MODEL-BASED INFERENCE AND CLASSIFICATION OF IMMUNOLOGICAL CONTROL MECHANISMS FROM TKI CESSATION AND DOSE REDUCTION IN CML PATIENTS
Author(s): ,
Ingmar Glauche
Affiliations:
TU Dresden,Dresden,Germany
,
Tom Hähnel
Affiliations:
TU Dresden,Dresden,Germany
,
Christoph Baldow
Affiliations:
TU Dresden,Dresden,Germany
,
Andrea Gottschalk
Affiliations:
TU Dresden,Dresden,Germany
,
Joëlle Guilhot
Affiliations:
INSERM CIC 1402 - CHU Poitiers,Poitiers,France
,
François Guilhot
Affiliations:
INSERM CIC 1402 - CHU Poitiers,Poitiers,France
,
Susanne Saussele
Affiliations:
III. Medizinische Klinik, Universitätsmedizin Mannheim, Heidelberg University,Mannheim,Germany
,
Satu Mustjoki
Affiliations:
Hematology Research Unit Helsinki, Helsinki University Hospital Comprehensive Cancer Center,Helsinki,Finland;Translational Immunology Research Program and Department of Clinical Chemistry and Hematology, University of Helsinki,Helsinki,Finland
,
Stefanie Jilg
Affiliations:
III. Medizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München,München,Germany
,
Philipp J. Jost
Affiliations:
III. Medizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München,München,Germany
,
Stephanie Dulucq
Affiliations:
Laboratory of Hematology , University Hospital of Bordeaux,Bordeaux,France
,
François-Xavier Mahon
Affiliations:
Bergonie institute, INSERM U1218 University of Bordeaux,Bordeaux,France
,
Silvia Cicconi
Affiliations:
Department of Molecular and Clinical Cancer Medicine, University of Liverpool,Liverpool,United Kingdom
,
Richard E. Clark
Affiliations:
Institute of Translational Medicine, University of Liverpool,Liverpool,United Kingdom
,
Artur C. Fassoni
Affiliations:
Instituto de Matemática e Computação, Universidade Federal de Itajubá,Itajubá,Brazil
Ingo Roeder
Affiliations:
TU Dresden,Dresden,Germany;National Center for Tumor Diseases (NCT), Partner Site Dresden,Dresden,Germany
EHA Library. Glauche I. 06/12/20; 294986; S166
Ingmar Glauche
Ingmar Glauche
Contributions
Abstract

Abstract: S166

Type: Oral Presentation

Presentation during EHA25: All oral abstract presentations will be made available on the on-demand Virtual Congress platform as of Friday, June 12 at 08:30 CEST and will be accessible until October 15, 2020.

Session title: Mechanisms and strategies to address TKI resistance and stem cell persistance in CML

Background
Recent clinical findings in chronic myeloid leukemia (CML) patients suggest that the risk of molecular recurrence after stopping tyrosine kinase inhibitor (TKI) treatment substantially depends on an individual’s leukemia-specific immune response. However, it is still not possible to prospectively identify patients that will remain in treatment-free remission (TFR).

Aims
To adapt a patient specific, mathematical model of CML-immune interactions and to apply and verify it for alternative treatment scenarios.

Methods
We suggest a mathematical model for CML, which explicitly includes an anti-leukemic immunological effect and apply it to time course data of 21 CML patients for whom BCR-ABL1/ABL1 measurements have been quantified before and after TKI cessation. Fitting the model simulations to data, we identify patient-specific parameters that allow patient classification as well as model predictions for alternative treatment scenarios, i.e. intermediate dose reduction before treatment cessation.

Results
Implementing immunological control in our mathematical CML model was conceptually necessary to explain TFR as observed in about half of the patients. Fitting the model simulations to data, we identify patient-specific parameters and classify patients into three different groups according to their predicted immune system configuration ('immunological landscapes”). While one class of patients required complete CML eradication to achieve TFR, other patients were able to control residual leukemia levels after treatment cessation. Among them were a third class of patients, that maintained TFR only if an optimal balance between leukemia abundance and immunological activation was achieved before treatment cessation. We further apply the model to study changes in the BCR-ABL1 dynamics resulting from intermediate TKI dose reduction. Our results indicate that the linear slope of the BCR-ABL1 ratios correlates with the risk of recurrence after TKI stop (OR: 1.21, 95% CI: 1.07–1.51) and conveys information about the patient-specific immune system. Our results are in qualitative and quantitative agreement with a recent reanalysis of clinical data from the DESTINY trial (NCT01804985), for which we could demonstrate that the patient-individual slope of BCR-ABL1/ABL1 ratios monitored during TKI dose reduction strongly correlates with the risk of individual recurrence after TKI stop (OR: 1.28; 95% CI: 1.17-1.42).

Conclusion

This inference of individual immunological configurations based on treatment alterations underlines the importance of understanding immunological control mechanisms and acts as a showcase for other cancer types in which the endogenous immune system supports maintenance therapy, long-term disease control or even cure.

 

 

References:

Hähnel T, Baldow C, Guilhot J, Guilhot F, Saussele S, Mustjoki S, Jilg S, Jost PJ, Dulucq S, Mahon FX, Roeder I, Fassoni AC, Glauche I. Model-based inference and classification of immunological control mechanisms from TKI cessation and dose reduction in CML patients. Cancer Res. 2020 Feb 10. doi: 10.1158/0008-5472.CAN-19-2175. [Epub ahead of print]

Gottschalk A, Glauche I, Cicconi S, Clark RE, Roeder I. Molecular dynamics during reduction of TKI dose reliably identify molecular recurrence after treatment cessation in CML. Blood. 2020 Jan 14. doi: 10.1182/blood.2019003395. [Epub ahead of print]

Session topic: 07. Chronic myeloid leukemia - Biology & Translational Research

Keyword(s): Chronic myeloid leukemia, Therapy, Tyrosine kinase inhibitor

Abstract: S166

Type: Oral Presentation

Presentation during EHA25: All oral abstract presentations will be made available on the on-demand Virtual Congress platform as of Friday, June 12 at 08:30 CEST and will be accessible until October 15, 2020.

Session title: Mechanisms and strategies to address TKI resistance and stem cell persistance in CML

Background
Recent clinical findings in chronic myeloid leukemia (CML) patients suggest that the risk of molecular recurrence after stopping tyrosine kinase inhibitor (TKI) treatment substantially depends on an individual’s leukemia-specific immune response. However, it is still not possible to prospectively identify patients that will remain in treatment-free remission (TFR).

Aims
To adapt a patient specific, mathematical model of CML-immune interactions and to apply and verify it for alternative treatment scenarios.

Methods
We suggest a mathematical model for CML, which explicitly includes an anti-leukemic immunological effect and apply it to time course data of 21 CML patients for whom BCR-ABL1/ABL1 measurements have been quantified before and after TKI cessation. Fitting the model simulations to data, we identify patient-specific parameters that allow patient classification as well as model predictions for alternative treatment scenarios, i.e. intermediate dose reduction before treatment cessation.

Results
Implementing immunological control in our mathematical CML model was conceptually necessary to explain TFR as observed in about half of the patients. Fitting the model simulations to data, we identify patient-specific parameters and classify patients into three different groups according to their predicted immune system configuration ('immunological landscapes”). While one class of patients required complete CML eradication to achieve TFR, other patients were able to control residual leukemia levels after treatment cessation. Among them were a third class of patients, that maintained TFR only if an optimal balance between leukemia abundance and immunological activation was achieved before treatment cessation. We further apply the model to study changes in the BCR-ABL1 dynamics resulting from intermediate TKI dose reduction. Our results indicate that the linear slope of the BCR-ABL1 ratios correlates with the risk of recurrence after TKI stop (OR: 1.21, 95% CI: 1.07–1.51) and conveys information about the patient-specific immune system. Our results are in qualitative and quantitative agreement with a recent reanalysis of clinical data from the DESTINY trial (NCT01804985), for which we could demonstrate that the patient-individual slope of BCR-ABL1/ABL1 ratios monitored during TKI dose reduction strongly correlates with the risk of individual recurrence after TKI stop (OR: 1.28; 95% CI: 1.17-1.42).

Conclusion

This inference of individual immunological configurations based on treatment alterations underlines the importance of understanding immunological control mechanisms and acts as a showcase for other cancer types in which the endogenous immune system supports maintenance therapy, long-term disease control or even cure.

 

 

References:

Hähnel T, Baldow C, Guilhot J, Guilhot F, Saussele S, Mustjoki S, Jilg S, Jost PJ, Dulucq S, Mahon FX, Roeder I, Fassoni AC, Glauche I. Model-based inference and classification of immunological control mechanisms from TKI cessation and dose reduction in CML patients. Cancer Res. 2020 Feb 10. doi: 10.1158/0008-5472.CAN-19-2175. [Epub ahead of print]

Gottschalk A, Glauche I, Cicconi S, Clark RE, Roeder I. Molecular dynamics during reduction of TKI dose reliably identify molecular recurrence after treatment cessation in CML. Blood. 2020 Jan 14. doi: 10.1182/blood.2019003395. [Epub ahead of print]

Session topic: 07. Chronic myeloid leukemia - Biology & Translational Research

Keyword(s): Chronic myeloid leukemia, Therapy, Tyrosine kinase inhibitor

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