Comparing and contrasting predictive biomarkers for immunotherapy and targeted therapy of NSCLC
The era of personalized medicine for advanced-stage non-small-cell lung cancer (NSCLC) began when biomarker-based evidence of molecular pathway and/or oncogene addiction of the tumour became mandatory for the allocation of specific targeted therapies. More recently, the immunotherapy revolution, spe...
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Published in | Nature reviews. Clinical oncology Vol. 16; no. 6; pp. 341 - 355 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
01.06.2019
Nature Publishing Group |
Subjects | |
Online Access | Get full text |
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Abstract | The era of personalized medicine for advanced-stage non-small-cell lung cancer (NSCLC) began when biomarker-based evidence of molecular pathway and/or oncogene addiction of the tumour became mandatory for the allocation of specific targeted therapies. More recently, the immunotherapy revolution, specifically, the development of immune-checkpoint inhibitors (ICIs), has dramatically altered the NSCLC treatment landscape. Herein, we compare and contrast the clinical development of immunotherapy and oncogene-directed therapy for NSCLC, focusing on the role of predictive biomarkers. Immunotherapy biomarkers are fundamentally different from oncogene biomarkers in that they are continuous rather than categorical (binary), spatially and temporally variable and reliant on multiple complex interactions rather than a single, dominant determinant. The performance of predictive biomarkers for ICIs might be improved by combining different markers to reduce the assumptive risks associated with each one. Novel combinations with chemotherapy and ICIs complicate biomarker discovery but do not decrease the value of the markers identified. Perfectly predictive biomarkers of benefit from immunotherapy are unlikely to be identified, although exclusionary biomarkers of minimal benefit or an unacceptable risk of toxicity might be feasible. The clinical adoption and applicability of such biomarkers might vary depending on line of treatment, the available therapeutic alternatives and health economic considerations.
The advent of effective molecularly targeted treatments and immunotherapies for non-small-cell lung cancer (NSCLC) has greatly improved patient outcomes. Whereas most patients selected for treatment with molecularly targeted drugs derive benefits from these agents, benefit from immunotherapy is more difficult to predict. Herein, Camidge and colleagues compare and contrast predictive biomarkers for immunotherapy and targeted therapy of NSCLC to highlight considerations for biomarker development.
Key points
Immunotherapy biomarkers are fundamentally different from the core driver oncogene biomarkers identified for molecularly targeted therapies: they are continuous rather than categorical (binary), spatially and temporally variable and influenced by multiple complex interactions rather than a single, dominant determinant.
Immunotherapy biomarkers enrich for clinical benefit but are currently unable to guarantee or exclude benefit and, therefore, have predominantly been used to identify subgroups of patients with a sufficient likelihood of benefit to suggest immunotherapy as the preferred option in a particular line of therapy.
Biomarkers related to the initiation of an immune cascade (such as tumour mutational burden) could be used to enrich for benefit from any potential immunotherapy; those more towards the final effector phase of the immune cascade (such as programmed cell death 1 ligand 1 (PD-L1)) are more likely to enrich for drug-specific effects.
The next steps in improving the performance of predictive biomarkers of responsiveness to immunotherapy in patients with non-small-cell lung cancer might involve combining different markers to lessen the assumptive risks associated with each one.
The use of chemotherapy–immunotherapy combinations adds additional complexities to the study of immunotherapy biomarkers but does not negate the value of such markers.
Currently, perfectly predictive biomarkers of benefit from immunotherapy seem unattainable, but exclusionary biomarkers based on minimal benefit or maximal toxicity risk might be attainable; their adoption and applicability might vary by line of therapy, available therapeutic alternatives and health economic considerations. |
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AbstractList | The era of personalized medicine for advanced-stage non-small-cell lung cancer (NSCLC) began when biomarker-based evidence of molecular pathway and/or oncogene addiction of the tumour became mandatory for the allocation of specific targeted therapies. More recently, the immunotherapy revolution, specifically, the development of immune-checkpoint inhibitors (ICIs), has dramatically altered the NSCLC treatment landscape. Herein, we compare and contrast the clinical development of immunotherapy and oncogene-directed therapy for NSCLC, focusing on the role of predictive biomarkers. Immunotherapy biomarkers are fundamentally different from oncogene biomarkers in that they are continuous rather than categorical (binary), spatially and temporally variable and reliant on multiple complex interactions rather than a single, dominant determinant. The performance of predictive biomarkers for ICIs might be improved by combining different markers to reduce the assumptive risks associated with each one. Novel combinations with chemotherapy and ICIs complicate biomarker discovery but do not decrease the value of the markers identified. Perfectly predictive biomarkers of benefit from immunotherapy are unlikely to be identified, although exclusionary biomarkers of minimal benefit or an unacceptable risk of toxicity might be feasible. The clinical adoption and applicability of such biomarkers might vary depending on line of treatment, the available therapeutic alternatives and health economic considerations.
The advent of effective molecularly targeted treatments and immunotherapies for non-small-cell lung cancer (NSCLC) has greatly improved patient outcomes. Whereas most patients selected for treatment with molecularly targeted drugs derive benefits from these agents, benefit from immunotherapy is more difficult to predict. Herein, Camidge and colleagues compare and contrast predictive biomarkers for immunotherapy and targeted therapy of NSCLC to highlight considerations for biomarker development.
Key points
Immunotherapy biomarkers are fundamentally different from the core driver oncogene biomarkers identified for molecularly targeted therapies: they are continuous rather than categorical (binary), spatially and temporally variable and influenced by multiple complex interactions rather than a single, dominant determinant.
Immunotherapy biomarkers enrich for clinical benefit but are currently unable to guarantee or exclude benefit and, therefore, have predominantly been used to identify subgroups of patients with a sufficient likelihood of benefit to suggest immunotherapy as the preferred option in a particular line of therapy.
Biomarkers related to the initiation of an immune cascade (such as tumour mutational burden) could be used to enrich for benefit from any potential immunotherapy; those more towards the final effector phase of the immune cascade (such as programmed cell death 1 ligand 1 (PD-L1)) are more likely to enrich for drug-specific effects.
The next steps in improving the performance of predictive biomarkers of responsiveness to immunotherapy in patients with non-small-cell lung cancer might involve combining different markers to lessen the assumptive risks associated with each one.
The use of chemotherapy–immunotherapy combinations adds additional complexities to the study of immunotherapy biomarkers but does not negate the value of such markers.
Currently, perfectly predictive biomarkers of benefit from immunotherapy seem unattainable, but exclusionary biomarkers based on minimal benefit or maximal toxicity risk might be attainable; their adoption and applicability might vary by line of therapy, available therapeutic alternatives and health economic considerations. The era of personalized medicine for advanced-stage non-small-cell lung cancer (NSCLC) began when biomarker-based evidence of molecular pathway and/or oncogene addiction of the tumour became mandatory for the allocation of specific targeted therapies. More recently, the immunotherapy revolution, specifically, the development of immune-checkpoint inhibitors (ICIs), has dramatically altered the NSCLC treatment landscape. Herein, we compare and contrast the clinical development of immunotherapy and oncogene-directed therapy for NSCLC, focusing on the role of predictive biomarkers. Immunotherapy biomarkers are fundamentally different from oncogene biomarkers in that they are continuous rather than categorical (binary), spatially and temporally variable and reliant on multiple complex interactions rather than a single, dominant determinant. The performance of predictive biomarkers for ICIs might be improved by combining different markers to reduce the assumptive risks associated with each one. Novel combinations with chemotherapy and ICIs complicate biomarker discovery but do not decrease the value of the markers identified. Perfectly predictive biomarkers of benefit from immunotherapy are unlikely to be identified, although exclusionary biomarkers of minimal benefit or an unacceptable risk of toxicity might be feasible. The clinical adoption and applicability of such biomarkers might vary depending on line of treatment, the available therapeutic alternatives and health economic considerations. The advent of effective molecularly targeted treatments and immunotherapies for non-small-cell lung cancer (NSCLC) has greatly improved patient outcomes. Whereas most patients selected for treatment with molecularly targeted drugs derive benefits from these agents, benefit from immunotherapy is more difficult to predict. Herein, Camidge and colleagues compare and contrast predictive biomarkers for immunotherapy and targeted therapy of NSCLC to highlight considerations for biomarker development. Key points Immunotherapy biomarkers are fundamentally different from the core driver oncogene biomarkers identified for molecularly targeted therapies: they are continuous rather than categorical (binary), spatially and temporally variable and influenced by multiple complex interactions rather than a single, dominant determinant. Immunotherapy biomarkers enrich for clinical benefit but are currently unable to guarantee or exclude benefit and, therefore, have predominantly been used to identify subgroups of patients with a sufficient likelihood of benefit to suggest immunotherapy as the preferred option in a particular line of therapy. Biomarkers related to the initiation of an immune cascade (such as tumour mutational burden) could be used to enrich for benefit from any potential immunotherapy; those more towards the final effector phase of the immune cascade (such as programmed cell death 1 ligand 1 (PD-L1)) are more likely to enrich for drug-specific effects. The next steps in improving the performance of predictive biomarkers of responsiveness to immunotherapy in patients with non-small-cell lung cancer might involve combining different markers to lessen the assumptive risks associated with each one. The use of chemotherapy-immunotherapy combinations adds additional complexities to the study of immunotherapy biomarkers but does not negate the value of such markers. Currently, perfectly predictive biomarkers of benefit from immunotherapy seem unattainable, but exclusionary biomarkers based on minimal benefit or maximal toxicity risk might be attainable; their adoption and applicability might vary by line of therapy, available therapeutic alternatives and health economic considerations. The era of personalized medicine for advanced-stage non-small-cell lung cancer (NSCLC) began when biomarker-based evidence of molecular pathway and/or oncogene addiction of the tumour became mandatory for the allocation of specific targeted therapies. More recently, the immunotherapy revolution, specifically, the development of immune-checkpoint inhibitors (ICIs), has dramatically altered the NSCLC treatment landscape. Herein, we compare and contrast the clinical development of immunotherapy and oncogene-directed therapy for NSCLC, focusing on the role of predictive biomarkers. Immunotherapy biomarkers are fundamentally different from oncogene biomarkers in that they are continuous rather than categorical (binary), spatially and temporally variable and reliant on multiple complex interactions rather than a single, dominant determinant. The performance of predictive biomarkers for ICIs might be improved by combining different markers to reduce the assumptive risks associated with each one. Novel combinations with chemotherapy and ICIs complicate biomarker discovery but do not decrease the value of the markers identified. Perfectly predictive biomarkers of benefit from immunotherapy are unlikely to be identified, although exclusionary biomarkers of minimal benefit or an unacceptable risk of toxicity might be feasible. The clinical adoption and applicability of such biomarkers might vary depending on line of treatment, the available therapeutic alternatives and health economic considerations. The era of personalized medicine for advanced-stage non-small-cell lung cancer (NSCLC) began when biomarker-based evidence of molecular pathway and/or oncogene addiction of the tumour became mandatory for the allocation of specific targeted therapies. More recently, the immunotherapy revolution, specifically, the development of immune-checkpoint inhibitors (ICIs), has dramatically altered the NSCLC treatment landscape. Herein, we compare and contrast the clinical development of immunotherapy and oncogene-directed therapy for NSCLC, focusing on the role of predictive biomarkers. Immunotherapy biomarkers are fundamentally different from oncogene biomarkers in that they are continuous rather than categorical (binary), spatially and temporally variable and reliant on multiple complex interactions rather than a single, dominant determinant. The performance of predictive biomarkers for ICIs might be improved by combining different markers to reduce the assumptive risks associated with each one. Novel combinations with chemotherapy and ICIs complicate biomarker discovery but do not decrease the value of the markers identified. Perfectly predictive biomarkers of benefit from immunotherapy are unlikely to be identified, although exclusionary biomarkers of minimal benefit or an unacceptable risk of toxicity might be feasible. The clinical adoption and applicability of such biomarkers might vary depending on line of treatment, the available therapeutic alternatives and health economic considerations.The advent of effective molecularly targeted treatments and immunotherapies for non-small-cell lung cancer (NSCLC) has greatly improved patient outcomes. Whereas most patients selected for treatment with molecularly targeted drugs derive benefits from these agents, benefit from immunotherapy is more difficult to predict. Herein, Camidge and colleagues compare and contrast predictive biomarkers for immunotherapy and targeted therapy of NSCLC to highlight considerations for biomarker development. |
Audience | Academic |
Author | Kerr, Keith M. Doebele, Robert C. Camidge, D. Ross |
Author_xml | – sequence: 1 givenname: D. Ross surname: Camidge fullname: Camidge, D. Ross email: ross.camidge@ucdenver.edu organization: Division of Medical Oncology, Department of Medicine, University of Colorado Cancer Center – sequence: 2 givenname: Robert C. surname: Doebele fullname: Doebele, Robert C. organization: Division of Medical Oncology, Department of Medicine, University of Colorado Cancer Center – sequence: 3 givenname: Keith M. surname: Kerr fullname: Kerr, Keith M. organization: Department of Pathology, Aberdeen University Medical School, Aberdeen Royal Infirmary |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30718843$$D View this record in MEDLINE/PubMed |
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Title | Comparing and contrasting predictive biomarkers for immunotherapy and targeted therapy of NSCLC |
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