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Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics
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| Zeitschriftentitel: | Physiological Genomics |
|---|---|
| Personen und Körperschaften: | , , , , , , , , , , , |
| In: | Physiological Genomics, 46, 2014, 13, S. 467-481 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
American Physiological Society
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| Schlagwörter: |
| author_facet |
Heroux, Maxime S. Chesnik, Marla A. Halligan, Brian D. Al-Gizawiy, Mona Connelly, Jennifer M. Mueller, Wade M. Rand, Scott D. Cochran, Elizabeth J. LaViolette, Peter S. Malkin, Mark G. Schmainda, Kathleen M. Mirza, Shama P. Heroux, Maxime S. Chesnik, Marla A. Halligan, Brian D. Al-Gizawiy, Mona Connelly, Jennifer M. Mueller, Wade M. Rand, Scott D. Cochran, Elizabeth J. LaViolette, Peter S. Malkin, Mark G. Schmainda, Kathleen M. Mirza, Shama P. |
|---|---|
| author |
Heroux, Maxime S. Chesnik, Marla A. Halligan, Brian D. Al-Gizawiy, Mona Connelly, Jennifer M. Mueller, Wade M. Rand, Scott D. Cochran, Elizabeth J. LaViolette, Peter S. Malkin, Mark G. Schmainda, Kathleen M. Mirza, Shama P. |
| spellingShingle |
Heroux, Maxime S. Chesnik, Marla A. Halligan, Brian D. Al-Gizawiy, Mona Connelly, Jennifer M. Mueller, Wade M. Rand, Scott D. Cochran, Elizabeth J. LaViolette, Peter S. Malkin, Mark G. Schmainda, Kathleen M. Mirza, Shama P. Physiological Genomics Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics Genetics Physiology |
| author_sort |
heroux, maxime s. |
| spelling |
Heroux, Maxime S. Chesnik, Marla A. Halligan, Brian D. Al-Gizawiy, Mona Connelly, Jennifer M. Mueller, Wade M. Rand, Scott D. Cochran, Elizabeth J. LaViolette, Peter S. Malkin, Mark G. Schmainda, Kathleen M. Mirza, Shama P. 1094-8341 1531-2267 American Physiological Society Genetics Physiology http://dx.doi.org/10.1152/physiolgenomics.00034.2014 <jats:p>Cancer is a complex disease; glioblastoma (GBM) is no exception. Short survival, poor prognosis, and very limited treatment options make it imperative to unravel the disease pathophysiology. The critically important identification of proteins that mediate various cellular events during disease is made possible with advancements in mass spectrometry (MS)-based proteomics. The objective of our study is to identify and characterize proteins that are differentially expressed in GBM to better understand their interactions and functions that lead to the disease condition. Further identification of upstream regulators will provide new potential therapeutic targets. We analyzed GBM tumors by SDS-PAGE fractionation with internal DNA markers followed by liquid chromatography-tandem mass spectrometry (MS). Brain tissue specimens obtained for clinical purposes during epilepsy surgeries were used as controls, and the quantification of MS data was performed by label-free spectral counting. The differentially expressed proteins were further characterized by Ingenuity Pathway Analysis (IPA) to identify protein interactions, functions, and upstream regulators. Our study identified several important proteins that are involved in GBM progression. The IPA revealed glioma activation with z score 2.236 during unbiased core analysis. Upstream regulators STAT3 and SP1 were activated and CTNNα was inhibited. We verified overexpression of several proteins by immunoblot to complement the MS data. This work represents an important step towards the identification of GBM biomarkers, which could open avenues to identify therapeutic targets for better treatment of GBM patients. The workflow developed represents a powerful and efficient method to identify biomarkers in GBM.</jats:p> Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics Physiological Genomics |
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| title |
Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics |
| title_unstemmed |
Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics |
| title_full |
Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics |
| title_fullStr |
Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics |
| title_full_unstemmed |
Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics |
| title_short |
Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics |
| title_sort |
comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics |
| topic |
Genetics Physiology |
| url |
http://dx.doi.org/10.1152/physiolgenomics.00034.2014 |
| publishDate |
2014 |
| physical |
467-481 |
| description |
<jats:p>Cancer is a complex disease; glioblastoma (GBM) is no exception. Short survival, poor prognosis, and very limited treatment options make it imperative to unravel the disease pathophysiology. The critically important identification of proteins that mediate various cellular events during disease is made possible with advancements in mass spectrometry (MS)-based proteomics. The objective of our study is to identify and characterize proteins that are differentially expressed in GBM to better understand their interactions and functions that lead to the disease condition. Further identification of upstream regulators will provide new potential therapeutic targets. We analyzed GBM tumors by SDS-PAGE fractionation with internal DNA markers followed by liquid chromatography-tandem mass spectrometry (MS). Brain tissue specimens obtained for clinical purposes during epilepsy surgeries were used as controls, and the quantification of MS data was performed by label-free spectral counting. The differentially expressed proteins were further characterized by Ingenuity Pathway Analysis (IPA) to identify protein interactions, functions, and upstream regulators. Our study identified several important proteins that are involved in GBM progression. The IPA revealed glioma activation with z score 2.236 during unbiased core analysis. Upstream regulators STAT3 and SP1 were activated and CTNNα was inhibited. We verified overexpression of several proteins by immunoblot to complement the MS data. This work represents an important step towards the identification of GBM biomarkers, which could open avenues to identify therapeutic targets for better treatment of GBM patients. The workflow developed represents a powerful and efficient method to identify biomarkers in GBM.</jats:p> |
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| author | Heroux, Maxime S., Chesnik, Marla A., Halligan, Brian D., Al-Gizawiy, Mona, Connelly, Jennifer M., Mueller, Wade M., Rand, Scott D., Cochran, Elizabeth J., LaViolette, Peter S., Malkin, Mark G., Schmainda, Kathleen M., Mirza, Shama P. |
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| description | <jats:p>Cancer is a complex disease; glioblastoma (GBM) is no exception. Short survival, poor prognosis, and very limited treatment options make it imperative to unravel the disease pathophysiology. The critically important identification of proteins that mediate various cellular events during disease is made possible with advancements in mass spectrometry (MS)-based proteomics. The objective of our study is to identify and characterize proteins that are differentially expressed in GBM to better understand their interactions and functions that lead to the disease condition. Further identification of upstream regulators will provide new potential therapeutic targets. We analyzed GBM tumors by SDS-PAGE fractionation with internal DNA markers followed by liquid chromatography-tandem mass spectrometry (MS). Brain tissue specimens obtained for clinical purposes during epilepsy surgeries were used as controls, and the quantification of MS data was performed by label-free spectral counting. The differentially expressed proteins were further characterized by Ingenuity Pathway Analysis (IPA) to identify protein interactions, functions, and upstream regulators. Our study identified several important proteins that are involved in GBM progression. The IPA revealed glioma activation with z score 2.236 during unbiased core analysis. Upstream regulators STAT3 and SP1 were activated and CTNNα was inhibited. We verified overexpression of several proteins by immunoblot to complement the MS data. This work represents an important step towards the identification of GBM biomarkers, which could open avenues to identify therapeutic targets for better treatment of GBM patients. The workflow developed represents a powerful and efficient method to identify biomarkers in GBM.</jats:p> |
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| spelling | Heroux, Maxime S. Chesnik, Marla A. Halligan, Brian D. Al-Gizawiy, Mona Connelly, Jennifer M. Mueller, Wade M. Rand, Scott D. Cochran, Elizabeth J. LaViolette, Peter S. Malkin, Mark G. Schmainda, Kathleen M. Mirza, Shama P. 1094-8341 1531-2267 American Physiological Society Genetics Physiology http://dx.doi.org/10.1152/physiolgenomics.00034.2014 <jats:p>Cancer is a complex disease; glioblastoma (GBM) is no exception. Short survival, poor prognosis, and very limited treatment options make it imperative to unravel the disease pathophysiology. The critically important identification of proteins that mediate various cellular events during disease is made possible with advancements in mass spectrometry (MS)-based proteomics. The objective of our study is to identify and characterize proteins that are differentially expressed in GBM to better understand their interactions and functions that lead to the disease condition. Further identification of upstream regulators will provide new potential therapeutic targets. We analyzed GBM tumors by SDS-PAGE fractionation with internal DNA markers followed by liquid chromatography-tandem mass spectrometry (MS). Brain tissue specimens obtained for clinical purposes during epilepsy surgeries were used as controls, and the quantification of MS data was performed by label-free spectral counting. The differentially expressed proteins were further characterized by Ingenuity Pathway Analysis (IPA) to identify protein interactions, functions, and upstream regulators. Our study identified several important proteins that are involved in GBM progression. The IPA revealed glioma activation with z score 2.236 during unbiased core analysis. Upstream regulators STAT3 and SP1 were activated and CTNNα was inhibited. We verified overexpression of several proteins by immunoblot to complement the MS data. This work represents an important step towards the identification of GBM biomarkers, which could open avenues to identify therapeutic targets for better treatment of GBM patients. The workflow developed represents a powerful and efficient method to identify biomarkers in GBM.</jats:p> Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics Physiological Genomics |
| spellingShingle | Heroux, Maxime S., Chesnik, Marla A., Halligan, Brian D., Al-Gizawiy, Mona, Connelly, Jennifer M., Mueller, Wade M., Rand, Scott D., Cochran, Elizabeth J., LaViolette, Peter S., Malkin, Mark G., Schmainda, Kathleen M., Mirza, Shama P., Physiological Genomics, Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics, Genetics, Physiology |
| title | Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics |
| title_full | Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics |
| title_fullStr | Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics |
| title_full_unstemmed | Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics |
| title_short | Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics |
| title_sort | comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics |
| title_unstemmed | Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics |
| topic | Genetics, Physiology |
| url | http://dx.doi.org/10.1152/physiolgenomics.00034.2014 |