Holistic Analysis of Glioblastoma Stem Cell DNA Using Nanoengineered Plasmonic Metasensor for Glioblastoma Diagnosis. Issue 9 (30th July 2022) - Dhinakaran, Ashok Kumar; Ganesh, Swarna; Haldavnekar, Rupa; Tan, Bo; Das, Sunit; Venkatakrishnan, Krishnan
Abstract: The clinical relevance of liquid biopsy for glioblastoma (GBM) remains undetermined due to practical and biological limitations such as absence of a reliable GBM‐specific biomarker, trace levels in circulation due to the blood–brain–barrier, and lack of a sensitive method to detect the trace levels of biomarkers. It is hypothesized that GBM stem cell (GSC)‐associated cell free DNA can function as reliable biomarker for GBM because it accounts for tumor heterogeneity and provide accurate molecular information about the cancer. An integrative methodology is used for GBM diagnosis by utilizing the sub‐single molecular sensitivity of nanoengineered plasmonic metasensors for real‐time genomic profiling of GSC DNA. The nanoengineered metasensors can detect the rare circulating GSC‐DNA accurately from just 5 µL of blood and the test can be performed in under 10 min. Analysis of clinical serum samples from GBM patients and healthy volunteers demonstrates that the technology yielded an accurate classification of GBM in an independent validation cohort (accuracy 98.3%, specificity 100%). The methodology detects GBM‐signatures from the patient blood rapidly within the half‐life period of cfDNA in circulation, non‐invasively and amplification‐free with a high diagnostic accuracy. With clinical validation, this methodology can evolve as a clinically viable diagnostic tool for fatal and hard‐to‐detect cancer like GBM. Abstract : Glioblastoma (GBM) diagnosis using liquid biopsy suffers limitations due to biological and practical limitations. This research introduces nanoengineered plasmonic metasensors with sub‐single molecule level sensitivity to detect GBM biomarkers in blood accurately and in under 10 min. This methodology is noninvasive and amplification free with a high diagnostic accuracy of 98.7%.