Glioblastoma multiforme (GBM) is the deadliest form of primary brain tumor. GBM tumors are highly heterogeneous, being composed of tumor cells as well as glioblastoma stem cells (GSCs) that contribute to drug resistance and tumor recurrence following treatment. To develop therapeutic strategies, an improved understanding of GSC behavior in their microenvironment is critical. Herein, we have employed three‐dimensional (3D) hyaluronic acid (HA) hydrogels that allow the incorporation of brain microenvironmental cues to investigate GSC behavior. U87 cell line and patient‐derived D456 cells were cultured as suspension cultures (serum‐free) and adherently (in the presence of serum) and were then encapsulated in HA hydrogels. We observed that all the seeded single cells expanded and formed spheres, and the size of the spheres increased with time. Increasing the initial cell seeding density of cells influenced the sphere size distribution. Interestingly, clonal expansion of serum‐free grown tumor cells in HA hydrogels was observed. Also, stemness marker expression of serum and/or serum‐free grown cells was altered when cultured in HA hydrogels. Finally, we demonstrated that HA hydrogels can support long‐term GSC culture (up to 60 days) with retention of stemness markers. Overall, such biomimetic culture systems could further our understanding of the microenvironmental regulation of GSC phenotypes.
Glioblastoma multiforme (GBM) is the most lethal primary brain tumor characterized by high cellular and molecular heterogeneity, hypervascularization, and innate drug resistance. Cellular components and extracellular matrix (ECM) are the two primary sources of heterogeneity in GBM. Here, biomimetic tri‐regional GBM models with tumor regions, acellular ECM regions, and an endothelial region with regional stiffnesses patterned corresponding to the GBM stroma, pathological or normal brain parenchyma, and brain capillaries, are developed. Patient‐derived GBM cells, human endothelial cells, and hyaluronic acid derivatives are used to generate a species‐matched and biochemically relevant microenvironment. This in vitro study demonstrates that biophysical cues are involved in various tumor cell behaviors and angiogenic potentials and promote different molecular subtypes of GBM. The stiff models are enriched in the mesenchymal subtype, exhibit diffuse invasion of tumor cells, and induce protruding angiogenesis and higher drug resistance to temozolomide. Meanwhile, the soft models demonstrate enrichment in the classical subtype and support expansive cell growth. The three‐dimensional bioprinting technology utilized in this study enables rapid, flexible, and reproducible patient‐specific GBM modeling with biophysical heterogeneity that can be employed by future studies as a tunable system to interrogate GBM disease mechanisms and screen drug compounds.
more » « less- Award ID(s):
- 1937653
- NSF-PAR ID:
- 10444403
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Small
- Volume:
- 17
- Issue:
- 15
- ISSN:
- 1613-6810
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Background Glioblastoma Multiforme, an aggressive primary brain tumor, has a poor prognosis and no effective standard of care treatments. Most patients undergoing radiotherapy, along with Temozolomide chemotherapy, develop resistance to the drug, and recurrence of the tumor is a common issue after the treatment. We propose to model the pathways active in Glioblastoma using Boolean network techniques. The network captures the genetic interactions and possible mutations that are involved in the development of the brain tumor. The model is used to predict the theoretical efficacies of drugs for the treatment of cancer.
Results We use the Boolean network to rank the critical intervention points in the pathway to predict an effective therapeutic strategy for Glioblastoma. Drug repurposing helps to identify non-cancer drugs that could be effective in cancer treatment. We predict the effectiveness of drug combinations of anti-cancer and non-cancer drugs for Glioblastoma.
Conclusions Given the genetic profile of a GBM tumor, the Boolean model can predict the most effective targets for treatment. We also identified two-drug combinations that could be more effective in killing GBM cells than conventional chemotherapeutic agents. The non-cancer drug Aspirin could potentially increase the cytotoxicity of TMZ in GBM patients.
