AB062. Investigating miR-21 as a non-invasive prognostic biomarker in glioma patients.

BACKGROUND: Glioma prognosis remains a challenge due to its high recurrence and resistance to treatment. Diagnosis and follow-up in resource-constrained regions often lead to significant patient attrition. Serum microRNAs (miRNAs) are seen to be aberrantly expressed in malignancies can be found in tumor tissues and peripheral samples. This offers a pathway for non-invasive liquid biopsies. miR-21 is an established biomarker for glioma prognosis, which needs to be validated in our population. METHODS: We collected 89 intraoperative tumor tissue samples, and 42 pre- and post-operative serum samples from glioma patients, ten control tissues, eight healthy serum samples and analysed for miR-21 expression through quantitative polymerase chain reaction (qPCR) analysis. Correlational analysis with molecular markers isocitrate dehydrogenase (IDH), Ki-67, ATRX, p53, and survival curves through the Kaplan-Meier method were calculated in high and low miR-21 expression groups. The hazard ratio was quantitatively determined using Cox regression analysis, considering both univariate associations and multivariate correlations with clinical parameters. RESULTS: miR-21 expression in tissue was significantly upregulated with increase of glioma grades (P<0.001) and in patients above 50 years (P=0.003) age group. Whereas no gender bias was seen in its expression pattern. Its expression did not show any correlation with tumor volume (r=0.22, P=0.08). A similar expression pattern of miR-21 was observed in serum samples of glioma. IDH-wildtype (P=2.06e-03) and high Ki-67 (P=2.50e-03) patient group showed significant upregulation of miR-21 expression compared to IDH-mutant and low Ki-67 group. Patients with low miR-21 expression had significantly longer overall survival (OS) than patients with high miR-21 expression (P =0.006). Similarly, quantitative hazard analysis indicates that patients in the high expression group have 2.77 times higher risk of mortality [95% confidence interval (CI): 0.19-0.92], in comparison to patients in the low expression group (P=0.008). CONCLUSIONS: Our findings validate the utility of miR-21 as a prognostic serum biomarker to help diagnose and assess treatment response in advancing glioma grades, within our population.

AB059. Molecular signatures for survival prediction in glioma: a prospective, real-world data analysis.

BACKGROUND: Glioma characterization and follow-up are underreported from low-and-middle-income country centers within the literature. With the recent emphasis on molecular markers for survival prediction, there is a need for robust data exploring molecular epidemiology in these countries. In Pakistan particularly, there is a significant gap in glioma outcomes reporting and survival analysis. METHODS: One hundred and sixty-five consecutive glioma patients were enrolled from 2019 onwards; histopathological and molecular analysis was performed on archived formalin-fixed paraffin-embedded (FFPE) blocks for isocitrate dehydrogenase (IDH), P53, α-thalassemia retardation X-linked (ATRX) and Ki-67 immunohistochemical (IHC) markers. Survival analysis was calculated using the Kaplan-Meier method; hazard ratios are reported through a multivariate Cox regression model. RESULTS: Fifty-seven (35%) histopathological diagnoses were revised according to the updated criteria; 30% (n=16) glioblastoma were converted to a new category on re-analysis. IDH wild type (IDH-WT) gliomas had a significantly worse overall survival (log-rank =0.002), with a 2-year survival rate of 60% for IDH-mutant (IDH-M) and 38% for IDH-WT. Significant survival differences were seen for the Ki-67 index (log-rank =0.001) and methylguanine methyltransferase (MGMT) promotor methylation [log-rank =0.027, 2-year survival rate: 100% (methylation detected), 33% (methylation not detected)]. On Cox proportional hazards regression, gross total resection (P<0.001), IDH mutation (P<0.001), and updated histopathological diagnosis (P<0.001) were significant predictors of survival, with good sensitivity and specificity as seen on receiver operating characteristic (ROC) analysis [area under the curve (AUC) =0.86]. CONCLUSIONS: In our cohort, the revised World Health Organization (WHO) classification shows significant implications on prognosis and implications for treatment. Although these markers are not commonly used in low-and-middle-income country centers, our results strongly support their greater implementation for improved prognostication and reclassification.

AB060. Autophagy-associated biomarkers ULK2, UVRAG, and miRNAs miR-21, miR-126, and miR-374: prognostic significance in glioma patients.

BACKGROUND: Autophagy is a self-renewing process of the cell having a dual role in gliomagenesis depending on the tumor stage. Several microRNAs play a key role in the regulation of autophagy and the outcome of cancer. We investigated the potential relevance of autophagy in gliomagenesis and survival by exploring the association of the basal gene expression of autophagy-associated markers LC3, ULK1/2, UVRAG, Beclin1, mTOR, UVRAG, PI3K, AKT, PTEN and their target microRNAs miR-126, miR-374, miR-21, miR-7, miR-204 and miR-100 in low- and high-grades of gliomas. METHODS: A total of 50 fresh glioma tissues were used for the extraction of RNA using TRIzol-Chloroform method and reverse transcribed cDNA. The cDNA was used to determine the expression of genes and microRNAs using quantitative real-time polymerase chain reaction (qPCR). Mann-Whitney U-test was used to determine the statistical significance. RESULTS: In high-grade glioma, increased expression of AKT and miR-21, coupled with reduced ULK2 and LC3 expression was distinctly observed. While correlation analysis identified a strong positive correlation between ULK2 and UVRAG, PTEN, miR-7, and miR-100 and a moderate positive correlation emerged between ULK2 and mTOR, miR-7, miR-30, miR-100, miR-204, and miR-374, also between miR-21 and miR-126 in low-grade glioma. Similarly, a positive correlation appeared between ULK2 and AKT, LC3, PI3K, PTEN, ULK1, VPS34, mTOR, Beclin1, UVRAG, miR-7 and miR-374. AKT positively correlated with LC3, PI3K, PTEN, ULK1, VPS34, mTOR, Beclin1, UVRAG, miR-7, miR-30, miR-204, miR-374, miR-126 and miR-21 weakly correlated with AKT and miR-30 in high-grade glioma. The low ULK2, UVRAG, and miR-374 expression group exhibited significantly poor overall survival in glioma, while miR-21 over-expression indicated a poor prognosis in glioma patients. CONCLUSIONS: This study provides comprehensive insights into the molecular landscape of gliomas, highlighting the dysregulation of autophagy genes ULK2, and UVRAG and the associated miR-21, miR-126 and miR-374 as potential prognostic biomarkers and emphasizing their unique significance in shaping survival outcomes in gliomas patients.

Investigating the Association between the Autophagy Markers LC3B, SQSTM1/p62, and DRAM and Autophagy-Related Genes in Glioma.

High-grade gliomas are extremely fatal tumors, marked by severe hypoxia and therapeutic resistance. Autophagy is a cellular degradative process that can be activated by hypoxia, ultimately resulting in tumor advancement and chemo-resistance. Our study aimed to examine the link between autophagy markers' expression in low-grade gliomas (LGGs) and high-grade gliomas (HGGs). In 39 glioma cases, we assessed the protein expression of autophagy markers LC3B, SQSTM1/p62, and DRAM by immunohistochemistry (IHC) and the mRNA expression of the autophagy genes PTEN, PI3K, AKT, mTOR, ULK1, ULK2, UVRAG, Beclin 1, and VPS34 using RT-qPCR. LC3B, SQSTM1/p62, and DRAM expression were positive in 64.1%, 51.3%, and 28.2% of glioma cases, respectively. The expression of LC3B and SQSTM1/p62 was notably higher in HGGs compared to LGGs. VPS34 exhibited a significant differential expression, displaying increased fold change in HGGs compared to LGGs. Additionally, it exhibited robust positive associations with Beclin1 (rs = 0.768), UVRAG (rs = 0.802), and ULK2 (rs = 0.786) in HGGs. This underscores a potential association between autophagy and the progression of gliomas. We provide preliminary data for the functional analysis of autophagy using a cell culture model and to identify potential targets for therapeutic interventions.