Ethical Statement
Informed consent was obtained from the patient’s family or relative. The entire study protocol was approved and supervised by the Medical and Health Research Ethics Committee (MHREC), Universitas Gadjah Mada (UGM), Indonesia (Ref: KE/FK/0878/EC/2023).
Research Subjects
This study retrospectively collected data on newly-diagnosed cases of glioma (n = 18) from Dr. Sardjito General Hospital and its satellite hospitals in Yogyakarta, Indonesia. The data was collected over a period of three years (July 2019-July 2022). Additionally, control samples of healthy people (n = 6) were acquired during this data collection. The cases were divided into two groups based on the 2016 WHO Classification of CNS Tumors, which is LGG and HGG. Written informed consent was obtained from the patient's family or relative. The diagnosis of glioma, including its histopathology, was confirmed by expert neuropathologists from the Department of Anatomical Pathology at Dr. Sardjito General Hospital. Each patient received personalized standardized therapy based on their diagnosis and clinical condition. Basic demographic, clinical, and supportive examinations, such as pathology and radiology, were obtained from medical records. Preoperative blood samples were taken during tumor resection procedures. The entire study protocol was approved by the Medical and Health Research Ethics Committee (MHREC), Universitas Gadjah Mada (UGM), Indonesia (Ref: KE/FK/0878/EC/2023).
Obtaining peripheral blood sample
Blood samples were taken from a peripheral vein or artery using ethylenediamine-tetra acetic acid (EDTA) anticoagulated tubes. To ensure anonymity, all samples were coded according to the ethics protocol. The sample was immediately centrifuged at 3000×g for 10 minutes, and the plasma was separated and stored at -80°C for further analysis. Additionally, the Buffy coat was also extracted and kept for future study purposes.
RNA Isolation and Purification for Nanostring Assay
The plasma samples were thawed at room temperature. Afterwards, total cell-free RNA was extracted from 200 µL of plasma and purified by using the miRNeasy® Serum/Plasma Advanced kit (Qiagen, Germany) according to the standard protocol provided by the manufacturer. To assess the quality of the RNA, a Nanodrop device (Thermo Scientific, Waltham, MA, USA) was used.
Nanostring nCounter Assay and Data Analysis
A NanoString nCounter Human v3 miRNA Expression Assay was conducted on all samples. The assay used 798 unique miRNA barcodes. To perform the analysis, 100 ng total cell-free RNA from each sample was mixed with pairs of capture and reporter probes customized for specific recognition of each miRNA presence. Overnight hybridization at a temperature of 65°C allowed sequence-specific probes to form complexes with targets. Two-step magnetic-beads-based purification on an automated fluidic handling system (nCounter Prep Station, Thermo Scientific, Waltham, MA, USA) was used to remove excess probes, and target-probe complexes were immobilized on the cartridge for data collection. Data collection was carried out on the nCounter Digital Analyzer (NanoString Technologies, Seattle, WA, USA) following the manufacturer's instructions, to count individual fluorescent barcodes and quantify target RNA molecules present in each sample. For each assay, a high-density scan (600 fields of view) was performed.
The NanoString raw data or Reporter Code Counts (RCC) file was analyzed using ROSALIND® (https://rosalind.bio/), which employs a HyperScale architecture developed by ROSALIND, Inc. (San Diego, CA). As part of the quality control step, ROSALIND generated Read Distribution percentages, violin plots, identity heatmaps, and sample MDS plots. Nanostring's criteria were used to calculate normalization, fold changes, and p-values. Background subtraction was performed based on POS_A probe correction factors, followed by normalization in two steps: positive control normalization and codeset normalization. During both normalization steps, the geometric mean of each probeset was used to create a normalization factor. ROSALIND employed the t-test method to calculate fold changes and p-values for comparisons. P-value adjustment was performed using the Benjamini-Hochberg method to estimate false discovery rates (FDR). For the final heatmap of differentially expressed miRNA, clustering was done using the PAM (Partitioning Around Medoids) method with the fpc R library. This method takes into consideration the direction and type of all signals on a pathway, as well as the position, role, and type of every miRNA.
Statistical analysis
Relevant data were extracted from ROSALIND® (https://rosalind.bio/) and statistical analysis was performed using IBM SPSS Ver. 26 to generate demographic data and analysed the correlation between LGG and HGG with candidate miRNA. The first step was to generate boxplots for all unique significantly expressed miRNAs based on ROSALIND® analysis. p-value was determined using Kruskal Wallis Test. ROC-AUC graph were then generated using the normalized expression of candidate miRNA. All significant miRNAs were subjected to univariate analysis using Mann-Whitney Test to determine their correlation with glioma grading. A p-value of less than 0.05 was considered significant in all tests.