, Greg Gydush, Sarah Reed, Justin Rhoades, Samuel S. Freeman, Gavin Ha, Andres Gelrud, Uzma Siddiqui, Kyle Hogarth, Paul Chang, Kiran Turaga, Kevin Roggin, Mitchell C. Posner, Yuan Ji, Haley A. Coleman, Bruce M. Wollison, Matthew D. Ducar, Aaron R. Thorner, Andrew Dunford, David J. Oh, Agoston T. Agoston, Rick Lanman, Hideo Baba, Masayuki Watanabe, Lea O'Keefe, Katie S. Nason, Byung-Hoon Min, Min-Gew Choi, Kyoung-Mee Kim, Rebecca J. Nagy, John Hart, Shu-Yuan Xiao, Namrata Setia, Christopher Weber, Carrie Fitzpatrick, Rajani Kanteti, Melissa Maranto, Samantha Lomnicki, Emily O'Day, Kenisha Allen, Manish R. Sharma, Blase Polite, Hedy Kindler, Heewon Kwak, Lindsay Alpert, Mirazul Islam, Steven Maron, Yang Liu, Sarah Derks, Matthew D. Stachler, and Eirini Pectasides

Abstract

Supplementary Methods

Published
2023

24. Supplementary Tables 1-8 from Genomic Heterogeneity as a Barrier to Precision Medicine in Gastroesophageal Adenocarcinoma

Author

Daniel V. Catenacci, Adam J. Bass, Jeeyun Lee, Viktor Adalsteinsson, Yu Imamura, Jon Davison, Denisse Rotem, Greg Gydush, Sarah Reed, Justin Rhoades, Samuel S. Freeman, Gavin Ha, Andres Gelrud, Uzma Siddiqui, Kyle Hogarth, Paul Chang, Kiran Turaga, Kevin Roggin, Mitchell C. Posner, Yuan Ji, Haley A. Coleman, Bruce M. Wollison, Matthew D. Ducar, Aaron R. Thorner, Andrew Dunford, David J. Oh, Agoston T. Agoston, Rick Lanman, Hideo Baba, Masayuki Watanabe, Lea O'Keefe, Katie S. Nason, Byung-Hoon Min, Min-Gew Choi, Kyoung-Mee Kim, Rebecca J. Nagy, John Hart, Shu-Yuan Xiao, Namrata Setia, Christopher Weber, Carrie Fitzpatrick, Rajani Kanteti, Melissa Maranto, Samantha Lomnicki, Emily O'Day, Kenisha Allen, Manish R. Sharma, Blase Polite, Hedy Kindler, Heewon Kwak, Lindsay Alpert, Mirazul Islam, Steven Maron, Yang Liu, Sarah Derks, Matthew D. Stachler, and Eirini Pectasides

Abstract

Supplementary Table 1. Tumor and sequencing information for Cohort 1, paired primary and metastatic gastric adenocarcinoma samples; Supplementary Table 2. 243-gene targeted panel used for sequencing of Cohort 2 samples; Supplementary Table 3: Wild type and mutant read counts for paired primary and metastatic samples in cohort 1; Supplementary Table 4. Clinical and pathologic characteristics of Cohort 2; Supplementary Table 5. Complete sequencing results of Cohort 2; Supplementary Table 6. Clinical characteristics of Cohort 3; Supplementary Table 7. Treatment assignment algorithm of PANGEA clinical trial; Supplementary Table 8. Clinical Characteristics and Response Data of evaluable patients in the PANGEA cohort (N = 21)

Published
2023

26. Supplementary Figure Legends from EGFR and MET Amplifications Determine Response to HER2 Inhibition in ERBB2-Amplified Esophagogastric Cancer

Author

Yelena Y. Janjigian, Nikolaus Schultz, Maurizio Scaltriti, Jorge A. Carrasquillo, David B. Solit, Jason S. Lewis, Barry S. Taylor, Elisa de Stanchina, Michael F. Berger, Wolfgang A. Weber, David H. Ilson, Christine A. Iacobuzio-Donahue, Heiko Schöder, Neeta Pandit-Taskar, Steven M. Larson, Richard B. Lanman, Rebecca J. Nagy, Todd Hembrough, Yuan Tian, Fabiola Cecchi, Besnik Qeriqi, Marissa Mattar, Marinela Capanu, Mario E. Lacouture, Karen Brown, Robert A. Lefkowitz, David P. Kelsen, Mark Schattner, Efsevia Vakiani, Joanne Soong, Gouri J. Nanjangud, Nancy Bouvier, Christopher J. Fong, Helen Won, Yaelle Tuvy, Geoffrey Y. Ku, Pau Castel, Jaclyn F. Hechtman, and Francisco Sanchez-Vega

Abstract

Supplementary Figure Legends

Published
2023

27. Supplementary Figures from Landscape of Acquired Resistance to Osimertinib in EGFR-Mutant NSCLC and Clinical Validation of Combined EGFR and RET Inhibition with Osimertinib and BLU-667 for Acquired RET Fusion

Author

Lecia V. Sequist, Aaron N. Hata, Beni Wolf, Sai-Hong I. Ou, Corinne Clifford, Erica K. Evans, Alice T. Shaw, Rebecca S. Heist, A. John Iafrate, Mari Mino-Kenudson, Dora Dias-Santagata, Richard B. Lanman, Rebecca J. Nagy, Jessica J. Lin, Varuna Nangia, Amanda K. Riley, Satoshi Yoda, Wenjia Su, Subba R. Digumarthy, Mandeep K. Banwait, Nicolas Marcoux, Viola W. Zhu, Inga T. Lennes, Justin F. Gainor, Jochen K. Lennerz, Hideko Isozaki, and Zofia Piotrowska

Abstract

Supplementary Figures

Published
2023

28. Supplementary Methods from Amplification of Wild-type KRAS Imparts Resistance to Crizotinib in MET Exon 14 Mutant Non–Small Cell Lung Cancer

Author

Pasi A. Jänne, Yu Imamura, Daniel B. Costa, Paul A. VanderLaan, Amanda J. Redig, Emily S. Chambers, Marzia Capelletti, Richard B. Lanman, Rebecca J. Nagy, Mizuki Nishino, Hideo Baba, Masayuki Watanabe, Paul T. Kirschmeier, Cloud P. Paweletz, Bryan C. Ulrich, Giulia C. Leonardi, Elena V. Ivanova, Jihyun Choi, Sangeetha Palakurthi, Stephen Wang, Man Xu, Frederick H. Wilson, Lynette M. Sholl, Mark M. Awad, and Magda Bahcall

Abstract

Detailed description of methodology and reagents

Published
2023

29. Figure S2 from Validation of a Plasma-Based Comprehensive Cancer Genotyping Assay Utilizing Orthogonal Tissue- and Plasma-Based Methodologies

Author

AmirAli Talasaz, Darya I. Chudova, Richard B. Lanman, Helmy Eltoukhy, Cloud P. Paweletz, Lesli A. Kiedrowski, Christine E. Lee, Rebecca J. Nagy, Diana Abdueva, Reza Mokhtari, Marcin Sikora, Oliver A. Zill, Stephen R. Fairclough, Kimberly C. Banks, Bryan C. Ulrich, James V. Vowles, Stefanie Mortimer, John J. Vincent, and Justin I. Odegaard

Abstract

Empirical determination of the limit of detection. Defined oncogenic driver and background SNVs (a), oncogene and tumor suppressor indels (b), and oncogenic fusions (c) were titrated to specified VAFs, and multiple replicates were measured to determine the 95% LOD. (d) Cell lines comprising defined gene amplifications were titrated to bracket the expected LOD, and the 95% LOD was determined from statistical detection models as per the CLSI Classical Approach.

Published
2023

30. Suppl. Figure S2 from Amplification of Wild-type KRAS Imparts Resistance to Crizotinib in MET Exon 14 Mutant Non–Small Cell Lung Cancer

Author

Pasi A. Jänne, Yu Imamura, Daniel B. Costa, Paul A. VanderLaan, Amanda J. Redig, Emily S. Chambers, Marzia Capelletti, Richard B. Lanman, Rebecca J. Nagy, Mizuki Nishino, Hideo Baba, Masayuki Watanabe, Paul T. Kirschmeier, Cloud P. Paweletz, Bryan C. Ulrich, Giulia C. Leonardi, Elena V. Ivanova, Jihyun Choi, Sangeetha Palakurthi, Stephen Wang, Man Xu, Frederick H. Wilson, Lynette M. Sholl, Mark M. Awad, and Magda Bahcall

Abstract

Next generation sequencing copy number plots for Case #2

Published
2023

32. Data from Treatment with Next-Generation ALK Inhibitors Fuels Plasma ALK Mutation Diversity

Author

Alice T. Shaw, Richard B. Lanman, Justin F. Gainor, Jochen K. Lennerz, Aaron N. Hata, Anna F. Farago, Jennifer Ackil, Emily Chin, Harper Hubbeling, Beow Y. Yeap, Rebecca J. Nagy, Jessica J. Lin, Marguerite Rooney, and Ibiayi Dagogo-Jack

Abstract

Purpose:Acquired resistance to next-generation ALK tyrosine kinase inhibitors (TKIs) is often driven by secondary ALK mutations. Here, we investigated utility of plasma genotyping for identifying ALK resistance mutations at relapse on next-generation ALK TKIs.Experimental Design:We analyzed 106 plasma specimens from 84 patients with advanced ALK-positive lung cancer treated with second- and third-generation ALK TKIs using a commercially available next-generation sequencing (NGS) platform (Guardant360). Tumor biopsies from TKI-resistant lesions underwent targeted NGS to identify ALK mutations.Results:By genotyping plasma, we detected an ALK mutation in 46 (66%) of 70 patients relapsing on a second-generation ALK TKI. When post-alectinib plasma and tumor specimens were compared, there was no difference in frequency of ALK mutations (67% vs. 63%), but plasma specimens were more likely to harbor ≥2 ALK mutations (24% vs. 2%, P = 0.004). Among 29 patients relapsing on lorlatinib, plasma genotyping detected an ALK mutation in 22 (76%), including 14 (48%) with ≥2 ALK mutations. The most frequent combinations of ALK mutations were G1202R/L1196M and D1203N/1171N. Detection of ≥2 ALK mutations was significantly more common in patients relapsing on lorlatinib compared with second-generation ALK TKIs (48% vs. 23%, P = 0.017). Among 15 patients who received lorlatinib after a second-generation TKI, serial plasma analysis demonstrated that eight (53%) acquired ≥1 new ALK mutations on lorlatinib.Conclusions:ALK resistance mutations increase with each successive generation of ALK TKI and may be underestimated by tumor genotyping. Sequential treatment with increasingly potent ALK TKIs may promote acquisition of ALK resistance mutations leading to treatment-refractory compound ALK mutations.

Published
2023

33. Data from Plasma HER2 (ERBB2) Copy Number Predicts Response to HER2-targeted Therapy in Metastatic Colorectal Cancer

Author

Alberto Bardelli, Salvatore Siena, Silvia Marsoni, Livio Trusolino, Richard B. Lanman, Justin I. Odegaard, Kanwal Raghav, Rebecca J. Nagy, Andrea Sartore-Bianchi, and Giulia Siravegna

Abstract

Purpose:ERBB2 (HER2) amplification is an emerging biomarker in colon cancer, conferring sensitivity to combination anti-HER2 therapy. Measurement of HER2 copy number is typically performed using surgical specimens, but cell-free circulating tumor DNA (ctDNA) analysis may be a noninvasive alternative. We determined the sensitivity of plasma copy number (pCN) for detecting ERBB2 amplifications and whether pCN correlated with tissue-detected copy number. We also assessed response to HER2-targeted therapy based on pCN and suggest a pCN threshold predictive of response.Experimental Design:Forty-eight pretreatment and progression plasma samples from 29 HER2-positive patients in the HERACLES A clinical trial were tested using the Guardant360 cfDNA assay. We correlated ERRB2 pCN with progression-free survival (PFS) and best objective response (BOR) and applied an adjustment method based on tumor DNA shedding using the maximum mutant allele fraction as a surrogate for tumor content to accurately determine the pCN threshold predictive of response.Results:Forty-seven of 48 samples had detectable ctDNA, and 46 of 47 samples were ERBB2-amplified on the basis of cfDNA [2.55–122 copies; 97.9% sensitivity (95% confidence interval, 87.2%–99.8%)]. An adjusted ERBB2 pCN of ≥25.82 copies correlated with BOR and PFS (P = 0.0347).Conclusions:cfDNA is a viable alternative to tissue-based genotyping in the metastatic setting. The cfDNA platform utilized correctly identified 28 of 29 (96.6%) of pretreatment samples as ERBB2-amplified and predicted benefit from HER2-targeted therapy. In this study, an observed pCN of 2.4 and an adjusted pCN of 25.82 copies of ERBB2 are proposed to select patients who will benefit from HER2-targeted therapy.

Published
2023

34. Supplementary Table S3. from Cell-Free DNA and Circulating Tumor Cells: Comprehensive Liquid Biopsy Analysis in Advanced Breast Cancer

Author

Massimo Cristofanilli, William J. Gradishar, Leonidas C. Platanias, Firas H. Wehbe, Amir Behdad, Timothy J. Taxter, Vittorina Zagonel, Rebecca J. Nagy, Ricardo Lima Barros Costa, Kimberly S. Strickland, Laura K. Austin, Alfred W. Rademaker, Zhaomei Mu, and Giovanna Rossi

Abstract

Distribution of the patients according to the change of treatment based on ctDNA findings.

Published
2023

35. Supplementary Figures from MET Alterations Are a Recurring and Actionable Resistance Mechanism in ALK-Positive Lung Cancer

Author

Aaron N. Hata, Alice T. Shaw, Justin F. Gainor, Michael S. Lawrence, Christopher G. Azzoli, Cyril H. Benes, Rebecca J. Nagy, Ashish Saxena, Subba R. Digumarthy, Sara E. Stevens, Hetal D. Marble, Andrew Do, Emily Chin, Beow Y. Yeap, Nathaniel A. Adams, Audris Oh, Kylie Prutisto-Chang, Marguerite M. Rooney, Jessica J. Lin, Adam Langenbucher, Jochen K. Lennerz, Satoshi Yoda, and Ibiayi Dagogo-Jack

Abstract

Supplementary Figure 1-5

Published
2023

36. Supplemental Materials from The Landscape of Actionable Genomic Alterations in Cell-Free Circulating Tumor DNA from 21,807 Advanced Cancer Patients

Author

AmirAli Talasaz, Richard B. Lanman, Darya I. Chudova, Helmy Eltoukhy, Arthur M. Baca, Rebecca J. Nagy, Justin I. Odegaard, Philip C. Mack, David R. Gandara, Reza Mokhtari, James V. Vowles, Stefanie A. Mortimer, Stephen R. Fairclough, Kimberly C. Banks, and Oliver A. Zill

Abstract

Supplemental Methods, Supplemental References, Supplemental Figure Legends, Figure S1-13, Table S1-5 and S14

Published
2023

37. Supplemental Table 1 from Baseline Plasma Tumor Mutation Burden Predicts Response to Pembrolizumab-based Therapy in Patients with Metastatic Non–Small Cell Lung Cancer

Author

Erica L. Carpenter, Roger B. Cohen, Corey J. Langer, Joshua M. Bauml, Jeffrey S. Wasser, Aditi P. Singh, Christine A. Ciunci, Abigail T. Berman, Elena Helman, Rebecca J. Nagy, Kimberly C. Banks, Benjamin A. Silva, Michael J. LaRiviere, Theresa E. Christensen, Stephanie S. Yee, Taylor A. Black, Wei-Ting Hwang, Katie J. Quinn, Austin L. Chien, Jeffrey C. Thompson, and Charu Aggarwal

Abstract

Mutations Analyzed

Published
2023

38. Supplemental Data from Combined Blockade of Activating ERBB2 Mutations and ER Results in Synthetic Lethality of ER+/HER2 Mutant Breast Cancer

Author

Carlos L. Arteaga, Nick V. Grishin, Richard B. Lanman, Vincent A. Miller, Alshad S. Lalani, Richard E. Cutler, Jie He, Massimo Cristofanilli, Eric H. Bernicker, Aju Mathew, Rebecca J. Nagy, Dhivya R. Sudhan, Paula I. Gonzalez-Ericsson, Lisa N. Kinch, Luigi Formisano, and Sarah Croessmann

Abstract

Table S1 - HER2 mutations Fig S1 - HER2 co-occur Fig S2 - Long Term Fulv. Fig S3 - L755S CI index Fig S4 - L755S RTprofile Fig S5 - Prot Align Fig S6 - Drug Assays Fig S7 - Quant of Drug Fig S8-11 - immunoblot Fig S12 - L755S mouse Fig S13 - S6 IHC - mouse

Published
2023

40. Table S1 from Validation of a Plasma-Based Comprehensive Cancer Genotyping Assay Utilizing Orthogonal Tissue- and Plasma-Based Methodologies

Author

AmirAli Talasaz, Darya I. Chudova, Richard B. Lanman, Helmy Eltoukhy, Cloud P. Paweletz, Lesli A. Kiedrowski, Christine E. Lee, Rebecca J. Nagy, Diana Abdueva, Reza Mokhtari, Marcin Sikora, Oliver A. Zill, Stephen R. Fairclough, Kimberly C. Banks, Bryan C. Ulrich, James V. Vowles, Stefanie Mortimer, John J. Vincent, and Justin I. Odegaard

Abstract

Digital Sequencing analytical performance metrics summary table.

Published
2023

41. Table S13 from The Landscape of Actionable Genomic Alterations in Cell-Free Circulating Tumor DNA from 21,807 Advanced Cancer Patients

Author

AmirAli Talasaz, Richard B. Lanman, Darya I. Chudova, Helmy Eltoukhy, Arthur M. Baca, Rebecca J. Nagy, Justin I. Odegaard, Philip C. Mack, David R. Gandara, Reza Mokhtari, James V. Vowles, Stefanie A. Mortimer, Stephen R. Fairclough, Kimberly C. Banks, and Oliver A. Zill

Abstract

cfDNA variants associated with resistance to on-label targeted therapies across six cancer types

Published
2023

42. Supplementary Data from Plasma HER2 (ERBB2) Copy Number Predicts Response to HER2-targeted Therapy in Metastatic Colorectal Cancer

Author

Alberto Bardelli, Salvatore Siena, Silvia Marsoni, Livio Trusolino, Richard B. Lanman, Justin I. Odegaard, Kanwal Raghav, Rebecca J. Nagy, Andrea Sartore-Bianchi, and Giulia Siravegna

Abstract

Copy number plots from two pre-treatment HERACLES A samples. X axis represents chromosome (chr) number across the Guardant360 genomic footprint. Y axis represents observed copy number in plasma. Colored dots represent probe-specific copy number signals at each chromosomal position and light green horizontal line represents the sample-specific normalized diploid copy number. The 18 reported gene amplifications are labelled, including ERBB2 on chromosome 17. The sample represented in panel 2A is suggestive of chromosome 17 aneuploidy, as all 5' probe specific signals adjacent to and including ERBB2 are increased (ERBB2 observed pCN = 52.8). In contrast, panel 2B shows clear focal amplification of ERBB2 only (ERBB2 observed pCN = 7.7).

Published
2023

43. Suppl. Table S1 from Amplification of Wild-type KRAS Imparts Resistance to Crizotinib in MET Exon 14 Mutant Non–Small Cell Lung Cancer

Author

Pasi A. Jänne, Yu Imamura, Daniel B. Costa, Paul A. VanderLaan, Amanda J. Redig, Emily S. Chambers, Marzia Capelletti, Richard B. Lanman, Rebecca J. Nagy, Mizuki Nishino, Hideo Baba, Masayuki Watanabe, Paul T. Kirschmeier, Cloud P. Paweletz, Bryan C. Ulrich, Giulia C. Leonardi, Elena V. Ivanova, Jihyun Choi, Sangeetha Palakurthi, Stephen Wang, Man Xu, Frederick H. Wilson, Lynette M. Sholl, Mark M. Awad, and Magda Bahcall

Abstract

Antibodies, compounds, oligonucleotides, and other reagents used in the study

Published
2023

45. Data from Baseline Plasma Tumor Mutation Burden Predicts Response to Pembrolizumab-based Therapy in Patients with Metastatic Non–Small Cell Lung Cancer

Author

Erica L. Carpenter, Roger B. Cohen, Corey J. Langer, Joshua M. Bauml, Jeffrey S. Wasser, Aditi P. Singh, Christine A. Ciunci, Abigail T. Berman, Elena Helman, Rebecca J. Nagy, Kimberly C. Banks, Benjamin A. Silva, Michael J. LaRiviere, Theresa E. Christensen, Stephanie S. Yee, Taylor A. Black, Wei-Ting Hwang, Katie J. Quinn, Austin L. Chien, Jeffrey C. Thompson, and Charu Aggarwal

Abstract

Purpose:The role of plasma-based tumor mutation burden (pTMB) in predicting response to pembrolizumab-based first-line standard-of-care therapy for metastatic non–small cell lung cancer (mNSCLC) has not been explored.Experimental Design:A 500-gene next-generation sequencing panel was used to assess pTMB. Sixty-six patients with newly diagnosed mNSCLC starting first-line pembrolizumab-based therapy, either alone or in combination with chemotherapy, were enrolled (Clinicaltrial.gov identifier: NCT03047616). Response was assessed using RECIST 1.1. Associations were made for patient characteristics, 6-month durable clinical benefit (DCB), progression-free survival (PFS), and overall survival (OS).Results:Of 66 patients, 52 (78.8%) were pTMB-evaluable. Median pTMB was 16.8 mutations per megabase (mut/Mb; range, 1.9–52.5) and was significantly higher for patients achieving DCB compared with no durable benefit (21.3 mut/Mb vs. 12.4 mut/Mb, P = 0.003). For patients with pTMB ≥ 16 mut/Mb, median PFS was 14.1 versus 4.7 months for patients with pTMB < 16 mut/Mb [HR, 0.30 (0.16–0.60); P < 0.001]. Median OS for patients with pTMB ≥ 16 was not reached versus 8.8 months for patients with pTMB < 16 mut/Mb [HR, 0.48 (0.22–1.03); P = 0.061]. Mutations in ERBB2 exon 20, STK11, KEAP1, or PTEN were more common in patients with no DCB. A combination of pTMB ≥ 16 and absence of negative predictor mutations was associated with PFS [HR, 0.24 (0.11–0.49); P < 0.001] and OS [HR, 0.31 (0.13–0.74); P = 0.009].Conclusions:pTMB ≥ 16 mut/Mb is associated with improved PFS after first-line standard-of-care pembrolizumab-based therapy in mNSCLC. STK11/KEAP1/PTEN and ERBB2 mutations may help identify pTMB-high patients unlikely to respond. These results should be validated in larger prospective studies.

Published
2023

46. Supplemental Figure 3 from Baseline Plasma Tumor Mutation Burden Predicts Response to Pembrolizumab-based Therapy in Patients with Metastatic Non–Small Cell Lung Cancer

Author

Erica L. Carpenter, Roger B. Cohen, Corey J. Langer, Joshua M. Bauml, Jeffrey S. Wasser, Aditi P. Singh, Christine A. Ciunci, Abigail T. Berman, Elena Helman, Rebecca J. Nagy, Kimberly C. Banks, Benjamin A. Silva, Michael J. LaRiviere, Theresa E. Christensen, Stephanie S. Yee, Taylor A. Black, Wei-Ting Hwang, Katie J. Quinn, Austin L. Chien, Jeffrey C. Thompson, and Charu Aggarwal

Abstract

pTMBand PD-L1 expression levels.

Published
2023

48. Data from Validation of a Plasma-Based Comprehensive Cancer Genotyping Assay Utilizing Orthogonal Tissue- and Plasma-Based Methodologies

Author

AmirAli Talasaz, Darya I. Chudova, Richard B. Lanman, Helmy Eltoukhy, Cloud P. Paweletz, Lesli A. Kiedrowski, Christine E. Lee, Rebecca J. Nagy, Diana Abdueva, Reza Mokhtari, Marcin Sikora, Oliver A. Zill, Stephen R. Fairclough, Kimberly C. Banks, Bryan C. Ulrich, James V. Vowles, Stefanie Mortimer, John J. Vincent, and Justin I. Odegaard

Abstract

Purpose: To analytically and clinically validate a circulating cell-free tumor DNA sequencing test for comprehensive tumor genotyping and demonstrate its clinical feasibility.Experimental Design: Analytic validation was conducted according to established principles and guidelines. Blood-to-blood clinical validation comprised blinded external comparison with clinical droplet digital PCR across 222 consecutive biomarker-positive clinical samples. Blood-to-tissue clinical validation comprised comparison of digital sequencing calls to those documented in the medical record of 543 consecutive lung cancer patients. Clinical experience was reported from 10,593 consecutive clinical samples.Results: Digital sequencing technology enabled variant detection down to 0.02% to 0.04% allelic fraction/2.12 copies with ≤0.3%/2.24–2.76 copies 95% limits of detection while maintaining high specificity [prevalence-adjusted positive predictive values (PPV) >98%]. Clinical validation using orthogonal plasma- and tissue-based clinical genotyping across >750 patients demonstrated high accuracy and specificity [positive percent agreement (PPAs) and negative percent agreement (NPAs) >99% and PPVs 92%–100%]. Clinical use in 10,593 advanced adult solid tumor patients demonstrated high feasibility (>99.6% technical success rate) and clinical sensitivity (85.9%), with high potential actionability (16.7% with FDA-approved on-label treatment options; 72.0% with treatment or trial recommendations), particularly in non–small cell lung cancer, where 34.5% of patient samples comprised a directly targetable standard-of-care biomarker.Conclusions: High concordance with orthogonal clinical plasma- and tissue-based genotyping methods supports the clinical accuracy of digital sequencing across all four types of targetable genomic alterations. Digital sequencing's clinical applicability is further supported by high rates of technical success and biomarker target discovery. Clin Cancer Res; 24(15); 3539–49. ©2018 AACR.

Published
2023

49. Supplementary Tables from Circulating Tumor DNA Sequencing Analysis of Gastroesophageal Adenocarcinoma

Author

Daniel V.T. Catenacci, Jeeyun Lee, Seung Tae Kim, Richard B. Lanman, Rebecca J. Nagy, Lesli A. Kiedrowski, Julie Johnson, Stacie Landron, Smita S. Joshi, Kelly L. Moore, Sara Kochanny, Samantha Lomnicki, Leah M. Chase, and Steven B. Maron

Abstract

Supplemental Table S1. Description of cohorts and sub-cohorts utilized in this study. Supplemental Table S2. Clinical information detailing patients in the "Baseline-cohort" ie untreated stage IV patients from UC and SMC who underwent ctDNA-NGS testing (n=144). Supplemental Table S3. Peri-operative ctDNA samples and their timing relative to surgery, DFS, maxVAF at the time of draw, and staging. Supplemental Table S4. Alterations detected in ctDNA in post-operative patients within 180 days of surgery. Supplemental Table S5. Frequencies of A) genomic alterations, B) mutations, or C) amplifications in initial tests across the entire Global GEA (n=1627) and UC/SMC subsets as seen in Figure 3. D) GA frequencies in genes common to ctDNA-NGS, MSK-Impact, and TCGA reported as percentage altered. Supplemental Table S6. Frequencies of GAs across the "Global-cohort" and UC/SMC subsets when narrowing patients from figure 3A to A) only initial tests with detectable non-synonymous alterations (n=1329) or B) only initial tests with maxVAF>0.5% (n=936), as seen in figure S3A-B. Similarly, initial tests from the "Global-cohort" were compared with MSK-Impact and TCGA using C) only ctDNA-NGS cases with non-synonymous alterations and D) ctDNA-NGS cases with maxVAF>0.5%. Supplemental Table S7. Detailed molecular information regarding clinically HER2-positive patient cohort (n=58). Supplemental Table S8. Alterations present upon progression of disease after 1L HER2-targeted therapy in patients with persistent HER2 amplification. Supplemental Table S9. Prognostic significance of alterations, mutations, and amplifications in potentially actionable genes.

Published
2023

50. Data from Cell-Free DNA and Circulating Tumor Cells: Comprehensive Liquid Biopsy Analysis in Advanced Breast Cancer

Author

Massimo Cristofanilli, William J. Gradishar, Leonidas C. Platanias, Firas H. Wehbe, Amir Behdad, Timothy J. Taxter, Vittorina Zagonel, Rebecca J. Nagy, Ricardo Lima Barros Costa, Kimberly S. Strickland, Laura K. Austin, Alfred W. Rademaker, Zhaomei Mu, and Giovanna Rossi

Abstract

Purpose: Liquid biopsy provides a real-time assessment of metastatic breast cancer (MBC). We evaluated the utility of combining circulating tumor cells (CTC) and circulating tumor DNA (ctDNA) to predict prognosis in MBC.Experimental Design: We conducted a retrospective study of 91 patients with locally advanced breast cancer and MBC. CTCs were enumerated by CellSearch; the plasma-based assay was performed utilizing Guardant360 and the survival analysis using Kaplan–Meier curves.Results: Eighty-four patients had stage IV cancer, and 7 patients had no metastases. Eighty patients had CTC analysis: median number 2 (0–5,612). Blood samples [232 of 277 (84%)] had mutations. The average ctDNA fraction was 4.5% (0–88.2%) and number of alterations 3 (0–27); the most commonly mutated genes were TP53 (52%), PIK3CA (40%), and ERBB2 (20%). At the time of analysis, 36 patients (39.6%) were dead. The median follow-up for CTCs was 9 months; for ctDNA, it was 9.9 months. For CTCs and ctDNA, respectively, progression-free survival (PFS) was 4.2 and 5.2 months and overall survival (OS) was 18.7 and 21.5 months. There was a statistically significant difference in PFS and OS for baseline CTCs < 5 versus CTCs ≥ 5 (P = 0.021 and P = 0.0004, respectively); %ctDNA < 0.5 versus ≥ 0.5 (P = 0.003 and P = 0.012); number of alterations < 2 versus ≥ 2 (P = 0.059 borderline and P = 0.0015). A significant association by Fisher exact test was found between the number of alterations and the %ctDNA in the baseline sample (P < 0.0001).Conclusions: The study demonstrated that liquid biopsy is an effective prognostic tool. Clin Cancer Res; 24(3); 560–8. ©2017 AACR.

Published
2023

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