Skip to main content
Disease Models

Mouse Models of Glioblastoma

By June 28, 2021August 25th, 2021No Comments

What is Glioblastoma

Glioblastoma, also known as glioblastoma multiforme (GBM), is a high-grade (grade 4) glioma brain tumor. It’s considered an aggressive tumor, as it’s related to a group of tumors called astrocytomas, which are star-shaped cells that bolster nerve cells in the brain. This kind of tumor proliferates rapidly in the brain due to the fast cloning of cells and feeding on various blood vessels.

Nevertheless, its expansion is scarce to the other parts of the body.[1] Astrocytomas are divided into four types by the World Health Organization (WHO): Pilocytic astrocytoma, diffuse astrocytoma, anaplastic astrocytoma, and glioblastoma multiforme. Pilocytic and diffuse astrocytoma are both recognized by low expansion average.

In contrast, the anaplastic astrocytoma and glioblastoma multiforme are recognized by the frequent unrestricted growth, neurodegeneration, and spread tissue permeation.[2, 3, 4]

Furthermore, glioblastomas are divided into three subtypes by WHO, according to the IDH gene mutation case: glioblastoma-IDH-wild type, glioblastoma -IDH-mutant, and unclassified-glioblastoma-NOS.[5]

The IDH-wild type is the most prevalent in older patients, with 90% of cases mainly originating from genetic mutations. These genetic mutations are homozygous deletion of CDKN2A/ CDKN2B gene, loss of the short or long arm of chromosome 10, or other chromosomal rearrangements, and mutations in other genes such as P13K and PTEN. The IDH-mutant is prevalent in younger patients in 10% of cases and is characterized with minor glioma in most cases.[6]

The last one, glioblastoma-NOS, refers to the undetermined diagnosis test for the IDH estimation of this kind of tumor. Further genetic studies and molecular changes within tumor cells enhance the understanding of complex glioma cell biology. The analysis of the glioblastoma genome, epigenome, and transcriptome stimulated the identification of distinct subtypes with distinct molecular marks, thus providing a clear image of their molecular variations.[6]

Additionally, various subtypes can be found within a single tumor by studying single-cell RNA sequencing. Hence, it enhances the understanding of the glioblastoma inter-and intra- tumor heterogeneity.[7, 8]

The current paper investigates the different animal models of glioblastoma research and the possibilities of translating animal research into human studies. Preclinical mouse models give a promising research outcome to probably grasp the essence of the glioblastoma mechanisms and cellular process activities.[9]

Behavioral tests have also been used to study one of the major neurodegenerative symptoms resulting from both the anaplastic astrocytoma and glioblastoma multiforme, which is the memory or cognitive impairments. The Object Recognition (OR) and Morris Water Maze (MWM) tests have been utilized in studying the cognitive decline, short-term and long-term memory efficiency in mice.

OR test, in particular, is investigating the declarative memory deficits and examining the cognitive impairments in the immunodeficient (nude) mice.[9 10, 11] Additionally, the diagnosis, conventional and new treatments of glioblastoma, and possible future treatments through precision medicine will be discussed shortly in this article.

Diagnosis and Treatments of Glioblastoma

a) Diagnosis:

Most times, glioblastoma is diagnosed at its late stages due to the sedated spreading of brain tumors, which permits the structures to slowly adapt to the pressure and distortion produced by the tumor cluster. Therefore, even in the presence of the morphological clues of tumor breakthrough into brain tissue, the clinical aspects won’t be noticed.[12]

The central diagnostic tools for glioblastoma depend on neurological tests and neuroimaging methods implemented when the tumor is previously present at the front levels.[13, 14]

Microvascular hyperplasia and pseudopalisading necrosis are the critical features in the diagnosis of glioma as well. Both are beneficial tools in determining the spread of gliomas which describe the switch from a high-grade astrocytoma to glioblastoma.[15]

b) Treatments:

The traditional glioblastoma treatments are the surgical cutoff of the tumor cluster, followed by chemo-radiotherapy treatments. Despite the frequent use of the above-mentioned therapies, it was considered powerless, as it reflected a high setback and increased tumor resistance over a long period of orthodox treatments. This issue is going simultaneously with the patient’s neurological drop as well.[16]

Recently, new treatments were delivered to the glioblastoma patients, such as nitric oxide-releasing HIV protease inhibitors and anti-VEGF bevacizumab. Overall, it didn’t significantly enhance the patient’s survival rate over time.[17, 1819]

The future promising therapy is precision medicine to combat this kind of tumor. The concept of this therapy is the impact of presenting the appropriate treatment of the optimum amount of time for a certain patient.[20] This aim can be applied if a particular factor or all is available, including genetic composition, biomarkers, phenotypes, and the environmental conditions of each patient.[21]

The model organisms will enhance precision medicine through studying particular neurodegenerative diseases such as Alzheimer’s (AD), frontotemporal dementia (FTD), and cancer. Although the transgenic mice are the most exposing models to the AD genetic alterations, they lack the prolific genetic background, individual, and variability to know what path to cross to estimate the AD inheritance or underlying genetics.[22]

To increase the prolonged treatments over time, a preclinical model, the AD BXB model, is used to determine AD’s epigenetics and mimic the cognitive decline and behavioral properties of human patients.[23] The mouse strain of the latter model is the 5XFAD transgenic mouse strain, with a genetically diverse reference chart (the BXD genetic reference chart). This will lead to an F1 hybrid that carries out an original copy of the human big jeopardy AD genetic alterations.[23]

This new model will help identify the varied human genetic framework of known AD mutations and the memory deterioration phenotypes of human AD disorder. Furthermore, the AD-BXB displayed significant levels of genetic, transcriptomic, and phenotypic overlap with human AD, which will stimulate grasping certain points of how AD’s etiology works and how genetic and phenotypic diversity could contribute to AD formation and estimate the efficiency of patient’s response.

Frontotemporal dementia (FTD) is applied through precision medicine by determining the genetic risk factors, diagnostic biomarkers, and therapeutic targets detected in the early stages.[24] Tau pathology, the most important factor in forming the FTD, involves mutations in the microtubule-associated protein tau (MAPT) gene.[25] Tau protein’s primary role is ensuring normal cellular morphology and function by binding and stabilizing microtubules.

On the other hand, MAPT mutations cause tau to dissociate from microtubules and aggregate inside neurons and glial cells, causing axonal transport, synaptic defects, and observable cognitive defects, thus losing the stability of the microtubule. Therefore, precision medicine can reduce the tau protein accumulation inside cells and enhance the microtubule balance.

Furthermore, cancer is also an example of precision medicine’s application, as there are several applications to fight cancer, such as recombinant proteins, antibodies, checkpoint inhibitors, and vaccines. However, the most promising remedy against cancer in the future depends on the patient’s specific immune profile, which will boost the immunotherapy domain.

Preclinical Glioblastoma Paradigms

Preclinical glioblastoma models are xenograft, genetically engineered mouse models, and chemically induced models.[26]

1) Xenografts

Xenografts are classified into two categories: glioblastoma cell-line xenografts and patient-derived xenografts.

a) Glioblastoma cell-line xenograft:

Glioblastoma cell-line xenograft paradigm has a high disease expansion layout and reproducibility.[27] On the other hand, this model didn’t throw back the original clinical properties of the patient’s original tumor.[28] Hence, the xenograft glioblastoma cell-line is restricted and cannot be characterized by microvascular hyperplasia, pseudopalisading necrosis.[29, 30]

Moreover, the genotype of the cell-line model shows different initial characteristics of the primary glioblastoma tumor [26] as examined by the array-comparative genomic hybridization and whole-genome sequencing. This indicates different profiles from those found in the authentic tumor.[31, 32]

It can be concluded that the cell-line glioblastoma xenograft paradigm didn’t reflect the genuine biological nature, genomic and transcriptomic aberrations in situ of glioblastoma, hence considered a non-dependent preclinical model.[26, 32]

b) Patient-derived xenograft (PDX):

Patient-derived xenograft (PDX),[33, 34] unlike the xenograft cell-line, showed the same genetic and clinical parameters to the genuine glioblastoma features. As tumor cells proliferate through several mice offspring, PDX cells don’t get exhausted in cell-culture conditions.[35] Two methods through the PDX were used to gain the same genetic and clinical parameters to the original glioblastoma characteristics.

The first method was applied through injecting tumorspheres of glioblastoma into the immunodeficient mice, generated under serum-free neurosphere-culture conditions.[36] The second one is by injecting tissues from novel brain-tumor biopsies into the immunodeficient mice also.[37, 38] The biopsy tissue was put in flasks containing normal serum-supplemented tissue-culture medium.[39] When inoculated into the nude mice, both cultured tumorspheres and biopsy tissues mimic the genetic and phenotypic properties of the patient’s genuine neoplasm.[40, 41]

Nevertheless, the tumor biopsies process (second method) might provide better outcomes than tumorspheres (first method) in keeping the original tissue architecture, including the endothelium, extracellular matrix components, and macrophages.[40] There are several benefits of the PDX over the cell-line xenografts, which show similar molecular properties to the patient’s authentic tumor and thus sustain molecular outline over the passing time.[42, 43]

Therefore, it will return the mammalian primary glioblastoma’s tumorigenic, phenotypic characteristics, and other biological aspects. On the other hand, despite the correct injection of the tumorspheres or biopsy tissues into nude mice, collecting tumors will take between two and eleven months.[44]

Furthermore, the applied methods cannot be extracted from the early stages of glioblastoma patients.[44] PDX paradigm can give confirmed results, using the immunodeficient mice only, such as nude, NOD-SCID, or NOD-SCID-gamma mice. Thus, this model cannot be demonstrated with the host immune system.

2) Genetically Engineered Mouse Models (GEM):

Increasing the oncogenic biochemical pathways (p21–RAS, PI3K, EGFR, CDK4, MDM2) or the inhibition of the tumor suppressor gene role (p53) as a result of the irregular genetic variations (PTEN, TP53, CDKN2A, RB) within the cell cycle, will facilitate the formation of glioma tumors.[45]

The glial fibrillary acidic protein (GFAP) regulates the v-src kinase expression under the control of the GFAP gene regulatory element in astrocytes, which produces a transgenic animal model for early-stage astrocytoma or later astrocytoma stage.[46, 47, 48] The signaling mechanisms of the p21-RAS, wild-type EGFR, mutant EGFR  proteins,[49, 50] overexpression of CDK4, MDM2, and decreased expression of CDKN2A,[46] TP53, PTEN gene, are the most common deviant epigenetic variations to develop human malicious astrocytomas.

Hence, it enhances the production of a mouse expressing proteins under the regulation of the GFAP promoter.[48] Additionally, TP53 inactivation and stimulation of the p21-RAS pathway in the central nervous system will also have 100% penetration of the malignant astrocytoma as carriers of this phenotype.[49]

The Cre stimulated allele genes control gene expressions in many genetically engineered mouse models to switch the gene expression on or off during certain times and in certain cells. Moreover, the Cre recombinase genes could be delivered to the somatic host cell using the retroviral or adenoviral vectors, such as the RCAS/Tva system.[51]

The positive sides of the GEM paradigm are spotting the molecular genetic aberrations induced by the above-mentioned pathways (v-src kinase and Cre recombinase genes) concerning tumor initiation and development, as well as sending back the genuine biological and histological features of human glioblastoma.

However, gene alterations in the GEM paradigm cannot reflect the true linked cases in human glioblastoma. It contains homogenous genetic changes caused by specific mutations inside cells that would not cover the concise glioblastoma micro-environment.[52] Also, the tumor initiation cannot be regulated, as a clue that GEM considered insufficient models for therapeutic studies.

3) Chemically Induced Models:

Many mouse models such as GL261, GL26, and CT-2A are related to the chemically induced murine glioma. GL261 is the most widely used mouse model of glioblastoma and the P560.[53]

These models are reflecting the biological and histological properties of glioblastoma and implementing immunocompetent mice. Thus the chemical mouse paradigm is a suitable candidate for immunotherapeutic research and glioblastoma tumor immunology.[54]

Object Recognition & Morris Water Maze Behavioral Tests

a) Behavioral Changes:

The object recognition model (OR)  tests animal memory functioning by distinguishing unfamiliar and ordinary objects.[55] OR facilitates the action of the hippocampus (an essential part of the brain that is responsible for learning, memory, and mood).[56] Other studies illustrated that OR activates the peri-postrhinal cortex as well.[57] Regarding cognitive decay, OR evaluates a certain feature of declarative memory;  the ability to predict and act before happening.[58, 59]

The declarative part needs few learning attempts to gain the cognitive ability to distinguish between unfamiliar and ordinary objects through the OR model. In contrast, the non-declarative part needs further learning attempts for the experimental mice to adapt to the learning and memory tests.[59]  Moreover, the non-declarative part is similar to the hippocampus brain part, which requires many learning attempts to perform well in the learning and memory tests usually done by the Morris Water Maze (MWM).

A correlation study was found between the proliferation of the xenografts human glioblastoma in the immunodeficient mice and the cognitive impairments. In the nude mice, the Forkhead box N1 (Foxn1) transcription factor mutation was expressed in a thymic epithelial cell lineage responsible for thymopoiesis.[60] These mice models have been linked with studying the xenograft human glioblastoma in vivo due to the absence of mature T cells and the inability to form an immune reaction. The U87-MG tumors nude mice tolerances were spotted in much-delayed levels of brain tumor development, such as the imbalance of both sensory and motor functions, therefore few behavioral tests were used to study these kinds of immunodeficient mice.[61]

The OR model presents a suitable test to measure the memory decay of nude mice due to the ability to detect its early levels of tumor development.[62] For instance, the OR displays the cognitive impairments before clinical signs appear in nude mice, as explained by a particular study.

On the scale of five, animals were graded 0, and then at tumor progression of day 22. They showed the first clinical symptoms, thus suggesting a quick and efficient model for displaying memory dysfunction in the nude mice.[63, 64]

Additionally, injected glioblastoma mice cells were examined for OR. They practiced through two typical objects to gain decent learning. During the experiment, one target is switched with another one. Thus, the natural choice of mice is to discover the new object provided, which will be approached in a prolonged time.

Another behavioral test has been used to measure the cognitive defects of locative learning in SCID mice (BALB/cByJSmn-Prkdc-scid) as well as nude mice (BALB/c/OLA) through the Morris Water Maze (MWM) model.[65] Despite the MWM variant role in nude mice regarding the locative learning of memory impairments by integrating the adaptive immune reaction by restoring  T- cells, nude mice still do better tasks through the OR model.[65]

The MWM applied different learning methods for rats by exposing them under taxing conditions as swimming to reach a hidden platform, then assisting them to follow direct clues to enter a specified gate.[66] Hence, MWM requires rats to adapt to this environmental training by activating the hippocampus partly responsible for the practice and spatial learning mechanisms.

Other brain parts activated by the MWM are nucleus accumbens (movement directions), caudate nucleus (place–reward information), lateral mammillary and thalamic nuclei (head direction), posterior parietal cortex (local panoramic view system), subiculum, entorhinal cortex, and superior colliculus (orientation toward specific cues).[67]

b) Cognitive Impairments (Memory and Learning):

MWM needs extra learning and training memory function of rats to put them in a suitable environment for the desired study than the OR model, which examined a less tensional process for determining the memory decline.[68]

Some studies showed that tumor volume might affect the short-term and long-term memory in mice.[69] The development of tumors will decline the cognitive ability as estimated by differentiating between the novel and old objects, thus immediately could affect the short-term memory more than the long-term as it’s dependent on other factors.

Additionally, both memories are biochemically distinct and could be separately affected by the tumor volume. Long-term memory demands gene expression and protein production to determine the cognitive decline by tumor size.[70, 71] In contrast, short-term memory still needs further investigation into how tumor size can cause memory impairment.

Nevertheless, the cognitive impairment may be caused by other mechanisms such as permeation and incorporation of tumor cells into neuronal pressure or excretion of certain features.[52, 72] This process does not consider The U87MG tumor; hence it didn’t show cognitive decay through permeation and/or incorporation into the neuronal circuitry.[73]

The hippocampus part is involved in determining the above process through the presence of neuronal pressure.[55] Although the OR test hasn’t been applied effectively in defining the memory impairments through the hippocampus as with the MWM due to rats’ acquiring learning and practice skills, OR can define the cognitive impairments of the compression of hippocampus brain structure through certain factors.[74]

Soluble molecules such as neurotransmitters, cytokines, and growth factors are produced by tumor cells. Furthermore, an example of neurotransmitters, glutamate, is linked with excitotoxicity released in large quantities by neoplasm cells, enhancing neurodegeneration.[74] Additionally, a cytokine associated with the glioma permeation called monocyte chemoattractant protein-1 (MCP-1) is linked to adjust hippocampal role and learning.[75, 76]

Conclusion:

Glioblastoma diagnosis was utilized in different ways, such as neurological tests, neuroimaging methods, microvascular hyperplasia, and pseudopalisading necrosis. The traditional therapies for this brain tumor, such as surgical resection and chemo-radiotherapy, were not showing a promising outcome for glioblastoma patients over time.

However, precision medicine is essential for finding a robust treatment against different neurodegenerative disorders such as Alzheimer’s (AD), frontotemporal dementia (FTD), and cancer.

On the other hand, the Preclinical glioblastoma mouse models were applied to study and analyze the glioblastoma features and the genetic biochemical role of glioblastoma in human brain tissues. Object Recognition (OR) behavioral protocol is considered an easy and straightforward test for nude mice to measure cognitive impairments (learning and memory), tumor progression, and behavioral change.

The Morris Water Maze (MWM) has also been used to identify the hippocampus brain’s cognitive decay in rats, as needing further learning and training skills.

References:

  1. Salcman M. (1990). Malignant glioma management. Neurosurg. Clin. N. Am. 1:49–63. doi: 10.1016/S1042-3680(18)30823-4.
  2. Cao H., Wang F., Li X.J. Future strategies on glioma research: From big data to the clinic. (2017) Genom. Proteom. Bioinform. 15,263–265. doi: 10.1016/j.gpb.2017.07.001.
  3. Kalinina JPeng JRitchie J.CVan Meir E.G. (2011). Proteomics of gliomas: Initial biomarker discovery and evolution of technology. Neuro Oncol. 13,926–942. doi: 10.1093/neuonc/nor078.
  4. Sontheimer H. (2008). A role for glutamate in growth and invasion of primary brain tumors. J. Neurochem. 105,287–295. doi: 10.1111/j.1471-4159.2008.05301.x.
  5. Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella- Branger D, Cavenee WK, Ohgaki H, Wiestler OD, Kleihues P, Ellison DW. (2016). The 2016 World Health Organization classification of tumors of the central nervous system: a summary. Acta Neuropathol 131(6),803–820. doi:10.1007/s00401-016-1545-1.
  6. Brennan CW, et al. (2013). The somatic genomic landscape of glioblastoma. Cell. 155,462–477.
  7. Sottoriva A, et al. (2013). Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics. Proc Natl Acad Sci USA110, 4009–4014.
  8. Patel AP, et al. (2014). Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science. 344,1396–1401.
  9. Ennaceur A, Delacour J. (1988). A new one-trial test for neurobiological studies of memory in rats. 1: behavioral data. Behav Brain Res. 31,47–59.
  10. Rossato JI, Bevilaqua LR, Myskiw JC, Medina JH, Izquierdo I, Cammarota M. (2007). On the role of hippocampal protein synthesis in the consolidation and reconsolidation of object recognition memory. Learn Mem,14,36–46.
  11. Prado VF, Martins-Silva C, de Castro BM, Lima RF, Barros DM, Amaral E, et al. (2006). Mice deficient for the vesicular acetylcholine transporter are myasthenic and have deficits in object and social recognition. Neuron,51,601–12.
  12. Sizoo E.M., Braam L., Postma T.J., Pasman H.R., Heimans J.J., Klein M., Reijneveld JC Taphoorn M.J. (2010). Symptoms and problems in the end-of-life phase of high-grade glioma patients. Neuro Oncol.,12,1162–1166. doi: 10.1093/neuonc/nop045.
  13. Posti J.P., Bori M., Kauko T., Sankinen M., Nordberg J., Rahi M., Frantzén J., Vuorinen V., Sipilä J.O.(2015). Presenting symptoms of glioma in adults. Acta Neurol. Scand.131, 88–93. doi: 10.1111/ane.12285.
  14. Mondal A., Kumari Singh D., Panda S., Shiras A. Extracellular Vesicles as Modulators of Tumor Microenvironment and Disease Progression in Glioma. (2017). Front. Oncol. 7,144. doi: 10.3389/fonc.2017.00144.
  15. Brat DJ, Van Meir EG. Vaso-occlusive and prothrombotic mechanisms associated with tumor hypoxia, necrosis, and accelerated growth in glioblastoma. (2004) Lab Invest.84,397–405.
  16. Ozdemir-Kaynak E., Qutub A.A., Yesil-Celiktas O. (2018). Advances in glioblastoma multiforme treatment: New models for nanoparticle therapy. Front. Physiol. 9,170. doi: 10.3389/fphys.2018.00170.
  17. Basile M.S., Mazzon E., Krajnovic T., Draca D., Cavalli E., Al-Abed Y., Bramanti P., Nicoletti F., Mijatovic S., Maksimovic-Ivanic D. (2018). Anticancer and differentiation properties of the nitric oxide derivative of lopinavir in human glioblastoma cells. Molecules. 23,2463. doi: 10.3390/molecules23102463.
  18. Lazarević M., Mazzon E., Momčilović M., Basile M.S., Colletti G., Petralia M.C., Bramanti P., Nicoletti F., Miljković Đ. (2018). The H2S donor GYY4137 stimulates reactive oxygen species generation in BV2 cells while suppressing the secretion of TNF and nitric oxide. Molecules.23,2966. doi: 10.3390/molecules23112966.
  19. Gilbert M.R., Dignam J.J., Armstrong T.S., Wefel J.S., Blumenthal D.T., Vogelbaum M.A., Colman H., Chakravarti A., Pugh S., Won M., et al. (2014). A randomized trial of bevacizumab for newly diagnosed glioblastoma. N. Engl. J. Med. 370,699–708. doi: 10.1056/NEJMoa1308573.
  20. Tibbetts, J. (2018). Precision medicine brings mouse models closer to human patients. BioScience, 68, 828
  21. Jones, D. S. (2013). How personalized medicine became genetic, and racial: Werner Kalow and the formations of pharmacogenetics. Journal of the History of Medicine and Allied Sciences, 68(1), 1–48.
  22. Gatz, Margret, Pedersen, Nancy, Berg, Stig, Johansson, Boo, Johansson, K, Mortimer, J A,  Ahlbom, A. (1997). Heritability for Alzheimer’s disease: The study of dementia in Swedish twins Biological Sciences And Medical Sciences, 52(2), M117–125. https://doi.org/10.1093/gerona/52A.2.M117.
  23. Neuner, S. M., Heuer, S. E., Huentelman, M. J., O’connell, K. M., …, & Kaczorowski, C. C. (2019). Harnessing genetic complexity to enhance translatability of Alzheimer’s disease mouse models: A Path toward Precision Medicine. Neuron, 101(3), 399–411.e5. https://doi.org/10.1016/j.neuron.2018.11.040 (2019).
  24. Liu, M. N., Lau, C. I. & Lin, C. P. (2019). Precision medicine for frontotemporal dementia. Front Psychiatry, 10, 75, doi:10.3389/fpsyt.2019.00075.
  25. Fanny M. Elahi, & Bruce L. Miller. (2017). A clinicopathological approach to the diagnosis of dementia. Nature Reviews Neurology, 13(8), 457–476. https://doi.org/10.1038/nrneurol.2017.96.
  26. Huszthy PC, Daphu I, Niclou SP, Stieber D, Nigro JM, Sakariassen PØ, et al. (2012). In vivo models of primary brain tumors: Pitfalls and perspectives. Neuro Oncol. 14(8):979–93.
  27. Martens T, Laabs Y, Günther HS, Kemming D, Zhu Z, Witte L, et al. (2008). Inhibition of glioblastoma growth in a highly invasive nude mouse model can be achieved by targeting epidermal growth factor receptors but not vascular endothelial growth factor receptor-2. Clin Cancer Res. 14(17):5447–58.
  28. Mahesparan R, Read TA, Lund-Johansen M, Skaftnesmo KO, Bjerkvig R, Engebraaten O.(2003). Expression of extracellular matrix components in a highly infiltrative in vivo glioma model. Acta Neuropathol.,105(1),49–57.
  29. Kijima N, Hosen N, Kagawa N, Hashimoto N, Kinoshita M, Oji Y, et al. (2014). Wilms’ tumor 1 is involved in the tumorigenicity of glioblastoma by regulating cell proliferation and apoptosis. Anticancer Res.,34(1),61–7.
  30. Ernst A, Hofmann S, Ahmadi R, Becker N, Korshunov A, Engel F, et al. (2009). Genomic and expression profiling of glioblastoma stem cell-like spheroid cultures identifies novel tumor-relevant genes associated with survival. Clin Cancer Res.,15(21),6541–50.
  31. Clark MJ, Homer N, O’Connor BD, Chen Z, Eskin A, Lee H, et al. (2010). U87MG decoded: The genomic sequence of a cytogenetically aberrant human cancer cell line. PLoS Genet,6(1):e1000832.
  32. Li A, Walling J, Kotliarov Y, Center A, Steed ME, Ahn SJ, et al. Genomic changes and gene expression profiles reveal that established glioma cell lines are poorly representative of primary human gliomas. Mol Cancer Res. 2008;6(1):21–30.
  33. Jin K, Teng L, Shen Y, He K, Xu Z, Li G. Patient-derived human tumour tissue xenografts in immunodeficient mice: A systematic review. Clin Transl Oncol. 2010;12(7):473–80.
  34. Hidalgo M, Amant F, Biankin AV, Budinská E, Byrne AT, Caldas C, et al. (2014). Patient-derived xenograft models: An emerging platform for translational cancer research. Cancer Discov.,4(9),998–1013.
  35. Daniel VC, Marchionni L, Hierman JS, Rhodes JT, Devereux WL, Rudin CM, et al. (2009). A primary xenograft model of small-cell lung cancer reveals irreversible changes in gene expression imposed by culture in vitro. Cancer Res. ,69(8),3364–73.
  36. Kang SG, Cheong JH, Huh YM, Kim EH, Kim SH, Chang JH. (2015). Potential use of glioblastoma tumorsphere: Clinical credentialing. Arch Pharm Res. ,38(3),402–7.
  37. Fei XF, Zhang QB, Dong J, Diao Y, Wang ZM, Li RJ, et al. (2010). Development of clinically relevant orthotopic xenograft mouse model of metastatic lung cancer and glioblastoma through surgical tumor tissues injection with trocar. J Exp Clin Cancer Res.29(1),84.
  38. Kim KM, Shim JK, Chang JH, Lee JH, Kim SH, Choi J, et al. (2016). Failure of a patient-derived xenograft for brain tumor model prepared by implantation of tissue fragments. Cancer Cell Int,16,43.
  39. Bjerkvig R, Tønnesen A, Laerum OD, Backlund EO. (1990). Multicellular tumor spheroids from human gliomas maintained in organ culture. J Neurosurg.72(3),463–75.
  40. Lee J, Kotliarova S, Kotliarov Y, Li A, Su Q, Donin NM, et al.(2006). Tumor stem cells derived from glioblastomas cultured in bFGF and EGF more closely mirror the phenotype and genotype of primary tumors than do serum-cultured cell lines. Cancer Cell.9(5),391–403.
  41. Chen R, Nishimura MC, Bumbaca SM, Kharbanda S, Forrest WF, Kasman IM, et al. (2010). A hierarchy of self-renewing tumor-initiating cell types in glioblastoma. Cancer Cell. 17(4),362–75.
  42. Günther HS, Schmidt NO, Phillips HS, Kemming D, Kharbanda S, Soriano R, et al. (2008). Glioblastoma-derived stem cell-enriched cultures form distinct subgroups according to molecular and phenotypic criteria. Oncogene. 27(20),2897–909.
  43. Wakimoto H, Mohapatra G, Kanai R, Curry WT Jr, Yip S, Nitta M, et al.(2012). Maintenance of primary tumor phenotype and genotype in glioblastoma stem cells. Neuro Oncol. 14(2),132–44.
  44. Wang J, Miletic H, Sakariassen PØ, Huszthy PC, Jacobsen H, Brekkå N, et al. (2009). A reproducible brain tumour model established from human glioblastoma biopsies. BMC Cancer, 9,465.
  45. Holland EC. (2001). Gliomagenesis: genetic alterations and mouse models. Nat Rev Genet, 2(2),120–129. doi:10.1038/35052535.
  46. Furnari FB, Fenton T, Bachoo RM, Mukasa A, Stommel JM, Stegh A, Hahn WC, Ligon KL, Louis DN, Brennan C, Chin L, DePinho RA, Cavenee WK. (2007). Malignant astrocytic glioma: genetics, biology, and paths to treatment. Genes Dev, 21(21),2683– 2710.  doi:10.1101/gad.1596707.
  47. Parsons DW, Jones S, Zhang X, Lin JC, Leary RJ, Angenendt P, Mankoo P, Carter H, Siu IM, Gallia GL, OliviA, McLendon R, Rasheed BA, Keir S, Nikolskaya T, Nikolsky Y, Busam DA, Tekleab H, Diaz LA Jr, Hartigan J, Smith DR, Strausberg RL, Marie SK, Shinjo SM, Yan H, Riggins GJ, Bigner DD, Karchin R, Papadopoulos N, Parmigiani G, Vogelstein B, Velculescu VE, Kinzler KW. (2008). An integrated genomic analysis of human glioblastoma multiforme. Science 321,(5897),1807–1812. doi:10.1126/science.1164382.
  48. Weissenberger J, Steinbach JP, Malin G, Spada S, Rulicke T, Aguzzi A. (1997).Development and malignant progression of astrocytomas in GFAP-v-src transgenic mice. Oncogene, 14(17):2005–2013. doi:10.1038/sj.onc.1201168.
  49. Ding H, Roncari L, Shannon P, Wu X, Lau N, Karaskova J, Gutmann DH, Squire JA, Nagy A, Guha A. (2001). Astrocyte-specific expression of activated p21-ras results in malignant astrocytoma formation in a transgenic mouse model of human gliomas. Cancer Res, 61(9),3826–3836.
  50. Ding H, Shannon P, Lau N, Wu X, Roncari L, Baldwin RL, Takebayashi H, Nagy A, Gutmann DH, Guha A. (2003.) Oligodendrogliomas result from the expression of an activated mutant epidermal growth factor receptor in a RAS transgenic mouse astrocytoma model. Cancer Res, 63(5),1106–1113.
  51. Federspiel MJ, Bates P, Young JA, Varmus HE, Hughes SH. (1994). A system for tissue-specific gene targeting: Transgenic mice susceptible to subgroup A avian leukosis virus-based retroviral vectors. Proc Natl Acad Sci USA.,91(23),11241–5.
  52. Charles N, Holland EC.(2010).The perivascular niche microenvironment in brain tumor progression. Cell Cycle.,9(15),3012–3021.
  53. Oh T, Fakurnejad S, Sayegh ET, Clark AJ, Ivan ME, Sun MZ, et al.(2014). Immunocompetent murine models for the study of glioblastoma immunotherapy. J Transl Med.,29(12),107.
  54. Ni HT, Spellman SR, Jean WC, Hall WA, Low WC. (2001). Immunization with dendritic cells pulsed with tumor extract increases survival of mice bearing intracranial gliomas. J Neurooncol 51(1),1–9.
  55. Squire LR,Wixted JT, Clark RE. (2007). Recognition memory and the medial temporal lobe: a new perspective. Nat Rev Neurosci, 8,872–83.
  56. Rossato JI, Bevilaqua LR, Myskiw JC, Medina JH, Izquierdo I, Cammarota M. (2007). On the role of hippocampal protein synthesis in the consolidation and reconsolidation of object recognition memory. Learn Mem, 2007,;14,36–46.
  57. Winters BD, Forwood SE, Cowell RA, Saksida LM, Bussey TJ. (2004). Double dissociation between the effects of peri-postrhinal cortex and hippocampal lesions on tests of object recognition and spatial memory: heterogeneity of function within the temporal lobe. J Neurosci,24,5901–8.
  58. Squire LR, Wixted JT, Clark RE. (2007). Recognition Memory and the medial temporal lobe: a new perspective. Nat Rev Neurosci,8,872–83.
  59. Winters BD, Saksida LM, Bussey TJ. (2008). Object recognition memory: neurobiological mechanisms of encoding, consolidation, and retrieval. Neurosci Biobehav Rev,321055–70.
  60. Yonelinas AP. (2001). Consciousness, control, and confidence: the 3 Cs of recognition memory. J Exp Psychol Gen,130:,61–79.
  61. Corbeaux T, Hess I, Swann JB, Kanzler B, Haas-Assenbaum A, Boehm T. (2010).Thymopoiesis in mice depends on a Foxn1-positive thymic epithelial cell lineage. Proc Natl Acad Sci USA, 107,16613–8.
  62. Yang H, Chopp M, Zhang X, Jiang F, Zhang Z, Kalkanis S, et al. (2007). Using behavioral measurement to assess tumor progression and functional outcome after antiangiogenic treatment in mouse glioma models. Behav Brain Res,182,42–50.
  63. Kipnis J, Cohen H, Cardon M, Ziv Y, Schwartz M. (2004).T cell deficiency leads to cognitive dysfunction: implications for therapeutic vaccination for schizophrenia and other psychiatric conditions. Proc Natl Acad Sci USA,101,8180–5.
  64. Weissert R,Wallstrom E, Storch MK, Stefferl A, Lorentzen J, Lassmann H, et al.(1998). MHC haplotype-dependent regulation of MOG-induced EAE in rats. J Clin Invest, 102,1265–73.
  65. Simonini MV, Polak PE, Sharp A, McGuire S, Galea E, Feinstein DL. (2010). Increasing CNS noradrenaline reduces EAE severity. J Neuroimmune Pharmacol, 5,252–9.
  66. Morris, R., (1984). Developments of a water-maze procedure for studying spatial learning in the rat. J Neurosci Methods, 11(1): p. 47-60.
  67. Garthe A, Kempermann G. (2013). An old test for new neurons: refining the Morris water maze to study the functional relevance of adult hippocampal neurogenesis. Front Neurosci,7,63.
  68. Dere E, Huston JP, De Souza Silva MA. (2005). Episodic-like memory in mice: simultaneous assessment of object, place and temporal order memory. Brain Res Brain Res Protoc,16,10–9.
  69. Taphoorn, Klein M. (2004). Cognitive deficits in adult patients with brain tumours. Lancet Neurol,3,159–68.
  70. Izquierdo LA, Barros DM, Vianna MR, Coitinho A, deDavid e Silva, Choi H, et al. (2002). Molecular pharmacological dissection of short- and long-term memory. Cell Mol Neurobiol,22,269–87.
  71. Bevilaqua LR, Kerr DS, Medina JH, Izquierdo I, Cammarota M. (2003). Inhibition of hippocampal Jun N-terminal kinase enhances short-term memory but blocks long-term memory formation and retrieval of an inhibitory avoidance task. Eur J Neurosci,17,897–902.
  72. Anderson SW, Damasio H, Tranel D. (1990). Neuropsychological impairments associated with lesions caused by tumor or stroke. Arch Neurol.47,397–405.
  73. Jacobs VL, Valdes PA, Hickey WF, De Leo JA. (2011). Current review of in vivo GBM rodent models: emphasis on the CNS-1 tumour model. ASN Neuro,3:e00063.
  74. Lee SG, Kim K, Kegelman TP, Dash R, Das SK, Choi JK, et al. (2011). Oncogene AEG-1 promotes glioma-induced neurodegeneration by increasing glutamate excitotoxicity. Cancer Res ,71,6514–23.
  75. Zhu X, Fujita M, Snyder LA, Okada H. (2011). Systemic delivery of neutralizing antibody targeting CCL2 for glioma therapy. J Neurooncol,104,83–92.
  76. Nelson TE, Hao C, Manos J, Ransohoff RM, Gruol DL. (2011). Altered hippocampal synaptic transmission in transgenic mice with astrocyte-targeted enhanced CCL2 expression. Brain Behav Immun,25(Suppl. 1),S106–19.
Author Details
MazeEngineers makes behavioral mazes for all species with high precision and accuracy. Each maze is hand made for exacting specifications, with automation, AI integration and open software integration. We’re here to build the world’s best behavioral library, we’d love to help you with your experiments. Send us questions and we’ll answer!
×
MazeEngineers makes behavioral mazes for all species with high precision and accuracy. Each maze is hand made for exacting specifications, with automation, AI integration and open software integration. We’re here to build the world’s best behavioral library, we’d love to help you with your experiments. Send us questions and we’ll answer!
Close Menu