Cancer remains a major global health challenge, accounting for millions of deaths each year despite rapid advances in diagnostics and therapeutics. The pharmacology of anti-cancer agents is central to improving clinical outcomes, requiring an integrated understanding of how drugs engage targets, distribute within tissues, and trigger desired biological effects. However, persistent barriers—including tumor heterogeneity, intrinsic and acquired resistance, limited drug specificity, and dose-limiting toxicities—continue to restrict therapeutic success. Recent breakthroughs in molecular oncology and chemical biology have expanded therapeutic strategies beyond conventional cytotoxic agents to include cell surface–targeted therapies—such as antibody–drug conjugates (ADCs), CAR-T cells, radioligand therapies, and monoclonal antibodies—as well as intracellularly targeted therapies, including small-molecule inhibitors, targeted protein degraders (e.g., PROTACs, molecular glues), RNA-based drugs, and emerging nucleic acid–guided systems. Together, these advances highlight an urgent need to dissect the mechanistic basis of drug action, from target engagement at the cell surface to modulation within intracellular signaling networks, enabling the rational design of safer and more effective anti-cancer interventions.

This Research Topic aims to deepen the mechanistic and translational understanding of anti-cancer drug pharmacology across cell surface and intracellular targets. We seek studies that reveal how therapeutic agents interact with membrane antigens, intracellular proteins, nucleic acids, or metabolic pathways, and how the tumor microenvironment, immune landscape, and patient-specific genomic factors shape therapeutic responses. Key scientific questions include optimizing pharmacokinetic and pharmacodynamic profiles, elucidating determinants of sensitivity and resistance, identifying predictive biomarkers, and designing rational drug combinations or engineered formulations that maximize efficacy while minimizing systemic toxicity. Interdisciplinary contributions that combine experimental pharmacology, structural and computational biology, medicinal chemistry, systems pharmacology, nanomedicine, and translational oncology are particularly encouraged. By integrating mechanistic discoveries with therapeutic innovation, this collection aims to accelerate precision oncology and support the development of next-generation targeted therapies.

This collection covers all aspects of anti-cancer drug pharmacology across preclinical, translational, and clinical research. Topics of interest include mechanisms of action for cytotoxic, antigen-directed targeted, immunotherapeutic, and protein degradation–targeted agents; pharmacokinetics and pharmacodynamics; molecular and cellular drivers of drug resistance; drug combinations and engineered formulations; biomarker-guided therapy; and advances in nanomedicine, computational pharmacology, and drug delivery.

We welcome Original Research Articles, Reviews, Mini Reviews, Perspectives, Brief Research Reports, and Methodology Papers. Submissions may address, but are not limited to, the following themes:

• Mechanisms of action and resistance for cytotoxic, targeted, immune-based, and degradative therapies
• Pharmacokinetics, pharmacodynamics, and drug distribution in complex tumor environments
• Cell surface–targeted therapeutics (ADCs, CAR-T, radioligands, monoclonal antibodies)
• Intracellular-targeted agents (kinase inhibitors, PROTACs, RNA drugs, epigenetic and metabolic modulators)
• Biomarker-guided and pharmacogenomic approaches in precision oncology
• Systems pharmacology, computational modeling, and network-level analyses
• Drug repurposing, rational design, and high-throughput screening of anti-cancer compounds
• Advances in nanomedicine, targeted delivery platforms, and multifunctional therapeutics
• Translational and clinical pharmacology informing patient selection and therapeutic optimization
• AI-driven treatment-response prediction models and computational methods, including deep learning, machine learning, and data-driven risk stratification
• Bioinformatics pipelines for multi-omics integration (genomics, transcriptomics, proteomics, metabolomics) to identify pharmacologically actionable targets and predict treatment response

Submissions providing mechanistic depth, translational relevance, or conceptually innovative therapeutic strategies are especially encouraged.

Please note:

1. The journal endorses protocols including a minimum of 2 cell-lines in vitro as an evidential basis to demonstrate proposed anti-cancer effects in all relevant studies submitted to all specialty sections in the journal.

2. Studies that are purely statistical or predictive in nature, without providing novel insights into pharmacological mechanisms or drug development, are not within the scope of this journal.

3. Frontiers’ journals require that manuscripts primarily comprising computational studies of public data, such as NHANES or Mendelian Randomization studies, must include appropriate validation. Please refer to the Frontiers Standards for research methodology policy, for more information. Manuscripts not adhering to these standards will not be considered.

Are you interested in contributing a manuscript to this Research Topic?

Integrated Targeted Therapies for Cell Surface and Intracellular Targets