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Modeling and Bioinformatics Identify Responders to G-CSF in Patients With Amyotrophic Lateral Sclerosis

Objective: Developing an integrative approach to early treatment response classification using survival modeling and bioinformatics with various biomarkers for early assessment of filgrastim (granulocyte colony stimulating factor) treatment effects in amyotrophic lateral sclerosis (ALS) patients. Fi...

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Autores principales: Johannesen, Siw, Huie, J. Russell, Budeus, Bettina, Peters, Sebastian, Wirth, Anna M., Iberl, Sabine, Kammermaier, Tina, Kobor, Ines, Wirkert, Eva, Küspert, Sabrina, Tahedl, Marlene, Grassinger, Jochen, Pukrop, Tobias, Schneider, Armin, Aigner, Ludwig, Schulte-Mattler, Wilhelm, Schuierer, Gerhard, Koch, Winfried, Bruun, Tim-Henrik, Ferguson, Adam R., Bogdahn, Ulrich
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8012841/
https://www.ncbi.nlm.nih.gov/pubmed/33815246
http://dx.doi.org/10.3389/fneur.2021.616289
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author Johannesen, Siw
Huie, J. Russell
Budeus, Bettina
Peters, Sebastian
Wirth, Anna M.
Iberl, Sabine
Kammermaier, Tina
Kobor, Ines
Wirkert, Eva
Küspert, Sabrina
Tahedl, Marlene
Grassinger, Jochen
Pukrop, Tobias
Schneider, Armin
Aigner, Ludwig
Schulte-Mattler, Wilhelm
Schuierer, Gerhard
Koch, Winfried
Bruun, Tim-Henrik
Ferguson, Adam R.
Bogdahn, Ulrich
author_facet Johannesen, Siw
Huie, J. Russell
Budeus, Bettina
Peters, Sebastian
Wirth, Anna M.
Iberl, Sabine
Kammermaier, Tina
Kobor, Ines
Wirkert, Eva
Küspert, Sabrina
Tahedl, Marlene
Grassinger, Jochen
Pukrop, Tobias
Schneider, Armin
Aigner, Ludwig
Schulte-Mattler, Wilhelm
Schuierer, Gerhard
Koch, Winfried
Bruun, Tim-Henrik
Ferguson, Adam R.
Bogdahn, Ulrich
author_sort Johannesen, Siw
collection PubMed
description Objective: Developing an integrative approach to early treatment response classification using survival modeling and bioinformatics with various biomarkers for early assessment of filgrastim (granulocyte colony stimulating factor) treatment effects in amyotrophic lateral sclerosis (ALS) patients. Filgrastim, a hematopoietic growth factor with excellent safety, routinely applied in oncology and stem cell mobilization, had shown preliminary efficacy in ALS. Methods: We conducted individualized long-term filgrastim treatment in 36 ALS patients. The PRO-ACT database, with outcome data from 23 international clinical ALS trials, served as historical control and mathematical reference for survival modeling. Imaging data as well as cytokine and cellular data from stem cell analysis were processed as biomarkers in a non-linear principal component analysis (NLPCA) to identify individual response. Results: Cox proportional hazard and matched-pair analyses revealed a significant survival benefit for filgrastim-treated patients over PRO-ACT comparators. We generated a model for survival estimation based on patients in the PRO-ACT database and then applied the model to filgrastim-treated patients. Model-identified filgrastim responders displayed less functional decline and impressively longer survival than non-responders. Multimodal biomarkers were then analyzed by PCA in the context of model-defined treatment response, allowing identification of subsequent treatment response as early as within 3 months of therapy. Strong treatment response with a median survival of 3.8 years after start of therapy was associated with younger age, increased hematopoietic stem cell mobilization, less aggressive inflammatory cytokine plasma profiles, and preserved pattern of fractional anisotropy as determined by magnetic resonance diffusion tensor imaging (DTI-MRI). Conclusion: Long-term filgrastim is safe, is well-tolerated, and has significant positive effects on disease progression and survival in a small cohort of ALS patients. Developing and applying a model-based biomarker response classification allows use of multimodal biomarker patterns in full potential. This can identify strong individual treatment responders (here: filgrastim) at a very early stage of therapy and may pave the way to an effective individualized treatment option.
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spelling pubmed-80128412021-04-02 Modeling and Bioinformatics Identify Responders to G-CSF in Patients With Amyotrophic Lateral Sclerosis Johannesen, Siw Huie, J. Russell Budeus, Bettina Peters, Sebastian Wirth, Anna M. Iberl, Sabine Kammermaier, Tina Kobor, Ines Wirkert, Eva Küspert, Sabrina Tahedl, Marlene Grassinger, Jochen Pukrop, Tobias Schneider, Armin Aigner, Ludwig Schulte-Mattler, Wilhelm Schuierer, Gerhard Koch, Winfried Bruun, Tim-Henrik Ferguson, Adam R. Bogdahn, Ulrich Front Neurol Neurology Objective: Developing an integrative approach to early treatment response classification using survival modeling and bioinformatics with various biomarkers for early assessment of filgrastim (granulocyte colony stimulating factor) treatment effects in amyotrophic lateral sclerosis (ALS) patients. Filgrastim, a hematopoietic growth factor with excellent safety, routinely applied in oncology and stem cell mobilization, had shown preliminary efficacy in ALS. Methods: We conducted individualized long-term filgrastim treatment in 36 ALS patients. The PRO-ACT database, with outcome data from 23 international clinical ALS trials, served as historical control and mathematical reference for survival modeling. Imaging data as well as cytokine and cellular data from stem cell analysis were processed as biomarkers in a non-linear principal component analysis (NLPCA) to identify individual response. Results: Cox proportional hazard and matched-pair analyses revealed a significant survival benefit for filgrastim-treated patients over PRO-ACT comparators. We generated a model for survival estimation based on patients in the PRO-ACT database and then applied the model to filgrastim-treated patients. Model-identified filgrastim responders displayed less functional decline and impressively longer survival than non-responders. Multimodal biomarkers were then analyzed by PCA in the context of model-defined treatment response, allowing identification of subsequent treatment response as early as within 3 months of therapy. Strong treatment response with a median survival of 3.8 years after start of therapy was associated with younger age, increased hematopoietic stem cell mobilization, less aggressive inflammatory cytokine plasma profiles, and preserved pattern of fractional anisotropy as determined by magnetic resonance diffusion tensor imaging (DTI-MRI). Conclusion: Long-term filgrastim is safe, is well-tolerated, and has significant positive effects on disease progression and survival in a small cohort of ALS patients. Developing and applying a model-based biomarker response classification allows use of multimodal biomarker patterns in full potential. This can identify strong individual treatment responders (here: filgrastim) at a very early stage of therapy and may pave the way to an effective individualized treatment option. Frontiers Media S.A. 2021-03-18 /pmc/articles/PMC8012841/ /pubmed/33815246 http://dx.doi.org/10.3389/fneur.2021.616289 Text en Copyright © 2021 Johannesen, Huie, Budeus, Peters, Wirth, Iberl, Kammermaier, Kobor, Wirkert, Küspert, Tahedl, Grassinger, Pukrop, Schneider, Aigner, Schulte-Mattler, Schuierer, Koch, Bruun, Ferguson and Bogdahn. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neurology
Johannesen, Siw
Huie, J. Russell
Budeus, Bettina
Peters, Sebastian
Wirth, Anna M.
Iberl, Sabine
Kammermaier, Tina
Kobor, Ines
Wirkert, Eva
Küspert, Sabrina
Tahedl, Marlene
Grassinger, Jochen
Pukrop, Tobias
Schneider, Armin
Aigner, Ludwig
Schulte-Mattler, Wilhelm
Schuierer, Gerhard
Koch, Winfried
Bruun, Tim-Henrik
Ferguson, Adam R.
Bogdahn, Ulrich
Modeling and Bioinformatics Identify Responders to G-CSF in Patients With Amyotrophic Lateral Sclerosis
title Modeling and Bioinformatics Identify Responders to G-CSF in Patients With Amyotrophic Lateral Sclerosis
title_full Modeling and Bioinformatics Identify Responders to G-CSF in Patients With Amyotrophic Lateral Sclerosis
title_fullStr Modeling and Bioinformatics Identify Responders to G-CSF in Patients With Amyotrophic Lateral Sclerosis
title_full_unstemmed Modeling and Bioinformatics Identify Responders to G-CSF in Patients With Amyotrophic Lateral Sclerosis
title_short Modeling and Bioinformatics Identify Responders to G-CSF in Patients With Amyotrophic Lateral Sclerosis
title_sort modeling and bioinformatics identify responders to g-csf in patients with amyotrophic lateral sclerosis
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8012841/
https://www.ncbi.nlm.nih.gov/pubmed/33815246
http://dx.doi.org/10.3389/fneur.2021.616289
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