Prospective Prediction of Treatment Response in High-Grade Glioma Patients using Pre-Treatment Tumor ADC Value and miR-222 and miR-205 Expression Levels in Plasma

Abstract

Background: Treatment response in High-grade Glioma (HGG) patients changes based on their genetic and biological characteristics. MiRNAs, as important regulators of drug and radiation resistance, and the Apparent Diffusion Coefficients (ADC) value of tumor can be used as a prognostic predictor for glioma.Objective: This study aimed to identify some of the pre-treatment individual patient features for predicting the treatment response in HGG patients.Material and Methods: In this prospective study, 18 HGG patients, who were candidated for chemo-radiation treatment, participated after informed consent of the patients. The investigated features were the expression level of miR-222 and miR-205 in plasma, the ADC value of tumor, Body Mass Index (BMI), and age. Treatment response was assessed, and Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to obtain a model to predict the treatment response. Mann-Whitney U test was also applied to select the variables with a significant relationship with patients’ treatment response.Results: The LASSO coefficients for miR-205, miR-222, tumor’s mean ADC value, BMI, and age were 3.611, -1.683, 2.468, -0.184, and -0.024, respectively. Mann-Whitney U test results showed miR-205 and tumor’s mean ADC significantly related to treatment response (P-value˂0.05). Conclusion: The miR-205 expression level of the patient in plasma and tumor’s mean ADC value has the potential for prognostic predictors in HGG.

Keywords

• micrornas
• adc map
• regression analysis
• lasso model
• glioma