BIOM-35. A NEW PRECISION-MEDICINE APPROACH TO PREDICT TUMOR TREATMENT RESPONSE IDENTIFIES IN GLIOBLASTOMA A 17 GENE SIGNATURE PROGNOSTIC OF TMZ RESPONSE AND SURVIVAL WITH ROBUST PREDICTIVE VALUE
Аннотация:Abstract The Glioblastoma (GB) field has been experiencing a therapeutic standstill since 2005, primarily due to ineffective preclinical approaches to test anti-cancer treatments. Therefore, better treatment screening approaches are required. We developed a NADH FLIM-based functional precision medicine approach, that within one week after surgery identified two groups of TMZ Responder and Non-Responder tumors. A 17 gene molecular signature able to classify with 100% precision the TMZ responder and non-responder samples was discovered and identified by Kaplan Meier analysis, a Low-Risk and a High-Risk survival group, interrogating the TCGA GB database (Hazard Ratio = 1.87 p=0.00098,n=148) and TCGA LGG database (Hazard Ratio = 7.66 p=1.197e−35, n=660). Same results were obtained in the CCGA datasets. The 17 gene signature power for independently predicting prognosis (Hazard Ratio = 1.9, p=0.002) was then confirmed by direct RNAseq analysis of a separate clinically characterized cohort of 235 GB patients. Then, we combined the methylation status of the MGMT promoter to analyze the survival status of patients. The survival analysis based on the 17 gene risk signature and MGMT promoter methylation status demonstrated remarkable stratification of the clinical courses into four subgroups. Patients with MGMT promoter unmethylation and 17 gene High-Risk score had the worst prognosis, while patients with MGMT promoter methylation and 17 gene Low-Risk score had the best prognosis. In the latter group, a significant 24-month increase in survival was observed with 10% of 100 months Long Survivors with a difference of 35 months compared to the other groups. Our data indicate a new statistically strong RNAseq-based prognostic survival and TMZ response tool for patients with malignant glioma. The accuracy of this functional precision medicine approach allowed the development of a new prognostic gene signature that can improve the clinical management of GB patients. The approach could be implemented on other cancers as well.
