2378 Proteomics 2012, 12, 2378–2390 DOI 10.1002/pmic.201200002 RESEARCH ARTICLE Investigation of serum proteome alterations in human glioblastoma multiforme Kishore Gollapalli 1 , Sandipan Ray 1 , Rajneesh Srivastava 1 , Durairaj Renu 2 , Prateek Singh 2 , Snigdha Dhali 3 , Jyoti Bajpai Dikshit 2 , Rapole Srikanth 3 , Aliasgar Moiyadi 4 and Sanjeeva Srivastava 1 1 Department of Biosciences and Bioengineering, Wadhwani Research Center for Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai, India 2 Strand Life Sciences Pvt. Ltd., Kirloskar Business Park, Hebbal, Bangalore, India 3 Proteomics Laboratory, National Centre for Cell Science, Ganeshkhind, Pune, India 4 Department of Neurosurgery, Advanced Center for Treatment Research and Education in Cancer, Tata Memorial Center, Kharghar, Navi Mumbai, India Glioblastoma multiforme (GBM) or grade IV astrocytoma is the most common and lethal adult malignant brain tumor. The present study was conducted to investigate the alterations in the serum proteome in GBM patients compared to healthy controls. Comparative proteomic anal- ysis was performed employing classical 2DE and 2D-DIGE combined with MALDI TOF/TOF MS and results were further validated through Western blotting and immunoturbidimetric as- say. Comparison of the serum proteome of GBM and healthy subjects revealed 55 differentially expressed and statistically significant (p <0.05) protein spots. Among the identified proteins, haptoglobin, plasminogen precursor, apolipoprotein A-1 and M, and transthyretin are very significant due to their functional consequences in glioma tumor growth and migration, and could further be studied as glioma biomarkers and grade-specific protein signatures. Anal- ysis of the lipoprotein pattern indicated elevated serum levels of cholesterol, triacylglycerol, and low-density lipoproteins in GBM patients. Functional pathway analysis was performed using multiple software including ingenuity pathway analysis (IPA), protein analysis through evolutionary relationships (PANTHER), database for annotation, visualization and integrated discovery (DAVID), and GeneSpring to investigate the biological context of the identified pro- teins, which revealed the association of candidate proteins in a few essential physiological pathways such as intrinsic prothrombin activation pathway, plasminogen activating cascade, coagulation system, glioma invasiveness signaling, and PI3K signaling in B lymphocytes. A subset of the differentially expressed proteins was applied to build statistical sample class pre- diction models for discrimination of GBM patients and healthy controls employing partial least squares discriminant analysis (PLS-DA) and other machine learning methods such as support vector machine (SVM), Decision Tree and Na¨ ıve Bayes, and excellent discrimination between GBM and control groups was accomplished. Keywords: Biomedicine / 2D-DIGE / Glioblastoma multiforme / Glioma / Serum biomarker Received: January 3, 2012 Revised: April 9, 2012 Accepted: April 23, 2012 Correspondence: Professor Sanjeeva Srivastava, Department of Biosciences and Bioengineering, IIT Bombay, Mumbai 400 076, India E-mail: sanjeeva@iitb.ac.in Fax: +91-22-2572-3480 Abbreviations: DT, Decision Tree; GBM, glioblastoma multi- forme; HC, healthy control; IPA, ingenuity pathway analysis; NB, Naive Bayes; PLS-DA, partial least squares discriminant analysis; SVM, support vector machine 1 Introduction Uncontrolled proliferation of the glial cells result in the for- mation of tumors in brain; known as gliomas, which is con- sidered as one of the prime causes of cancer-related fatality [1, 2]. According to the WHO classification, gliomas can be Colour Online: See the article online to view Figs. 1–4 in colour. C  2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com