Krishanthan Vigneswaran1, Stewart Neill1, Costas G Hadjipanayis1. 1. 1 Department of Neurosurgery; 2 Department of Pathology, Brain Tumor Nanotechnology Laboratory, Winship Cancer Institute of Emory University, Emory University School of Medicine Atlanta, GA 30322, USA.
Abstract
BACKGROUND: Traditional classification of diffuse infiltrating gliomas (DIGs) as World Health Organization (WHO) grades II-IV is based on histological features of a heterogeneous population of tumors with varying prognoses and treatments. Over the last decade, research efforts have resulted in a better understanding of the molecular basis of glioma formation as well as the genetic alterations commonly identified in diffuse gliomas. METHODS: A systematic review of the current literature related to advances in molecular phenotypes, mutations, and genomic analysis of gliomas was carried out using a PubMed search for these key terms. Data was studied and synthesized to generate a comprehensive review of glioma subclassification. RESULTS: This new data helps supplement the existing WHO grading scale by subtyping gliomas into specific molecular groups. The emerging molecular profile of diffuse gliomas includes the studies of gene expression and DNA methylation in different glioma subtypes. The discovery of novel mutations in isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2) provides new biomarkers as points of stratification of gliomas based on prognosis and treatment response. Gliomas that harbor CpG island hypermethylator phenotypes constitute a subtype of glioma with improved survival. The difficulty of classifying oligodendroglial lineage of tumors can be aided with identification of 1p/19q codeletion. Glioblastomas (GBMs) previously described as primary or secondary can now be divided based on gene expression into proneural, mesenchymal, and classical subtypes and the identification of mutations in the promoter region of the telomerase reverse transcriptase (TERTp) have been correlated with poor prognosis in GBMs. CONCLUSIONS: Incorporation of new molecular and genomic changes into the existing WHO grading of DIGs may provide better patient prognostication as well as advance the development of patient-specific treatments and clinical trials.
BACKGROUND: Traditional classification of diffuse infiltrating gliomas (DIGs) as World Health Organization (WHO) grades II-IV is based on histological features of a heterogeneous population of tumors with varying prognoses and treatments. Over the last decade, research efforts have resulted in a better understanding of the molecular basis of glioma formation as well as the genetic alterations commonly identified in diffuse gliomas. METHODS: A systematic review of the current literature related to advances in molecular phenotypes, mutations, and genomic analysis of gliomas was carried out using a PubMed search for these key terms. Data was studied and synthesized to generate a comprehensive review of glioma subclassification. RESULTS: This new data helps supplement the existing WHO grading scale by subtyping gliomas into specific molecular groups. The emerging molecular profile of diffuse gliomas includes the studies of gene expression and DNA methylation in different glioma subtypes. The discovery of novel mutations in isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2) provides new biomarkers as points of stratification of gliomas based on prognosis and treatment response. Gliomas that harbor CpG island hypermethylator phenotypes constitute a subtype of glioma with improved survival. The difficulty of classifying oligodendroglial lineage of tumors can be aided with identification of 1p/19q codeletion. Glioblastomas (GBMs) previously described as primary or secondary can now be divided based on gene expression into proneural, mesenchymal, and classical subtypes and the identification of mutations in the promoter region of the telomerase reverse transcriptase (TERTp) have been correlated with poor prognosis in GBMs. CONCLUSIONS: Incorporation of new molecular and genomic changes into the existing WHO grading of DIGs may provide better patient prognostication as well as advance the development of patient-specific treatments and clinical trials.
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