Tumor Model for the Development of Anti-Cancer Drugs
A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Molecular Cancer Biology".
Deadline for manuscript submissions: closed (30 April 2026) | Viewed by 686
Special Issue Editor
Special Issue Information
Dear Colleagues,
Preclinical tumor models play a crucial role in advancing our understanding of cancer biology and the development of effective anti-cancer therapies. Conventional 2D cell lines and animal models, while historically valuable, often fail to capture the complexity of the human tumor microenvironment, tumor heterogeneity, and immune interactions. To bridge this translational gap, researchers are increasingly turning to more physiologically relevant platforms—including 3D organoids, patient-derived xenografts (PDX), syngeneic models, tumor-on-chip technologies, and 3D bioprinting systems.
This Special Issue aims to explore recent advances in the development and application of innovative preclinical tumor models for anti-cancer drug discovery and evaluation. It is aligned with the scope of the Cancers journal, which emphasizes translational and preclinical oncology. We welcome contributions that showcase how these models can be used to study tumor biology, identify novel therapeutic targets, test drug efficacy, predict treatment responses, and develop biomarker-guided strategies.
In this Special Issue, original research articles and review papers are welcome. We seek to compile a multidisciplinary collection that reflects diverse modeling systems, cancer types, and therapeutic approaches—including immunotherapy, chemotherapy, targeted therapy, and combination regimens.
Topics of Interest
We invite original research and review articles on (but not limited to) the following themes, with a focus on emerging and high-impact preclinical tumor models and their applications:
- Next-generation tumor models for precision oncology: development and optimization of advanced tumor, modes including cancer organoids, spheroids, patient-derived xenograft (PDX), tumor-on-chip systems, and 3D bioprinting platforms. Studies on AI-driven modeling and computational approaches for treatment outcomes are also warmly welcomed.
- Applications in drug discovery and personalized therapy: organoids-based personalized drug screening, PDX and AI-enhanced models for drug efficacy evaluation, and integration of high-throughput screening assay.
- Modeling challenging and understudied cancer areas: preclinical modeling of rare cancers, tumor models to study mechanisms of drug resistance, immune–tumor interaction studies in syngeneic, humanized, and immune-competent models.
- Microenvironment-integrated systems: co-culture systems (tumor–stromal, tumor–immune) and engineered extracellular matrices mimicking the tumor niche, and organ-on-chip platforms replicating dynamic tumor–microenvironment interactions.
- Future perspectives: translating innovative tumor modeling technologies into clinical trial design, combining AI analytics, multi-omics integration, and functional assays for next-generation preclinical oncology research.
We look forward to receiving your valuable contributions.
Prof. Dr. Joohee Jung
Guest Editor
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.
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Keywords
- tumor models
- preclinical cancer models
- organoids and spheroids
- patient-derived xenografts (PDX)
- syngeneic models
- 3D bioprinting (tumors)
- tumor-on-chip
- drug development
- cancer immunotherapy
- targeted therapy
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