Innovative Strategies for the Discovery of New Therapeutic Targets in Cancer Treatment

Despite significant advances in cancer diagnosis and treatment, tumor recurrence, metastasis, and drug resistance remain major clinical challenges. These are associated with the high heterogeneity of cancer, whose key contributors are the presence of a subpopulation of cells, named cancer stem cells (CSCs), able to self-renew and escape conventional anticancer therapies, and the peculiar tumor microenvironment (TME) often hypoxic. Thus, traditional anticancer agents, usually targeting rapidly dividing cells, are inefficacious in most cases, highlighting the urgent need for the development of innovative, targeted approaches.

This Research Topic aims to bring together cutting-edge research focused on the identification and validation of novel therapeutic targets for anticancer drug development, with a specific emphasis on strategies aimed at eradicating CSCs based on small molecule multitargeting agents and gene therapy-related approaches.

It welcomes original research and comprehensive reviews related to:

• Rational drug design and structure-based approaches, including computer-aided drug design (CADD), virtual screening, in silico studies, and machine learning-driven drug discovery;

• Biological evaluation of anticancer compounds through in vitro, ex vivo, and in vivo assays and including models in compliance with the 3Rs (Replacement, Reduction, and Refinement);

• Drug repurposing and repositioning approaches

• Innovative approaches for multitargeting and PROTACs-based agents;

• Combinatorial therapies, integrating small molecules, biologics, gene therapy (e.g., nucleic acid-based strategies such as siRNA, miRNA), or immunotherapeutic agents;

• Identification and validation of innovative biomarkers of CSCs and tumor heterogeneity;

• Bioinformatics studies revealing molecular signatures, signaling pathways, and targetable enzymes in cancer; however, Bioinformatics articles will only be considered if they have biological validation;

• Preclinical and clinical studies, focusing on translational aspects and patient stratification based on molecular profiles;

• Innovative analytic methods to identify biomarkers and tools to assist drug discovery, including MS and NMR studies and biosensor-related approaches.

Contributions are encouraged from multidisciplinary perspectives, including medicinal, computational, and analytical chemistry, pharmacology, molecular biology, biochemistry, bioinformatics, clinical research, and translational medicine.

By fostering interdisciplinary dialogue, this Research Topic aims to accelerate the discovery and development of next-generation anticancer therapies capable of overcoming resistance and preventing relapse.




Please note that manuscripts consisting solely of bioinformatics or computational analysis of public omics databases that are not supplemented by relevant functional validation (clinical cohort or biological validation, in vitro or in vivo) are out of scope for this Research Topic.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Systematic Review
• Technology and Code

Keywords: Bioinformatics; biomarkers, cancer stem cells, combination therapy, drug design, drug repurposing, drug resistance, gene therapy, in silico, machine learning, multitargeting, PROTAC, rational drug design, translational oncology, tumor heterogeneity

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.