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

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

Mohammad Hamza Bajwa1, Altaf Ali Laghari1, Sufiyan Sufiyan2, Wajiha Amin2, Arsalan Ahmed3, Syed Hani Abidi4, Ahmed Gilani3, Nouman Mughal2,5,6, Syed Ather Enam1,6

1Section of Neurosurgery, The Aga Khan University, Karachi, Pakistan; 2Department of Surgery, The Aga Khan University, Karachi, Pakistan; 3Department of Histopathology, The Aga Khan University, Karachi, Pakistan; 4School of Medicine, Nazarbayev University, Astana, Kazakhstan; 5Department of Biological and Biomedical Sciences, The Aga Khan University, Karachi, Pakistan; 6Center of Oncological Research in Surgery, The Aga Khan University, Karachi, Pakistan

Correspondence to: Syed Ather Enam, SI, MD, PhD, FRCSI, FRCSC, FRCSG, FACS. Professor of Neurosurgery, Director, Center of Oncological Research in Surgery, The Aga Khan University, National Stadium Road, Aga Khan University Hospital, 3500 Karachi, Sindh, Pakistan; Section of Neurosurgery, The Aga Khan University, Karachi, Pakistan. Email: ather.enam@aku.edu; Nouman Mughal, PhD. Assistant Professor, Department of Biological and Biomedical Sciences, The Aga Khan University, National Stadium Road, Karachi, Pakistan; Center of Oncological Research in Surgery, The Aga Khan University, National Stadium Road, Aga Khan University Hospital, 3500 Karachi, Sindh, Pakistan; Department of Surgery, The Aga Khan University, Karachi, Pakistan. Email: muhammad.nouman@aku.edu.

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.

Keywords: Glioma; neuro-oncology; glioblastoma; molecular epidemiology


Acknowledgments

Funding: None.


Footnote

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://cco.amegroups.com/article/view/10.21037/cco-24-ab059/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013) and approved by the Aga Khan University ERC (No. 2021-1945-17282). Written informed consent was obtained from patients.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the noncommercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.


Cite this abstract as: Bajwa MH, Laghari AA, Sufiyan S, Amin W, Ahmed A, Abidi SH, Gilani A, Mughal N, Enam SA. AB059. Molecular signatures for survival prediction in glioma: a prospective, real-world data analysis. Chin Clin Oncol 2024;13(Suppl 1):AB059. doi: 10.21037/cco-24-ab059

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