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Sharpnack MF, Ranbaduge N, Srivastava A, et al. Proteogenomic Analysis of Surgically Resected Lung Adenocarcinoma. J Thorac Oncol. 2018;13(10):1519-1529doi: 10.1016/j.jtho.2018.06.025.
Sharpnack, M. F., Ranbaduge, N., Srivastava, A., Cerciello, F., Codreanu, S. G., Liebler, D. C., Mascaux, C., Miles, W. O., Morris, R., McDermott, J. E., Sharpnack, J. L., Amann, J., Maher, C. A., Machiraju, R., Wysocki, V. H., Govindan, R., Mallick, P., Coombes, K. R., Huang, K., & Carbone, D. P. (2018). Proteogenomic Analysis of Surgically Resected Lung Adenocarcinoma. Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer, 13(10), 1519-1529. https://doi.org/10.1016/j.jtho.2018.06.025
Sharpnack, Michael F, et al. "Proteogenomic Analysis of Surgically Resected Lung Adenocarcinoma." Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer vol. 13,10 (2018): 1519-1529. doi: https://doi.org/10.1016/j.jtho.2018.06.025
Sharpnack MF, Ranbaduge N, Srivastava A, Cerciello F, Codreanu SG, Liebler DC, Mascaux C, Miles WO, Morris R, McDermott JE, Sharpnack JL, Amann J, Maher CA, Machiraju R, Wysocki VH, Govindan R, Mallick P, Coombes KR, Huang K, Carbone DP. Proteogenomic Analysis of Surgically Resected Lung Adenocarcinoma. J Thorac Oncol. 2018 Oct;13(10):1519-1529. doi: 10.1016/j.jtho.2018.06.025. Epub 2018 Jul 11. PMID: 30017829; PMCID: PMC7135954.
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J Thorac Oncol. 2018 Oct;13(10):1519-1529. doi: 10.1016/j.jtho.2018.06.025. Epub 2018 Jul 11.

Proteogenomic Analysis of Surgically Resected Lung Adenocarcinoma.

Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer

Michael F Sharpnack, Nilini Ranbaduge, Arunima Srivastava, Ferdinando Cerciello, Simona G Codreanu, Daniel C Liebler, Celine Mascaux, Wayne O Miles, Robert Morris, Jason E McDermott, James L Sharpnack, Joseph Amann, Christopher A Maher, Raghu Machiraju, Vicki H Wysocki, Ramaswami Govindan, Parag Mallick, Kevin R Coombes, Kun Huang, David P Carbone

Affiliations

  1. Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio.
  2. Department of Chemistry, The Ohio State University, Columbus, Ohio.
  3. Department of Computer Science and Engineering, The Ohio State University, Columbus, Ohio.
  4. Department of Oncology, University Hospital Zurich, Zürich, Switzerland.
  5. Department of Chemistry, Vanderbilt University, Nashville, Tennessee.
  6. Department of Biochemistry, Vanderbilt University, Nashville, Tennessee.
  7. Department of Multidisciplinary Oncology and Therapeutic Innovations, Assistance Publique des Hôpitaux de Marseille, France; Aix-Marseille University, Marseille, France.
  8. Center for Regenerative Medicine, Massachusetts General Hospital, Boston, Massachusetts.
  9. Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA.
  10. Department of Statistics, University of California, Davis, California.
  11. Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio.
  12. Department of Medicine, Washington University in St. Louis, St. Louis, Missouri.
  13. Department of Radiology, Stanford University, Palo Alto, California.
  14. Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio. Electronic address: [email protected].

PMID: 30017829 PMCID: PMC7135954 DOI: 10.1016/j.jtho.2018.06.025

Abstract

INTRODUCTION: Despite apparently complete surgical resection, approximately half of resected early-stage lung cancer patients relapse and die of their disease. Adjuvant chemotherapy reduces this risk by only 5% to 8%. Thus, there is a need for better identifying who benefits from adjuvant therapy, the drivers of relapse, and novel targets in this setting.

METHODS: RNA sequencing and liquid chromatography/liquid chromatography-mass spectrometry proteomics data were generated from 51 surgically resected non-small cell lung tumors with known recurrence status.

RESULTS: We present a rationale and framework for the incorporation of high-content RNA and protein measurements into integrative biomarkers and show the potential of this approach for predicting risk of recurrence in a group of lung adenocarcinomas. In addition, we characterize the relationship between mRNA and protein measurements in lung adenocarcinoma and show that it is outcome specific.

CONCLUSIONS: Our results suggest that mRNA and protein data possess independent biological and clinical importance, which can be leveraged to create higher-powered expression biomarkers.

Copyright © 2018 International Association for the Study of Lung Cancer. All rights reserved.

Keywords: Biomarkers; Lung adenocarcinoma; NSCLC; Proteogenomics; Proteomics

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