Review on Immunological Biomarkers in Gliomas

Abstract

Gliomas are the most common subgroup of primary malignant brain tumors in adults, constituting >40% of all primary CNS neoplasms. Although all gliomas originate from neuroepithelial tissues, they vary considerably in morphology, location, genetic alterations and in their response to therapy. The most malignant of gliomas (Grade IV) is Glioblastoma Multiforme (GBM), causing over 10,000 deaths each year in the US alone. Despite robust therapeutic advances, median survival for GBM still remains 14-20 months with very high tumor recurrence rate. Various investigation modalities are available for establishing diagnosis of glioma, like: CT scan, MRI, X-ray, spinal tap, angiogram, myelogram & biopsy, though, histopathology represents the gold standard for their typing & grading. However, even this remains unsatisfactory because of the lack of reproducibility and absence of precision. Development of objective, diagnostic, prognostic & predictive markers for these lethal neoplasms is therefore a priority. Biomarkers for glioma can be identified in various biological samples like: DNA, mRNA, cell surface receptors, transcription factors, secretory proteins, metabolites or processes such as proliferation, angiogenesis or apoptosis. Tumor biomarkers help oncologists in managing gliomas at various levels, from screening till assessment of longitudinal response to therapy. Identifying the molecular & pathogenetic characteristics of glioma regulation network may increase the precision of customized medication. Further, the proteomic approach has the potential to identify novel diagnostic, prognostic and therapeutic biomarkers. In the near future, improved proteomic profiling is anticipated to bring about a merger of biology, engineering and informatics, with a profound impact on glioma research and treatment. Optimization of experimental design and validation in independent cohorts, improved multiplex proteomic methodologies and bioinformatics tools, and their integration with genetic and metabolomic profiling technologies promise to play critical roles in the post proteomics era of cancer diagnosis and treatment.