Cancer metastasis is a complex, multistep process in which cancer cells spread from the primary tumor to distant sites throughout the body (1, 2) ( Figure 1 ). Understanding the mechanisms underlying metastasis is essential for developing effective therapeutic strategies. To this end, a wide range of experimental models—including xenograft models, orthotopic models, genetically engineered mouse models (GEMMs), and in vivo imaging approaches—have been established to investigate different aspects of metastatic progression (3). Each model offers unique advantages and limitations, and selecting the appropriate model depends on the specific research questions and objectives (4). Importantly, integrating multiple experimental models can yield a more comprehensive understanding of metastasis and enhance the translational relevance of preclinical findings. This review provides an overview of the existing, widely used, and emerging models of cancer metastasis for basic, translational, and clinical research. We highlight their critical roles in elucidating metastatic mechanisms, advancing metastasis-specific therapeutic strategies, and establishing clinically relevant platforms for drug development and therapeutic evaluation in patients with metastatic cancer.

Modeling cancer metastasis plays a pivotal role in advancing our understanding of the metastatic process and its clinical implications. Experimental metastasis models are essential for identifying metastasis-related genes and pathways, assessing therapeutic strategies, investigating tumor–microenvironment interactions, evaluating imaging techniques, enabling personalized medicine, discovering biomarkers, and conducting preclinical testing for drug development (5). These models allow researchers to dissect the molecular and cellular mechanisms driving metastasis by recapitulating key steps of the process, including invasion, intravasation, circulation, extravasation, and colonization. By comparing metastatic and non-metastatic cells or tissues, researchers can identify genetic and epigenetic alterations that promote metastatic progression, providing valuable insights into potential therapeutic targets (6). Experimental models are also indispensable for evaluating the efficacy of anti-metastatic therapies. Preclinical testing (7) of drugs or combination treatments in these models helps determine their ability to inhibit metastasis, reduce tumor burden at distant sites, and improve overall survival, serving as a critical step before advancing to clinical trials. Since the tumor microenvironment profoundly influences metastasis, these models enable researchers to investigate interactions between cancer cells and surrounding stromal cells, immune cells, extracellular matrix components, and vasculature. Such interactions regulate processes like epithelial-to-mesenchymal transition (EMT) (8), angiogenesis, immune evasion, and metastatic colonization.

Metastasis models are also essential for developing and optimizing imaging techniques to detect and monitor metastatic lesions. The use of fluorescent probes, radiolabeled tracers, and advanced imaging modalities facilitates real-time visualization of cancer cell dissemination, assessment of metastatic potential, monitoring of treatment response, and evaluation of imaging-guided therapeutic interventions (9). Patient-derived experimental models, such as xenografts and organoids, enable the study of metastasis in the context of individual tumors. These models provide a platform for identifying predictive biomarkers, evaluating personalized treatment responses, and informing clinical decision-making (10). Overall, metastasis research models serve as a crucial bridge between basic research and clinical translation. Extensive exploration and refinement of these models will greatly enhance our understanding of metastatic mechanisms, aid in the identification of therapeutic targets, improve treatment strategies, and ultimately contribute to better outcomes for patients with metastatic cancer.

Cancer metastasis modeling has evolved as our understanding of the disease has advanced. The phenomenon of cancer metastasis was first documented in the 19th century, but the underlying mechanisms were not well defined at the time (11). Surgeons noticed that some patients developed tumors in distant sites after surgical removal of the primary tumor implying that cancer could spread throughout the body.

In the early 20th century, scientists found that cancer cells can grow and form tumors in different hosts by transplanting tumor fragments or cells from one animal to another, which laid the foundation for studying tumor biology and provided early insights into the metastatic potential of cancer cells. In the mid-20th century, researchers began developing experimental models to focus on the spread of cancer. This research involved injecting cancer cells into experimental animals, primarily mice, to investigate their ability to form secondary tumors at distant sites in which these models allowed for controlled experimentation and provided a framework to study the different steps of metastasis. The adventure of cell culture techniques, such as establishing cancer cell lines, allowed researchers to study cancer cells in a controlled laboratory setting since the late 20^th century and facilitated the investigation of cellular and molecular mechanisms underlying metastasis, including cell migration, invasion, and adhesion (12).

Cancer research was further revolutionized by the advent of genetic engineering techniques in the late 20th century. Genetically engineered mouse models (GEMMs) that carried specific genetic alterations found in human cancers were established. These models allowed for the study of tumor initiation, progression, and metastasis in a more physiologically relevant context. In the meantime, xenograft models, where human tumor cells are transplanted into immunocompromised mice, became widely used for studying cancer metastasis. This approach allowed for the transplantation of human cancer cells and the assessment of their metastatic potential in an in vivo system (13).

Imaging technologies have gained substantial advancements since the beginning of the 21st century especially in intravital microscopy and bioluminescence imaging (14). These techniques enabled real-time visualization and tracking of cancer cells in live animals to provide dynamic insights into the metastatic process (15).

Patient-derived models, such as patient-derived xenografts (PDX) and organoids, have been introduced more recently for studying cancer metastasis. These models better preserve the genetic and molecular heterogeneity of human tumors and allow for personalized medicine approaches and drug testing (16).

In summary, the history of cancer metastasis modeling is outlined by a progression from observational studies to the development of controlled experimental models that mimic different aspects of metastasis (17). All those models have played a crucial role in advancing our understanding of cancer metastasis and have facilitated the development of new therapies and treatment strategies (18).

While mammalian models like mice are the most adapted models for studying cancer metastasis, non-mammalian models utilized to gain insights into metastatic processes are also available. These non-mammalian models offer more benefits such as lower cost, ease of manipulation, and unique experimental opportunities (19). Some non-mammalian models such as zebrafish (Danio rerio), drosophila melanogaster (Fruit Fly), caenorhabditis elegans (Nematode), chick embryo chorioallantoic membrane (CAM) assay, and cnidarians (Hydra and Sea Anemones) are currently selected in cancer metastasis research ( Figure 2 ).

Zebrafish (Danio rerio) has been a powerful model for studying cancer metastasis, in which its transparent embryos allow direct visualization of cancer cell behavior and interactions with host tissues (20). The genetic and molecular similarities between zebrafish and humans make this model valuable in studying cancer cell migration, invasion, extravasation, and colonization for understanding metastasis and screening anti-metastatic drugs (21).

Fruit flies (Drosophila melanogaster) can be easily manipulated with well-characterized genetics to study various biological processes, including cancer metastasis (22). Drosophila models were frequently employed to investigate cellular invasion, epithelial-mesenchymal transition (EMT), and interactions between cancer cells and the tumor microenvironment (23) in identifying novel metastasis-regulating genes and signaling pathways.

As a transparent roundworm, C. elegans (Caenorhabditis elegans) are widely applied to study various biological processes (24). Despite lacking an immune system, its simple anatomy and well-defined cell lineage allow for precise observations of cancer cell behavior by using C. elegans to explore aspects of metastasis such as cell migration, invasion, and response to therapeutic interventions.

Chick embryo chorioallantoic membrane (CAM) assay involves grafting tumor cells onto the chick embryo CAM as an ex vivo model which provides a rich vascular network, facilitating tumor cell growth and angiogenesis (25). This assay has been used to study tumor cell invasion, angiogenesis, and the effects of anti-angiogenic therapies. It is required for assessing tumor cell interactions with the vasculature during metastasis.

Cnidarians (Hydra and Sea Anemones) are simple aquatic organisms exhibiting regenerative capabilities. Some species of hydra and sea anemones have been used as models for studying cancer cell migration, invasion, and regeneration (26). These models offer the advantage of easy manipulation and can provide insights into the early evolutionary origins of metastatic processes.

While non-mammalian models provide valuable insights into metastatic processes, they have limitations. They may not fully recapitulate the complexity of human metastasis, including interactions with the immune system and organ-specific microenvironments. Therefore, non-mammalian models are often used complementary to mammalian models to provide additional insights and novel perspectives in cancer metastasis research (27).

Mammalian cancer metastasis models are experimental systems used to study the process of cancer metastasis, which is the spread of cancer cells from the primary tumor to distant organs or tissues in the body. These models are designed to replicate the complex interactions and steps involved in metastasis, allowing researchers to investigate the underlying mechanisms and test potential therapeutic interventions (27). Here are some mammalian cancer metastasis models commonly used in research discussed next.To better understand the strengths and limitations of currently available metastasis models, Table 1 summarizes the key characteristics of several commonly used experimental systems ( Table 1 ).

PDX-based cancer metastasis models, also known as patient-derived xenograft models, are preclinical models that involve the implantation of patient-derived tumor tissue directly into immunocompromised mice or other animal hosts. These models are developed to preserve the genetic and phenotypic characteristics of the original tumor, including its metastatic potential, allowing researchers to study the metastatic behavior of cancer cells in a more clinically relevant context (28).

PDX models begin with the collection of tumor tissue from cancer patients, typically obtained through biopsies or surgical resections. The patient-derived tumor tissue from primary tumors or metastatic sites is then implanted into immunodeficient mice including severe combined immunodeficiency (SCID), NOD/SCID, or NSG (NOD/SCID/IL2Rγnull) mice, which lack a functional immune system ( Figure 3 ). The implanted tumor tissue can be subcutaneously implanted or orthotopically transplanted into the appropriate anatomical site to mimic the original tumor as a PDX model. The tumor survives, grows, and can be passed into subsequent generations of mice. Extensive characterization of PDX models using various molecular and histopathological techniques is required to confirm their fidelity to the original patient tumor (29).

Researchers can study the metastatic behavior of cancer cells. This includes monitoring the dissemination of cancer cells from the primary tumor site to distant organs or tissues, investigating the mechanisms of metastasis, and assessing the response to anti-metastatic therapies once the PDX models are established. PDX-based cancer metastasis models have been applied to evaluate the efficacy of potential therapeutic agents in a more clinically relevant setting. Treating the PDX models with different drugs or drug combinations helps researchers assess their impact on primary tumor growth and metastasis (30). Using PDX models to explore personalized medicine approaches, treatment responses in individual patient-derived models can guide treatment decisions (31).

PDX-based cancer metastasis models offer several advantages over traditional cell line-based models by maintaining the genetic and phenotypic heterogeneity of the original tumor, including the metastatic potential, making them more representative of patient tumors (32). These models provide a novel platform for researchers to study the complex interactions between cancer cells and the tumor microenvironment, and they have the potential to guide clinical decision-making and the development of targeted therapies for metastatic disease (33).

Patient-derived organoid models or tumor organoids are three-dimensional cultures derived from patient tumor tissues that mimic the complexity and heterogeneity of the original tumor which have gained increasing attention in cancer research and are useful for studying various aspects of cancer, including metastasis. Tumor cells isolated from biopsies or surgical resections of patients are first embedded in a suitable matrix, such as Matrigel, and cultured in a specialized medium that supports their growth as three-dimensional organoids. This culture allows the cells to maintain their genetic and phenotypic characteristics, including their metastatic potential (34).

Manipulation of Patient-derived organoids is valuable in studying various steps of the metastatic cascade, including invasion, intravasation, circulation, extravasation, and colonization. Behavior analysis of cancer cells within the organoids enables researchers to gain insights into the molecular mechanisms underlying metastasis and identify potential therapeutic targets (35) and provides a valuable tool for studying cancer metastasis by offering a more physiologically relevant and patient-specific context compared to traditional cell line models (36).

PDX-derived tumor cell line models are established from patient-derived xenografts to study the metastatic behavior of cancer cells (37). PDX tumor cells can be isolated and cultured in vitro to establish cell lines (38) which are derived from the patient’s tumor and are representative of the tumor’s genetic and phenotypic features.

Researchers have applied PDX-derived tumor cells in various experimental setups (39), including in vitro migration and invasion assays and in vivo metastasis models. These systems allow monitoring of metastatic potential and evaluation of therapeutic responses (40).

PDX-derived tumor cell line-based models have both advantages of PDX models (retention of patient tumor characteristics) and in vitro cell line models (ease of manipulation and scalability) (41). Those models offer a valuable tool for studying the metastatic behavior of cancer cells and assessing potential therapeutic interventions in a controlled experimental setting. While PDX-derived tumor cell lines can provide important insights, they still belong to an in vitro model and may not fully recapitulate the complexity of the tumor microenvironment and the entire metastatic process seen in vivo (42) ( Figure 4 ).

GEM cancer metastasis models are specifically designed to study cancer metastasis which involves the manipulation of specific genes or signaling pathways in mice to recapitulate key aspects of human cancer metastasis (43) for understanding the molecular mechanisms underlying metastasis and testing novel therapeutic approaches (44).

Manipulation of specific genes or signaling pathways to mimic key features of human cancer metastasis induces the formation of primary tumors and subsequent metastasis to some organs or tissues in GEM models mimicking what occurs in human cancers (45–47). Tissue or organ-specific metastasis GEM models have been established in breast cancer metastasis research by targeting specific genes in the mammary gland to induce the development of primary breast tumors that subsequently metastasize to other organs, such as lungs or bones.

Metastasis models modified from GME provide an opportunity to investigate the molecular mechanisms underlying metastasis by studying the genetic alterations introduced in the mice and analyzing the resulting tumors and metastases in which researchers can identify critical genes and signaling pathways involved in different steps of the metastatic cascade (43). GEM cancer metastasis models are valuable for testing the efficacy of novel therapeutic interventions specifically targeting metastasis which involve administering targeted therapies, immunotherapies, or combination treatments to the mice and assessing their impact on primary tumor growth, metastasis, and overall survival (47). However, GEM models have limitations and may not fully recapitulate the entire complexity of human metastasis, a combination of GEM models with other experimental systems is often used to gain a comprehensive understanding of metastatic processes.

Cancer cell line xenograft models are commonly used in cancer metastasis studies which involve the transplantation of established cancer cell lines into immunocompromised mice or other animal hosts to investigate various aspects of metastasis (48). Cancer cell lines derived from human or animal tumors are selected based on their known metastatic potential or specific molecular characteristics associated with metastasis (39) and cultured in vitro and prepared for transplantation into animal hosts (40). Cancer cells are injected or implanted into immunocompromised mice, typically subcutaneously or orthotopically, to mimic the primary tumor site in a controlled in vivo environment (49).

Development of the primary xenograft tumors is crucial in assessing the dissemination of cancer cells from the primary site to distant organs or tissues, the colonization of secondary tumors, and the evaluation of metastatic burden. Xenograft tumors can be analyzed using molecular techniques to study the genetic and phenotypic features associated with metastasis which include genetic profiling, gene expression analysis, and examination of specific markers or signaling pathways involved in metastasis (50).

Application of cancer cell line xenograft models to evaluate the efficacy of therapeutic interventions targeting metastasis includes testing the impact of different drugs, treatment combinations, or experimental therapies on primary tumor growth and metastatic spread (51). Cancer cell line xenograft models are a simplified and controlled system for studying certain aspects of cancer metastasis allowing researchers to investigate the behavior of cancer cells in vivo, assess their metastatic potential, and evaluate therapeutic interventions (52). The limitations of these models, including potential differences from human tumors, lack of immune system interactions, and limited representation of the complex tumor microenvironment (48) make it essential to integrate cancer cell line xenograft models with other model systems to gain more comprehensive insights into cancer metastasis.

Ex vivo cancer metastasis models apply cultured tissues or organoids derived from patients or animal models to study the metastatic behavior of cancer cells which provide a controlled and manipulable environment to investigate various aspects of metastasis, such as the invasion of cancer cells, interactions with the surrounding microenvironment, and response to therapeutic agents (56). Ex vivo cancer metastasis models currently include organotypic slice cultures, organoid cultures, microfluidic platforms, and explant cultures (57).

Organotypic slice cultures are culturing thin slices of intact tumor or normal tissue ex vivo to maintain the architecture and cellular heterogeneity of the original tissue, allowing researchers to study the invasive behavior of cancer cells within a more physiologically relevant environment. The slices can be exposed to different factors or drugs to investigate their effects on metastasis (58).

Organoid cultures can initiate and sustain three-dimensional structures derived from stem cells or tissue samples capable of self-organizing and recapitulating the characteristics of the original tissue. Cancer organoids can be generated from patient-derived tumor samples or genetically engineered models providing a platform to study various aspects of metastasis, including invasion, intravasation, and colonization while retaining the genetic and phenotypic features of the primary tumor (59).

Microfluidic platforms as microfluidic devices offer a controlled and dynamic environment to mimic specific aspects of the metastatic process. These platforms are applied to recreate features of the tumor microenvironment, such as blood vessels, lymphatics, and extracellular matrix components so cancer cells can be introduced into these devices to study their migratory behavior, response to chemotactic signals, and interactions with different cell types (60).

Explant cultures can maintain small tissue fragments from tumors or metastatic sites ex vivo and be cultivated in various culture systems, including three-dimensional matrices or bioreactors, to investigate metastatic behavior. Explant cultures preserve the complex interactions between cancer cells and the surrounding stroma (61) while allowing researchers to monitor the growth and spread of cancer cells.

As a valuable tool for studying the biological processes of metastasis and evaluating potential therapeutic interventions, ex vivo cancer metastasis models offer a compromise between in vivo models being complex and less controlled, and in vitro cell culture models lacking the physiological context of the tumor microenvironment (62). Integrating ex vivo models with other experimental systems provides more comprehensive insights into the metastatic process and develops strategies to prevent or target metastasis more effectively.

Tissue or organ-specific cancer metastasis models are essential for studying the unique aspects of metastasis in different tissues or organs, and they can mimic the microenvironment of a particular tissue or organ where metastasis occurs and incorporate key cellular and extracellular components, such as stromal cells, immune cells, and extracellular matrix components, that are specific to the tissue of interest (63). These models provide insights into the interactions between metastatic cancer cells and the surrounding tissue, which influence metastatic progression by recapitulating the tissue-specific microenvironment (64).

To unravel the underlying mechanisms of metastasis in different tissues or organs, tissue-specific metastasis models can be tailored to represent specific aspects of metastatic processes observed in tissues. For example, liver metastasis models may focus on understanding the interactions between cancer cells and hepatocytes, meanwhile, models of lung metastasis may refer to the mechanisms of extravasation and interaction with lung epithelial cells. Tissue or organ-specific metastasis models are valuable in evaluating the efficacy of therapeutic strategies targeting tissue-specific metastases if a particular tissue is known to have unique signaling pathways or immune responses (65).

Tissue-specific metastasis models which improve the characterization and evaluation of biomarkers specific to tissues or organs can be adapted to assess the expression or functions of tissue-specific biomarkers in metastatic tumors. Metastasis models with tissue or organ specificity enable the further analysis of tissue-specific immune responses and immunomodulatory factors to elucidate the interactions between metastatic cancer cells and immune cells within the tissue microenvironment for identifying potential targets for immunotherapies and develop strategies to enhance anti-tumor immune responses in specific tissues (66).

Tissue or organ-specific metastasis models facilitate the translation of preclinical findings to clinical practice. They provide platforms for studying tissue-specific metastasis and evaluating the efficacy of tissue-specific treatment approaches. The knowledge gained from these models can inform clinical decision-making, treatment selection, and the design of clinical trials for patients with tissue-specific metastases (66).

Cancer metastasis models with tissue or organ-specific characteristics are critical in understanding the unique aspects of metastasis in different tissues or organs which help recapitulate tissue-specific microenvironments, investigate tissue-specific metastatic mechanisms, evaluate tissue-specific therapeutic strategies, assess tissue-specific biomarkers, examine tissue-specific immune responses, and facilitate the translational impact of research on tissue-specific metastasis (67).Among various organ-specific metastases, bone metastasis represents a particularly well-characterized and clinically relevant model.

Bone metastasis is a complex, multistep process involving the colonization and growth of cancer cells within the bone microenvironment, dramatically contributing to disease progression and poor clinical outcomes. This process is characterized by a dynamic and reciprocal interaction between metastatic cancer cells and the bone microenvironment, commonly referred to as the “vicious cycle” of bone metastasis (68). Following dissemination from the primary tumor, cancer cells that reach the bone must first survive within the unique bone microenvironment. They adhere to the bone matrix and interact with resident cells, including osteoblasts, osteoclasts, bone marrow stromal cells, and immune cells (69). Once established, metastatic cells disrupt the normal balance between bone formation and resorption.

In osteolytic bone metastases, which are typical of breast cancer and some lung cancers, tumor cells secrete factors such as parathyroid hormone-related protein (PTHrP), interleukins (e.g., IL-6, IL-11), and other osteoclast-activating factors (70). These stimulate osteoblasts to express receptor activator of nuclear factor kappa-β ligand (RANKL), which in turn promotes osteoclast differentiation and activation. The resulting bone resorption releases growth factors stored in the bone matrix, such as transforming growth factor-beta (TGF-β) and insulin-like growth factors (IGFs), which further stimulate tumor growth, thereby perpetuating the vicious cycle. Conversely, osteoblastic bone metastases, commonly seen in prostate cancer, are associated with excessive bone formation (71). Tumor-derived factors such as endothelin-1 and bone morphogenetic proteins (BMPs) stimulate osteoblast activity, leading to abnormal bone deposition. However, this newly formed bone is often structurally weak and disorganized, contributing to skeletal complications.

Experimental models are essential tools for dissecting the complex interactions between cancer cells and the bone microenvironment, as well as for evaluating potential therapeutic strategies. In vitro models, including 2D co-culture systems, 3D spheroids, and organ-on-a-chip platforms, allow controlled studies of cancer–bone cell interactions and early metastatic steps (72). In vivo models, such as intratibial injection, intracardiac injection, or orthotopic models in mice, recapitulate various stages of bone colonization and the development of osteolytic or osteoblastic lesions, providing insights into disease progression and therapeutic responses. Importantly, the integration of complementary in vitro and in vivo models is crucial to overcome the limitations of individual systems and to generate a more comprehensive understanding of bone metastasis. Such integrative approaches can more accurately mimic the complex biology of the bone metastatic niche, helping to identify molecular drivers of metastasis and to develop clinically relevant therapeutic strategies ( Figure 5 ).

Lineage tracing molecular marks utilized in cancer metastasis models to track and identify the progeny of specific cells or lineages during the metastatic process enables researchers to understand the clonal dynamics, cellular heterogeneity, and fate of individual cells during metastasis (85). Lineage tracing in cancer metastasis models includes genetic lineage tracing, fluorescent protein labeling, barcoding, Single-cell RNA sequencing, and various lineage-specific reporter systems.

Genetic lineage tracing introduces genetic markers or reporters into specific cell populations by using genetically engineered mice or viral vectors to express fluorescent proteins, such as GFP (green fluorescent protein), or enzymes capable of permanently labeling cells, such as Cre recombinase or Flp recombinase (86). Crossing these mice with cancer models or inducing the expression of the markers in specific cells helps track the descendants of marked cells during metastasis.

Fluorescent proteins, such as GFP, can be expressed under the control of specific promoters or genetic elements associated with metastatic cells. By introducing these markers into cancer cells or using them to label specific populations of cells, researchers can track the migration, invasion, and colonization of these cells during metastasis (87).

Barcoding is to introduce unique DNA or RNA sequences into individual cell clones labeled with a specific barcode, allowing the identification, and tracking of their progeny during metastasis through applying viral vectors or CRISPR-based techniques to introduce the barcodes into cancer cells. Barcoding with high-throughput sequencing technologies is the most used method for analysis of the metastatic potential and clonal evolution of individual cancer cells (88).

Single-cell RNA sequencing (scRNA-seq) profiles gene expression at the single-cell level. Sequencing the RNA from individual cells helps identify the transcriptional signatures of specific cell lineages or clones during metastasis and provides insights into the cellular heterogeneity and differentiation trajectories of metastatic cells (89).

Various lineage-specific reporter systems are employed to trace the progeny of specific cell types during metastasis by using genetic elements or promoters that are active only in certain cell lineages or stages of development. The metastatic potential of cell populations can be selectively labeled and tracked by driving the expression of reporters or markers under these lineage-specific promoters, researchers. Lineage tracing molecular marks helps trace the origin, dynamics, and fate of cancer cells during metastasis and uncover the clonal evolution, cellular heterogeneity, and mechanisms underlying metastatic progression (90). Lineage tracing with advanced molecular and imaging approaches allows for a deeper understanding of the metastatic process and may contribute to the development of targeted therapies against metastatic disease (91).

Evolutionary profiling of cancer metastasis models involves studying the dynamic changes and evolutionary processes that occur during metastasis. This profiling aims to understand how tumors evolve, acquire metastatic properties, and adapt to new microenvironments. Some approaches for evolutionarily profiling cancer metastasis models include genetic profiling, studying clonal dynamics and heterogeneity, tumor microenvironment characterization, functional profiling, imaging-based profiling, and integrating multi-omics data (92).

Genetic profiling of genomic alterations in primary tumors and metastatic lesions, such as mutations, copy number variations, and chromosomal rearrangements, is crucial in identifying genetic changes contributing to metastasis and assessing the clonal evolution of metastatic cells.

Analysis of clonal dynamics and heterogeneity of the subpopulations of cells contribute to metastasis. Techniques like single-cell sequencing, bulk sequencing, and lineage tracing are available to detect the clonal composition, genetic diversity, and evolutionary trajectories in metastatic tumors to understand the cellular dynamics and selection pressures during metastasis.

Evolutionary profiling of the tumor microenvironment in metastasis involves characterizing the interactions between cancer cells and the surrounding stromal cells, immune cells, and extracellular matrix components which includes assessing the presence and activation state of immune cells, analyzing the composition of the extracellular matrix, and evaluating angiogenesis and hypoxia within metastatic lesions. Functional profiling of functional changes associated with metastasis includes analyzing alterations in signaling pathways, gene expression profiles, epigenetic modifications, and metabolic changes. Profiling of functional genomics, proteomics, and metabolomics, provides insights into the molecular mechanisms underlying metastasis (93).

MRI, PET, optical imaging, and other imaging techniques utilized to profile the spatial and temporal dynamics of metastatic lesions allow researchers to monitor tumor growth, visualize the distribution of metastatic lesions, and assess the response to therapeutic interventions. Advanced imaging approaches like multiplexed imaging and intravital microscopy can confer more high-resolution characterization of the tumor microenvironment and cellular interactions (94).

Integrating multi-omics data including genomic, transcriptomic, proteomic, and epigenomic data can acquire a comprehensive view of the evolutionary landscape of metastatic tumors in identifying key driver events, pathways, and regulatory networks associated with metastasis (95). Evolutionarily profiling cancer metastasis models provides a deeper understanding of the molecular and cellular changes that occur during metastasis. All this knowledge can guide the development of targeted therapies, identify biomarkers of metastatic progression, and offer insights into strategies for prevention and treatment of metastatic disease (96).

The future of cancer metastasis models will provide more exciting promise and potential for advancing our understanding of cancer progression and developing effective treatments. Since cancer metastasis models will continue to evolve and become more accurate and sophisticated, advances in new technologies like computational modeling, machine learning, and artificial intelligence (AI) will generate more realistic and comprehensive models. Better models will more efficiently capture the complexity of metastasis and incorporate various factors such as genetic mutations, cellular interactions, and microenvironmental influences.

Predictably, the future of cancer metastasis models will likely be tailored to individual patients by integrating patient-specific data, such as genomic information, molecular profiles, and clinical data, models. Metastasis models will be highlighted by integrating data from multiple omics technologies, such as genomics, transcriptomics, proteomics, and metabolomics. The combination of these diverse datasets enhances a more comprehensive understanding of the molecular mechanisms underlying metastasis in identifying novel biomarkers, therapeutic targets, and potential drug combinations (139).

Future models will also focus on accurately exploring the interactions between cancer cells and their surrounding microenvironment, including immune cells, stromal cells, and extracellular matrix components. This holistic approach will be applied to the dynamic processes driving metastasis and facilitate the development of targeted therapies.

Combining in vitro and in vivo systems will likely be crucial in studying cancer metastasis despite that in silico models are valuable. In vitro models, such as organoids and 3D cultures, can capture specific aspects of cancer biology, while animal models offer a more systemic view. Integrating these approaches will enhance our understanding of metastasis and enable the evaluation of therapeutic interventions.

Cancer metastasis models will continue to play a vital role in high-throughput screening platforms for drug discovery. Utilizing large-scale screening approaches benefits researchers in identifying potential drugs specifically targeting metastatic processes. These models can also be used to predict drug response and optimize treatment regimens for individual patients (140).

Collaboration and data sharing among researchers and institutions will be crucial for advancing cancer metastasis models. Integrating diverse datasets from various research groups will enable the development of more robust and generalizable models. Initiatives like data consortia and open-access repositories will facilitate the sharing of data, methods, and models, accelerating progress in the field (141).

The future of cancer metastasis models is promising. Advances in computational modeling, personalized medicine, multi-omics integration, microenvironment modeling, hybrid in vitro/in vivo approaches, high-throughput screening, and collaborative efforts will revolutionize our understanding of metastasis and aid in developing effective treatments for cancer patients( Figure 7 ).