ReviewJournal of biomedical science2026
Tumor-on-chip's alliance with molecular pathology against metastatic disease.
Review in Journal of biomedical science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Synthesis and In Vitro Anticancer Activity of New Acridone Derivatives: Computational DFT and Molecular Docking Studies.Chemistry & biodiversity · 2026Article
- Targeting the cancer metabolism-immunity interface: update and perspectives.Experimental hematology & oncology · 2026Review
- Prostatic fibroblast reprogramming by Interleukin-30 activates prostate cancer metastasis programs.Molecular biomedicine · 2026Article
- Modeling and targeting the hostile physicochemical niche in bone metastasis: from experimental platforms to niche-directed therapy.Frontiers in cell and developmental biology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
backgroundCancer is the second leading cause of death worldwide. While significant progress has been made in early detection and treatment, metastasis remains the major cause of cancer-related morbidity and mortality. In the last decade the rate of long-term survivorship of metastatic cancer has continued to improve and overcoming resistance to therapy has now become a challenge. Developing strategies to prevent and treat metastatic disease is a priority for public health and requires a thorough understanding of the mechanisms driving progression of a specific patient's tumor and the rapid identification of targetable cancer drivers and drug resistance genes. DISCUSSION: Custom bioprinted tumors, which recreate the interactions between tumors and surrounding tissues, can be integrated into organ-on-chip platforms, and leveraging molecular pathology and OMICS data, can provide highly realistic patient-specific models. These biomimetic tools enable the investigation of metastasis organotropism, the identification of therapeutic targets and the design of drug administration protocols to prevent metastasis and to overcome resistance. Benefits, limitations, and challenges to address for an efficient and routine application of this cutting-edge approach, together with the role of Artificial-Intelligence (AI) in managing the complex datasets generated by OMICS technologies will be highlighted in this review, as well as their real-life implications and evolutionary prospects.
conclusionApplying patient-derived bioprinted tumors and organs for clinical purpose and developing standardized 4D and 5D bioprinting protocols would allow assessment of cancer response to treatments in a dynamic and faithfully reconstructed microenvironment. Integration of advanced molecular diagnostics and multi-OMICS data, with customized small-scale tumor models, assisted by AI-powered tools, requires a multidisciplinary framework. This integrated approach can upgrade clinical management of metastatic diseases, by accelerating the identification of actionable biomarkers and resistance mechanisms for timely therapy adjustments, thus enabling tailored treatment regimens based on individual tumor behavior.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.