Journal List > Brain Tumor Res Treat > v.11(1) > 1516081738

Lee and Yang: Advances in Brain Metastasis Models

Abstract

To obtain achievements in addressing the clinical challenges of brain metastasis, we need a clear understanding of its biological mechanisms. Brain metastasis research is challenged by many practical scientific barriers. Depending on the purpose of the study, experimental brain metastasis models in vivo can be used. It is now possible to re-create the architecture and physiology of human organs. Human organoids provide unique opportunities for the study of human disease and complement animal models. The translation of experimental findings to clinical application has several barriers in the development of treatment for brain metastasis. A variety of models have provided significant contributions to the knowledge of brain metastasis pathology and remain pivotal tools for examining novel therapeutic strategies.

INTRODUCTION

Metastasis is a cancer that has spread beyond the point of origin to distant areas of the body [1]. Of all organs that these metastatic cells colonize, it is estimated that the brain is responsible for 9% to 17% of systemic cancers [2]. The occurrence of brain metastasis varies according to the type of primary cancer, occurring most frequently in primary lung (20%), melanoma (7%), and breast (5%) cancers [3]. As treatment modalities for primary cancers have improved, metastasis is becoming the major cause of morbidity and mortality in cancer patients [4]. The improved control of primary tumors results in longer survival and the possibility of brain metastasis is subsequently increased [5].
The mechanisms regulating and initiating brain metastasis are not clearly known due to lack of identifying the early stages of metastasis even though by using the detection modalities and visualizing techniques, which are hindering the development of preventive therapies [6]. Therefore, it is urgent to have experimental models in order to recapitulate clinical courses, to investigate the metastatic process, and to validate new therapeutic targets. However, few models can handle the range of unresolved questions. Thus, choosing an appropriate model depends on the scientific topics that the researcher is seeking. In this review, we summarize different experimental brain metastasis models. While most studies have used murine models, different models are also considered to complement these experimental resources and are introduced.

BRAIN METASTATIC PROCESS

After cancer cells have grown to form a primary tumor, several enzymes allow the cancer cells to invade local tissues by degrading basement membranes. The cancer cells can enter the blood stream or lymphatic system in a process called intravasation, by squeezing through the surface of blood vessels. Once within the circulatory system, they disseminate to distinct sites of the body and become lodged into the capillaries of other organs. These cells then undergo extravasation by moving through the vessel membranes and forming micrometastasis. At this point, the cancer cells can colonies, forming secondary tumors. Most cancer cells will not survive this process, particularly due to a hostile microenvironment. A period of latency is required [7]. Even if only organ colonization is considered, the number of successful metastatic cells that complete extravasation into the brain could be 1 in 100 [8]. The brain microenvironment is a unique compartment within the body. The resident cells, such as microglia, oligodendrocytes, astrocytes, and neurons, create a complex and dynamic microenvironment and are involved with metastatic cancer cells [9]. Additionally, the brain is separated from the peripheral vasculature by the blood–brain barrier (BBB), which is a selective filter that enters the systemic circulation. The BBB impairment is frequently observed in brain metastasis and the blood-tumor barrier (BTB) is created [10]. The formation of the tumor destroys the integrity of BBB and BTB, which causes damage to the original environment. This unique condition allows tumors located in the brain to have unique cell types, anatomical structures, metabolic constraints, and immune environments [11].

IN VITRO MODELS OF METASTASIS

Even though the dynamic cascade of the metastasis makes it challenging to investigate each step precisely, many assays of high value have been developed. Scratch-wound and zone exclusion assays examine the migration and invasion of cancer cells [12]. This method has the variability in the locations selected at each experiment. Time-lapse microscopy allows the observation of real-time imaging of cell motility, from determining the rate of cell, characterizing the morphological changes achieved by metastatic cells and identifying the type of motility [1314].
The in vitro assay is largely two-dimensional (2D) lacking microenvironmental influence and cell to cell interactions. These deficiencies hinder the translation of the assays. Many efforts have been performed to develop three-dimensional (3D) assays retaining these essential interactions, such as assays incorporating stromal cells [15] and assays that allow adhesion [16]. The tumorsphere is spherical structures generated by cancer stem cells (CSCs). CSCs facilitate the migration. Genetic signatures in CSCs are thought to predict tumor recurrence and metastasis [1718].
Organoids generated from resected tumors can organize into hierarchical structures that reflect the original tissue [19]. Organoids have similarities to patient’s specimens than cells grown under 2D culture system [20]. A recent protocol using human cancer cells and embryonic stem cell-derived brain organoids successfully recapitulates the brain metastasis process and provides a useful platform for drug development [21].
The type of cell line can be selected according to the experimental purpose. Commercial cell lines are easily available and characterized by simple maintenance and consistent growth rates. Primary patient-derived cell lines are developed through several passages of culture. This cell line has a more accurate molecular characterization of the original patient tumor than commercial cell lines. Because these model systems serve to predict the efficacy of potential therapies, they help make clinical decisions and improve the application of personalized medicine [22].

IN VIVO MODELS OF METASTASIS

The advantage of in vivo models to identify therapeutic candidates is their ability to replicate the clinical progression of a given disease (Table 1). Rodents have proven valuable for developing models that advance the knowledge of brain metastasis research [23] and evaluating novel candidate therapies [24]. Several patient-derived xenograft (PDX) models have been developed and evaluated for studying brain metastasis. PDXs can maintain better tumor heterogeneity, biology and microenvironment compared to in vitro models [25]. The use of these in vivo models has led to the proposal of relevant genetic alterations essential for metastatic progression and the identification of potential drug candidates to treat them.

Syngeneic

The syngeneic mouse model is a brain metastasis model that involves direct injection of an allograft of immortalized mouse cancer cells into mice [26]. Both the donor mouse and the host mouse are usually from the same inbred lineage. Because the species of the cell origin and the host model are matched, the syngeneic model allows mice to maintain consistently competent immune system [27]. This feature ensures that the syngeneic model is particularly suitable for studying the interaction between cancer and immune cells as well as the efficacy of immunotherapy.

Humanized

Humanized models are created by grafting immune system tissues and immune cells derived from human into immunodeficient mice. In the beginning, this model was established by the transplantation of human-derived peripheral blood mononuclear cells or hematopoietic stem cells. Humanized mice could accept the xenograft steady growth and mimic human immune system. The establishment of cell-line-derived xenograft and PDX into humanized mouse models facilitate diverse experiments to explore cancer pathogenesis and therapeutic effects [28]. Mouse and human immune systems are fundamentally different [29]. However, humanized mouse models can be utilized to evaluate antitumor efficacy against human checkpoint molecules. Researchers use humanized mice as a more accurate model to study complex immune responses during immunotherapy [30]. New immunotherapeutic drugs underline the significance of humanized mouse models in reforming clinical practice.

Genetically engineered

Genetically engineered mouse models (GEMMs) are classified into two groups. Transgenic GEMMs are developed by inoculation of a zygote or embryonic stem cell in which an exogenous oncogene carries the construct of the gene of interest. Targeted GEMMs are achieved by incorporating homologous recombination into mouse embryonic stem cells [31]. With GEMMs, tumors develop in an environment of natural immunity, where the histopathological and molecular characteristics of the resulting tumor are very similar to those found in humans, and tumors can spontaneously metastasize. The benefit of GEMMs enable the study of the microenvironment and immunological components of the metastasis process, as well as mimicking the clinical state with the hallmarks of spontaneous metastatic development in immunocompetent hosts [32]. Because syngeneic cell lines can also be inoculated to GEMM, this model is a useful tool for the study of brain metastasis related to the immune system. This model forms brain metastasis more rapidly than the PDX model [3334].

Xenograft

PDX models of brain metastasis are established by transplanting fresh human cancer specimens or patient-derived cells cultured through early passage into immunodeficient or humanized mice. A deficiency of the immune system in the same species promotes a higher occurrence of tumor engraftment. The advantage of the PDX model is that it can better preserve the genomic, histopathological, and phenotypic heterogeneity of the original tissue. Therefore, this improves the screening of potential therapeutics and increases the value in assessing personalized medicine [3536].

IN VIVO MODELS OF BRAIN METASTASIS

To generate brain metastasis in vivo, these cells are inoculated into animals via several routes (Table 2). The route of inoculation is intravenous (IV) and the dissemination of tumor cells varies due to circulation. Inoculation of cells via the tail vein often results in metastasis that progress primarily in the lungs and central nervous system. Delivery via this route has high survival rates and is easy to implement [37]. To avoid pulmonary metastasis of cells, inoculation through the left ventricle, called intracardiac, allows systemic circulation of cells throughout the body. The intracardiac model has a high survival rate in skilled hands and the procedure is relatively simple.
To minimize the spread of cancer cells to locations outside the brain, intra-carotid inoculation is preferred. This model can be time intensive, requires microsurgical techniques for ligation of the required arteries, and has high intraoperative mortality (Fig. 1, video clip at https://www.youtube.com/watch?v=TfoyzYVwRiA). Both methods involve robust selective steps of efflux, but early steps in the metastasis process, for example, invasion and formation of metastatic niches, are ignored [38].
Cancer cells are usually administered directly into the brain using a stereotaxic device. A single, precisely located, and established lesion is produced by the stereotactic procedure [3940]. However, intracranial inoculation does not fully represent metastatic cascades.
An ideal model of brain metastasis would require cancer cells to go through all stages of brain metastasis in orthotopiccally injected tumor cells, such as a mammary fat pad for breast cancer or a subcutaneous for melanoma or GEMM. They can spontaneously develop brain metastasis following the genetic manipulation of oncogenes or tumor suppressors. Due to the low incidence of brain metastases in this model, the high experimental variability requires a larger population of mice.

METASTATIC BRAIN CANCER MODELS USING HUMAN CEREBRAL ORGANOIDS

One of the most human like model is the organoid. Recently, several protocols have been developed to generate cerebral organoids (COs) using human pluripotent stem cells (hPSCs) [414243]. CO is hPSC-derived organoids that self-assemble a form an organized architecture, composed of neural progenitors, neurons and glial cells. Unlike 2D cell cultures, CO recapitulates the human brain not only at the cellular level, but also in terms of general tissue structure [44]. Therefore, CO can overcome the limitations of metastatic mouse models [45]. A reproducible brain metastasis model is recently reported using human lung cancer cells and human embryonic stem cell (hESC)-derived CO [21]. Cancer cell proliferation, identification of specific gene functions, cell-cell interactions, and drug screening using metastatic brain cancer CO model were investigated. Such experiments are difficult to recapitulate in 2D cell cultures or animal models. The metastatic brain cancer CO model is an in vitro model for metastatic brain cancer and is located between 2D and animal models. However, it has an advantage to provide additional information over 2D or animal models. Although metastatic brain cancer CO models are promising, they have limitations such as the lack of important brain vasculature (e.g., BBB and BTB), immunological properties, the mature tissue, and the natural metastasis cascades when the real brain metastasis is considered. Disease modeling with new organoid techniques are also being developed through genetic and tissue engineering.
Even though 3D COs offer a complex model system that presents the opportunity to model various neurological diseases, there are still limitations. COs are different in size and shape, and the positions of the brain regions within each organoid also differ. Cells in brain organoids lack vascular systems as a result of the restricted culture techniques. The supply of gas and nutrients to COs mainly depends on simple diffusion from the medium, which causes a number of organoid cells to undergo apoptosis. In addition to the lack of a vascular system, stromal components, including microglia, are absent from current brain organoids, substantially limiting their application in the relevant research. Therefore, it is necessary to establish a circulatory system for long-term in vitro culture [46]. Recently, it is showen that on-chip hPSC-derived pericytes and endothelial cells sprout and self-assemble into organized vascular networks, and use COs to explore interactions with generated vasculature. Vascular cells physically interact with the CO and form an integrated neurovascular organoid on chip. The organoid vascularization approach opens several avenues for further studies in brain cancer and BBB [47].

CONCLUSION

Brain metastasis remains an unmet medical problem because treatment is inadequate, but the incidence continues to rise. Various brain metastasis models provide an opportunity to investigate how cancer cells interact with cells in the brain microenvironment at different stages of the metastasis cascade. With the appropriate laboratory resources available, researchers can initiate and advance relevant research to change the current clinical reality of brain metastasis.

Notes

Ethics Statement: Not applicable

Author Contributions:

  • Conceptualization: Seung Ho Yang.

  • Funding acquisition: Jung Eun Lee, Seung Ho Yang.

  • Writing—original draft: Jung Eun Lee, Seung Ho Yang.

  • Writing—review & editing: Seung Ho Yang.

Conflicts of Interest: The authors have no potential conflicts of interest to disclose.

Funding Statement: This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2022R1A2C1007556, 2021R1C1C2010469). The authors wish to acknowledge the financial support of the St.Vincent’s hospital, research institute of medical science (SVHR-2021-05).

Availability of Data and Material

The data generated or analyzed during the study are available from the corresponding author upon reasonable request.

References

1. Nathoo N, Chahlavi A, Barnett GH, Toms SA. Pathobiology of brain metastases. J Clin Pathol. 2005; 58:237–242. PMID: 15735152.
2. Nayak L, Lee EQ, Wen PY. Epidemiology of brain metastases. Curr Oncol Rep. 2012; 14:48–54. PMID: 22012633.
3. Barnholtz-Sloan JS, Yu C, Sloan AE, Vengoechea J, Wang M, Dignam JJ, et al. A nomogram for individualized estimation of survival among patients with brain metastasis. Neuro Oncol. 2012; 14:910–918. PMID: 22544733.
4. Palmieri D, Chambers AF, Felding-Habermann B, Huang S, Steeg PS. The biology of metastasis to a sanctuary site. Clin Cancer Res. 2007; 13:1656–1662. PMID: 17363518.
5. Steeg PS, Camphausen KA, Smith QR. Brain metastases as preventive and therapeutic targets. Nat Rev Cancer. 2011; 11:352–363. PMID: 21472002.
6. Chambers AF, Groom AC, MacDonald IC. Dissemination and growth of cancer cells in metastatic sites. Nat Rev Cancer. 2002; 2:563–572. PMID: 12154349.
7. Lambert AW, Pattabiraman DR, Weinberg RA. Emerging biological principles of metastasis. Cell. 2017; 168:670–691. PMID: 28187288.
8. Kienast Y, von Baumgarten L, Fuhrmann M, Klinkert WE, Goldbrunner R, Herms J, et al. Real-time imaging reveals the single steps of brain metastasis formation. Nat Med. 2010; 16:116–122. PMID: 20023634.
crossref
9. Quail DF, Joyce JA. The microenvironmental landscape of brain tumors. Cancer Cell. 2017; 31:326–341. PMID: 28292436.
crossref
10. Arvanitis CD, Ferraro GB, Jain RK. The blood-brain barrier and blood-tumour barrier in brain tumours and metastases. Nat Rev Cancer. 2020; 20:26–41. PMID: 31601988.
crossref
11. Valiente M, Ahluwalia MS, Boire A, Brastianos PK, Goldberg SB, Lee EQ, et al. The evolving landscape of brain metastasis. Trends Cancer. 2018; 4:176–196. PMID: 29506669.
crossref
12. Kramer N, Walzl A, Unger C, Rosner M, Krupitza G, Hengstschläger M, et al. In vitro cell migration and invasion assays. Mutat Res. 2013; 752:10–24. PMID: 22940039.
crossref
13. Huth J, Buchholz M, Kraus JM, Schmucker M, von Wichert G, Krndija D, et al. Significantly improved precision of cell migration analysis in time-lapse video microscopy through use of a fully automated tracking system. BMC Cell Biol. 2010; 11:24. PMID: 20377897.
crossref
14. Jain P, Worthylake RA, Alahari SK. Quantitative analysis of random migration of cells using time-lapse video microscopy. J Vis Exp. 2012; 63:e3585.
crossref
15. Infanger DW, Lynch ME, Fischbach C. Engineered culture models for studies of tumor-microenvironment interactions. Annu Rev Biomed Eng. 2013; 15:29–53. PMID: 23642249.
16. Kenney RM, Loeser A, Whitman NA, Lockett MR. Paper-based Transwell assays: an inexpensive alternative to study cellular invasion. Analyst. 2018; 144:206–211. PMID: 30328422.
17. Lee CH, Yu CC, Wang BY, Chang WW. Tumorsphere as an effective in vitro platform for screening anti-cancer stem cell drugs. Oncotarget. 2016; 7:1215–1226. PMID: 26527320.
crossref
18. Yelle N, Bakhshinyan D, Venugopal C, Singh SK. Introduction to brain tumor stem cells. Methods Mol Biol. 2019; 1869:1–9. PMID: 30324509.
19. Drost J, Clevers H. Organoids in cancer research. Nat Rev Cancer. 2018; 18:407–418. PMID: 29692415.
20. Duarte AA, Gogola E, Sachs N, Barazas M, Annunziato S, R de Ruiter J, et al. BRCA-deficient mouse mammary tumor organoids to study cancer-drug resistance. Nat Methods. 2018; 15:134–140. PMID: 29256493.
crossref
21. Choe MS, Kim JS, Yeo HC, Bae CM, Han HJ, Baek K, et al. A simple metastatic brain cancer model using human embryonic stem cell-derived cerebral organoids. FASEB J. 2020; 34:16464–16475. PMID: 33099835.
22. Kodack DP, Farago AF, Dastur A, Held MA, Dardaei L, Friboulet L, et al. Primary patient-derived cancer cells and their potential for personalized cancer patient care. Cell Rep. 2017; 21:3298–3309. PMID: 29241554.
23. Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011; 144:646–674. PMID: 21376230.
24. Day CP, Merlino G, Van Dyke T. Preclinical mouse cancer models: a maze of opportunities and challenges. Cell. 2015; 163:39–53. PMID: 26406370.
25. Cassidy JW, Caldas C, Bruna A. Maintaining tumor heterogeneity in patient-derived tumor xenografts. Cancer Res. 2015; 75:2963–2968. PMID: 26180079.
26. Daphu I, Sundstrøm T, Horn S, Huszthy PC, Niclou SP, Sakariassen PØ, et al. In vivo animal models for studying brain metastasis: value and limitations. Clin Exp Metastasis. 2013; 30:695–710. PMID: 23322381.
27. Zhong W, Myers JS, Wang F, Wang K, Lucas J, Rosfjord E, et al. Comparison of the molecular and cellular phenotypes of common mouse syngeneic models with human tumors. BMC Genomics. 2020; 21:2. PMID: 31898484.
28. Walsh NC, Kenney LL, Jangalwe S, Aryee KE, Greiner DL, Brehm MA, et al. Humanized mouse models of clinical disease. Annu Rev Pathol. 2017; 12:187–215. PMID: 27959627.
29. Tao L, Reese TA. Making mouse models that reflect human immune responses. Trends Immunol. 2017; 38:181–193. PMID: 28161189.
crossref
30. Nieblas-Bedolla E, Nayyar N, Singh M, Sullivan RJ, Brastianos PK. Emerging immunotherapies in the treatment of brain metastases. Oncologist. 2021; 26:231–241. PMID: 33103803.
31. Kersten K, de Visser KE, van Miltenburg MH, Jonkers J. Genetically engineered mouse models in oncology research and cancer medicine. EMBO Mol Med. 2017; 9:137–153. PMID: 28028012.
crossref
32. Gómez-Cuadrado L, Tracey N, Ma R, Qian B, Brunton VG. Mouse models of metastasis: progress and prospects. Dis Model Mech. 2017; 10:1061–1074. PMID: 28883015.
crossref
33. Taggart D, Andreou T, Scott KJ, Williams J, Rippaus N, Brownlie RJ, et al. Anti-PD-1/anti-CTLA-4 efficacy in melanoma brain metastases depends on extracranial disease and augmentation of CD8+ T cell trafficking. Proc Natl Acad Sci U S A. 2018; 115:E1540–E1549. PMID: 29386395.
34. Valiente M, Van Swearingen AED, Anders CK, Bairoch A, Boire A, Bos PD, et al. Brain metastasis cell lines panel: a public resource of organotropic cell lines. Cancer Res. 2020; 80:4314–4323. PMID: 32641416.
crossref
35. Siolas D, Hannon GJ. Patient-derived tumor xenografts: transforming clinical samples into mouse models. Cancer Res. 2013; 73:5315–5319. PMID: 23733750.
crossref
36. Xu C, Li X, Liu P, Li M, Luo F. Patient-derived xenograft mouse models: a high fidelity tool for individualized medicine. Oncol Lett. 2019; 17:3–10. PMID: 30655732.
37. Cranmer LD, Trevor KT, Bandlamuri S, Hersh EM. Rodent models of brain metastasis in melanoma. Melanoma Res. 2005; 15:325–356. PMID: 16179861.
crossref
38. Schwartz H, Blacher E, Amer M, Livneh N, Abramovitz L, Klein A, et al. Incipient melanoma brain metastases instigate astrogliosis and neuroinflammation. Cancer Res. 2016; 76:4359–4371. PMID: 27261506.
crossref
39. Sarmiento Soto M, Larkin JR, Martin C, Khrapitchev AA, Maczka M, Economopoulos V, et al. STAT3-mediated astrocyte reactivity associated with brain metastasis contributes to neurovascular dysfunction. Cancer Res. 2020; 80:5642–5655. PMID: 33106335.
crossref
40. Priego N, Zhu L, Monteiro C, Mulders M, Wasilewski D, Bindeman W, et al. STAT3 labels a subpopulation of reactive astrocytes required for brain metastasis. Nat Med. 2018; 24:1024–1035. PMID: 29892069.
crossref
41. Lancaster MA, Renner M, Martin CA, Wenzel D, Bicknell LS, Hurles ME, et al. Cerebral organoids model human brain development and microcephaly. Nature. 2013; 501:373–379. PMID: 23995685.
crossref
42. Li Y, Muffat J, Omer A, Bosch I, Lancaster MA, Sur M, et al. Induction of expansion and folding in human cerebral organoids. Cell Stem Cell. 2017; 20:385–396.e3. PMID: 28041895.
crossref
43. Sutcliffe M, Lancaster MA. A simple method of generating 3D brain organoids using standard laboratory equipment. Methods Mol Biol. 2019; 1576:1–12. PMID: 28361479.
crossref
44. Qian X, Song H, Ming GL. Brain organoids: advances, applications and challenges. Development. 2019; 146:dev166074. PMID: 30992274.
crossref
45. Lim JY, Lee JE, Park SA, Park SI, Yon JM, Park JA, et al. Protective effect of human-neural-crest-derived nasal turbinate stem cells against amyloid-β neurotoxicity through inhibition of osteopontin in a human cerebral organoid model of Alzheimer’s disease. Cells. 2022; 11:1029. PMID: 35326480.
crossref
46. Song G, Zhao M, Chen H, Zhou X, Lenahan C, Ou Y, et al. The application of brain organoid technology in stroke research: challenges and prospects. Front Cell Neurosci. 2021; 15:646921. PMID: 34234646.
crossref
47. Salmon I, Grebenyuk S, Abdel Fattah AR, Rustandi G, Pilkington T, Verfaillie C, et al. Engineering neurovascular organoids with 3D printed microfluidic chips. Lab Chip. 2022; 22:1615–1629. PMID: 35333271.
crossref
Fig. 1

Anterior neck dissection of the mice reveals the vagus nerve, common carotid artery, external carotid artery, and internal carotid artery.

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Table 1

In vivo models for metastasis research

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Model Characteristics Advantages Disadvantages
Syngeneic model Ingraft cancer cells that derive from the same species as the host animal Retains a fully competent immune system; effective for testing new immunotherapies Does not always reflect the effect of the human immune system
Humanized mouse model Ingraft human immune system tissue into immunodeficient mice Reflects a human-like immune environment in animals Higher mortality rates than wild-type mice
Grafting efficiency can vary
Genetically engineered mouse mode Knockdown/upregulation of selected genes in a mouse model Allows for the isolation and subsequent study of specific genes/oncogenic pathways Takes a long time to render
Xenograft Ingraft human tumor tissue into humanized or immunodeficient mice Reflects the tumor microenvironment of the original cancer sample Many tumor types will not successfully survive or metastasize after implantation
Table 2

In vivo models of brain metastasis

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Brain metastasis method Description Disadvantages
Intracardiac or tail vein injection Recapitulates the second half of the metastatic process
Serial brain metastasis selection can increase the success rate of brain metastasis
Bypasses the first half of the metastatic process
Animals may succumb to lung metastasis prior to brain metastasis formation
Intracarotid arterial injection Recapitulates the second half of the metastatic process
Reproducible, consistent, specific brain metastasis formation
Bypasses the first half of the metastatic process
Technically challenging
Stereotactic intracerebral injection Reproducible and consistent brain metastasis formation Ignores all stages of the metastasis cascade except secondary organ outgrowth
Bolus cancer cell injection to the brain parenchyma may not show the metastatic colonization of single or few cells
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