Identification of genomic biomarkers and their pathway crosstalks for deciphering mechanistic links in glioblastoma

Artificial Intelligence-Assisted Drug and Biomarker Discovery for Glioblastoma: A Scoping Review of the Literature

Background: Artificial intelligence (AI) has emerged as a transformative tool in healthcare, particularly in drug and biomarker discovery, where it can enhance precision, streamline discovery processes, and optimize treatment strategies. Despite its potential, the application of AI in glioblastoma (GB) research, especially in identifying novel biomarkers and therapeutic targets, remains underexplored. The aim of this review is to map the existing literature on AI-driven approaches for biomarker and drug discovery in GB, highlighting key trends and gaps in current research. Design: Following a PRISMA methodology, this scoping review examined studies published between 2012 and 2024. Searches were conducted across multiple databases, including MEDLINE (PubMed), Scopus, the Cochrane Library, and Web of Science (WOS). Eligible studies were screened, and relevant data were extracted and synthesized to provide a comprehensive overview of AI applications in GB research. Results: A total of 224 records were identified, including 210 from PubMed, 104 from Scopus, 4 from WOS, and 6 from the Cochrane Library. After screening and applying eligibility criteria, 33 studies were included in the final review. These studies showcased diverse AI methodologies applied to both drug discovery and biomarker identification, focusing on various aspects of GB biology and treatment. Conclusions: This scoping review reveals an increasing interest in AI-driven strategies for biomarker and drug discovery in GB, with promising initial results. However, further large-scale, rigorous studies are needed to validate real-world applications of AI and the development of standardized protocols to enhance reproducibility and clinical translation.

Hydrogel Applications in the Diagnosis and Treatment of Glioblastoma

Glioblastoma multiforme (GBM), a common malignant neurological tumor, has boundaries indistinguishable from those of normal tissue, making complete surgical removal ineffective. The blood-brain barrier (BBB) further impedes the efficacy of radiotherapy and chemotherapy, leading to suboptimal treatment outcomes and a heightened probability of recurrence. Hydrogels offer multiple advantages for GBM diagnosis and treatment, including overcoming the BBB for improved drug delivery, controlled drug release for long-term efficacy, and enhanced relaxation properties of magnetic resonance imaging (MRI) contrast agents. Hydrogels, with their excellent biocompatibility and customizability, can mimic the in vivo microenvironment, support tumor cell culture, enable drug screening, and facilitate the study of tumor invasion and metastasis. This paper reviews the classification of hydrogels and recent research for the diagnosis and treatment of GBM, including their applications as cell culture platforms and drugs including imaging contrast agents carriers. The mechanisms of drug release from hydrogels and methods to monitor the activity of hydrogel-loaded drugs are also discussed. This review is intended to facilitate a more comprehensive understanding of the current state of GBM research. It offers insights into the design of integrated hydrogel-based GBM diagnosis and treatment with the objective of achieving the desired therapeutic effect and improving the prognosis of GBM.

Bioinformatics Analysis and Experimental Validation for Exploring Key Molecular Markers for Glioblastoma

Glioblastoma (GBM) is the most common primary intracranial malignancy with a very low survival rate. Exploring key molecular markers for GBM can help with early diagnosis, prognostic prediction, and recurrence monitoring. This study aims to explore novel biomarkers for GBM via bioinformatics analysis and experimental verification. Dataset GSE103229 was obtained from the GEO database to search differentially expressed lncRNA (DELs), mRNAs (DEMs), and miRNAs (DEMis). Hub genes were selected to establish competing endogenous RNA (ceRNA) networks. The GEPIA database was employed for the survival analysis and expression detection of hub genes. Hub gene expression in GBM tissue samples and cell lines was validated using RT-qPCR. Western blotting was employed for protein expression evaluation. SYT1 overexpression vector was transfected in GBM cells. CCK-8 assay and flow cytometry were performed to detect the malignant phenotypes of GBM cells. There were 901 upregulated and 1086 downregulated DEMs identified, which were prominently enriched in various malignancy-related functions and pathways. Twenty-two hub genes were selected from PPI networks. Survival analysis and experimental validation revealed that four hub genes were tightly associated with GBM prognosis and progression, including SYT1, GRIN2A, KCNA1, and SYNPR. The four genes were significantly downregulated in GBM tissues and cell lines. Overexpressing SYT1 alleviated the proliferation and promoted the apoptosis of GBM cells in vitro. We identify four genes that may be potential molecular markers of GBM, which may provide new ideas for improving early diagnosis and prediction of the disease.

Click-chemistry mediated synthesis of OTBN-1,2,3-Triazole derivatives exhibiting STK33 inhibition with diverse anti-cancer activities

There is a continuous and pressing need to establish new brain-penetrant bioactive compounds with anti-cancer properties. To this end, a new series of 4'-((4-substituted-4,5-dihydro-1H-1,2,3-triazol-1-yl)methyl)-[1,1'-biphenyl]-2-carbonitrile (OTBN-1,2,3-triazole) derivatives were synthesized by click chemistry. The series of bioactive compounds were designed and synthesized from diverse alkynes and N3-OTBN, using copper (II) acetate monohydrate in aqueous dimethylformamide at room temperature. Besides being highly cost-effective and significantly reducing synthesis, the reaction yielded 91-98 % of the target products without the need of any additional steps or chromatographic techniques. Two analogues exhibit promising anti-cancer biological activities. Analogue 4l shows highly specific cytostatic activity against lung cancer cells, while analogue 4k exhibits pan-cancer anti-growth activity. A kinase screen suggests compound 4k has single-digit micromolar activity against kinase STK33. High STK33 RNA expression correlates strongly with poorer patient outcomes in both adult and pediatric glioma. Compound 4k potently inhibits cell proliferation, invasion, and 3D neurosphere formation in primary patient-derived glioma cell lines. The observed anti-cancer activity is enhanced in combination with specific clinically relevant small molecule inhibitors. Herein we establish a novel biochemical kinase inhibitory function for click-chemistry-derived OTBN-1,2,3-triazole analogues and further report their anti-cancer activity in vitro for the first time.