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We discuss the importance of the in vivo models in elucidating cancer biology, focusing on the patient-derived xenograft (PDX) models, which are classic and standard functional in vivo platforms for preclinical evaluation. We provide an overview of the most representative models, including cell-derived xenografts (CDX), tumor and metastatic cell-derived xenografts, and PDX models utilizing humanized mice (HM). The orthotopic models, which could reproduce the cancer environment and its progression, similar to human tumors, are particularly common. The standard procedures and rationales of gastric adenocarcinoma (GAC) orthotopic models are addressed. Despite the significant advantages of the PDX models, such as recapitulating key features of human tumors and enabling drug testing in the in vivo context, some challenges must be acknowledged, including loss of heterogeneity, selection bias, clonal evolution, stroma replacement, tumor micro-environment (TME) changes, host cell carryover and contaminations, human-to-host cell oncogenic transformation, human and host viral infections, as well as limitations for immunologic research. To compensate for these limitations, other mouse models, such as syngeneic and humanized mouse models, are currently utilized. Overall, the PDX models represent a powerful tool in cancer research, providing critical insights into tumor biology and potential therapeutic targets, but their limitations and challenges must be carefully considered for their effective use. Lastly, we present an intronic quantitative PCR (qPCR) method to authenticate, detect, and quantify human/murine cells in cell lines and PDX samples.

Background Patient-derived xenograft (PDX) mouse models of cancer have been recognized as better mouse models that recapitulate the characteristics of original malignancies including preserved tumor heterogeneity, lineage hierarchy, and tumor microenvironment. However, common challenges of PDX models are the significant time required for tumor expansion, reduced tumor take rates, and higher costs. Here, we describe a fast, simple, and cost-effective method of expanding PDX of pancreatic ductal adenocarcinoma (PDAC) in mice. Methods We used two established frozen PDAC PDX tissues (derived from two different patients) and implanted them subcutaneously into SCID mice. After tissues reached 10–20 mm in diameter, we performed survival surgery on each mouse to harvest 90–95% of subcutaneous PDX (incomplete resection), allowing the remaining 5–10% of PDX to continue growing in the same mouse. Results We expanded three consecutive passages (P1, P2, and P3) of PDX in the same mouse. Comparing the times required for in vivo expansion, P2 and P3 (expanded through incomplete resection) grew 26-60% faster than P1. Moreover, such expanded PDX tissues were successfully implanted orthotopically into mouse pancreases. Within 20 weeks using only 14 mice, we generated sufficient PDX tissue for future implantation of 200 mice. Our histology study confirmed that the morphologies of cancer cells and stromal structures were similar across all three passages of subcutaneous PDX and the orthotopic PDX and were reflective of the original patient tumors. Conclusions Taking advantage of incomplete resection of tumors associated with high local recurrence, we established a fast method of PDAC PDX expansion in mice.

Animal models refers to the animal experimental objects and related materials that can simulate human body established in medical research. As the second-largest disease in terms of morbidity and mortality after cardiovascular disease, cancer has always been the focus of human attention all over the world, which makes it a research hotspot in the medical field. At the same time, more and more animal models have been constructed and used in cancer research. With the deepening of research, the construction methods of cancer animal models are becoming more and more diverse, including chemical induction, xenotransplantation, gene programming, and so on. In recent years, patient-derived xenotransplantation (PDX) model has become a research hotspot because it can retain the microenvironment of the primary tumor and the basic characteristics of cells. Animal models can be used not only to study the biochemical and physiological processes of the occurrence and development of cancer in objects but also for the screening of cancer drugs and the exploration of gene therapy. In this paper, several main tumor animal models and the application progress of animal models in tumor research are systematically reviewed. Finally, combined with the latest progress and development trend in this field, the future research of tumor animal model was prospected.

Osteosarcoma (OS) is a rare malignant primary tumor of mesenchymal origin affecting bone. It is characterized by a complex genotype, mainly due to the high frequency of chromothripsis, which leads to multiple somatic copy number alterations and structural rearrangements. Any effort to design genome-driven therapies must therefore consider such high inter- and intra-tumor heterogeneity. Therefore, many laboratories and international networks are developing and sharing OS patient-derived xenografts (OS PDX) to broaden the availability of models that reproduce OS complex clinical heterogeneity. OS PDXs, and new cell lines derived from PDXs, faithfully preserve tumor heterogeneity, genetic, and epigenetic features and are thus valuable tools for predicting drug responses. Here, we review recent achievements concerning OS PDXs, summarizing the methods used to obtain ectopic and orthotopic xenografts and to fully characterize these models. The availability of OS PDXs across the many international PDX platforms and their possible use in PDX clinical trials are also described. We recommend the coupling of next-generation sequencing (NGS) data analysis with functional studies in OS PDXs, as well as the setup of OS PDX clinical trials and co-clinical trials, to enhance the predictive power of experimental evidence and to accelerate the clinical translation of effective genome-guided therapies for this aggressive disease.

Cancer research has achieved remarkable breakthroughs over the past decades with the aid of patient-derived xenograft (PDX) models. However, the limitations of conventional PDX models in hindering clinical translation have become increasingly apparent. In 2025, the National Institutes of Health (NIH) announced a funding shift away from exclusive reliance on animal models without justified integration of novel alternative methods (NAMs), human-relevant modeling approaches. Nevertheless, PDX models cannot be fully replaced currently due to the lingering immaturity and uncertainties of NAMs technologies, indicating that a complete non-animal research paradigm will require sustained methodological development. Therefore, developing an innovative, optimized PDX model to navigate this transitional phase remains the holy grail of preclinical cancer research. Herein, we propose PDX 2.0, a novel conceptual framework that advances conventional PDX models via the systematic integration of NAMs and complementary technologies, thereby enabling more efficient and precise cancer research. This review first delineates the core determinants, major applications, and critical limitations of traditional PDX models, then defines the conceptual architecture and distinctive characteristics of PDX 2.0. We further highlight emerging applications of this framework in high-throughput drug screening, biomarker discovery, and adaptive therapeutic evaluation, positioning PDX 2.0 as a critical evolution of PDX-based research to better support clinically actionable precision oncology.

Patient derived xenografts (PDXs) are widely used in preclinical research. However, lymphoproliferative ‘outgrowths’ at the site of tumour xenoplantation are a common source of failure in the creation of the disease model. In this work, we assessed the performance of 10-second molecular profiling of xenoplanted tissue with picosecond infrared laser mass spectrometry (PIRL-MS) as a new method for rapid identification of lymphoproliferative ‘outgrowths’ in serial passages to streamline the quality control workflow. PIRL-MS can identify ‘imposter’ lymphoproliferative tumours with sensitivity and specificity values of > 99%. This observation is established over n  = 258 independent PDX specimens and n  = 3,393 ten-second mass spectral data points used for building and validating (blind assessment) a classifier multivariate model to enable discrimination. We first established a classifier model based on principal component analysis coupled with linear discriminant analysis (PCA-LDA) to discriminate between true solid tumour PDXs (of 5 common epithelioid cancer types originating from lung, pancreas, ovarian, colon and head & neck as well as imposter tumours of lymphoproliferative origin. Implementation of the classifier only requires 10 seconds of mass spectral data collection (using a hand-held probe) and less than an additional second for data processing and evaluation against the model towards a classification. In addition, PIRL-MS analysis does not require any tissue preparation before analysis, and from previous research can also be deployed in situ/in vivo to save time. These attributes, coupled with its reported high sensitivity and specificity for identification of imposter lymphoproliferative tumours, position PIRL-MS as a rapid quality control method for fidelity assessment of xenoplanted tissues. These observations motivate follow-on work to reduce the cost and the footprint of the PIRL-MS platform towards lowering the adoption barrier for routine use.

Background Metastatic breast cancer (MBC) is incurable, with a 5-year survival rate of 28%. In the USA, more than 42,000 patients die from MBC every year. The most common type of breast cancer is estrogen receptor-positive (ER+), and more patients die from ER+ breast cancer than from any other subtype. ER+ tumors can be successfully treated with hormone therapy, but many tumors acquire endocrine resistance, at which point treatment options are limited. There is an urgent need for model systems that better represent human ER+ MBC in vivo, where tumors can metastasize. Patient-derived xenografts (PDX) made from MBC spontaneously metastasize, but the immunodeficient host is a caveat, given the known role of the immune system in tumor progression and response to therapy. Thus, we attempted to develop an immune-humanized PDX model of ER+ MBC. Methods NSG-SGM3 mice were immune-humanized with CD34+ hematopoietic stem cells, followed by engraftment of human ER+ endocrine resistant MBC tumor fragments. Strategies for exogenous estrogen supplementation were compared, and immune-humanization in blood, bone marrow, spleen, and tumors was assessed by flow cytometry and tissue immunostaining. Characterization of the new model includes assessment of the human tumor microenvironment performed by immunostaining. Results We describe the development of an immune-humanized PDX model of estrogen-independent endocrine resistant ER+ MBC. Importantly, our model harbors a naturally occurring ESR1 mutation, and immune-humanization recapitulates the lymphocyte-excluded and myeloid-rich tumor microenvironment of human ER+ breast tumors. Conclusion This model sets the stage for development of other clinically relevant models of human breast cancer and should allow future studies on mechanisms of endocrine resistance and tumor-immune interactions in an immune-humanized in vivo setting.

The establishing of the first cancer models created a new perspective on the identification and evaluation of new anti-cancer therapies in preclinical studies. Patient-derived xenograft models are created by tumor tissue engraftment. These models accurately represent the biology and heterogeneity of different cancers and recapitulate tumor microenvironment. These features have made it a reliable model along with the development of humanized models. Therefore, they are used in many studies, such as the development of anti-cancer drugs, co-clinical trials, personalized medicine, immunotherapy, and PDX biobanks. This review summarizes patient-derived xenograft models development procedures, drug development applications in various cancers, challenges and limitations.

Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational preclinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and “Triple-negative” (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward “credentialing” of PDX models as surrogates to represent individual patients for use in preclinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research.

The use of patient‐derived xenografts (PDXs) has recently attracted attention as a drug discovery platform with a high predictive clinical efficacy and a preserved tumor heterogeneity. Given the racial differences in genetic variations, it would be desirable to establish a PDX library from Japanese cancer patients on a large scale. We thus tried to construct the Japanese PDX (J‐PDX) library with a detailed clinical information for further clinical utilization. Between August 2018 and May 2020, a total of 1126 cancer specimens from 1079 patients were obtained at the National Cancer Center Hospital and National Cancer Center Hospital East, Japan, and were immediately transplanted to immunodeficient mice at the National Cancer Center Research Institute. A total of 298 cross‐cancer PDXs were successfully established. The time to engraftment varied greatly by cancer subtypes, especially in the first passage. The engraftment rate was strongly affected by the clinical stage and survival time of the original patients. Approximately 1 year was needed from tumor collection to the time when coclinical trials were conducted to test the clinical utility. The 1‐year survival rates of the patients who were involved in establishing the PDX differed significantly, from 95.6% for colorectal cancer to 56.3% for lung cancer. The J‐PDX library consisting of a wide range of cancer subtypes has been successfully established as a platform for drug discovery and development in Japan. When conducting coclinical trials, it is necessary to consider the target cancer type, stage, and engraftment rate in light of this report. We have successfully established a PDX library derived from Japanese cancer patients. In less than 2 years, we have registered more than 1000 specimens and established nearly 300 PDXs. We will further enrich the library and use it as a platform to accelerate drug discovery in Japan.