Shoji Jun-Ya, Davis Richard P, Mummery Christine L, Krauss Stefan
Hybrid Technology Hub, Centre of Excellence, Institute of Basic Medical Sciences, University of Oslo, 0372 Oslo, Norway.
Department of Anatomy & Embryology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands.
Cancers (Basel). 2025 Jan 1;17(1):108. doi: 10.3390/cancers17010108.
: Tumor organoid and tumor-on-chip (ToC) platforms replicate aspects of the anatomical and physiological states of tumors. They, therefore, serve as models for investigating tumor microenvironments, metastasis, and immune interactions, especially for precision drug testing. To map the changing research diversity and focus in this field, we performed a quality-controlled text analysis of categorized academic publications and clinical studies. : Previously, we collected metadata of academic publications on organoids or organ-on-chip platforms from PubMed, Web of Science, Scopus, EMBASE, and bioRxiv, published between January 2011 and June 2023. Here, we selected documents from this metadata corpus that were computationally determined as relevant to tumor research and analyzed them using an in-house text analysis algorithm. Additionally, we collected and analyzed metadata from ClinicalTrials.gov of clinical studies related to tumor organoids or ToC as of March 2023. : From 3551 academic publications and 139 clinical trials, we identified 55 and 24 tumor classes modeled as tumor organoids and ToC models, respectively. The research was particularly active in neural and hepatic/pancreatic tumor organoids, as well as gastrointestinal, neural, and reproductive ToC models. Comparative analysis with cancer statistics showed that lung, lymphatic, and cervical tumors were under-represented in tumor organoid research. Our findings also illustrate varied research topics, including tumor physiology, therapeutic approaches, immune cell involvement, and analytical techniques. Mapping the research geographically highlighted the focus on colorectal cancer research in the Netherlands, though overall the specific research focus of countries did not reflect regional cancer prevalence. These insights not only map the current research landscape but also indicate potential new directions in tumor model research.
肿瘤类器官和芯片上肿瘤（ToC）平台可复制肿瘤的解剖和生理状态。因此，它们可作为研究肿瘤微环境、转移和免疫相互作用的模型，尤其适用于精准药物测试。为了梳理该领域不断变化的研究多样性和重点，我们对分类后的学术出版物和临床研究进行了质量控制的文本分析。
此前，我们从PubMed、Web of Science、Scopus、EMBASE和bioRxiv收集了2011年1月至2023年6月期间发表的关于类器官或芯片上器官平台的学术出版物的元数据。在此，我们从这个元数据语料库中选择了通过计算确定与肿瘤研究相关的文献，并使用内部文本分析算法对其进行分析。此外，我们收集并分析了截至2023年3月来自ClinicalTrials.gov的与肿瘤类器官或ToC相关的临床研究的元数据。
从3551篇学术出版物和139项临床试验中，我们分别确定了55种和24种被建模为肿瘤类器官和ToC模型的肿瘤类别。该研究在神经和肝/胰腺肿瘤类器官以及胃肠道、神经和生殖ToC模型方面特别活跃。与癌症统计数据的比较分析表明，肺、淋巴和宫颈肿瘤在肿瘤类器官研究中的代表性不足。我们的研究结果还说明了不同的研究主题，包括肿瘤生理学、治疗方法、免疫细胞参与和分析技术。按地理区域绘制研究地图突出了荷兰对结直肠癌研究的关注，不过总体而言，各国的具体研究重点并未反映区域癌症患病率。这些见解不仅梳理了当前的研究格局，还指出了肿瘤模型研究的潜在新方向。
