(2) Li Xiaoxi, Ren Weijun, Liu Ling, Liu Chuan, Chen Xiang. A Critical Reassessment of Tumor Metastasis Simulation in Murine Models: Insights Into Methodological Advances and Biological Relevance. Advanced Therapeutics. 2025;8(12):e00277. 

Abstract: Metastasis drives treatment failure and cancer mortality, yet preclinical studies still rely heavily on subcutaneous xenograft models that prioritize tumor growth over metastatic biology. This disconnection from clinical reality significantly contributes to the high failure rate of experimental therapies in trials. Here, current mechanistic insights is integrated into metastasis and critically assess transplantation models to inform rational model selection for metastasis research. Tumor transplantation models exhibit distinct dissemination patterns governed by implantation methodology rather than intrinsic tumor properties. Subcutaneous models, while technically accessible, predominantly assess primary tumor growth and fail to capture critical metastatic steps like intravasation, pre-metastatic niche formation, and organotropism. Orthotopic transplantation faithfully replicates native tissue microenvironments, enabling simultaneous assessment of tumor growth and metastatic potential. Intravascular models, while inducing rapid colonization, distort natural metastatic progression by skipping early dissemination stages. Metastatic site transplantation isolates microenvironmental impacts on tumor adaptation but fails to capture de novo metastatic initiation. Ultimately, three strategies is proposed for preventing metastasis: Eradicating circulating tumor cells, blocking colonization, and stifling outgrowth. This perspective catalyzes the strategic advancement of tumor metastasis models, thereby strengthening the reliability of preclinical findings and accelerating their clinical translation.

(1) Li Xiaoxi; Luo Lingli; Qian Hui ; Improving the predictive accuracy of efficacy evaluation using tumor orthotopic transplant and resection model, Frontiers in Pharmacology, 2024, 15:1309876 

Abstract: Preclinical efficacy evaluation and tumor drug sensitivity analysis are two main applications of efficacy evaluation. Preclinical efficacy evaluation is to predict whether candidate drugs or therapies may improve patient outcomes in clinical trials. Tumor drug sensitivity analysis is an approach for the personalized evaluation and optimization of approved anti-cancer drugs and treatment regimens. Overall survival (OS) is the gold standard to evaluate the outcome of drugs or therapies in both clinical trials and clinical treatment. Many efficacy evaluation models, such as cell model, tumor cell-line transplant model, patient-derived tumor xenograft model, tumor organoid model, have been developed to assess the inhibitory effect of tested drugs or therapies on tumor growth. In fact, many treatments may also lead to malignant progression of tumors, such as chemotherapy, which can lead to metastasis. Therefore, tumor growth inhibition does not necessarily predict OS benefit. Whether it can prevent or inhibit tumor recurrence and metastasis is the key to whether drugs and therapies can improve patient outcomes. In this perspective, we summarize the current understanding of the pathological progression of tumor recurrence and metastasis, point out the shortcomings of existing tumor transplant models for simulating the clinical scenario of malignant progression of tumors, and propose five improved indicators for comprehensive efficacy evaluation to predict OS benefit using tumor orthotopic transplant and resection model. Improvement in the accuracy of efficacy evaluation will accelerate the development process of anti-cancer drugs or therapies, optimize treatment regimens to improve OS benefit, and reduce drug development and cancer treatment costs.