A novel approach to enhance glioblastoma multiforme treatment efficacy: non-coding RNA targeted therapy and adjuvant approaches

Abstract

Background: Glioblastoma multiforme (GBM) is a lethal brain tumor. With the current gold standard chemotherapy treatment, temozolomide (TMZ), many patients do not survive beyond one year. While the urgency of researching novel treatments is understandable, the prohibitively high costs and the prolonged duration of research and clinical trials significantly delay the availability of medical advancements to the general public. This highlights the urgent need for adjuvant therapies to enhance treatment effectiveness.

Main body: Recent research has suggested the potential of repurposing FDA-approved drugs such as temozolomide (TMZ), disulfiram (DSF), and aspirin for the treatment of glioblastoma, with encouraging evidence particularly for DSF and aspirin. Additionally, compounds like histone deacetylase inhibitors (e.g., vorinostat) are being investigated for their impact on non-coding RNA (ncRNA) modulation, including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). Combining traditional therapies with ncRNA modulation has shown potential in enhancing therapeutic efficacy and targeting specificity. NcRNAs play a crucial role in regulating gene expression and have been implicated in tumor growth, invasion, and treatment resistance. Recent discoveries, such as cuproptosis, offer new insights into tumor cell death mechanisms.

Conclusion: This review focuses on how these molecular insights can serve as novel therapeutic targets and how drug adjuvant therapy may improve GBM treatment strategies. It focuses on how the integration of ncRNA modulation with conventional therapies and the combination strategy of enhancing efficacy of drugs can enhance treatment efficacy and pave the way for innovative approaches in managing GBM. In short, we will explore how non-coding RNAs (ncRNAs) might serve as promising targets and how repurposing TMZ, DSF, and aspirin could help enhance the efficacy of GBM treatment.

Keywords: Aspirin; Cuproptosis; Disulfiram; Glioblastoma multiforme; Non-coding RNA; Temozolomide.

Fig. 1

The chemical structure and detailed mechanism of the medical effect of TMZ. The left part shows that temozolomide is metabolized to its active form MTIC by esterase and carbonic anhydrase. MTIC causes DNA damage by double strand breaks to tumor cells and induces apoptosis. The right part shows that MTIC binds to DNA through an additional reaction, resulting in DNA double-strand breaks. The antitumor activity of TMZ begins with the hydrolysis of its tetrazine ring under basic conditions. This reaction transforms TMZ into the active intermediate 3-methyl-(triazen-1-yl) imidazole-4-carboxamide (MTIC), accompanied by the release of H₂O and CO₂. Under acidic conditions, MTIC further degrades into 5-aminoimidazole-4-carboxamide (AIC) and a highly reactive methyl diazonium ion (CH3N2+) [45, 47]

Fig. 2

Antitumor mechanisms of Disulfiram/Copper adjuvant therapy. Disulfiram acts on cancer-initiating cells by inhibiting ALDH, preventing their growth and leading to cell cycle arrest and cell apoptosis. At the same time, the copper-disulfiram complex (DSF/Cu²⁺) induces the generation of ROS, destroys the DNA structure, and causes DNA damage and DNA double-strand breaks. In addition, the complex further enhances the apoptosis of tumor cells by regulating the NF-κB and MAPK signaling pathways

Fig. 3

Antitumor mechanisms of Aspirin. Aspirin inhibits the production of prostaglandins by blocking COX activity, thereby affecting various biological processes related to tumor progression. Specifically, by reducing the synthesis of prostaglandins, aspirin effectively inhibits tumor cell proliferation, cancer-related inflammation, and platelet-driven carcinogenesis. In addition, aspirin promotes DNA repair and induces tumor cell apoptosis, while inhibiting angiogenesis, further preventing tumor growth and spread

Fig. 4

The latest developments and advancements of repurposing traditional drugs against GB. The success rate of traditional drug repurposing is improved by selecting patient biomarkers, among which the success rate of new anticancer drugs is 3.4% and that of orphan drugs is 1.2%. After biomarker screening, the success rate can be increased to 10.7% [113]. At the same time, machine learning plays an important role in drug development, promoting the simulation of drug-target interactions through new target identification and chemical structure optimization, and combining CRISPR technology to achieve precise RNA editing [117]