Improved prediction of radiation pneumonitis by combining biological and radiobiological parameters using a data-driven Bayesian network analysis

Tonaye Hinton; David Karnak; Ming Tang; Ralph Jiang; Yi Luo; Philip Boonstra; Yilun Sun; Derek J. Nancarrow; Erin Sandford; Paramita Ray; Christopher Maurino; Martha Matuszak; Matthew J. Schipper; Michael D. Green; Gregory A. Yanik; Muneesh Tewari; Issam El Naqa; Caitlin A. Schonewolf; Randall Ten Haken; Shruti Jolly; Theodore S. Lawrence; Dipankar Ray

Translational Oncology (Jul 2022)

Improved prediction of radiation pneumonitis by combining biological and radiobiological parameters using a data-driven Bayesian network analysis

Tonaye Hinton,
David Karnak,
Ming Tang,
Ralph Jiang,
Yi Luo,
Philip Boonstra,
Yilun Sun,
Derek J. Nancarrow,
Erin Sandford,
Paramita Ray,
Christopher Maurino,
Martha Matuszak,
Matthew J. Schipper,
Michael D. Green,
Gregory A. Yanik,
Muneesh Tewari,
Issam El Naqa,
Caitlin A. Schonewolf,
Randall Ten Haken,
Shruti Jolly,
Theodore S. Lawrence,
Dipankar Ray

Affiliations

Tonaye Hinton: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA
David Karnak: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA
Ming Tang: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA; Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
Ralph Jiang: Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
Yi Luo: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA
Philip Boonstra: Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
Yilun Sun: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA; Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
Derek J. Nancarrow: Department of Surgery, Division of Hematology-Oncology, Department of Internal Medicine, Medical School, University of Michigan, Ann Arbor, MI, USA
Erin Sandford: Division of Hematology and Oncology, Department of Internal Medicine, Henry Ford Cancer Institute/Henry Ford Hospital, Detroit, MI, USA
Paramita Ray: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA
Christopher Maurino: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA
Martha Matuszak: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA
Matthew J. Schipper: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA; Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
Michael D. Green: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA
Gregory A. Yanik: Division of Hematology and Oncology, Department of Internal Medicine, Henry Ford Cancer Institute/Henry Ford Hospital, Detroit, MI, USA
Muneesh Tewari: Division of Hematology and Oncology, Department of Internal Medicine, Henry Ford Cancer Institute/Henry Ford Hospital, Detroit, MI, USA
Issam El Naqa: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA
Caitlin A. Schonewolf: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA
Randall Ten Haken: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA
Shruti Jolly: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA
Theodore S. Lawrence: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA
Dipankar Ray: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA; Corresponding author at: Department of Radiation Oncology, Medical School, The University of Michigan Medical School, University of Michigan, Ann Arbor, MI 48109–2026, USA.

Journal volume & issue: Vol. 21
p. 101428

Abstract

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Grade 2 and higher radiation pneumonitis (RP2) is a potentially fatal toxicity that limits efficacy of radiation therapy (RT). We wished to identify a combined biomarker signature of circulating miRNAs and cytokines which, along with radiobiological and clinical parameters, may better predict a targetable RP2 pathway. In a prospective clinical trial of response-adapted RT for patients (n = 39) with locally advanced non-small cell lung cancer, we analyzed patients’ plasma, collected pre- and during RT, for microRNAs (miRNAs) and cytokines using array and multiplex enzyme linked immunosorbent assay (ELISA), respectively. Interactions between candidate biomarkers, radiobiological, and clinical parameters were analyzed using data-driven Bayesian network (DD-BN) analysis. We identified alterations in specific miRNAs (miR-532, -99b and -495, let-7c, -451 and -139-3p) correlating with lung toxicity. High levels of soluble tumor necrosis factor alpha receptor 1 (sTNFR1) were detected in a majority of lung cancer patients. However, among RP patients, within 2 weeks of RT initiation, we noted a trend of temporary decline in sTNFR1 (a physiological scavenger of TNFα) and ADAM17 (a shedding protease that cleaves both membrane-bound TNFα and TNFR1) levels. Cytokine signature identified activation of inflammatory pathway. Using DD-BN we combined miRNA and cytokine data along with generalized equivalent uniform dose (gEUD) to identify pathways with better accuracy of predicting RP2 as compared to either miRNA or cytokines alone. This signature suggests that activation of the TNFα-NFκB inflammatory pathway plays a key role in RP which could be specifically ameliorated by etanercept rather than current therapy of non-specific leukotoxic corticosteroids.

Published in Translational Oncology

ISSN: 1944-7124 (Print); 1936-5233 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Medicine: Internal medicine: Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Website: https://www.journals.elsevier.com/translational-oncology/

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