An Eighteen Serum Cytokine Signature for Discriminating Glioma from Normal Healthy Individuals

• Published in: PloS one Vol. 10; no. 9; p. e0137524
• Main Authors: Nijaguna, Mamatha B, Patil, Vikas, Hegde, Alangar S, Chandramouli, Bangalore A, Arivazhagan, Arimappamagan, Santosh, Vani, Somasundaram, Kumaravel
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 21.09.2015; Public Library of Science (PLoS)
• Subjects: Accuracy; Adult; Angiogenesis; Astrocytoma; Astrocytoma - blood; Astrocytoma - diagnosis; Bioindicators; Biology; Biomarkers; Biomarkers, Tumor - blood; Brain; Brain - pathology; Brain cancer; Brain Neoplasms - blood; Brain Neoplasms - diagnosis; Cancer therapies; Cytokines; Cytokines - blood; Development and progression; Encyclopedias; Gene expression; Genetic aspects; Genomes; Glioblastoma - blood; Glioblastoma - diagnosis; Glioma; Glioma - blood; Glioma - diagnosis; Gliomas; Humans; Medical diagnosis; Medical imaging; Medical prognosis; Mental health; Middle Aged; Neurosurgery; NMR; Nuclear magnetic resonance; Patients; Physiological aspects; Science; Support Vector Machine; Test sets; Training; Tumors; Young Adult; India
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0137524

Glioblastomas (GBM) are largely incurable as they diffusely infiltrate adjacent brain tissues and are difficult to diagnose at early stages. Biomarkers derived from serum, which can be obtained by minimally invasive procedures, may help in early diagnosis, prognosis and treatment monitoring. To develop a serum cytokine signature, we profiled 48 cytokines in sera derived from normal healthy individuals (n = 26) and different grades of glioma patients (n = 194). We divided the normal and grade IV glioma/GBM serum samples randomly into equal sized training and test sets. In the training set, the Prediction Analysis for Microarrays (PAM) identified a panel of 18 cytokines that could discriminate GBM sera from normal sera with maximum accuracy (95.40%) and minimum error (4.60%). The 18-cytokine signature obtained in the training set discriminated GBM sera from normal sera in the test set as well (accuracy 96.55%; error 3.45%). Interestingly, the 18-cytokine signature also differentiated grade II/Diffuse Astrocytoma (DA) and grade III/Anaplastic Astrocytoma (AA) sera from normal sera very efficiently (DA vs. normal-accuracy 96.00%, error 4.00%; AA vs. normal-accuracy 95.83%, error 4.17%). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using 18 cytokines resulted in the enrichment of two pathways, cytokine-cytokine receptor interaction and JAK-STAT pathways with high significance. Thus our study identified an 18-cytokine signature for distinguishing glioma sera from normal healthy individual sera and also demonstrated the importance of their differential abundance in glioma biology.