MPTH-56. ALGORITHM BASED LIQUID BIOPSY FOR THE DIAGNOSIS OF GLIOBLASTOMA

Abstract

AIM: The aim of this study was to develop an algorithm that would accurately diagnose, offer therapy management options and help in the monitoring of recurrence in patients with glioblastoma. METHODS: In a prospective study, after ethics committee approval, ninety samples and fifty controls were collected from Apollo Hospitals. All patients had lesions that had the radiological appearance of a high grade glioma. All patients had attempted radical resections. Blood samples were drawn after written consent either on the day or on the day before surgery. Pathological diagnosis was considered to be the gold standard. Liquid biopsy was performed using the 'Next Gen Sequencing' platform. Analysis was based on the data obtained from analysis of exosomal RNA, cell free DNA and micro RNA. The lab was blinded to the results of the biopsy till the entire study was completed. RESULTS: Big data analysis revealed 19 different markers that can help in the diagnosis, pathway analysis and recurrence monitoring of glioblastoma. This included EGFR amplification, PDGFR amplification, NF1 mutation, TP53 mutation, PTEN mutation etc and microRNAs miR-27a, 210, 124, 210 etc. 48 tumors were diagnosed to be GBMs by the pathologists. All 48 were diagnosed on liquid biopsy as well. 27 tumors were diagnosed as grade 3. Liquid biopsy identified 24 as grade 3 and 3 as GBMs. The rest were Grade 2 according to pathology. Of these, there were 15 tumors. However, 3 were classified as GBMs and 4 were thought to be grade 3 tumors. All control samples were negative. CONCLUSION: Liquid biopsy can play an important role in the diagnosis of patients with gliomas and reduce the under reporting of high grade gliomas caused by tumor heterogeneity.