Introduction to animal modelling: factors and tools for choosing the optimal model for sarcoma research—a comprehensive literature review
Review Article

Introduction to animal modelling: factors and tools for choosing the optimal model for sarcoma research—a comprehensive literature review

Piotr Remiszewski1,2 ORCID logo, Anna M. Czarnecka1,3,4, Eryk Siedlecki1,2, Michał Mikula5, Piotr Rutkowski1

1Department of Soft Tissue/Bone Sarcoma and Melanoma, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland; 2Medical Faculty, Medical University of Warsaw, Warsaw, Poland; 3Outpatient Chemotherapy Department, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland; 4Department of Experimental Pharmacology, Mossakowski Medical Research Institute, Polish Academy of Sciences, Warsaw, Poland; 5Department of Genetics, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland

Contributions: (I) Conception and design: P Remiszewski, AM Czarnecka; (II) Administrative support: AM Czarnecka, P Rutkowski; (III) Provision of study materials or patients: P Remiszewski, AM Czarnecka, P Rutkowski; (IV) Collection and assembly of data: P Remiszewski, AM Czarnecka, E Siedlecki; (V) Data analysis and interpretation: All authors; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Correspondence to: Prof. Piotr Rutkowski, MD, PhD, DSc. Department of Soft Tissue/Bone Sarcoma and Melanoma, Maria Sklodowska-Curie National Research Institute of Oncology, Roentgen 5 Street, 02-781 Warsaw, Poland. Email: piotr.rutkowski@pib-nio.pl.

Background and Objective: Most sarcomas have complex karyotypes, making them particularly challenging to study and treat due to their genetic diversity and aggressive nature. Animal models are essential in sarcoma research as they provide a comprehensive approach to studying tumour biology, progression and therapeutic responses that cannot be fully replicated in vitro. However, choosing the right model requires consideration of many practical aspects that have not been adequately addressed, particularly in sarcomas. Therefore, we aim to fill this gap by focusing on several animal models used in sarcoma research.

Methods: We performed a literature search in Scopus, MEDLINE and Web of Science using specific search terms to identify published original in vivo studies regarding different sarcoma subtypes, as well as selection tools.

Key Content and Findings: The most commonly used models are: syngeneic, genetically engineered mouse (GEM), chemically induced, cell-derived xenografts (CDX), patient-derived xenografts (PDX), humanised PDX (huPDX), and zebrafish. Each model has its own advantages, for example: CDXs enable high-throughput drug screening, PDXs preserve tumour heterogeneity in patients, while huPDXs most closely resemble the human immune response, However, there are various limitations to each model, including a lack of genetic diversity in syngeneic models, the complexity and time requirements of GEMs, and the short life span of cost-effective zebrafish. We also described various tools that can be used to help select the right animal model, including the International Mouse Strain Resource (ISMR) and the Mouse Tumour Biology Database (MTB), and inoculation methods (e.g., subcutaneus, orthopic).

Conclusions: With the right model, researchers can accurately study tumour behaviour, therapeutic responses and the basic mechanisms that underlie sarcoma development. We provide a practical guide for animal model selection though detailed discussion of model classes, inoculation routes, and endpoint to sarcoma-specific use cases as well as a list of active repositories/databases.

Keywords: Sarcoma; animal models; genetically engineered mouse (GEM); preclinical models; translational sarcoma research

Submitted Jun 09, 2025. Accepted for publication Dec 10, 2025. Published online Jan 27, 2026.

doi: 10.21037/tcr-2025-1218

Introduction

Background

Animal models play a crucial role in cancer research, providing insights into tumor biology, testing new therapies, biomarkers discovery, and understanding the mechanisms of cancer progression. The most commonly used animal models are rodents, particularly mice, due to their genetic similarities to humans, short life cycles, the availability of spontaneous models for multiple cancers, and the ease of manipulating their genomes. Sarcomas are a diverse group of cancers of mesenchymal origin. Although sarcomas account for less than 1% of cancer, there are more than 50 different subtypes that are very different in terms of biology and clinical appearance (1). Sarcomas, particularly ultra-rare subtypes, face significant barriers to treatment development due to their rarity posing a challenge to clinical trial testing and limited commercial interest from pharmaceutical companies (2). Utilization of a variety of advanced sarcoma models is addressing these challenges by enabling basic research, drug repurposing, and preclinical validation of new treatment strategies before clinical implementation. Currently, the standard for treating localised sarcoma is surgery, frequently combined with radiotherapy and/or (poly)chemotherapy (3,4). Unfortunately, approximately one-third of sarcoma patients continue to experience poor outcomes, especially in patients with metastatic disease, with a median survival of only 12 months (5). Usually, the goal of treatment in a metastatic soft tissue sarcoma (STS) setting is considered palliative and chemotherapy is usually administered to control tumour growth despite a poor improvement in survival (5,6). Targeted drugs may offer improvements beyond current therapies; however, identifying actionable targets in sarcomas is particularly challenging (7). While omic analyses have proposed numerous novel therapies, their translation to clinical practice has been limited by unsatisfactory results in clinical trials (1,8-10). Also, they can have different types of karyotypes, which refers to the number and structure of their chromosomes. Some sarcomas have a diploid karyotype, meaning they have a relatively normal set of chromosomes with few structural abnormalities. These sarcomas typically include subtypes with specific, well-defined genetic alterations, like Ewing sarcoma, which has the EWS-FLI1 fusion. In contrast, most sarcomas belong to a group with complex karyotypes. These include undifferentiated pleomorphic sarcomas, pleomorphic rhabdomyosarcomas, embryonal rhabdomyosarcomas, and osteosarcomas. Cytogenetic studies show that these sarcomas have highly unstable genomes, with many deletions, amplifications, and chromosomal fusions contributing to their more aggressive behaviour. Moreover, molecular studies have shown that many sarcomas with complex karyotypes lose key tumour suppressor pathways, like p53 and retinoblastoma (Rb). Some also carry activating mutations, such as oncogenic K-ras. These genetic disruptions drive sarcoma development. Unlike diploid sarcomas, where a single genetic event, like a translocation, is often the cause, it’s harder to pinpoint the driving mutations in complex sarcomas due to the many alterations present. The high variability observed in these tumours also presents a significant challenge for clinicians seeking to implement personalised treatment approaches. It is of the utmost importance to replicate this complexity and dynamic tumour-host interaction to better understand sarcomagenesis, tumour growth, metastasis and the response to therapies.

Rationale and knowledge gap

The wide differences between the preclinical and clinical trials of the same drugs especially show the need to develop animal models further in sarcoma research. Today, the US Food and Drug Administration (FDA) generally requires preclinical testing of any new drug or biologic “for pharmacological activity and acute toxicity in animals” before human clinical trials (11). In certain cases, such as emergency treatment for dangerous exposures, the FDA may even approve human use based on animal testing under the “Animal Efficacy Rule” (12,13). While many factors have to be considered, the choice of animal models plays a huge role. Approximately 12% of drugs pass preclinical testing to enter clinical trials (14). Of these, only 60% completed phase I trials (15). About 89% of new drugs fail in human clinical trials, with about half of these failures due to unanticipated human toxicity (13). Forbes estimates that in 2012, the industry will have already spent between $4 billion and $11 billion on a single market release. This highlights the importance of each step in the decision tree regarding time and lost revenue (16). Despite the gaps in our understanding of sarcoma development, various biological tools now enable exploring these complex processes at both molecular and organismal levels (10,17).

Objective

Accurate animal models must reflect not only the molecular characteristics of these tumours, but also their microenvironment and dynamic interaction with the host immune system. Therefore, choosing the right model requires the consideration of multiple factors and challenges, some of them sarcoma-specific, which we reviewed and proposed possible solutions. We aim to provide a concise introduction to animal modelling for sarcoma researchers and clinicians, focusing on practical aspects. Moreover, we highlighted resources such as the Mouse Tumour Biology Database (MTB) and the International Mouse Strain Resource (IMSR), which provide detailed phenotypic and genotypic data to guide model selection. The review also explains the inoculation methods as well as description of most common animal models and their critical evaluation. Better animal models streamline the drug development pipeline, preventing costly failures and accelerating the introduction of effective therapies to patients in need. This review is distinguished by a methods-first selection framework that operationalises model choice for sarcoma endpoints rather than listing models descriptively. We present this article in accordance with the Narrative Review reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1218/rc).

Methods

We conducted a narrative review of preclinical sarcoma models and selection tools following a structured, non-systematic approach. We selectively search for preclinical studies up to April 2025 using Medline, Scopus, and Web of Science to identify original in vivo studies of any sarcoma subtype that described model type, inoculation method, or selection tools. The search strategy summary is presented in detail in Table 1.

Table 1

Summary of the methodology of literature review

Items Specification
Date of search 1st May 2025
Databases searched Medline, Scopus, Web of Science
Search terms used Table S1
Timeframe From the inception of the database to 30th April 2025
Inclusion and exclusion criteria Inclusion: (I) original in vivo studies of any sarcoma subtype; (II) explicit description of the model type, inoculation method, or selection tool; (III) published in English
Exclusion: (I) reviews without new data; (II) in vitro-only studies; (III) studies irrelevant to the discussed topic
Selection process No restrictions on the publication date or sarcoma subtype; emphasis on relevance to model type and methodological details. Three authors (Piotr Remiszewski, E.S., A.M.C.) have selected the included studies together

Notable challenges in sarcoma animal research

Traditional genetically engineered mouse models (GEMMs) using Cre-lox technology often lack the flexibility to capture the role of epigenetic alterations, such as those mediated by SWI/SNF complex dysfunction in synovial sarcoma, or the immunologically “cold” nature of many sarcomas (18,19). For example, models of Ewing sarcoma with EWS-FLI1 expression often result in embryonic lethality or fail to develop the intended tumour type. In contrast, fusion-driven sarcomas such as EWSR1-WT1 in clear cell sarcoma are difficult to replicate due to their complex transcriptional reprogramming (20).

In addition, models for studying metastasis are limited. Soft tissue sarcomas often metastasise to the lung, but existing models, such as the Kras/Trp53 GEMMs, generate primary tumours but usually fail to accurately mimic metastatic progression (21,22). Even advanced tools such as CRISPR/Cas9, while enabling rapid generation of mutations (e.g., Nf1 and Trp53 knockouts for MPNST), require optimisation to effectively study tumour heterogeneity and clonal evolution (23).

Patient-derived xenografts (PDX), however, provide some translational value but lack an intact immune system, making them unsuitable for studying immunotherapy. Immunocompetent GEMMs, such as Kras/Trp53 models, show some promise but often fail to fully recapitulate the immunosuppressive microenvironment observed in human sarcomas, such as the M2 macrophage-dominated landscapes in dedifferentiated liposarcoma (24,25). These and other challenges are summarised in Table 2, along with possible solutions.

Table 2

Challenges and solutions for animal research in sarcoma

Challenge Description Possible solution/strategy References
Rare subtypes and fusion variants Sarcomas have more than 100 histological subtypes, many of which are extremely rare. For example, ASPS and clear cell sarcoma are among the rarest subtypes, each accounting for less than 1% of all sarcomas. The diversity of subtypes makes it difficult to generalise models Develop subtype-specific models using CRISPR to replicate fusion genes such as ASPSCR1-TFE3 for ASPS or EWSR1-ATF1 for clear cell sarcoma (26,27)
Establish PDX for rare subtypes to test therapies
Leverage collaborations with international sarcoma networks to pool resources and samples for rare subtypes
Use biobanks to analyse rare tumour samples and generate organoid models
Apply fusion-specific drug screening, such as testing MET inhibitors in ASPS or immune checkpoint inhibitors in fusion-driven sarcomas
Epigenetic drivers Sarcomas are often driven by epigenetic changes (e.g., DNA methylation, histone modifications) rather than mutations. Fusion oncoproteins, such as EWS-FLI1 in Ewing sarcoma or SS18-SSX in synovial sarcoma, reprogramme chromatin and gene expression, altering key pathways Use CRISPR tools to knock out or edit specific chromatin regulators such as components of the SWI/SNF complex (ARID1A, SMARCB1) to study their role (28)
Test small molecule inhibitors targeting epigenetic regulators, such as EZH2 inhibitors (tazemetostat) for epithelioid sarcoma or BET inhibitors for fusion-driven tumours
Establish patient-derived tumour organoids combined with RNA sequencing and ChIP-seq to understand how fusion oncoproteins alter the chromatin landscape
Investigate epigenetic resistance mechanisms using drug combinations with HDAC or DNMT inhibitors
Angiogenesis and hypoxia Hypoxia is a hallmark of sarcoma progression, driving angiogenesis, resistance to therapy and tumour aggressiveness. Hypoxic conditions stabilise HIF-1α, promote pro-angiogenic factors such as VEGF, and alter metabolic and survival pathways. Standard animal models often fail to reproduce the dynamic hypoxic gradients within tumours, which are critical for studying drug resistance and metastasis. In addition, hypoxia-induced changes in immune suppression and ECM remodelling are difficult to capture Develop models under hypoxic conditions using hypoxia chambers or 3D tissue scaffolds (29-32)
Use angiogenesis inhibitors such as VEGF inhibitors (bevacizumab) or tyrosine kinase inhibitors (sunitinib) to block blood vessel formation
Combine anti-angiogenesis therapies with chemotherapy or immunotherapy to exploit vulnerabilities in hypoxic tumours
Create vasculature-on-a-chip systems to study how sarcomas interact with abnormal blood supply
Use hypoxia-targeted imaging (e.g., hypoxia-sensitive MRI or PET) to track hypoxia in real time
Resistance to therapy Sarcomas often develop resistance to therapies such as chemotherapy, radiotherapy and targeted therapies through mechanisms such as drug efflux, activation of alternative signalling pathways and metabolic reprogramming. For example, osteosarcoma often exhibits resistance by overexpressing ABC transporters, while leiomyosarcoma activates PI3K/mTOR pathways to evade the effects of therapy Use CRISPR or RNAi screens to identify pathways involved in resistance, such as activation of the PI3K/AKT/mTOR pathway (33,34)
Develop preclinical models of resistance by exposing cells to increasing doses of chemotherapeutic agents such as doxorubicin or trabectedin
Combining standard therapies with targeted drugs, such as PI3K inhibitors (alpelisib) or CDK4/6 inhibitors in liposarcomas
Testing ABC transporter inhibitors (e.g., tariquidar) to overcome drug efflux-mediated resistance
Investigate resistance mechanisms in 3D culture systems to mimic in vivo conditions
TME The TME in sarcomas is highly complex and includes tumour cells, immune cells, stromal cells, blood vessels and ECM. A key feature is the dominance of TAMs, often polarised to an M2-like pro-tumour state, which suppress the immune response and promote angiogenesis through factors such as IL-10, VEGF and TGF-β. Sarcomas thrive in hypoxic conditions, triggering angiogenesis via VEGF and stabilising HIF-1α, while ECM remodelling by enzymes such as MMP-9 promotes invasion. Immune evasion is facilitated by PD-L1 expression and high levels of regulatory T cells. For example, osteosarcoma exhibits TAM-driven resistance to therapy through IL-6 and IL-34, which promote tumour growth and metastasis. To model this TME in animals, hypoxia, immunosuppression and ECM dynamics must be reproduced using tools such as humanised mice or 3D scaffolds Develop co-culture systems incorporating fibroblasts, macrophages and tumour cells to replicate sarcoma-TME interactions (35,36)
Use 3D hydrogels to simulate extracellular matrix properties such as stiffness and composition
Test VEGF inhibitors (e.g., bevacizumab) to target angiogenesis within the TME
Incorporate endothelial cell-lined scaffolds into models to recapitulate the vasculature and study how sarcomas evade vascular targeting
Apply proteomic analysis to identify TME-related druggable targets, such as CXCR4 or MMP inhibitors
Immunologically “Cold” tumours Immunologically 'cold' tumours such as sarcomas have low immune activity due to a lack of T cell infiltration, low neoantigen production and an immunosuppressive tumour microenvironment dominated by regulatory T cells, MDSCs and M2 polarised macrophages. These characteristics make it difficult to study immune-based therapies in animal models, especially since standard immunodeficient mice lack a functional immune system and even syngeneic models may not fully recapitulate the human immune response Develop immunocompetent or humanised mouse models, such as NSG mice with reconstituted human immune systems (18,37)
Incorporate CSF-1R inhibitors (pexidartinib) or TGF-β inhibitors to deplete immunosuppressive macrophages
Introduce engineered neoantigens or oncolytic viruses such as T-VEC to enhance immune recognition
Combine immune checkpoint inhibitors (e.g., pembrolizumab) with epigenetic drugs such as HDAC inhibitors to modulate immunogenicity
Use CAR-T therapies targeting sarcoma-specific antigens (e.g., GD2 in osteosarcoma)
Metastatic behaviour Sarcomas often metastasise haematogenously (through the bloodstream), typically to the lungs, rather than through the lymphatic system like carcinomas. Modelling lung metastasis requires replication of the specific lung microenvironment Use lineage tracing tools such as fluorescent reporters or barcode tagging systems to track tumour cell dissemination (38)
Incorporate PDX to represent personalised metastatic behaviour
Develop lung organoids or co-cultures that mimic the lung microenvironment
Use imaging techniques such as intravital microscopy to study metastasis in animal models in real time
Use CRISPR screens to identify genes that promote metastasis and test their role in vivo
Lack of suitable animal models Many sarcomas, such as UPS, leiomyosarcoma and osteosarcoma, have complex karyotypes with widespread chromosomal instability, making them difficult to model in animals. Unlike translocation-driven sarcomas (e.g., Ewing sarcoma), these types lack a single genetic driver, requiring models to replicate diverse, random mutations, which is challenging. For example, osteosarcoma is characterised by chaotic chromosomal rearrangements, while UPS and leiomyosarcoma are associated with loss of tumour suppressors such as TP53 and RB1. Because of the limited research on the subject and the difficulty of developing these models, their availability is insubstantial Develop GEMMs with sarcoma-specific drivers, such as P53/RB deletion models for osteosarcoma or EWS-FLI1 fusion models for Ewing sarcoma (39,40)
Use orthotopic transplantation to implant sarcomas in their tissue of origin (e.g., bone for osteosarcoma, soft tissue for liposarcoma)
Use zebrafish models for rapid screening of genetic mutations and drug effects
Use organoid-based models for sarcoma subtypes such as leiomyosarcoma to personalise treatment approaches
Integrate machine learning with experimental models to predict outcomes based on genetic and microenvironmental inputs
Species-specific genetic differences Human sarcomas often involve specific genetic alterations, such as translocations (e.g., EWS-FLI1 in Ewing sarcoma) or complex karyotypes, which are difficult to recapitulate in rodent models. Many mouse models cannot naturally develop these alterations or mimic their effects without genetic engineering Use GEMMs with specific translocations, such as Prx-Cre Ews-Fli1 for Ewing sarcoma or Pax3-FKHR for alveolar rhabdomyosarcoma (41)
Combine genetic models with additional tumour suppressor deletions (e.g., p53, Rb) to induce sarcomagenesis observed in humans
Use orthotopic transplantation models to improve the anatomical relevance of genetic alterations
Dormancy and recurrence Sarcomas, such as osteosarcoma and leiomyosarcoma, often exhibit dormancy, with residual tumour cells surviving for years before recurrence or metastasis. Dormant cells are difficult to model because they remain in a quiescent state, influenced by the microenvironment and factors such as CXCR4 signalling or autophagy. Animal models often fail to capture this long-term behaviour Use long-term mouse models with sensitive imaging tools (e.g., bioluminescence) to monitor dormant tumour cells (42,43)
Investigate dormancy-related signalling pathways such as TGF-β, autophagy or CXCR4 signalling in vivo
Develop mathematical models to simulate tumour dormancy and predict recurrence
Investigate therapies that target dormant cells, such as anti-CXCR4 drugs (plerixafor) or autophagy inhibitors

ASPS, alveolar soft part sarcoma; ECM, extracellular matrix; GEMMs, genetically engineered mouse models; HIF-1α, hypoxia-inducible factor-1 alpha; IL, interleukin; MDSCs, myeloid-derived suppressor cells; MRI, magnetic resonance imaging; PD-L1, programmed death-ligand 1; PDX, patient-derived xenograft; PET, positron-emission tomography; TAMs, tumour-associated macrophages; TGF-β, transforming growth factor beta; TME, tumour microenvironment; UPS, undifferentiated pleomorphic sarcoma; VEGF, vascular endothelial growth factor.

Tools helpful in choosing the right animal model

Many tools are available to help researchers find animal models relevant to human disease, and Link Animal Models to Human Disease (LAMHDI) was once a key resource (44). Funded by the NIH, LAMHDI provided centralised access to animal models from databases such as Mouse Genome Informatics (MGI), the Rat Genome Database and FlyBase (44). It allowed users to search by disease, gene or specific animal model, and to link directly to external resources such as PrimateLit for primate research and other curated web links. However, LAMHDI is no longer available as it was discontinued in 2015. Even though, it is still featured in articles as a functioning tool (45).

One of the alternatives can be The Rat Genome Database (RGD) is a comprehensive, NIH-funded resource designed to support and enhance genetic and genomic research in the rat, one of the most important model organisms for the study of human disease (46). Hosted at the Medical College of Wisconsin in collaboration with The Jackson Laboratory and NCBI, RGD consolidates a vast amount of genetic data, including detailed information on rat genes, quantitative trait loci (QTL), microsatellite markers, and numerous rat strains. The database is continually updated through curated literature and mass data integration, ensuring that researchers have access to the latest genetic knowledge. RGD includes VCMap, a powerful tool that allows researchers to explore gene and sequence homology across the rat, mouse and human genomes, a valuable feature for comparative genomics. Additional tools in RGD facilitate gene prediction, radiation hybrid mapping and polymorphic marker selection. Disease-based curation of the database is expanding, making it an increasingly rich resource for researchers investigating diseases such as hypertension, diabetes, obesity and cancer (47-50). With resources such as the Rat Community Forum and outreach programmes, RGD provides both a collaborative platform and a high-quality, disease-centric data source for the scientific community, making it an essential tool for rat genetics and translational research into human disease (46). Table 3 presents a summary of the databases for animal model selection in sarcoma research.

Table 3

Comprehensive databases for selecting animal models in sarcoma research

Database Description Access link References
Mouse Tumour Biology Database (MTB) Repository of mouse cancer models with data on tumour characteristics, histopathology, and genetic background https://tumor.informatics.jax.org/mtbwi/index.do (51,52)
NCI Genomic Data Commons (GDC) Genomic data from cancer studies useful for selecting models with matching molecular features https://datacommons.cancer.gov/repository/genomic-data-commons (45,53)
Cancer Models (caMOD) Community-driven platform with a large collection of cancer models, including patient-derived xenograft (PDX), cell lines, and organoids across cancer types, with detailed annotations and advanced filtering options https://www.cancermodels.org/ (54)
The Jackson Laboratory (JAX) Mouse Models Database Mouse Genome Informatics (MGI) Extensive library of genetically engineered mice and PDX models for various cancers, including sarcomas https://www.informatics.jax.org/ (55)
EuroPDX European network offering well-characterised PDX models with clinical and molecular annotations https://europdx.eu/ (56)
Phenotype comparisons for Disease Genes and Models (PhenoDigm) Tool for comparing phenotypes between disease genes and models, aiding in research on disease mechanisms https://www.sanger.ac.uk/tool/phenodigm/ (57)
International Mouse Strain Resource (ISMR) Repository of mouse strains with detailed phenotype and genotype information https://www.findmice.org/ (58)
Model Development for the Human Cancer Model Initiative (HCMI) HCMI’s models, accompanied by comprehensive clinical, genomic, and transcriptomic data from patients’ tumours and normal tissues, address the limitations of traditional cell lines, offering a more accurate representation of the biological characteristics of the cells under study. Researchers may access over 250 NGCMs via HCMI’s Searchable Catalog, with comprehensive biospecimen and molecular data available via the NCI Genomic Data Commons (GDC) and distributed by ATCC https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/dataset.cgi?study_id=phs001486.v3.p3&phv=400437&phd=&pha=&pht=8700&phvf=&phdf=&phaf=&phtf=&dssp=1&consent=&temp=1 (59)
Rat Genome Database The Rat Genome Database (RGD), which is funded by the National Institutes of Health (NIH), serves to centralise and provide access to data from research projects concerned with the genetics and genomics of the rat. It comprises information on inbred rat strains, genetic maps, markers, and mapping tools, in addition to curated quantitative trait loci (QTL) data for a range of phenotypes. Furthermore, RGD incorporates a genome browser and a homology tool for the comparison of rat genetic data with homologous regions in mice and humans https://rgd.mcw.edu/ (60)
Mouse Genome Database with High Added Value (MoG+) The database provides high-value, visualized genomic variation data, particularly focusing on the comparison between Japanese inbred mouse strains and classical strains like C57BL/6J. MoG+ offers a visual representation of genomic variations, including single-nucleotide polymorphisms (SNPs) and short insertions and deletions (indels). Beyond sequence variation, it includes data on genetics, epigenetics, and phenotype information, with links to publications and other resources – (61-63)

Inoculation (injection) methods in sarcoma models

A variety of injection methods are available for establishing preclinical sarcoma models, each with different characteristics, advantages and limitations. These methods, ranging from subcutaneous and orthotopic to intravenous and intracardiac injections, provide unique insights into tumour behaviour, progression and therapeutic responses. Understanding the strengths and limitations of each method allows researchers to design experiments that are tailored to specific research objectives, ultimately improving the relevance and applicability of preclinical findings. For example, intravenous injections are valuable for studying haematogenous dissemination, particularly lung metastasis (40), whereas orthotopic models recapitulate the tumour microenvironment, and metastatic routes, so route-of-inoculation dictates pharmacodynami readouts: orthotopic for matrix-dependent effects and spontaneous pulmonary spread; IV or intracardiac for colonisation timing; subcutaneous for high-throughput, size-based endpoints.

This ability to mimic metastatic patterns was used in the study by Yao et al. (40) highlights an orthotopic osteosarcoma model developed using Sprague-Dawley (SD) rats and UMR-106 osteosarcoma cells. In this model, tumour fragments or cells were implanted into the femur, closely mimicking the bone-specific tumour microenvironment of human osteosarcoma. Over successive generations, tumour implantation success rates improved from an initial 30% to more reliable results, largely due to in vivo immune selection, which allowed tumours to evade the host immune response. This model exhibited hallmark features of human osteosarcoma, including aggressive local growth, bone destruction and neoplastic calcification. Micro-CT imaging and histological analysis revealed osteolytic lesions and active calcification in the tumour area. Tumour proliferation was confirmed by Ki-67 staining, which showed high mitotic activity. One of the most clinically relevant features of the model was the frequent occurrence of pulmonary metastases, reflecting advanced stages of osteosarcoma in humans. This metastatic progression provided an ideal system to study the mechanisms of metastasis and to test anti-metastatic therapies. The orthotopic location allowed the tumour to interact naturally with the surrounding bone matrix, cytokines and stromal cells, making it highly relevant for drug testing and understanding tumour-bone interactions. However, setting up the model required considerable technical expertise, as surgical implantation into the femur is delicate and time-consuming. This study demonstrated the usefulness of this model for evaluating new therapeutic strategies and understanding the biology of osteosarcoma in its native environment. Similarly, Barrott et al. (64) used localized intramuscular injection which can be considered an orthotopic injection. The study investigated the role of Pten silencing in synovial sarcomagenesis and metastasis using a GEMM. Synovial sarcoma is a soft tissue malignancy characterised by the SS18-SSX fusion oncogene. The researchers used mice with conditional alleles for SS18-SSX1 or SS18-SSX2 and Pten activated by TATCre injection. This was a localised intramuscular injection into the quadriceps of one-month-old mice to induce site-specific recombination of the targeted alleles. The method ensured localised tumour formation with minimal systemic effects. Drugs used in some parts of the study included BLZ945, a potent CSF1R inhibitor, which was administered to assess its effects on tumour growth and inflammatory cell recruitment. In addition, LY294002, a pan-PI3' lipid kinase inhibitor, was used to assess its effect on PI3' lipid signalling and the downstream expression of inflammatory mediators such as CSF1. The results of the study showed that Pten silencing significantly enhanced tumorigenesis, shortened the latency to tumour formation and increased the prevalence and penetrance of tumour development compared to Pten-proficient mice. Tumours arising in Pten-silenced mice exhibited characteristics of synovial sarcoma, including monophasic and biphasic histology, without morphological aberrations due to Pten loss. Importantly, Pten knockdown dramatically increased lung metastasis, with metastatic foci observed in approximately 70% of Pten-deficient mice. In contrast, metastases were rare in Pten-proficient mice. Analysis revealed that Pten-deficient tumours exhibited enhanced angiogenesis, increased vessel density and an inflammatory transcriptome. RNA sequencing identified more than 4,000 differentially expressed genes in Pten-deficient tumours, with a significant enrichment in inflammatory pathways. Key inflammatory mediators such as CSF1, Ccl2 and Ccl7 were upregulated, driving the recruitment of myeloid-derived cells, in particular macrophages and neutrophils, into the tumour microenvironment. Flow cytometry confirmed an increase in CD11b+ cells, including macrophages and neutrophils, in Pten-deficient tumours. Immunohistochemical analyses further validated these findings, with macrophages showing activation of the CSF1R signalling pathway. To test the functional role of CSF1-CSF1R signalling, mice were treated with BLZ945, which significantly reduced macrophage infiltration and slowed tumour growth. LY294002 treatment reduced PI3' lipid signalling and the expression of inflammatory mediators, suggesting that the inflammatory phenotype is driven by tumour cell intrinsic PI3' lipid signalling. In addition, PCR analysis revealed increased dissemination of tumour cells to the lungs in Pten-deficient mice, even in the absence of detectable metastatic foci.

Another common injection method is intravenous injection (IV) is a commonly used method for systemic delivery of substances, including tumor cells, drugs, or other agents, into mice (65). The material is injected directly into the bloodstream, typically through the tail vein. For intravenous injection, mice are restrained and the tail vein is identified under gentle heat to dilate the vessels. A fine needle or catheter is then used to inject the substance directly into the vein. The most common sites for intravenous injection in mice are the lateral tail veins. This method allows the compound to circulate systemically and reach multiple tissues and organs, including the lungs, liver and kidneys. For tumour cell inoculation, intravenous injection can mimic the metastatic process, particularly in the generation of lung metastases, as circulating tumour cells often seed in the lungs. One of the studies (66) compared this method with Isolated Lung Perfusion (ILP) which delivers drugs exclusively to the lungs by isolating the pulmonary vasculature. It avoids systemic circulation and allows precise targeting of lung tissue which is particularly useful for studying lung-specific drug effects, local immune responses or metastases (67). The study (66) measured the concentration of doxorubicin in the tumour and surrounding lung tissue using high performance liquid chromatography (HPLC) ILP showed significantly higher drug concentrations in both tumour and lung tissue compared to intravenous injection, with increases of up to tenfold depending on the dose. This suggests that ILP can achieve improved localised drug delivery. However, the spatial distribution of the drug in the lung was more heterogeneous when delivered via ILP compared to IV administration, with considerable inter-animal variability. Histological analysis of the untreated tumours showed that they were well circumscribed, highly vascularised and composed of undifferentiated cells with minimal spontaneous necrosis. This vascular network was critical in assessing drug penetration. The study showed that free doxorubicin delivered via ILP resulted in a higher tumour/lung tissue drug ratio compared to intravenous administration, especially at higher doses. Liposomal doxorubicin, known for its altered pharmacokinetics and tumour targeting potential, performed differently. It achieved similar drug concentrations in tumour and lung tissue regardless of whether it was administered by ILP or IV injection. This behaviour was attributed to its formulation and size, which limited its penetration into tumours. Interestingly, while ILP improved the tumour-to-lung drug ratio for both formulations, liposomal doxorubicin showed lower overall concentrations compared to free doxorubicin. This may be due to the specific microvascular characteristics of the sarcoma model, where high intratumoral interstitial fluid pressure limits drug diffusion. In addition, the lack of enzymes required to depegylate liposomal doxorubicin in the ILP solution may have further limited its efficacy. We summarised most common inoculation methods with their advantages and limitations in Table 4.

Table 4

Inoculation methods in sarcoma models

Inoculation method Description Advantages Limitations Examples/applications References
SC Tumour cells or fragments are injected under the skin, often in the scruff or flank area Simple and minimally invasive Poor replication of the natural TME Used in soft tissue sarcomas and osteosarcomas for testing initial tumour growth and chemotherapy regimens (40,68,69)
Allows easy visual monitoring of tumour growth Limited metastatic potential
Can handle larger volumes of cells or substances without significant damage to the animal
Orthotopic Tumour cells implanted in the tissue of origin (e.g., bone for osteosarcoma, muscle for rhabdomyosarcoma) Mimics the native TME Technically demanding and time consuming Often used in osteosarcoma to study metastasis or in Ewing sarcoma to evaluate targeted therapies (40,68,69)
Replicates natural invasion and metastasis patterns Requires imaging tools to monitor progress
Enhances translational relevance
IP Injection of cells into the peritoneal cavity Effective for studying widespread sarcoma spread in abdominal tissue Risk of damaging internal organs like the bladder or liver Often used in advanced soft tissue sarcoma models or rare peritoneal sarcomas (70,71)
Allows evaluation of advanced sarcoma models Non-specific tumour spread
IV Tumour cells injected into the bloodstream through the tail vein Efficiently produces lung and other haematogenous metastases Does not replicate the early stages of tumour development Widely used in osteosarcoma to model lung metastasis and evaluate metastasis-directed therapies. Also, used in Ewing sarcoma for metastatic spread to lung tissues (66,72,73)
Ideal for studying late-stage disease progression Requires precise technique for successful injections
Effective for delivering tumour cells or therapeutic agents directly into the circulation May result in variable metastatic efficacy
Less invasive than intracardiac methods
ILP Tumour cells, therapeutic agents or other substances are delivered directly to the lung by isolating the pulmonary vasculature for perfusion Localised and targeted delivery to the lungs Highly invasive, requiring surgical intervention Often used in metastasis studies to model lung-specific colonisation by cancer cells or to test localised therapies for pulmonary malignancies (67,74,75)
Minimises systemic effects Requires advanced technical skills
Allows precise study of lung-specific responses Limited to studies focused on the lung
Retro-Orbital Cells are injected into the venous plexus behind the eye Low animal stress compared to tail vein injections Requires skill to avoid complications Used in rhabdomyosarcoma and systemic sarcoma models to study therapies that affect vascular dissemination (76,77)
High efficacy for systemic spread models Used less frequently for sarcomas than for other cancers
Intracardiac Injection of tumour cells into the left ventricle of the heart Efficiently mimics widespread metastasis to multiple organs Technically demanding with a higher risk of procedural error Commonly used in osteosarcoma to model multi-organ metastasis and to study bone-targeting drugs such as bisphosphonates (78-80)
Particularly useful for bone and lung metastasis studies Requires advanced imaging for validation

ILP, isolated lung perfusion; IP, intraperitoneal; IV, intravenous; SC, subcutaneous; TME, tumour microenvironment.

Types of animal models and their evaluation

Sarcomas are divided into sarcomas with simple karyotypes, which are driven by specific genetic mutations such as the EWS-FLI1 fusion in Ewing sarcoma, and sarcomas with complex karyotypes, such as osteosarcoma and leiomyosarcoma, which exhibit widespread chromosomal instability and multiple genetic alterations. These differences require tailored approaches for model development. The main advantages and disadvantages of the models are summarised in Table 5.

Table 5

Overview of animal models in sarcoma research: main strengths and limitations

Model type Description Strengths Limitations References
Syngeneic models Tumour cells from the same species are transplanted into immunocompetent mice, allowing the study of tumour-immune interactions Immunocompetent system enables studying immune-tumour interactions; tumours are genetically matched with immune system and stroma Limited genetic diversity (41,81,82)
High throughput and cost-effectiveness for rapid drug screening May not fully replicate human sarcomas; the murine immune system may not react in the same way
Useful for immunotherapy evaluation Inherent variability in tumour growth and treatment response
Large pool of historical data for comparison
GEMMs Genetically modified mice are designed to express or delete specific oncogenes or tumour suppressor genes, mimicking human sarcoma mutations Recapitulates human genetic alterations in sarcoma Time-consuming to develop (41,45,83-86)
Useful for studying tumour progression and metastasis Breeding challenges
Can incorporate advanced gene-editing tools (e.g., CRISPR) Limited by specific gene mutations
May not fully replicate the complexity of human tumours, including their microenvironment
Chemically induced models Tumours are induced in animals through exposure to chemical carcinogens, such as MCA, mimicking environmental factors in cancer development Mimics environmental carcinogenesis, helping study mutations seen in human sarcomas Variability in tumour formation due to random mutation introduction (82,87,88)
Can mimic mutation profiles of human sarcomas Non-reproducibility due to random mutations leading to inconsistent tumour profiles
Allows exploration of immune system roles in tumour progression Difficult to pinpoint exact mechanisms of chemical-induced sarcoma formation
CDX Human sarcoma cell lines are implanted into immunocompromised mice to study tumour growth and drug response Fast and cost-effective Lack of tumour heterogeneity due to long-term culture in vitro (82,89,90)
Ideal for large-scale drug screening Limited genetic and phenotypic diversity of sarcomas in established cell lines
Useful for studying tumour growth and therapeutic responses in humanised environments Lack of an immune system limits their utility in immunotherapy studies
PDX Direct implantation of patient tumour samples into immunocompromised mice, maintaining the original tumour’s histological and genetic features Retains genetic, histological, and molecular features of human sarcomas Low engraftment success rates for some tumour types (rates largely differ based on the tumour type) (87,88,91,92)
Mimics human tumour microenvironment Limited by availability of fresh patient tumour samples
Useful for personalised therapy and studying drug resistance Costly and time-consuming to establish
Limited immune response due to the use of immunocompromised mice
Humanised PDX models Combines patient-derived tumours with reconstituted human immune systems in immunocompromised mice Accurately models tumour-immune system interactions; it enables the study of interactions in the human immune system implanted into the mice Allogeneic immune response may not fully mimic natural tumour-associated antigen recognition; limitations of immune cells engraftment (83,93-97)
Allows testing of immunotherapies (e.g., anti-PD-1 therapy) Practical challenges such as matching immune cells and repeated sampling; species mismatch between tumour/immune cells and stroma; the supporting stroma is still of murine origin
Long-term immune system engraftment using CD34+ cells Potential for graft vs. host disease as human T-cells and phagocytes can target hosts’ tissues
Costly

CDX, cell-derived xenografts; GEMMs, genetically engineered mouse models; MCA, 3-methylcholanthrene; PD-1, programmed death 1; PDX, patient-derived xenograft.

With the right model, researchers can accurately study tumour behaviour, therapeutic responses and the basic mechanisms that underlie sarcoma development. Their advantages and limitations have to be considered. Syngeneic models (Figure 1A), for instance, are cost-effective and well suited to drug screening, and allow the study of tumour-immune interactions, although they lack genetic diversity. For example, in osteosarcoma model, Roudi et al. (98) established that iron-oxide-enhanced MRI T2/T2* mapping yields highly repeatable and reproducible readouts of tumour-associated macrophages in BALB/c mice, introducing a quantitative imaging endpoint for response monitoring to macrophage-modulating regimens.

Figure 1 The following graphic illustrates the various animal models employed in sarcoma research, delineating the specific methodologies utilised to investigate tumour development and treatment. (A) Syngeneic model: sarcoma cells derived from an inbred strain are implanted into genetically identical mice. This model maintains a functional immune system, thereby facilitating the investigation of immune-tumour interactions. (B) GEM: the mice are genetically modified to express specific mutations that are analogous to those observed in human sarcomas, resulting in the spontaneous development of tumours. (C) Chemically induced model: the mice are exposed to carcinogenic compounds in order to induce cancer, thereby providing insight into the processes of cancer initiation and progression. (D) CDX: the transplantation of established human sarcoma cell lines into immunodeficient mice enables researchers to study the growth of human tumours in a living organism. (E) PDX: tumour tissue from a sarcoma patient is implanted directly into immunodeficient mice, thereby preserving the heterogeneity of the original tumour. This model is of great importance for the advancement of personalised medicine studies. CDX, cell-derived xenograft; GEM, genetically engineered mouse; PDX, patient-derived xenograft.

While genetically engineered mouse (GEM; Figure 1B) models effectively recapitulate human genetic mutations and are valuable for studying tumour progression, they are time-consuming to develop and may not fully capture the genetic complexity of human tumours. GEM have been used for instance, in the conditional KrasG12D;Trp53fl/fl soft-tissue sarcoma model introduced by Kirsch et al. (99) recapitulates de novo sarcomagenesis with lung tropism in immune-competent hosts, introducing a tractable system for co-clinical testing of radiotherapy and targeted agents where tumour evolution and metastasis can be followed longitudinally.

Chemically induced models (Figure 1C) are useful for mimicking environmental carcinogenesis, but their results can be inconsistent. This model was used for example in methylcholanthrene-induced murine sarcomas, Gubin et al. (100) demonstrated that tumour-specific mutant (neo)antigens are key therapeutic targets: checkpoint blockade against CTLA-4/PD-1 elicited rejection, and synthetic long-peptide vaccines encoding the identified neoantigens reproduced the therapeutic effect, establishing this model for immunotherapy and vaccine evaluation.

One of the most common models cell-derived xenograft (CDX, Figure 1D) models allow efficient large-scale drug testing, while PDX (Figure 1E) models retain the genetic characteristics of the original tumour, making them valuable for personalised therapies. However, both CDX and PDX models lack immune system interactions and are often costly and difficult to establish. Igarashi et al. (101) introduced a PDOX model of undifferentiated spindle-cell soft-tissue sarcoma in which pazopanib was found to be more effective than standard treatment regimens. This demonstrated the potential of angiogenesis-directed evaluation in a histology-matched setting. Also, Xu et al. (102) established retroperitoneal liposarcoma PDX lines for subtype-specific drug testing workflows.

Humanised PDX models, although difficult to develop, provide the best representation of the human immune system. For instance, Choi et al. (103) introduced a humanised NSG PDX of dedifferentiated liposarcoma in which pembrolizumab produced tumour-growth inhibition associated with human CD8+ T-cell and NK-cell activity, enabling assessment of human-specific immune mechanisms.

Zebrafish, on the other hand, are less expensive than mice and require less space and maintenance, making them ideal for large-scale studies despite their shorter lifespan. Grissenberger et al. introduced high-content screening in Ewing sarcoma zebrafish xenografts, revealing dual MCL-1/BCL-X_L inhibition to be a potent combination within days. This provided a rapid triage step before murine confirmation (104). In parallel, Sturtzel et al. introduced a standardised, imaging-assisted, 96-well zebrafish workflow applicable to paediatric solid tumours, including sarcomas (105).

Conclusions

Choosing the right animal model is in very complex and requires the consideration of multiple factors. Some rare sarcoma types, owing to their rarity and complex molecular drivers, such as clear cell sarcoma and alveolar soft part sarcoma, present significant challenges for developing relevant models. Collaborative efforts, such as international sarcoma networks and biobank initiatives, are essential to pool resources to develop and validate models for these subtypes. In addition, understanding the metastatic behaviour of sarcomas, particularly their predilection for lung metastases, requires refined models that recapitulate the specific tumour microenvironment, including hypoxia and angiogenesis.

The role of signalling pathways such as p53, Rb, PI3K/AKT and Wnt in driving sarcomagenesis and the contribution of epigenetic alterations mediated by fusion oncoproteins such as EWS-FLI1 and SS18-SSX must also be considered in model selection. Recent studies using GEMMs and PDX models have identified therapeutic vulnerabilities, such as the dependence on oxidative phosphorylation in YAP1-driven sarcomas, which could be exploited with combination therapies. Multiple tools can help with the selection, including International Mouse Strain Resource and Rat Genome Database.

Our review also comes with limitations; it primarily summarises existing preclinical studies and methodological descriptions, with limited quantitative synthesis (e.g., meta-analysis or systematic scoring of model fidelity or translational success) included. Furthermore, the paper notes that many sarcoma models fail to fully capture the genetic and immunological complexity of human tumours, particularly ultra-rare or fusion-driven subtypes. Some models, such as chemically induced sarcomas or CDX, have limited clinical relevance due to the artificial evolution of tumours or the lack of interactions with the immune system. The authors acknowledge the gap between preclinical findings and clinical outcomes, citing the high failure rate in drug development and the inability of many models to accurately predict human toxicity or treatment efficacy.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the Narrative Review reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1218/rc

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1218/prf

Funding: This work was supported by the National Science Centre (No. 2019/35/O/NZ2/03761, to A.M.C.).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1218/coif). Piotr Rutkowski serves as an unpaid editorial board member of Translational Cancer Research from April 2025 to March 2027. Piotr Rutkowski declared that he has received consulting fees from Bristol-Myers Squibb, MSD, Novartis, Pierre Fabre, Philogen, Genesis, Medison Pharma; honoraria from Bristol-Myers Squibb, MSD, Novartis, Pierre Fabre, Genesis, and Medison Pharma; Speakers’ Bureau from Novartis, Pierre Fabre, MSD, BMS, and Genesis; and support for attending meetings from Pierre Fabre. His institution has received research funding from Pfizer, Roche, and Bristol-Myers Squibb. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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Cite this article as: Remiszewski P, Czarnecka AM, Siedlecki E, Mikula M, Rutkowski P. Introduction to animal modelling: factors and tools for choosing the optimal model for sarcoma research—a comprehensive literature review. Transl Cancer Res 2026;15(1):66. doi: 10.21037/tcr-2025-1218

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