Bridging Preclinical Models and Clinical Translation in Combination Cancer Therapies

Despite remarkable advances in cancer research, the translation of promising preclinical discoveries into clinically effective combination therapies remains a major challenge. A key limitation lies in the limited predictive value of conventional experimental models, which often fail to recapitulate the complexity of human tumors, their microenvironment, and their dynamic response to treatment. Consequently, there is an increasing need for preclinical platforms that more faithfully model tumor biology while providing robust and reproducible data to support clinical decision-making.Recent years have witnessed the rapid development of advanced preclinical models, including patient-derived systems, organoids, spheroids, organ-on-chip technologies, the chorioallantoic membrane (CAM) model, and refined in vivo approaches. These platforms offer unprecedented opportunities to investigate tumor heterogeneity, therapeutic response, and tumor–microenvironment interactions. At the same time, the growing complexity of modern oncology, driven by multimodal therapeutic strategies combining radiotherapy, immunotherapy, nanomedicine, hyperthermia, targeted agents, and novel drug combinations, demands experimental models capable of accurately evaluating efficacy, toxicity, and synergistic effects.However, significant challenges remain in standardizing experimental methodologies, identifying predictive biomarkers, understanding mechanisms of resistance, and integrating emerging technologies to enhance the translational value of preclinical research. Addressing these challenges is essential to accelerate the successful implementation of innovative combination therapies into clinical practice.The goal of this Research Topic is to address one of the major bottlenecks in translational oncology: the limited ability of conventional preclinical models to predict the clinical efficacy of increasingly complex combination therapies. Advanced experimental models that more faithfully reproduce tumor heterogeneity, microenvironmental interactions, treatment response, and mechanisms of resistance are essential to improve the selection of therapeutic strategies with genuine translational potential. This Research Topic aims to bring together studies that develop, validate, or apply innovative preclinical platforms to evaluate combination therapies and identify determinants of therapeutic response. By integrating advanced disease modeling with emerging technologies, mechanistic investigation, and clinically relevant endpoints, this collection seeks to strengthen the connection between experimental oncology and patient-oriented research, ultimately promoting more predictive and efficient pathways from preclinical discovery to clinical implementation.This Research Topic welcomes original research articles, reviews, and systematic reviews addressing, but not limited to, the following themes:● Advanced preclinical cancer models, including CAM, organoids, spheroids, organ-on-chip, ex vivo models, murine models and patient-derived models● Combination therapeutic strategies, including radiotherapy, immunotherapy, nanomedicine, hyperthermia, targeted therapies and novel drug combinations● Biomarkers of treatment response, mechanisms of resistance and tumor microenvironment dynamics● Translational studies bridging preclinical discoveries with clinical implementation● Emerging technologies and innovative methodologies enhancing the predictive value of oncology research Topic editors: Patrizia Sarogni, Melissa Santi, Michela Cortesi Source: https://www.frontiersin.org/research-topics/84463/bridging-preclinical-models-and-clinical-translation-in-combination-cancer-therapies