Unknown

Dataset Information

0

Quantitative proteomic analysis of meningiomas for the identification of surrogate protein markers.


ABSTRACT: Meningiomas are the most common non-glial tumors of the brain and spine. Pathophysiology and definite histological grading of meningiomas are frequently found to be deceptive due to their unusual morphological features and locations. Here for the first time we report a comprehensive serum proteomic analysis of different grades of meningiomas by using multiple quantitative proteomic and immunoassay-based approaches to obtain mechanistic insights about disease pathogenesis and identify grade specific protein signatures. In silico functional analysis revealed modulation of different vital physiological pathways including complement and coagulation cascades, metabolism of lipids and lipoproteins, immune signaling, cell growth and apoptosis and integrin signaling in meningiomas. ROC curve analysis demonstrated apolipoprotein E and A-I and hemopexin as efficient predictors for meningiomas. Identified proteins like vimentin, alpha-2-macroglobulin, apolipoprotein B and A-I and antithrombin-III, which exhibited a sequential increase in different malignancy grades of meningiomas, could serve as potential predictive markers.

SUBMITTER: Sharma S 

PROVIDER: S-EPMC5382771 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

altmetric image

Publications

Quantitative proteomic analysis of meningiomas for the identification of surrogate protein markers.

Sharma Samridhi S   Ray Sandipan S   Moiyadi Aliasgar A   Sridhar Epari E   Srivastava Sanjeeva S  

Scientific reports 20141121


Meningiomas are the most common non-glial tumors of the brain and spine. Pathophysiology and definite histological grading of meningiomas are frequently found to be deceptive due to their unusual morphological features and locations. Here for the first time we report a comprehensive serum proteomic analysis of different grades of meningiomas by using multiple quantitative proteomic and immunoassay-based approaches to obtain mechanistic insights about disease pathogenesis and identify grade speci  ...[more]

Similar Datasets

| S-EPMC3415403 | biostudies-literature
| S-EPMC2360009 | biostudies-literature
| S-EPMC6682208 | biostudies-literature
| S-EPMC4278831 | biostudies-literature
| S-EPMC5119459 | biostudies-literature
| S-EPMC3735238 | biostudies-literature
| 2339705 | ecrin-mdr-crc
| S-EPMC4026414 | biostudies-literature
| S-EPMC3964225 | biostudies-literature
| S-EPMC4783941 | biostudies-literature