WO2017035315A1 - Procédés et dispositif pour la classification phénotypique de cellules basée sur le comportement migratoire - Google Patents

Procédés et dispositif pour la classification phénotypique de cellules basée sur le comportement migratoire Download PDF

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WO2017035315A1
WO2017035315A1 PCT/US2016/048575 US2016048575W WO2017035315A1 WO 2017035315 A1 WO2017035315 A1 WO 2017035315A1 US 2016048575 W US2016048575 W US 2016048575W WO 2017035315 A1 WO2017035315 A1 WO 2017035315A1
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cells
cell
migration
migratory
cancer cell
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WO2017035315A8 (fr
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Onur Kilic
Paula V. SCHIAPPARELLI
Alfredo QUINONES-HINOJOSA
Andre Levchenko
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The Johns Hopkins University
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
    • A61P35/00—Antineoplastic agents
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12M—APPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY; APPARATUS FOR CULTURING MICROORGANISMS FOR PRODUCING BIOMASS, FOR GROWING CELLS OR FOR OBTAINING FERMENTATION OR METABOLIC PRODUCTS, i.e. BIOREACTORS OR FERMENTERS
    • C12M3/00—Tissue, human, animal or plant cell, or virus culture apparatus
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
    • G01N33/5011—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics for testing antineoplastic activity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
    • G01N33/502—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics for testing non-proliferative effects
    • G01N33/5029—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics for testing non-proliferative effects on cell motility
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer

Definitions

  • the present invention relates generally to diagnosis and treatment of cancer, and more specifically to a device and methods for determining migratory phenotype signatures in a population of human cells.
  • Personalized medicine can benefit from patient-specific analysis of cell and tissue properties, especially if such tests are of prognostic value.
  • Aggressive cancers such as glioblastoma multiforme (GBM)
  • GBM glioblastoma multiforme
  • Genomic and proteomic profiling can provide a wealth of information about tumor samples, including cancer-causing abnormalities, specific mutations, and clinically relevant subclasses.
  • this information may not be easily interpretable or predictive of certain complex phenotypes, such as invasive growth and enhanced migratory cell dissemination.
  • aggressive cell migration can be a product of multiple and distinct combinations of genetic alterations, particularly in highly heterogeneous tumors, such as GBM.
  • GBM Aggressive cell migration and dispersal is common to GBM, helping the disease overcome standard treatments, including surgery, radio-, and chemotherapies.
  • individual GBM cells can spread from the primary tumor bulk, avoid detection, and reconstitute tumor masses in different areas of the body (e.g., form secondary tumor foci).
  • These migratory and invasive capacities are likely governed by a number of genetic and environmental variables. Therefore, there is a need to develop an experimental platform that would more realistically model the mechano-chemical cellular milieu, yet remain simple and accessible to allow practical, high throughput use.
  • the present invention is based on the seminal discovery that different migratory phenotypes are present in a tumor, and hence, one is able to provide phenotypic signatures that describe the tumor phenotype much more accurately than previous methods.
  • This information regarding the phenotypes is used for diagnostic purposes to better describe a patient’s disease and prognosis, to better predict disease progression, and to develop better targeted therapies that focus on subpopulations with aggressive phenotypes within the heterogeneous collection of cells that make up a tumor.
  • ECM extracellular matrix
  • the present invention is based on the ability to mimic cell migration through the 3D extracellular matrix in vivo: instead of the standard approach of studying migration on 2D matrices, one mimics the in vivo migration on a platform that biases a 1D migratory mechanism through fibrillary-like structures.
  • a method to classify a cell in a heterogeneous population of cells including providing a surface including a plurality of parallel ridges, wherein the ridges have a depth between about 50 to 1000 nm and a width between about 50 and 1000 nm; applying at least one attachment molecule to the surface, wherein the molecule is selected from the group consisting of collagen, fibronectin, laminin, poly-D-lysine, poly-L- ornithine, proteoglycan, vitronectin, and polysaccharide; contacting a plurality of living cells with the surface for a time and under conditions to allow the cells to attach to the surface, wherein a migration speed or migration direction of the attached cells is recorded over a time period; and classifying the cells based on their migration speed, migration direction, and/or the change in speed or direction over time.
  • the cells are cancer cells; the cancer cells are selected from the group consisting of carcinoma, sarcoma, lymphoma, leukemia, germ cell tumor, and glioblastoma; the cells are contacted with at least one agent selected from the group consisting of drugs, natural compounds, toxins, nanoparticles, nucleic acids, viruses, bacteria and other microbes, mammalian cells, hormones, growth factors, and cytokines prior to or simultaneous with the step of contacting the cells with the surface; and/or the growth factor is platelet-derived growth factor.
  • the cells are classified as a strong responder or a weak responder based on speed of migration; or more specifically, the cells are classified as a strong responder or a weak responder based on a speed of migration of 50% or less of the cells that have speeds of migration faster than all other cells.
  • a method for determining an effect of an agent on a cell attached to a surface wherein the surface includes a plurality of parallel ridges including contacting the cells with platelet-derived growth factor; and measuring a change in migration speed and/or migration direction of cells, thereby classifying the cells as a strong or a weak responder based on a speed of migration of 50% or less of the cells that have speeds of migration faster than all other cells.
  • a method for classifying a cancer cell including recording a migration speed or a migration direction of a cell over a period of time; contacting the cell with an agent, wherein the agent is selected from the group consisting of a drug, a natural compound, a toxin, a nanoparticle, a nucleic acid, virus, bacteria, mammalian cell, a biological ligand, a hormone, a growth factor, and a cytokine; and classifying the cell based on migration speed, migration direction, and/or a change of speed or direction over time.
  • the cancer cells are glioblastoma cells; the growth factor is platelet-derived growth factor; and/or the cells are classified as a strong responder or a weak responder based on a speed of migration of about 25% of the cells that have speeds of migration faster than other cells.
  • a method of phenotyping a cancer cell sample including placing a sample including a cancer cell onto a surface, wherein the surface includes a plurality of parallel ridges; and assessing at least one migratory characteristic of the cancer cell, thereby phenotyping the cancer cell sample based on the migratory characteristic.
  • the cancer cell is selected from the group consisting of carcinoma cells, sarcoma cells, lymphoma cells, leukemia cells, germ cell tumor cells, and glioblastoma cells; the cancer cell is a glioblastoma cell; the glioblastoma cell is obtained from a resected brain tissue of a patient having glioblastoma multiforme; the surface further includes a molecule selected from the group consisting of a collagen, fibronectin, laminin, poly-D- lysine, poly-L-ornithine, proteoglycan, vitronectin, and polysaccharide; the parallel ridges are spaced from each other by substantially uniform inter-ridge distances; the parallel ridges have heights of about 500 nanometers, widths of about 350 nanometers, and inter-ridge distances of about 1.5 micrometers; the migratory characteristic of the cancer cell is observed using an optical imaging system in a time-resolved mode
  • the migratory characteristic includes a speed that corresponds to a ratio of migration distance to migration time; the migratory characteristic includes a directionality that corresponds to a ratio of migration distance parallel with a ridge to migration distance perpendicular to a ridge; the migratory characteristic includes a persistence that corresponds to a ratio of shortest migration distance between a start point and an end point to total migration distance between the start point and the end point; the sample includes a plurality of cancer cells; the cancer cells are classified based on a migratory characteristic of a subset of the cancer cells; the cancer cells are classified based on a speed of about a quarter of the cancer cells that are faster moving than any other cancer cells; the cancer cells are classified based on a change in the migratory characteristic between the migratory characteristic of a subset of a test cancer cell sample contacted with an agent and the migratory characteristic of a subset of a control cancer cell sample not contacted with the agent; the agent is platelet
  • a method of identifying an agent which reduces the invasiveness of a cancer cell including contacting a platelet-derived growth factor with a sample containing a cancer cell to obtain a processed cancer cell sample; contacting an agent with the processed cancer cell sample to obtain a treated cancer cell sample; placing the treated cancer cell sample onto a surface including a plurality of parallel ridges, thereby allowing the cancer cell to migrate on the surface; determining at least one migratory characteristic of the cancer cell; and determining that the agent reduces invasiveness of the cancer cell if the migratory characteristic of the cancer cell from the treated sample and a migratory characteristic of a cancer cell from an unprocessed and untreated cancer cell sample are both less than or greater than a migratory characteristic of a cancer cell from a processed but untreated cancer cell sample.
  • the cancer cell is selected from the group consisting of a carcinoma cell, sarcoma cell, lymphoma cell, leukemia cell, germ cell tumor cell, and glioblastoma cell; the cancer cell includes a glioblastoma cell; the glioblastoma cell is obtained from a marginal area of a glioblastoma tumor in a brain of a patient having glioblastoma multiforme; the surface further includes a molecule selected from the group consisting of a collagen, fibronectin, laminin, poly-D-lysine, poly-L-ornithine, proteoglycan, vitronectin, and polysaccharide; the parallel ridges are spaced from each other by uniform inter-ridge distances; the parallel ridges have heights of about 500 nanometers, widths of about 350 nanometers, and inter-ridge distances of about 1.5 micrometers; the cells are placed onto the surface through a multi-well dish; the
  • a method of identifying an agent that reduces aggressiveness of glioblastoma cells including contacting a platelet-derived growth factor with a sample containing a plurality of glioblastoma cells to obtain a processed glioblastoma cell sample; contacting an agent with the processed glioblastoma cell sample to obtain a treated glioblastoma cell sample; placing the treated glioblastoma cell sample onto a surface including a plurality of parallel ridges having uniform inter-ridge distances, thereby allowing the glioblastoma cells to migrate on the surface; determining an average speed of a subset of the treated glioblastoma cells, wherein the speed corresponds to a ratio of migration distance to migration time, wherein the subset includes at most half of the cells, and wherein the subset includes cells each of which is faster moving than all treated glioblastoma cells not within the subset; and identifying the agent as one that reduces aggressive
  • the disclosure provides a nanopatterned substrate having a plurality of substantially parallel ridges, each ridge having a height of between about 400 to 600 nm and a width of between about 300 to 1000 nm. In some embodiments, each ridge has a height of about 500 nm, a width of about 350 nm, and each ridge is separated by a groove of about 1500 nm.
  • the substrate is planar and composed of silicon, silicon dioxide, a polymer or quartz.
  • the disclosure provides a system for measuring cell motility.
  • the system includes the substrate of the disclosure and a detector for detecting movement of a cell on the substrate.
  • the detector is an optical imaging device, such as a microscope.
  • the system may optionally include a computing device having functionality to analyze cell motility data.
  • the disclosure provides a kit which includes the substrate of the disclosure, a platelet-derived growth factor receptor alpha (PDGFR ⁇ ) ligand, and optionally, instructions for performing cellular analysis along with appropriate packaging.
  • PDGFR ⁇ ligand is platelet-derived growth factor (PDGF).
  • a method for reducing invasiveness of a cancer cell including contacting the cell with an agent suspected of affecting invasiveness of the cell and determining a migration speed of the cell before and after contact with the agent in the substrate of the disclosure, wherein a reduction in migration speed is indicative of an agent that reduces the invasiveness of the cancer cell.
  • a method of reducing the time to recurrence after resection of a tumor containing a cancer cell including determining a migration speed of the cell before and after contact with an agent in the substrate of the disclosure, wherein a reduction in the migration speed is indicative of an agent that reduces the time to recurrence after resection of the tumor.
  • the present invention provides for high-throughput analysis for tumor single-cell migration; is more sensitive and physiologically relevant than classical screening assays; detects glioma cells showing inter- and intra-patient differential sensitivity to platelet- derived growth factor (PDGF); and demonstrates how glioma cell sensitivity to PDGF correlates with tumor recurrence and tumor location.
  • PDGF platelet- derived growth factor
  • FIGS 1A-1E Phenotypic Screening of Heterogeneous Cell Populations Recapitulates the Microenvironment of Migrating Cells.
  • A Cells with heterogeneous phenotypes are isolated from a patient’s tumor (MRI of tumor for sample GBM 612).
  • B The cells are seeded on a platform that has a multi-well structure, allowing testing of multiple conditions, and is an on-glass technology, allowing direct imaging of migration and morphology with single-cell resolution.
  • C Images show that GBM 612 cells migrating on the platform have similar morphology and migration speed compared to GBM 612 cells migrating in ex vivo human brain tissue and 3D Matrigel.
  • the platform provides important information on the migration response of heterogeneous cell populations.
  • GBM 612 samples show a subpopulation of cells whose migration is fast and stable over time. Additional experiments (not shown) indicate that even for samples having the same average migration speed, a detailed analysis with the platform can reveal that some samples have fast moving outliers, and a timelapse data obtained through the platform can show that there are significant differences at the beginning, which would be masked by averaging of the data. These details can have important implications for the disease.
  • Figures 2A-2D Migratory Response to PDGF Correlates with Tumor Characteristics Both In vitro and In vivo (part 1).
  • B Western blot for PDGFR ⁇ protein expression in GBM samples grown as adherent or spheroid cultures.
  • C and D Quantification of migration speed of cell lines GBM 253 (C) and GBM 276 (D) in the presence of PDGF-AA (50 ng/ml) and imatinib (30 ⁇ M) (n ⁇ 80 cells, mean + SEM, ⁇ p ⁇ 0.05, ⁇ p ⁇ 0.01, ⁇ p ⁇ 0.001, ⁇ paired against control group, #paired against PDGF group, Kruskal-Wallis one-way ANOVA on ranks, Dunn’s method) (asterisks indicate pairing against the control group, hash marks indicated pairing against the PDGF group).
  • FIGS 3A-3F Migratory Response to PDGF Correlates with Tumor Characteristics Both In vitro and In vivo (part 2).
  • a and B Migration speed of GBM 276 for the slowest (A) and fastest (B) quartile of the cells (i.e., 25% of the slowest- and fastest- moving cells, respectively), showing that only a subpopulation responds to PDGF.
  • C Quantification of migration measured by alignment of GBM 276 cells ( ⁇ p ⁇ 0.05, Kruskal- Wallis one-way ANOVA on ranks, Dunn’s method) (asterisks indicate comparisons to all other conditions).
  • FIGS 4A-4C Information on Migration Speed Reveals Important Differences among Patient Samples in Response to PDGF (part 1).
  • A Analyzing the fastest quartile (GBM 499) reveals that the subpopulations display a significant response to PDGF. In contrast, for the whole population, there is no significant response.
  • B Migration speed time lapse demonstrates that sample GBM 501 does not respond to PDGF at all times (compared to GBM 609); on average, however, both samples respond significantly to PDGF.
  • GBM 630 and GBM 544 samples display a significant increase in average migration speed ( ⁇ p ⁇ 0.05, ⁇ p ⁇ 0.01, ⁇ p ⁇ 0.001, Wilcoxon rank-sum test). However, GBM 630 has a significantly larger number of fast outliers, while GBM 544 displays a uniform increase in speed.
  • Figure 5 Information on Migration Speed Reveals Important Differences among Patient Samples in Response to PDGF (part 2).
  • the platform allows patient sample classification based on multiple characteristics, permitting a better description of the heterogeneity of the samples.
  • the samples were grouped based on whether there is a significant increase (p ⁇ 0.05, Wilcoxon rank-sum test) in average migration speed in response to PDGF (group I) and whether this significant increase is persistent over time (group II).
  • groups are grouped based on the number of outliers (cells faster than the fastest cells in the control group) with a threshold of 4 cells (5%, for a total of 80 cells) (group III).
  • the PDGFR ⁇ protein expression level (group IV) and the subclass of the GBM cells (group V) are also provided.
  • Figures 6A-6B GBM Migratory Response to PDGF Correlates with Patient Tumor Characteristics (part 1).
  • the p values were calculated using a two-tailed log-rank (Mantel-Cox) test.
  • Figures 7A-7F GBM Migratory Response to PDGF Correlates with Patient Tumor Characteristics (part 2).
  • A–D Magnetic Resonance Imaging (MRI) scans of patients with tumors from the unresponsive group (A and B) and the responsive group (C and D).
  • F Time to recurrence for GBM samples separated into low-directionality ( ⁇ 3.25) and high-directionality ( ⁇ 3.25) groups (n ⁇ 4, mean + SEM, Wilcoxon rank-sum test) (the threshold of 3.25 was determined using linear discriminant analysis).
  • Figures 8A-8G Multi-well, nanopatterned platform induces changes in cell morphology and migration (part 1).
  • A SEM images of topographic pattern with parallel ridges 350 nm wide, 350 nm high, spaced 1.5 ⁇ m apart. Box (left) indicates higher magnification image (right)
  • B SEM images of human GBM sample 318 cells cultured on nanogroove pattern for 24 hours in vitro. Box as in A.
  • C Schematic describing construction of multi-well, nanopatterned device, wherein multiple conditions (red and yellow colors) can be observed simultaneously.
  • D Bright-field images comparing cells migrating on a smooth surface vs. a nanopatterned substrate of the present invention.
  • E Quantitative comparison of average cell area and spindle shape (n ⁇ 50 cells, mean + s.e.m., *P ⁇ .05, Mann-Whitney Rank Sum Test).
  • F Quantitative comparison of migration measured by speed, alignment, and persistence (n ⁇ 60 cells, mean + s.e.m., *P as in E).
  • G Instantaneous migration speed quantified as a function of time (n ⁇ 60 cells).
  • Figures 9A-9G Multi-well, nanopatterned platform induces changes in cell morphology and migration (part 2).
  • A-B Quantitative comparison of average cell area (A) and spindle shape (B) of GBM 253 (n ⁇ 45 cells, mean + s.e.m., *P ⁇ .05, Mann-Whitney Rank Sum Test).
  • C Bright-field images of GBM 276 cells cultured on smooth PUA surface (left) and nanogroove pattern (right) for approximately 24 hours in vitro.
  • A-B Quantification of migration measured by speed, alignment, and persistence of GBM 318 cells cultured on a smooth surface (A) or a nanopatterned surface of the present invention (B) coated with varying laminin concentrations. Values normalized to 5 ⁇ g/mL condition. (n ⁇ 50 cells, mean + s.e.m., *P ⁇ .05, Kruskal-Wallis One Way ANOVA on Ranks, Dunn’s Method. Brackets denote pairwise comparisons. Asterisks without brackets indicate comparisons to all other conditions).
  • Figures 11A-11B Nanopatterned platform enables higher sensitivity to soluble and immobilized factors (part 2).
  • A-B Quantification of migration measured by speed and persistence of GBM 318 cells cultured on a smooth surface (A) or a nanopatterned surface of the present invention (B) in the presence of varying PDGF concentrations. Values normalized to control condition. (n ⁇ 75 cells, mean + s.e.m., *P as in A-B).
  • FIGS 12A-12D Nanopatterned platform enables higher sensitivity to soluble and immobilized factors (part 3).
  • A-B Quantification of migration speed of GBM 276 cells cultured on smooth surface (A) or nanopatterned surface (B). Comparisons made for varying laminin concentrations (n ⁇ 75 cells, mean + s.e.m., *P ⁇ .05, Kruskal-Wallis One Way ANOVA on Ranks, Dunn’s Method).
  • C Quantification of migration speed of GBM 630 cells (n ⁇ 60 cells, mean + s.e.m., *P ⁇ .05, Kruskal-Wallis One Way ANOVA on Ranks, Dunn’s Method. Brackets denote pairwise comparisons. Asterisks without brackets indicate comparisons to all other conditions).
  • D Instantaneous migration speed of GBM 630 quantified as a function of time shows that the increase is not time dependent (n ⁇ 60 cells).
  • Figures 13A-13E Effect of PDGF to migratory response and in vivo tumor formation (part 1).
  • B Western blot for PDGFR ⁇ protein expression in GBM samples 549, 609, and 630.
  • C Western blot for PDGFR ⁇ protein expression in additional responding and non-responding GBM samples.
  • D Migration speed of GBM 276 cells cultured on nanopatterned platform in the presence of Imatinib. Values normalized to control condition.
  • Figures 15A-15B Genotypic information does not correlate with time to recurrence or tumor location (part 1).
  • B Kaplan-Meier curve depicting survival with respect to PDGF responsiveness.
  • Figures 16A-16D Genotypic information does not correlate with time to recurrence or tumor location (part 2).
  • A-B Kaplan-Meier curves depicting time to recurrence among patients with tumors with High and Low PDGFR expression (A) and Mesenchymal or Proneural Sub-type (B).
  • Figure 17 Flow Chart disclosing classifying tumors for diagnostic or prognostics using cell-migration data.
  • Figure 18 Flow Chart disclosing determining the effect of an agent. DETAILED DESCRIPTION OF THE INVENTION
  • Standard methods for assessing a cancer such as glioblastoma suffer from at least two problems: (1) low signal to noise ratio, due to majority of cancer cells not being determinative of overall cancer properties, and (2) incorrect signal, due to the commonly used 2D surfaces not sufficiently mimicking the natural 3D environment.
  • the present invention solves, inter alia, these problems by mimicking the 3D environment with a platform that allows migration on 1D fibrillary surfaces and by allowing for detection of information at a single-cell level.
  • various embodiments provide for assessments using agents (e.g., platelet-derived growth factor), and for improved prognostic/diagnostic methods that rely on a defined subset of cancer cells characterized by a variety of metrics gleaned from the disclosed platforms and processes.
  • the present invention employs engineered nano-scale cell adhesion substrata to construct fibrillar surfaces that mimic topographical signals of natural ECM.
  • the provided platform provides a more representative model for studying the migration of glioma cells. This platform achieves far greater resolution and sensitivity in migration analyses than do commonly used methods. More importantly it can provide highly informative, patient specific results regarding tumor progression in vivo. Previous studies using nano-fabricated platforms have not evidenced such enhancements over existing approaches or obtained similar, medically relevant information.
  • PDGF non-responding tumors were predominantly derived from the temporal lobe could suggest that PDGF signaling is less critical to tumor progression in certain regions of the brain.
  • the information provided through the presented platform can be particularly useful in prognostic analyses of tumor samples at the time of surgery. Direct access to individual cell migration analysis would potentially gain critical importance for future treatment modalities.
  • the present invention demonstrates that high-throughput, single cell-resolution phenotypic screening is of great value in the diagnostic and prognostic analysis of human cancer samples. Furthermore, the present invention demonstrates that this analysis can be achieved by using a highly versatile, and convenient platform for interrogating migration phenotypes of primary GBM cells in the context of diverse environmental parameters, including different medium and ECM compositions. Using this assay, surprisingly, it was found that the clinical outcome of GBM tumors strongly correlated with the combined responsiveness of a subset of the cell population to two environmental inputs: the aligned surface fibers mimicking the ECM nano-topography and a growth factor, PDGF.
  • the ability to observe this responsiveness at the single cell level and thus examining different cell sub- populations was useful for the success of this phenotypic analysis, revealing correlations with such critical prognostic tumor characteristics as the time of recurrence after resection.
  • the present invention in addition to providing further insights into the mechanisms of invasive glioblastoma spread, strongly indicate considerable clinical, prognostic uses of the disclosed phenotypic analysis test.
  • the experimental platform described in the present invention has important advantages over other phenotypic analysis platforms designed to assay cell migration or invasion.
  • trans-well migration analysis Another relatively simple method directly assaying cell invasion, for which a multi-well design has also been described, usually requires at least an order of magnitude greater numbers of cells than the method described herein. More importantly, classical trans-well assays fail to yield the information on migration and morphology of each individual cell only showing information at the end-point, not taking in account the heterogeneity of the tumors, high speed outlier cells or time- dependent responses. This missing information can be critical in the analysis of human tumors.
  • Patterning the nano-topographic features in the form of parallel nano-scale ridge arrays had an added advantage of simplifying the analysis of cell migration, as cells moved primarily in one-dimensional paths consistent with the orientation of this mechanical cue.
  • This aspect of the experimental analysis makes the platform described here easy to use in both academic and clinical settings.
  • the present invention can provide an important prognostic tool, with benefits that include high-throughput label-free analysis with single-cell resolution, low demand for precious primary cell samples, and better physiological relevance compared to other migration assays.
  • the present invention provides for methods that classify, phenotype, or determine a property of cancer cells.
  • the methods detect an effect of an agent (e.g., drugs, natural compounds, herbal compounds, plant-based compounds, mineral-based compounds, marine-based compounds, chemically synthesized compounds, toxins, nanoparticles, nucleic acids, viruses, bacteria, archaea, eukaryotic microbes, mammalian cells, hormones, enzymes, growth factors, cytokines, chemokines, antibiotics, antibodies, antibody fragments, synthetic antibodies, vaccines, genetically- engineered biologics) on cancer cells.
  • an agent e.g., drugs, natural compounds, herbal compounds, plant-based compounds, mineral-based compounds, marine-based compounds, chemically synthesized compounds, toxins, nanoparticles, nucleic acids, viruses, bacteria, archaea, eukaryotic microbes, mammalian cells, hormones, enzymes, growth factors, cytokines, chemokines, antibiotics, antibodies,
  • the methods allow determination of the locations in the brain (e.g., frontal lobe, temporal lobe) of the tumors from which the cells had originated. In some embodiments, the methods allow prediction of time to recurrence of the cancer after a surgical resection. In other embodiments, disclosed methods allow identifying an agent that reduces the invasiveness or aggressiveness of a cancer cell. Some of the disclosed methods allow observing cells at a single-cell resolution.
  • Particular methods allow observing cells (e.g., at a single-cell resolution) using an optical imaging system (e.g., bright-field microscopy, fluorescence microscopy, dark-field microscopy, confocal microscopy) in a time-resolved mode (e.g., in a way that generates a time vs. location trajectory for an observed cell).
  • an optical imaging system e.g., bright-field microscopy, fluorescence microscopy, dark-field microscopy, confocal microscopy
  • a time-resolved mode e.g., in a way that generates a time vs. location trajectory for an observed cell.
  • Various device setups allow observing multiple groups of cells at the same time (e.g., via using a multi-well dish over the surface having the cells).
  • the methods encompassed by the present invention are applicable to various cancers, such as aggressive cancers, which may be heterogeneous and infiltrative.
  • An example cancer to which some of the methods are applicable is glioblastoma multiforme (GBM).
  • GBM glioblastoma multiforme
  • Other examples include carcinoma, sarcoma, lymphoma, leukemia, and germ cell tumor.
  • Some of the embodiments rely on a platform that has multiple parallel ridges.
  • the ridges may be separated from each other by substantially uniform inter-ridge distances.
  • the ridges have heights of about 500 nanometers, widths of about 350 nanometers, and inter-ridge distances of about 1.5 micrometers.
  • Ridge heights can take on other values, such as greater than or equal to 250, 300, 350, 400, 450, 550, 600, or 650 nanometers.
  • ridge widths can take on other values, such as greater than or equal to 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, or 600 nanometers.
  • the inter-ridge distances can be varied as well. For example, they may be greater than or equal to 1.0, 1.1, 1.2, 1.3, 1.4, 1.6, 1.7, 1.8, 1.9, or 2.0 micrometers.
  • the surface of the platform or device is coated with a molecule.
  • the molecule can be an attachment molecule.
  • An example molecule that can be used for this purpose is laminin.
  • Other such examples include collagens, fibronectins, poly- D-lysine, poly-L-ornithine, proteoglycans, vitronectin, polysaccharides, heparan sulfate, keratan sulfate, chondroitin sulfate, keratin sulfate, integrins, cadherins, selectins, immunoglobulins, glycosaminoglyclans, hyaluronic acid, elastin.
  • the molecule may be hemicellulose, pectin, extension, cellulose, and/or a biofilm component. Multiple molecules can be used together on the surface in some embodiments.
  • the present invention provides for methods that include detection of a migratory characteristic.
  • Migratory characteristic is a property derived from an observation of cells that migrate on a platform.
  • the migratory characteristic which may ultimately be used to estimate a time to recurrence, in some embodiments is directionality (also referred to as alignment).
  • Directionality can be measured by taking a ratio of a distance travelled parallel to a ridge and a distance travelled perpendicular to a ridge.
  • the distances in this or other embodiments, may be scalar distances (integrated along the path) or vectorial distances (the shortest straight line distance between the start and end points).
  • the distances in this or other embodiments, can be measured for a defined stretch of the platform, or for a defined time segment.
  • an average directionality of a first sample that is higher than that of a second sample indicates that the first sample has a longer time to recurrence than the second sample.
  • the migratory characteristic in various embodiments, can be obtained as an average of a population of cells. For example, it may be an average of the full group of cells, of half the cells, or a quarter of the cells. In particular, the migratory characteristic may be obtained as the average migratory characteristic of about 100%, 95%, 90%, 85%, 80%, 75%, 70%, 65%, 60%, 55%, 50%, 45%, 40%, 35%, 30%, 25%, 20%, 15%, 10%, or 5% of the cells. Other incremental percentages of cells between these values are also encompassed within embodiments of the present invention.
  • the migratory characteristic is persistence.
  • Persistence can be obtained as a ratio of the shortest migration distance between the start and end points and the total migration distance. It can also be defined with respect to a limited stretch of the platform or a limited time segment. In certain embodiments, a higher persistence of a first sample compared to that of a second sample indicates that the first sample has a shorter time to recurrence than the second sample. As in assessments of directionality, persistence can be obtained as an average of a group of cells.
  • the migratory characteristic is speed or is speed-based.
  • Cells may be classified into groups (e.g., groups of 2, 3, 4, or more) based on a migratory characteristic that is based on speed.
  • An assessment of speed can take many forms.
  • the speed-based migratory characteristic is obtained in the form of a change with respect to an agent.
  • a speed-based characteristic may be based on an average speed obtained from cells treated with PDGF as compared to an average speed obtained from cells not treated with PDGF.
  • the migratory characteristic is a percentage increase due to an agent in average migration speed of a group of cells.
  • groups of cells may range from 100% of the cells to a subset, such as about 25% of the cells.
  • the migratory characteristic is the percent of time when migration speed is increased due to an agent in the group of cells.
  • the migratory characteristic is the percent of cells in an agent-treated sample that are faster than a set of cells (e.g., 100%, 95%, 90%, 85%, 80%, 75%) in a sample not treated with the agent.
  • a consensus is taken by considering more than one of these migratory characteristics. As an example, one may bin (e.g., separate into two groups, such as agent-responsive and agent-nonresponsive) cancer cells by classifying them as below/above a threshold migratory characteristic, and then classify those that consistently are responsive to an agent according to different migratory characteristics as responsive, and those that are not responsive to an agent according to different migratory characteristics as non-responsive.
  • the threshold for a percentage increase in average migration speed can take many values, such as 75%, 70%, 65%, 60%, 55%, 50%, 45%, 40%, 35%, 30%, and 25%.
  • the threshold for a percent of time when migration speed is increased can take many values, such as 75%, 70%, 65%, 60%, 55%, 50%, 45%, 40%, 35%, 30%, and 25%.
  • the threshold for the percent of outliers faster than a group of cells in the control group can also take multiple values, such as 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, and 2%.
  • a speed-based migratory characteristic can also be used to determine the location in the brain of the tumor from which the cells originated.
  • a consensus grouping e.g., binning
  • the responsive cells would be determined to have been located at the frontal lobe of a brain.
  • the nonresponsive cells would be determined to substantially have been located at the temporal lobe of a brain.
  • migratory trajectories are recorded: a first one for cancer cells that are neither processed with a growth factor nor treated with a candidate agent; a second one for cancer cells that are processed (e.g., mixed in a solution together) with a growth factor (e.g., PDGF); and a third one for cancer cells that are both processed with a growth factor and treated with the candidate agent (e.g., a drug that is suspected of reducing the invasiveness of cancer cells).
  • a growth factor e.g., PDGF
  • the candidate agent would be identified as one that reduces the invasiveness (or aggressiveness or time to recurrence) of the tumor if it reverses the effects of the growth factor. For example, for an aggressive tumor of glioblastoma cells, speed-based metrics are expected to increase in processed cells (i.e., the processed cells would have higher speeds than unprocessed untreated cells). In that scenario, if an agent reduces the speed of the processed cells (i.e., if the migration speeds of both the unprocessed untreated cells and the processed treated cells are less than the migration speeds of the processed cells), one may infer that the agent reduces the invasiveness of the cancer cell.
  • migratory characteristics such as directionality and persistence
  • a growth factor such as PDGF and a candidate agent
  • the cancer cells may be obtained from a resected brain tissue of a patient having a form of cancer (e.g., an aggressive cancer, such as glioblastoma).
  • the cells are obtained from a marginal area of a glioblastoma tumor in the brain of a patient having GBM.
  • Figures 17 and 18 illustrate some of the methods described herein that make use of the migration of cells on the disclosed platforms. Various details of the present invention can be understood more clearly in light of the following examples.
  • GBM 221, GBM 253, GBM 276, GBM 318, GBM 499, GBM 501, GBM 544, GBM 549, GBM 567, GBM 609, GBM 612, GBM 626, GBM 630, and GBM 854) were derived from primary intraoperative tissues of patients undergoing surgery. Tissue donors received no treatment before surgery.
  • GBM Glioblastoma
  • IRB Institutional Review Board
  • Brain tumor samples GBM 221, GBM 253, GBM 276, GBM 318, GBM 499, GBM 501, GBM 544, GBM 549, GBM 567, GBM 609, GBM 612, GBM 626, GBM 630, and GBM 854 were derived from primary intraoperative tissues of patients undergoing surgery for glioblastoma. Tissue donors received no treatment prior to surgery. All tissue samples were pathologically confirmed as glioblastoma.
  • Adherent GBM cells were cultured in Dulbecco's Modified Eagle Medium: Nutrient Mixture F-12 containing 2 mM L-glutamine, with added 50 U mL -1 penicillin, 50 mg mL -1 streptomycin, and 10% fetal bovine serum (Invitrogen).
  • Spheroids were cultured in Dulbecco's Modified Eagle Medium: Nutrient Mixture F-12 containing 2 mM L-glutamine, with added 50 U mL -1 penicillin, 50 mg mL -1 streptomycin, supplemented with B27, 20 ng mL -1 endothelial growth factor (EGF), and 20 ng mL -1 fibroblast growth factor (FGF).
  • Dulbecco's Modified Eagle Medium Nutrient Mixture F-12 containing 2 mM L-glutamine, with added 50 U mL -1 penicillin, 50 mg mL -1 streptomycin, supplemented with B27, 20 ng
  • topographic nanopatterned substratum consisting of parallel ridges 350 nm wide, 500 nm high, spaced 1.5 ⁇ m apart, was fabricated onto glass coverslips as previously described (Kim, D.-H., Han, K., Gupta, K., Kwon, K.W., Suh, K.-Y., and Levchenko, A., Mechanosensitivity of fibroblast cell shape and movement to anisotropic substratum topography gradients, Biomaterials 30, 5433–5444 (2009); Kim, D.-H., Seo, C.-H., Han, K., Kwon, K.W., Levchenko, A., and Suh, K.-Y., Guided cell migration on microtextured substrates with variable local density and anisotropy, Adv.
  • the PUA precursor was dispensed onto the substrate, and a previously-constructed PUA mold was directly placed onto the surface.
  • Glioma cells migrate adjacent to elongated ECM fibers and blood vessels. These ECM-rich structures can range from 20 nm in diameter, e.g., collagen fibrils, to several microns across, e.g., myelinated axons. In this study, an intermediate ridge size of a few hundred nanometers was used to capture these different length scales.
  • nanopattern-coated glass coverslips were irreversibly bonded to modified Nunc®uLabTek®eII Chamber Slide (cat. no. 154534) using biocompatible medical adhesive. Prior to attachment, pattern-coated glass coverslips were washed with 70% and 100% ethanol (EtOH), and allowed to air dry in a sterile environment. During and after construction, multi-well, nanopattern devices were maintained under sterile conditions.
  • Nanoridged substrata were coated with poly-D-lysine (10 ⁇ g ml -1 ) for 15 minutes and mouse laminin (from 10 to 140 ⁇ g ml -1 ) for 1 hour.
  • the laminin was based on Engelbreth-Holm-Swarm murine sarcoma (basement membrane), Sigma (cat. L2020).
  • Dulbecco's Modified Eagle Medium Nutrient Mixture F-12 containing 2 mM L-glutamine, with added 50 U mL -1 penicillin, 50 mg mL -1 streptomycin. Where indicated, media contained 10% fetal bovine serum (Invitrogen) or alternatively, Platelet-Derive Growth Factor-AA (PDGF-AA) (LC Laboratories) at specified concentrations.
  • PDGF-AA Platelet-Derive Growth Factor-AA
  • Alignment to the nanoridge pattern was calculated by dividing the distance moved parallel to the ridges, by the distance moved perpendicular to the ridges. Averages of cell populations were calculated from at least 60 cells. Persistence distinguishes random, exploratory motility from continuous motion in a particular direction, a critical migratory mode for tumor dispersal. Alignment describes how strongly cells interact with the underlying substrate. Both spindle shape factor and alignment correlate with the structure and strength of cell-substrate adhesion complexes, which are critical regulators of cell motility and morphology.
  • Platelet-derived growth factor-AA ligand (PDGF-AA) was purchased from R&D Systems (10 ⁇ l) and reconstituted in 500 ⁇ l of 0.1% BSA.
  • Imatinib, Methanesulfonate Salt was purchased from LC Laboratories.
  • a 10 mM stock solution was dissolved in distilled water and stored at -20 oC, protected from light. Dilutions of the stock for both PDGF and Imatinib were prepared for use in cell culture medium and added directly to the cells when needed.
  • PCR products were analyzed on a 1.5% agarose gel (Invitrogen) containing SYBR® Safe DNA gel stain (Invitrogen) and imaged with Gel Logic® 100 Imaging System (Kodak). Quantitative RT-PCR was performed using SYBR® Green PCR Master Mix (Applied Biosystems) and 7300 Real Time® PCR Systems (Applied Biosystems).
  • the thermal cycling conditions were as follows: 50 °C for 2 minutes, 95 °C for 10 minutes followed by 40 cycles of 95 °C for 15 seconds, 60°C for 30 seconds, 72 °C for 30 seconds and finalized with 72 °C for 10 minutes.
  • GAPDH was amplified as endogenous control.
  • the sequence of PDGF Receptor- ⁇ primers employed is: sense, 5’- CCT GGT CTT AGG CTG TCT TCT -3’ (SEQ ID NO: 1); antisense, 5’- GCC AGC TCA CTT CAC TCT CC -3’ (SEQ ID NO: 2).
  • the GAPDH primers’ sequence is: sense, 5’- CAT GAG AAG TAT GAC AAC AGC CT -3’ (SEQ ID NO: 3); antisense, 5’- AGT CCT TCC ACG ATA CCA AAG T -3’ (SEQ ID NO: 4).
  • Spheroid and adherent cells were grown on cover slips.
  • the cells were fixed with 4% paraformaldehyde for 30 minutes at room temperature and permeabilized with PBS containing 0.1% Triton X-100® for 5 minutes.
  • the cells were incubated overnight with primary antibodies for PDGF Receptor alpha (1:100; Santa Cruz) and then incubated with the appropriate secondary antibody conjugated with fluorescent dye (1:500) for one hour.
  • Cells were subsequently stained against DAPI (1:200).
  • Coverslips were mounted with Aquamount®. 15-20 spheroids were placed in DMEM/F12 without growth factors for 18 hours and then exposed to PDGF-AA ligand for 24 hours.
  • Total cellular protein was extracted using NE-PER Nuclear and Cytoplasmic Extraction Reagents kit according to the manufacturer’s instructions (Thermo Scientific) containing protease (Roche) and phosphatase inhibitor (Thermo). Protein concentration was determined using the Bradford protein quantification method (Biorad Protein Assay, Biorad). SDS-PAGE was performed with 25 pg total cellular protein per lane using 4-12 % gradient Tris-glycine gels. The primary antibodies used were as follows: anti PDGFR-alpha (1:200; Santa Cruz); phospho-PDGFR alpha (1:1000; Cell Signaling); Akt (1:1000; Cell Signaling); phospho-Akt (1:1000; Cell Signaling).
  • Edu incorporation was used as a measure of proliferation.
  • cells (6 x 10E5) were cultured in DMEM/F12 medium without growth factors for 18 hours in a six well plate. Cells were exposed to EdU (10 ⁇ M Click-iT® EdU Flow Cytometry Assay Kit, Invitrogen) and PDGF-AA ligand (20 ng/mL) or a combination of PDGF-AA (20 ng/mL) and Imatinib (10uM) for 24 hours. After incubation cells were centrifuged, the supernatant was discarded and the pellet suspended in 100 ⁇ l of 4% paraformaldehyde for 15 minutes.
  • Flow cytometry was performed using a FACSCaliber TM Flow Cytometer (BD Biosciences) and data was analyzed with Kaluza® Flow Cytometry Software (Beckman Coulter). Analysis of 30,000 total events was performed after exclusion of dead cells by FSC/SSC gating. Fluorescence was measured in the FL4 channel.
  • mice Animal protocols were approved by the Johns Hopkins School of Medicine Animal Care and Use Committee. For intracranial xenografts, severe combined immunodeficiency mice received 100,000 viable cells in 1 ⁇ l of DMEM/F12 serum media without growth factors by stereotactic injection into the right striatum. Cells were cultured in DMEM/F12 serum media with epidermal growth factor, fibroblast growth factor, and PDGF ligand for 3 weeks before injections were performed. Cell viability was determined by trypan blue dye exclusion. Mice were perfused with 4% paraformaldehyde at the indicated times, and the brains were removed for histological analysis. Patient Clinical Information Used in the Study
  • the following table provides information about the dataset (e.g., as it relates to Figures 4A-7F).
  • the table shows the patients clinical data (from which the primary GBM cell lines were derived).
  • the table contains over 35 factors related to each patient's tumor, general health, and demographics, including tumor size, tumor shape, therapeutic regimen, age and are sorted according to their response to PDGF.
  • Results are presented as mean + SEM.
  • the Mann-Whitney rank-sum test was for pairwise comparisons; Dunn's test (rank-based ANOVA) was used in multiple group comparisons. When noted, Student's t test or standard ANOVA (the Holm-Sidak method) was used. Univariate Cox analysis was used to identify correlations among tumor characteristics.
  • thresholds were determined using linear discriminant analysis as previously described (Lin, B., et al., Synthetic spatially graded Rac activation drives cell polarization and movement, Proc. Natl. Acad. Sci. USA 109, E3668– E3677 (2012)). Statistics were analyzed using Sigmaplot®, GraphPad® Prism, and MATLAB® software.
  • topographic patterns consisting of regular, parallel ridges ( Figures 1A, 1B, and 8A–8C) similar in size to those found in the brain tissue ECM were fabricated (Kim, D.-H., et al., Guided cell migration on microtextured substrates with variable local density and anisotropy, Adv. Funct. Mater. 19, 1579–1586 (2009); Bellail, A.C., et al., Micro- regional extracellular matrix heterogeneity in brain modulates glioma cell invasion. Int. J. Biochem, Cell Biol.
  • PDGF-AA PDGF-AA
  • PDGFR ⁇ PDGF receptor alpha
  • Heterogeneity of cell properties within the same tumor reflects subpopulations promoting tumor growth, progression, and therapeutic resistance.
  • GBM also has populations with distinct expression profiles of receptor tyrosine kinases, particularly PDGFR ⁇ .
  • This heterogeneity can be tackled by analysis on the single-cell level, which is yielded in the quasi-3D platform with less than 1,000 cells (particularly beneficial for screening precious intraoperative human tissue specimens).
  • the single-cell resolution to quantify the distribution of cell speed in control versus PDGF-exposed conditions, the difference in migratory behaviors among 14 glioblastoma patients was investigated ( Figures 4A–4C). Both intra- and inter-patient differences in the cell population behavior were found.
  • the degree of cell migration may reflect the propensity for invasive tumor spread. More than 35 factors related to each patient’s tumor, general health, and demographics were examined (Table 1). It was found that the migratory response of GBM samples to PDGF correlated with time to tumor recurrence after surgical resection ( Figures 6A and 6B). This correlation was particularly significant when the analysis was focused on the consensus- responsive and consensus-unresponsive groups ( Figure 6A). In comparisons to the whole-cell populations, correlations were more significant for the aggressively moving cells: either the fastest 25% of the cells or the outlier population (Figure 6B).
  • the described experimental platform has important advantages over 2D migration assays, because it provides a cellular environment similar to in vivo conditions (as evidenced in the similarity of several aspects of migration in ex vivo human brain tissue and a 3D hydrogel, e.g., increased cell polarity and migration speed). These factors can be important in migration.
  • Another advantage is the reduced number of cells required when compared to commonly used transwell migration assays.
  • transwell assays fail to yield the information on migration and morphology of individual cells and only originate endpoint information. A substantial degree of heterogeneity was found in the glioblastoma samples analyzed.
  • the increased average migration speed of a cell population in the presence of PDGF was ascribed to a small subpopulation of aggressive cells (approximately 25%).
  • Knowledge of the degree of population heterogeneity can be critical to the decision-making in the clinic.
  • the quasi-3D tissue mimetic platform can distinguish the effects of cell proliferation and migration phenotypes, which can be a confounding factor in both transwell and in vivo migration studies.
  • results here support the proposed methodology as a simpler, more biomimetic, and informative method to gain critical information about patient tumors and cell populations.
  • the analysis presented here reveals the importance of careful engineering of chemical and mechanical extracellular milieu in cell migration analysis. This methodology will provide an important prognostic tool, with benefits that include high-throughput, label- free analysis of single-cell resolution; low demand for precious primary cell samples; and better physiological relevance compared to other migration assays.

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Abstract

La présente invention concerne un dispositif et des procédés qui permettent des études à résolution temporelle de migration avec une résolution monocellulaire sur une surface fibrillaire qui imite la migration in vivo de cellules. Cette plate-forme est utilisée pour le tri, avec un contenu élevé, d'échantillons de glioblastome spécifiques à un patient pour analyser les hétérogénéités dans le phénotype de cellules migratoires. Les informations que la plate-forme fournit ont une valeur de pronostic puisqu'elles présentent des différences significatives dans le temps en termes de récurrence et d'emplacement de tumeur sur la base des classificateurs phénotypiques.
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EP3968025A1 (fr) * 2020-09-15 2022-03-16 Institut Gustave Roussy Procédés pour la détermination de la capacité d'invasion de cellules de tumeurs cérébrales et pour le diagnostic et le pronostic de tumeurs cérébrales

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EP3760728A4 (fr) * 2018-02-28 2021-10-27 National University Corporation Tokai National Higher Education and Research System Procédé d'évaluation de médicament
EP3968025A1 (fr) * 2020-09-15 2022-03-16 Institut Gustave Roussy Procédés pour la détermination de la capacité d'invasion de cellules de tumeurs cérébrales et pour le diagnostic et le pronostic de tumeurs cérébrales
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