Targeting Tumor Suppressor Genes for Cancer Therapy

Dear Colleagues,

Tumor suppressor genes (TSGs) are crucial components of the genome that regulate cell growth and maintain genomic stability. They encode proteins that act as safeguards, preventing uncontrolled cell proliferation by inducing cell cycle arrest; promote DNA repair; and trigger programmed cell death (apoptosis) in response to cellular stress or genomic injury. Aberrations in their function, through mutations, deletions, or epigenetic silencing, or their normal regulatory mechanisms breaking down can increase the risk of uncontrolled cell division, which is a key event in cancer initiation and progression.

Recent advances in cancer therapy leverage this knowledge to develop precision medicine approaches that restore or mimic TSG function. Key oncogenic signaling pathways commonly deregulated upon TSG loss include PI3K/AKT/mTOR and Wnt/β-catenin, which drive tumor cell survival, proliferation, and metastasis. Targeting these pathways through small molecules, monoclonal antibodies, or combined therapies enhances tumor suppression and treatment efficacy.

Innovative modalities include gene replacement therapy, RNA interference (RNAi) for gene silencing, and CRISPR-Cas9-mediated genome editing to correct mutations or reactivate wild-type TSGs. Immunotherapeutic strategies such as engineered CAR-T cells and immune checkpoint inhibitors are also being combined with TSG-targeting approaches to modulate the tumor microenvironment (TME) and overcome resistance mechanisms. Recent research highlights the potential of allogeneic “off-the-shelf” CAR-T therapies and non-viral delivery systems (e.g., lipid nanoparticles) to improve safety, accessibility, and delivery efficiency.

Despite this progress, challenges remain, including tumor heterogeneity, delivery barriers, immune evasion, and off-target effects. Future research should integrate multi-omics analyses and artificial intelligence (AI)-driven predictive modeling, focusing on combinational regimens that simultaneously target genetic (AI) and machine learning (ML). These new technologies are poised to revolutionize the field by optimizing therapeutic design, predicting drug responses, and personalizing treatment strategies based on tumor heterogeneity and patient-specific data. These strategies hold promise in the development of personalized cancer therapy.

This Special Issue will advance our understanding of the molecular mechanisms underlying TSG inactivation and dysfunction across diverse cancer types and will explore innovative therapeutic strategies aimed at restoring TSG activity. Emphasizing recent discoveries, including gene editing, RNA interference, and immunotherapy approaches, we aim to present state-of-the-art developments in targeting TSGs to improve clinical outcomes. Additionally, it will focus on the interplay between TSGs and the TME, the challenges of tumor heterogeneity, and resistance mechanisms. A special emphasis will be placed on emerging technologies, such as AI and ML, which hold promise in optimizing targeted therapies and personalizing cancer treatment. Ultimately, we aim to foster interdisciplinary research and stimulate novel approaches that could revolutionize cancer therapy by effectively harnessing tumor-suppressive pathways.

Dr. Jogendra Pawar
Dr. Smita Kumari
Dr. Naseem Akhter
Guest Editors

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