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Animal models and pathogenesis of gastric cancer: from premalignant conditions-to-metastasis
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Yumeng Pan, Licong Zhao, Jingyuan Fang
Cancer Biology & Medicine | 2026, 23(5) : 637 - 656
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Cancer Biology & Medicine | 2026, 23(5): 637-656
• Review •
Animal models and pathogenesis of gastric cancer: from premalignant conditions-to-metastasis
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Yumeng Pan, Licong Zhao, Jingyuan Fang
Affiliations
  • 1Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200001, China
About Author:

Author contributions

Conceived and designed the review: Yumeng Pan, Licong Zhao, Jingyuan Fang.

Collected the data: Yumeng Pan.

Figure preparation: Licong Zhao, Yumeng Pan.

Wrote the paper: Yumeng Pan, Licong Zhao.

Reviewed and revised the paper: Jingyuan Fang.

Published: 2026-05-15 doi: 10.20892/j.issn.2095-3941.2025.0576
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Gastric cancer (GC) remains one of the most prevalent malignancies of the gastrointestinal tract worldwide, ranking fifth in incidence and continuing to be a leading cause of cancer-related mortality. Elucidating the mechanisms underlying GC development and progression, as well as exploring effective preventive and therapeutic strategies, is therefore of paramount importance. Animal models are indispensable tools in this endeavor, providing platforms to investigate carcinogenic processes, recapitulate disease features, and evaluate therapeutic interventions, thereby bridging the gap between laboratory discoveries and clinical application. However, the establishment of reliable GC models remains challenging due to variations in tumor induction techniques, experimental conditions, and the profound heterogeneity and aggressive metastatic potential of GC. In this review we systematically summarize animal models used for studying gastric premalignant conditions and GC organized by disease stage. We analyze recent advances and limitations of each model, considering methodologic approaches, underlying mechanisms, and translational potential. Particular emphasis is placed on aligning model characteristics with contemporary clinical challenges. Ultimately, we highlight the pivotal role of animal models in advancing precision medicine for GC, offering novel perspectives to inform both mechanistic research and therapeutic development.

Gastric cancer  /  animal model  /  gastric premalignant conditions  /  carcinogenesis
Yumeng Pan, Licong Zhao, Jingyuan Fang. Animal models and pathogenesis of gastric cancer: from premalignant conditions-to-metastasis[J]. Cancer Biology & Medicine, 2026 , 23 (5) : 637 -656 . DOI: 10.20892/j.issn.2095-3941.2025.0576
Gastric cancer (GC) is a major global health concern, ranking fifth in incidence and fourth in cancer-related mortality worldwide. Approximately 1.09 million new cases were reported in 2020 and this number is projected to increase by 62% to 1.77 million by 20401. The epidemiologic distribution of GC exhibits striking geographic variation with the highest incidence reported in Eastern Asia and substantially lower rates reported in North America and Northern Europe. The disease burden is particularly pronounced among males and in regions with a high Human Development Index, such as East Asia. An increasing trend in younger populations has also been observed, highlighting the growing global impact of GC2.
Animal models are widely used in cancer research, providing essential platforms for mechanistic studies, drug discovery, and therapeutic validation. Commonly used models in GC research include chemical or biological induction models, xenograft models, and genetically engineered models. Despite the utility, these models have important limitations, including interspecies anatomic differences, the absence of systems that can faithfully recapitulate the entire cascade of GC progression, and challenges in fully reproducing the complex heterogeneity of the human tumor microenvironment (TME).
In this review we summarize strategies for constructing GC animal models, covering the selection of experimental animals and commonly used methodologies (Figure 1), while outlining the advantages, limitations, and applicability. We further integrate model construction and application across different stages of GC pathogenesis, thereby clarifying the relationship between models and disease progression and enhancing the relevance to clinical questions. Finally, we provide perspectives on future research directions, offering guidance for refining models to address key scientific challenges and support personalized cancer therapy, ultimately reinforcing the role of models as translational bridges between basic research and clinical practice.
GC is divided into intestinal-, diffuse-, and mixed/indeterminate-types based on histologic characteristics, according to Lauren’s classification3. Familial clusters caused by genetic factors account for approximately 10% of GC cases, whereas most GC cases are sporadic with the intestinal-type GC (IGC) the most common subtype4. Unlike the multifactorial, multi-step cascade that occurs in IGC, diffuse-type GC lacks clearly defined precursor lesions5. Specifically, diffuse-type GC typically exhibits a poorly differentiated phenotype with complete loss of glandular structures, carries a high risk of peritoneal dissemination, is associated with poorer prognosis, and represents a relatively rare but clinically more aggressive subtype6.
Correa et al.7 described a stepwise cascade of oncogenic progression following chronic Helicobacter pylori infection, as follows: normal gastric mucosa → chronic superficial gastritis (CSG) → chronic atrophic gastritis (CAG) → gastric intestinal metaplasia (GIM) → dysplasia → eventually progressing to IGC. The key pathologic states within this cascade are collectively referred to as gastric premalignant conditions (GPMC). GPMC include atrophic gastritis (AG), GIM, dysplasia (now more often termed intraepithelial neoplasia8), and some gastric epithelial polyps according to the inaugural 2025 American College of Gastroenterology guidelines9. The global prevalence estimates for AG, IM, and dysplasia are approximately 25.4%, 16.2%, and 2.0%, respectively10.
Although terms, such as gastric precancerous lesions (GPLs) or precancerous lesions of GC10,11 are often used interchangeably in the literature, the terms share the core concept of denoting pathologic states with an increased risk of progression to GC. Early prevention, interruption, or reversal of the Correa cascade can effectively halt this malignant progression and reduce disease incidence9. Therefore, elucidating the molecular mechanisms that drive the evolution of GPMC and identifying stage-specific biomarkers are critical research priorities with animal models playing an indispensable role in mechanistic validation and exploration.
CAG is a chronic condition characterized by the loss of gastric glands, mucosal thinning, and thickening of the muscularis mucosae caused by persistent inflammation or injury. CAG may occur with or without spasmolytic polypeptide-expressing metaplasia (SPEM), intestinal metaplasia (IM), or dysplasia, and generally follows a protracted course12. As a major risk factor for GC, AG increases disease incidence by approximately 3.5-fold and may progress to IM and dysplasia13.
GIM refers to the pathologic replacement of damaged gastric mucosal epithelium with intestinal-type epithelial cells. Moreover, the global prevalence of GIM is increasing14. GIM is categorized into three subtypes based on morphology and mucin secretion patterns: type 1, or complete intestinal metaplasia (CIM); and types 2 and 3, collectively known as incomplete intestinal metaplasia (IIM)15. GIM markedly increases the risk of GC, with an estimated annual progression rate of about 0.1%16. The risk escalates progressively from Type 1 to Type 3, with IIM carrying a higher likelihood of progressing to dysplasia and cancer compared with CIM17. As such, IIM serves as an important marker for identifying individuals at elevated risk of GC18.
Metaplasia describes the presence of a normal cell lineage in a location where a normal cell lineage is not typically found. Both acute and chronic injury to the gastrointestinal mucosa can trigger the development of metaplastic lineages, including pyloric metaplasia, pseudopyloric metaplasia (PPM), ulcer-associated cell lineage (UACL), and SPEM19. Among these metaplastic lineages, IM and SPEM are most closely linked to the pathologic progression of IGC20.
SPEM, also referred to as pseudopyloric or mucinous metaplasia, is a gastric metaplastic response first identified in animal models and later confirmed in humans. SPEM is strongly associated with chronic Helicobacter pylori (H. pylori) infection and gastric adenocarcinoma21. SPEM shares morphologic features with PPM but can be distinguished by specific molecular markers, such as TFF2 and MUC622. SPEM often represents the earliest metaplastic response to gastric injury. Under persistent inflammatory conditions, SPEM may act as a precursor to IM, dysplasia, and ultimately IGC. Although IM and SPEM have been reported in humans, most murine models of gastric metaplasia only exhibit SPEM23. The cumulative evidence indicates that SPEM serves as an initial response to chronic injury, and under sustained inflammatory stimuli, may represent a potential cellular origin for IM, dysplasia, and subsequent malignant transformation24.
Individuals with precursor lesions remain at elevated risk for GC, even after H. pylori eradication. Of note, eradication efficacy diminishes as progression along the Correa cascade advances18,25. In parallel, the activation of gastric stem cells and accumulation of genetic alterations drive the transition from metaplasia-to-dysplasia-to-GC26. Consequently, GIM represents a pivotal juncture in carcinogenesis27, although emerging evidence suggests that partial reversal may be possible28. These insights highlight the importance of additional risk factors to H. pylori. Therefore, future research should prioritize early eradication strategies and the development of novel interventions aimed at reversing mucosal injury.
Rats provide several advantages as experimental models due to a larger body size, which facilitates surgical manipulation and sample collection. Wistar rats have a low incidence of spontaneous tumors and possess gastric mucosal structures that closely resemble humans, making rats well-suited for studying the progression from chronic inflammation to GC. Male Wistar rats are frequently selected to improve the success rate and histologic fidelity of N-methyl-N′-nitro-N-nitrosoguanidine (MNNG)-induced GC29. Sprague–Dawley (SD) rats, derived from the Wistar strain, offer additional benefits, including superior adaptability, strong disease resistance, well-characterized genetic backgrounds, and metabolic stability, making SD rats highly suitable for long-term toxicologic and pharmacologic studies. However, SD rats are typically more costly than Wistar rats. At present, 4–5-week-old male Wistar rats remain the most widely used strain in GC research30. Despite the advantages, rat models also have notable limitations, such as higher acquisition and maintenance costs and greater housing space requirements compared to mouse models.
The commonly used immunocompetent mouse strains include C57BL/6 and BALB/c. C57BL/6 mice exhibit a Th1-biased cellular immune response and are widely used in genetic engineering studies owing to the availability of well-established gene-editing tools. In contrast, BALB/c mice mount balanced Th1/Th2/Th17 responses that more closely resemble human immunity and are therefore preferred for H. pylori vaccine research31. Several less commonly used strains have also been applied in GC research. For example, 615 mice were the first reported strain in which GC was induced through methylbenzylnitrosamine (MBNA) exposure32, while FVB mice, especially INS-GAS FVB mice, have been used to study GC pathogenesis33. Immunodeficient mice provide an important platform for xenograft studies but require strict rearing conditions. Although mice offer distinct advantages, including short reproductive cycles, efficient breeding, and advanced genetic modification systems, mice rarely develop spontaneous gastric tumors. As a result, most murine models of GC rely on induction with chemical carcinogens or infection with mouse-adapted Helicobacter strains, such as H. pylori SS1 or H. felis. Because these strains differ in pathogenicity from human H. pylori isolates, Helicobacter strains may introduce mechanistic discrepancies compared to human gastric carcinogenesis34.
The MG model, first established by Watanabe et al. in 199835, successfully recapitulates key stages of human gastric disease progression, including severe chronic gastritis, ulcers, IM, and ultimately adenocarcinoma. Yoshizawa et al.36 demonstrated H. pylori infection–induced SPEM in the fundic glands of MG in 2007. Prolonged infection resulted in SPEM glandular expansion, progression to gastritis cystica profunda, and subsequent IM with SPEM and IM frequently co-existing in later stages to form a continuous pathologic spectrum. The MG model closely mirrors human gastric carcinogenesis and provides a valuable system for investigating H. pylori–induced pathophysiologic processes37. Nevertheless, a broader utility of the MG model is limited by differences in IM incidence compared to humans, less common husbandry practices, and a restricted capacity to replicate the genetic mutations observed in human GC, often requiring validation through complementary models.
Spontaneous canine GC exhibits notable molecular and therapeutic similarities to human disease38. Shimosato et al.39 established a canine GC model in 1971 via MNNG induction. Xiao et al.40 subsequently demonstrated the chemopreventive effect of high-dose folic acid in N-ethyl-N′-nitro-N-nitrosoguanidine (ENNG)-induced GC using 16 male Beagle dogs. Unlike in humans, The association between canine GC and H. pylori is weak. Instead, a variety of novel non-H. pylori species have been identified in dogs, raising concerns about potential zoonotic transmission41,42. Although GC is rare in the general canine population, Belgian Shepherd dogs display a strong breed predisposition, often presenting with complex histologic features, such as signet ring cell carcinoma, that do not strictly follow the human Correa cascade43,44. This unique heterogeneity provides a valuable perspective for investigating non-classical pathways of gastric tumorigenesis.
Pigs possess anatomic and physiologic features that closely resemble humans. Eaton et al.45 established the first gnotobiotic piglet model of H. pylori infection in 1989, which reproduced gastritis pathology similar to that observed in humans. This model demonstrated that highly motile strains (e.g., strain 26,695) achieved superior colonization and induced more severe gastritis than low-motility or non-motile strains (e.g., strain Tx30a), making the gnotobiotic piglet model particularly valuable for studying bacterial virulence factors and antimicrobial efficacy. Koga et al.46 subsequently confirmed the suitability of the model for chronic infection studies by showing H. pylori persistence for > 22 months accompanied by a robust antibody response. These features highlight the utility of the gnotobiotic piglet model for evaluating antibiotics and vaccines. More recently, advances in CRISPR/Cas9 technology have enabled the efficient generation of genetically engineered pigs, opening new avenues for developing GC models that better recapitulate human disease.
Mätz-Rensing et al.47 established an H. pylori–infected rhesus monkey model in 2001, documenting progressive gastric mucosal atrophy over 18 months and confirming stable colonization of H. pylori strains in the gastric mucosa. As non-human primates, rhesus monkeys closely replicate H. pylori infection patterns that occur in humans, including the development of chronic gastritis and the potential progression to atrophic gastritis. The immune response of rhesus monkeys, dominated by Th1-mediated chronic inflammation, also parallels that of humans, making rhesus monkeys a reliable model for long-term studies of chronic H. pylori infection. However, the high natural prevalence of H. pylori among captive rhesus monkeys complicates experimental infection studies48. Moreover, experimental infection with human-derived H. pylori strains is frequently unsuccessful or only leads to transient colonization49, often necessitating the use of specific strains, such as human-derived H. pylori J16650. In addition, the substantial cost of rhesus monkeys considerably limits the widespread use as an experimental model.
Fox et al. first isolated and identified a gastric Helicobacter species from ferrets in 1989 [H. mustelae (Hm)], providing the earliest evidence of gastric Helicobacter pathogenicity in an animal and laying the foundation for model development in other species. Shortly thereafter, Fox et al.51 demonstrated the susceptibility of ferrets to chemical carcinogenesis, showing that MNNG administration combined with Hm infection significantly increased the incidence of GC, thereby modeling the potential role of H. pylori as a co-carcinogen in humans. The high natural prevalence of Hm infection in ferrets produces gastric pathology closely resembling human H. pylori infection, while the availability of specific pathogen-free ferrets further enhances utility for mechanistic studies52,53. Nonetheless, ferret, pig, and rhesus monkey models often lack adequate characterization of the active inflammatory component severity, which differs from the chronic active gastritis typically observed in human H. pylori infection53.
Zebrafish represent a powerful tool for dissecting oncogenic mechanisms and enabling high-throughput screening. Neal et al.54 developed transgenic zebrafish models, providing the first direct in vivo evidence of the carcinogenic synergy between CagA and p53 mutations in GC development, while also inspiring exploration of multiple pathogenic factors at different stages of the disease course. A major advantage of zebrafish is the high engraftment rate in patient-derived xenograft (zPDX) models, which exceeds the engraftment rate in mice and permits real-time visualization of angiogenesis and metastasis55. However, zebrafish lack gastric gland cells and the genes required for gastric-specific functions, relying instead on the intestinal bulb to mimic gastric epithelium. This limitation compromises the fidelity of GC TME modeling56,57. Future optimization strategies include refining zPDX models or applying CRISPR/Cas9 to introduce gastric-specific gene expression systems or generate immune-reconstituted zebrafish, thereby improving the accuracy of GC simulation and enhancing translational relevance.
Although rodents remain the predominant models for GC research due to the low cost, ease of handling, and high tumor induction rates, differences in gastric anatomy and H. pylori colonization compared to humans limit the translational precision. Therefore, non-rodent species increasingly serve as important complementary models, offering unique advantages that extend the scope of GC research and provide valuable insights for refining rodent-based systems (Figure 2). The applications, advantages, and limitations of these five non-rodent models are summarized in Table 1 to assist researchers in selecting the most appropriate experimental system.
Chemical carcinogens (e.g., MNNG and MNU) and pathogens (e.g., H. pylori) are well-recognized inducers of gastric carcinogenesis and are widely utilized in experimental models. However, multiple carcinogenic factors, including lifestyle and dietary habits, pathogen infections, and chemical carcinogens, often act synergistically during GC development. Consequently, constructing animal models based on combined factors can more accurately replicate the etiologic complexity of human GC and significantly increase tumor incidence and progression rates. The distinct mechanisms, pathologic characteristics, and inherent limitations of these environmental and inducible models are comprehensively evaluated in Table 2.
Warren et al.75 successfully isolated a spiral-shaped gram-negative bacterium from the gastric mucosa of a patient with chronic active gastritis in 1982. This bacterium was later identified as H. pylori and subsequently classified as a Group 1 carcinogen by the International Agency for Research on Cancer (IARC)76. Lee et al.77 were the first to culture H. felis from cat gastric mucosa in 1990, thereby establishing the first bacterial gastritis animal model. This model demonstrated disease progression from acute-to-chronic active inflammation in the stomachs of H. felis–infected mice that closely resembled long-term H. pylori infection in humans. Notably, the pathologic changes induced by H. felis vary significantly across mouse strains and genders. Specifically, C57BL/6 mice develop higher rates of gastric atrophy than BALB/c mice, which is likely due to the Th1-prone immune response68, while infected females are more susceptible to GC-related changes than males78. Lee et al.37 isolated the H. pylori Sydney strain (SS1) in 1997, which is cagA- and vacA-positive. This strain robustly colonizes in C57BL/6 mice and consistently induces chronic active gastritis, mucosal atrophy, and SPEM, making SS1 a standard model for studying pathogenesis and vaccine development.
While H. pylori has historically been regarded as the predominant inhabitant of the stomach, advances in isolation techniques, 16S rRNA sequencing, and metagenomics have revealed a diverse microbial community. These microorganisms interact with one another and the host, contributing to the development and progression of GPMC and GC.
Streptococcus anginosus is a newly identified initiator of gastric disease. Coker et al. first applied 16S rRNA analysis to gastric mucosal samples from 81 patients and identified a microbial panel (including Peptostreptococcus stomatis and S. anginosus) associated with GC progression79. Zhou et al.80 demonstrated significant enrichment of S. anginosus and S. constellatus during precancerous and early GC stages in a larger multicenter cohort of 1,043 subjects. Notably, fecal detection of these bacteria showed high sensitivity for early GC screening, suggesting the potential as non-invasive biomarkers. Fu et al.81 used mouse models to demonstrate that S. anginosus promotes gastric inflammation, mucosal atrophy, and tumorigenesis via MAPK pathway activation. Subsequently, Yuan et al.82 revealed that S. anginosus remodels the tumor immune microenvironment by metabolizing arginine-to-ornithine, thereby driving GC progression. Most recently, Zhou et al.83 confirmed that S. anginosus promotes the progression of GC by causing metabolic reprogramming through the metabolite, methionine. In conclusion, these studies all underscored the crucial role of host-microbiota interactions in gastric carcinogenesis.
In addition to S. anginosus, other non-H. pylori bacteria have been implicated. For example, oral commensals, like Fusobacterium nucleatum and Porphyromonas gingivalis, can translocate to the stomach, promoting inflammation and tumor progression, while some Lactobacillus species and Staphylococcus epidermidis exhibit protective effects by attenuating H. pylori virulence and host inflammatory responses84.
Germ-free (GF) mice can be used to completely eliminate the interference of endogenous microorganisms. Kwon et al.85 transplanted the gastric microbiota of IM or GC patients into wild-type GF mouse models and successfully reproduced the main histopathologic features of precancerous lesions. Gnotobiotic mouse models have become a key tool to precisely analyze the functions of specific microbial members. This model enables researchers to purposefully introduce a single or a group of specific strains, thereby revealing the specific pathogenic or protective mechanisms in a controlled context86,87.
With the deepening understanding of the dynamic interaction between the host and the microbiota, research models have evolved from focusing on a single pathogen to exploring complex ecosystems. Future research should aim to define microbial signatures within GPMC and GC, identify key non-H. pylori bacteria, and further use artificial intelligence (AI) and omics data to identify key microbial characteristics. Also, synthetic microbial communities (SynComs) with fully defined components can be constructed to study the interaction relationships among microorganisms and between microorganisms and the host, and to more accurately simulate the process of GC progression88.
Cell suspensions or tissue fragments are implanted into either immunodeficient (xenograft) or immunocompetent (allograft) hosts to establish GC models. While the lack of a functional immune system in xenografts necessitates the use of immunocompetent models for evaluating immune checkpoint inhibitors and tumor-immune interactions, xenograft models remain the cornerstone for human tumor profiling89,90. These models are broadly categorized as heterotopic (e.g., subcutaneous) or orthotopic based on the implantation site. While heterotopic models, such as the subcutaneous approach, offer simplicity and ease of tumor monitoring, orthotopic implantation is recognized for superior clinical relevance because orthotopic implantation recapitulates the gastric TME and facilitates the study of spontaneous metastasis. The key features, advantages, limitations, and applications of these predominant surgical approaches are systematically compared in Table 3.
Human GC cell lines are stable populations established through in vitro culture and monoclonal screening of primary tumor cells. These cells lines are commonly classified by degree of differentiation (e.g., moderate: NCI-N87 and MKN74; poor/undifferentiated: HGC-27 and MGC803), tumor origin (primary tumor vs. metastatic site), and pathologic subtype (e.g., adenocarcinomas, such as MKN45 and AGS). Some cell lines also exhibit metastatic tropism, such as MKN45, which preferentially disseminates to the liver and peritoneum.
Cell line-derived xenograft (CDX) murine model construction has historically relied on a limited number of mouse-derived GC cell lines. The earliest mouse-derived GC cell line was the murine forestomach carcinoma (MFC) line, which was established in 1987 by Qian et al.32 through chemical induction of squamous cell carcinoma in the forestomach of inbred strain 615 mice. While MFC readily forms tumors and exhibits spontaneous lung metastasis in immunocompetent mice, the histologic features differ markedly from human GC subtypes and the unique genetic background of strain 615 limits broader applicability. This finding highlights the need to develop GC cell lines compatible with more common inbred strains, such as C57BL/6 and BALB/c.
Yamamoto et al.103 established the first transplantable GC cell lines (YTN2, YTN3, YTN5, and YTN16) for immunocompetent C57BL/6 mice in 2018, derived from MNU-induced gastric adenocarcinomas. Among these transplantable GC cell lines, YTN16 has particularly high invasiveness with frequent lung, lymph node, and peritoneal metastasis. YTN16 has become a widely used model due to the well-defined genetic background and responsiveness to targeted therapies81,104,105. More recently, Wang et al.106 developed a gastric body adenocarcinoma model in BALB/c mice by combining MNU treatment with a high-salt diet, successfully establishing the MCC cell line. Tumors derived from MCC closely resemble the molecular characteristics of clinical diffuse-type GC, making this line especially valuable for studying TME interactions and immunotherapy strategies.
Although CDX models offer advantages, such as standardization, high throughput, and relatively low cost, CDX models present the following key limitations: lack of tumor specificity; limited representation of the TME; and a weaker correlation with patient tumor biology. As a result, complementary use of CDX and patient-derived xenograft (PDX) models has become an important strategy for constructing robust GC animal models.
PDX models are established by implanting human tumor tissue or patient-derived primary cells into immunocompromised hosts, followed by serial in vivo passaging90. Several patient-derived GC xenograft (PDGCX) models have been reported107–110, demonstrating clear advantages over CDX models. PDX systems not only have a central role in personalized and precision medicine but also represent the most clinically relevant in vivo preclinical models for investigating novel therapeutic strategies.
One key advantage of PDX models is the ability to preserve the genetic heterogeneity and histologic features of primary tumors. Zhang et al.108 established 32 stable PDX models from 207 GC surgical samples. Histologic and molecular analyses confirmed that these models retained the pathologic subtypes of the original tumors with key biomarkers (e.g., ERBB2, PTEN, and MET) remaining stable up to passage F12. This genetic stability is crucial for analyzing intratumoral heterogeneity and clonal evolution.
PDX models also provide a reliable platform for drug sensitivity testing and targeted drug screening. Zhang et al.111 transplanted tumor tissues from 20 GC patients into NOG mice to establish PDX models for therapeutic evaluation. The models displayed strong sensitivity to oxaliplatin, fluorouracil, and capecitabine in early passages and remained responsive to capecitabine in later passages in a dose-dependent manner. MiniPDX was developed, enabling 7-day drug screening with high PDX concordance to guide personalized treatment for advanced GC and further enhance screening efficiency112,113. PDX platforms serve as patient “avatars,” enabling dynamic, parallel testing of therapeutic regimens alongside actual clinical treatment to guide real-time decisions and overcome resistance.
However, a major limitation of standard PDX models is the absence of a functional immune system. To address this limitation, humanized PDX (Hu-PDX) models have been developed by reconstituting immunodeficient mice with human immune components (e.g., PBMCs or CD34⁺ HSCs)114. Zhao et al.115 developed a Hu-PDX model using HLA-matched human immune systems, which successfully replicated the tumor immune microenvironment and allowed for the evaluation of immune checkpoint inhibitors, like pembrolizumab. In addition to monotherapy, Luo et al.116 utilized Hu-PDX models to demonstrate that the anti-angiogenic agent apatinib remodels the immunosuppressive tumor ecosystem by reducing tumor-associated neutrophil (TAN) recruitment, thereby synergistically enhancing the efficacy of anti-PD-1 immunotherapy. These models are currently the most advanced tools for evaluating the efficacy and toxicity of immunotherapies.
Further advances in patient-derived organoid (PDO) technology have led to the emergence of patient-derived organoid-based xenograft (PDOX) models, in which in vitro cultured PDOs are transplanted into immunodeficient mice to form in vivo xenografts. Zhao et al.117 generated 57 organoids from 73 GC patients (78% success rate) in 2024 and used 5 to create PDOX models. The in vivo responses to chemotherapeutic drugs in these models were highly consistent with in vitro PDO results. Corso et al.118 further demonstrated the utility of large-scale PDX platforms by transplanting tissues from 349 patients into NOD/SCID mice, successfully establishing 145 PDX models (42% success rate). This multi-level platform integrating tissue culture, organoids, and in vivo systems encompassed all Lauren histologic and TCGA molecular subtypes. Such large-scale, well-characterized biobanks generate the massive and diverse datasets essential for training AI models. The integration of histologic, molecular, and pharmacologic data from these platforms empowers AI to uncover complex patterns and significantly enhance the prediction of therapeutic outcomes.
In conclusion, while traditional CDX models offer a cost-effective route for basic screening, the inability to recapitulate tumor heterogeneity and the microenvironment severely limits the translational relevance. Standard PDX models remain the gold standard for preserving patient-specific tumor biology. Hu-PDX models, despite the complexity, are indispensable for immunotherapy research. In addition, PDOX models provide a scalable platform for high-throughput drug screening and generate the rich datasets essential for AI-driven discovery. Looking ahead, the field should prioritize optimizing engraftment methods and advancing next-generation models that robustly integrate the human TME, ultimately accelerating the path toward precision medicine.
Advances in gene editing have facilitated the development of diverse transgenic, knockout, and knockin mouse models that enable the study of spontaneous GC tumorigenesis, metastasis, pathogenic gene discovery, and molecular subtype simulation. These models are considered among the most robust and informative tools for GC research (summarized in Table 4). When combined with H. pylori infection or chemical carcinogens, the models more effectively replicate the multifactorial nature of gastric carcinogenesis. However, the application is limited by high cost and the frequent reliance on single-gene alterations, which do not fully capture the complex, multigene interactions underlying human GC. Nevertheless, emerging technologies, such as CRISPR/Cas9 and Cre-loxP, have markedly improved the efficiency, precision, and versatility of these models, expanding the potential in both mechanistic studies and translational applications150.
In addition to the classical Correa cascade, which describes the progression from IM-to-GC, SPEM has emerged as a key focus in gastric metaplasia research due to the close association with cancer development. Current SPEM animal models are broadly divided into two categories (acute and chronic). Acute SPEM models are typically induced by chemical agents, such as DMP-777, L-635, or high-dose tamoxifen, which act by triggering rapid parietal cell loss and oxyntic atrophy. In contrast, chronic SPEM models are established primarily through H. pylori or H. felis infection, mimicking the human chronic inflammatory process and allowing progression to IM or dysplasia. The selection of an appropriate model therefore depends on the specific research context, a decision guided by the key comparative criteria summarized in Table 5.
Despite recent progress, SPEM research still faces significant challenges. First, there is limited clinical evidence to confirm the universality of mouse-derived findings in humans. Second, chemically induced acute models cannot adequately simulate the irreversible progression observed in clinical practice. Third, standardized criteria for pathologic marker detection and non-invasive screening biomarkers are lacking.
Future efforts should focus on establishing more stable, proliferative SPEM models that recapitulate clinical pathologic features. Key research priorities include elucidating the molecular mechanisms underlying SPEM cell differentiation and transformation, clarifying their interactions with H. pylori and the gastric microbiome, and identifying critical time windows for the reversibility of gastric mucosal lesions. Ultimately, refining the Correa cascade and developing drugs that specifically target and block distinct GPMC stages may enable early intervention in GC and potentially reverse the malignant progression.
Invasion and metastasis are fundamental biological characteristics of malignant tumors157. The liver and peritoneum are the most common metastatic sites for GC, together accounting for nearly 80% of all metastases and exerting a profound impact on the prognosis of patients with advanced disease158.
Recurrence models are typically developed from pre-existing growth or metastasis models. These involve administering stage-specific treatments and subsequently monitoring the primary or metastatic sites for tumor recurrence. However, due to tumor heterogeneity and the limited availability of paired clinical specimens, most current models fail to exhibit highly aggressive phenotypes. Moreover, many models focus predominantly on metaplastic lesions and lack long-term monitoring of invasion or distant metastasis, leaving the malignant transformation potential uncertain. Therefore, developing clinically relevant models that faithfully reproduce the invasive phenotype of human GC remains essential. Among available systems, xenograft models are most frequently used for investigating GC metastasis and recurrence.
CDX models serve as important platforms for metastasis studies because of reproducibility and controllability. A major challenge in constructing these models is accurately recapitulating the invasive phenotype of human GC and reliably detecting tumor penetration through the muscularis mucosa. To visualize the metastatic process, Busuttil et al.159 utilized GFP-luciferase–labeled GC cell lines (AGS, MKN45, and MKN28) to generate orthotopic models, enabling dynamic in vivo imaging of local invasion and hematogenous/lymphatic dissemination. Addressing the TME, Fujimori et al.160 co-inoculated the murine GC cell line, YTN16, with myofibroblasts (LmcMF), successfully reconstructing the fibrotic stroma characteristic of peritoneal metastasis. In another study, Gao et al.161 developed a peritoneal metastasis model by intraperitoneally injecting MKN-45-luc cells into BALB/c nude mice and demonstrated that combining lidocaine hydrochloride with paclitaxel produced significant synergistic anti-tumor effects by promoting apoptosis and suppressing migration and invasion. This finding highlights the potential of such models for preclinical evaluation of therapeutic strategies against GC with PM.
The establishment of PDX metastasis models depends on multiple factors, including tumor type, sampling site and quality, tumor aggressiveness, and the choice of immunocompromised host. In 1993, Furukawa et al.97 first reported an orthotopic PDX model by transplanting intact human GC tissue into the stomach wall of nude mice. This achieved 100% tumor formation and metastasis with widespread dissemination to lymph nodes, liver, and lungs. In contrast, injecting cell suspensions resulted in only a 6.7% metastasis rate, underscoring the importance of preserving tumor integrity and employing orthotopic implantation to maximize metastatic potential. More recently, Li et al.162 established PDX models that could be stably passaged up to 10 generations by subcutaneously implanting fresh GC tissue blocks from surgical resections into the inguinal, axillary, or dorsal regions of nude mice. These models exhibited high tumor formation and metastasis rates, particularly with inguinal implantation, making the models suitable for mechanistic studies of invasion and high metastasis-phenotype drug screening.
Tumor metastasis is strongly influenced by the intrinsic metastatic potential of tumor cells and the microenvironment in which the tumor grows163. PDX models faithfully preserve the biological characteristics of the primary tumor, making PDX models highly applicable for metastasis research. Although subcutaneous transplantation is technically straightforward, subcutaneous transplantation produces relatively low metastasis rates and may result in the loss of some tumor phenotypes. In contrast, orthotopic transplantation provides a more physiologically relevant environment by maintaining patient-derived stromal and immune components. Implantation of GC tissue or cells directly into the stomach allows modeling of the entire metastatic cascade, from local invasion and intravasation-to-distant metastasis formation, thereby more closely replicating the clinical metastatic process. In addition, PDX systems are invaluable for studying inter- and intra-tumoral heterogeneity, tumor evolution over time, and mechanisms of drug resistance164.
In this review we have integrated modeling strategies, pathogenic mechanisms, and research contexts across the key stages of GC development, providing a systematic framework for mechanistic exploration and translational application. Specifically, environmental and inducible models are optimal for investigating early-stage disease and the inflammation-to-cancer transition. Genetically engineered mouse models (GEMMs) are indispensable for validating driver gene functions throughout tumor evolution and orthotopic PDX or PDOX systems serve as essential “avatars” for studying the mechanisms of late metastasis and drug resistance. Nevertheless, current approaches have notable limitations. Specifically, rodent systems are constrained by species-specific differences, chemically induced models require prolonged induction periods, and conventional xenografts fail to fully replicate the complexity of the human TME.
To surmount these limitations, GC animal models are evolving from monotypic approaches toward complex ecosystems capable of deeply replicating the heterogeneity of the disease. Notably, an emerging THX mouse model recapitulates a human system with functional immunity, establishing a new foundation for realistically simulating the tumor immune microenvironment165. Double humanized BLT-mice, which integrate human immunity with gut microbiota, offer a robust platform for dissecting the “tumor-immune-microbiota” axis166.
Future research should prioritize the development of models that encompass the entire pathologic continuum of GC with well-defined molecular markers delineating stage transitions and a competent immune microenvironment. Parallel to this, the convergence of AI with other cutting-edge technologies, including single-cell multi-omics and advanced gene editing, will be fundamental to building these precision models. Such an integrated approach will not only enable the design of subtype-specific therapeutic strategies but will also accelerate the translation of personalized medicine into clinical practice for gastric cancer.
  • This project was supported by grants from the National Key R&D Program of China (Grant No. 2020YFA0509200) and the National Natural Science Foundation of China (Grant Nos. 82530086 and 82330086).
1.
Bray F,Laversanne M,Sung H,Ferlay J,Siegel RL,Soerjomataram I, et al.Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.CA Cancer J Clin.2024; 74: 229–63.
2.
Huang J,Lucero-Prisno DE,Zhang L,Xu W,Wong SH,Ng SC, et al.Updated epidemiology of gastrointestinal cancers in East Asia.Nat Rev Gastroenterol Hepatol.2023; 20: 271–87.
3.
Laurén P.The two histological main types of gastric carcinoma: diffuse and so-called intestinal-type carcinoma. An attempt at a histo-clinical classification.Acta Pathol Microbiol Scand.1965; 64: 31–49.
4.
Carneiro F.Familial and hereditary gastric cancer, an overview.Best Pract Res Clin Gastroenterol.2022; 58-59: 101800.
5.
Altayar O,Davitkov P,Shah SC,Gawron AJ,Morgan DR,Turner K, et al.AGA technical review on gastric intestinal metaplasia-epidemiology and risk factors.Gastroenterology.2020; 158: 732–44.e16.
6.
Wu LW,Jang SJ,Shapiro C,Fazlollahi L,Wang TC,Ryeom SW, et al.Diffuse gastric cancer: a comprehensive review of molecular features and emerging therapeutics.Target Oncol.2024; 19: 845–65.
7.
Correa P,Piazuelo MB.The gastric precancerous cascade.J Dig Dis.2012; 13: 2–9.
8.
Nagtegaal ID,Odze RD,Klimstra D,Paradis V,Rugge M,Schirmacher P, et al.The 2019 WHO classification of tumours of the digestive system.Histopathology.2020; 76: 182–8.
9.
Morgan DR,Corral JE,Li D,Montgomery EA,Riquelme A,Kim JJ, et al.ACG clinical guideline: diagnosis and management of gastric premalignant conditions.Am J Gastroenterol.2025; 120: 709–37.
10.
Mülder DT,Hahn AI,Huang RJ,Zhou MJ,Blake B,Omofuma O, et al.Prevalence of gastric precursor lesions in countries with differential gastric cancer burden: a systematic review and meta-analysis.Clin Gastroenterol Hepatol.2024; 22: 1605–17.e46.
11.
Zhang M,Zhong J,Song Z,Xu Q,Chen Y,Zhang Z.Regulatory mechanisms and potential therapeutic targets in precancerous lesions of gastric cancer: a comprehensive review.Biomed Pharmacother.2024; 177: 117068.
12.
Ming SC.Cellular and molecular pathology of gastric carcinoma and precursor lesions: a critical review.Gastric Cancer.1998; 1: 31–50.
13.
Song H,Ekheden IG,Zheng Z,Ericsson J,Nyrén O,Ye W.Incidence of gastric cancer among patients with gastric precancerous lesions: observational cohort study in a low risk Western population.BMJ.2015; 351: h4134.
14.
Soroorikia S,Kazeminia M,Qaderi K,Ziapour A,Hodhodi T,Javanbakht Z.Global prevalence of gastric intestinal metaplasia: a systematic review and meta-analysis.Syst Rev.2024; 13: 247.
15.
Sugano K,Moss SF,Kuipers EJ.Gastric intestinal metaplasia: real culprit or innocent bystander as a precancerous condition for gastric cancer?Gastroenterology.2023; 165: 1352–66.e1.
16.
Gawron AJ,Shah SC,Altayar O,Davitkov P,Morgan D,Turner K, et al.AGA technical review on gastric intestinal metaplasia-natural history and clinical outcomes.Gastroenterology.2020; 158: 705–31.e5.
17.
Wei N,Zhou M,Lei S,Zhong Z,Shi R.A meta-analysis and systematic review on subtypes of gastric intestinal metaplasia and neoplasia risk.Cancer Cell Int.2021; 21: 173.
18.
Mera RM,Bravo LE,Camargo MC,Bravo JC,Delgado AG,Romero-Gallo J, et al.Dynamics of Helicobacter pylori infection as a determinant of progression of gastric precancerous lesions: 16-year follow-up of an eradication trial.Gut.2018; 67: 1239–46.
19.
Goldenring JR.Pyloric metaplasia, pseudopyloric metaplasia, ulcer-associated cell lineage and spasmolytic polypeptide-expressing metaplasia: reparative lineages in the gastrointestinal mucosa.J Pathol.2018; 245: 132–7.
20.
Meyer AR,Goldenring JR.Injury, repair, inflammation and metaplasia in the stomach.J Physiol.2018; 596: 3861–7.
21.
Schmidt PH,Lee JR,Joshi V,Playford RJ,Poulsom R,Wright NA, et al.Identification of a metaplastic cell lineage associated with human gastric adenocarcinoma.Lab Invest.1999; 79: 639–46.
22.
Lee SH,Jang B,Min J,Contreras-Panta EW,Presentation KS,Delgado AG, et al.Up-regulation of aquaporin 5 defines spasmolytic polypeptide-expressing metaplasia and progression to incomplete intestinal metaplasia.Cell Mol Gastroenterol Hepatol.2022; 13: 199–217.
23.
Nam KT,Lee HJ,Mok H,Romero-Gallo J,Crowe JE,Peek RM, et al.Amphiregulin-deficient mice develop spasmolytic polypeptide expressing metaplasia and intestinal metaplasia.Gastroenterology.2009; 136: 1288–96.
24.
Goldenring JR.Spasmolytic polypeptide-expressing metaplasia (SPEM) cell lineages can be an origin of gastric cancer.J Pathol.2023; 260: 109–11.
25.
Take S,Mizuno M,Ishiki K,Kusumoto C,Imada T,Hamada F, et al.Correction to: risk of gastric cancer in the second decade of follow-up after Helicobacter pylori eradication.J Gastroenterol.2020; 55: 289–90.
26.
Hayakawa Y,Fox JG,Wang TC.The origins of gastric cancer from gastric stem cells: lessons from mouse models.Cell Mol Gastroenterol Hepatol.2017; 3: 331–8.
27.
Zivny J,Wang TC,Yantiss R,Kim KH,Houghton J.Role of therapy or monitoring in preventing progression to gastric cancer.J Clin Gastroenterol.2003; 36: S50–60; discussion S61-62.
28.
Chinese Society of Gastroenterology, Cancer Collaboration Group of Chinese Society of Gastroenterology, Chinese Medical Association.Guidelines for diagnosis and treatment of chronic gastritis in China (2022, Shanghai).J Dig Dis.2023; 24: 150–80.
29.
Campbell-Thompson M,Lauwers GY,Reyher KK,Cromwell J,Shiverick KT.17Beta-estradiol modulates gastroduodenal preneoplastic alterations in rats exposed to the carcinogen N-methyl-N′-nitro-nitrosoguanidine.Endocrinology.1999; 140: 4886–94.
30.
Taylor I,Mowat V.Comparison of longevity and common tumor profiles between Sprague-Dawley and Han Wistar rats.J Toxicol Pathol.2020; 33: 189–96.
31.
Liu Z,Li H,Huang X,Liu Q.Animal models of Helicobacter pylori infection and vaccines: current status and future prospects.Helicobacter.2024; 29: e13119.
32.
Qian SS,Gao J,Wang JX,Liu Y,Dong HY.[Establishment of a mouse forestomach carcinoma cell line (MFC) with spontaneous hematogenous metastasis and preliminary study of its biological characteristics].Zhonghua Zhong Liu Za Zhi.1987; 9: 261–4.
33.
Wang TC,Koh TJ,Varro A,Cahill RJ,Dangler CA,Fox JG, et al.Processing and proliferative effects of human progastrin in transgenic mice.J Clin Invest.1996; 98: 1918–29.
34.
Pritchard DM,Przemeck SMC.Review article: how useful are the rodent animal models of gastric adenocarcinoma?Aliment Pharmacol Ther.2004; 19: 841–59.
35.
Watanabe T,Tada M,Nagai H,Sasaki S,Nakao M.Helicobacter pylori infection induces gastric cancer in mongolian gerbils.Gastroenterology.1998; 115: 642–8.
36.
Yoshizawa N,Takenaka Y,Yamaguchi H,Tetsuya T,Tanaka H,Tatematsu M, et al.Emergence of spasmolytic polypeptide-expressing metaplasia in Mongolian gerbils infected with Helicobacter pylori.Lab Invest.2007; 87: 1265–76.
37.
Lee A,O’Rourke J,De Ungria M,Robertson B,Daskalopoulos G,Dixon M.A standardized mouse model of Helicobacter pylori infection: introducing the Sydney strain.Gastroenterology.1997; 112: 1386–97.
38.
Paoloni M,Khanna C.Translation of new cancer treatments from pet dogs to humans.Nat Rev Cancer.2008; 8: 147–56.
39.
Shimosato Y,Tanaka N,Kogure K,Fujimura S,Kawachi T.Histopathology of tumors of canine alimentary tract produced by N-methyl-N′-nitro-N-nitrosoguanidine, with particular reference to gastric carcinomas.J Natl Cancer Inst.1971; 47: 1053–70.
40.
Xiao SD,Meng XJ,Shi Y,Hu YB,Zhu SS,Wang CW.Interventional study of high dose folic acid in gastric carcinogenesis in beagles.Gut.2002; 50: 61–4.
41.
Rimbara E,Aoki S,Suzuki M,Kobayashi H,Nakagawa T,Goto-Koshino Y, et al.Characterization of three novel Helicobacter species infecting stomachs of dogs and cats: Helicobacter gastrocanis sp. nov., Helicobacter gastrofelis sp. nov., and Helicobacter felistomachi sp. nov.Front Microbiol.2025; 15: 1459401.
42.
Wandji S,Jehanne Q,Bénéjat L,Ducournau A,Aptel J,Levast M, et al.The first two human infections with Helicobacter zhangjianzhongii, a new Helicobacter closely related to Helicobacter canis.Eur J Clin Microbiol Infect Dis.2025; 44: 939–49.
43.
Hugen S,Limpens C,Robben JH,Fieten H,Mandigers PJJ.Incidence and heritability of gastric carcinoma in the Belgian Shepherd dog population in the Netherlands.Vet Sci.2025; 12: 18.
44.
Cândido MV,Syrjä P,Hanifeh M,Lepajõe J,Salla K,Kilpinen S, et al.Gastric mucosal pathology in Belgian Shepherd dogs with and without clinical signs of gastric disease.Acta Vet Scand.2021; 63: 7.
45.
Eaton KA,Morgan DR,Krakowka S.Campylobacter pylori virulence factors in gnotobiotic piglets.Infect Immun.1989; 57: 1119–25.
46.
Koga T,Shimada Y,Sato K,Takahashi K,Kikuchi I,Miura T, et al.Experimental helicobacter pylori gastric infection in miniature pigs.J Med Microbiol.2002; 51: 238–46.
47.
Mätz-Rensing K,Kunz E,Kraft C,Lorenzen D,Suerbaum S,Kaup FJ.Experimental Helicobacter pylori infection of Rhesus macaques (Macaca mulatta).Int J Med Microbiol.2001; 291: 33–43.
48.
Solnick JV,Hansen LM,Canfield DR,Parsonnet J.Determination of the infectious dose of Helicobacter pylori during primary and secondary infection in rhesus monkeys (Macaca mulatta).Infect Immun.2001; 69: 6887–92.
49.
Dubois A,Berg DE,Incecik ET,Fiala N,Heman-Ackah LM,Perez-Perez GI, et al.Transient and persistent experimental infection of nonhuman primates with Helicobacter pylori: implications for human disease.Infect Immun.1996; 64: 2885–91.
50.
Dubois A,Berg DE,Incecik ET,Fiala N,Heman-Ackah LM,Del Valle J, et al.Host specificity of Helicobacter pylori strains and host responses in experimentally challenged nonhuman primates.Gastroenterology.1999; 116: 90–6.
51.
Fox JG,Wishnok JS,Murphy JC,Tannenbaum SR,Correa P.MNNG-induced gastric carcinoma in ferrets infected with Helicobacter mustelae.Carcinogenesis.1993; 14: 1957–61.
52.
O’Toole PW,Snelling WJ,Canchaya C,Forde BM,Hardie KR,Josenhans C, et al.Comparative genomics and proteomics of Helicobacter mustelae, an ulcerogenic and carcinogenic gastric pathogen.BMC Genomics.2010; 11: 164.
53.
Fox JG,Correa P,Taylor NS,Lee A,Otto G,Murphy JC, et al.Helicobacter mustelae-associated gastritis in ferrets. An animal model of helicobacter pylori gastritis in humans.Gastroenterology.1990; 99: 352–61.
54.
Neal JT,Peterson TS,Kent ML,Guillemin K.H. pylori virulence factor CagA increases intestinal cell proliferation by Wnt pathway activation in a transgenic zebrafish model.Dis Models Mech.2013; 6: 802–10.
55.
Wu JQ,Zhai J,Li CY,Tan AM,Wei P,Shen LZ, et al.Patient-derived xenograft in zebrafish embryos: a new platform for translational research in gastric cancer.J Exp Clin Cancer Res.2017; 36: 160.
56.
Fazio M,Ablain J,Chuan Y,Langenau DM,Zon LI.Zebrafish patient avatars in cancer biology and precision cancer therapy.Nat Rev Cancer.2020; 20: 263–73.
57.
Xiao J,Glasgow E,Agarwal S.Zebrafish xenografts for drug discovery and personalized medicine.Trends Cancer.2020; 6: 569–79.
58.
Lawley PD.Methylation of DNA by N-methyl-N-nitrosourethane and N-methyl-N-nitroso-N′-nitroguanidine.Nature.1968; 218: 580–1.
59.
Tatematsu M,Furihata C,Katsuyama T,Hasegawa R,Nakanowatari J,Saito D, et al.Independent induction of intestinal metaplasia and gastric cancer in rats treated with N-methyl-N′-nitro-N-nitrosoguanidine.Cancer Res.1983; 43: 1335–41.
60.
Sugimura T,Fujimura S.Tumour production in glandular stomach of rat by N-methyl-N′-nitro-N-nitrosoguanidine.Nature.1967; 216: 943–4.
61.
Wakui S,Motohashi M,Muto T,Takahashi H,Hano H,Jutabha P, et al.Sex-associated difference in estrogen receptor β expression in N-methyl-N′-nitro-N-nitrosoguanidine-induced gastric cancers in rats.Comp Med.2011; 61: 412–8.
62.
Fujimura S,Kogure K,Oboshi S,Sugimura T.Production of tumors in glandular stomach of hamsters by N-methyl-N′-nitro-N-nitrosoguanidine.Cancer Res.1970; 30: 1444–8.
63.
Tatematsu M,Ogawa K,Hoshiya T,Shichino Y,Kato T,Imaida K, et al.Induction of adenocarcinomas in the glandular stomach of BALB/c mice treated with N-methyl-N-nitrosourea.Jpn J Cancer Res.1992; 83: 915–8.
64.
Ichinose M,Nakanishi H,Fujino S,Tatematsu M.Establishment and characterization of two cell lines from N-methyl-N-nitrosourea-induced mouse glandular stomach carcinomas.Jpn J Cancer Res.1998; 89: 516–24.
65.
Kurihara M.Inducement of canine gastric cancer by N-ethyl-N′-nitro-N-nitrosoguanidine (ENNG).Gastric Cancer.1998; 1: 95–103.
66.
Sasajima K,Kawachi T,Sano T,Sugimura T,Shimosato Y.Esophageal and gastric cancers with metastases induced in dogs by N-ethyl-N′-nitro-N-nitrosoguanidine.J Natl Cancer Inst.1977; 58: 1789–94.
67.
Druffner SR,Venkateshwaraprabu S,Khadka S,Duncan BC,Morris MT,Sen-Kilic E, et al.Comparison of gastric inflammation and metaplasia induced by Helicobacter pylori or Helicobacter felis colonization in mice.Microbiol Spectrum.2024; 12: e0001524.
68.
Wang TC,Goldenring JR,Dangler C,Ito S,Mueller A,Jeon WK, et al.Mice lacking secretory phospholipase A2 show altered apoptosis and differentiation with Helicobacter felis infection.Gastroenterology.1998; 114: 675–89.
69.
Leung WK,Wu KC,Wong CY,Cheng AS,Ching AK,Chan AW, et al.Transgenic cyclooxygenase-2 expression and high salt enhanced susceptibility to chemical-induced gastric cancer development in mice.Carcinogenesis.2008; 29: 1648–54.
70.
Kronsteiner-Gicevic S,Thompson AS,Gaggl M,Bell W,Cassidy A,Kühn T.Adding salt to food at table as an indicator of gastric cancer risk among adults: a prospective study.Gastric Cancer.2024; 27: 714–21.
71.
Takahashi M,Nishikawa A,Furukawa F,Enami T,Hasegawa T,Hayashi Y.Dose-dependent promoting effects of sodium chloride (NaCl) on rat glandular stomach carcinogenesis initiated with N-methyl-N′-nitro-N-nitrosoguanidine.Carcinogenesis.1994; 15: 1429–32.
72.
Maruta F,Sugiyama A,Ishida K,Ikeno T,Murakami M,Kawasaki S, et al.Timing of N-methyl-N-nitrosourea administration affects gastric carcinogenesis in Mongolian gerbils infected with Helicobacter pylori.Cancer Lett.2000; 160: 99–105.
73.
Sugiyama A,Maruta F,Ikeno T,Ishida K,Kawasaki S,Katsuyama T, et al.Helicobacter pylori infection enhances N-methyl-N-nitrosourea-induced stomach carcinogenesis in the Mongolian gerbil.Cancer Res.1998; 58: 2067–9.
74.
Fox JG,Dangler CA,Taylor NS,King A,Koh TJ,Wang TC.High-salt diet induces gastric epithelial hyperplasia and parietal cell loss, and enhances Helicobacter pylori colonization in C57BL/6 mice.Cancer Res.1999; 59: 4823–8.
75.
Warren JR,Marshall B.Unidentified curved bacilli on gastric epithelium in active chronic gastritis.Lancet.1983; 1: 1273–5.
76.
Infection with Helicobacter pylori.IARC Monogr Eval Carcinog Risks Hum.1994; 61: 177–240.
77.
Lee A,Fox JG,Otto G,Murphy J.A small animal model of human Helicobacter pylori active chronic gastritis.Gastroenterology.1990; 99: 1315–23.
78.
Court M,Robinson PA,Dixon MF,Jeremy AHT,Crabtree JE.The effect of gender on Helicobacter felis-mediated gastritis, epithelial cell proliferation, and apoptosis in the mouse model.J Pathol.2003; 201: 303–11.
79.
Coker OO,Dai Z,Nie Y,Zhao G,Cao L,Nakatsu G, et al.Mucosal microbiome dysbiosis in gastric carcinogenesis.Gut.2018; 67: 1024–32.
80.
Zhou CB,Pan SY,Jin P,Deng JW,Xue JH,Ma XY, et al.Fecal signatures of Streptococcus anginosus and Streptococcus constellatus for noninvasive screening and early warning of gastric cancer.Gastroenterology.2022; 162: 1933–47.e18.
81.
Fu K,Cheung AHK,Wong CC,Liu W,Zhou Y,Wang F, et al.Streptococcus anginosus promotes gastric inflammation, atrophy, and tumorigenesis in mice.Cell.2024; 187: 6783.
82.
Yuan L,Pan L,Wang Y,Zhao J,Fang L,Zhou Y, et al.Characterization of the landscape of the intratumoral microbiota reveals that Streptococcus anginosus increases the risk of gastric cancer initiation and progression.Cell Discov.2024; 10: 117.
83.
Zhou CB,Zhao LC,Qin Y,Yu J,Li W,Feng Q, et al.Streptococcus anginosus-derived methionine promotes gastric cancer progression.Gut.2026; gutjnl-2025-336966.
84.
Lowe MS,Peek RM.Microbial oncogenesis within the gastric niche: how the gastric microbiota influences H. pylori-induced disease progression.Front Microbiol.2025; 16: 1691080.
85.
Kwon SK,Park JC,Kim KH,Yoon J,Cho Y,Lee B, et al.Human gastric microbiota transplantation recapitulates premalignant lesions in germ-free mice.Gut.2022; 71: 1266–76.
86.
Darnaud M,De Vadder F,Bogeat P,Boucinha L,Bulteau AL,Bunescu A, et al.A standardized gnotobiotic mouse model harboring a minimal 15-member mouse gut microbiota recapitulates SOPF/SPF phenotypes.Nat Commun.2021; 12: 6686.
87.
Lunger C,Shen Z,Holcombe H,Mannion AJ,Dzink-Fox J,Kurnick S, et al.Gastric coinfection with thiopeptide-positive Cutibacterium acnes decreases FOXM1 and pro-inflammatory biomarker expression in a murine model of Helicobacter pylori-induced gastric cancer.Microbiol Spectrum.2024; 12: e0345023.
88.
Gonzalez-Garcia J,Delgado-Villalobos A,Hernandez-Ruiz G,Díaz-Torres O,García-Cayuela T,Gradilla-Hernández MS, et al.Synthetic microbial communities as novel models to study gut microbiome–host interactions in metabolic diseases.Discov Endocrinol Metab.2025; 1: 12.
89.
Song J,Zhu J,Jiang Y,Guo Y,Liu S,Qiao Y, et al.Advancements in immunotherapy for gastric cancer: unveiling the potential of immune checkpoint inhibitors and emerging strategies.Biochim Biophys Acta Rev Cancer.2025; 1880: 189277.
90.
Blanchard Z,Brown EA,Ghazaryan A,Welm AL.PDX models for functional precision oncology and discovery science.Nat Rev Cancer.2024; 25: 153–66.
91.
Liu L,Liu W,Deng W.Amylin inhibits gastric cancer progression by targeting CCN1 and affecting the PI3K/AKT signalling pathway.Ann Med.2025; 57: 2480754.
92.
Jung J.Human tumor xenograft models for preclinical assessment of anticancer drug development.Toxicol Res.2014; 30: 1–5.
93.
Guan X,Wang Y,Yu W,Wei Y,Lu Y,Dai E, et al.Blocking ubiquitin-specific protease 7 induces ferroptosis in gastric cancer via targeting stearoyl-CoA desaturase.Adv Sci (Weinh).2024; 11: e2307899.
94.
Wang C,Xie GM,Zhang LP,Yan S,Xu JL,Han YL, et al.High engraftment and metastatic rates in orthotopic xenograft models of gastric cancer via direct implantation of tumor cell suspensions.Cancers.2024; 16: 759.
95.
Hoffman RM.Patient-derived orthotopic xenografts: better mimic of metastasis than subcutaneous xenografts.Nat Rev Cancer.2015; 15: 451–2.
96.
Reddavid R,Corso S,Moya-Rull D,Giordano S,Degiuli M.Patient-derived orthotopic xenograft models in gastric cancer: a systematic review.Updates Surg.2020; 72: 951–66.
97.
Furukawa T,Fu X,Kubota T,Watanabe M,Kitajima M,Hoffman RM.Nude mouse metastatic models of human stomach cancer constructed using orthotopic implantation of histologically intact tissue.Cancer Res.1993; 53: 1204–8.
98.
Lv J,Zhao R,Wu D,Zheng D,Wu Z,Shi J, et al.Mesothelin is a target of chimeric antigen receptor T cells for treating gastric cancer.J Hematol Oncol.2019; 12: 18.
99.
Bonnot PE,Piessen G,Kepenekian V,Decullier E,Pocard M,Meunier B, et al.Cytoreductive surgery with or without hyperthermic intraperitoneal chemotherapy for gastric cancer with peritoneal metastases (CYTO-CHIP study): a propensity score analysis.J Clin Oncol.2019; 37: 2028–40.
100.
Ng D,Cyr D,Khan S,Dossa F,Swallow C,Kazazian K.Molecular mechanisms of metastatic peritoneal dissemination in gastric adenocarcinoma.Cancer Metastasis Rev.2025; 44: 50.
101.
Qi C,Shi H,Fan M,Chen W,Yao H,Jiang C, et al.Microvesicles from bone marrow-derived mesenchymal stem cells promote Helicobacter pylori-associated gastric cancer progression by transferring thrombospondin-2.Cell Commun Signal.2023; 21: 274.
102.
Berce C.Between prometheus and thanatos: reflections on intracardiac injection models for metastasis in mice.J Am Assoc Lab Anim Sci.2025; 64: 1–10.
103.
Yamamoto M,Nomura S,Hosoi A,Nagaoka K,Iino T,Yasuda T, et al.Established gastric cancer cell lines transplantable into C57BL/6 mice show fibroblast growth factor receptor 4 promotion of tumor growth.Cancer Sci.2018; 109: 1480–92.
104.
Capuano A,Vescovo M,Canesi S,Pivetta E,Doliana R,Nadin MG, et al.The extracellular matrix protein EMILIN-1 impacts on the microenvironment by hampering gastric cancer development and progression.Gastric Cancer.2024; 27: 1016–30.
105.
Nagaoka K,Shirai M,Taniguchi K,Hosoi A,Sun C,Kobayashi Y, et al.Deep immunophenotyping at the single-cell level identifies a combination of anti-IL-17 and checkpoint blockade as an effective treatment in a preclinical model of data-guided personalized immunotherapy.J ImmunoTher Cancer.2020; 8: e001358.
106.
Wang Y,Li X,Wang Y,Qin J.Establishment and characterization of a new mouse gastric carcinoma cell line, MCC.Cancer Cell Int.2025; 25: 9.
107.
Huynh H,Ong R,Zopf D.Antitumor activity of the multikinase inhibitor regorafenib in patient-derived xenograft models of gastric cancer.J Exp Clin Cancer Res.2015; 34: 132.
108.
Zhang T,Zhang L,Fan S,Zhang M,Fu H,Liu Y, et al.Patient-derived gastric carcinoma xenograft mouse models faithfully represent human tumor molecular diversity.PLoS One.2015; 10: e0134493.
109.
Ji X,Chen S,Guo Y,Li W,Qi X,Yang H, et al.Establishment and evaluation of four different types of patient-derived xenograft models.Cancer Cell Int.2017; 17: 122.
110.
Lu JH,Wang Y,Meng Q,Zeng ZL.Establishment of gastric cancer patient-derived xenograft models and primary cell lines.J Vis Exp.2019; e59871.
111.
Zhang Y,Yang Y,Zhou J,Yu Q,Chen L,Zhao L, et al.Patient-derived tumor xenograft animal model of gastric cancer in precision chemotherapy.Naunyn-Schmiedeberg’s Arch Pharmacol.2025; 398: 10305–16.
112.
Zhang F,Wang W,Long Y,Liu H,Cheng J,Guo L, et al.Characterization of drug responses of mini patient-derived xenografts in mice for predicting cancer patient clinical therapeutic response.Cancer Commun (Lond).2018; 38: 60.
113.
Wang J,Huang J,Wang H,Yang W,Bai Q,Yao Z, et al.Personalized treatment of advanced gastric cancer guided by the MiniPDX model.J Oncol.2022; 2022: 1987705.
114.
Chuprin J,Buettner H,Seedhom MO,Greiner DL,Keck JG,Ishikawa F, et al.Humanized mouse models for immuno-oncology research.Nat Rev Clin Oncol.2023; 20: 192–206.
115.
Zhao Y,Shuen TWH,Toh TB,Chan XY,Liu M,Tan SY, et al.Development of a new patient-derived xenograft humanised mouse model to study human-specific tumour microenvironment and immunotherapy.Gut.2018; 67: 1845–54.
116.
Luo Q,Dong Z,Xie W,Fu X,Lin L,Zeng Q, et al.Apatinib remodels the immunosuppressive tumor ecosystem of gastric cancer enhancing anti-PD-1 immunotherapy.Cell Rep.2023; 42: 112437.
117.
Zhao Y,Li S,Zhu L,Huang M,Xie Y,Song X, et al.Personalized drug screening using patient-derived organoid and its clinical relevance in gastric cancer.Cell Rep Med.2024; 5: 101627.
118.
Corso S,Isella C,Bellomo SE,Apicella M,Durando S,Migliore C, et al.A comprehensive PDX gastric cancer collection captures cancer cell–intrinsic transcriptional MSI traits.Cancer Res.2019; 79: 5884–96.
119.
Wang TC,Dangler CA,Chen D,Goldenring JR,Koh T,Raychowdhury R, et al.Synergistic interaction between hypergastrinemia and Helicobacter infection in a mouse model of gastric cancer.Gastroenterology.2000; 118: 36–47.
120.
Wang TC,Bonner-Weir S,Oates PS,Chulak M,Simon B,Merlino GT, et al.Pancreatic gastrin stimulates islet differentiation of transforming growth factor alpha-induced ductular precursor cells.J Clin Invest.1993; 92: 1349–56.
121.
Koh TJ,Goldenring JR,Ito S,Mashimo H,Kopin AS,Varro A, et al.Gastrin deficiency results in altered gastric differentiation and decreased colonic proliferation in mice.Gastroenterology.1997; 113: 1015–25.
122.
Zavros Y,Eaton KA,Kang W,Rathinavelu S,Katukuri V,Kao JY, et al.Chronic gastritis in the hypochlorhydric gastrin-deficient mouse progresses to adenocarcinoma.Oncogene.2005; 24: 2354–66.
123.
Fourmy D,Gigoux V,Reubi JC.Gastrin in gastrointestinal diseases.Gastroenterology.2011; 141: 814–8.e1-3.
124.
Jenkins BJ,Grail D,Nheu T,Najdovska M,Wang B,Waring P, et al.Hyperactivation of STAT3 in gp130 mutant mice promotes gastric hyperproliferation and desensitizes TGF-β signaling.Nat Med.2005; 11: 845–52.
125.
Judd LM,Bredin K,Kalantzis A,Jenkins BJ,Ernst M,Giraud AS.STAT3 activation regulates growth, inflammation, and vascularization in a mouse model of gastric tumorigenesis.Gastroenterology.2006; 131: 1073–85.
126.
Elmaci DN,Hopping G,Hoffmann W,Muttenthaler M,Stein M.The structural integrity of human TFF1 under reducing conditions.Redox Biol.2025; 81: 103534.
127.
Soutto M,Chen Z,Bhat AA,Wang L,Zhu S,Gomaa A, et al.Activation of STAT3 signaling is mediated by TFF1 silencing in gastric neoplasia.Nat Commun.2019; 10: 3039.
128.
Tomita H,Takaishi S,Menheniott TR,Yang X,Shibata W,Jin G, et al.Inhibition of gastric carcinogenesis by the hormone gastrin is mediated by suppression of TFF1 epigenetic silencing.Gastroenterology.2011; 140: 879–91.
129.
Soutto M,Chen Z,Katsha AM,Romero-Gallo J,Krishna US,Piazuelo MB, et al.Trefoil factor 1 expression suppresses helicobacter pylori-induced inflammation in gastric carcinogenesis.Cancer.2015; 121: 4348–58.
130.
Tu S,Bhagat G,Cui G,Takaishi S,Kurt-Jones EA,Rickman B, et al.Overexpression of interleukin-1β induces gastric inflammation and cancer and mobilizes myeloid-derived suppressor cells in mice.Cancer Cell.2008; 14: 408–19.
131.
Han Y,Zhang YY,Pan YQ,Zheng XJ,Liao K,Mo HY, et al.IL-1β-associated NNT acetylation orchestrates iron-sulfur cluster maintenance and cancer immunotherapy resistance.Mol Cell.2023; 83: 1887–902.e8.
132.
Brembeck FH,Schreiber FS,Deramaudt TB,Craig L,Rhoades B,Swain G, et al.The mutant K-ras oncogene causes pancreatic periductal lymphocytic infiltration and gastric mucous neck cell hyperplasia in transgenic mice.Cancer Res.2003; 63: 2005–9.
133.
Okumura T,Ericksen RE,Takaishi S,Wang SSW,Dubeikovskiy Z,Shibata W, et al.K-ras mutation targeted to gastric tissue progenitor cells results in chronic inflammation, an altered microenvironment, and progression to intraepithelial neoplasia.Cancer Res.2010; 70: 8435–45.
134.
Won Y,Choi E.Mouse models of K-ras activation in gastric cancer.Exp Mol Med.2022; 54: 1793–8.
135.
Mukhopadhyay S,Vander Heiden MG,McCormick F.The metabolic landscape of RAS-driven cancers from biology to therapy.Nat Cancer.2021; 2: 271–83.
136.
Matkar SS,Durham A,Brice A,Wang TC,Rustgi AK,Hua X.Systemic activation of K-ras rapidly induces gastric hyperplasia and metaplasia in mice.Am J Cancer Res.2011; 1: 432–45.
137.
Choi E,Hendley AM,Bailey JM,Leach SD,Goldenring JR.Expression of activated ras in gastric chief cells of mice leads to the full spectrum of metaplastic lineage transitions.Gastroenterology.2016; 150: 918–30.e13.
138.
Hayakawa Y,Ariyama H,Stancikova J,Sakitani K,Asfaha S,Renz BW, et al.Mist1 expressing gastric stem cells maintain the normal and neoplastic gastric epithelium and are supported by a perivascular stem cell niche.Cancer Cell.2015; 28: 800–14.
139.
Lu XX,Yu JL,Ying LS,Han J,Wang S,Yu QM, et al.Stepwise cumulation of RUNX3 methylation mediated by helicobacter pylori infection contributes to gastric carcinoma progression.Cancer.2012; 118: 5507–17.
140.
Ito Y,Bae SC,Chuang LSH.The RUNX family: developmental regulators in cancer.Nat Rev Cancer.2015; 15: 81–95.
141.
Ito K,Lim ACB,Salto-Tellez M,Motoda L,Osato M,Chuang LSH, et al.RUNX3 attenuates beta-catenin/T cell factors in intestinal tumorigenesis.Cancer Cell.2008; 14: 226–37.
142.
Chuang LSH,Matsuo J,Douchi D,Bte Mawan NA,Ito Y.RUNX3 in stem cell and cancer biology.Cells.2023; 12: 408.
143.
Ito K,Chuang LSH,Ito T,Chang TL,Fukamachi H,Salto-Tellez M, et al.Loss of RUNX3 is a key event in inducing precancerous state of the stomach.Gastroenterology.2011; 140: 1536–46.e8.
144.
Katz JP,Perreault N,Goldstein BG,Actman L,McNally SR,Silberg DG, et al.Loss of KLF4 in mice causes altered proliferation and differentiation and precancerous changes in the adult stomach.Gastroenterology.2005; 128: 935–45.
145.
Yu T,Chen X,Lin T,Liu J,Li M,Zhang W, et al.KLF4 deletion alters gastric cell lineage and induces MUC2 expression.Cell Death Dis.2016; 7: e2255.
146.
Liu Z,Demitrack ES,Keeley TM,Eaton KA,El-Zaatari M,Merchant JL, et al.IFNγ contributes to the development of gastric epithelial cell metaplasia in Huntingtin interacting protein 1 related (Hip1r)-deficient mice.Lab Investig J Tech Methods Pathol.2012; 92: 1045–57.
147.
Jain RN,Al-Menhali AA,Keeley TM,Ren J,El-Zaatari M,Chen X, et al.Hip1r is expressed in gastric parietal cells and is required for tubulovesicle formation and cell survival in mice.J Clin Invest.2008; 118: 2459–70.
148.
Keeley TM,Samuelson LC.Cytodifferentiation of the postnatal mouse stomach in normal and Huntingtin-interacting protein 1-related-deficient mice.Am J Physiol Gastrointest Liver Physiol.2010; 299: G1241–1251.
149.
Nam KT,Varro A,Coffey RJ,Goldenring JR.Potentiation of oxyntic atrophy-induced gastric metaplasia in amphiregulin-deficient mice.Gastroenterology.2007; 132: 1804–19.
150.
Jiang Y,Yu Y.Transgenic and gene knockout mice in gastric cancer research.Oncotarget.2017; 8: 3696–710.
151.
Weis VG,Sousa JF,LaFleur BJ,Nam KT,Weis JA,Finke PE, et al.Heterogeneity in mouse spasmolytic polypeptide-expressing metaplasia lineages identifies markers of metaplastic progression.Gut.2013; 62: 1270–9.
152.
Goldenring JR,Ray GS,Coffey RJ,Meunier PC,Haley PJ,Barnes TB, et al.Reversible drug-induced oxyntic atrophy in rats.Gastroenterology.2000; 118: 1080–93.
153.
Huh WJ,Khurana SS,Geahlen JH,Kohli K,Waller RA,Mills JC.Tamoxifen induces rapid, reversible atrophy, and metaplasia in mouse stomach.Gastroenterology.2012; 142: 21–4.e7.
154.
Petersen CP,Meyer AR,De Salvo C,Choi E,Schlegel C,Petersen A, et al.A signalling cascade of IL-33 to IL-13 regulates metaplasia in the mouse stomach.Gut.2018; 67: 805–17.
155.
Nam KT,Lee HJ,Sousa JF,Weis VG,O’Neal RL,Finke PE, et al.Mature chief cells are cryptic progenitors for metaplasia in the stomach.Gastroenterology.2010; 139: 2028–37.e9.
156.
Nomura S,Baxter T,Yamaguchi H,Leys C,Vartapetian AB,Fox JG, et al.Spasmolytic polypeptide expressing metaplasia to preneoplasia in H. felis-infected mice.Gastroenterology.2004; 127: 582–94.
157.
Li Y,Liu F,Cai Q,Deng L,Ouyang Q,Zhang XHF, et al.Invasion and metastasis in cancer: molecular insights and therapeutic targets.Sig Transduct Target Ther.2025; 10: 57.
158.
Hundahl SA,Phillips JL,Menck HR.The National Cancer Data Base Report on poor survival of U.S. gastric carcinoma patients treated with gastrectomy: fifth edition American Joint Committee on Cancer staging, proximal disease, and the “different disease” hypothesis.Cancer.2000; 88: 921–32.
159.
Busuttil RA,Liu DS,Di Costanzo N,Schröder J,Mitchell C,Boussioutas A.An orthotopic mouse model of gastric cancer invasion and metastasis.Sci Rep.2018; 8: 825.
160.
Fujimori D,Kinoshita J,Yamaguchi T,Nakamura Y,Gunjigake K,Ohama T, et al.Established fibrous peritoneal metastasis in an immunocompetent mouse model similar to clinical immune microenvironment of gastric cancer.BMC Cancer.2020; 20: 1014.
161.
Gao P,Peng F,Liu J,Wu W,Zhao G,Liu C, et al.Lidocaine enhanced antitumor efficacy and relieved chemotherapy-induced hyperalgesia in mice with metastatic gastric cancer.Int J Mol Sci.2025; 26: 828.
162.
Li K,Du H,Lian X,Chai D,Li X,Yang R, et al.Establishment and characterization of a metastasis model of human gastric cancer in nude mice.BMC Cancer.2016; 16: 54.
163.
Shi X,Wang X,Yao W,Shi D,Shao X,Lu Z, et al.Mechanism insights and therapeutic intervention of tumor metastasis: latest developments and perspectives.Signal Transduction Targeted Ther.2024; 9: 192.
164.
Liu Y,Wu W,Cai C,Zhang H,Shen H,Han Y.Patient-derived xenograft models in cancer therapy: technologies and applications.Signal Transduct Target Ther.2023; 8: 160.
165.
Chupp DP,Rivera CE,Zhou Y,Xu Y,Ramsey PS,Xu Z, et al.A humanized mouse that mounts mature class-switched, hypermutated and neutralizing antibody responses.Nat Immunol.2024; 25: 1489–506.
166.
Daharsh L,Lohani SC,Ramer-Tait AE,Li Q.Characterization of double humanized BLT-mice with stable engraftment of a human gut bacterial microbiome.Front Microbiomes.2024; 3: 1404353.
Year 2026 volume 23 Issue 5
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doi: 10.20892/j.issn.2095-3941.2025.0576
  • Receive Date:2025-09-22
  • Online Date:2026-11-07
  • Published:2026-05-15
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  • Received:2025-09-22
  • Accepted:2026-02-05
Funding
This project was supported by grants from the National Key R&D Program of China (Grant No. 2020YFA0509200) and the National Natural Science Foundation of China (Grant Nos. 82530086 and 82330086).
Affiliations
    1Division of Gastroenterology and Hepatology, Shanghai Institute of Digestive Disease, NHC Key Laboratory of Digestive Diseases, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200001, China

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Correspondence to: Jingyuan Fang E-mail:
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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