Combined Proteomic-Molecular Epidemiology Approach to Identify Precision Targets in Brain Cancer
(2018) In ACS Chemical Neuroscience 9(1). p.80-84- Abstract
Primary brain tumors are predominantly malignant gliomas. Grade IV astrocytomas (glioblastomas, GBM) are among the most deadly of all tumors; most patients will succumb to their disease within 2 years of diagnosis despite standard of care. The grim outlook for brain tumor patients indicates that novel precision therapeutic targets must be identified. Our hypothesis is that the cancer proteomes of glioma tumors may contain protein variants that are linked to the aggressive pathology of the disease. To this end, we devised a novel workflow that combined variant proteomics with molecular epidemiological mining of public cancer data sets to identify 10 previously unrecognized variants linked to the risk of death in low grade glioma or GBM.... (More)
Primary brain tumors are predominantly malignant gliomas. Grade IV astrocytomas (glioblastomas, GBM) are among the most deadly of all tumors; most patients will succumb to their disease within 2 years of diagnosis despite standard of care. The grim outlook for brain tumor patients indicates that novel precision therapeutic targets must be identified. Our hypothesis is that the cancer proteomes of glioma tumors may contain protein variants that are linked to the aggressive pathology of the disease. To this end, we devised a novel workflow that combined variant proteomics with molecular epidemiological mining of public cancer data sets to identify 10 previously unrecognized variants linked to the risk of death in low grade glioma or GBM. We hypothesize that a subset of the protein variants may be successfully developed in the future as novel targets for malignant gliomas.
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- author
- Mostovenko, Ekaterina ; Liu, Yanhong ; Amirian, E. Susan ; Tsavachidis, Spiridon ; Armstrong, Georgina N. ; Bondy, Melissa L. and Nilsson, Carol L. LU
- organization
- publishing date
- 2018-01-17
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- drug target, GBM, Glioblastoma, molecular epidemiology, precision medicine, proteomic
- in
- ACS Chemical Neuroscience
- volume
- 9
- issue
- 1
- pages
- 5 pages
- publisher
- The American Chemical Society (ACS)
- external identifiers
-
- scopus:85040670652
- pmid:28657708
- ISSN
- 1948-7193
- DOI
- 10.1021/acschemneuro.7b00165
- language
- English
- LU publication?
- yes
- id
- 95a30486-91ef-4910-a96e-329caa2d4c07
- date added to LUP
- 2018-01-30 11:07:09
- date last changed
- 2024-01-14 14:23:32
@article{95a30486-91ef-4910-a96e-329caa2d4c07,
abstract = {{<p>Primary brain tumors are predominantly malignant gliomas. Grade IV astrocytomas (glioblastomas, GBM) are among the most deadly of all tumors; most patients will succumb to their disease within 2 years of diagnosis despite standard of care. The grim outlook for brain tumor patients indicates that novel precision therapeutic targets must be identified. Our hypothesis is that the cancer proteomes of glioma tumors may contain protein variants that are linked to the aggressive pathology of the disease. To this end, we devised a novel workflow that combined variant proteomics with molecular epidemiological mining of public cancer data sets to identify 10 previously unrecognized variants linked to the risk of death in low grade glioma or GBM. We hypothesize that a subset of the protein variants may be successfully developed in the future as novel targets for malignant gliomas.</p>}},
author = {{Mostovenko, Ekaterina and Liu, Yanhong and Amirian, E. Susan and Tsavachidis, Spiridon and Armstrong, Georgina N. and Bondy, Melissa L. and Nilsson, Carol L.}},
issn = {{1948-7193}},
keywords = {{drug target; GBM; Glioblastoma; molecular epidemiology; precision medicine; proteomic}},
language = {{eng}},
month = {{01}},
number = {{1}},
pages = {{80--84}},
publisher = {{The American Chemical Society (ACS)}},
series = {{ACS Chemical Neuroscience}},
title = {{Combined Proteomic-Molecular Epidemiology Approach to Identify Precision Targets in Brain Cancer}},
url = {{http://dx.doi.org/10.1021/acschemneuro.7b00165}},
doi = {{10.1021/acschemneuro.7b00165}},
volume = {{9}},
year = {{2018}},
}