Constitutive Interferon Pathway Activation in Tumors as an Efficacy Determinant Following Oncolytic Virotherapy

Cheyne Kurokawa, Ianko D. Iankov, S. Keith Anderson, Ileana Aderca, Alexey A. Leontovich, Matthew J. Maurer, Ann L Oberg, Mark A. Schroeder, Caterina Giannini, Suzanne M. Greiner, Marc A. Becker, E Aubrey Thompson, Paul Haluska, Mark E. Jentoft, Ian F Parney, Saravut (John) Weroha, Jin Jen, Jann N Sarkaria, Evanthia Galanis

Research output: Contribution to journalArticle

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Abstract

Background: Attenuated measles virus (MV) strains are promising agents currently being tested against solid tumors or hematologic malignancies in ongoing phase I and II clinical trials; factors determining oncolytic virotherapy success remain poorly understood, however.

Methods: We performed RNA sequencing and gene set enrichment analysis to identify pathways differentially activated in MV-resistant (n = 3) and -permissive (n = 2) tumors derived from resected human glioblastoma (GBM) specimens and propagated as xenografts (PDX). Using a unique gene signature we identified, we generated a diagonal linear discriminant analysis (DLDA) classification algorithm to predict MV responders and nonresponders, which was validated in additional randomly selected GBM and ovarian cancer PDX and 10 GBM patients treated with MV in a phase I trial. GBM PDX lines were also treated with the US Food and Drug Administration-approved JAK inhibitor, ruxolitinib, for 48 hours prior to MV infection and virus production, STAT1/3 signaling and interferon stimulated gene expression was assessed. All statistical tests were two-sided.

Results: Constitutive interferon pathway activation, as reflected in the DLDA algorithm, was identified as the key determinant for MV replication, independent of virus receptor expression, in MV-permissive and -resistant GBM PDXs. Using these lines as the training data for the DLDA algorithm, we confirmed the accuracy of our algorithm in predicting MV response in randomly selected GBM PDX ovarian cancer PDXs. Using the DLDA prediction algorithm, we demonstrate that virus replication in patient tumors is inversely correlated with expression of this resistance gene signature (ρ = -0.717, P = .03). In vitro inhibition of the interferon response pathway with the JAK inhibitor ruxolitinib was able to overcome resistance and increase virus production (1000-fold, P = .03) in GBM PDX lines.

Conclusions: These findings document a key mechanism of tumor resistance to oncolytic MV therapy and describe for the first time the development of a prediction algorithm to preselect for oncolytic treatment or combinatorial strategies.

Original languageEnglish (US)
Pages (from-to)1123-1132
Number of pages10
JournalJournal of the National Cancer Institute
Volume110
Issue number10
DOIs
StatePublished - Oct 1 2018

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Oncolytic Virotherapy
Measles virus
Interferons
Glioblastoma
Heterografts
Discriminant Analysis
Neoplasms
Virus Replication
Ovarian Neoplasms
Viruses
RNA Sequence Analysis
Virus Receptors
Phase II Clinical Trials
Clinical Trials, Phase I
Virus Diseases
Hematologic Neoplasms
United States Food and Drug Administration
Transcriptome
Genes

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

Constitutive Interferon Pathway Activation in Tumors as an Efficacy Determinant Following Oncolytic Virotherapy. / Kurokawa, Cheyne; Iankov, Ianko D.; Anderson, S. Keith; Aderca, Ileana; Leontovich, Alexey A.; Maurer, Matthew J.; Oberg, Ann L; Schroeder, Mark A.; Giannini, Caterina; Greiner, Suzanne M.; Becker, Marc A.; Thompson, E Aubrey; Haluska, Paul; Jentoft, Mark E.; Parney, Ian F; Weroha, Saravut (John); Jen, Jin; Sarkaria, Jann N; Galanis, Evanthia.

In: Journal of the National Cancer Institute, Vol. 110, No. 10, 01.10.2018, p. 1123-1132.

Research output: Contribution to journalArticle

Kurokawa, C, Iankov, ID, Anderson, SK, Aderca, I, Leontovich, AA, Maurer, MJ, Oberg, AL, Schroeder, MA, Giannini, C, Greiner, SM, Becker, MA, Thompson, EA, Haluska, P, Jentoft, ME, Parney, IF, Weroha, SJ, Jen, J, Sarkaria, JN & Galanis, E 2018, 'Constitutive Interferon Pathway Activation in Tumors as an Efficacy Determinant Following Oncolytic Virotherapy', Journal of the National Cancer Institute, vol. 110, no. 10, pp. 1123-1132. https://doi.org/10.1093/jnci/djy033
Kurokawa, Cheyne ; Iankov, Ianko D. ; Anderson, S. Keith ; Aderca, Ileana ; Leontovich, Alexey A. ; Maurer, Matthew J. ; Oberg, Ann L ; Schroeder, Mark A. ; Giannini, Caterina ; Greiner, Suzanne M. ; Becker, Marc A. ; Thompson, E Aubrey ; Haluska, Paul ; Jentoft, Mark E. ; Parney, Ian F ; Weroha, Saravut (John) ; Jen, Jin ; Sarkaria, Jann N ; Galanis, Evanthia. / Constitutive Interferon Pathway Activation in Tumors as an Efficacy Determinant Following Oncolytic Virotherapy. In: Journal of the National Cancer Institute. 2018 ; Vol. 110, No. 10. pp. 1123-1132.
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title = "Constitutive Interferon Pathway Activation in Tumors as an Efficacy Determinant Following Oncolytic Virotherapy",
abstract = "Background: Attenuated measles virus (MV) strains are promising agents currently being tested against solid tumors or hematologic malignancies in ongoing phase I and II clinical trials; factors determining oncolytic virotherapy success remain poorly understood, however.Methods: We performed RNA sequencing and gene set enrichment analysis to identify pathways differentially activated in MV-resistant (n = 3) and -permissive (n = 2) tumors derived from resected human glioblastoma (GBM) specimens and propagated as xenografts (PDX). Using a unique gene signature we identified, we generated a diagonal linear discriminant analysis (DLDA) classification algorithm to predict MV responders and nonresponders, which was validated in additional randomly selected GBM and ovarian cancer PDX and 10 GBM patients treated with MV in a phase I trial. GBM PDX lines were also treated with the US Food and Drug Administration-approved JAK inhibitor, ruxolitinib, for 48 hours prior to MV infection and virus production, STAT1/3 signaling and interferon stimulated gene expression was assessed. All statistical tests were two-sided.Results: Constitutive interferon pathway activation, as reflected in the DLDA algorithm, was identified as the key determinant for MV replication, independent of virus receptor expression, in MV-permissive and -resistant GBM PDXs. Using these lines as the training data for the DLDA algorithm, we confirmed the accuracy of our algorithm in predicting MV response in randomly selected GBM PDX ovarian cancer PDXs. Using the DLDA prediction algorithm, we demonstrate that virus replication in patient tumors is inversely correlated with expression of this resistance gene signature (ρ = -0.717, P = .03). In vitro inhibition of the interferon response pathway with the JAK inhibitor ruxolitinib was able to overcome resistance and increase virus production (1000-fold, P = .03) in GBM PDX lines.Conclusions: These findings document a key mechanism of tumor resistance to oncolytic MV therapy and describe for the first time the development of a prediction algorithm to preselect for oncolytic treatment or combinatorial strategies.",
author = "Cheyne Kurokawa and Iankov, {Ianko D.} and Anderson, {S. Keith} and Ileana Aderca and Leontovich, {Alexey A.} and Maurer, {Matthew J.} and Oberg, {Ann L} and Schroeder, {Mark A.} and Caterina Giannini and Greiner, {Suzanne M.} and Becker, {Marc A.} and Thompson, {E Aubrey} and Paul Haluska and Jentoft, {Mark E.} and Parney, {Ian F} and Weroha, {Saravut (John)} and Jin Jen and Sarkaria, {Jann N} and Evanthia Galanis",
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T1 - Constitutive Interferon Pathway Activation in Tumors as an Efficacy Determinant Following Oncolytic Virotherapy

AU - Kurokawa, Cheyne

AU - Iankov, Ianko D.

AU - Anderson, S. Keith

AU - Aderca, Ileana

AU - Leontovich, Alexey A.

AU - Maurer, Matthew J.

AU - Oberg, Ann L

AU - Schroeder, Mark A.

AU - Giannini, Caterina

AU - Greiner, Suzanne M.

AU - Becker, Marc A.

AU - Thompson, E Aubrey

AU - Haluska, Paul

AU - Jentoft, Mark E.

AU - Parney, Ian F

AU - Weroha, Saravut (John)

AU - Jen, Jin

AU - Sarkaria, Jann N

AU - Galanis, Evanthia

PY - 2018/10/1

Y1 - 2018/10/1

N2 - Background: Attenuated measles virus (MV) strains are promising agents currently being tested against solid tumors or hematologic malignancies in ongoing phase I and II clinical trials; factors determining oncolytic virotherapy success remain poorly understood, however.Methods: We performed RNA sequencing and gene set enrichment analysis to identify pathways differentially activated in MV-resistant (n = 3) and -permissive (n = 2) tumors derived from resected human glioblastoma (GBM) specimens and propagated as xenografts (PDX). Using a unique gene signature we identified, we generated a diagonal linear discriminant analysis (DLDA) classification algorithm to predict MV responders and nonresponders, which was validated in additional randomly selected GBM and ovarian cancer PDX and 10 GBM patients treated with MV in a phase I trial. GBM PDX lines were also treated with the US Food and Drug Administration-approved JAK inhibitor, ruxolitinib, for 48 hours prior to MV infection and virus production, STAT1/3 signaling and interferon stimulated gene expression was assessed. All statistical tests were two-sided.Results: Constitutive interferon pathway activation, as reflected in the DLDA algorithm, was identified as the key determinant for MV replication, independent of virus receptor expression, in MV-permissive and -resistant GBM PDXs. Using these lines as the training data for the DLDA algorithm, we confirmed the accuracy of our algorithm in predicting MV response in randomly selected GBM PDX ovarian cancer PDXs. Using the DLDA prediction algorithm, we demonstrate that virus replication in patient tumors is inversely correlated with expression of this resistance gene signature (ρ = -0.717, P = .03). In vitro inhibition of the interferon response pathway with the JAK inhibitor ruxolitinib was able to overcome resistance and increase virus production (1000-fold, P = .03) in GBM PDX lines.Conclusions: These findings document a key mechanism of tumor resistance to oncolytic MV therapy and describe for the first time the development of a prediction algorithm to preselect for oncolytic treatment or combinatorial strategies.

AB - Background: Attenuated measles virus (MV) strains are promising agents currently being tested against solid tumors or hematologic malignancies in ongoing phase I and II clinical trials; factors determining oncolytic virotherapy success remain poorly understood, however.Methods: We performed RNA sequencing and gene set enrichment analysis to identify pathways differentially activated in MV-resistant (n = 3) and -permissive (n = 2) tumors derived from resected human glioblastoma (GBM) specimens and propagated as xenografts (PDX). Using a unique gene signature we identified, we generated a diagonal linear discriminant analysis (DLDA) classification algorithm to predict MV responders and nonresponders, which was validated in additional randomly selected GBM and ovarian cancer PDX and 10 GBM patients treated with MV in a phase I trial. GBM PDX lines were also treated with the US Food and Drug Administration-approved JAK inhibitor, ruxolitinib, for 48 hours prior to MV infection and virus production, STAT1/3 signaling and interferon stimulated gene expression was assessed. All statistical tests were two-sided.Results: Constitutive interferon pathway activation, as reflected in the DLDA algorithm, was identified as the key determinant for MV replication, independent of virus receptor expression, in MV-permissive and -resistant GBM PDXs. Using these lines as the training data for the DLDA algorithm, we confirmed the accuracy of our algorithm in predicting MV response in randomly selected GBM PDX ovarian cancer PDXs. Using the DLDA prediction algorithm, we demonstrate that virus replication in patient tumors is inversely correlated with expression of this resistance gene signature (ρ = -0.717, P = .03). In vitro inhibition of the interferon response pathway with the JAK inhibitor ruxolitinib was able to overcome resistance and increase virus production (1000-fold, P = .03) in GBM PDX lines.Conclusions: These findings document a key mechanism of tumor resistance to oncolytic MV therapy and describe for the first time the development of a prediction algorithm to preselect for oncolytic treatment or combinatorial strategies.

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