WO2023049884A2

WO2023049884A2 - Multivariate biomimetic biomaterial arrays for precision medicine and screening applications

Info

Publication number: WO2023049884A2
Application number: PCT/US2022/076997
Authority: WO
Inventors: Stephanie SEIDLITS; Jesse Liang; Alireza SOHRABI
Original assignee: The Regents Of The University Of California
Priority date: 2021-09-27
Filing date: 2022-09-26
Publication date: 2023-03-30
Also published as: WO2023049884A3

Abstract

The present disclosure provides methods for identifying effective chemotherapeutic agents against cancer by exposing cancer cells to potential chemotherapeutic agents in a tumor-optimized hydrogel matrix that mimics the in vivo tumor environment, such that the potential effectiveness in vivo is optimized. Methods for identifying such conditions by tuning the biomechanical properties of the tumor growth matrix are provided.

Description

MULTIVARIATE BIOMIMETIC BIOMATERIAL ARRAYS FOR PRECISION MEDICINE AND SCREENING APPLICATIONS

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Patent Application No. 63/248,685, filed September 27, 2021, which is incorporated herein by reference in its entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH

[0002] This invention was made with government support under Grant Number HG002536, awarded by the National Institutes of Health. The government has certain rights in the invention.

FIELD OF THE INVENTION

[0003] The present disclosure relates in general to the field of patient-specific drug screening. In one embodiment, the present disclosure provides multivariate biomimetic polymer scaffold compositions for drug screening applications.

BACKGROUND OF THE INVENTION

[0004] A major barrier to the translation of therapies to clinical practice is the lack of efficacy of therapeutics in later stages of clinical trials. A scarcity of models which can adequately capture the complexity and uniqueness of human physiology in disease explains a major portion of this gap. To address the need of patient-specific drug screening, also known as personalized medicine, presently a variety of techniques are employed by practitioners for the purposes of drug screening and precision medicine. Most commonly in the drug screening space is the usage of human cell lines, typically cultured in 2D monolayers in plastic well plates, but more advanced 3D models are gaining traction. The 3D nature of these cultures may more accurately capture in vivo biology and serve as better models/predictors of human physiology. Methods to generate these cultures include forming cellular aggregates (spheroids) or seeding cells in biomaterials comprised of natural and/or synthetic polymers.

[0005] Early efforts to identify optimal material compositions for specific uses are dependent on the cellular phenotype desired. The lack of successful translated therapies suggests that there is significant room for optimization of these conditions. Recent advances in cell biology have revealed that the physical microenvironment plays a greater role in regulating cellular behavior than previously appreciated. These findings position the diversity of biomolecules, sugars, lipids, proteins found in cellular microenvironments as potential players in novel therapies and must be investigated to harness their potential for next generation therapeutics. Beyond the complexity of the biochemical agents, physical parameters like stiffness, pore size and degradability must also be considered when evaluating biomaterials for screening purposes. Incorporating these parameters is not straightforward as the increase in model complexity concomitantly increases the number of conditions to be screened in a factorial manner which can quickly become prohibitive to screening from a cost and manpower metric. Methods to screen and investigate this large parameter space are therefore of interest to pharmaceutical companies for drug development and medical centers for personalized medicine screening.

[0006] Thus, there is a need to develop improved patient-specific drug screening methodology capable of adequately capture the complexity and uniqueness of human physiology.

SUMMARY OF THE INVENTION

[0007] In one embodiment, the system presented herein utilizes specific bioconjugation chemistries that are compatible with live human cells and enable orthogonal tuning of several scaffold parameters (e.g. polymer content, stiffness, bioactive ligands), thereby generating multivariate biomimetic biomaterial arrays for screening purposes. For example, identifying the optimal scaffold properties for a particular tumor’s growth and invasiveness ex vivo affords the opportunity to identify chemotherapeutic and other treatments for that particular tumor that will likely be effective in vivo. In one example of reduction to practice, hyaluronic acid, an FDA-approved natural polymer, is modified with a thiol moiety and crosslinked with a multiarmed, norbornene-modified polyethylene glycol (e.g. PEG via a photo-initiated, radical-based thiol-ene chemistry). The radical generation is accomplished by exposing lithium phenyl-2,4,6- trimethylbenzoylphosphinate (LAP) to UV radiation (365 nm). Biomimetic peptides (e.g. integrin-binding, e.g. RGD containing) can be incorporated via a thiol moiety in a similar fashion. Optionally, thiolated polyethylene glycol is included to modulate hydrogel stiffness. The amount of thiolated PEG added to the mixture can be used to control the biomaterial properties independently of the amount of bioactive polymers or ligands added. By varying the ratio of these components, one can construct a combinatorial library of hydrogels with varying biomechanical features, including content of biomolecules and bioactive peptides and physical stiffness. Cells of varying origin (human, animal), number (encapsulation density), and mixtures (co-cultures) can be cultured in 3D within these hydrogels. [0008] In one embodiment of the platform technology, the ungelled solutions can be dispensed with automated liquid handlers into multi well plates (e.g. 96, 384-well plate) and crosslinked to form an array of cell laden multivariate gels. Following encapsulation, cell culture and screening for a variety of phenotypes can take place. For example, viability dyes can be added to the media to quantify the number of live cells following drug challenge, siRNA screen or other novel phenotypic screens. This invention thus enables precise interrogation of biomaterials on cellular activities.

[0009] In one aspect, a method is provided for selecting one or more chemotherapeutic agents for treating a tumor in a patient, comprising the steps of: a. obtaining a tumor biopsy from the patient and isolating tumor cells therefrom; b. preparing a plurality of samples comprising isolated tumor cells, each sample comprising a matrix comprising: i. a high molecular weight hyaluronic acid at a concentration of about 0.25 wt% to about 2 wt%, wherein about 4% to about 10% of glucuronic acid moieties on the hyaluronic acid are thiolated; ii. a thiolated polyethylene glycol; and ii. a polymer comprising an integrin binding moiety; wherein the thiolated hyaluronic acid, the thiolated polyethylene glycol and the polymer comprising the integrin binding moiety are cross-linked; c. exposing tumor cells in the plurality of samples to a plurality of first chemotherapeutic agents, each chemotherapeutic agent individually or in combination; and d. identifying among the samples one or more individual or combination of said first chemotherapeutic agents having maximal effect on suppressing growth or invasiveness of the tumor cells, thereby selecting one or more chemotherapeutic agents for treating a tumor in the patient.

[0010] In some embodiments, the polymer comprising an integrin binding moiety comprises a norbornene-terminated polyethylene glycol, a maleimide-terminated polyethylene glycol or a vinyl sulfone terminated polyethylene glycol.

[0011] In some embodiments, the matrix does not comprise thiolated polyethylene glycol.

[0012] In some embodiments, the thiolated hyaluronic acid, the thiolated polyethylene glycol and the polymer comprising an integrin binding moiety are cross-linked by: a. further including maleimide polyethylene glycol or vinyl sulfone polyethylene glycol, wherein the cross-linking occurs by Michael-type addition; b. further including vinyl sulfone polyethylene glycol and a radical generator; or c. further including a norbomene-terminated polyethylene glycol and a radical generator.

[0013] In some embodiments, the radical generator is a photo-crosslinker. In some embodiments, the photo-crosslinker is lithium phenyl-2,4,6-trimethylbenzoylphosphinate.

[0014] In some embodiments, the polyethylene glycol comprises multiple arms. In some embodiments, the polyethylene glycol comprises 4 arms or 8 arms.

[0015] In some embodiments, the integrin-binding moiety is a peptide. In some embodiments, the peptide comprises RGD. In some embodiments, the peptide comprises GCGYGRGDSPG (SEQ ID NO:1), NGEPRGDTYRAY (SEQ ID NO:2), KGGPQVTRGDVFTMP (SEQ ID NOG), RSTDLPGLKAATHYTITIRGV (SEQ ID NO:4), VFDNFVLK (SEQ ID NOG), ESQEEVVSESRGDNPDPTTSY (SEQ ID NOG), TVDVPDGRGDSLAYG (SEQ ID NO:7), SVVYGLR (SEQ ID NOG), or any one of SEQ ID NO: 9-30, or any combination thereof. In some embodiments, the integrin-binding moiety is derived from vitronectin, tenascin-C, integrin-binding sialoprotein, dentin-matrix phosphoprotein, osteopontin, or any combination thereof.

[0016] In some embodiments, the matrix further comprises a plasmin degradable peptide.

[0017] In some embodiments, about 4% to about 6% of the glucuronic acid moieties on the high molecular weight hyaluronic acid are thiolated.

[0018] In some embodiments, the high molecular weight hyaluronic acid has a molecular weight equal to or greater than about 500 kDa. In some embodiments, the high molecular weight HA has a molecular weight greater than about 500 kDa. In some embodiments the high molecular weight HA has a molecular weight less than about 1,800 kDa. In some embodiments the high molecular weight HA has a molecular weight less than about 1,500 kDa. In some embodiments, the high molecular weight HA has a molecular weight of between about 500 kDa and about 1,500 kDa. In some embodiments, the high molecular weight HA has a molecular weight of between about 500 kDa and about 1,000 kDa. In some embodiments, the high molecular weight HA has a molecular weight of between about 750 kDa and about 1,000 kDa. In some embodiments, the high molecular weight HA has a molecular weight of between about 500 kDa and about 749 kDa. In some embodiments, the high molecular weight HA has a molecular weight of between about 750 kDa and about 1,000 kDa. In some embodiments, the high molecular weight HA has a molecular weight of between about 1,000 kDa and about 1,800 kDa. In some embodiments, the high molecular weight HA has a listed molecular weight of 700 kDa and a listed range of 500 kDa - 750 kDa. In some embodiments, the high molecular weight HA has a listed molecular weight of 1,000 kDa and a listed range of 750 kDa - 1,000 kDa. In some embodiments, the high molecular weight HA has a listed molecular weight of 1,500 kDa and a listed range of 1,010 kDa - 1,800 kDa.

[0019] In one aspect, a method is provided for selecting one or more chemotherapeutic agents for treating a tumor in a patient, comprising the steps of: a. obtaining a tumor biopsy from the patient and isolating tumor cells therefrom; b. preparing a plurality of samples comprising isolated tumor cells, each sample comprising a matrix comprising: i. a high molecular weight hyaluronic acid at a concentration of about 0.25 wt% to about 2 wt%, wherein about 4% to about 10% of glucuronic acid moieties on the hyaluronic acid are thiolated; and ii. a polymer comprising an integrin binding moiety; wherein the thiolated hyaluronic acid and the polymer comprising the integrin binding moiety are cross-linked; c. exposing tumor cells in the plurality of samples to a plurality of first chemotherapeutic agents, each chemotherapeutic agent individually or in combination; and d. identifying among the samples one or more individual or combination of said first chemotherapeutic agents having maximal effect on suppressing growth or invasiveness of the tumor cells, thereby selecting one or more chemotherapeutic agents for treating a tumor in the patient.

[0020] In the foregoing embodiment, all other aspects are as described herein above.

[0021] In some embodiments, the matrix for preparing the plurality of samples comprising isolated tumor cells is selected by a process comprising generating a plurality of matrix compositions having variations in porosity, stiffness, high molecular weight hyaluronic acid content, degree of thiolation of the high molecular weight hyaluronic acid, integrin-binding sites, biodegradability, or any combination thereof, each of said matrix compositions is prepared by a method comprising combining thiolated, high molecular weight hyaluronic acid having about 4% to about 10% of glucuronic acid moieties thiolated, thiolated polyethylene glycol, norbomene-terminated polyethylene glycol, thiolated polymer comprising an integrin-binding moiety, plasmin-degradable peptide, or any combination thereof; cross-linking the thiolated hyaluronic acid, thiolated polyethylene glycol and thiolated polymer comprising an integrin-binding moiety, incubating the tumor cells in each of the plurality of matrix compositions; and identifying a matrix composition in which the tumor cells exhibit one or both of maximal tumor growth and maximal tumor invasion, thereby selecting the matrix.

[0022] In some embodiments, the matrix for preparing the plurality of samples comprising isolated tumor cells is selected by a process comprising generating a plurality of matrix compositions having variations in porosity, stiffness, high molecular weight hyaluronic acid content, degree of thiolation of the high molecular weight hyaluronic acid, integrin-binding sites, biodegradability, or any combination thereof, each of said matrix compositions is prepared by a method comprising combining thiolated, high molecular weight hyaluronic acid having about 4% to about 10% of glucuronic acid moieties thiolated, norbornene-terminated polyethylene glycol, thiolated polymer comprising an integrin-binding moiety, plasmin-degradable peptide, or any combination thereof; cross-linking the thiolated hyaluronic acid and thiolated polymer comprising an integrin-binding moiety, incubating the tumor cells in each of the plurality of matrix compositions; and identifying a matrix composition in which the tumor cells exhibit one or both of maximal tumor growth and maximal tumor invasion, thereby selecting the matrix.

[0023] In some embodiments, a plurality of matrix compositions for any of the foregoing purposes may comprise one or more matrix compositions comprising a thiolated polyethylene glycol and one or more matrix compositions not comprising a thiolated polyethylene glycol.

[0024] In some embodiments, the identifying a matrix composition may be carried out in two or more successive cycles, e.g., initially using a wide range of matrix properties, identifying a maximal tumor growth and/or maximal tumor invasion within the wide range, then preparing a narrower range of matrix properties based on e.g. bracketing the maximal tumor response, identifying within the narrower range the optimal tumor growth and/or optimal tumor invasion, thereby selecting the matrix. In some embodiments, further narrowing the range may be carried out to identify the optimal matrix for screening.

[0025] In some embodiments, the tumor is a glioblastoma. In some embodiments, the matrix is configured to allow one or both of maximal growth of the tumor cells and maximal invasiveness of the tumor cells. In some embodiments, the matrix allows for maximal clustering of integrins with other receptors, including other integrin receptors, on the tumor cells. In some embodiments, before exposing the tumor cells to said chemotherapeutic agents, the matrix is optimized for properties that maximize one or both of growth of the tumor cells and invasion of the tumor cells. In some embodiments, those properties comprise one or more of matrix stiffness, high molecular weight hyaluronic acid concentration, degree of thiolation of the high molecular weight hyaluronic acid, concentration and selection of integrin binding peptide, porosity, biodegradability, and any combination thereof.

[0026] In some embodiments, the matrix does not comprise thiolated polyethylene glycol.

[0027] In some embodiments, the matrix has a storage modulus between about 50 to about 2000 Pa. In some embodiments, the matrix has a pore size of up to about 13 nm.

[0028] In some embodiments, the growth of the tumor cells is determined by imaging, biochemical assay, luminescent assay, or assay for a reporter product. In some embodiments, the invasiveness of the tumor cells is determined by imaging, biochemical assay, luminescent assay, or assay for a reporter product.

[0029] In some embodiments, one or more visible or fluorescent labeled reagents or reporters are used to monitor the growth or invasiveness of the tumor cells.

[0030] In some embodiments, tumor growth kinetics are determined over time. [0031] In some embodiments, an increase in the growth of the tumor cells after a certain time indicates development of resistance of the tumor cells to said first chemotherapeutic agents after exposure for said time. In some embodiment, development of said resistance to the first chemotherapeutic agent is used to evaluate effects of a combination of said first chemotherapeutic agent with another one or more second chemotherapeutic agents on the development of resistance.

[0032] In some embodiments, the chemotherapeutic agent is an agent approved for treatment of the tumor, an agent approved for treatment of cancer other than the tumor, an agent approved for compassionate use, an agent in clinical trials for treatment of the tumor, an agent in clinical trials for treatment of cancer other than the tumor, or an approved or experimental agent used in combination with a chemotherapeutic agent for the tumor or for a cancer other than the tumor.

[0033] In one aspect, a composition is provided for evaluating growth or invasiveness of tumor cells for identifying potential chemotherapeutic agents, the composition comprising a matrix comprising: i. a high molecular weight hyaluronic acid at a concentration of about 0.25 wt% to about 2 wt%, wherein about 4% to about 10% of glucuronic acid moieties on the hyaluronic acid are thiolated; ii. a thiolated polyethylene glycol; and ii. a polymer comprising an integrin binding moiety; wherein the thiolated hyaluronic acid, the thiolated polyethylene glycol and the polymer comprising the integrin binding moiety are cross-linked.

[0034] In some embodiments, about 4% to about 6% of the glucuronic acid moieties on the high molecular weight hyaluronic acid are thiolated.

[0035] In some embodiments, the matrix does not comprise thiolated polyethylene glycol.

[0036] In some embodiments, the polymer comprising an integrin binding moiety comprises a norbornene-terminated polyethylene glycol, a maleimide-terminated polyethylene glycol or a vinyl sulfone terminated polyethylene glycol.

[0037] In some embodiments, the composition further includes: a. a maleimide polyethylene glycol or vinyl sulfone polyethylene glycol; b. a vinyl sulfone polyethylene glycol and a radical generator; or c. a norbomene-terminated polyethylene glycol and a radical generator.

[0038] In some embodiments, the radical generator is a photo-crosslinker. In some embodiments, the photo-crosslinker is lithium phenyl-2,4,6-trimethylbenzoylphosphinate.

[0039] In some embodiments, the polyethylene glycol comprises multiple arms.

[0040] In some embodiments, the integrin-binding moiety is a peptide. In some embodiments, the peptide comprises RGD. In some embodiments, the peptide comprises GCGYGRGDSPG (SEQ ID NO:1), RGDSPG (SEQ ID NO:9), NGEPRGDTYRAY (SEQ ID NO:2), KGGPQVTRGDVFTMP (SEQ ID NOG), RSTDLPGLKAATHYTITIRGV (SEQ ID NO:4), VFDNFVLK (SEQ ID NOG), ESQEEVVSESRGDNPDPTTSY (SEQ ID NOG), TVDVPDGRGDSLAYG (SEQ ID NO:7), SVVYGLR (SEQ ID NOG), or any one of SEQ ID NO: 10-30, or any combination thereof, or any combination thereof. In some embodiments, the integrin-binding moiety is derived from vitronectin, tenascin-C, integrin-binding sialoprotein, dentin-matrix phosphoprotein, osteopontin, or any combination thereof.

[0041] In some embodiments, the high molecular weight hyaluronic acid has a molecular weight average of about 700 kDa and a listed range of about 500kDa - about 750kDa.

[0042] In some embodiments, the composition further comprising a plasmin-degradable peptide.

[0043] In some embodiments, the matrix comprises thiolated, high molecular weight hyaluronic acid having about 4 % to about 10 % of glucuronic acid moieties thiolated, thiolated polyethylene glycol, norbomene-terminated polyethylene glycol, thiolated polymer comprising an integrin-binding moiety, plasmin-degradable peptide, or any combination thereof. In some embodiments, about 4% to about 6% of the glucuronic acid moieties on the high molecular weight hyaluronic acid are thiolated.

[0044] In some embodiments, the matrix has a storage modulus between about 50 to about 2000 Pa. In some embodiments, the matrix has a pore size of up to about 13 nm.

[0045] In one aspect, a composition is provided for evaluating growth or invasiveness of tumor cells for identifying potential chemotherapeutic agents, the composition comprising a matrix comprising: i. a high molecular weight hyaluronic acid at a concentration of about 0.25 wt% to about 2 wt%, wherein about 4% to about 10% of glucuronic acid moieties on the hyaluronic acid are thiolated; and ii. a polymer comprising an integrin binding moiety; wherein the thiolated hyaluronic acid and the polymer comprising the integrin binding moiety are cross-linked.

[0046] In the foregoing embodiment, all other aspects are as described herein above.

[0047] In one aspect, a method is provided for treating a tumor in a patient comprising the steps of: a. selecting one or more first chemotherapeutic agents for treating the tumor in the patient according the any of the methods described above; and b. administering said chemotherapeutic agents to the patient.

[0048] In some embodiments, the tumor is a glioblastoma.

[0049] In some embodiments, when resistance to the first chemotherapeutic agent is detected, treatment of said patient with said first chemotherapeutic agent is limited to a duration prior to said resistance is developed. In some embodiments, treatment for said patient is continued with a second chemotherapeutic agent.

[0050] In some embodiments, the patient is treated with the first chemotherapeutic agent in combination with one or more chemotherapeutic agents that delay or prevent resistance to the first chemotherapeutic agent.

[0051] In some embodiments, the chemotherapeutic agent is an agent approved for treatment of the tumor, an agent approved for treatment of a cancer other than the tumor, an agent approved for compassionate use, an agent in clinical trials for treatment of the tumor, an agent in clinical trials for treatment of a cancer other than the tumor, or an approved or experimental agent used in combination with a chemotherapeutic agent for the tumor or for a cancer other than the tumor.

[0052] These and other aspects of the invention will be appreciated from the ensuing descriptions of the figures and detailed description of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Some embodiments of the invention are herein described, by way of example only, with reference to the accompanying drawings. With specific reference now to the drawings in detail, it is stressed that the particulars shown are by way of example and for purposes of illustrative discussion of embodiments of the invention. In this regard, the description taken with the drawings makes apparent to those skilled in the art how embodiments of the invention may be practiced.

[0054] Figures 1A-D show that glioblastoma (GBM) xenografts acquire resistance to erlotinib at cranial sites with faster kinetics than at subcutaneous sites. FIG. 1A) bioluminescence of orthotopic xenografts of GMB39 cells, N=3. Initial response to erlotinib (before day 20) confirms erlotinib crosses the blood-brain barrier. FIG. IB) volume of subcutaneously xenografted GBM39 cells, N=4; FIG. 1A and FOG. IB data shown were normalized to day 0 before treatment with 50 mg/kg erlotinib. Error bars show standard deviation. FIG. 1C and FIG. ID) representative images of GBM39 xenografts. FIG. 1C) IHC for HA (brown) counterstained with hematoxylin (purple). White dashed lines delineate tumor. Scale bars = 100 um. FIG. ID) IF staining for CD44 (red), p-EGFR (Tyrl068) (green), Hoechst 33342 (blue) and H&E of adjacent tissue sections. Scale bars = 200 um.

[0055] Figure 2 shows the relationships between experimental models of GBM and the original tumor.

[0056] Figures 3A-E depict the fabrication and characterization of biomaterial scaffolds. FIG. 3A) hydrogels formed from thiolated HA and RGD-modified PEG for 3D encapsulation of cells for culture (and control modified PEG, modified only with cysteines). FIG. 3B) effective diffusion coefficients cm2/s) for 20 kDa and 70 kDa dextrans, respectively, through hydrogels, N=3. FIG. 3C) linear compressive moduli of hydrogels. Percentages indicate weight to volume ratios (w/v). FIG. 3D) effective diffusion coefficients (cm2/s) for 20 kDa and 70 kDa dextrans, respectively, through hydrogels, N=3. FIG. 3D) viable cells quantified from images of live (Calcein AM)/dead (ethidium bromide) staining 24 hours after encapsulation, N=3. FIG. 3E) on the 4^th day of culture, encapsulated cells were pulsed with EdU (I uM) for 2.5 hours. Cells were removed from hydrogels and percentage of cells that had proliferated (EdU+) assessed using a flow cytometer, N=3. FIGS. 3A-E) Error bars show S.E.M. One, two-way ANOVA with Tukey’s test for multiple comparisons was performed. (*p<0.05, ***p<0.001).

[0057] Figures 4A-E depicts the modeling of resistance in tissue-engineered scaffolds. FIG. 4A) bioluminescence of erlotinib-treated TE-GS. N=3. FIG. 4B) proliferation rate in TE-GS (EdU incorporation over 2.5 hours) during erlotinib treatment. N=3. FIGS. 4A,B) Two-way ANOVA with Sidak’s test for multiple comparisons against GS. Treated samples normalized to non-treated samples and prior to treatment. FIG. 4C) apoptotic (c-PARP+) cells after 6 days of treatment, N=3. One-way ANOVA with Tukey’s test. FIG. 4D) bioluminescence of GS-DX (normalized to day 0 before adding 75 mg/kg erlotinib). N=4. FIG. 4E) number of cells (HK301) in GSs after treatment. N-3. GS, TE-GS received 1 uM erlotinib. FIGS. 4A-E) All used HK301 patient derived GS. Error bars show S.E.M. ***p<0.001, ****p<0.0001.

[0058] Figures 5A-C show that CD44-HA interactions facilitate erlotinib resistance. FIG. 5A) IF staining for CD44 (red) in cryosectioned TE-GS and GS of HK301 cells. shRNA knockdown was sustained at least 15 days (see image). Scale bars = 100 um. FIG. 5B) proliferation rates in TE-GS (EdU pulse over 2.5 hours) during erlotinib treatment. N=3. Two way ANOVA with Sidak’s test. Treated normalized to non-treated. FG. 5C) apoptotic (c-PARP+) cells after 6 days of treatment, N=3. One-way ANOVA with Tukey’s test. Error bars show S.E.M.

[0059] Figures 6A-B show that HA and RGD have cooperative effects on acquisition of treatment resistance and spreading in TE-GS models. FIG. 6A) apoptotic cells (HK301) (cPARP+/total nuclei) after 3 days of erlotinib (1 uM), N=3. Error bars show S.E.M. One-way ANOVA with Tukey’s test. *p<0.05, **p<0.01. FIG. 6B) phase contrast images of HK301s in 3D culture. Al scaffolds are 1 kPa. Scale bars = 200 um.

[0060] Figures 7A-E show that GBM cells gain resistance to multiple treatments in TE-GS.

[0061] Figure 8 shows gene expression profiles in patent-matched GS-DX, TE-GS and GS models. FIG. 8 A) principal component analysis (PCA) was used to construct plots based on gene expression profiles from individual samples. Numbers in x and y axis show percentage of variation accounted in the graphical representation (n=2, for each patient-derived GMB line, GS204 and GS025).

[0062] Figure 9 depicts tissue-engineered scaffolds for 3-D culture. Left: schematic of scaffold formulations. Right: representative image of a mass of GBM cells cultured in 3D scaffolds. Here, both RGD peptides and hyaluronic acid are included, which induced co-expression of integrin alphaV and CD44 receptors.

[0063] Figures 10A-E show that HA-CD44 and RGD-INTAV interactions synergistically enhance resistance to alkylating chemotherapies (TMZ, carmustine) through Src activation. FIG. 10A) shRNA knockdown of either CD44 or intav9cleaved PARP) in response to TMZ. Bioluminescence tracking indicates that very few cells survive treatment with double knock down. FIG. 10B) shRNA knock down of CD44 and/or INTAV decreased pSrc/tSrc. FIG. 10C) inclusion of HA and RGD in TES induces co-expression of CD44 and INTAV, which is eliminated by the INTAV binding inhibitor cilengitide. FIG. 10D) Src inhibition enhances TMZ sensitivity.

[0064] Figures 11A-D depicts gene expression (bulk RNAseq) in patient-derived GBM cells. PCA showed that expression profiles in hydrogels cultures were more similar along PC2 to patient-matched (GS025) PDOX than gliomaspheres (GS) (FIG. 11 A). PC2 included genes associated with PMT and hypoxia. After 1 TMZ cycle (3 days on, 4 days off), hydrogel cultures (HA+RGD) were further enriched in genes associated with hypoxia (FIG. 11B) DNA repair (FIG. 11C) and PMT (FIG. 11D), compared to GS cultures. N=2.

[0065] Figure 12 depicts ECM-activated resistance pathways in GBM. Red starburst indicate proteins whose activities will be measured using xMAP ELISAs (example data for mTOR and MK1 are shown).

[0066] Figure 13 depicts genesets associated with GBM progression, assessed through RNA sequencing, are enriched in TE-GS and GS-DX, compared to GS models. Enrichment plots are shown for genesets. When drilling down into these data, it was observed that GBM cells in the TE-GS are phenotypically more similar to GS-DX models than are GS models. In particular, TE-GS better retains in vivo expression of genesets related to cancer progression, including upregulation of TNF-alpha-NF-kB signaling and hypoxia-induced factors.

[0067] Figures 14A-C depict GBM39 cells show sensitivity to erlotinib treatment in both TEGS cultures and murine intracranial xenografts. FIG. 14A) flow cytometry plots showing proliferating cells on day 3 of treatment with erlotinib (1 uM) or vehicle. EDU was added to culture medium for 2 hours, during which time proliferating cells incorporate EDU and can be visualized using flow cytometry. TE-GS cultures have fewer proliferating cells than GS cultures. FIG. 14B) bioluminescence tracking of GBM39 cells in TE-GS cultures over time. Treated cultures (1 uM erlotinib) are normalized to vehicle controls. FIG. 14C) Kaplan- Meier plot showing survival of GS-DX mice with GBM39 when treated with erlotinib (50 mg/kg) or vehicle control. These data confirm that the biomaterial platform is compatible with assessing treatment resistance in a second patient-derived cell line. This was shown for another line, HK301, in Figure 4.

[0068] Figure 15 shows hydrogel cross-linked via Michael-type addition reaction. Solution A, a mixture of PEG-maleimide, RGD, and single-cells, is combined with Solution B, HA-SH bonded to PEG-SH through di-sulfides, to allow for 3D encapsulation of cells in a hydrogel cross-linked via Michael-type Addition reaction.

[0069] Figure 16 shows hydrogel cross-linked via thiol-ene photoclick chemistry. A mixture of RGD, and PEG-norbornene, HA-SH bonded to PEG-SH through di-sulfides, combined with photoinitiator, LAP, and illuminated with UV light to allow for 3D encapsulation of cells in a hydrogel cross-linked via thiol-ene photoclick chemistry.

[0070] Figure 17 shows a 96-well set up for each encapsulation experiment. Five control groups and 5 experimental groups per condition. Five plates were prepared for each experiment, each for one timepoint. Blue: Control groups treated with DMSO, Yellow: Experimental groups treated with chemotherapeutic, TMZ.

[0071] Figure 18 shows a 96-well set up for each encapsulation experiment. Three control groups and 3 experimental groups per condition. Two plates were prepared for each experiment, each for one timepoint. Blue: Control groups treated with DMSO, Yellow: Experimental groups treated with chemotherapeutic, TMZ. Purple: Treated with ezrin inhibitor. Green: Treated with cilengitide.

[0072] Figure 19 shows GFP and Phase-contrast images (lOx) of GS54 gliomaspheres in suspension culture on Day 1, 3, 6, 9, and 12 (Control and Treated). Scale bars are 100 pm.

[0073] Figure 20 shows GFP and Phase-contrast images (lOx) of GS25 gliomaspheres in suspension culture on Day 1, 3, 6, 9, and 12 (Control and Treated). Scale bars are 100 μm.

[0074] Figure 21 shows GFP and Phase-contrast images (lOx) of Michael-type addition reaction hydrogels with encapsulated GS54 cells on Day 1, 3, 6, 9, and 12 (Control and Treated). Scale bars are 100 μm.

[0075] Figure 22 shows GFP and Phase-contrast images (lOx) of Michael-type addition reaction hydrogels with encapsulated GS25 cells on Day 1, 3, 6, 9, and 12 (Control and Treated). Scale bars are 100 μm.

[0076] Figure 23 shows GFP and Phase-contrast images (lOx) of photo-crosslinked hydrogels with encapsulated GS54 cells on Day 1, 3, 6, 9, and 12 (Control and Treated). Scale bars are 100 μm.

[0077] Figure 24 shows GFP and Phase-contrast images (lOx) of photo-crosslinked hydrogels with encapsulated GS25 cells on Day 1, 3, 6, 9, and 12 (Control and Treated). Scale bars are 100 μm.

[0078] Figure 25 shows GFP and Phase-contrast images (lOx) of HyStem hydrogels with encapsulated GS54 cells on Day 1, 3, 6, 9, and 12 (Control and Treated). Scale bars are 100 μm.

[0079] Figure 26 shows GFP and Phase-contrast images (lOx) of HyStem hydrogels with encapsulated GS25 cells on Day 1, 3, 6, 9, and 12 (Control and Treated). Scale bars are 100 μm.

[0080] Figure 27 shows GFP and Phase-contrast images (lOx) of Matrigel hydrogels with encapsulated GS54 cells on Day 1, 3, 6, 9, and 12 (Control and Treated). Scale bars are 100 μm.

[0081] Figure 28 shows GFP and Phase-contrast images (lOx) of Matrigel hydrogels with encapsulated GS25 cells on Day 1, 3, 6, 9, and 12 (Control and Treated). Scale bars are 100 μm.

[0082] Figure 29 shows control groups for GS54 cells encapsulated in the hydrogel scaffolds and cultured in 2D, on Days 3, 6, 9, and 12.

[0083] Figure 30 shows control groups for GS25 cells encapsulated in the hydrogel scaffolds and cultured in 2D, on Days 3, 6, 9, and 12.

[0084] Figure 31 shows comparison of control and treated groups for GS54 cells encapsulated in the hydrogel scaffolds and cultured in 2D, on Days 3, 6, 9, and 12.

[0085] Figure 32 shows comparison of control and treated groups for GS25 cells encapsulated in the hydrogel scaffolds and cultured in 2D, on Days 3, 6, 9, and 12. [0086] Figure 33 shows GFP and phase-contrast images (lOx) of GS54 gliomaspheres cells on Day 1, 3, 6, 9, and 12 (Control and Treated). Cells were treated with cilengitide, ezrin inhibitor, TMZ, and a combination of TMZ and inhibitor. Scale bars are 100 μm.

[0087] Figure 34 shows GFP and phase-contrast images (lOx) of Michael-type addition reaction hydrogels with encapsulated GS54 cells on Day 1, 3, 6, 9, and 12 (Control and Treated). Cells were treated with cilengitide, ezrin inhibitor, TMZ, and a combination of TMZ and inhibitor. Scale bars are 100 μm.

[0088] Figure 35 shows GFP and phase-contrast images (lOx) of photo-crosslinked hydrogels with encapsulated GS54 cells on Day 1, 3, 6, 9, and 12 (Control and Treated). Cells were treated with cilengitide, ezrin inhibitor, TMZ, and a combination of TMZ and inhibitor. Scale bars are 100 μm.

[0089] Figure 36 shows GFP and phase-contrast images (lOx) of Matrigel with encapsulated GS54 cells on Day 1, 3, 6, 9, and 12 (Control and Treated). Cells were treated with cilengitide, ezrin inhibitor, TMZ, and a combination of TMZ and inhibitor. Scale bars are 100 μm.

[0090] Figure 37 shows GFP and phase-contrast images (lOx) of HyStem with encapsulated GS54 cells on Day 1, 3, 6, 9, and 12 (Control and Treated). Cells were treated with cilengitide, ezrin inhibitor, TMZ, and a combination of TMZ and inhibitor. Scale bars are 100 μm.

[0091] Figure 38 shows comparison of Control, Control + Ezrin Inhibitor, Control + Cilengitide to Treatment + Ezrin Inhibitor, Treatment + Cilengitide groups of GS54 cells encapsulated in the hydrogel scaffolds and cultured in 2D, on Days 3, 6, 9, and 12.

[0092] Figure 39 shows comparison of Control, Control + Ezrin Inhibitor, Control + Cilengitide to Treatment + Ezrin Inhibitor, Treatment + Cilengitide groups of GS54 cells encapsulated in the hydrogel scaffolds and cultured in 2D, on Days 3, 6, 9, and 12.

[0093] Figure 40 shows immunostaining for Ki67 and Hoescht to observe tumor cell proliferation. Hydrogel conditions were sectioned (18 μm) on days 3 and 12 (control and treated) and stained to compare proliferation through the course of the experiment and between groups.

[0094] Figure 41 shows immunostaining for CD44 and Hoescht to observe cell apoptosis.

Hydrogel conditions were sectioned (18 μm) on days 3 and 12 (control and treated) and stained to qualitatively compare CD44 expression of tumor cells through the course of the experiment and between groups.

[0095] Figure 42 shows immunostaining for cPARP and Hoescht to observe cell apoptosis. Hydrogel conditions were sectioned (18 μm) on days 3 and 12 (control and treated) and stained to qualitatively compare apoptosis through the course of the experiment and between groups.

[0096] Figures 43A-43E show the importance of HA in GBM pathophysiology. Fig. 43A: Representative image of IHC staining of TMA slides. Brown, positive stain; dark blue, hematoxylin. Scale bar = 100 μm. Fig. 43B: 34 GBM and 19 lower-grade CNS cancer TMA stainings semi-quantitatively scored. Mann- Whitney U Test was used to assess significance. Fig. 43C: Staining of patient-resected tumor sample. Blue square = area of high HA concentration. Yellow square = area of low HA concentration. Scale bar = 100 μm. Fig. 43D: HA (yellow) staining images of HK408 xenograft. Scale bar = 200 μm E) HA (yellow) staining images of HK408 xenograft. Scale bar = 100 μm.

[0097] Figures 44A-44C show hydrogel characterization. Fig. 44A: Mass swelling ratios of individual hydrogels following fabrication. Fig. 44B: Storage moduli of hydrogels of varied HA concentrations show no significant differences. Fig. 44C: Diffusion rates of 20 kDa and 70 kDa FITC-Dextran polymers are similar across hydrogel conditions and match that of PBS controls.

[0098] Figures 45A-45D show characterization of GSs in 3D culture conditions. Fig. 45 A: LIVE/DEAD staining and subsequent quantification was performed to assess cell viability following 6 days in culture for HK408 and GS054 gliomaspheres. Fig. 45B: Quantification of Cl-PARP positive cells in HK408 and GS054 GS sections following 6 days in culture. Fig. 45C: Representative images of Ki-67 staining of HK408 and GS054 GS sections following 6 days in culture. Scale bar = 50 μm. Fig. 45D: EdU proliferation assay performed at day 6 for HK408 GSs in hydrogel and media culture. **, p < 0.01; ***, p < 0.001; ****, p < 0.0001.

[0099] Figures 46A-46E show images of HK408 and GS054 GSs following 6 days in culture. Fig. 46A: Representative images of HK408 and GS054 GSs following 6 days in culture. Scale bar = 100 μm. Fig. 46B: Shape factor quantification of HK408 GSs from days 1 - 6. Fig. 46C: Migration lengths of HK408 GSs at the end of sixth day in culture. Fig. 46D: Shape factor quantification of GS054 GSs from days 1 - 6. Fig. 46E: Migration lengths of GS054 GSs at the end of sixth day in culture. *, p < 0.05; ***, p < 0.001; ****, p < 0.0001. [0100] Figures 47A-47E show images of HK217 and HK177 GSs following 6 days in culture. Fig. 47A: Representative images of HK217 and HK177 GSs following 6 days in culture. Scale bar = 100 μm. Fig. 47B: Shape factor quantification of HK217 GSs from days 1 - 6. Fig. 47C: Migration lengths of HK217 GSs at the end of sixth day in culture. Fig. 47D: Shape factor quantification of HK177 GSs from days 1 - 6. Fig. 47E: Migration lengths of HK177 GSs at the end of sixth day in culture. *, p < 0.05; **, p < 0.01; ****, p < 0.0001.

[0101] Figure 48 shows representative images of HK408 GSs stained for CD44 and RHAMM following 6 days of culture. Scale bar = 10 μm.

[0102] Figure 49 shows representative images of GS054 GSs stained for CD44 and RHAMM following 6 days of culture. Scale bar = 10 μm.

[0103] Figures 50A-50D show representative images of HK408 xenografts stained for CD44, RHAMM, and Ezrin. Fig. 50A: Image of HK408 cells stained for CD44 (green) and RHAMM (red). Scale bar = 25 μm. Fig. 50B: Insets of HK408 cells stained for CD44 (green) and RHAMM (red). Scale bar = 10 μm. Fig. 50C: Image of HK408 cells stained for CD44 (green) and Ezrin (red). Scale bar = 25 μm. Fig. 50D: Insets of HK408 cells stained for CD44 (green) and Ezrin (red). Scale bar = 10 μm. Arrows designate regions of relatively higher overlap between CD44 and Ezrin in migrating and mechanosensing cells. High levels of collective migration also notable.

[0104] Figure 51A shows representative images of HK408 GSs stained for CD44 and Ezrin following 6 days of culture. Scale bar = 10 μm. Figure 51B shows Pearson correlation coefficient distribution of overlapping green and red pixel per staining for HK408 and GS054 GSs. *, p < 0.05; **«, p < 0.0001.

[0105] Figure 52 shows representative images of GS054 GSs stained for CD44 and Ezrin following 6 days of culture. Scale bar = 10 μm.

[0106] Figures 53A-53C show ERM inhibition studies on HK408 and GS054 GSs. Fig. 53A: Shape factor distribution of GS054 GSs at endpoint following treatment with 0 - 20 pM of ERMi. Fig. 53B: Shape factor distribution of HK408 GSs at endpoint following treatment with 0 - 20 pM of ERMi. Fig. 53C: Representative images of HK408 and GS054 GSs at endpoint following treatment with 0, 5, and 20 μM ERMi. Scale bar = 100 μm. **, p < 0.01; ****, p < 0.0001. [0107] Figures 54A-54B show ERM inhibition studies on HK217 GSs. Fig. 54A: Shape factor distribution of HK217 GSs at endpoint following treatment with 0 - 20 pM of ERMi. Fig. 54B: Representative images of HK217 and GS054 GSs at endpoint following treatment with 0, 5, and 20 pM ERMi. Scale bar = 100 μm. ***, p < 0.001; ****, p < 0.0001.

[0108] Figure 55 shows representative images of HK408 GSs following 6 days in culture in HA hydrogels with CYS substituted for RGD peptides. Arrows in images of zoomed insets indicate instances of cell motility at GS peripheries.

[0109] Figures 56A-56C show RHAMM inhibition studies on HK217 and HK408 GSs. Fig. 56A: Migration length quantification of HK217 GSs 36 hours following administration of RBP. Fig. 56B: Migration length quantification of HK408 GSs at day 1 timepoint (9 hours post administration of RBP). Fig. 56C: Migration length quantification of HK408 GSs at day 3 timepoint (9 hours following 2^nd administration of RBP). *, p < 0.05; **, p < 0.01; ***, p < 0.001.

DETAILED DESCRIPTION OF THE INVENTION

[0110] In one embodiment, the present disclosure utilizes glioblastoma as an example to illustrate the various features of the present patient-specific drug screening methodology. One of ordinary skill in the art would readily apply the patient-specific drug screening platform disclosed herein to other cancer or diseases.

[0111] Glioblastoma (GBM) is an uniformly lethal cancer originating in the brain with a median survival time of only 12-15 months from diagnosis. GBM tumors overwhelmingly acquire resistance to treatment. High degrees of heterogeneity both across patients and within single tumors make a blanket treatment option for GBM patients unlikely to be effective. Thus, develoμment of strategies to identify effective, patient-specific therapies, otherwise known as personalized medicine, is a major goal of cancer researchers and clinicians. While GBM tumors in different patients carry unique genomic aberrations that represent druggable targets, this strategy has been largely unsuccessful due to the plastic ability of GBM to acquire resistance. The tumor microenvironment is key to its dynamic ability to acquire resistance. Cells and the extracellular matrix (ECM) in the microenvironment act together in an “ecosystem” to enable resistance to a wide variety of treatments. Given this cooperation, it is believed that accounting for the unique brain ECM when developing strategies for personalized medicine will be key to their clinical translation. Thus, the present disclosure describes biomaterial scaffolds that mimic the brain ECM for three-dimensional (3D) culture of patient-derived, primary GBM cells. Importantly, in these tissue-engineered models, multiple patient cells lines acquire resistance to treatment with kinetics approximating those in patient-matched, in vivo xenografts.

[0112] In one embodiment, the present disclosure describes an innovative platform for personalized medicine that combines genotypic and phenotypic data with functional assays in tissue-engineered platforms to accurately predict clinical responses to treatment. In addition, these platforms will be useful for discovery of new treatments in a research setting.

GBM Heterogeneity And Personalized Medicine

[0113] A large effort to genotype clinical tumors through whole-exome sequencing (WES) has identified several common genetic aberrations in GBM. These results revealed significant intertumoral heterogeneity. However, attempts to use the genotype of a single tumor to motivate personalized treatments targeting a single genetic aberration have been largely unsuccessful. One likely explanation is that genomic alterations do not directly predict downstream transcriptomic or proteomic profiles. Moreover, functional redundancy of signaling networks within tumor cells, coupled with genomic alterations induced by treatment resistance, motivate the need to integrate patient-specific phenotypic information into approaches to personalized medicine.

Microenvironment, ECM And Treatment Resistance

[0114] Beyond intrinsic genotypic and phenotypic features, GBM cells dynamically respond to extrinsic factors in their local microenvironment, including chemical and physical properties of the ECM, which in turn plays a critical role in treatment resistance. GBM is not a metastasizing cancer. Instead, tumors rarely spread beyond the brain and retain a close relationship with their microenvironment. Previous results have clearly demonstrated the importance of the unique brain microenvironment to GBM resistance. Patient-derived GBM cells were xenografted at either intracranial or subcutaneous (dorsal flank) sites in NOD-SCID gamma null (NSG) mice and treated with erlotinib, a targeted inhibitor of epidermal growth factor receptor (EGFR). Results showed that intracranial xenografts acquired resistance ~10x faster than subcutaneous xenografts from the same clinical tumor tumors (Figs. 1A-B). [0115] Compared to other tissues, the brain ECM is physically softer and highly enriched in the long-chain polysaccharide hyaluronic acid (HA). High levels of HA predict aggressiveness in many cancers. In GBM, the HA receptor CD44 is often upregulated and high expression of CD44 in clinical tumors is a poor prognostic indicator. While HA was present within both intracranially and subcutaneously xenografted tumors and surrounding brain tissue (Fig. 1C), it was not detectable in the tissue surrounding subcutaneous tumors (Fig. ID). These findings agree with previous reports in which HA-CD44 interactions were found to contribute to events throughout cancer progression, including initial tumor develoμment, cell proliferation, invasion and resistance to multiple therapeutic agents. Besides HA, increased deposition of several other ECM components, including vitronectin and fibronectin, directly correlates with poor prognosis of GBM tumors. These ECM proteins interact with multiple integrins through the ubiquitous integrin-binding RGD sequence, as well as other less-studied peptide sequences. Many integrins are also overexpressed in GBM tumors. Together, these observations support the hypothesis that the unique brain ECM facilitates survival and treatment resistance of tumors originating in the brain.

Experimental Models of GBM

[0116] Patient-derived gliomaspheres (GSs), the current standard culture model, do not adequately reflect clinical outcomes. This shortcoming is likely because GSs do not sufficiently capture two key aspects of patient tumors. First, GSs are highly enriched in stem-like glioma cells (GSCs), which reside in relatively low abundance in native tumors, while cells of various subtypes within the original tumor population with low self-renewal capabilities are lost. Second, while GS culture provides a 3D environment, the lack of ECM until after GS cultures have been established may result in the loss of important phenotypic characteristics.

[0117] Moreover, while xenograft models enable study of GBM within the microenvironment of a living host, the cost, time, reproducibility and complexity of performing in vivo experiments all present significant disadvantages.

Tissue- Engineered Models Address Many of These Limitations

[0118] Through orthogonal control of biochemical and biophysical features, tissue-engineered scaffolds can provide a simplified, reproducible experimental platform. Hydrogel biomaterials — which exhibit tissue-like water content and mechanical properties, support 3D cell culture, and can be fabricated from ECM-derived biomolecules — are particularly suitable as ex vivo scaffolds. While xenografts typically take weeks to months to establish, and thus are not feasible for informing treatment plans that are truly patient-specific for GBM, where the median survival time is <15 months, tissue-engineered models can be established within clinically actionable time frame of days to weeks. As ex vivo models do not account for systemic factors — such as endocrine and immune signals — or an intact blood-brain barrier (BBB), they cannot completely replace in vivo models. While no model is perfect, it is essential to understand the degree by which each model system (e.g., cell culture, murine xenograft) recapitulates specific molecular and functional characteristics of human tumors. In one embodiment, the work is to develop models of human GBM that can address how intertumoral heterogeneity among clinical tumors contributes to acquisition of treatment resistance and tumor evolution with disease progression. Given the advantages in reproducibility, experimental control, affordability and speed that tissue-engineered constructs can provide over animal models, it would be feasible to perform ex vivo assays on a patient’s own cells that could be used to identify and implement patient-specific treatment strategies within a clinically relevant time frame. When developing such a model in vivo, one must strike a balance between adding more complexity — and moving closer to the in vivo case — and maintaining a degree of simplicity that preserves these advantages. Moreover, effective use of ex vivo, preclinical models requires cross-comparison of models across tumors with various genetic alterations to best determine their ability to preserve relevant features of original patient tumors — in this case an ecosystem of tumor cells recapitulating the diversity of molecular alterations and phenotypes unique to a specific patient’s tumor.

[0119] Most approaches to personalized medicine for GBM have sought to predict patientspecific outcomes to genomic aberrations; however, these have yet to demonstrate adequate robustness for broad clinical translation. The studies herein explore the relationship between tumor genotype, microenvironment and treatment resistance. While the cell components of the microenvironment are obviously important to tumor physiology, it is believed that contributions of the non-cell, extracellular matrix (ECM) features are similarly significant. While the ECM is known to maintain the phenotype of various cells in different tissues, the mechanisms of how the ECM affects cell phenotype in brain tissues and cancers are not well understood. The experiments will directly compare multiple experimental models established from a single tumor (Fig. 2). Together, the proposed studies will provide transformative insight into how the brain tumor ECM affects the ability of tumor cells to gain resistance to treatment across a heterogeneous patient population.

[0120] In one embodiment, experimental models for GBM, with improved fidelity to patient tumors, are described herein. Data are collected across hierarchies of biological (e.g., genetic, transcriptomic and functional data) and physiological (single cell, microenvironment, tissue) function. Experiments include using state-of-the art WES and single-cell RNA sequencing (scRNAseq) to collect data from clinical samples. Finally, by collecting data from patient- derived GBM cell lines that reflect the diverse range of the genomic characteristics seen clinically, one could identify predictable relationships between a patient’s specific pathological data (genomic and phenotypic) and treatment response.

[0121] Key technological innovations are included herein that elevate biomaterial scaffolds to compelling new preclinical models of GBM. First, in the present disclosure, hyaluronic acid (HA) is minimally modified (~5% of disaccharides contain a thiol substitution) to maintain the native ability of high molecular weight HA to interact with CD44 receptors. In contrast, other methods often modify up to 70% of HA disaccharides. Secondly, biomaterials used herein incorporate high molecular weight HA (e.g., 500-750 kDa), which represents the species found in healthy brain and has distinct bioactivities from its low molecular weight forms. The platforms disclosed herein provide an innovative tool kit from which to modularly construct a defined, 3D matrix for culture of primary human cells, enabling systematic characterization of how individual features affect tumor features. Such advanced models more accurately model clinical tumors than standard culture models to facilitate develoμment of new, more effective treatments while providing opportunities to functionally screen patient-specific responses to existing treatments for personalized medicine.

[0122] As shown herein, the same scaffold conditions — where both HA content and mechanical properties most closely mimicked native brain — are sufficient to model in vivo- like resistance to pharmacological treatments with broadly distinct mechanisms of action: inhibition of EGFR (erlotinib, lapatinib) or alkylating chemotherapies (temozolomide, carmustine). This finding was consistent across several patient-derived GBM cell lines, regardless of genotype. In the culture platforms, HA concentration is controlled independently of mechanical properties — without altering scaffold permeability, cell viability or proliferation (Figs. 3D-E). While patient-derived gliomaspheres (GSs) were extremely sensitive to EGFR inhibition, those cultured in hydrogels most closely mimicking native brain rapidly acquired both cytotoxic and cytostatic resistance (Fig. 4). 3D cultures of GBM cells established in these hydrogels exhibited resistance kinetics to multiple treatments that best closely matched observations in patient-matched, orthotopic xenografts (Figs. 4D, 1A).

[0123] Brain-mimetic levels of HA and mechanical properties were required — emphasizing the need for orthogonal control of HA concentration and scaffolds mechanics — a major advantage of the platforms described herein. Furthermore, mitigation of HA-CD44 interactions through lentiviral shRNA knockdown of CD44 or reduction of HA content in hydrogels so that CD44 expression is not upregulated compared to GS cultures prevented cytotoxic and delayed cytostatic resistance to EGFR inhibition (Fig. 5). Like clinical GBM tumors, cultures in hydrogels with 0.5 wt% HA maintain high levels of CD44 expression (Fig. 5A). The importance of HA-CD44 interactions in acquisition of treatment resistance in GBM is strongly supported by: 1) a lack of resistance and CD44 expression in both GS and 3D hydrogel cultures with low HA (Fig. 5A) and 2) attenuation of resistance in 3D, high HA hydrogel cultures with shRNA knockdown of CD44 (Figs. 5B,C). Conjugation of integrin-binding RGD peptide into HA-containing hydrogels further amplifies resistance to erlotinib and cooperation of CD44 and integrins enabled GBM cells to transition to an invasive phenotype (Figs. 6A, B). Effects were inhibited by addition of cilengitide to disrupt the integrin engagement to the hydrogel matrix or CD44 shRNA knockdown. It is confirmed that the TE-GS model (0.5% HA, 1 kPa elastic modulus, 280 pM RGD) approximated resistance to EGFR inhibition in GS-DX models in 4 patient-derived lines. Data also indicate that the TE-GS model approximates resistance to alkylating agents (Fig. 7). Data from bulk RNA sequencing (RNAseq) show that gene expression in 3D-cultured cells is more similar to that in patient-matched GS-DXs than in GS cultures (Fig. 8). Further analysis indicates that expression of functional genesets relating to hypoxia and mesenchymal transition — key processes regulating GBM progression — are better preserved in hydrogel cultures. The consistency of these findings across GS lines and treatment types provides a basis for feasibility of the work.

[0124] The components of the matrices described here include:

[0125] Hyaluronic acid (sodium hyaluronate; HA). In some embodiments, the high molecular weight HA has a molecular weight greater than about 500 kDa. In some embodiments the high molecular weight HA has a molecular weight less than about 1,800 kDa. In some embodiments the high molecular weight HA has a molecular weight less than about 1,500 kDa. In some embodiments, the high molecular weight HA has a molecular weight of between about 500 kDa and about 1,500 kDa. In some embodiments, the high molecular weight HA has a molecular weight of between about 500 kDa and about 1,000 kDa. In some embodiments, the high molecular weight HA has a molecular weight of between about 750 kDa and about 1,000 kDa. In some embodiments, the high molecular weight HA has a molecular weight of between about 500 kDa and about 749 kDa. In some embodiments, the high molecular weight HA has a molecular weight of between about 750 kDa and about 1,000 kDa. In some embodiments, the high molecular weight HA has a molecular weight of between about 1,000 kDa and about 1,800 kDa. In some embodiments, the HA has a molecular weight of about 622 kDa. In some embodiments, the HA has a molecular weight of about 670 kDa. In some embodiments, the HA has a molecular weight of about 830 kDa. In some embodiments, the HA has a molecular weight of about 880 kDa. In some embodiments, the HA has a molecular weight of about 1670 kDa. In any of the embodiments herein, the molecular weight may be an average molecular weight. By way of non-limiting example, a high molecular weight hyaluronic acid, for example having a molecular weight average of about 700 kDa and a listed range of 500 kDa - 750 kDa (e.g., about 622 kDa or 670 kDa, supplied by Lifecore Biomedical, Catalog No. HA700K-1) is used in one embodiment. In other examples, Lifecore Biomedical catalog no. HAIM-1 is used, having a molecular weight range of 750 kDa to 1,000 kDa; e.g., 830 kDa or 880 kDa; catalog no. HA15M-1, having a molecular weight of 1,010 kDa to 1,800 kDa (e.g., 1,670 kDa). In some embodiments, a mixture of the aforementioned products is used. The concentration of HA in the matrix as disclosed herein is about 0.25 wt% to about 2 wt%, which are to be varied in screening tumor cells for optimal growth and/or invasion. In some embodiments, about 4% to about 10% of the glucuronic acid moieties on the hyaluronic acid are thiolated. In some embodiments, about 4% to about 6% of glucuronic acid moieties on the hyaluronic acid are thiolated. The degree of thiolation is varied by altering the molar ratios of l-ethyl-3(3- dimethylamino) propyl carbodiimide (EDC), N-hydroxysuccinimide (NHS), and cystamine; see Nakajima N and Ikada Y, Mechanism of amide formation by carbodiimide for bioconjugation in aqueous media, Bioconjugate Chem. 1995, 6, 1, 123-130; Sehgal, D., & Vijay, I. K. (1994). A method for the high efficiency of water-soluble carbodiimide-mediated amidation. Analytical Biochemistry, 218(1), 87-91.

[0126] Thiolation. For a description of thiolation, see, for example, Ehsanipour, A., Nguyen, T., Aboufadel, T., Sathialingam, M., Cox, P., Xiao, W., Walthers, C. M., & Seidlits, S. K. (2019). Injectable, Hyaluronic Acid-Based Scaffolds with Macroporous Architecture for Gene Delivery. Cellular and Molecular Bioengineering, 12(5), 399-413. [0127] Thiolated polyethylene glycol (PEG). Thiolated PEG is an optional component of the matrices described herein. The polyethylene glycol may have multiple arms, such as 4 arms or 8 arms. Inclusion of thiolated PEG modulates the stiffness of the matrix. In any of the embodiments described herein, one or more matrices comprising thiolated PEG, and one or more matrices not comprising thiolated PEG, may be used concurrently in any screening or optimization procedure for example to identify the optimal matrix in which to screen GBM against chemotherapeutic agents.

[0128] A polymer comprising an integrin binding moiety. A polymer such as PEG comprising an integrin-binding moiety is provided in the matrix. In some embodiments the peptide comprises RGD or another integrin-binding peptide such as YGRGDSPG (SEQ ID NO: 10), NGEPRGDTYRAY (SEQ ID NO:2), KGGPQVTRGDVFTMP (SEQ ID NOG), RSTDLPGLKAATHYTITIRGV (SEQ ID NO:4), VFDNFVLK (SEQ ID NOG), ESQEEVVSESRGDNPDPTTSY (SEQ ID NOG), TVDVPDGRGDSLAYG (SEQ ID NO:7), or SVVYGLR (SEQ ID NO:8), by way of non-limiting examples. Such examples of RGD containing or other integrin binding peptides may be incorporated a polymer as described herein using, by way of non-limiting example, an extension of amino acids such as GCG or GGCGGC, which can then be cross-linked using methods described herein. As noted here, the N-terminal extensions comprising one or more cysteines provide a thiol for cross-linking to a polymer as described herein. Such N-terminal extended, integrin-binding peptides thus have one or more N-terminal proximal cysteines available for thiol cross-linking. Non-limiting examples of such extended peptides include GCGYGRGDSPG (SEQ ID NO:1), GCGNGEPRGDTYRAY (SEQ ID NO: 11), GCGKGGPQVTRGDVFTMP (SEQ ID NO: 12), GCGRSTDLPGLKAATHYTITIRGV (SEQ ID NO: 13), GCGVFDNFVLK (SEQ ID NO: 14), GCGESQEEVVSESRGDNPDPTTSY (SEQ ID NO: 15), GCGTVDVPDGRGDSLAYG (SEQ ID NO: 16), GCGSVVYGLR (SEQ ID NO: 17), GGCGGCYGRGDSPG (SEQ ID NO: 18), GGCGGCNGEPRGDTYRAY (SEQ ID NO: 19), GGCGGCKGGPQVTRGDVFTMP (SEQ ID NO:20),

GGCGGCRSTDLPGLKAATHYTITIRGV (SEQ ID NO:21), GGCGGCVFDNFVLK (SEQ ID NO:22), GGCGGCESQEEVVSESRGDNPDPTTSY (SEQ ID NO:23), GGCGGCTVDVPDGRGDSLAYG (SEQ ID NO:24), or GGCGGCSVVYGLR (SEQ ID NO:25). In other embodiments, the peptides are GCGYGRSTDLPGLKAATHYTITIRGV (SEQ ID NO:28), GCGYGGGGNGEPRGDTYRAY (SEQ ID NO:29), GCGYGTVDVPDGRGDSLAYG (SEQ ID NO:30). In these and other embodiments, the integrin-binding moiety is derived from, for example, vitronectin, tenascin-C, integrin-binding sialoprotein, dentin-matrix phosphoprotein, osteopontin, or any combination thereof. Other integrin-binding peptides and proteins containing them are fully embraced herein. See Feng Y., & Mrksich M. (2004). The synergy peptide PHSRN and the adhesion peptide RGD mediate cell adhesion through a common mechanism. Biochemistry, 43(50), 15811-15821.

[0129] The integrin-binding peptide may be included in the matrix at a concentration of about 50 uM to about 280 uM. The degree of decoration of the peptide on the polymer may be modified by adjusting its final molar concentration in the preparation of the hydrogel solution. See for example Xiao W, Zhang R, Sohrabi A, Ehsanipour A, Sun S, Liang J, Walthers C, Ta L, Nathanson DA, Seidlits SK., Brain-mimetic 3D culture platforms allow investigation of cooperative effects of extracellular matrix features on therapeutic resistance in glioblastoma. Cancer Res. 2018; 78(5): 1358-1370. PMCID: PMC5935550.

[0130] Thiol cross-linking. In the matrix, the thiolated hyaluronic acid, the thiolated polyethylene glycol (if included) and the polymer comprising the integrin binding moiety are cross-linked. Such cross-linking may be carried out by a number of means. In one embodiment, the aforementioned components further include maleimide polyethylene glycol or vinyl sulfone polyethylene glycol, wherein the cross-linking occurs by Michael-type addition. In one embodiment, the aforementioned components further include vinyl sulfone polyethylene glycol and a radical generator. In one embodiment, the aforementioned components further include a norbornene-terminated polyethylene glycol and a radical generator. In the embodiments utilizing a radical generator to induce cross-linking, the radical generator may be a photocrosslinker. A non-limiting example of a photo-crosslinker is lithium phenyl-2,4,6- trimethylbenzoylphosphinate. The aforementioned reactions are described in, respectively, Xiao W, Zhang R, Sohrabi A, Ehsanipour A, Sun S, Liang J, Walthers C, Ta L, Nathanson DA, Seidlits SK. Brain-mimetic 3D culture platforms allow investigation of cooperative effects of extracellular matrix features on therapeutic resistance in glioblastoma. Cancer Res. 2018; 78(5): 1358-1370. PMCID: PMC5935550.

[0131] PEG-vinyl sulfone: see Ehsanipour, A., Nguyen, T., Aboufadel, T., Sathialingam, M., Cox, P., Xiao, W., Walthers, C. M., & Seidlits, S. K. (2019). Injectable, Hyaluronic Acid-Based Scaffolds with Macroporous Architecture for Gene Delivery. Cellular and Molecular Bioengineering, 12(5), 399^413. [0132] PEG-Norbornene crosslinking: see Lin, C.-C., Ki, C. S., & Shih, H. (2015). Thiolnorbornene photoclick hydrogels for tissue engineering applications. Journal of Applied Polymer Science, 132(8), 41563.

[0133] Matrix preparation using the aforementioned components. In a non-limiting example, hydrogels are crosslinked via Michael addition between four-arm, maleimide-terminated polyethylene glycol (PEG-Mal, 20 kDa) and thiolated HA (700 kDa, -5% modified) (as shown in Fig. 3A). Integrin-binding peptides such as RGD -containing peptides (-280 pM) are conjugated to hydrogels, such as but not limited to via Michael addition of an N-terminal proximal cysteine group on one or more integrin-binding peptide to PEG-Mal, prior to gelation. This formulation yielded hydrogels that best approximated healthy mammalian brain (-0.5 wt% HA; compressive modulus -1 kPa) (Fig. 3C). See, for example, Xiao W, Zhang R, Sohrabi A, Ehsanipour A, Sun S, Liang J, Walthers C, Ta L, Nathanson DA, Seidlits SK. Brain-mimetic 3D culture platforms allow investigation of cooperative effects of extracellular matrix features on therapeutic resistance in glioblastoma. Cancer Res. 2018; 78(5): 1358-1370. PMCID: PMC5935550.

[0134] Proteolytically degradable peptides. In some matrices, a proteolytically-degradable peptide is included, such as but not limited to GCYKNRGCYKNRCG (plasmin degradable peptide) or GCGYGVPLSLYSGYGCG (MMP9 degradable peptide). The peptide may be included at a concentration of about 200 uM to 800 uM. See Wen, J., Anderson, S. M., Du, J., Yan, M., Wang, J., Shen, M., Lu, Y., & Segura, T. (2011). Controlled protein delivery based on enzyme-responsive nanocapsules. Advanced Materials, 23(39), 4549-4553, and Turk, B. E., Huang, L. L., Piro, E. T., & Cantley, L. C. (2001). Determination of protease cleavage site motifs using mixture-based oriented peptide libraries. Nature Biotechnology, 19(7), 661-667.

[0135] Biomechanical properties. As noted herein, the orthogonal tuning of the matrix components allows for the generation of a variety of matrix properties with minimal variation in components, to identify the optimal conditions for tumor growth and invasiveness in order to evaluate chemotherapeutic agents under conditions that mimic in vivo conditions. Conditions such as porosity, biodegradability and stiffness can be varied by adjusting the concentrations and ratios of the high molecular weight hyaluronic content, presence or absence of thiolated PEG, degree of thiolation of the high molecular weight hyaluronic acid, integrin- binding sites, and the other components described herein. For example, the matrix has a storage modulus between about 50 to about 2000 Pa. In some embodiments the storage modulus is about 100 Pa. Storage modulus is determined by, for example, a rheometer utilizing a parallel plate geometry in the frequency range of .1 to 1 Hz with a 1% strain rate and a 10% uniaxial compression. In another example, the matrix has a pore size of up to about 13 nm. Pore size is determined by, for example, fluorescence recovery after photobleaching with fluorescein modified dextran’s of varying sizes, or size exclusion chromatography followed by multi light angle scattering. These are merely exemplary of the variation in the matrices that can be prepared. See Xiao W, Zhang R, Sohrabi A, Ehsanipour A, Sun S, Liang J, Walthers C, Ta L, Nathanson DA, Seidlits SK. Brain-mimetic 3D culture platforms allow investigation of cooperative effects of extracellular matrix features on therapeutic resistance in glioblastoma. Cancer Res. 2018; 78(5): 1358-1370. PMCID: PMC5935550.

[0136] Detecting tumor growth and invasiveness. Growth of tumor cells can be determined by imaging, biochemical assay, luminescent assay, or assay for a reporter product, by way of nonlimiting examples. Invasiveness of the tumor cells can be determined by imaging, biochemical assay, luminescent assay, or assay for a reporter product, by way of non-limiting examples. For example, one or more visible or fluorescent labeled reagents or reporters can be used to monitor the growth or invasiveness of the tumor cells. Tumor growth kinetics can be determined over time. FASTFUCCI: see Koh, S. B., Mascalchi, P., Rodriguez, E., Lin, Y., Jodrell, D. I., Richards, F. M., & Lyons, S. K. (2017). A quantitative FastFUCCI assay defines cell cycle dynamics at a single-cell level. Journal of Cell Science. .Gaussia luciferase: see Wurdinger, T., Badr, C., Pike, L., de Kleine, R., Weissleder, R., Breakefield, X. O., & Tannous, B. A. (2008). A secreted luciferase for ex vivo monitoring of in vivo processes. Nature Methods. 5(2): 171- 173. Lifeact: see Riedl, J., Crevenna, A. H., Kessenbrock, K., Yu, J. H., Neukirchen, D., Bista, M., Bradke, F., Jenne, D., Holak, T. A., Werb, Z., Sixt, M., & Wedlich-Soldner, R. (2008). Lifeact: A versatile marker to visualize F-actin. Nature Methods. 5(7): 605-607.

[0137] In any of the methods herein described, evaluating tumor cells for growth and/or invasiveness to identify the optimal matrix composition for subsequent chemosensitivity screening may be achieved by any of the methods described herein. In one embodiment, the optimal matrix composition is determined on the tumor cells first, and subsequently such optimal matrix composition is used to screen tumor cells for chemosensitivity to identify a therapeutic regimen.

[0138] In some embodiments, such identifying a matrix composition may be carried out in two or more successive cycles, e.g., initially using a wide range of matrix properties, identifying a maximal tumor growth and/or maximal tumor invasion within the wide range, then preparing a narrower range of matrix properties based on e.g. bracketing the maximal tumor response, identifying within the narrower range the maximal tumor growth and/or maximal tumor invasion, thereby selecting the optimal matrix composition. In some embodiments, further narrowing the range may be carried out to identify the optimal matrix composition for screening. Moreover, in some embodiments, matrix optimization as described herein may be re-performed to identify and maintain optimal conditions for screening, for example, optimal conditions change as tumor cells are propagated, and/or if chemotherapeutic screening conditions change, in order to maximize the therapeutic guidance provided by the methods disclosed herein.

[0139] In some embodiments, an initial range of matrix compositions may be provided for each tumor type, based on prior experience in carrying out the methods disclosed herein, or empirically on a tumor sample. If the tumor is found to exhibit a maximal growth and/or invasiveness within the initial range, a subsequent round of evaluation may be performed expanding the matrix properties within or around that maximal range, to further optimize the growth and/or invasiveness characteristics to identify the optimal matrix composition to evaluate chemosensitivity. In some embodiments, that optimal matrix composition is similar in biomechanical and other properties to that of the tissue type the tumor was obtained from.

[0140] Thus, by way of non- limiting example, a tumor sample is collected from a patient who underwent surgery to resect a glioblastoma, and an optimal chemotherapeutic regimen is sought for the patient for eliminating any remaining tumor in the patient. Tumor is maintained in culture as gliomaspheres. To identify the optimal matrix composition for evaluating chemosensitivity, a range of matrix characteristics, such as varying the thiolated hyaluronic acid (HA) content, varying the matrix stiffness, and varying the porosity, using a range of 0.25% to 2% (stepwise increase by 0.25%) high molecular weight HA with 4% thiolation of glucuronic acids, a range of 10 to 100 mg/ml (stepwise increase by 10 mg/mL) 4-arrn thiolated polyethylene glycol, and cross-linked with integrin-binding peptide GGCGGCSVVYGLR using norbornene-terminated PEG and a photocrosslinker lithium phenyl-2,4,6- trimethylbenzoylphosphinate. At the same time, a range of HA with the same concentrations but at 6% thiolation, and without thiolated polyethylene glycol is evaluated. Wells containing the array of different HA I thiolated PEG and different HA I higher HA thiolation I no thiol- PEG are seeded with tumor cells obtained by disrupting gliomaspheres. Tumor growth and invasiveness are evaluated using methods described elsewhere herein, and the maximal composition of HA content, with or without thiolated PEG is identified in which tumor cells grown and/or invade. Tumor cells are then reevaluated in the same fashion, but with finer gradations, for example, if maximal growth and/or invasion was observed with thiolated-PEG, HA and thiolated-PEG ranges (e.g., 1.0 to 1.25% HA stepwise by 0.05%; 30 to 40 mg/mL thiolated PEG stepwise by 1 mg/mL) are used. After reevaluation, the optimal HA and thiolated PEG content are used for chemosensitivity screening to identify a chemotherapeutic agent or combination, that maximally inhibits tumor growth and/or invasiveness in the optimized matrix. Such chemotherapeutic regimen is then administered to the patient. If further rounds of finer tuning of the matrix is needed to optimize the tumor growth and/or invasiveness conditions, these are performed. The disclosure is not limited as to the number of such cycles, or matrix compositions or ranges of components or properties, for each cycle.

[0141] Resistance. As described herein, one aspect of the invention is to identify potential radiotherapeutic and chemotherapeutic regimens for the tumor before the tumor becomes resistant thereto. In one aspect of the testing of agents on the tumor samples, an increase in the growth of the tumor cells after a certain time indicates develoμment of resistance of the tumor cells to a chemotherapeutic agent after exposure for a certain time. The kinetics of develoμment of resistance can then be used to evaluate effects of a combination of a first chemotherapeutic agent with another one or more second chemotherapeutic agents on the develoμment of resistance. In another aspect, radiation therapeutic regimens may be evaluated using the teaching as described herein. See Xiao W, Zhang R, Sohrabi A, Ehsanipour A, Sun S, Liang J, Walthers C, Ta L, Nathanson DA, Seidlits SK. Brain-mimetic 3D culture platforms allow investigation of cooperative effects of extracellular matrix features on therapeutic resistance in glioblastoma. Cancer Res. 2018; 78(5): 1358-1370.

[0142] Chemotherapeutic agents. Chemotherapeutic agents that can be tested on tumor cells in accordance with the various embodiments herein, including but not limited to agents approved for treatment of the particular tumor (Temozolomide), agents approved for treatment of cancer other than the tumor (Erlotinib), agents approved for compassionate use (ABT-414), agents in clinical trials for treatment of the tumor (Chlorpromazine), agents in clinical trials for treatment of cancer other than the tumor , or any approved or experimental agents used in combination with a chemotherapeutic agent for the tumor or for a cancer other than the tumor (Fluzoparil + Temozolomide). The aforementioned drugs are described in Temozolomide: Huang, J., Liu, F., Liu, Z., Tang, H., Wu, H., Gong, Q., & Chen, J. (2017). Immune checkpoint in glioblastoma: Promising and challenging. In Frontiers in Pharmacology.

[0143] For additional information on erlotinib, see: Ueno, N. T., & Zhang, D. (2011). Targeting EGFR in triple negative breast cancer. Journal of Cancer. 2:324-328. For additional information on ABT414, see NCT03123952. For additional information on chlorpromazine, see NCT04224441. For additional information on Fluzoparil + Temozolomide, see NCT04552977

[0144] Dose Response. To determine sensitivity to a chemotherapeutic agent, a dose-response curve can be performed. In one non-limiting example, dose-response curves are formed from a minimum of 7 points, use a half-log fold dilution covering a 1000-fold concentration range.

[0145] For example, after identifying the optimal matrix for evaluation, a 1000-fold concentration range of 10 approved chemotherapeutic agents alone, in combinations, and a number of experimental agents in clinical trials, are tested on the tumor cells in the optimal matrix. After identifying the chemotherapeutic regimen that maximally inhibits growth and/or invasion, the test may be performed again using finer gradations of agent, or, for a combination of drugs, different ratios of drugs. From this or one or more additional rounds of screening, the recommended chemotherapeutic regimen is provided to the patient’s health care professional.

[0146] The terms “comprise”, "comprises", "comprising", "includes", "including", “having” and their conjugates mean "including but not limited to".

[0147] As used herein, the singular form "a", "an" and "the" include plural references unless the context clearly dictates otherwise. For example, the term "an enzyme" or "at least one enzyme" may include a plurality of enzymes, including mixtures thereof.

[0148] Throughout this application, various embodiments of the present disclosure may be presented in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the invention. Accordingly, the description of a range should be considered to have specifically disclosed all the possible subranges as well as individual numerical values within that range. For example, description of a range such as from 1 to 6 should be considered to have specifically disclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numbers within that range, for example, 1, 2, 3, 4, 5, and 6. This applies regardless of the breadth of the range.

[0149] Whenever a numerical range is indicated herein, it is meant to include any cited numeral (fractional or integral) within the indicated range. The phrases “ranging/ranges between” a first indicate number and a second indicate number and “ranging/ranges from” a first indicate number “to” a second indicate number are used herein interchangeably and are meant to include the first and second indicated numbers and all the fractional and integral numerals therebetween.

[0150] As used herein the term “about” refers to ± 10 %.

[0151] Unless otherwise defined, all technical and/or scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention pertains. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of embodiments of the invention, exemplary methods and/or materials are described below. In case of conflict, the patent specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and are not intended to be necessarily limiting. Each literature reference or other citation referred to herein is incorporated herein by reference in its entirety.

[0152] In the description presented herein, each of the steps of the invention and variations thereof are described. This description is not intended to be limiting and changes in the components, sequence of steps, and other variations would be understood to be within the scope of the present invention.

[0153] It is appreciated that certain features of the invention, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the invention, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable subcombination or as suitable in any other described embodiment of the invention. Certain features described in the context of various embodiments are not to be considered essential features of those embodiments, unless the embodiment is inoperative without those elements.

[0154] Various embodiments and aspects of the present invention as delineated hereinabove and as claimed in the claims section below find experimental support in the following examples. EXAMPLE 1

Clinical Use of Tissue-Engineered Models

[0155] The present example addresses current limitations of genotype-based strategies for personalized medicine by integrating these genotypic data with tissue-engineered models that can accurately predict patient-specific treatment responses. Integration of these strategies will lead to a technological platform in which accurate, patient-tailored predictions can be made within a clinically actionable time frame. In addition, experiments have been designed so that results have potential for near-term clinical impacts through identification of specific ECM- receptor interactions that facilitate both genomic, proteomic and kinomic adaptations that result in treatment resistance.

[0156] Tissue-engineered scaffolds that embody key biochemical and physical features of the brain ECM can predict patient-specific responses to a wide range of candidate treatments at least as well as in vivo GS-DX models. Three experimental models of GBM are evaluated in parallel: 1) GS culture, 2) GS-DX (the current “gold standard” for pre-clinical studies) and 3) 3D cultures of dissociated GSs in hydrogel mimicking brain ECM as tissue-engineered GSs (TE-GSs) (Fig. 2), as described herein. By comparing how cells from a single patient behave in parallel models, experiments generate data that might otherwise be masked by noise from data averaged across a heterogeneous patient population. This approach has potential to uncover new correlations between patient-specific features and treatment response.

Hydrogel Fabrication

[0157] Hydrogels are crosslinked via Michael addition between four-arm, maleimide- terminated polyethylene glycol (PEG-Mal, 20 kDa) and thiolated HA (700 kDa, -5% modified) (Fig. 3A). Integrin-binding RGD peptides (-280 pM) are conjugated to hydrogels, via Michael addition of N-terminal proximal cysteine groups to PEG-Mal, prior to gelation. It is found that this formulation yielded hydrogels that best approximated healthy mammalian brain (-0.5 wt% HA; compressive modulus -1 kPa) (Fig. 3C).

Experimental Models of GBM

[0158] After isolation from patients, GBM cells are first maintained as GS cultures, as previously described. Cells are transduced with lentiviral vectors encoding constitutive expression of Gaussia luciferase (GLuc) and GFP so that cell number can be tracked in either live mice or cultures through bioluminescence imaging (Fig. 2). To establish 3D cultures, dissociated GSs are suspended in RGD-modified PEG and quickly mixed with the HA-thiol to induce gelation (HEPES buffer, pH 7.4, 37°C), which occurs within 5 min. After gelation, cultures are maintained in serum-free medium with bFGF and EGF, as standard for GS. To establish GS-DXs, dissociated GSs are transplanted intracranially into NSG mice.

Evaluating Treatment Resistance

[0159] Patient-derived cell lines will encompass a range of common genotypes in clinical tumors. Treatment responses of cells derived from at least 10 individual patients (Table 1) can be compared in GS-DX, TE-GS and GS models. Treatments will include current clinical standards and promising experimental drugs (Table 2).

Treatment Administration And Schedule

[0160] Treatments will begin 24 hrs after 1) GLuc is detected in blood collected via tail vein for GS-DXs and 2) one doubling (typically <1 wk), as detected by GLuc in culture medium, for GS and TE-GS samples. All drugs (or vehicle controls) will be administered daily via oral gavage, which is standard procedure for treating mice with GBM xenografts with drugs from a number of different classes. Treatments (or vehicle controls) will be added to cultures with replenished medium daily. All GBM models (GS-DX, GS, TE-GS) will be irradiated in a single dose. Radiation will be delivered in a single, focused dose using an image-guided small animal irradiator (SmART, PXI225cx, Precision X-Ray). Rigorous NIST-traceable radiation dosimetry will be performed to facilitate reproducibility and comparability of treatment results.

Treatment Dosing

[0161] Dosing will performed at clinically relevant concentrations and schedules. For drug treatments of GS-DXs, one can apply a widely accepted allometric scaling approach to convert the dosage used in humans to the equivalent dosage in mice. However, in cases where a number of studies have reported effective dosages against human GBM xenografts in mice that vary somewhat from the calculated mouse equivalent dose, one can instead use the reported effective dosages in mice (Table 3). For in vitro culture models (GS, TE-GS), one can construct dose-response curves for each GBM cell line (Table 1) and drug (Table 2) combination. Doseresponse curves will be formed from a minimum of 7 points, use a half-log fold dilution covering a 1000-fold concentration range. To best relate results in mice to those in vitro while maintaining clinical relevance, the Cmax (maximum concentration) of bioavailable drug found in the cerebral spinal fluid (CSF) — estimated from published data of clinical studies in human and preclinical studies in mice — will be evaluated as part of the dose-response curve (Table 4). For radiation treatment of GBM cultures (GS or TE-GS), five-point dose-curves (4, 6, 8, 10, 12 Gy) centered around 8 Gy, which is commonly used as the total dose for human xenografts in immunocompromised mice in preclinical studies, will be constructed. For in vivo studies, radiation will be delivered in a single 10 Gy dose.

Measurements of Sensitivity And Resistance

[0162] After initiation of treatment, tumor cell burden in live cultures and animals will be tracked over time using bioluminescence to provide an approximate measure of resistance that can be directly compared among patient-matched GS, TE-GS and GS-DX models. After addition of coelenterazine substrate, secreted GLuc — collected from tail vein blood or culture media — can be sensitively detected using a luminescence plate reader. Bioluminescence data will be collected from live cultures and mice 1 day before treatment (day 0), after 24 hrs of treatment, then every 48 hrs to capture kinetics of resistance acquisition over the course of 21 days. Based on bioluminescence data, GBM cell (Table 1) and treatment (Table 2) combinations will be designated as “resistant” once at least 3 consecutive measurements show enhanced tumor growth. One could define the first time point where enhanced tumor growth was observed as the time-to-resistance (TTR). In contrast, it is expected that “sensitive” combinations will continually exhibit slower growth rates, especially when compared to vehicle controls. As a parallel metric based on bioluminescence, one can also assess the area- under-the-curve (AUC) on the 6^th day of treatment, where an equivalent or increased AUC of treated samples, compared to untreated controls, indicates resistance while a decreased AUC indicates sensitivity. After 21 days of treatment, GS-DX, GS and TE-GS samples will be fixed and cryo-sectioned. H&E will be performed to identify to evaluate tumor morphology. At least 5 sections from different regions will be stained to assess treatment response and tumor phenotype. Immunohistochemistry (IHC) will be used to evaluate effects of treatment on the presence of proliferating (Ki67+) and apoptotic (TUNEL+) cells and phenotypic characteristics of tumor cells. To minimize the number of animals required, the following assessments of resistance will only be made in culture models. First, IHC, Western blots and targeted RNAseq will be performed on separate samples taken during the experimental time course (days 0, 3, 10 and 21). Second, resistance will be confirmed by assessing proliferation, apoptosis and activation of downstream oncogenic pathways before treatment (i.e., day 0), during initial treatment (i.e., day 3) and after acquisition of resistance (e.g., days 10, 21). Proliferation (EDU+) and apoptosis (c-PARP+, annexin V+) — indicating cytostatic and cytotoxic effects, respectively — will be quantified using flow cytometry and immunofluorescence imaging. Finally, as dose-response curves will be constructed, one can also calculate the IC50 (half maximal inhibitory) or each treatment. A study endpoint of 21 days is chosen based on results (Fig. 1A) demonstrating that even when initially sensitive to treatment, intracranially xenografted, patient-derived GBM cells typically acquire resistance within 20-30 days. Similar resistance kinetics was observed in TE-GSs (Figs. 4, 5B, 7). For example, growth rates (Fig. 1A) and Kaplan-Meier plots (data not shown) of GBM39 xenografts show initial sensitivity to erlotinib that confers an overall survival advantage, even though tumors do acquire resistance after around 20 days. Similarly, GBM39 cells cultured in TE-GSs are initially sensitive to erlotinib treatment for at least 12 days (data not shown), demonstrating the potential of TE- GSs to predict drug sensitivities in vivo within a timeline compatible with personalized medicine.

Statistical Methods

[0163] For GS and TE-GS cultures, all measurements will include a minimum of 4 technical replicates — with cultures established at the same time from the same batch/passage of cells — and 3 independent repeats. Given 9 treatments (8 + vehicle negative control) and 10 GBM cell lines, there will be 90 separate conditions. For bioluminescence, the same cultures will be tracked over time. For GS-DXs, there are 8 mice per experimental group — 720 mice for 10 cell lines x 9 treatment groups. Based on previous studies (Fig. 1A), this should be sufficient to attain at least 80% power with 95% confidence (α < 0.05). From bioluminescence tracking over time, one can evaluate TTR in vivo. Within each model (GS, TE-GS, GS-DX), statistically significant changes over time will be assessed using a one-way ANOVA using the Bonferroni method for post-hoc comparisons.

[0164] The TE-GS model more accurately recapitulates in vivo treatment response than GS cultures. To confirm this, one can regress in 2 assessments of response poorly reproducible. Therefore, for each treatment and experimental model, one can classify cells from each patient as responsive or non-responsive. Using different threshold values, one can establish a receiver operating characteristic (ROC) curve. One can compare the prediction performance here to that observed when randomizing the identities of each clinical tumor. One can then compare the area under the ROC curve for the model and GS culture. Randomization will robustly account for unbalanced representation between resistant and non-resistant classes. In effect, this will allow one to assess if one can predict which among a set of tumors is responsive to a given therapy. [0165] It is anticipated that results will demonstrate the fidelity of ex vivo, TE-GS models of GBM to patient-matched, in vivo GS-DX models, as evaluated by: 1) comparing treatment sensitivity and 2) phenotypic similarity of tumors assessed by IHC and Western blots. While data (Fig. 1, 2, 5, 7) indicate an experimental time course of 21 days — using the 6^th day for evaluation of IC50 and AUC — will be appropriate for combinations of GBM cell lines (Table 1) and treatments (Table 2), one can adjust the time course as needed to best capture the kinetics of acquired resistance for each combination. Given the assumptions made to equate the animal dosages to those used in humans, drug doses in vivo can be adjusted and GS-DX experiments repeated in some cases. Although not expected, if results show that the TE-GS model is not predictive for all treatments and/or individual tumors, one can still obtain useful data about dependence of resistance on specific matrix properties. In particular, results will quantify the relative importance of intrinsic features to tumor cells (e.g., genotype) and extrinsic features in the tumor matrix. For example, a powerful finding might be that resistance to a particular treatment is ECM-dependent in patient cells when specific characteristics are present. In this case, co-therapies targeting matrix interactions (e.g., cilengitide, an integrin-a_v inhibitor used currently for treatment of GBM) may be more effective at preventing resistance to the primary treatment. Or, one may find that specific tumor genotypes can be predicted by the ex vivo platform while others cannot. This result would provide a clear path forward to identify specific patients whom this technology could help. Finally, one can investigate whether genotype (or other patient data) correlates with inconsistencies between TE-GS and GS-DX models. If there are trends, one can tune material properties to identify those that best approximate resistance in vivo for a particular genotype.

TABLE 3

Drug Dosages For Mouse Xenografts Studies

*Daily dosages estimated based on average patient values of 1.62 m² and 60 kg.

**Mouse equivalent dose based on Nair, et al.

***While other cited studies used intracranial GBM xenografts in immunocompromised mice, osimertinib study was performed using immunocompromised mice with brain metastasis from non-small cell lung carcinomas.

TABLE 4

Drug Dosages For Mouse Xenografts Studies

*Data not available in clinical patients. Values shown are for NSG mice with GBM xenografts.

** Data not available in preclinical GBM models. Values shown are for NSG mice with brain metastasis from non-small cell lung carcinomas.

***Wide variations in brain to plasma ratios are reported. An estimate of 40% is used.

****Based on finding that 4.1% brain penetration when 50 mg/kg was given to rats with intact BBB. EXAMPLE 2 Characterize How Specific ECM-Cell Receptor Interactions Directly Affect Acquisition of Resistance

[0166] Figure 13 shows the pathways expected to be perturbed by ECM receptor engagement as tumor cells acquire treatment resistance. Using tissue-engineered, 3D culture scaffolds and high-throughput assays, the present example evaluates how engagement of GBM cell surface receptors by pathologically overexpressed ECM components affects sensitivity and kinetics of acquired resistance through rewiring of downstream oncogenic pathways.

[0167] Findings from standard GBM models have largely failed to translate clinically, thus there is a vital need to implement improved models that better account for the tumor microenvironment. While patient-derived orthotopic xenograft models provide the context of a living organism, their cost, time and reproducibility all present significant disadvantages. Moreover, the complexity of in vivo models makes it challenging to isolate contributions of individual microenvironmental features and, thus, identify potential therapeutic targets. While in vitro models provide a simplified experimental context, standard culture methods omit microenvironmental features that are crucial to preserving tumor cell physiology and thus neglect key mechanisms of resistance.

[0168] To address these limitations, tissue-engineered scaffolds are designed for 3D patient- derived GBM cells as organoid-like structures to mimic brain ECM (Fig. 9). Using these scaffolds, it is demonstrated that ECM is critical for GBM resistance to both targeted therapies, like erlotinib, and alkylating chemotherapies, like Temozolomide (TMZ) (Fig. 10). The scaffold design provides brain-mimetic mechanical properties, HA and RGD peptides, by incorporating a mixture of integrin-binding peptides derived from ECM proteins overexpressed in GBM tumors. Individual and combined effects of each peptide on treatment resistance can be characterized, and both experimental and computational tools can be used to determine the simplest ECM compositions that drive the most resistant phenotypes.

[0169] Tissue-engineered scaffolds can be modularly constructed for 3D culture of patient- derived GBM cells with defined ECM cues. GBM cultures in 3D, ECM-mimetic scaffolds provide more physiologically accurate data than 2D or gliomasphere cultures. For example, it has been reported that, compared to standard gliomaspheres, acquired resistance of GBM cells cultured in tissue-engineered scaffolds better approximates observations in patient-matched xenografts. Tissue-engineered culture scaffolds provide distinct advantages over organoids including: 1) faster time to establish (days vs months) and 2) better control over the microenvironment. Using a bottom-up approach, experiments presented herein aim to develop modular, tissue-engineered models of GBM that can be used to “tease apart” contributions of specific aspects of the tumor microenvironment to cell behavior. The proposed scaffolds embody key features of the tumor ECM, including: 1) integrin-binding peptides to which cells can adhere, 2) a highly hydrated and viscoelastic 3D scaffolding, 3) mechanical properties that can be tuned to approximate those of brain and GBM tissues, and 4) the ability to be degraded by cell-produced enzymes (Fig. 9). The ability to modularly add and subtract cell-instructive cues in these culture scaffolds is essential to the success of the proposed studies, which seek to characterize their individual and combined contributions to cell behavior.

Tissue- Engineered Models Can Preserve Molecular Features Of The Parent Tumors

[0170] Principal Component Analysis (PCA) demonstrated that, compared to cells in gliomasphere cultures, gene expression profiles (generated from RNA sequencing) in those cultured in HA-based scaffolds better approximated patient-matched, orthotopic xenografts in mice. Geneset enrichment analysis (GSEA) revealed that genes whose expression are similar between hydrogel cultures and murine xenografts (PC2) included those relevant to mesenchymal transition, DNA repair and hypoxia — all hallmark characteristics of GBM tumors (Fig. 11). Genes whose expression was more similar between hydrogel and gliomasphere cultures than to xenografts (PCI) included those related to allograft rejection (a possible artifact of xenografting) and immune cells. Furthermore, treatment with TMZ induced larger shifts in expression of genes associated with PC2 in GBM cells cultured in hydrogels than those in patient-matched gliomaspheres (Fig. 11).

[0171] An experimental model of GBM that integrates systems-level, computational predications and measurements of functional responses within tissue-engineered scaffolds is developed to better understand the mechanisms behind ECM-induced resistance in GBM. First, tissue-engineered scaffolds are compatible with moderate-to-high-throughput data collection, which is needed for construction of truly predictive computational models. Second, building a library of scaffolds representing all possible combinations of ECM cues that might have synergistic effects would be impractical as far as labor, expense and current technology. However, by using experimental data acquired from a few rationally designed scaffolds to characterize any synergistic activities between pairs of ECM cues, one may construct a computational model that predicts the effects of more complex microenvironments. While the majority of approaches to personalized cancer treatment have relied solely on a patient’s genetic characteristics, this approach to integrate genetic information with patient-specific functional assessments would better predict treatment response.

[0172] Systems-level analysis of how signaling networks interact, upstream of genomic changes, to induce treatment resistance will be critical in the search for new therapeutic targets and the design of new combination therapies for GBM. While several targeted therapies have been found to be highly effective in preclinical models, they have been largely unsuccessful in clinical trials. It is believed that these failures were at least in part due to inadequate consideration of co-activation/amplification of potentially compensatory pathways. It is found that ECM co-engagement of CD44 and ITGAV synergistically increases Src activation, subsequently suppressing apoptosis and essentially “priming” GBM cells to be insensitive to TMZ (Fig. 10). Furthermore, simultaneous treatment with TMZ and dasatinib, a Src inhibitor, virtually eliminates resistance. These findings emphasize the importance of incorporating a systems level approach to data analysis and interpretation, which will provide opportunities to identify signaling nodes that have predictable, and thus potentially druggable, shifts during acquisition of resistance. In contrast to most studies which focus on changes at the genomic level, the studies presented herein will provide critical information about how the ECM augments resistance of tumor cells to treatment through direct, upstream rewiring of signaling pathways.

[0173] Success of the proposed studies will represent significant strides towards developing tissue-engineered platforms for personalized medicine in GBM that can predict patient outcomes within a clinically actionable time frame. The methods developed for combining 3D, biomimetic scaffolds for cell culture, high-throughput data acquisition and systems-level computational modeling would also have utility for other cancers with high rates of treatment resistance, such as pancreatic cancer.

Experimental Designs

[0174] Tissue-engineered scaffolds will be used to characterize how specific ECM-receptor interactions affect the sensitivity and kinetics of acquired resistance through interactions with cell surface receptors and subsequent rewiring of downstream oncogenic pathways. Patient- derived GBM cells will be cultured as organoid-like “micro-tissues” within 3D scaffolds, in which ECM cues will be varied. At least 6 patient-derived cell lines, representing a range of clinical phenotypes, will be evaluated (Table 5).

[0175] Studies will focus on ECM components and ECM receptors identified as overexpressed in GBM tumors through initial studies — including 1) immunohistochemistry analysis of clinical tissue and 2) whole-transcriptome sequencing of clinical tumors — and an extensive search of the scientific literature (Table 6). Candidate ECM-derived peptides and/or HA will be incorporated into culture scaffolds in combinations of 3 cues at a time. This experimental design will provide critical information about how simultaneous binding to multiple matrix components affects the state of oncogenic signaling networks and how adoption of the matrix- induced state alters response to treatments. For HA, a high molecular weight form will be incorporated to enable native binding of CD44 receptors. For ECM proteins, synthetic peptides containing specific integrin-binding domains will be used (Table 6). Compared to native proteins, peptides are more reproducible, cost effective and compatible with scaffold fabrication chemistries, while maintaining integrin-binding specificity. Negative controls will include scaffolds lacking cell binding sites or with RGD peptides lacking protein- specific amino acids.

[0176] Hydrogel scaffolds will be fabricated from norbornene-terminated polyethylene glycol (PEG) (40 kDa, 8 arm), thiolated PEG (20 kDa, 8-arm) and/or thiolated HA (-700 kDa) (Fig. 9). Integrin-binding peptides (Table 6) will be tethered to scaffolds during photo-gelation via cysteines to achieve a 140 pM concentration of each peptide. Hydrogel precursors will be dispensed into 384-well plates using a solenoid nozzle and microfludic chip with a pressure- driven diaphragm that enables controlled delivery of 100-500 nL volumes. Hydrogels are crosslinked upon exposure to UV light (-365 nm, 4.15 mW/cm², 15 s) and the cytocompatible initiator lithium phenyl-2, 4, 6-trimethylbenzoylphosphinate (0.025% w/v). Single cells will be suspended in hydrogel precursors prior to printing, embedded in 3D scaffolds during crosslinking and cultured in serum-free medium with heparin, FGF2 and EGF.

[0177] GBM patients are typically administered RT, followed by several cycles of treatment with TMZ. To best mimic this protocol, one can administer a single dose of RT (8 Gy) on day 4 of scaffold culture and then begin TMZ treatment on day 6 (3 cycles of 3 days on, then 4 days off). Thus, GBM cells are cultured for 27 days, with treatment during the last 23 days. During “on” days, fresh TMZ (500 pM) will be added to the medium daily. For RT only and no treatment conditions, vehicle (DMSO) will be added instead. Focal RT will be delivered using an image-guided small animal irradiator. One can adjust dosages and time points for measurements, as needed, to ensure that data capture changes as cells acquire resistance and after they have become resistant. Given 6 cell lines, 58 scaffold conditions (56 + 2 controls) and 4 treatment arms, one will have a total of 1392 experimental conditions. 3D culture scaffolds can be adapted for this type of high-throughput data collection by using automated systems for 1) printing hydrogel-encapsulated cells into 384-well plates, and 2) imaging live, 3D-cultured cells. Triplicate repeats of the proposed experiments will require eleven 384- plates. Tumor cell burden in 3D cultures, transduced to produce Gaussia luciferase, can be tracked by bioluminescence measurements in a plate reader. To enable high-throughput monitoring of cytotoxic and cytostatic responses to treatment, cells can be transduced with the FUCCI (Fluorescent Ubiquitination-based Cell Cycle Indicator) reporter, which indicates cells in G1 phase as red and S, G2 or M phases as green with transitioning cells as orange. A high- content, confocal imager can be used to track treatment response in live, 3D cultures. Numbers of live cells and proliferating cells can be quantified from images. Luminescence and fluorescence measurements can begin 24 hrs before treatment (day 3) and continue every 24 hrs for the remainder of the 28-day study.

[0178] Changes in downstream signaling pathways associated with ECM scaffold and treatment conditions can be characterized before (day 3) and at the end (day 27) of treatment using a bead-based, high-throughput ELISA (Luminex xMap) (Fig. 12). One can evaluate 10 scaffold conditions found to be the most resistant and 10 found to be the least resistant for at least 6 cell lines. As many assays are run in parallel, Luminex technology inherently provides internal controls for normalization of expression levels; for example, of cell surfaces receptors to downstream signaling proteins — an advantage that should improve the quality of data used to construct, and thus the accuracy of, the computational model described herein. Luminex assays can be used to capture the simultaneous phosphorylation states of key oncogenic signaling proteins in response to ECM and treatment (Fig. 12, starbursts). Using Western blots and immunostaining, one can also characterize how expression of ECM-binding, cell surface receptors (Table 6) changes 1) when available matrix-binding sites are varied, and 2) with and without treatment.

[0179] For receptors upregulated in the presence of a particular ECM component or as cells acquire resistance, one can characterize their contributions to treatment resistance by repeating the above experiments with 1) shRNA-based knockdowns of receptor expression and/or 2) targeted disruption of receptor binding through blocking antibodies and/or small molecule inhibitors. For integrin receptors, subunits can be knocked down individually. If data indicate that expression of a certain a-subunit correlates with that of a certain P-subunit, then one can repeat experiments with both subunits knocked down. While it is possible that no single receptor knockdown mitigates the protective effects of a particular matrix environment, as other receptors may have redundant or compensatory activities, assessing how expression of other receptors shifts when a single targeted receptor has been knocked down will provide critical information about the compensatory mechanisms of ECM-induced resistance.

[0180] One can investigate the in vivo relevance of ECM-receptor interactions (identified in above) to resistance using patient-derived, orthotopic xenografts established in NOD-SCID gamma null (NSG) mice. Xenografts can be established from a subset of GBM cell lines (at least 2) found in vitro to exhibit the most robust ECM-dependent resistance. Prior to xenografting, one can transduce GBM cells with a lentiviral vector where expression of the candidate ECM receptor found to have the greatest influences on resistance in scaffold cultures is under control of a promoter with a tetracycline -responsive element, TET-OFF. Also, tumor cells can be transduced to overexpress GLuc, which enables assessment of tumor burden by sampling of blood from the tail vein. Once tumors are established, as detected by GLuc in the tail vein blood, doxycycline will be administered continuously for the remainder of experiments to repress receptor expression. Treatment can begin 4 days after GLuc is detected. Tumors can be irradiated in a single dose (8 Gy). TMZ (100 mg/kg) or vehicle (negative control) will be administered via oral gavage starting on the 3^rd day of treatment. TMZ can be administered in 3 cycles (3 days on, 4 days off) for 23 days. Based on previous studies, it is expected that 6 mice per condition will be adequate to compare treated versus untreated tumors. However, xenograft tumors fail to establish around 5-10% of the time. Thus, it is anticipated that 7 mice per condition are required. Kaplan-Meier analysis can be performed to relate knockdown conditions with overall survival (OS) and progression-free survival (PFS).

TABLE 5

TABLE 6

EXAMPLE 3

[0181] Figure 13 depicts genesets associated with GBM progression, assessed through RNA sequencing, are enriched in TE-GS and GS-DX, compared to GS models. Enrichment plots are shown for genesets. When drilling down into these data, it was observed that GBM cells in the TE-GS are phenotypically more similar to GS-DX models than are GS models. In particular, TE-GS better retains in vivo expression of genesets related to cancer progression, including upregulation of TNF-alpha-NF-kB signaling and hypoxia-induced factors.

[0182] Figure 14 depicts GBM39 cells show sensitivity to erlotinib treatment in both TE-GS cultures and murine intracranial xenografts. FIG. 14A) flow cytometry plots showing proliferating cells on day 3 of treatment with erlotinib (1 uM) or vehicle. EDU was added to culture medium for 2 hours, during which time proliferating cells incorporate EDU and can be visualized using flow cytometry. TE-GS cultures have fewer proliferating cells than GS cultures. FIG. 14B) bioluminescence tracking of GBM39 cells in TE-GS cultures over time. Treated cultures (1 uM erlotinib) are normalized to vehicle controls. FIG. 14C) Kaplan- Meier plot showing survival of GS-DX mice with GBM39 when treated with erlotinib (50 mg/kg) or vehicle control. These data confirm that the biomaterial platform is compatible with assessing treatment resistance in a second patient-derived cell line. This was shown for another line, HK301, in Figure 4.

EXAMPLE 4

Comparison of 3D Culture Models of Chemotherapy Resistance Mechanisms In Glioblastoma

[0183] This example examines the cell responses elicited as a result of temozolomide (TMZ) exposure in four different 3D cell culture hydrogels to determine whether they behave as they would in the in vivo GBM tumor microenvironment. GBM cells derived from patient tumors were cultured in two commercially available hydrogel platforms, Matrigel®, a non-covalently crosslinked ECM derived from murine sarcoma, and HyStem™, a thiolated-HA covalently crosslinked to polyethylene glycol diacrylate (PEG), and two HA-based hydrogels fabricated using the Michael-type addition chemistry (MA hydrogels), and thiol-ene photoclick chemistry (Photogels). Table 7 describes the four different 3D culture conditions evaluated in this example. TABLE 7

Descriptions of 3D Culture Conditions

METHODS

CELL CULTURE

Preparation of Cell Culture Media

[0184] To culture the GBM cells, basal media was prepared. The primary GBM media preparation has two steps: 1) preparation of epidermal growth factor (EGF) solution, basic fibroblast growth factor (FGF) solution, and heparin solution, which are then combined to create the “HEF” solution and 2) preparation of the GBM primary media.

[0185] To prepare the HEF solution, the EGF solution was first prepared by dissolving 1 mg/mL of Animal-Free Recombinant Human EGF (PeproTech AF-100-15) in 0.1% Bovine Serum Albumin (BSA) (Bioworld 22070008-1) in Phosphate-Buffered Saline (PBS) to create a primary solution. 100 mg/mL of this primary solution was added to Dulbecco's Modified Eagle Medium/Nutrient Mixture F-12 (DMEM-F12) (Thermo Fisher Scientific 11330057) to create the secondary solution. The FGF solution was prepared by creating a primary solution of 1 mg/mE of Recombinant Human FGF-basic (154 a.a.) (PeproTech 100-18B) in 0.1% BSA- PBS, and then adding 25 ug/mL of the primary solution to DMEM-F12 media to create the secondary solution. The Heparin solution was prepared by dissolving 5 mg/mL of Heparin sodium salt from porcine intestinal mucosa (Sigma- Aldrich H3149-100KU) in DMEM-F12. These solutions are combined in the following amount to create HEF (400X): 5 mL EGF, 8 mL FGF, 10 mL Heparin, and 2 mL DMEM-F12. 1.25 mL aliquots of HEF are stored in -20 C until ready to be used. To prepare 500 mL of media, 12.25 mL of DMEM-F12 was removed from the bottle, and replaced with one 1.25 mL aliquot of HEF, one 10 mL aliquot of Gem21 NeuroPlex™ Serum- Free Supplement (Gemini Bio-Products 400-160), and one 1 mL vial of Normocin (Invivogen ant-nr-2). The primary GBM media was thoroughly mixed, aliquoted, and frozen in -20o C until use.

Patient-Derived Cells and Maintenance of Cell Culture

[0186] Glioblastoma cells derived from patients were kindly provided by Dr. David Nathanson at UCLA. Two different cell lines were used, the GS054 cell line, which has methylated MGMT promoter regions, and GS025 line, which is MGMT unmethylated. The GS054 cells were used between passages 14 and 20. The GS025 cells were used between passages 4 and 6 or 19 and 20. Both cell lines were cultured in suspension in primary GBM media, seeded into T75 tissue culture treated flasks with vented caps (Genesee Scientific 25-209) at a density of 100,000 cells/mL, and maintained in an incubator (37 °C 5% CO2 95% humidity). Medium was added to the flasks every three days and the cells were passaged every 7 days or when they reached 80% confluency.

[0187] To passage the GBM cells, the media from the flask was transferred to a 50 mL conical tube and spun down in a centrifuge at 400 x g, 9 acceleration, 7 deceleration, and 22° C for 5 minutes. The supernatant was aspirated carefully to make sure the pellet of cells was not disturbed, and the pellet was then resuspended in 1 mL of accutase (Fisher Scientific NC9464543). The conical tube was placed in an incubator for 4-5 minutes. Then, 4 mL of media were added to stop the reaction and the solution was triturated a few times until the cells are seen floating. Another 50 mL conical tube was obtained with a cell strainer (CELLTREAT 229481) attached. The cell strainer was washed with 1 mL of media, the cell solution was strained to obtain single cells, and the strainer was washed with 1 mL of media again. The conical tube was spun again according to the same parameters, the supernatant was aspirated, and then the pellet was resuspended in 5 mL of media. The cell solution was combined at 1 : 1 ratio with Trypan Blue solution (Sigma- Aldrich T8154) to count viable cells using a hemocytometer. The cell solution representing the appropriate volume was added to a flask or a 15 mL conical tube in preparation for encapsulation.

HYDROGEL FABRICATION

HyStem Hydrogels

[0188] HyStem® Cell Culture Scaffold Kits (Sigma- Aldrich HYS020-1KT) include Gly cosil® (thiolated hyaluronic acid), Extralink- Lite® (polyethylene glycol diacrylate), and DG (degassed and deionized) water. In preparation for HyStem® encapsulation, the components, which are usually stored in -20° C, were allowed to thaw for one hour at room temperature. A syringe and a needle were used to reconstitute Glycosil® and Extralink-Lite® with 1 mL and 0.5 mL of degassed water, respectively. Once the water was added to the components, they were vortexed for a few seconds, and then left on a shaker for 1 hour to ensure that they were completely dissolved. Once the components dissolved, Glycosil® was used to resuspend the cell pellet with the appropriate number of cells (50,000 cells/30 pL HyStem® hydrogel). Extralink- Lite® was then mixed with the Glycosil®-cell solution at a ratio of 1:4. To ensure that the cells were properly distributed within the HyStem® solution, the mixture was triturated multiple times. Next, a pipette was used to dispense 30 pL of HyStem® into each well. Once gelation had completed after 1 hour, media was carefully added to the well to ensure the hydrogel was not disturbed.

Matrigel

[0189] Coming™ Matrigel™ hESC-Qualified Matrix (Fisher Scientific 08774552) was purchased, aliquoted at 250 pL, and stored in -20°C. To prepare for hydrogel formation, Matrigel aliquots were thawed and kept on ice since they gel above 10°C. Furthermore, 200 pL wide-bore pipette tips and GBM primary media were chilled to prevent premature gelation of Matrigel™ when being dispensed. The cell pellet with the appropriate number of cells was resuspended in chilled GBM primary media. 800 pL of GBM primary media with resuspended cells was added to each aliquot of Matrigel™, resulting in the appropriate volume for 35 hydrogels (30 pL/hydrogel). Thirty pL of Matrigel™ solution was quickly dispensed into each well to form circular, 3D hydrogels. The well-plate was then placed in the incubator for 45 minutes to ensure full gelation before media was added to the wells. Thiolation of HA

[0190] To be used in the fabrication of the hydrogels, the HA was modified with thiol groups, conjugated to about 5% of the repeating disaccharides, via the carboxylate groups on the HA polymer to create thiolated-HA. HA (700 kDa, LifeCore Biomedical) was allowed to fully dissolve at 10 mg/mL in distilled, deionized water. The pH of the HA solution was adjusted to 5.5 using 0.1 M hydrochloric acid (HC1). l-ethyl-3-[3- dimethylaminopropyl] carbodiimide (EDC) at 0.25x molar ratio and N-hydroxysuccinimide (NHS) at 0.13x molar ratio were added to the solution, and the solution was stirred for 45 minutes, while adjusting the pH to 5.5 using 0.1 M HC1. Next, 0.25x molar ratio cystamine dihydrochloride (Sigma- Aldrich, St. Louis, MO USA) was added into the reaction solution, the pH was adjusted to 6.5, and the reaction was allowed to incubate overnight while being stirred. The next day, the pH was adjusted to 8, 4x molar ratio of dithiothreitol (DTT) (Sigma- Aldrich) was added to cleave the cleave cystamine disulfides and yield thiolated HA, and the pH was adjusted to 8 once again. The solution was left to stir for 2 hours. The reaction was quenched by adjusting the pH of the solution to 4. The solution was dialyzed (MWCO 14 kDa, regenerated cellulose, ThermoFisher Scientific) against diH2O (pH 4, 1 M NaCl) for 3 days. The HA was filtered through 0.22 pM filters, lyophilized, and stored at 20°C. HA thiolation percentage was determined using H-NMR spectroscopy and an Ellman’s assay for free thiols.

Michael-Type Addition Reaction Hydrogels

[0191] Thiolated-HA, with an average molecular weight of 700 kDa, was dissolved at 15 mg/mL in 20 mM HEPES in Hanks' Balanced Salt Solution (HBSS), pH 7.0. The HA-SH was placed in a capped, brown vial with a small magnetic stir bar, and then was allowed to dissolve in the HEPES buffer on a magnetic stir plate for 1 hour at RT. While the HA-SH dissolved, solutions were prepared based on the thiolation percentage of the HA-SH so that each resulting gel would have 1) 5 mg of HA/gel (0.5% w/v), the ideal concentration for GBM cell migration and proliferation, 2) a ratio of thiol groups on the HA-SH and PEG-SH to PEG-maleimide of 1 : 1.2 to ensure that the PEG-maleimide and the thiol groups completely crosslink, and 3) and a final RGD concentration of 250 pM.

[0192] The hydrogel precursor solution was prepared in two steps: Solution A and Solution B (Fig. 15). Solution A, the crosslinker solution, constituted of 4-arm PEG-maleimide, with a molecular weight of 20kDa, (Laysan Bio, 4arm-PEG-MAL-20K-lg) dissolved in 20 mM HEPES in HBSS (pH 7.0) at 100 mg/mL, 4 mM RGD-SH (GenScript, SC1848), and 20 mM HEPES in HBSS (pH 7.0) so that the RGD was conjugated to about 13% of the maleimide groups on the PEG-maleimide. The solution was thoroughly mixed in a 2 mL centrifuge tube, the tube was placed in a bead bath (37°C) for 20 minutes to ensure full conjugation with RGD, and then placed on ice until use. After the HA-SH finished dissolving, the pH was adjusted to 6.5-7 using pH strips and IM sodium hydroxide (NaOH). Solution B, the HA-SH solution, was prepared by combining 4-arrn PEG-SH, with a molecular weight of 20kDa, (Laysan Bio, 4arm- PEG-SH-20K-lg) dissolved in 20 rnM HEPES in HBSS (pH 7.0) at 100 mg/mL, the dissolved HA-SH, and 20 rnM HEPES in HBSS (pH 7.0). The solution was placed on ice until use.

[0193] Once the solutions were prepared, the cell pellet with the appropriate number of cells was resuspended in Solution A. Because gelation occurs quickly upon mixing of the two solutions, the hydrogels were fabricated on ice to slow down the reaction. Thirty pL silicone molds, which were stored in 70% ethanol, were dried, and placed on a sterile microscope glass slide. To ensure that the molds were securely in place, the back of a 1000 pL pipette tip was used to press down on the silicone. Solution B is more viscous due to the HA-SH solution, so 15 pL of the solution was dispensed into each mold first. Next, a positive displacement pipette was used to dispense the remaining 15 pL of Solution A into each mold. Solution A and B were mixed thoroughly by quickly triturating 3-4 times. The glass slide with the silicone molds was then placed in a petri dish and placed in an incubator for 20 minutes to allow for complete gelation. The silicone mold was then carefully removed from the slide, and each gel was gently placed in a well with 100 pL of media using a small spatula.

Photo-Crosslinked Hydrogels

[0194] HA-SH preparation was done as described for the Michael-type addition gels. The hydrogel solution was prepared by combining the dissolved HA-SH (0.5% w/v), 4-arm PEG- SH, with a molecular weight of 20kDa, (Laysan Bio, 4arm- PEG-SH- 20 K-lg) and 8-arm PEG- norbornene (JenKem Technologies, A10037-1) dissolved in 20 mM HEPES in HBSS (pH 7.0) at 100 mg/mL, 0.025% w/v lithium phenyl-2,4,6 trimethylbenzoylphosphinate, abbreviated as LAP, (Sigma- Aldrich, 900889-1G), and 250 pM of 4 mM RGD-SH (GenScript, SC1848) (Fig. 16). Like the Michael-type addition gels, 30 pL silicone molds were dried, and multiple molds were placed on a sterile microscope glass slide. The hydrogel precursor solution was dispensed into the silicone molds, and the glass slide with the silicone molds was exposed to long-wave UV (365 nm, 4.2 mW/cm2) (Blak-RayTM B-100A UV lamp, UVPTM) for 15 seconds to form multiple hydrogels at a time. The silicone molds were carefully removed so the gels remained on the glass slide, and the gels were placed into the well-plate using a small spatula.

DRUG TREATMENT

[0195] Experimental groups were treated with the drug, TMZ (Sigma-Aldrich, T2577-25MG), on Days 3, 4, 5 and 9, 10, 11, using IC50 values that were determined for each cell line. Stock solution for TMZ was prepared at 100 mM in DMSO. The GS54 cell line was treated with 166.2 pM of TMZ, while the GS25 cell line was treated with 44.96 pM of TMZ. The control (non-treated) groups were exposed to 0.1% DMSO.

EXPERIMENTAL SETUP

[0196] For each experimental repeat, the plate was set up as shown in Fig. 17. Tissue-cultured 96-well plates (CELLTREAT, 229195) were used, with 10 samples per condition. All conditions were seeded at a density of 50,000 cells, where the cells were encapsulated in the hydrogels and the gliomaspheres were resuspended in 100 pL of media per well. Five samples per condition were the “control” group, and were treated with DMSO, while the remaining samples per condition were the “experimental” group and treated with TMZ. As a result, there were 50 samples per plate, with 40 samples of different gel conditions and 10 samples of gliomaspheres suspended in 100 pL of media. One hundred pL of GBM primary media was also added to each well with a gel sample, while 100 pL of PBS was added to the wells on the sides of the plate to prevent edge effects. Five 96-well plates were prepared per experiment, where one plate was evaluated for cell proliferation at each time point. Experimental time points were as followed: Day 1 (day of encapsulation), Day 3 (beginning of treatments), Day 6 (end of treatments), Day 9 (beginning of treatments), and Day 12 (end of experiment). Therefore, cell proliferation of the different conditions was evaluated on the day of encapsulation, prior to the first round of treatments, at the end of the first cycle of treatments, prior to the second round of treatments, and the end of the experiment, after the end of the second round of treatments.

INTEGRIN AND EZRIN INHIBITION

[0197] To determine whether GBM cell-ECM interactions affected resistance to TMZ treatment, a knockout experiment was also conducted. Experimental setup of the 96-well plate was like the previously described encapsulation experiment with different columns for the control and treated groups for each condition. However, conditions were also treated with Cilengitide (Sigma Aldrich, SML1594-5MG), color coded green, to inhibit RGD-integrin binding and with Ezrin inhibitor, NSC668394 (Sigma Aldrich, 341216-10MG), color coded purple, to interfere with GBM cell-HA interactions (Fig. 18). In this experiment, the control and experimental groups for each condition were compared to the control + cilengitide, control + ezrin inhibitor, TMZ treated + cilengitide, and TMZ treated + ezrin inhibitor. TMZ treatment was administered in the same 12-day cycle as described previously. However, cell viability was only evaluated before the start of the treatment cycle (day 3) and at the end of the experiment (day 12). Stock solutions for both Cilengitide and the ezrin inhibitor were prepared at 5 mM in DMSO. Conditions were treated with 10 pM of Cilengitide and 1 pM of the Ezrin inhibitor to ensure that inhibition could be studied without hindering migration or leading to cell death.

QUANTITATIVE EVALUATION

Cell Proliferation

[0198] Cell Counting Kit 8 (WST-8/CCK8) (Abeam) was used to quantify proliferation by determining the number of viable cells. Proliferation was evaluated on the different timepoints, where 10 pL (10% of the media in each well) of the CCK-8 reagent was added directly to the cell media in each well using a Repeater® M4 Multi-Dispenser Pipette (Eppendorf). The plate was placed back in an incubator with 5% CO2 for 5 hours at 37°C and then the absorbance was measured using a multifunction microplate reader (Synergy Hl Hybrid Reader, BioTek Instruments) at 450 nm and the Gen5 microplate reader software.

Statistical Analysis

[0199] For the CCK8 data, all data points were normalized by dividing by the day 1 average for each condition and treatment. For example, for the GS54 encapsulations, the day 3, 6, 9, and 12 data for the control groups for the gliomasphere condition were normalized to the average of the day 1 gliomasphere control group. The error bars on the graphs represent standard error of the mean, incorporating standard deviation from the three independent biological repeats of the encapsulation experiments. Statistical analysis was performed using GraphPad Prism 9. Three-way Analysis of Variance (ANOVA) was used to compare all the conditions of both the different cell lines on each timepoint day, and to compare before and after treatment for all conditions, for each cell line separately. Two-way ANOVA was performed to compare the control and treated groups for all culture conditions on one timepoint day, for each cell line separately, and to compare the control and treated groups at all timepoints, for each culture condition. A Bonferroni post-hoc test was performed after ANOVA for all the different comparisons to determine any statistical significance between cell lines, conditions, days, and groups. The p-value was set to 0.05, where any comparison with a p-value under 0.05 meant that the null hypothesis was rejected, and therefore, there were significant differences observed.

QUALITATIVE EVALUATION

Imaging

[0200] All conditions were imaged on a Zeiss Axio-Observer microscope, using the Zen software, at each timepoint (days 1, 3, 6, 9, 12). Fluorescence (green fluorescence protein (eGFP) and phase contrast images were acquired of 3D hydrogel and gliomasphere cultures at lOx magnification.

Cryopreservation and Sectioning of Hydrogels

[0201] On days 3 (before administration of treatment) and 12 of the end of the experiment, all cultures were fixed with 200 mL of 4% paraformaldehyde (PF A), the plate was wrapped with Parafilm, and was allowed to incubate at 4°C overnight. The PFA was then aspirated and incubated in 200 mL of 5% sucrose dissolved in PBS for one hour at room temperature. One hundred mL of the 5% sucrose in PBS was replaced with 100 mL of 20% sucrose dissolved in PBS and was incubated at room temperature for 30 minutes. This was done twice, and the solution was aspirated and replaced with 200 mL of 20% sucrose dissolved in PBS, the plate was wrapped with Parafilm, and allowed to incubate at 4°C overnight. The next day, 20% sucrose in Tissue-Plus™ Optical Cutting Temperature (OCT) Compound (Fisher Scientific 23- 730-571) was used to embed the hydrogels in disposable embedding molds, and then were flash frozen in 2-methyl -butane and dry ice. The samples were placed in -80°C until they were ready to be sectioned. 18 μm thick sections were cut on a cryostat (Leica Microsystems) and mounted onto positively charged microscope slides. The slides were stored at -20° C until they were ready to be imaged.

Immunostaining

[0202] Immunostaining was performed on cryosectioned hydrogels on day 3 and day 12. Sections were immunostained for cleaved PARP (cP ARP), Ki67, and CD44 to evaluate cell apoptosis and proliferation, as well as markers that are associated with invasive tumor growth.

[0203] To begin immunostaining, the hydrogel sections were left out to dry at room temperature for 20 minutes. Next, sections were fixed with 4% PFA using silicone isolators for 12 minutes. Following fixation, the sections were washed (3 x 5 minutes) in IX Tris-buffered saline (TBS) using slide holders (Fisher Scientific 501899558). The slides were then permeabilized for 15 minutes using 0.5% Triton in IX Tris. Blocking solution was prepared using a mixture of 10% Normal Donkey Serum (Sigma- Aldrich D9663) and 5% Bovine Serum Albumin (Spectrum Chemical 22070008) in IX Tris-buffered saline with 0.1% Tween® 20 Detergent (TBST). The blocking solution was added to each slide, the slides were covered with silicone isolators, and allowed to rest at room temperature for 1 hour. Primary antibody solutions were prepared by adding the primary antibody of choice to blocking solution, according to the dilution factors listed in Table 2. Slides were then placed in slide boxed and placed in 4° C overnight. The next day, the slides were washed (3 x 5 min) in IX TBST using the slide holders. Fluorescent secondary antibody solution was prepared by adding the secondary antibody in blocking buffer, according to desired dilution factors. The secondary antibody solution was added to the slides, they were covered with silicone isolators, and left in room temperature for 1 hour. Next, the slides were rinsed again (3 x 5 min) in IX TBST using the slide holders. To counterstain, Hoechst 33342 was added to IX TBST at a 1:1000 dilution, and then the solution was added to the slides for 2 minutes. The slides were washed for 3 minutes using deionized water. Fluoromount G (Southern Biotech, Fisher Scientific OB 100- 01) was added to the slides, they were mounted with coverslips, and left to rest for 30 minutes. Once the slides dried, the edges were sealed with clear nail polish to ensure the coverslips stayed fixed to the slides. The slides were stored at 4° C until images were taken. The sections were imaged using a Zeiss Axio-Observer microscope (20x magnification).

RESULTS

Morphology

[0204] Phase and fluorescence images were acquired at each timepoint to visualize and qualitatively assess any similarities and differences across the control and treated groups, culture/scaffold conditions, and the two patient-derived GBM cell lines. Both cell lines were modified to express green fluorescent protein (GFP), which fluoresces when exposed to blue light and allows the living GBM cells to be visualized.

[0205] Spheroids cultured in suspension (no hydrogel) progressed from single cells at the time of seeding to spheres during the 12-day experiment. For the GS54 line, cells formed small spheres by day 3, which grew larger on subsequent days, indicating proliferation over time (Fig. 19). While the spheres for the control groups were nearly perfectly circular, the treated groups showed more irregularity in the shape of the spheres. This variation may be attributed to TMZ treatment-induced cell death, which resulted in single cells breaking away from the spheres. For the GS25 line, similar behavior was observed on day 3, where the cells proliferated and/or migrated towards each to form spheres (Fig. 20). While the GS54 cells arranged themselves as spheres, the GS25 cells appeared to form irregularly shaped clusters (observed on days 6, 9, and 12) for both the control and treated groups. As GBM tumors are highly heterogeneous, with both inter- and intratumoral cellular and histopathological heterogeneity, the variability between cells derived from different patients is expected to reflect clinical heterogeneity. One such molecular biomarker that distinguishes the cell lines is their MGMT methylation status, which influences their response to TMZ in clinical cases. The GS54 cells are MGMT unmethylated, and are expected to be unresponsive to TMZ, while the GS25 cells are MGMT methylated and are expected to show increased sensitivity to chemotherapeutics. By day 12, the control group for the GS54 cells formed multiple large spheroids, while GS25 cells had relatively smaller clusters. This observation indicates more cell proliferation and overall viable cells in the GS54 gliomaspheres.

[0206] As with suspension cultures, images of the Michael-type addition chemistry hydrogels (MA hydrogels), for both the GS54 and GS25 cell lines, had single cells on day 1 (Figs. 21- 22). However, the cells were not homogeneously spread throughout the hydrogel. This could be attributed to the fast reaction kinetics of the Michael-type addition chemistry, where the hydrogel begins to immediately crosslink upon mixture of the hydrogel solutions, resulting in relatively heterogeneous cell encapsulation. By day 6 for the GS54 cells and day 9 for the GS25 cells, cells had started to form small, irregularly shaped clusters. By day 12, the clusters appear larger in the control groups compared to the treated groups. Additionally, more cells at day 12 groups were present in the GS54 cultures, compared to the GS25 cultures.

[0207] Compared to the MA hydrogel conditions, the spatiotemporal control provided by photocrosslinking led to a more even distribution of cells after encapsulation into photogels on day 1 (Figs. 23-24). In both cell lines with or without treatment, cells predominantly remained as single cells throughout the 12-day experimental time course. Furthermore, visual observations support CCK8 viability assay data, which is discussed below, showing that cells did not proliferate much, or at least that proliferation balanced cell death, throughout the experiment.

[0208] On day 1, cells encapsulated in HyStem (Figs. 25-26) also start as single cells dispersed throughout the hydrogel, as expected. While the cells in the MA hydrogels formed clusters and were heterogeneously spread throughout the hydrogel, the single cells in the HyStem were uniformly distributed, similar to the photogels. However, the number of cells on the subsequent days dramatically decreased, even in the control groups, with the GS25 cells having a greater decrease in numbers compared to the GS54 cells. No noticeable differences were seen between the control and treated groups for either cell line.

[0209] Similar to the other culture conditions, cells in the Matrigel hydrogels started off as round, single cells on day 1 (Figs. 27-28). However, by day 3 both cells from both lines spread out and become elongated in shape. Matrigel contains multiple oncogenic growth factors, such as transforming growth factor beta (TGF-beta), epidermal growth factor (EGF), which may enhance the invasive potential of the GBM cells. Over the 12-day experiment, GS54 and GS25 cells proliferated in both control and treated groups. Furthermore, as observed with other conditions, the GS54 cells appeared to proliferate more than the GS25 cells.

Viability

[0210] As the experimental setup consisted of multiple scaffold conditions, two cell lines, control and treatment groups, and assessment over several days, several comparisons can be made. First, GBM cell proliferation was assessed across scaffold conditions. Next, effects of the TMZ treatment on GBM cells in each scaffold condition were compared at each timepoint. Effects of the treatment over time were also compared across scaffold conditions. Finally, the two patient-derived GBM cell lines were compared to determine whether MGMT methylation status affected the TMZ response observed in all culture conditions, as expected from clinical observations.

[0211] At each time point (days 3, 6, 9 and 12), cell viability was analyzed using a CCK8 colorimetric assay. To account for variation in absolute absorbance measurements in the plate reader instrument day-to-day and any small variations in initial seeding densities, absorbance values at days 3, 6, 9 and 12 were each normalized to their day 1 values for each condition and treatment group. As a result, the baseline for measurement on day 1 was 1, and for observed values after day 1, a value of greater than 1 indicates cell proliferation and values less than 1 indicates cell death.

Comparisons of Culture Conditions

[0212] Control groups for each condition were compared to determine effects of culture condition on cell viability without treatment over 12 days (Figs. 29 and 30 for the GS54 and GS25 cell line, respectively).

[0213] As gliomaspheres, GS54 cells showed no net proliferation between day 1 and day 6. By day 9, there was about a 50% increase in proliferation, and then cell viability remains unchanged at day 12. Statistical analysis found significant differences in viability only between day 1 and day 12 and day 3 and day 12 (Table 8). Similarly, the GS25 gliomaspheres had very little to no net proliferation between day 1 and day 9; however, they experienced a decrease in cell viability between days 9 and 12 (Table 9). One explanation for this slow proliferation may be the size of the gliomaspheres, which could be too large for nutrients to diffusion into the sphere interior. Cells in vivo require active transport of blood at least 100-200 μm away from them to supply them with nutrients and oxygen. Similarly, gliomaspheres that are larger than 200 μm would prevent cells further from the edge of the sphere from receiving any nutrients. Figure 19 and Figure 20 show that spheres grow larger than 200 μm for both GS54 and GS25 gliomaspheres, indicating that there was limited diffusion of nutrients to cells, and reduced cell proliferation as a result. At day 3, GS54 gliomaspheres exhibited similar cell viability as when cultured in the MA hydrogel or HyStem cultures, but significantly less than the photogel or Matrigel cultures. While gliomaspheres remained significantly different from the Matrigel cultures over the 12-day experiment, there were no statistically significant differences between GS54 gliomaspheres and photogels or MA hydrogels after day 3 (Table 10). However, gliomaspheres were significantly more viable than the cells in HyStem after day 6. In contrast, the GS25 gliomaspheres had significantly less viability than all other culture conditions on all timepoints, expect when compared to the HyStem cultures (Fig. 30, Table 11).

[0214] The GS54 cells in the MA hydrogels appeared to proliferate slowly, but consistently over time, with the largest increase in proliferation occurring from day 9 to day 12 (Fig. 29). This result is reflected in statistical differences observed between each earlier timepoint compared to day 12, which had the greatest cell viability (Table 8). Meanwhile, the GS25 cells in the MA hydrogels were statistically different between day 1 and 3, during which time they experienced a net proliferation before remaining steady, with no significant differences when comparing any other days (Table 9). This result suggests that cell death and cell proliferation occurred at the same rate, perhaps because cells experienced confluency and or contact inhibition in the hydrogels. The images of the GS25 cells in MA hydrogels taken on timepoint days (Fig. 22) show a slight increase in cell viability from day 3 to day 6, and similar cell viability on day 9 and day 12, which support the data shown in Fig. 30. At day 3, GS54 cells in the MA hydrogels exhibited similar cell viability as the gliomaspheres, significantly greater viability than the GS54 cells in HyStem, and much less cell viability than the GS54 cells in photogels or Matrigel. These trends largely continued over the 12-day experiment, with the exception that there were no significant differences between MA hydrogels and photogels after day 3 (Table 8). GS25 cells showed similar results, having significantly more viability than gliomasphere and HyStem cultures, equivalent viability to photogel cultures, and significantly less viability than Matrigel cultures at most time points (Table 9). However, GS25 cells in MA hydrogels were more similar to Matrigel at day 12, as Matrigel cultures lost cell viability between days 9 and 12 (Fig. 30, Table 11).

[0215] GS54 and GS25 cells cultured in photogels significantly increased their net cell viability from day 1 to day 3 (Figs. 29-30). GS54 cell viability remained steady for the remainder of the experiment, with no statistical differences between any timepoint pairs after day 1 (Table 8). Cell viability for the GS25 cells slightly decreased on day 6, and then increased again on day 9, summing to a non-significant net cell proliferation from day 3 to day 9 (Table 9). This steady response in cell viability may be because cells in the photogel conditions used up culture media faster than cells cultured in other conditions, which resulted in decreased amount of nutrients available to promote cell proliferation. For both GS54, this initial proliferation led to significantly greater cell viability than all other conditions at day 3, with the exception of Matrigel (Table 10). After day 3, significant differences between photogel and HyStem conditions remained, but were lost between photogels and MA hydrogels, and between photogels and the gliomasphere condition (Table 10). Despite their similarity at day 3, photogel culture viability significantly lagged behind that in Matrigel for the remainder of the 12-day culture period. GS25 cells exhibited similar behavior to GS54, with statistically similar viability as MA hydrogels, significantly higher viability than HyStem, and significantly less viability than Matrigel, cultures at most time points (Fig. 30, Table 11). However, GS25 cells in photogels were also statistically different from the gliomaspheres at all timepoints, unlike with the GS54 cells.

[0216] Both GS54 and GS25 cells in HyStem had a 50% decrease in cell viability between day 1 and day 3, which resulted in statistical differences between day 1 and every subsequent timepoint (Table 8 and Table 9). For the GS54 cells, cell viability remained steady after day 3, with significantly less viability compared to all other conditions at most time points (Table 8, Fig. 29). Meanwhile, cell viability for GS25 continued to significantly decrease from day 3 to day 6, and then stayed steady (Table 9, Fig. 30).

[0217] The cell viability for both GS54 and GS25 cells in Matrigel doubled from day 1 to day 3, and then continued to proliferate until day 9, likely from presence of growth factor mitogens in the Matrigel (Figs. 29-30). However, cell viability decreased from day 9 to day 12 to the amount present on day 6 of each cell line. As a result, there were no significant differences in cell viability between day 6 and day 12 (Table 8 and Table 9). Expect for a few individual comparisons discussed above, GS25 or GS54 cells in Matrigel conditions had significantly more cell viability than all other culture conditions at all timepoints (Table 10 and Table 11).

62

SUBSTITUTE SHEET ( RULE 26)

[0218] In general, it was concluded that the HyStem hydrogels are ineffective in their ability to support cultures of patient-derived GBM cells, as cells do not readily proliferate in these scaffolds. In contrast, Matrigel cultures proliferated robustly up until 9 days. This initial increase in cell viability in the Matrigel condition might be attributed to Matrigel composition, which is ECM, such as laminin, collagen IV, and heparan sulfate proteoglycan, and growth factors, such as EGF. GBM cell interactions with laminin, has proven to increase cell survival and invasion. Expression of multiple integrins is upregulated in GBM, and the interaction between these ligands with laminin and collagen IV in the basement membrane regulate cell adhesion and migration that contributes to the aggressive and invasive nature of GBM. However, Matrigel cultures lost substantial viability between days 9 and 12. This could be a result of hydrogel degradation, which eliminates structural support for cell proliferation. While the Photogel, MA hydrogels, and HyStem scaffolds retained their scaffold structure during the experiment, Matrigel degraded rapidly in culture and the gel was not visible in the well-plate by day 12. Matrigel is non-covalently crosslinked and, therefore, is more susceptible to degradation. GBM cells overexpress matrix metalloproteinase-2 (MMP-2) and MMP-9 which degrade basement membrane components such as laminin and collagen IV. Thus, Matrigel does not appear to support cultures over periods of time likely needed to observe acquisition of treatment resistance.

Relationships Between Culture Conditions And Temozolomide (TMZ) Treatment

[0219] Two-way ANOVA (treatment, time) was performed to determine whether time,

64

SUBSTITUTE SHEET ( RULE 26) treatment, or if the interaction between treatment at all timepoints affected the results. For both GS54 and GS25 cells, both culture time and condition had the greatest effects on viability measurements. (Tables 12-13). For the GS54 cells, treatment had significant effects only in the Matrigel condition. In contrast, GS25 cells were significantly affected by treatment and time in Matrigel, HyStem, and MA hydrogels. Additionally, the interaction between treatment and time was statistically significant only for the Matrigel condition with the GS25 cells.

[0220] Figs. 31-32 summarize the responses of GS54 and GS2.5 cells, respectively, across culture conditions over the 12-day experimental timeline. 2-way ANOVA, followed by post- hoc comparisons using the Bonferroni method, was performed to evaluate the statistical differences between control and treated groups for each condition. For GS54 cells, no

65

SUBSTITUTE SHEET ( RULE 26) significant differences were observed between treatment and control at any timepoint for any culture condition, except for Matrigel cultures at day 12 where treated cultures were significantly less viable (Fig. 31). Furthermore, while significant higher viability was apparent in non- treated controls between days 3 and 12 for gliomasphere, MA hydrogel, and Matrigel conditions, no differences were seen for MA hydrogels when treated with TMZ. For TMZ treatment compared to non- treated controls, there was significantly less viability in Matrigel cultures and a similar non-significant trend was observed in gliomaspheres cultures, indicating some cytotoxic treatment response. In contrast, treatment induced a significant increase in cell viability in MA hydrogel conditions, indicating that cultures had acquired a strong TMZ resistance. No differences between were seen with or without treatment in photogels or HyStem conditions, indicating that cultures were non-responsive to TMZ. In addition, pairwise comparisons among culture conditions found similar significant differences as for non-treated controls. The GS54 line is expected to be resistant, or at least non-responsive, to TMZ given its unmethylated MGMT status and presumed expression of MGMT.

[0221] Overall, these data suggest that the GS54 line, as expected from its MGMT status, is largely resistant to TMZ treatment when cultured in MA hydrogel or photogel conditions, with the MA hydrogel condition possibly induces a highly proliferative, resistant phenotype, whereas gliomasphere and Matrigel conditions do not support cultures with physiologically relevant resistance phenotypes. Given the low overall cell numbers in HyStem hydrogels, it is difficult to assess their value as a tumor resistance model.

[0222] For the GS25 cell line, significant differences between the control and treated group were observed in the Matrigel condition on day 6, in the MA hydrogels and Matrigel on day 9, and MA hydrogel, photogel, and Matrigel culture conditions on day 12 (Fig. 32). While the treated GS54 gliomaspheres saw some cell proliferation as well as a slight cytotoxic response to TMZ, the GS25 gliomaspheres exhibited a significant decrease in cell viability, similar to the HyStem condition. Treatment did not induce a difference in the HyStem condition. Although not statistically significant, a slight difference on day 9, and a negligible difference was observed on day 12 for the gliomaspheres. Additionally, the photogel and MA hydrogels demonstrated similar trends, where treatment resulted in a significant increase in cell viability compared to their non-treated control counterparts, indicating that both had acquired resistance to TMZ. This is similar to the phenomenon observed with the GS54 cells cultured in the MA hydrogels. Finally, the treated Matrigel condition observed a significant decrease in cell viability compared to the control groups in all days after treatment exposure, indicating that TMZ elicited a cytotoxic response.

[0223] As a result, it is concluded that even when considering an MGMT methylated cell line, which should comparatively be more sensitive to TMZ, HA content in hydrogel cultures also contributed to treatment resistance. Specifically, TMZ-treated GS25 cultures in photogel and MA hydrogel conditions acquired TMZ resistance by the end of the 12-day experiment and exhibited an increase in cell viability. However, TMZ induced a significant cytotoxic response in Matrigel cultures of methylated and unmethylated cell lines, indicating that the Matrigel model does not constitute a microenvironment relevant to GBM physiology. Finally, both HyStem and gliomasphere conditions were unable to support cell proliferation, proving to be ineffective culture models in which to study GBM treatment resistance.

[0224] Overall, robust treatment resistance was only observed in the hydrogel conditions, fabricated from high molecular weight, minimally modified HA. As mentioned earlier, GBM cells dynamically interact with the ECM, allowing for cell growth and invasion. The abundant ECM component, HA, which is also overexpressed by GBM cells, contributes to tumor progression, cell proliferation, and invasion through interaction with the CD44 receptors on GBM cells. It has been reported that CD44-mediated adhesion of GBM cells to HA leads to downstream activation of Src in the cells, which contributes to treatment resistance and increased cell invasion. Because the MA hydrogels and photogels are composed of HA, the conditions observe the interaction between the GBM cells and the HA that contributes to the aggressive nature of GBM, as well as treatment resistance.

[0225] Integrins on GBM cells also interact with RGD in ECM proteins to promote cell invasion and resistance to chemo therapeutics. It has been found that high HA-hydrogels with RGD observed enhanced resistance to drug-induced apoptosis compared to hydrogels with high levels of HA and no RGD or low HA hydrogels. As a result, the cooperative effect of both integrin binding to RGD and the interaction between CD44 and HA contribute to protection against treatment. HyStem does not have any integrin binding sites. The lack of integrin engagement in the HyStem conditions diminishes treatment resistance and cell invasion and contributes to the decreased cell proliferation observed in these hydrogels. In contrast, the photogels and MA hydrogels incorporate RGD and HA content and observe increased proliferation and resistance to treatment. Effects oflntegrin and CD44 Inhibition on Cell Viability

[0226] The experiments described thus far have demonstrated that the biomaterial composition of the hydrogels may also influence resistance to TMZ treatment, even when considering a methylated cell line, which should be more sensitive to treatment compared to the unmethylated cell line. The effects of cell-ECM interaction in different culture matrices on treatment resistance were studied next. In the GBM microenvironment, GBM cells interact with the ECM primarily through two interactions: CD44-HA and integrin-RGD. As mentioned earlier, CD44 expression is upregulated in GBM, and is activated through its interaction with HA. An increase in HA content in engineered hydrogel models also contributes to an increase in CD44. CD44-HA engagement results in an increase in tumor cell proliferation, invasion, and treatment resistance. Additionally, integrins are upregulated in malignant cancers, such as GBM, and integrin binding to peptides on the ECM facilitates increased cell survival, migration, and invasion. Specifically, the av integrin is upregulated in GBM. The photocrosslinked hydrogels and the Michael-type addition reaction hydrogels are both HA-based, and incorporate the ECM peptide, RGD.

[0227] In order to assess the roles HA and RGD play in treatment resistance of cells cultured in various matrix-mimetic scaffolds, encapsulated, MGMT-unmethylated, GS54 cells were treated with cilengitide and an ezrin inhibitor to inhibit integrin-RGD binding, and CD44-HA interactions, respectively. Cilengitide, a cyclized RGD-containing peptide, inhibits RGD that is incorporated in the hydrogel from binding to the integrin av, therein preventing integrin activation, which may mediate resistance to chemotherapeutics. Cilengitide demonstrated efficacy in phase I and phase II of clinical trials but showed no differences between the overall survival of the control group and cilengitide group in phase III trials. Nevertheless, cilengitide is often used as an adjunct therapy alongside chemotherapeutics and has implication in understanding the interactions between the ECM and GBM cells. Meanwhile, ezrin, a protein part of the ezrin-radixin-moesin (ERM) family, and CD44 interaction allows for engagement with F-actin cytoskeleton, and activation of the downstream signaling pathways involved in cell proliferation and survival. As a result, an ezrin inhibitor was used to inhibit CD44-HA interaction, and therefore, prevent CD44 engagement with ezrin.

[0228] Images were acquired on day 3 and day 12 to visualize cultures treated with cilengitide and/or ezrin inhibitor. For the gliomaspheres, there are no effects of cilengitide on cell viability by day 12 (Fig. 33). However, gliomaspheres secrete HA which interact with the CD44 receptors to increase cell proliferation. The addition of the ezrin inhibitor which inhibits this interaction led to increased cell death. This can be seen in Fig. 33 as the edges of the clusters start to look frayed, and the GFP that was expressed constitutively by the cells was disrupted. The encapsulated cells in MA hydrogels (Fig. 34), photogels (Fig. 35), and Matrigel (Fig. 37) were affected by both cilengitide and ezrin inhibitor. The cells in the groups with inhibitors were visually smaller, even more so in the group with the ezrin inhibitor. Furthermore, cell proliferation appeared to decrease in all conditions with inhibitors.

[0229] Data were assessed to determine whether the addition of cilengitide and ezrin inhibitor would influence treatment responses. The control and treated groups on each time point, and for each condition with all the treatments, were compared using 2-way ANOVA. If the inhibitors influenced the treatment response, the control versus treated + cilengitide or treated + ezrin inhibitor would yield statistical differences, indicating that the cells should be able to respond to TMZ or observe an enhanced response to the chemotherapeutic when used in conjugation with an inhibitor. GBM cells in all the conditions were exposed to the inhibitors post-encapsulation. There were no statistical differences between any groups on day 3 (Fig. 38). However, Matrigel cultures exhibited a decrease in cell viability, compared to the control, with the addition of inhibitors. A slight decrease in cell viability with added inhibitors was also seen in the Gliomaspheres.

[0230] By day 12, statistical differences were observed between the control group for the photo-crosslinked hydrogels and all the treated groups, as well as for the Matrigel (Fig. 39). The decrease in cell viability can largely be attributed to addition of inhibitors in all conditions. For the gliomaspheres, the combination of TMZ and ezrin inhibitor, or ezrin inhibitor alone each resulted in decreased cell proliferation compared to the controls, while there was no effect of cilengitide alone. The effect of ezrin inhibitor on gliomaspheres can be attributed to the increased amount of secretion of HA by GBM cells. By inhibiting the HA-CD44 interaction, GBM cell proliferation decreases. GBM cells also enhance deposition of ECM proteins that interact with integrin av through RGD contained within the proteins. However, it has been demonstrated that interactions between integrin av and CD44, especially in high HA hydrogels with increased CD44 expression, are necessary to enhance GBM invasion and chemoresistance. As a result, gliomaspheres, which lack interactions with a high HA matrix and observe decreased expression of CD44, do not exhibit decreased cell proliferation due to cilengitide-mediated inhibition of RGD-integrin av. [0231] While TMZ treated cells in MA hydrogels resulted in acquired resistance and showed increased cell proliferation compared to the control, the addition of ezrin inhibitor and cilengitide in combination with TMZ resulted in decreased cell proliferation (Fig. 39). However, the sole addition of cilengitide resulted in the same cell proliferation response as the group with TMZ and cilengitide, indicating that the MA hydrogels were not more susceptible to TMZ treatment with cilengitide. In contrast, the group with just ezrin inhibitor showed similar viability to the control group with no inhibitors while cell proliferation decreased with the combination of TMZ and ezrin inhibitor. As a result, it is assumed that the MA hydrogels are more susceptible to TMZ treatment when used in conjugation with the ezrin inhibitor. While RGD-integrin binding is important for increased cell proliferation, these results demonstrate that it is the interactions between CD44 and HA that are integral to treatment resistance. This confirms a study done by Kim and Kumar et al. where they demonstrated that CD44-HA interactions are essential for enhanced cell proliferation, treatment resistance, and survival, and their effect on GBM cannot be replaced by increased cell attachment peptides.

[0232] Cell viability in HyStem was not affected by any inhibitors, indicating no effects of matrix engagement on net cell survival or proliferation. Since RGD-containing biomolecules were not incorporated into the HyStem hydrogels, it was not expected to be responsive to cilengitide. However, HyStem has HA content and preventing interactions between HA and CD44 through ezrin inhibitors should result in decreased cell proliferation. This was not observed in HyStem, which indicates that it is possible that these scaffolds express very low amounts of CD44. It has been demonstrated that GBM cells cultured in hydrogels with high HA content exhibited greater cell growth and enhanced resistance to treatment. As a result, it is concluded that HyStem exhibits similar characteristics to low HA content hydrogels, in which decreased expression of CD44 ultimately prevented GBM cell proliferation and treatment resistance.

[0233] Meanwhile, the photogel and Matrigel conditions experienced drastic decreases in cell proliferation with the addition of inhibitors. However, the sole addition of inhibitors led to a decrease in viability, indicating that increased cell death was due to inhibition of matrix interactions alone and that the combination of TMZ with inhibitors does not make the cells more susceptible to TMZ.

[0234] It was hypothesized that poor response to TMZ observed by the HA-based hydrogels could be attributed to the active engagement of CD44 with HA and RGD with integrins. As one can see from the above results, the addition of inhibitors results in a significant decrease in cell viability in the photogels, indicating that GBM cell-ECM interactions are critical for GBM cell survival and proliferation. Additionally, although not statistically significant, the MA hydrogels appeared somewhat more susceptible to TMZ treatment with the addition of the ezrin inhibitor, indicating that HA-CD44 binding affects resistance to treatment. As GS54 cells are unmethylated and not expected to respond to TMZ, the combination of TMZ with an inhibitor would be expected to cause a decrease in cell proliferation only solely to disruption of the critical interactions between the cells and their matrix environment.

Qualitative Assessment of Cell Proliferation and Apoptosis

[0235] Staining of biomarkers was used to qualitatively assess proliferation and apoptosis in encapsulated GS54 cells. Results shown in Fig. 40 demonstrate little to no Ki67 in the day 3, pre- treatment groups, and an increased cell proliferation in the control groups compared to the treated groups, for all three conditions. While CCK8 data showed that HyStem cultures had very little cell proliferation over the course of the experiment, it was observed qualitatively that there is more Ki67 present in the control group so treatment may stop proliferation. Next, GBM cells upregulate expression of CD44 and therefore, it can be used to detect viable tumor cells. The control and treated groups for both Michael-addition reaction hydrogels and photocrosslinked hydrogels show an abundance of CD44 compared to the HyStem condition (Fig. 41). GBM cells also overexpress CD44 when interacting with a greater amount of HA, as observed with the HA-based hydrogels. However, HyStem, which is also HA-based, does not have much CD44 present. Therefore, cell culture in HyStem are not upregulated CD44 in response to HA or engaging with HA via CD44. The CD44 expression observed here is similar to the expression in low HA-content (0.1% w/v) hydrogels as demonstrated by Xiao et al., indicating that there is insufficient HA in HyStem. This can be confirmed by its lack of ability to culture GBM cells, as demonstrated with the cell proliferation assay experiments. Finally, cP ARP is seen consistently throughout all conditions (Fig. 42). One can quantitatively observe that the amount of cPARP is very similar for the control and treated groups in the HyStem conditions, photogels, and the MA hydrogels. This which supports the data observed in Fig. 31, where differences in cell viability for groups on day 12 were statistically insignificant.

EXAMPLE 5 Hyaluronan Concentration-Dependent Invasion and Mechanotransduction in Glioblastoma METHODS

HA Thiolation and Hydrogel Fabrication

[0236] Approximately 4.5-6% of D-glucuronic acid carboxylic acid groups in the repeating hyaluronic acid (HA) disaccharide chain (Mw = 700kDa, LifeCore Biomedical) was thiolated via carbodiimide chemistry (A-hydroxysuccinimide (NHS); l-ethyl-3-[3-dimethylaminpropyl] (EDC)), and reaction with cysteamine (Sigma- Aldrich) to yield HA-SH. Following reduction with Dithiothreitol (DTT) and subsequent dialysis for purification, proton nuclear magnetic resonance spectroscopy and an Ellman’s Test were conducted to verify HA-SH thiolation percentage.

[0237] Prior to gelation, compounds were buffered in 4-(2-hydroxyethyl)-l- piperazineethanesulfonic acid (HEPES; Fisher BioReagents) with Hank’s Buffer Salt Solution (HBSS; Sigma-Aldrich) to yield the following solution densities: 10 mg/mL HA-SH; 100 mg/ml . thiol-terminated 4-arrn polyethylene glycol (PEG-SH, Mw = 20kDa, Laysan Bio); 100 mg/mL 8- arm polyethylene glycol norbornene (PEG-Norb; Mw = 20kDa, Laysan Bio); 4mM thiolated RGD peptide (RGD-SH, ‘GCGYGRGDSPG’ (SEQ ID NO:1); GenScript); 1-3 mg/mL Lithium phenyl-2,4,6- trimethylbenzoylphosphinate (LAP; Sigma-Aldrich). Prepared gel solutions contained 0.25% w/v LAP, 0.25 mM RGD-SH, and either 0.10, 0.25, 0.50, or 0.75 percent weight per volume (w/v) of HA-SH.

[0238] The crosslink factor was empirically determined to provide sufficient crosslinking and avoid the thiol-ene click chemistry termination reaction series to ensue. The remainder of the formulation consisted of HEPES:HBSS, which was added to achieve a desired volume. Thirty mL of finalized gel solutions were added to 30 mm³ cylindrical slots in silicone molds. These solutions were then exposed to 3.95 - 4.05 mW/cm² magnitude of 365 nm UV radiation for 15 seconds to initiate gelation. Gel products were removed from molds and maintained in phosphate buffered saline (PBS, Dulbecco’s PBS) until characterization.

HYDROGEL CHARACTERIZATION

Mechanical Property Testing

[0239] Hydrogel storage moduli (G’) were measured using a discovery hybrid rheometer-2 (DHR-2, TA Instruments) at 37°C. Frequency sweeps were performed under 1% constant strain in the range of 0.1 to 1.0 Hz. Storage modulus of each sample was calculated as the average value of the linear region of the storage curve from the frequency sweep plot. For statistical analysis, 3 separate measurements were taken in which 5 samples from each condition were measured.

Mass-Swelling Ratio

[0240] Fabricated hydrogels without cells were weighed using a scale (Weight;, ;) and subsequently incubated in IX PBS at 37°C and 5% CO2. After 24 hours, the weight of each hydrogel was again recorded (Weight;, 2). The formula below was used to calculate the mass swelling ratio per hydrogel: Mass Swelling Ratio = Weight;, 2/ Weight;, 1

Diffusion Modeling

[0241] Fluorescence recovery after photo-bleaching (FRAP) was used for diffusion measurements. Hydrogels were incubated with fluorescein isothiocyanate-dextran (FITC- Dextran) solution (0.33 mg/ml in PBS) overnight. Five pre-bleach images were taken at 10% power of 488 laser under a SP5 laser scanning confocal microscope (Leica). In order to bleach, 30 μm region of hydrogels were exposed to a 488 laser (600 μm pinhole) for 20 seconds. One thousand frame of images were taken as post bleached images. t_d values (time for half recover) were calculated from fluorescence recovery graphs. Diffusion coefficients (D_e) were calculated using simplified Fick’s law:

M;/ Minf = 2[Det/ 71X²]^1/2

Patient-Derived GBM Cell Culture

[0242] GS54, HK177, HK217, and HK408 were the patient-derived GBM lines used in this study. Patient line GS54 (passages 14 - 18) and lines HK177 (passages 15 - 17), HK217 (passages 11 - 22), and HK408 (passages 15 - 24) were generously provided by Dr. David Nathanson (UCLA, GS54) and Dr. Harley Kornblum (UCLA, HK lines), respectively. While all patient lines were sphere-forming, HK217, HK177, and GS54 were in suspension while HK408 was adhesive. All GBM cells were cultured in T-75 flasks with complete media which consisted of DMEM/F12 with L-glutamine and 15mM HEPES in IX Gem21, 0.2% Normocin, 20 ng/mL human fibroblast growth factor-basic (hFGF-2), 50 ng/mL human epidermal growth factor (hEGF), and 25 mg/ml , heparin. Both 2D and 3D cultures were incubated in 5% CO2 and 37°C throughout the course of all experiments.

[0243] For passaging, cells were centrifuged at 400g for 5 minutes and resuspended in IX TrypLE (Life Technologies) for no longer than 5 minutes. Following the addition of 4 mL of complete media, cells were again centrifuged at 400g for 5 minutes. As final steps, cells were reconstituted in 1 mL media, filtered using a 40 mm cell strainer, and manually counted by use of a hemocytometer. A 100,000 cells/mL cell seeding density for culturing was maintained following each passage.

Gliomasphere (GS) Culture and 3D Encapsulation

[0244] Following passaging, single GBM cells were seeded (600,000 cells/well) into individual wells of a 24-well AggreWell™ plate pre-coated with 5% Pluronic in IX PBS solution. Centrifugation (300 g for 3 minutes) and incubation (5% CO2 and 37°C) followed. After 18 hours, GSs were prepared for suspension culture or 3D encapsulation within hydrogels.

[0245] For suspension culture, GSs were harvested using a plOOO pipette and resuspended them in 10 mL media over the course of experiments. For 3D encapsulation, GSs were similarly harvested and resuspended in prepared gel solutions (0.10% - 0.75% w/v) (see “HA Thiolation and Hydrogel Fabrication”). Gelation of mixed gel and GS solutions ensued as previously described in the methods and yielded the 3D hydrogels containing the patient- derived GBM spheroids.

Microscopy and Quantification of Invasion

[0246] Phase contrast images were obtained using the Zeiss Axio-Observer microscope and Zen software, and image analysis was performed using the ImageJ software. GS invasion was quantified by shape factor, a ratio of a GS’s area to its squared perimeter, and migration length, the maximum protrusion radius from a GS’s periphery. Perimeter and area values were obtained by manually tracing GSs, and shape factor was calculated using the following formula: Shape Factor = 4;iA/p²

Cryopreservation, Immuno staining, and Confocal Imaging

[0247] Hydrogels underwent fixation in 4% paraformaldehyde (PFA) in IX PBS solution for 1 hour at room temperature. Then followed sequential incubations in solutions of 5% and 20% sucrose in IX PBS for 1 hour time periods. After leaving the hydrogels in 20% sucrose solutions overnight at 4°C, hydrogels were embedded in 20% sucrose in preservation molds containing IX Optimal Cutting Temperature (OCT) compound for 3 hours at 4°C and flash frozen in 2- methylbutane. Frozen hydrogels were cut into 12 mm sections using the Leica Cryostat. [0248] Sections were fixed in 4% PFA in IX PBS solution for 12 minutes before being subsequently washed using 0.10% tween-20 in IX tris-buffered saline (TBS-T) and blocked with 4% bovine serum albumin (BSA) in IX TBS-T for 1 hour in room temperature. Then, sections were incubated at 4°C overnight with primary antibodies for CD44 (1:400, Cell Signaling Technology), RHAMM (1:400, Novus Biologicals), Ezrin (1:200 Cell Signaling Technology), Ki-67 (1:100, Invitrogen), and cleaved PARP (Cl-PARP, 1:400, Cell Signaling Technology) or biotinylated HA binding protein (HABP; EMD Millipore) diluted in blocking solution according to the provided manufacturer’s recommendations. The next day, samples were incubated in Hoechst 33342 and appropriate secondary antibody solutions with limited light exposure for 1 hour. Following a final wash, slides were mounted using coverslips with applied Fluoromount G (Southern Biotech, Birmingham, AL, USA).

[0249] Confocal laser scanning microscopy was performed at the Advanced Light Microscopy/Spectroscopy Laboratory and the Leica Microsystems Center of Excellence at the California NanoSystems Institute at UCLA.

Cell Extraction from Hydrogels and EdU Proliferation Assay

[0250] Cultured and encapsulated spheres were incubated in a 1:1000 dilution of EdU solution (Cayman Chemical Company 20518) for 4 hours. Following a wash in PBS, hydrogel samples were broken down using a 10 mL syringe with a 20G needle and passed through a 40 mm filter into collection tubes. Cultured samples were not broken down using a 20G needle to avoid mechanically induced stress and were rather incubated in TrypLE solution for 5 minutes, resuspended in media, and passed through a 40 mm filter. All samples were subsequently centrifuged (400g for 5 minutes), resuspended in 4% PFA in IX PBS, and stored in 4°C overnight.

[0251] The following day, samples were centrifuged (400g for 5 minutes) and washed in 1 % BSA in IX PBS. Cells were permeabilized for 15 minutes in permeabilization buffer (0.1% Saponin and 1% BSA in IX PBS). Staining solution was prepared and added to the cells undergoing the permeabilization reaction. After 30 minutes of incubation without light in room temperature, samples were washed twice and ultimately resuspended in permeabilization buffer. Flow cytometry data was collected using the Guava easyCyte™ Flow Cytometer and analyzed using FlowJo™ software.

Cell Viability Quantification [0252] Encapsulated GSs were incubated at 37°C and 5% CO2 for 15 minutes in LIVE/DEAD working reagent prepared by diluting 2 mM Ethidium homodimer-1 (1:500) and 4 mM Calcein AM solution (1 :2000) stock solutions in IX PBS. Spheres were imaged and three separate counters quantified the presence of live or dead cells in images provided.

Tissue Microarray (TMA ) HA Staining and Scoring

[0253] TMAs were prepared by clinically isolated tissue biopsy samples from 39 GBM and 19 lower-grade CNS cancer (grade I-III astrocytoma, grade I-III oligodendroglioma, pituitary gland cancer, and meningioma) patients, prepared and provided by Dr. William Yong and the UCLA Brain Tumor Tissue Resource. Paraffin-embedded slides of 5 mm thickness were deparaffined using 100% xylene and a 5-step reduction in alcohol presentation from 100% ethanol to deionized water. Samples were washed (0.1% Tween in IX TBS), blocked (5% normal goat serum and 1% BSA in washing solution), and incubated with biotinylated HA binding peptide (HABP) overnight at 4°C. The following day, samples were washed and incubated using Vectastain ABC kit reagents and 3,3’-diaminobenzidine (DAB) substrate. Samples were mounted onto slides using a toluene solution. Images were taken using the Zen Axio- Observer microscope and images were semi-quantitatively scored according to a previously described method.

Statistics

[0254] All statistics were performed using GraphPad Prism software. Kolmogorov-Smirnov test was performed to assess normality of data. For parametric data, a Student’s T-test and one- or two- way Analysis of Variance (ANOVA) was performed to assess significance between two and multiple data sets, respectively, followed by post-hoc Tukey’s multiple comparisons test. In the case of non-parametric data, a Kruskal- Wallis ANOVA was used to assess significant differences between any data sets followed by post-hoc Dunn’s multiple comparisons test. Modes of significance were reported as follows: ns, non-significant; *, p < 0.05; **, p < 0.01; ***, p< 0.001; ****, p < 0.0001.

RESULTS

Greater HA Deposition in Higher Grade Gliomas

[0255] HA deposition is a key feature in GBM pathophysiology. To assess potential differences in HA deposition in clinical brain tumors, tissue microarray (TMA) staining was performed for HA in GBM (N = 34) and lower-grade CNS (N = 19) tumor samples. Representative images of tissue samples are shown, with darker brown coloration being indicative of greater HA abundance within samples (Fig. 43A). On average, HA concentration was elevated in GBM tissues relative to lower grade CNS cancers (p = 0.008) (Fig. 43B). Notably, the spatial distribution of HA in the samples was nonuniform, containing regions with relatively high (darker brown) and low (lighter brown) HA concentrations (Fig. 43C). Even following orthotopic implantation in mice, HK408 cells demonstrated greater HA deposition especially along the tumor edge, where high rates of invasion occur (Fig. 43D). Matching the phenotype described in patient samples, HA concentration in xenografts also was heterogeneous along the tumor edge (Fig. 43E).

Fabrication of HA Concentration-Tunable, Biocompatible Hydrogels

[0256] To investigate the effects of varying HA concentration on GBM phenotypes, GSs were encapsulated in mechanochemically tunable, 3D hydrogels. Specifically, HA hydrogels were fabricated with 0.10%, 0.25%, 0.50%, and 0.75% weight per volume (w/v) HA. All hydrogels contained 0.025% (w/v) of RGD peptides, were exposed to equal intensities and durations of UV radiation during gelation and had similar mechanical properties. Swelling characterization was performed by incubating priorly weighed hydrogels in Dulbecco’s phosphate buffered saline (D-PBS) for 24 hours. The ratio of the final to initial mass, or mass swelling ratio, gradually increased with increasing HA concentrations in the hydrogels (Fig. 44A). Given that the total polymer content was constant between hydrogels, this result demonstrates that hydrogel hygroscopy was associated with its HA content. Moreover, hydrogels had similar storage moduli of 115.1±14.2 (G’) Pa, 116.3±19.0 (G’) Pa, 116.3±20.3 (G’) Pa, 124.4+16.3 (G’) Pa for the 0.10% - 0.75% (w/v) HA conditions, respectively (Fig. 44B). Low storage moduli were used to mimic the mechanical integrity of healthy brain tissue interfaced with the GBM peritumoral environment. The associated porosity across hydrogels was also similar. Using fluorescence recovery after photobleaching (FRAP), it was noted the effective diffusion rates of 20 kDa and 70 kDa FITC-Dextran polymers were equivalent to that of PBS and between 0.10% - 0.75% (w/v) hydrogels (Fig. 44C). As such, moieties up to 70 kDa in size, which includes the important media components (EGF and FGF) and the later-used small molecule inhibitor, can freely diffuse throughout the gel.

[0257] Given GSs better capture cell-cell adhesions and interactions normally present within nascent tumors compared to 2D monolayer culture, GSs of controlled sphere size were formed using AggreWell™ plates and encapsulated them in hydrogels. The viability of GSs patient lines at experimental endpoints remained high over the course of our studies (Fig. 45A). To quantify the numbers of apoptotic cells within GSs, immunostaining for cleaved PARP (Cl- PARP) was performed. GSs of both patient lines exhibited low apoptosis in hydrogels. Specifically, HK408 GSs in 0.10% - 0.75% (w/v) HA hydrogels had 6+2%, 3+2%, 3+1%, and 3+1% apoptotic cells, respectively, while GS054 GSs had 2+1%, 2+1%, 2+1%, and 2+1% apoptotic cells, respectively (Fig. 45B). Additionally, immunostaining was performed for proliferation marker Ki-67, which was heavily expressed by most cells within GSs across hydrogels (Fig. 45C). Notably, HK408 GS in 0.10% (w/v) HA hydrogel had observably less proliferation than GSs in 0.25% - 0.75% (w/v) HA hydrogels. An EdU assay was next used to investigate potential differences S and G2 phase cell cycle activity in the HK408 line. Confirming the Ki-67 staining, HK408 GSs in the low HA environment had significantly less cells in S & G2 phases of proliferation than GSs in higher HA environments (p = 0.0001 [0.25% (w/v)]; p = 0.0062 [0.50% (w/v)]; p = 0.0011 [0.75% (w/v)]). Interestingly, GSs in 0.25%- 0.75% (w/v) HA hydrogels had similar percentages of cells in S and G2 phase (Fig. 45D).

Determining Optimal HA Concentration for Invasion in Patient Lines

[0258] At the endpoint, GSs in 3D culture displayed diverse morphologies dependent on both the patient line as well as hydrogel HA concentration. Interestingly, the migration morphologies were independent of the patient’s GBM classification as proneural (HK408, HK217) or mesenchymal (GS054, HK177). While HK217 and GS054 GSs displayed mainly thinner, single cell protrusions extending into matrix, the periphery of HK408 and HK177 GSs heavily displayed thicker, multicellular protrusions indicative of collective migration (Fig. 46A; Fig. 47A). Still, instances of single and collective cell migration were noted in all patient lines. Uniquely, GS054 spheroids encapsulated in 0.75% (w/v) HA hydrogels adopted polarized, crescent- like shapes, which did not resemble the invasive phenotypes observed in 0.10%-0.50% (w/v) HA hydrogel cultures or for other cell lines. In accordance with previous work by Xiao et al. (2020), both HA and RGD peptide interactions were necessary for elongated cell migration phenotypes depicted across conditions.

[0259] Migratory activity of GSs across hydrogels was quantified over the course of six days for HK408, HK177, and GS054, and nine days for HK217. Migration length quantified the maximum Euclidian displacement by a single cell or multicellular protrusion from the sphere periphery into matrix, while shape factor quantified the circularity of spheroids as a scaled ratio of area to squared circumference and approximated the overall protrusion density per GS. In general, GSs across patient lines exhibited greater cell migration in 0.25%-0.75% (w/v) HA hydrogels compared to 0.10% (w/v) HA. Yet, any significant variations of GS invasiveness in hydrogels with 0.25% (w/v) HA were patient-line dependent. Interestingly, HA concentrations for peak, or optimal, invasiveness were apparent for the HK408 and HK177 patient lines in 0.25% (w/v) HA hydrogels. For HK408, differences in shape factor were nonsignificant in 0.25% (w/v) HA hydrogels (Fig. 46B). However, the median migration length of GSs in 0.75% (w/v) HA hydrogels was significantly less than those in 0.50% (w/v) HA (p = 0.0343) and approximate to the median migration length in 0.25% (w/v) HA hydrogels (p = 0.8633) (Fig. 46C). The median shape factor for HK177 GSs was lower in hydrogels with 0.25% (w/v) % HA compared to 0.50% (w/v) (p = 0.0013) and 0.75% (w/v) (p < 0.0001) HA hydrogels, while differences migration lengths between these conditions were non-significant (Figs. 47B-C). Thus, even though the median protrusion density of spheres was relatively similar in conditions of 0.25% (w/v) HA, the concentration of 0.50% (w/v) HA was optimal for cellular displacement from the sphere periphery in HK408 GSs. In contrast, 0.25% (w/v) HA was optimal for HK177 GS protrusion density, while HA concentrations 0.25% (w/v) did not influence maximal cellular displacement. No HA concentration was identified within the 0.25%-0.75% (w/v) HA range as a maximum of migratory activity for GS054 and HK217. Specifically, both the median shape factor and migration lengths of GS054 GSs were the greatest in 0.75% (w/v) HA hydrogels, with no significant differences in 0.25% and 0.50% (w/v) HA conditions (Figs. 46D-E). No significant differences in HK217 GS motility were apparent across 0.25% (w/v) HA hydrogels (Figs. 47D-E).

Greater Cellular CD44 Expression in More Invasive GSs

[0260] Next, the roles of HA receptors CD44 and RHAMM in determining the invasive profiles of GSs across HA conditions were investigated. To avoid potential errors introduced while dissociating the CD44 and RHAMM from the HA matrix, absolute protein quantification between conditions using methods such as Western Blot or Flow Cytometry was not perform. Instead, immunofluorescent staining of GSs was done at experimental endpoints to evaluate potential differences in the spatial distribution of HA receptors CD44 and RHAMM. HK408 and GS054 GSs both exhibited similar patterns of CD44 and RHAMM protein expression such that CD44 was localized to membranous and pericellular regions while RHAMM was primarily localized within the cytoplasmic and nuclear domains of cells. However, HK408 GSs expressed greater densities of CD44 per cell compared to GS054 GSs which had intermittent CD44 expression at lower densities along cell membranes. Yet, for both lines, CD44 was presumed to be the main receptor mediating cell-ECM interactions given its location at the cell membrane. Interestingly, no variations in HA receptor expression were obvious between migratory and stationary regions of the GS peripheries within each HA condition (Figs. 48- 49). In addition, the spatial patterns of expression for CD44 and RHAMM in HK408 GSs within 3D hydrogels were very similar to those observed in HK408 xenografts (Fig. 50A). Insets provided of stained cells reveal the HK408 cells are extending microtentacles as reported by Wolf et al. (2020) and may be performing mechanosensation of local microenvironment via CD44 (Fig. 50B).

CD44-ERM-Actin Engagement Determines GS Propensity to Invade

[0261] Given no clear instances of CD44-mediated mechanosensation in the xenografts, potential variations in receptor-cytoskeleton engagement was investigated next. Specifically, immunofluorescent staining was performed for CD44 and the ezrin subunit of ERM. Within HK408 xenografts, instances of CD44 and ezrin colocalization seemed high especially towards the peripheral regions of the tumor mass, where we also identified higher concentrations of HA. Moreover, the cells along the tumor periphery are migratory given their phenotype, complementing findings of higher HA concentrations causing higher migration in the hydrogels (Fig. 50C). At punctuate points along the cell membrane, high degrees of overlap between CD44 and ezrin occurred, suggesting CD44-mediated mechanosensation could be the result of ERM-mediated cytoskeletal anchoring (Fig. 50D). Immunostaining of the hydrogel samples was performed to investigate whether relatively minute differentials in HA concentrations could contribute to variations in CD44 and ezrin colocalization at the cell membrane. The Pearson correlation coefficient (r) metric was used to assess degrees of CD44 and ERM overlap, or colocalization, in 100X magnification confocal microscopy images. Remarkably, CD44-ERM colocalization of HK408 gliomaspheres in 0.10% (w/v) HA hydrogels was significantly lower than 0.25% (w/v) HA (p < 0.0001), 0.50% (w/v) HA (p = 0.0158), and 0.75% (w/v) HA (p = 0.0009) hydrogels, while no differences in colocalization were apparent for GS054 GSs across 0.10%-0.75% (w/v) HA hydrogels (Figs. 51A-B; Fig. 52B). Interestingly, CD44-ERM colocalization was not limited to cells in direct contact with the HA matrix at GS edges, but included cells located within the spheroid mass (Fig. 51A). Thus, the HA concentration in the surrounding matrix appeared to mediate levels CD44-ERM engagement in not only single cell, but throughout GSs, perhaps through cell-cell or cell-ECM- cell connections.

CD44-ERM Axis Inhibition Modules GBM Invasion in Patient-Dependent Manner [0262] To further assess ERM-mediated CD44 engagement of the actin cytoskeleton in individual patient lines, pharmacological inhibition of ERM was performed using the small molecule inhibitor NSC668394 (ERMi). Five pM was selected as the initial working concentration in accordance with past studies. To evaluate potential concentration-dependent effects by the inhibitor, 10 pM and 20 pM regimens were also completed. The inhibitor was administered 15 hours following encapsulation, when initial signs of invasion were observed across patient lines, and every 48 hours thereafter until the experimental endpoint.

[0263] Following administration of 5 pM ERMi to 0.25% (w/v) HA hydrogels, GS054 GSs underwent complete loss of invasiveness (p < 0.0001) (Fig. 53A). Furthermore, HK217 GSs in 0.25% and 0.50% (w/v) HA hydrogels had significantly higher shape factors compared to respective controls (p < 0.0001 [0.25% (w/v)]; p = 0.0002 [0.50% (w/v)]). No difference in HK217 GS migration was notable with ERMi treatment within 0.75% (w/v) HA hydrogels (Figs. 54A-B). HK408 GSs had similar levels of invasion with ERMi as controls in ³0.25% (w/v) HA hydrogels. Interestingly, and inconsistent with previously reported findings in literature, the 5 pM inhibitor regimen led to heightened HK408 (p = 0.0019) and HK217 (p < 0.0001) GS invasiveness compared to untreated GSs when encapsulated in a 0.10% (w/v) HA matrix (Fig. 53B; Fig. 54A). Phenotypically, both HK408 and HK217 GSs exhibited rounded, single cell invasion along sphere peripheries with ERMi. HK408 GSs had instances of multicellular protrusions and HK217 also displayed instances of single cell protrusions resembling the migration of untreated GSs in 0.25% (w/v) HA hydrogels. In contrast to HK408 and HK217 GSs, a complete loss of invasion was observed in GS054 GSs in 0.10% (w/v) HA hydrogels following the 5 pM ERMi treatment.

[0264] Administration of 10 pM ERMi completely halted HK217 and GS054 GS invasiveness across hydrogel conditions and remained consistent even following the 20 pM ERMi regimen (Fig. 53A; Fig. 54A). Yet, HK408 GSs in 0.25% (w/v) HA hydrogels treated with ERMi displayed similar levels of invasion as compared to controls. Yet, HK408 GS invasion increased in 0.10% (w/v) HA hydrogels (p < 0.0001), aphenomenon which persisted even with the administration of a 20 pM inhibitor regimen (p < 0.0001) (Fig. 53B). The migratory phenotypes observed in the 0.10% (w/v) HA condition HK408 GSs treated with 10 pM and 20 pM ERMi were similar to those treated with 5 pM ERMi. In 0.25% (w/v) HA conditions, administration of 20 pM ERMi resulted in a stark reduction in HK408 GS migration (p < 0.0001 [0.25%-0.75% (w/v)]. While the density of multicellular protrusions was reduced compared to control conditions, single cell invasion persisted and was phenotypically similar to treated GSs in 0.10% (w/v) HA hydrogels (Fig. 53C). These invading single cells could be the result of new single cell invasion from the sphere periphery and/or cellular dismemberment of the multicellular protrusions present within control GSs. Moreover, single cells may exhibit matrix-independent migration, such as non-binding or ameboid.

RGD-Integrin and CD44-ERM Engagements Modulate Migration

[0265] A similar rise in single cell migration ensued in HK408 GSs when RGD peptides functionalized to the hydrogel scaffold were substituted with cysteine (CYS). Higher magnification (400x) images of the HK408 GSs provide a clearer view of the sphere periphery populated by colonies of cells. In the 0.50% and 0.75% (w/v) HA conditions, clear instances of lamellipodia-like structures, indicating migration, were apparent. Thus, when individually abrogating ERM and integrin signaling within the HK408 patient line, the multicellular protrusions noted in control 0.25% (w/v) HA hydrogels were unable to form while instances of single cell invasion became apparent in 0.10% (w/v) HA hydrogels. Importantly, besides HA, the RGD peptides incorporated within the scaffold were critical for the rise of the observed migration phenotypes.

HA-RHAMM Inhibition Increases GBM Invasiveness in High HA Environments

[0266] Given that RHAMM was not completely absent from the periphery of GSs, the importance of perimembranous RHAMM on GS motility was further interrogated using an HA-mimetic RHAMM blocking peptide (RBP). Esguerra et al. (2015) previously demonstrated that this peptide exclusively interacts with the HA binding site of RHAMM and does not interact with CD44. 32 pM of peptide was sufficient for high HA binding. Initially, 32 pM of blocking peptide was administered immediately following the initiation of migration in HK217 cell lines and assessed invasion every 12 hours. Surprisingly, 36 hours following administration, migration lengths were significantly increased in GSs encapsulated in 0.50% (w/v) and 0.75 (w/v) HA hydrogels (p < 0.0001 [0.50% (w/v)]; p = 0.0282 [0.75% (w/v)]) (Fig. 56A).

[0267] Given vast studies identifying RHAMM inhibition results in reduced cell motility, in general, the effects of RBP administration to a second patient line was evaluated. A similar, preliminary study to the aforementioned ERM inhibition studies was designed to evaluate the effects of peptide administration over time. Specifically, 100 pM of RBP was administered exactly 15 hours following encapsulation of HK408, given this was when initial instances of invading cells were notable. A second 100 pM dose of RBP was administered exactly 48 hours after the initial administration and invasiveness was monitored over the course of 3 days. On day 1, the RBP regimen had increased the migration lengths of HK408 GSs cultured in hydrogels with 0.25% (w/v) HA (p = 0.0126). On day 3, treated and untreated GSs in 0.25% (w/v) HA hydrogels had similar migration lengths, however, treated GSs in 0.50% (w/v) HA hydrogels had increased migration lengths (p = 0.0013) (Figs. 56B-C). Interestingly, the initial 100 pM administration of RBP was sufficient to increase invasion in GSs in 0.25% (w/v) HA conditions, but a second administration was required to see any effect in the higher 0.50% (w/v) HA environment. It is hypothesized that greater HA-RHAMM interactions are present in higher HA environments. Furthermore, when the HA-RHAMM binding is targeted, cells may activate compensatory mechanisms to return to normal rates of invasion. At day 1, the average migration length of treated GSs in 0.25% (w/v) HA environments even surpasses that of GSs in 0.50% (w/v) HA. It is possible that excessive invasion is unfavorable to cells given it reduces their propensity for proliferation according to the “Go or Grow” hypothesis.

[0268] While certain features of the invention have been illustrated and described herein, many modifications, substitutions, changes, and equivalents will now occur to those of ordinary skill in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the invention.

Claims

What is claimed is:

1. A method of selecting one or more chemotherapeutic agents for treating a tumor in a patient, comprising the steps of: a. obtaining a tumor biopsy from the patient and isolating tumor cells therefrom; b. preparing a plurality of samples comprising isolated tumor cells, each sample comprising a matrix comprising: i. a high molecular weight hyaluronic acid at a concentration of about 0.25 wt% to about 2 wt%, wherein about 4% to about 10% of glucuronic acid moieties on the hyaluronic acid are thiolated; ii. a thiolated polyethylene glycol; and ii. a polymer comprising an integrin binding moiety; wherein the thiolated hyaluronic acid, the thiolated polyethylene glycol and the polymer comprising the integrin binding moiety are crosslinked; c. exposing tumor cells in the plurality of samples to a plurality of first chemotherapeutic agents, each chemotherapeutic agent individually or in combination; and d. identifying among the samples one or more individual or combination of said first chemotherapeutic agents having maximal effect on suppressing growth or invasiveness of the tumor cells, thereby selecting one or more chemotherapeutic agents for treating a tumor in the patient.

2. A method of selecting one or more chemotherapeutic agents for treating a tumor in a patient, comprising the steps of: a. obtaining a tumor biopsy from the patient and isolating tumor cells therefrom; b. preparing a plurality of samples comprising isolated tumor cells, each sample comprising a matrix comprising:

84 i. a high molecular weight hyaluronic acid (<500 kDa) at a concentration of about 0.25 wt% to about 2 wt%, wherein about 4% to about 10% of glucuronic acid moieties on the hyaluronic acid are thiolated; and ii. a polymer comprising an integrin binding moiety; wherein the thiolated hyaluronic acid the polymer comprising the integrin binding moiety are cross-linked; c. exposing tumor cells in the plurality of samples to a plurality of first chemotherapeutic agents, each chemotherapeutic agent individually or in combination; and d. identifying among the samples one or more individual or combination of said first chemotherapeutic agents having maximal effect on suppressing growth or invasiveness of the tumor cells, thereby selecting one or more chemotherapeutic agents for treating a tumor in the patient. The method of claim 1 or 2, wherein the polymer comprising an integrin binding moiety comprises a norbomene-terminated polyethylene glycol, a maleimide-terminated polyethylene glycol or a vinyl sulfone terminated polyethylene glycol. The method of claim 1, wherein the thiolated hyaluronic acid, the thiolated polyethylene glycol and the polymer comprising an integrin binding moiety are crosslinked by: a. further including maleimide polyethylene glycol or vinyl sulfone polyethylene glycol, wherein the cross-linking occurs by Michael-type addition; b. further including vinyl sulfone polyethylene glycol and a radical generator; or c. further including a norbomene-terminated polyethylene glycol and a radical generator. The method of claim 2, wherein the thiolated hyaluronic acid and the polymer comprising an integrin binding moiety are cross-linked by: a. further including maleimide polyethylene glycol or vinyl sulfone polyethylene

85 glycol, wherein the cross-linking occurs by Michael-type addition; b. further including vinyl sulfone polyethylene glycol and a radical generator; or c. further including a norbomene-terminated polyethylene glycol and a radical generator. The method of claim 4 or 5, wherein the radical generator is a photo-crosslinker. The method of claim 6, wherein the photo-crosslinker is lithium phenyl-2,4,6- trimethylbenzoylphosphinate. The method of claim 1 or 4, wherein the polyethylene glycol comprises multiple arms. The method of claim 8, wherein the polyethylene glycol comprises 4 arms or 8 arms. The method of claim 1, wherein the integrin-binding moiety is a peptide. The method of claim 10, wherein the peptide comprises RGD. The method of claim 10, wherein the peptide comprises the sequence of any one of SEQ ID NOs:l-30, or any combination thereof. The method of claim 1 or 2, wherein the integrin-binding moiety is derived from vitronectin, tenascin-C, integrin-binding sialoprotein, dentin-matrix phosphoprotein, osteopontin, or any combination thereof. The method of claim 1 or 2, wherein the matrix further comprises a plasmin degradable peptide. The method of claim 1 or 2, wherein the high molecular weight hyaluronic acid has a molecular weight average of about 700 kDa and a listed range of about 500 kDa - about 750 kDa. The method of claim 1 or 2, wherein about 4% to about 6% of glucuronic acid moieties on the hyaluronic acid are thiolated. The method of claim 1, wherein the matrix is selected by a process comprising i. generating a plurality of matrix compositions having variations in porosity,

86 stiffness, high molecular weight hyaluronic content, degree of thiolation of the high molecular weight hyaluronic acid, integrin-binding sites, biodegradability, or any combination thereof, each of said matrix compositions is prepared by a method comprising a. combining thiolated, high molecular weight hyaluronic acid having about 4% to about 10% of glucuronic acid moieties thiolated, thiolated polyethylene glycol, norbornene-terminated polyethylene glycol, thiolated polymer comprising an integrin-binding moiety, plasmin-degradable peptide, or any combination thereof; and b. cross-linking the thiolated hyaluronic acid, thiolated polyethylene glycol and thiolated polymer comprising an integrin-binding moiety, ii. incubating the tumor cells in each of the plurality of matrix compositions; and iii. identifying a matrix composition in which the tumor cells exhibit one or both of maximal tumor growth and maximal tumor invasion, thereby selecting a matrix for the method of claim 1. . The method of claim 2, wherein the matrix is selected by a process comprising i. generating a plurality of matrix compositions having variations in porosity, stiffness, high molecular weight hyaluronic content, degree of thiolation of the high molecular weight hyaluronic acid, integrin-binding sites, biodegradability, or any combination thereof, each of said matrix compositions is prepared by a method comprising a. combining thiolated, high molecular weight hyaluronic acid having about 4% to about 10% of glucuronic acid moieties thiolated, norbornene-terminated polyethylene glycol, thiolated polymer comprising an integrin-binding moiety, plasmin-degradable peptide, or any combination thereof; and b. cross-linking the thiolated hyaluronic acid and thiolated polymer comprising an integrin-binding moiety, ii. incubating the tumor cells in each of the plurality of matrix compositions; and iii. identifying a matrix composition in which the tumor cells exhibit one or both of

87 maximal tumor growth and maximal tumor invasion, thereby selecting a matrix for the method of claim 2. The method of claim 1 or 2, wherein the tumor is a glioblastoma. The method of claim 1 or 2, wherein the matrix is configured to allow one or both of maximal growth of the tumor cells and maximal invasiveness of the tumor cells. The method of claim 1 or 2, wherein the matrix allows for maximal clustering of integrins with other receptors, including other integrin receptors, on the tumor cells. The method of claim 1 or 2, wherein before exposing the tumor cells to said chemotherapeutic agents, the matrix is optimized for properties that maximize one or both of growth of the tumor cells and invasion of the tumor cells. The method of claim 22, wherein said properties comprise one or more of matrix stiffness, high molecular weight hyaluronic acid concentration, degree of thiolation of the high molecular weight hyaluronic acid, concentration and selection of integrin binding peptide, porosity, biodegradability, and any combination thereof. The method of claim 1 or 2, wherein the matrix has a storage modulus between about 50 to about 2000 Pa. The method of claim 1 or 2, wherein the matrix has a pore size of up to about 13 nm. The method of claim 1 or 2, wherein growth of the tumor cells is determined by imaging, biochemical assay, luminescent assay, or assay for a reporter product. The method of claim 1 or 2, wherein invasiveness of the tumor cells is determined by imaging, biochemical assay, luminescent assay, or assay for a reporter product. The method of claim 26 or 27, wherein one or more visible or fluorescent labeled reagents or reporters are used to monitor the growth or invasiveness of the tumor cells. The method of claim 1 or 2, wherein tumor growth kinetics are determined over time. The method of claim 1 or 2, wherein an increase in the growth of the tumor cells after a certain time indicates develoμment of resistance of the tumor cells to said first chemotherapeutic agents after exposure for said time.

88 The method of claim 30, wherein develoμment of said resistance to the first chemotherapeutic agent is used to evaluate effects of a combination of said first chemotherapeutic agent with another one or more second chemotherapeutic agents on the develoμment of resistance. The method of claim 1 or 2, wherein the chemotherapeutic agent is an agent approved for treatment of the tumor, an agent approved for treatment of cancer other than the tumor, an agent approved for compassionate use, an agent in clinical trials for treatment of the tumor, an agent in clinical trials for treatment of cancer other than the tumor, or an approved or experimental agent used in combination with a chemotherapeutic agent for the tumor or for a cancer other than the tumor. A composition for evaluating growth or invasiveness of tumor cells for identifying potential chemotherapeutic agents, the composition comprising a matrix comprising: i. a high molecular weight hyaluronic acid at a concentration of about 0.25 wt% to about 2 wt%, wherein about 4% to about 10% of glucuronic acid moieties on the hyaluronic acid are thiolated; ii. a thiolated polyethylene glycol; and ii. a polymer comprising an integrin binding moiety; wherein the thiolated hyaluronic acid, the thiolated polyethylene glycol and the polymer comprising the integrin binding moiety are cross-linked. A composition for evaluating growth or invasiveness of tumor cells for identifying potential chemotherapeutic agents, the composition comprising a matrix comprising: i. a high molecular weight hyaluronic acid at a concentration of about 0.25 wt% to about 2 wt%, wherein about 4% to about 10% of glucuronic acid moieties on the hyaluronic acid are thiolated; and ii. a polymer comprising an integrin binding moiety; wherein the thiolated hyaluronic acid and the polymer comprising the integrin binding moiety are cross-linked.

89 The composition of claim 33 or 34, wherein the polymer comprising an integrin binding moiety comprises a norbornene-terminated polyethylene glycol, a maleimide- terminated polyethylene glycol or a vinyl sulfone terminated polyethylene glycol. The composition of claim 33 or 34, wherein the composition further includes: a. a maleimide polyethylene glycol or vinyl sulfone polyethylene glycol; b. a vinyl sulfone polyethylene glycol and a radical generator; or c. a norbornene-terminated polyethylene glycol and a radical generator. The composition of claim 36, wherein the radical generator is a photo-crosslinker. The composition of claim 37, wherein the photo-crosslinker is lithium phenyl-2,4,6- trimethylbenzoylphosphinate. The composition of claim 33, wherein the polyethylene glycol comprises multiple arms. The composition of claim 33 or 34, wherein the integrin-binding moiety is a peptide. The composition of claim 40, wherein the peptide comprises RGD. The composition of claim 40, wherein the peptide comprises the sequence of any one of SEQ ID NOs:l-30, or any combination thereof. The composition of claim 33 or 34, wherein the integrin-binding moiety is derived from vitronectin, tenascin-C, integrin-binding sialoprotein, dentin-matrix phosphoprotein, osteopontin, or any combination thereof. The composition of claim 33 or 34, wherein the high molecular weight hyaluronic acid has a molecular weight average of about 700 kDa and a listed range of 500kDa - 750kDa. The composition of claim 33 or 34, wherein about 4% to about 6% of glucuronic acid moieties on the hyaluronic acid are thiolated. The composition of claim 33 or 34, further comprising a plasmin-degradable peptide. The composition of claim 33, wherein the matrix comprises thiolated, high molecular

90 weight hyaluronic acid having about 4 % to about 6 % of glucuronic acid moieties thiolated, thiolated polyethylene glycol, norbornene-terminated polyethylene glycol, thiolated polymer comprising an integrin-binding moiety, plasmin-degradable peptide, or any combination thereof. The composition of claim 34, wherein the matrix comprises thiolated, high molecular weight hyaluronic acid having about 4 % to about 6 % of glucuronic acid moieties thiolated, norbornene-terminated polyethylene glycol, thiolated polymer comprising an integrin-binding moiety, plasmin-degradable peptide, or any combination thereof. The composition of claim 33 or 34, wherein the matrix has a storage modulus between about 50 to about 2000 Pa. The composition of claim 33 or 34, wherein the matrix has a pore size of up to about 13 nm. A method for treating a tumor in a patient comprising the steps of: a. selecting one or more first chemotherapeutic agents for treating the tumor in the patient according the method of claim 1 or 2; and b. administering said chemotherapeutic agents to the patient. The method of claim 51, wherein the tumor is a glioblastoma. The method of claim 51, wherein when resistance to the first chemotherapeutic agent is detected, treatment of said patient with said first chemotherapeutic agent is limited to a duration prior to said resistance is developed. The method of claim 53, wherein treatment for said patient is continued with a second chemotherapeutic agent. The method of claim 53, wherein the patient is treated with the first chemotherapeutic agent in combination with one or more chemotherapeutic agents that delay or prevent resistance to the first chemotherapeutic agent. The method of claim 51, wherein the chemotherapeutic agent is an agent approved for treatment of the tumor, an agent approved for treatment of a cancer other than the tumor,

91 an agent approved for compassionate use, an agent in clinical trials for treatment of the tumor, an agent in clinical trials for treatment of a cancer other than the tumor, or an approved or experimental agent used in combination with a chemotherapeutic agent for the tumor or for a cancer other than the tumor.