Methods and materials for assessing cancer treatments

Abstract

This document relates to methods and materials for assessing cancer treatments and / or treating mammals (e.g., humans) having a cancer (e.g., a brain cancer such as glioma). For example, methods and materials provided herein can be used to identify candidate anti-cancer treatments as being likely to be effective in treating a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma). This document also provides methods and materials for treating a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma).

Description

[0001] METHODS AND MATERIALS FOR ASSESSING CANCER TREATMENTS

[0002] CROSS-REFERENCE TO RELATED APPLICATIONS

[0003] This application claims the benefit of Greece Patent Application Serial No. 20240100379, filed on May 21, 2024 and U.S. Patent Application Serial No. 63 / 653,642, filed on May 30, 2024. The disclosure of the prior applications is considered part of (and is incorporated by reference in) the disclosure of this application.

[0004] TECHNICAL FIELD

[0005] This document relates to methods and materials for assessing cancer treatments and / or treating mammals (e.g., humans) having a cancer (e.g., a brain cancer such as glioma). For example, the methods and materials provided herein can be used to identify one or more candidate anti-cancer treatments that are likely to be effective in treating a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma). This document also provides methods and materials for treating a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) by administering an anti-cancer treatment that was identified as being likely to be effective in treating that particular mammal’s cancer.

[0006] BACKGROUND INFORMATION

[0007] Diffuse gliomas are the most common malignant brain tumors in adults and include isocitrate dehydrogenase mutant (IDH-mut) astrocytomas, IDH-mut and chromosome lp / 19q-codeleted oligodendrogliomas, and IDH-wildtype glioblastomas (Louis et al., Neuro Oncol, 23: 1231 (2021)). Despite multi-modal treatment, gliomas remain incurable. Genomic and transcriptomic profiling have shown that high-grade gliomas (HGGs) are molecularly complex, with multiple cancer-driving events and oncogenic pathways concurrently deregulated in each tumor (N. Cancer Genome Atlas Research, Nature, 455: 1061 (2008)). Possibly due to this complexify, clinical trials targeting specific genomic alterations and / or developed based on drug efficacy in existing pre-clinical models have generally failed to achieve clinically meaningful benefit (Bagley et al., Clin Cancer Res, 28: 594 (2022)).

[0008] SUMMARY

[0009] This document provides methods and materials for assessing cancer treatments and / or treating mammals (e.g., humans) having a brain cancer (e.g., a brain cancer such as glioma). For example, the methods and materials provided herein can be used to identify one or more candidate anti-cancer treatments that are likely to be effective in treating a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma). In some cases, one or more samples (e.g., one or more tissue samples) obtained from a mammal (e.g., a human) having a cancer (e g., a brain cancer such as glioma) can be used to generate a collection of ex vivo 3- dimensional (3D) microcancer culture models (sometimes referred to herein as microcancer models) representative of that mammal’s cancer that can be used to identify one or more candidate anti-cancer treatments that are likely to be effective in treating that particular mammal’s cancer (e.g., that particular human’s glioma) based, at least in part, on a reduction of the cell viability of one or more of that mammal’s microcancer models following contact with a particular candidate anti-cancer treatment. For example, one or more samples (e.g., one or more tissue samples) obtained from a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) can be used to generate a collection of microcancer models that can be used to identify one or more candidate anti-cancer treatments that are likely to be effective in treating that particular mammal’s cancer (e.g., that particular human’s glioma) based, at least in part, on comparing the cell viability in one or more of that mammal’s microcancer models that were contacted with a particular candidate anti-cancer treatment to the cell viability in a one or more of that mammal’s microcancer models that were not contacted with the candidate anti-cancer treatment and / or any potential anti-cancer treatment to identify those that promote reduced cell viability.

[0010] In some cases, one or more samples (e.g., one or more tissue samples) obtained from a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) can be used to generate a collection of microcancer models that can be used to identify one or more candidate anti-cancer treatments that are likely to be effective in treating that particular mammal’s cancer (e.g., that particular human’s glioma) by exposing subsets of the microcancer models individually to one of tens, hundreds, or even thousands of potential anti-cancer treatments in parallel and comparing the cell viabilities of each to one or more controls (e.g., a subset of that mammal’s microcancer models that was not exposed to any potential anti-cancer treatment) to identify those that promote reduced cell viability. For example, a first potential anti-cancer treatment such as a combination of drug 1 and drug 2 can be exposed to one to ten microcancer models of a particular mammal (e.g., a human), a second potential anti-cancer treatment such as a combination of drug 3 and drug 4 can be exposed to one to ten microcancer models of a particular mammal (e.g., a human), a third potential anti-cancer treatment such as a combination of drug 5 and drug 6 can be exposed to one to ten microcancer models of a particular mammal (e.g., a human), a fourth potential anti-cancer treatment such as a combination of drug 1 and drug 3 can be exposed to one to ten microcancer models of a particular mammal (e.g., a human), a fifth potential anti-cancer treatment such as a combination of drug 1 and drug 4 can be exposed to one to ten microcancer models of a particular mammal (e.g., a human), a sixth potential anti-cancer treatment such as a combination of drug 1 and drug 5 can be exposed to one to ten microcancer models of a particular mammal (e.g.. a human), a seventh potential anti-cancer treatment such as a combination of drug 1 and drug 6 can be exposed to one to ten microcancer models of a particular mammal (e.g., a human), an eighth potential anti-cancer treatment such as a combination of drug 2 and drug 3 can be exposed to one to ten microcancer models of a particular mammal (e.g.. a human), and so forth for as many potential anti-cancer treatments one desires to assess. Following an incubation period, the cell viabilities of each can be compared to the cell viabilities of one or more controls (e.g., a subset of that mammal’s microcancer models that was not exposed to any potential anticancer treatment) to identify one or more candidate anti-cancer treatments as having the ability to promote reduced cell viability and thereby as being likely to be effective against that particular mammal’s cancer.

[0011] This document also provides methods and materials for treating a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) by administering an anti-cancer treatment that is selected based, at least in part, on whether or not the anti-cancer treatment was identified as being a candidate anti-cancer treatment likely to be effective against that particular mammal’s cancer using the microcancer models as described herein. For example, a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) can be administered an anti-cancer treatment that is selected based, at least in part, on its ability to promote reduced cell viability in one or more microcancer models for that mammal as compared to one or more control microcancer models for that mammal that were not exposed to any potential anti-cancer treatments.

[0012] As demonstrated herein, if the cell viability of one or more of a mammal's microcancer models contacted with a candidate anti-cancer treatment is reduced (as compared to the cell viability of one or more control microcancer models of that mammal), then that candidate anti-cancer treatment can be classified as being likely to be effective in treating that particular mammal (e.g., that particular human). In some cases, that candidate anti-cancer treatment identified as being likely to be effective in that particular mammal (e.g., that particular human) can be administered to that particular mammal to treat that mammal’s cancer. Having the ability to identify candidate anti-cancer treatments that are likely to be effective against a particular mammal's cancer as described herein (e.g., based, at least in part, on a reduction of the cell viability in one or more of that mammal’s microcancer models that were contacted with the candidate anti-cancer treatment) provides a unique and unrealized opportunity to provide an individualized approach for selecting cancer therapies based on the likelihood of success, thus providing cost-effective care with better outcomes.

[0013] In some cases, multi-omic data about a mammal’s cancer (e.g., whole genome sequencing data and / or RNAseq data) can be used to select possible candidate anti -cancer treatments to be assessed using that mammal’s microcancer models as described herein. For example, certain genetic mutations present is a mammal’s cancer can be used to select candidate anti-cancer treatments designed to exploit those genetic mutations of the cancer.

[0014] In general, one aspect of this document features a method for identifying a candidate anti-cancer treatment likely to be effective in treating a mammal having cancer. The method comprises (or consists essentially of. or consists of): (a) culturing a cell suspension of a sample of the cancer in each of a plurality of individual locations of a culture vessel in the presence of culture medium that does not contain hydrocortisone to generate a microcancer model of the cancer in each of the plurality of individual locations, (b) contacting one or more of the microcancer models with a potential anti-cancer treatment, and (c) identifying the potential anti-cancer treatment as having the ability to reduce cell viability of the microcancer model contacted with the potential anti-cancer treatment as compared to cell viability of one or more control microcancer models of the cancer not contacted with the potential anti-cancer treatment, thereby identifying the potential anti-cancer treatment as being the candidate anticancer treatment. The mammal can be a human. The cancer can be a brain cancer. The brain cancer can be a glioma. The culture vessel can be an ultra-low attachment plate. The culture vessel can be a hanging drop plate. The culture medium can be a medium that does not contain ROCK inhibitor. The culture medium can contain ROCK inhibitor. The culture medium can be removed from the culture vessel and replaced with a culture medium that does not contain ROCK inhibitor during the contacting step (b). The potential anti-cancer treatment can comprise a single compound. The single compound can be selected from the compounds set forth in Table 1. The potential anti-cancer treatment can comprise a combination of two compounds, a combination of three compounds, a combination of four compounds, a combination of five compounds, or a combination of six compounds. The combination can be selected from the combinations of compounds set forth in Table 2. In another aspect, this document features a method for identifying a candidate anticancer treatment likely to be effective in treating a mammal having cancer. The method comprises (or consists essentially of, or consists of): (a) dispensing a cell suspension of a sample of the cancer into each of a plurality of individual locations of a culture vessel in the presence of culture medium and culturing the cell suspension to generate a microcancer model of the cancer in each of the plurality of individual locations, wherein the cell suspension dispensed into each of the plurality of individual locations contained less than 4000 cells, (b) contacting one or more of the microcancer models with a potential anti-cancer treatment, and (c) identifying the potential anti-cancer treatment as having the ability to reduce cell viability of the one or more microcancer models contacted with the potential anticancer treatment as compared to cell viability of one or more control microcancer models of the cancer not contacted with the potential anti-cancer treatment, thereby identifying the potential anti-cancer treatment as being the candidate anti-cancer treatment. The mammal can be a human. The cancer can be a brain cancer. The brain cancer can be a glioma. The culture vessel can be an ultra-low attachment plate. The culture vessel can be a hanging drop plate. Each of the plurality of individual locations can contain 500 to 30,000 cells prior to the step (b). The culture medium can be medium that does not contain hydrocortisone. The culture medium can be medium that does not contain ROCK inhibitor. The culture medium can contain ROCK inhibitor. The culture medium can be removed from the culture vessel and replaced with a culture medium that does not contain ROCK inhibitor during the contacting step (b). The potential anti-cancer treatment can comprise a single compound. The single compound can be selected from the compounds set forth in Table 1. The potential anti-cancer treatment can comprise a combination of two compounds, a combination of three compounds, a combination of four compounds, a combination of five compounds, or a combination of six compounds. The combination can be selected from the combinations of compounds set forth in Table 2.

[0015] In another aspect, this document features a method for identify ing a candidate anticancer treatment likely to be effective in treating a mammal having cancer. The method comprises (or consists essentially of. or consists of): (a) obtaining a culture vessel comprising a plurality of locations, wherein each of the plurality of locations comprises a microcancer model of the cancer, (b) identify ing a potential anti-cancer treatment that involves administering a single drug at a set dose to the mammal, (c) contacting one or more of the microcancer models with the single drug at a concentration within 5 percent of Cmaxof the set dose in plasma or at the location of the cancer within the mammal, and (d) identifying the contacting of step (c) as having the ability to reduce cell viability of the one or more microcancer models contacted with the single drug as compared to cell viability of one or more control microcancer models of the cancer not contacted with the single drug, thereby identifying the potential anti-cancer treatment as being the candidate anti-cancer treatment. The mammal can be a human. The cancer can be a brain cancer. The brain cancer can be a glioma. The culture vessel can be an ultra-low attachment plate. The culture vessel can be a hanging drop plate. The single compound can be selected from the compounds set forth in Table 1.

[0016] In another aspect, this document features a method for identifying a candidate anticancer combination treatment likely to be effective in treating a mammal having cancer. The method comprises (or consists essentially of, or consists of): (a) obtaining a culture vessel comprising a plurality of locations, wherein each of the plurality of locations comprises a microcancer model of the cancer, (b) identifying a potential anti-cancer treatment that involves administering a combination of two drugs, each at a set dose, to the mammal, (c) contacting one or more of the microcancer models with a first drug of the two drugs at a concentration within 5 percent of Cmax of the set dose of the first drug in plasma or at the location of the cancer within the mammal, (d) contacting one or more of the microcancer models with a second drug of the two drugs at a concentration within 5 percent of Cmax of the set dose of the second drug in plasma or at the location of the cancer within the mammal, (e) contacting one or more of the microcancer models with the first drug at a concentration within 5 percent of Cm x of the set dose of the first drug in plasma or at the location of the cancer within the mammal and with the second drug at a concentration within 5 percent of Cmax of the set dose of the second drug in plasma or at the location of the cancer within the mammal, and (f) identifying the contacting of step (e) as having the ability to reduce cell viability of the one or more microcancer models contacted to a greater extent than that of the contacting of the step (c) and that of the contacting of the step (d), thereby identifying the potential anti-cancer treatment as being the candidate anti-cancer treatment. The identifying step (f) can comprise using a plot, where the x axis is the percent inhibition of cell viability of the first drug at the concentration of step (c) and the y axis is the percent inhibition of cell viability of the second drug at the concentration of step (d), wherein a first x,y data point is plotted based on the percent inhibition of cell viability of step (c) for (x) and the percent inhibition of cell viability- of step (d) for (y), and wherein a second X,Y data point is plotted based on the percent inhibition of cell viability- of step (e) for the combined exposition to the first drug for (X) and second drug for (Y) at the concentrations of step (e). The mammal can be a human. The cancer can be a brain cancer, or the cancer can be a glioma. The culture vessel can be an ultra-low attachment plate. The culture vessel can be a hanging drop plate. The combination can be selected from the combinations of compounds set forth in Table 2.

[0017] In another aspect, this document features a method for identifying a candidate anticancer treatment likely to be effective in treating a mammal having cancer. The method comprises (or consists essentially of, or consists of): (a) obtaining a culture vessel comprising a plurality of locations, wherein each of the plurality of locations comprises a microcancer model of the cancer, (b) contacting one or more of the microcancer models with a potential anti-cancer treatment, (c) conducting whole genome sequencing of a sample of the cancer or of the microcancer model to identify genetic mutations within the cancer, and optionally conducting whole genome sequencing of a germline sample of the mammal, and optionally conducting RNAseq of a sample of the cancer or of the microcancer model to identify expression profiles of the cancer, (d) identifying the potential anti-cancer treatment as having the ability to reduce cell viability of the one or more microcancer models contacted with the potential anti-cancer treatment as compared to cell viability of one or more control microcancer models of the cancer not contacted with the potential anti-cancer treatment, thereby identifying the potential anti-cancer treatment as being the candidate anti-cancer treatment, and (e) confirming that the genetic mutations of the cancer are not a counter indication for use of the candidate anti-cancer treatment in the mammal. The mammal can be a human. The cancer can be a brain cancer. The brain cancer can be a glioma. The culture vessel can be an ultra-low attachment plate. The culture vessel can be a hanging drop plate. The potential anti-cancer treatment can comprise a single compound. The single compound can be selected from the compounds set forth in Table 1. The potential anti-cancer treatment can comprise a combination of two compounds, a combination of three compounds, a combination of four compounds, a combination of five compounds, or a combination of six compounds. The combination can be selected from the combinations of compounds set forth in Table 2. The potential anti-cancer treatment can be selected based on the genetic mutations identified within the cancer.

[0018] In another aspect, this document features a method for identifying a candidate anticancer treatment likely to be effective in treating a mammal having cancer. The method comprises (or consists essentially of, or consists of): (a) obtaining a culture vessel comprising a plurality of locations, wherein each of the plurality of locations comprises a microcancer model of the cancer, (b) contacting one or more of the microcancer models with a potential anti-cancer treatment in the presence of one or more dyes that stain cells for cell death or cell death by apoptosis, autophagic cell death, or necrosis, (c) conducting live imaging of the one or more microcancer models to observe cell death, (d) identifying the potential anti-cancer treatment as having the ability to reduce cell viability of the one or more microcancer models contacted with the potential anti-cancer treatment as compared to cell viability of one or more control microcancer models of the cancer not contacted with the potential anti-cancer treatment, thereby identifying the potential anti-cancer treatment as being the candidate anticancer treatment, and (e) confirming death of cells during the live imaging. The mammal can be a human. The cancer can be a brain cancer. The brain cancer can be a glioma. The culture vessel can be an ultra-low attachment plate. The culture vessel can be a hanging drop plate. The potential anti-cancer treatment can comprise a single compound. The single compound can be selected from the compounds set forth in Table 1. The potential anti-cancer treatment can comprise a combination of two compounds, a combination of three compounds, a combination of four compounds, a combination of five compounds, or a combination of six compounds. The combination can be selected from the combinations of compounds set forth in Table 2. The one or more dyes can be selected from the group consisting of annexin V fluorescent conjugates, caspase 3 / 7 specific fluorescent dyes. Fluorescent Premo™ Autophagy Tandem Sensor RFP-GFP-LC3B, Autophagy LC3 HiBiT Reporter Assay System, propidium iodide, SYTOX™ green fluorescent dye, Deep Red fluorescent dye, and RealTime-Glo™ Annexin V Apoptosis and Necrosis Assay.

[0019] In another aspect, this document features a method for treating a mammal having a brain cancer. The method comprises (or consists essentially of, or consists of) administering a compound set forth in Table 1 to the mammal. The mammal can be a human. The cancer can be a brain cancer. The brain cancer can be a glioma.

[0020] In another aspect, this document features a method for treating a mammal having a brain cancer. The method comprises (or consists essentially of, or consists of) administering a combination of compounds set forth in Table 2 to the mammal. The mammal can be a human. The cancer can be a brain cancer. The brain cancer can be a glioma.

[0021] In another aspect, this document features a method for treating a mammal having a brain cancer with a candidate anti -cancer combination treatment identified as being likely to be effective in treating the mammal. The method comprises (or consists essentially of, or consists of): (a) obtaining a culture vessel comprising a plurality of locations, wherein each of the plurality' of locations comprises a microcancer model of the cancer, (b) identifying a potential anti-cancer treatment that involves administering a single drug at a set dose, to the mammal, (c) contacting one or more of the microcancer models with the single drug at a concentration within 5 percent of Cmax of the set dose in plasma or at the location of the cancer within the mammal, (d) identifying the contacting of step (c) as having the ability to reduce cell viability of the one or more microcancer models contacted with the single drug as compared to cell viability of one or more control microcancer models of the cancer not contacted with the single drug, thereby identifying the potential anti-cancer treatment as being the candidate anti-cancer treatment, and (e) administering the candidate anti -cancer treatment to the mammal. The mammal can be a human. The cancer can be a brain cancer. The brain cancer can be a glioma. The culture vessel can be an ultra-low attachment plate. The culture vessel can be a hanging drop plate. The single compound can be selected from the compounds set forth in Table 1.

[0022] In another aspect, this document features a method for treating a mammal having a brain cancer with a candidate anti -cancer combination treatment identified as being likely to be effective in treating the mammal. The method comprises (or consists essentially of, or consists of): (a) obtaining a culture vessel comprising a plurality of locations, w herein each of the plurality of locations comprises a microcancer model of the cancer, (b) identifying a potential anti-cancer treatment that involves administering a combination of two drugs, each at a set dose, to the mammal, (c) contacting one or more of the microcancer models with a first drug of the two drugs at a concentration within 5 percent of Cmax of the set dose of the first drug in plasma or at the location of the cancer within the mammal, (d) contacting one or more of the microcancer models with a second drug of the two drugs at a concentration within 5 percent of Cmax of the set dose of the second drug in plasma or at the location of the cancer within the mammal, (e) contacting one or more of the microcancer models with the first drug at a concentration within 5 percent of Cmax of the set dose of the first drug in plasma or at the location of the cancer within the mammal and with the second drug at a concentration within 5 percent of Cmax of the set dose of the second drug in plasma or at the location of the cancer within the mammal, (f) identifying the contacting of step (e) as having the abilify to reduce cell viability' of the one or more microcancer models contacted to a greater extent than that of the contacting of the step (c) and that of the contacting of the step (d). thereby identifying the potential anti-cancer treatment as being the candidate anti-cancer treatment, wherein the candidate anti-cancer treatment is a combination treatment set forth in Table 2, and (g) administering the candidate anti-cancer treatment to the mammal. The identify ing step (f) can comprise using a plot, where the x axis is the percent inhibition of cell viability of the first drug at the concentration of step (c) and the y axis is the percent inhibition of cell viability of the second drug at the concentration of step (d), wherein a first x,y data point is plotted based on the percent inhibition of cell viability of step (c) for (x) and the percent inhibition of cell viability of step (d) for (y). and wherein a second X.Y data point is plotted based on the percent inhibition of cell viability of step (e) for the combined exposition to the first drug for (X) and second drug for (Y) at the concentrations of step (e). The mammal can be a human. The cancer can be a brain cancer, or the cancer can be a glioma. The culture vessel can be an ultra-low attachment plate. The culture vessel can be a hanging drop plate. The combination can be selected from the combinations of compounds set forth in Table 2.

[0023] In another aspect, this document features a method for identifying a candidate anticancer treatment likely to be effective in treating a mammal having cancer and previously treated with a prior anti-cancer treatment. The method comprises (or consists essentially of, or consists of): (a) obtaining a culture vessel comprising a plurality of locations, wherein each of the plurality of locations comprises a microcancer model of the cancer, wherein each of the microcancer models was exposed to the prior anti-cancer treatment while the mammal was receiving the prior anti-cancer treatment, (b) contacting one or more of the microcancer models wi th a potential anti-cancer treatment, and (c) identifying the potential anti-cancer treatment as having the ability to reduce cell viability of the one or more microcancer models contacted with the potential anti-cancer treatment as compared to cell viability of one or more control microcancer models of the cancer not contacted with the potential anti-cancer treatment, thereby identifying the potential anti-cancer treatment as being the candidate anticancer treatment. The mammal can be a human. The cancer can be a brain cancer. The brain cancer can be a glioma. The culture vessel can be an ultra-low attachment plate. The culture vessel can be a hanging drop plate. The potential anti -cancer treatment can comprise a single compound. The single compound can be selected from the compounds set forth in Table 1. The potential anti-cancer treatment can comprise a combination of tw o compounds, a combination of three compounds, a combination of four compounds, a combination of five compounds, or a combination of six compounds. The combination can be selected from the combinations of compounds set forth in Table 2.

[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Although methods and materials similar or equivalent to those described herein can be used to practice the invention, suitable methods and materials are described below; All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present specification. including definitions, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting.

[0025] The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims.

[0026] DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 shows a schematic overview of an ex vivo glioma platform to identify individualized targeted treatments for HGG.

[0028] Figure 2 is a flow- chart indicating the number of patients enrolled and that proceeded with following applications for next generation sequencing (NGS) and microcancer model generation and drug testing.

[0029] Figure 3 is a schematic showing the trajectory of each case from patient enrollment, NGS. microcancer model generation and drug testing, to quality control.

[0030] Figure 4 shows the clinical parameters and glioma relevant molecular alterations of patient samples. RTK, MEK, and PI3K pathway components indicated. Histogram (right) depicting the frequency of pathogenic alterations of listed genes (tumor suppressor genes (TSGs) exhibiting double hit or loss-of-function (LoF) mutation(s); oncogenes exhibiting amplification, fusion, or gain-of-function (GoF) mutation(s)). Notes: 2021 WHO classification used for disease diagnosis. PT601 : hypermutated. LB, likely benign.

[0031] Figures 5A-5B show the characterization of patient derived microcancer models with parental glioblastoma including staining for Ki-67 proliferation marker in PDX GBM8 orthotopic xenograft tissue and a GBM8 microcancer model (pCancer) (Figure 5A), and cell viability, measured by nM ATP over 12-day of culture, for microcancer models (PT425) (Figure 5B).

[0032] Figure 6 is a genetic landscape comparing patient-derived microcancer models (pCancer) and parental glioblastoma and showing copy number alterations (CNAs) and mutation alterations (lollipops) in U plot (top), CNAs in horizontal view (middle top), heterozygosity status (middle bottom), and single base substitutions (SBS) mutational signature (bottom). Copy number gains, losses, diploid (grey) and DNA junctions (lines) indicated.

[0033] Figures 7A-7C show that glioma-relevant mutations identified in parental tumor are retained in microcancer models (pCancer) with a similar frequency (Figure 7A), the overlap in mutations captured by whole exome sequencing (WES) (Figure 7B), and the correlation between allele frequency of all mutations identified by WES (Figure 7C) in microcancer models (pCancer) and parental tumor.

[0034] Figures 8A-8B are comparisons between microcancer models and parental glioblastoma illustrated by a Venn diagram showing the similarity and difference of DNA junction numbers captured by mate pair sequencing (MPseq) in microcancer models (pCancer) and corresponding parental tumor PT311 (MPseq) (Figure 8A) and pTERT mutation status in the parental tumor PT311 and microcancer models identified by clinical testing (Neuro-Oncology expanded gene panel (NONCP), and PCR (Figure 8A).

[0035] Figure 9 shows the work for microcancer model (pCancer) generation and drug testing followed by biomarker identification.

[0036] Figures 10A-10D are dose-response curves of microcancer models (pCancer) (PT303) treated with pimasertib (Figure 10A), capivasertib (Figure 10B), and navitoclax (Figure IOC) and a heatmap showing % inhibition at Cmax for each culture condition (Figure 10D).

[0037] Figure 11 is a scatter plot depicting % viabi li ty of all replicates performed at different times of drug testing, each data point representing drug responses measured at first and second experiments, showing correlation between experiments. Pearson’s (rp) and Spearman’s (rs) correlation analyses performed.

[0038] Figure 12 is a schematic illustrating agents targeting key glioma-relevant pathways.

[0039] Figures 13A-13B show the normalized microcancer model dose-response curves for neratinib (Figure 13 A) and paxalisib (Figure 13B) across all samples.

[0040] Figures 14 is a three-tier drug response (Figure 14A) showing <35% (minimal response, MR; light gray), 35-70% (partial response, PR; gray), and >70% (strong response, SR; dark gray) of growth inhibition at Cmax for indicated inhibitors. Stacked bar graphs depict the percentage of differential responses for each drug (right) and case (bottom).

[0041] Figures 15A-15C are normalized dose-response curves for osimertinib (Figure 15A), foretinib (Figure 15B), and sunitinib (Figure 15C) targeting indicated RTKs, with Cmax indicated.

[0042] Figure 16 is a stacked bar graph showing the percentage of differential responses, <35% (minimal response, MR; light gray), 35-70% (partial response. PR; gray), and >70% (strong response, SR; dark gray), for birabresib, mivebresib, and trotabresib, and JQ1 plotted for comparison.

[0043] Figures 17A-17D are w aterfall plots of % inhibition at Cmax for microcancer models treated with capivasertib (Figure 17A), CC-115 (Figure 17B). navitoclax (Figure 17C). and vorinostat (Figure 17D) and the status of the genetic features related to the drug target for each case.

[0044] Figure 18 is a scatter plot with bars (mean±SEM) showing JQ1 efficacy in microcancers derived from tumors with wildtype or mutated pTERT or ATRX. P-value determined by unpaired t-test.

[0045] Figures 19A-19B show TCGA (Figure 19A) and pathway -based (Figure 19B) transcriptional subtypes (second row) with glioma subtype (first row) and normalized enrichment scores (NES) of each signature shown. NES indicating the degree of activation of each signature from high (1, dark grey, dashed) to no (0, gray, no dash). SPL representing the complexity of signatures involved from high (0, black) to low (1, white).

[0046] Figures 20A-20B show the association of assigned subtypes between the TCGA and pathway -based transcription classifiers in glioma (Figure 20 A) and the subtype assignment using the TCGA and pathway-based transcription classifications for individual cases (Figure 20B).

[0047] Figures 21A-21B are correlation plots showing the relationship between transcriptional subtype enrichment scores (ES, scale: 0-100) of TCGA (Figure 21 A) and pathway based transcriptional (txn) subtype (Figure 2 IB) (x-axes) and microcancer model response (% Inhibition (Inh) at Cmax; scale: 0-100) to JQ1, vorinostat, CC-115, capivasertib, and navitoclax (y-axes).

[0048] Figures 22A-22D are distribution plots showing % inhibition at Cmax from cases with low-to-high response from left to right to JQ1 (Figure 22A), vorinostat (Figure 22B), CC-115 (Figure 22C), and capivasertib (Figure 22D). Responders (R) and non-responders (NR) are cases above the yellow dashed lines and below the grey dashed lines, respectively.

[0049] Figures 23A-23D are heatmaps depicting statistically significant differentially- expressed genes for indicated subtypes between responder (R) and non-responder (NR) microcancer groups to JQ1 (Figure 23A), vorinostat (Figure 23B), CC-115 (Figure 23C), and capivasertib (Figure 23D). Raw Z-Score from low (dark grey) to high (dark grey, dashed) and % inhibition at Cmax (% Inh) indicated. Top 5 differentially expressed genes listed.

[0050] Figures 24A-24D are heatmaps showing differentially expressed genes for indicated gene sets between responder (R) and non-responder (NR) microcancer model groups following treatment with JQ1 (Figure 24A), vorinostat (Figure 24B and Figure 24C), and CC- 115 (Figure 24D). Raw- Z-Score from low to high and % inhibition at Cmax (% Inh) are indicated. Top 5 differentially expressed genes listed. Figure 25 is a schematic showing that Hippo kinases inactivate YAP / TAZ signaling and prevent DGC to G-STEM conversion.

[0051] Figures 26A-26C are correlation plots showing relationships between enrichment of indicated signatures (x-axes) and pCancer response to JQ1 (Figure 26A), CC-115 (Figure 26B). and vorinostat (Figure 26C). Linear correlation lines indicated. Signatures linked to Hippo inactivation (GOBP Positive Reg Hippo and DGC signature) and YAP / TAZ activation (G-STEM signature) separated by dashed vertical line. Grey, statistically significant p-values and corresponding rp.

[0052] Figure 27 is a heatmap depicting differentially expressed genes in the MT0RC1 signaling hallmark between CC-115 responder (R) and non-responder (NR) microcancer model groups. Raw Z-score from low (dark grey) to high (dark grey, dashed) and % inhibition at Cmax (% Inh) indicated.

[0053] Figure 28 shows the effect of combination strategies on microcancer model drug responses. An example dose-response curve graph indicates % inhibition of single agents and combination treatment at each drug’s Cmax, and conversion to a heatmap or an X-Y scatter plot show combination treatment being more effective that corresponding single agents.

[0054] Figure 29 is a graph depicting the effect of 7 drug combinations compared to their corresponding single agent treatments.

[0055] Figures 30A-30B are heatmaps depicting differential responses of combination treatments compared to single agents at each Cmax and the companion stacked column graph (Figure 30A-B) shows the relationship between drug combinations and single agent treatments and response category across cases.

[0056] Figures 31 A-3 IE show that JQ1 treatment resulted in alterations of transcriptional subtypes and enrichments of different gene sets, with corresponding enrichments in biological functions, protein complexes, and signaling pathways in non-responder (NR) PT431 and responder (R) PT440 microcancers (Figures 31 A-31D), and that increased expression of genes related to PI3K signaling in NR PT431 microcancers can be targeted to increase efficacy of JQ1 treatment (Figure 3 IE).

[0057] Figures 32A-32B show that JQ1 treatment resulted in alterations of pathway -based transcriptional subtypes in non-responder (NR) PT431 and responder (R) PT440 microcancers (Figure 32A) and the protein interaction network enriched in responder (R) PT440 microcancers_(Figure 32B). DETAILED DESCRIPTION

[0058] This document provides methods and materials for assessing cancer treatments and / or treating mammals (e.g., humans) having a brain cancer (e.g., a brain cancer such as glioma). For example, the methods and materials provided herein can be used to identify one or more candidate anti-cancer treatments that are likely to be effective in treating a particular mammal's cancer (e.g., a particular human’s cancer) such as a brain cancer (e.g., a glioma).

[0059] In some cases, one or more samples (e.g., one or more tissue samples) obtained from a mammal (e.g., a human) having a cancer (e g., a brain cancer such as glioma) can be used to generate an ex vivo 3D microcancer culture model (i.e., a microcancer model) that can be used to identify one or more candidate anti-cancer treatments that are likely to be effective in treating that mammal’s cancer (e.g., that human’s cancer).

[0060] Any appropriate sample from a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) can be obtained and used to generate a microcancer model as described herein. In some cases, a sample can be a biological sample. In some cases, a sample can contain one or more cancer cells (e.g.. one or more brain cancer cells such as glioma cells). Examples of samples that can be obtained and used to generate microcancer models as described herein include, without limitation, tissue samples and blood samples. In some cases, a sample that can be obtained and used to generate a microcancer model as described herein can be a cancer biopsy sample. In some cases, a sample can be a fresh sample. In some cases, a sample can be a frozen sample.

[0061] In some cases, a sample (e.g., a tissue sample) obtained from a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) for use in generating a collection of microcancer models as described herein can be dissociated into a single cell suspension. Any appropriate method can be used to dissociate cells of a sample (e.g.. a tissue sample) obtained from a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) into a single cell suspension. In some cases, a sample can be dissociated into a single cell suspension by mechanical dissociation. Examples of methods for mechanical dissociation of a sample (e.g., a tissue sample) that can be used as described herein include, without limitation, crushing, cutting, and scrapping of the sample. In some cases, a sample (e.g., a tissue sample) can be dissociated into a single cell suspension by enzymatic dissociation. An example of a method for enzymatic dissociation of a sample (e.g., a tissue sample) that can be used as described herein includes, without limitation, application of an enzy me (e.g., trypsin or collagenase) to the sample. In some cases, a sample (e.g., a tissue sample) can be dissociated into a single cell suspension by chemical dissociation. An example of a method for chemical dissociation of a tissue sample that can be used as described herein includes, without limitation, application of a chemical (e.g.. EGTA or egtazic acid) to the sample. In some cases, a sample (e.g. a tissue sample) can be dissociated into a single cell suspension by a combination of mechanical, enzymatic, and / or chemical dissociation.

[0062] In some cases, a sample (e.g., a tissue sample) obtained from a mammal (e.g., a human) having a cancer (e g., a brain cancer such as glioma) that has been dissociated into a single cell suspension as described herein can be added to the locations (e.g.. wells) of any appropriate cell culture vessel (e.g., a microtiter plate having 96, 384, or 1536 wells) to generate microcancer models. In some cases, an appropriate cell culture vessel is a hanging drop plate (e.g., a hanging drop plate having 96, 384, or 1536 wells). In some cases, an appropriate cell culture vessel is an ultra-low attachment plate (e.g., an ultra-low attachment plate having 96, 384, or 1536 wells). Any appropriate number of cells can be added to a location (e.g., a well) of a cell culture vessel (e.g., a microtiter plate having 96, 384, or 1536 wells) to generate a microcancer model. For example, from about 100 cells to about 20000 cells (e.g., from about 100 to about 20000, from about 100 to about 15000, from about 100 to about 10000, from about 100 to about 5000, from about 100 to about 1000, from about 100 to about 500, from about 100 to about 300, from about 300 to about 20000, from about 500 to about 20000, from about 1000 to about 20000, from about 5000 to about 20000, from about 10000 to about 20000, from about 15000 to about 20000, from about 300 to about 15000, from about 500 to about 10000, from about 1000 to about 5000 from about 300 to about 1000, from about 500 to about 1000, or from about 300 to about 500) can be added to a single location (e.g., a single well) of a cell culture vessel to generate a microcancer model. In some cases, 500 cells can be added to a single location (e.g., a single well) of a cell culture vessel to generate a microcancer model.

[0063] In some cases, when generating a microcancer model from a sample (e.g., a tissue sample) obtained from a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) that has been dissociated into a single cell suspension and added to a cell culture vessel as described herein, the cells can be incubated in an appropriate cell culture medium. In some cases, an appropriate cell culture medium that can be used to make a microcancer model described herein can include, without limitation, a medium such as DMEM / F-12 medium, Advanced DMEM / F12 medium, DMEM medium, or MEM medium supplemented with serum, one or more serum-free medias, insulin, one or more steroids, one or more growth factors, one or more growth regulators, one or more antibiotics, and one or more kinase inhibitors. Examples of serum that can be included within a culture medium for a microcancer model described herein include, without limitation, heat inactivated horse serum, heat inactivated fetal bovine serum, fetal bovine serum, and heat inactivated adult human serum. Examples of serum-free media that can be included within a culture medium for a microcancer model described herein include, without limitation, B-27 (with or without vitamin A), N-2, and Gem21. Examples of insulin that can be included within a culture medium for a microcancer model described herein include, without limitation, human insulin and bovine insulin. Examples of steroids that can be included wi thin a culture medium for a microcancer model described herein include, without limitation, hydrocortisone and dexamethasone. Examples of grow th factors that can be included within a culture medium for a microcancer model described herein include, without limitation, epidermal growth factor (EGF), fibroblast growth factor (FGF), platelet-derived growth factor (PDGF), brain-derived neurotrophic factor (BDNF), hepatocyte growth factor (HGF) , neurotrophin-3 (NT-3), neurotrophin-4 (NT-4), and hormones including, without limitation, 3,3',5'-Triiodo-L- thyronine (T3) and its precursor thyroxine (T4), P-estradiol, progesterone, gastrin I, prostaglandin El, and prostaglandin E2. Examples of growth regulators that can be included within a culture medium for a microcancer model described herein include, without limitation, N-Acetyl-L-cysteine, nicotinamide, and glutamine supplements (e.g., Glutamax). Examples of antibiotics that can be included within a culture medium for a microcancer model described herein include, without limitation, penicillin, streptomycin, amphotericin B. tetracycline, primocin. gentamicin, kanamycin, neomycin, and ciprofloxacin. Examples of kinase inhibitors that can be included within a culture medium for a microcancer model described herein include, without limitation, a rho kinase (ROCK) inhibitor (e.g., Y27632 and CAS 871543-07-6), a GSK-3a / p inhibitor (e.g. CHIR-99021), a myosin II ATPase inhibitor (e.g. blebbistatin), an ALK4 / 5 / 7 inhibitor (e.g. A83-01), and a Rael Inhibitor (e.g. CAS 1177865-17-6). In some cases, an appropriate cell culture medium that can be used to make and maintain a microcancer model described herein can be DMEM / F-12 medium containing heat inactivated horse serum, insulin, hydrocortisone, EGF, penicillin, and streptomycin. In some cases, an appropriate cell culture medium that can be used to make and maintain a microcancer model described herein can be DMEM / F-12 medium containing heat inactivated horse serum, insulin, EGF, penicillin, streptomycin, and ROCK inhibitor, without any hydrocortisone or without any steroid. In some cases, an appropriate cell culture medium that can be used to make and maintain a microcancer model described herein can be DMEM / F-12 medium containing heat inactivated horse serum, insulin. EGF. penicillin, and streptomycin, without any hydrocortisone or without any steroid, and without any ROCK inhibitor or without any kinase inhibitor. When including serum, the serum can be included in the range of 5 percent to 15 percent (e.g., from 8 percent to 12 percent). For example, when including serum, the serum can be included at a level of 10 percent. When including insulin, the insulin can be included in the range of 5 ng / mL to 5000 ng / mL (e.g., from 50 ng / mL to 1000 ng / mL). For example, when including insulin, 5 pg / ml of insulin can be included. When including a steroid such as hydrocortisone, the steroid can be included in the range of 5 ng / mL to 5000 ng / mL (e.g., from 50 ng / mL to 1000 ng / mL). For example, when including hydrocortisone, 5 pg / ml of hydrocortisone can be included. When including a growth factor such as EGF. the growth factor can be included in the range of 1 ng / mL to 100 ng / mL (e g., from 1 ng / mL to 20 ng / mL). For example, when including EGF, 10 ng / ml of EGF can be included. When including an antibiotic such as penicillin and / or streptomycin, the antibiotic can be included in the range of 5000 units / mL to 20000 units / mL (e.g., from 10000 units / mL to 15000 units / ml) or 5 mg / ml to 20 mg / ml. (e.g., from lOmg / mL to 10 mg / mL). For example, when including penicillin, 10,000 units / ml of penicillin can be included, and when including streptomycin, 10 mg / ml of streptomycin can be included. When including a kinase inhibitor such as ROCK inhibitor, the kinase inhibitor can be included in the range of 2pM to 20pM (e.g., from 5 pM to 15 pM). For example, when including ROCK inhibitor, lOpM of ROCK inhibitor can be included. In some cases, an appropriate cell culture medium that can be used to make and maintain a microcancer model described herein can be DMEM / F-12 medium containing 10 percent heat inactivated horse serum, 5 pg / mL insulin, 5 pg / mL hydrocortisone, 10 ng / mL EGF, 10,000 units / ml penicillin, and 10 mg / mL streptomycin. In some cases, an appropriate cell culture medium that can be used to make and maintain a microcancer model described herein can be DMEM / F-12 medium containing 10 percent heat inactivated horse serum, 5 pg / mL insulin, 10 ng / mL EGF, 10,000 units / ml penicillin, 10 mg / mL streptomycin, and 10 pM ROCK inhibitor, with zero hydrocortisone and with zero steroids. In some cases, an appropriate cell culture medium that can be used to make and maintain a microcancer model described herein can be DMEM / F-12 medium containing 10 percent heat inactivated horse serum, 5 pg / mL insulin, 10 ng / mL EGF, 10,000 units / ml penicillin, and 10 mg / mL streptomycin, with zero hydrocortisone and with zero steroids, and with zero ROCK inhibitor and with zero kinase inhibitors.

[0064] In some cases, a collection of microcancer models can be generated as described elsewhere (see. e.g., U.S. Patent No. 11,845,084). Once a microcancer model or collection of microcancer models are generated from a sample (e.g., a tissue sample) obtained from a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma), one or more of those microcancer models and / or a portion of the originally obtained sample (e.g., a portion of a cancer biopsy) can be assessed by any appropriate laboratory technique. For example, a microcancer model described herein can be assessed by live imaging. In some cases, a microcancer model described herein can be assessed by live imaging to monitor cell death (e.g.. apoptosis, autophagic cell death, and necrosis) in the microcancer model. In some cases, using live imaging to monitor cell death (e.g., apoptosis, autophagic cell death, and necrosis) in a microcancer model described herein can include incubating the microcancer model with one or more dyes specific for different types of cell death (e.g., apoptosis, autophagic cell death, and necrosis). In some cases, using live imaging to monitor cell death (e.g., apoptosis, autophagic cell death, and necrosis) in a microcancer model described herein can include incubating the microcancer model with one or more dyes specific for mitochondria membrane potential and / or mitochondrial superoxide production to assess apoptosis. For example, a microcancer model described herein can be incubated with annexin V fluorescent conjugates and / or caspase 3 / 7 specific fluorescent dyes to assess apoptosis. In some cases, a microcancer model described herein can be incubated with an RFP-GFP-LC3B tandem sensor such as a Fluorescent Premo™ Autophagy' Tandem Sensor RFP-GFP-LC3B or a luminescent LC3 reporter system such as an Autophagy LC3 HiBiT Reporter Assay System to visualize pH changes and quantitatively measure autophagic flux to assess autophagic cell death. In some cases, a microcancer model described herein can be incubated with propidium iodide, a green fluorescent nuclear and chromosome counterstain that is impermeant to live cells such as SYTOX™ green fluorescent dye, and / or Deep Red fluorescent dye to assess necrosis. In some cases, an assay that assesses annexin V binding and DNA release such as RealTime-Glo™ Annexin V Apoptosis and Necrosis Assay7can be used to assess necrosis in a microcancer model described herein. In some cases, using live imaging to monitor cell death in a microcancer model described herein can include incubating the microcancer model with one or more dyes that are agnostic to the mechanism of cell death. For example, a microcancer model described herein can be incubated with CellTox™, PKH26, Cytotox, and / or C.Live Tox to monitor cell death agnostic to the mechanism of cell death. In some cases, a microcancer model described herein can be assessed by live imaging to monitor cellular senescence in the microcancer model. For example, a microcancer model described herein can be incubated with Beta-Glow to monitor cellular senescence. In some cases, multiple different dyes can be incubated with the same microcancer model. For example, a dye for assessing apoptosis, a dye for assessing autophagic cell death, and a dye for assessing necrosis can be used together with one microcancer model. In some cases, a single dye can be incubated with a microcancer model to assess multiple characteristics. For example, a microcancer model described herein can be incubated with ApoTox-Glo™ to assess cell viability, cytotoxicity, and apoptosis.

[0065] In some cases, one or more of those microcancer models and / or a portion of the originally obtained sample (e.g.. a portion of a cancer biopsy) can be assessed by multi-omic analysis. For example, a microcancer model described herein and / or a portion of the originally obtained sample (e.g., a portion of a cancer biopsy) can be assessed by any appropriate multi-omic analysis technique. Examples of multi-omic analyses that can be performed to assess a microcancer model and / or a portion of the originally obtained sample (e.g., a portion of a cancer biopsy) include, without limitation, next generation sequencing (NGS), mate-pair whole-genome DNA sequencing (MPseq), RNA sequencing (RNAseq), whole exome sequencing (WES), whole genome sequencing (WGS), single cell or single nucleus RNA sequencing, epigenomic sequencing, spatial profiling, proteomics, and metabolomics. In some cases, a microcancer model described herein can be assessed by whole genome sequencing. In some cases, a portion of the originally obtained sample (e.g., a portion of a cancer biopsy) used to generate a microcancer model described herein can be assessed by whole genome sequencing. In some cases, both a microcancer model described herein and a portion of the originally obtained sample (e.g.. a portion of a cancer biopsy) used to generate that microcancer model can be assessed by whole genome sequencing.

[0066] As described herein, a microcancer model or a collection of microcancer models described herein can be used to identify one or more candidate anti-cancer treatments that are likely to be effective in treating a particular mammal’s cancer (e.g.. a particular human’s brain cancer such as a glioma) based, at least in part, on the ability to promote reduced cell viability in one or more of that mammal’s microcancer models (as compared to the cell viability in one or more of the mammal’s control microcancer models not contacted with any potential anti-cancer treatments). For example, if the cell viability in one or more of a mammal’s microcancer models (e.g., one or more of a human’s microcancer models) contacted with a candidate anti-cancer treatment is reduced (e.g., as compared to the cell viability in one or more of that mammal’s control microcancer models that were not contacted with the candidate anti-cancer treatment), then the candidate anti-cancer treatment can be classified as being likely to be effective in treating that mammal’s cancer. In some cases, if the cell viability in one or more of a mammal’s microcancer models contacted with a potential anti-cancer treatment is not reduced (e.g., as compared to the cell viabi li ty in one or more of that mammal’s control microcancer models not contacted with any potential anticancer treatments), then that potential anti-cancer treatment can be classified as being unlikely to be effective in treating that mammal’s cancer.

[0067] In some cases, determining if a potential anti-cancer treatment is likely to be effective in treating a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) can include comparing the cell viability in one or more of that mammal’s microcancer models contacted with the potential anti-cancer treatment to the cell viability in one or more of that mammal’s microcancer models not contacted with that potential anti-cancer treatment; and classifying the potential anti-cancer treatment as being likely to be effective in treating that mammal’s cancer if the cell viability in one or more of that mammal’s microcancer models contacted with the potential anti -cancer treatment is reduced compared to the cell viability in one or more of that mammal’s microcancer models not contacted with that potential anticancer treatment; or classifying the potential anti-cancer treatment as being unlikely to be effective in treating that mammal’s cancer if the cell viability in one or more of that mammal’s microcancer models contacted with that potential anti-cancer treatment is not reduced compared to the cell viability in one or more of that mammal’s microcancer models not contacted with that potential anti-cancer treatment. In some cases, determining if a potential anti-cancer treatment is likely to be effective in treating a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) can include (a) contacting one or more of that mammal’s microcancer models with the potential anti-cancer treatment; (b) comparing the cell viability in one or more of that mammal’s microcancer models contacted with the potential anti-cancer treatment following the contacting step (a) to the cell viability in one or more of that mammal’s microcancer models not contacted with that potential anti-cancer treatment; and (c) classifying the potential anti-cancer treatment as being likely to be effective in treating that mammal’s cancer if the cell viability in one or more that that mammal’s microcancer models contacted with the potential anti-cancer treatment is reduced compared to the cell viability in one or more of that mammal's microcancer models not contacted with that potential anti-cancer treatment; or (d) classifying the potential anti-cancer treatment as being unlikely to be effective in treating that mammal’s cancer if the cell viability in one or more of that mammal’s microcancer models contacted with the potential anti-cancer treatment is not reduced compared the cell viability in one or more of that mammal’s microcancer models not contacted with that potential anti-cancer treatment. Any appropriate method can be used to contact a microcancer model described herein with a potential anti-cancer treatment. In cases where a potential anti-cancer treatment includes administration of one or more anti-cancer compounds, contacting one or more microcancer models described herein can include culturing the one or more microcancer models in a solution (e.g., a culture medium) containing each of the one or more anti-cancer compounds. A microcancer model described herein can be contacted with a potential anticancer treatment for any appropriate amount of time. In some cases, a microcancer model described herein can be contacted with a potential anti-cancer treatment for the amount of time necessary7to determine whether the cell viability in the microcancer model has been reduced. For example, contacting a microcancer model described herein with a potential anticancer treatment can occur over several hours, several days, or several weeks. In some cases, contacting a microcancer model described herein with a potential anti-cancer treatment can occur from about 12 hours to about 10 weeks (e.g., from about 1 day to about 8 weeks, from about 3 days to about 8 weeks, from about 4 days to about 8 weeks, from about 5 days to about 8 weeks, from about 7 days to about 8 weeks, from about 8 days to about 8 weeks, from about 9 days to about 8 weeks, from about 10 days to about 8 weeks, from about 11 days to about 8 weeks, from about 12 days to about 8 weeks, from about 13 days to about 8 weeks, from about 14 days to about 8 weeks, or from about 3 weeks to about 8 weeks). In some cases, contacting a microcancer model described herein with a potential anti-cancer treatment can occur over 12 hours. In some cases, contacting a microcancer model described herein with a potential anti-cancer treatment can occur over 3 days. In some cases, contacting a microcancer model described herein with a potential anti-cancer treatment can occur over 6 days. In some cases, contacting a microcancer model described herein with a potential anticancer treatment can occur over 3 weeks.

[0068] Any appropriate mammal having a cancer (e.g., a brain cancer such as glioma) can be assessed and / or treated as described herein. Examples of mammals that can have cancer (e.g., a glioma) and can be assessed and / or treated as described herein include, without limitation, humans, non-human primates (e.g., monkeys), dogs, cats, horses, cows, pigs, sheep, mice, and rats. In some cases, a human having a cancer (e.g., a brain cancer such as glioma) can be assessed and / or treated as described herein.

[0069] When assessing anti-cancer treatments and / or treating a mammal (e.g., a human) having a cancer as described herein, the cancer can be any type of cancer. In some cases, the cancer can include one or more solid tumors. In some cases, the cancer can be a blood cancer. In some cases, the cancer can be a primary' cancer. In some cases, the cancer can be a metastatic cancer. In some cases, the cancer can be a refractory cancer. In some cases, the cancer can be a relapsed cancer. Examples of cancers that can be assessed and / or treated as described herein include, without limitation, brain cancers, breast cancers, lung cancers, liver cancers, skin cancers, colon cancers, renal cancers, head and neck cancers, hepatocellular carcinomas, endometrial cancers, cholangiocarcinomas, rhabdomyosarcomas, gallbladder cancers, ovarian cancers, uterine cancers, mesotheliomas, renal cancers, sarcomas, pancreas cancers, bladder cancers, anus cancers, bone marrow cancers, peritoneum cancers, prostate cancers, testis cancers, thyroid cancers, ureter cancers, and vaginal cancers. Examples of brain cancers that can assessed and / or treated as described herein include, without limitation, gliomas (e.g., GBMs), acoustic neuromas (schwannomas), pituitary adenomas, medulloblastomas, meningiomas, astrocytomas, oligodendrogliomas, and pediatric gliomas. When a brain cancer is a glioma, the glioma can be any grade glioma (e.g., grade 1 glioma, grade 2 glioma, grade 3 glioma, or grade 4 glioma (GBM)).

[0070] In some cases, the methods described herein can include identifying a mammal (e.g., a human) as having a cancer (e.g., a brain cancer such as glioma). Any appropriate method can be used to identify a mammal as having a cancer (e.g., a brain cancer such as glioma). Examples of techniques that can be used to confirm the presence of cancer (e.g., a brain cancer such as glioma) include, without limitation, neurological examinations (e.g., checking vision, hearing, balance, coordination, strength, and / or reflexes), imaging tests (e.g., MRI, computerized tomography (CT), and / or positron emission tomography (PET)), and laboratory tests based on blood or tissue biopsy samples.

[0071] As described herein, a potential anti-cancer treatment can be identified as being a candidate anti-cancer treatment that is likely to be effective in treating a particular mammal (e.g., a particular human) having a cancer (e.g., a brain cancer such as glioma) by comparing the cell viability in one or more of the mammal’s microcancer models generated as described herein and contacted with the potential anti-cancer treatment to the cell viability in one or more of that mammal’s microcancer models not contacted with that potential anti-cancer treatment. Any appropriate method can be used to assess cell viability . For example, cell viability can be assessed by examining live versus dead cells in a microcancer model. In some cases, cell viability' can be assessed by examining cellular mechanisms such as cell proliferation, membrane integrity, mitochondrial membrane integrity, enzy me activity, and / or metabolic activity'. For example, nucleic acid binding dyes, amine-reactive viability dyes, enzyme activity assays, Ki67 staining, and / or metabolic activity assays such as measurement of ATP concentration can be used to assess cell viability in a microcancer model. Such assays can be performed on any appropriate detection platform including, without limitation, light microscopy, fluorescence microscopy, immunohistochemistry’, flow cytometry, and microplate reader. In some cases, cell viability can be assessed by quantifying cell viability'. For example, a luminescent assay can be used to quantify cell viability in a microcancer model.

[0072] When assessing cell viability in a particular mammal's microcancer model described herein, any appropnate level of reduced cell viability can be detected and used to identify candidate anti-cancer treatments for that particular mammal (e.g., that particular human). For example, the cell viability' in a particular mammal’s microcancer model described herein that was contacted with a potential anti-cancer treatment can be reduced by at least 5% (e.g., about 5%, about 10%, about 20%, about 30%. about 40%, about 50%, about 60%, about 70%, about 80%, about 90%, about 95%, or more such as 100%) as compared to the cell viability in a control microcancer model for that mammal not contacted with the potential anti-cancer treatment. In some cases, the cell viability in a particular mammal’s microcancer model described herein that was contacted with a potential candidate anti-cancer treatment can be reduced by at least 2 (e.g., at least 5, at least 10, at least 15, at least 20, at least 25, at least 35, or at least 50) fold as compared the cell viability in a control microcancer model for that mammal not contacted with the potential anti -cancer treatment.

[0073] In some cases, the effectiveness of a potential anti-cancer treatment can be represented as a percentage of reduced cell viability in a particular mammal’s collection of microcancer models as compared to the cell viability in one or more control microcancer models for that mammal not contacted with the potential anti-cancer treatment. In some cases, the effectiveness of a potential anti -cancer treatment (e g., represented as a percentage of reduced cell viability in a mammal’s collection of microcancer models as compared the cell viability in one or more control microcancer models for that mammal not contacted with the potential anti-cancer treatment) can be assessed at various drug concentrations. For example, the effectiveness of a potential anti-cancer treatment (e.g., represented as a percentage of reduced cell viability in the mammal's collection of microcancer models as compared to the cell viability in one or more control microcancer models for that mammal not contacted with the potential anti-cancer treatment) can be assessed at the anticipated Cmax of a drug of a potential anti-cancer treatment.

[0074] In general, each drug of a potential anti-cancer treatment will be administered to a mammal (e.g., a human) at an acceptable dose per administration. In some cases, that dose is set by a regulatory agency such as the U.S. Federal Drug Administration or determined by a practicing clinician. After administering a drug at a particular dose to a mammal, that amount of administered drug will achieve a maximum concentration within the mammal’s blood, plasma, cerebral fluid, and / or tissues. That maximum concentration is referred to the Cmaxfor that dose of that drug. In general, Cmax values are know n or can be measured for the typical drug dosages used to treat mammals (e.g., humans).

[0075] In some cases, the anticipated Cmax values of drugs can be used to identify candidate anti-cancer treatments that are likely to be effective against a particular mammal’s cancer. For example, a first potential anti-cancer treatment can be a treatment that involves administering 100 mg of drug 1 to a human having brain cancer with that dose achieving a plasma Cmax of 10 ng / mL. In this case of assessing this first potential anti-cancer treatment, the mammal’s microcancer models can be exposed to that Cmax value and cell viability assessed and compared to one or more of that mammal’s control microcancer models. If cell viability assessed at that Cmaxvalue results in promoting a reduction in cell viability, then that first potential anti-cancer treatment can be identified as being a candidate anti-cancer treatment that is likely to be effective against that particular mammal’s cancer. If the Cmax value of drug 1 within brain tissue is known, then the mammal’s microcancer models can be exposed to that Cmax value and cell viability assessed and compared to one or more of that mammal’s control microcancer models.

[0076] In another example, a second potential anti-cancer treatment can be a treatment that involves administering 200 mg of drug 1 to a human having brain cancer with that dose achieving a plasma Cmax of 15 ng / mL. In this case of assessing this second potential anticancer treatment, the mammal’s microcancer models can be exposed to that Cmaxvalue and cell viability assessed and compared to one or more of that mammal’s control microcancer models. If cell viability' assessed at that Cmaxvalue results in promoting a reduction in cell viability, then that second potential anti-cancer treatment can be identified as being a candidate anti-cancer treatment that is likely to be effective against that particular mammal’s cancer.

[0077] In another example, a third potential anti-cancer treatment can be a treatment that involves administering 100 mg of drug 2 to a human having brain cancer with that dose achieving a Cmaxwithin the brain of 5 ng / mm3. In this case of assessing this third potential anti-cancer treatment, the mammal’s microcancer models can be exposed to that Cmaxvalue and cell viability assessed and compared to one or more of that mammal's control microcancer models. If cell viability assessed at that Cmax value results in promoting a reduction in cell viability, then that third potential anti-cancer treatment can be identified as being a candidate anti-cancer treatment that is likely to be effective against that particular mammal’s cancer.

[0078] In another example, a fourth potential anti-cancer treatment can be a treatment that involves administering a combination of 100 mg of drug 1 and 100 mg of drug 2 to a human having brain cancer with that dose of drug 1 achieving a plasma Cmaxof 10 ng / mL and with that dose of drug 2 achieving a Cmaxwithin the brain of 5 ng / mm3. In this case of assessing this fourth potential anti-cancer treatment, the mammal’s microcancer models can be exposed to that Cmax value for drug 1 and that Cmaxvalue for drug 2 and cell viability assessed and compared to one or more of that mammal's control microcancer models. If cell viability assessed at those Cmaxvalues results in promoting a reduction in cell viability, then that fourth potential anti-cancer treatment can be identified as being a candidate anti-cancer treatment that is likely to be effective against that particular mammal’s cancer.

[0079] In some cases, potential anti-cancer treatments that include two different drugs can be identified as being a candidate anti-cancer treatment that is likely to be effective against a particular mammal’s cancer by assessing each of the two drugs individually and each together and then comparing effectiveness in reducing cell viability of each drug individually to the effectiveness when used in combination. For example, when a potential anti-cancer treatment includes a combination of two different drugs (e.g., drug 1 plus drug 2), one or more of a mammal’s microcancer models can be exposed the first drug (e.g., drug 1), one or more of that mammal’s microcancer models can be exposed the second drug (e.g., drug 2). and one or more of that mammal’s microcancer models can be exposed both the first drug and the second drug (e.g., drug 1 and drug 2), and cell viability can be assessed. If the combination outperforms both drugs when used individually, then that particular anti-cancer treatment can be identified as being a candidate anti-cancer treatment that is likely to be effective against that particular mammal’s cancer.

[0080] In some cases, the anticipated Cmaxvalues of each drug used in a potential drug combination treatment can be used to identify candidate anti-cancer treatments involving the use of two or more drugs that are likely to be profoundly synergistically effective against a particular mammal’s cancer. For example, when a potential anti-cancer treatment involves administering a combination of 100 mg of drug 1 and 100 mg of drug 2 to a human having brain cancer with that dose of drug 1 achieving a plasma Cmaxof 10 ng / mL and with that dose of drug 2 achieving a Cmaxwithin the brain of 5 ng / mm’, one or more of that human’s microcancer models can be exposed to that Cmaxvalue for drug 1. one or more of that human’s microcancer models can be exposed to that Cmaxvalue for drug 2, and one or more of that human’s microcancer models can be exposed to both that Cmax value for drug 1 and that Cmax value for drug 2. In this case, the reduction in cell viabilities resulting from exposure to the Cmax value of drug 1 alone, the reduction in cell viabilities resulting from exposure to the Cm x value of drug 2 alone, and the reduction in cell viabilities resulting from exposure to both the Cmax value of drug 1 and the Cmax value of drug 2 can be compared to determine if the combination resulted in a meaningful additional benefit against that particular human’s cancer.

[0081] In some cases, combination treatment efficacy is depicted using an xy plot, where the x axis is the percent inhibition of cell viability of drug 1 at drug l’s Cmax and the y axis is the percent inhibition of cell viability of drug 2 at drug 2’s Cmax (see, e.g., Figure 28). The first (x,y) data point can be plotted based on the percent inhibition of cell viability of drug 1 alone at its Cmax (x) and the percent inhibition of cell viability of drug 2 tested alone at its Cmax (y), while the second (X,Y) data point can be plotted based on the percent inhibition of cell viability' for the combined exposition to both drug 1 and drug 2 at the Cmax of drug 1 (X) and the Cmax of drug 2 (Y). An example of such plotting is shown in Figure 28. When plotting the results in this manner, if a connecting line from the first data point to the second data point results in an upward slope angled to the right, then that potential anti-cancer treatment can be identified as being a candidate anti-cancer treatment involving a combination of two drugs likely to have an added level of effectiveness against that particular human’s cancer. For example, when viewed as the hour arm of a conventional clock, any position from after 12:00 to before 1 :00 or from after 2:00 to before 3:00 can be used to identify that potential anticancer treatment as being a candidate anti-cancer treatment involving a combination of two drugs likely to have an added level of effectiveness against that particular human’s cancer. In some cases, any position from 1 :00 to 2:00 can be used to identify that potential anti-cancer treatment as being a candidate anti-cancer treatment involving a combination of two drugs likely to be profoundly synergistically effective against that particular human’s cancer. Any other direction of the line from the first data point to the second data point can indicate that the combined use of the two drugs provides little, if any, added benefit for that particular mammal having cancer. For example, when viewed as the hour arm of a conventional clock, any position from after 3:00 to 12:00 can be used to identity' that potential anti-cancer treatment as involving a combination of two drugs unlikely to have an added level of effectiveness against that particular mammal’s cancer.

[0082] Generating this type of data for each drug individually and in combination and plotting that data in this manner can allow clinicians to quickly identify candidate anti-cancer treatments, from among tens, hundreds, and even thousands of potential anti-cancer treatments, that are meaningful candidates for the particular mammal (e.g., human) being assessed and treated. This approach also allows clinicians to avoid administering a potential anti-cancer treatment that may be very' effective in other mammals (e.g., other humans) to a particular mammal (e.g., a particular human) that is unlikely to experience a beneficial outcome with that otherwise effective treatment. This type of individually tailored approach can help prolong cancer survival for patients.

[0083] In some cases, a candidate anti-cancer treatment identified as being likely to be effective in treating a particular mammal (e.g., a particular human) having a cancer (e.g., a brain cancer such as glioma) as described herein can be selected to be administered to that particular mammal to treat that mammaTs cancer. For example, a candidate anti-cancer treatment identified as being likely to be effective in treating a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) based on, at least in part, a reduction of cell viability in one or more of that mammal’s microcancer models contacted with that candidate anti-cancer treatment as compared to cell viability’ in one or more control microcancer models for that mammal that were not contacted with the candidate anti-cancer treatment, can be selected to be administered to that mammal to treat that mammal’s cancer.

[0084] Any appropriate anti-cancer treatment or suspected anti-cancer treatment can be assessed as described herein to determine if it is likely to be effective against a particular mammal’s cancer. For example, individual chemotherapeutic agents, individual targeted cancer drugs, individual immunotherapy drugs, radiation therapy, antibodies, antibody-drug conjugates, bispecific antibodies, oncolytic viruses, cellular therapies, PROTACs, two or more chemotherapeutic agents, two or more targeted cancer drugs, two or more immunotherapy drugs, and any combination chemotherapeutic agents, targeted cancer drugs, and / or immunotherapy drugs can be assessed as described herein to identify anti-cancer treatments 1 i kely to be effective against a particular mammal’s cancer. Examples of anticancer treatments that can be assessed as described herein include, without limitation, temozolomide, carboplatin, cisplatin, doxorubicin, gemcitabine, paclitaxel, abemaciclib, vorinostat, neratinib. osimertinib, sunitinib, pimasertib, paxalisib. capivasertiv, idasanutlin. ulixertinib, foretinib, navitoclax, niraparib, JQ1, trotabresib, CC-115, vorasidenib, vistusertib, afatinib, alisertib, alpelisib, pembrolizumab, durvalumab, nivolumab, atezolizumab, sacituzumab govitecan, enfortumab vedotin. tisotumab vedorin, T-DM1, T-DXd, amivantamab-vmjw, teclistamab-cqyv. blinatumomab, VSV, Morreton virus, VMG, CAR T- cells), MZ-1, and MET-PROTAC. In some cases, after identifying a candidate anti-cancer treatment as being likely to be effective in treating a particular mammal (e.g., a particular human) having a cancer (e.g.. a brain cancer such as glioma) as described herein and administering that identified candidate anti-cancer treatment to that particular mammal, the effectiveness of that administered candidate anti-cancer treatment can be monitored over time using one or more of that mammal's microcancer models. For example, one or more of a mammal's microcancer models can be exposed to the candidate anti-cancer treatment administered to the mammal in a similar manner (e.g., at the same timing and at the predicted or measured Cmax for the cancer target) and those microcancer models can be monitored over time for the emergence of drug resistance or drug escape within the microcancer models.

[0085] In some cases, a large collection of a mammal's (e.g., a human’s) microcancer models can be exposed to the candidate anti -cancer treatment being administered to that mammal in a similar manner such that that the large collection of microcancer models potentially mimics the evolution of the actual cancer cells and / or cancer tissue within the treated mammal. Such microcancer models can be referred to herein as treatment-exposed microcancer models. If resistant cancer cells are observed as remaining and / or emerging across some, most, or all the treatment-exposed microcancer models, then the clinician can stop or taper off the administration of that candidate anti-cancer treatment for that mammal and a similar stopping or tapering can be carried out for the collection of treatment-exposed microcancer models. At that time or after a period of time (e.g., from about 14 days to about 48 days), potential anticancer treatments can be assessed using one or more of the treatment-exposed microcancer models for that mammal to identify one or more candidate anti-cancer treatments likely to be effective against that particular mammal’s potentially resistant cancer so that the clinician can select an effective second anti-cancer treatment for that particular mammal. Additional rounds of this ex vivo mimicking of in vivo cancer treatments can be carried out as well.

[0086] This document also provides methods for treating a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma). In some cases, a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) that is assessed using microcancer models for that mammal as described herein (e.g.. to identify one or more candidate anti-cancer treatment likely to be effective in treating that mammal ’s cancer) can be administered or instructed to self-administer a candidate anti-cancer treatment identified as being likely to be effective in treating that mammal. For example, a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) can be administered or instructed to self-administer an anti-cancer treatment that is selected based, at least in part, on its identification as being a candidate anti-cancer treatment likely to be effective in treating that mammal’s (e.g., that human’s) cancer (e.g., brain cancer such as glioma) using that mammal’s microcancer models as described herein.

[0087] In some cases, when a candidate anti-cancer treatment is identified as being likely to be effective in treating a mammal (e g., a human) having a cancer (e.g., a brain cancer such as glioma) based, at least in part, on the reduction of cell viability in one or more of that mammal’s microcancer models as described herein, the mammal can be administered or can be instructed to self-administer that candidate anti-cancer treatment.

[0088] In some cases, when treating a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) with a candidate anti-cancer treatment identified as being likely to be effective in treating that mammal’s cancer as described herein, that anti-cancer treatment can be the sole anti-cancer treatment used to treat that mammal’s cancer.

[0089] In some cases, when an anti-cancer treatment is identified as being unlikely to be effective in treating a mammal’s cancer (e g., a human’s cancer) based, at least in part, on an absence of a reduction of cell viability in one or more of that mammal’s microcancer models contacted with that potential anti-cancer treatment, the mammal can be administered or instructed to self-administer an alternative anti-cancer treatment.

[0090] This document also provides methods for treating a mammal (e.g., a human) having a brain cancer (e g., a glioma). For example, any one or more of the compounds set forth in Table 1 can be administered to a mammal (e.g., a human) having a brain cancer (e.g., a glioma) to treat that brain cancer. In some cases, a mammal (e.g., a human) having a brain cancer (e.g., a glioma) can be treated with any combination of compounds set forth in Table 2.

[0091] Table 1. Compounds for treating brain cancer

[0092] Table 2. Compound combinations for treating brain cancer

[0093] In some cases, one of the compounds set forth in Table 1 can be administered to a mammal (e.g., a human) having a brain cancer (e.g., a glioma) as the sole active ingredient to treat the cancer. In some cases, one of the combinations of compounds set forth in Table 2 can be administered to a mammal (e.g., a human) having a brain cancer (e.g., a glioma) as the sole active ingredients to treat the cancer.

[0094] In some cases, when treating a mammal (e.g., a human) having a brain cancer (e.g.. a glioma) as described herein (e.g., by administering (a) any one or more of the compounds set forth in Table 1 or (b) any combination of compounds set forth in Table 2), the one or more compounds can be administered to the mammal having cancer in any appropriate amount (e.g., any appropriate dose). In some cases, an effective dose of one or more compounds can be a flat dose. In some cases, and effective dose of one or more compounds can be based on the body of a mammal (e.g., a human) to be treated as described herein. In some cases, an effective amount of one or more compounds can be from about 0.001 mg of compound per kg body weight of a mammal (mg / kg) to about 100 mg / kg (e.g., from about 0.005 mg / kg to about 100 mg / kg, from about 0.01 mg / kg to about 100 mg / kg, from about 0.05 mg / kg to about 100 mg / kg, from about 0.1 mg / kg to about 100 mg / kg, from about 0.5 mg / kg to about 100 mg / kg, from about 1 mg / kg to about 100 mg / kg, from about 1.5 mg / kg to about 100 mg / kg, from about 5 mg / kg to about 100 mg / kg, from about 0.005 mg / kg to about 75 mg / kg, from about 0.005 mg / kg to about 50 mg / kg, from about 0.005 mg / kg to about 25 mg / kg, from about 0.005 mg / kg to about 10 mg / kg. from about 0.005 mg / kg to about 5 mg / kg, from about 0.005 mg / kg to about 1 mg / kg, from about 0.01 mg / kg to about 50 mg / kg, from about 0. 1 mg / kg to about 25 mg / kg, from about 0.5 mg / kg to about 25 mg / kg, from about 1 mg / kg to about 25 mg / kg, or from about 1 mg / kg to about 15 mg / kg). The effective amount of one or more compounds can remain constant or can be adjusted as a sliding scale or variable dose depending on the mammal’s response to treatment. Various factors can influence the actual effective amount used for a particular application. For example, the frequency of administration, duration of treatment, use of multiple treatment agents, route of administration, and / or severity of the cancer in the mammal being treated may require an increase or decrease in the actual effective amount administered.

[0095] In some cases, when treating a mammal (e.g., a human) having a brain cancer (e.g., a glioma) as described herein (e.g., by administering (a) any one or more of the compounds set forth in Table 1 or (b) any combination of compounds set forth in Table 2), the one or more compounds can be administered to a mammal having brain cancer at any appropriate frequency. The frequency of administration can be any frequency that can treat a mammal having cancer without producing significant toxicity to the mammal. For example, the frequency of administration can be from about twice a day to about once every7other day, from about once a day to about once a week, from about once a day to about once a month, from about once a week to about once a month, or from about twice a month to about once a month. The frequency of administration can remain constant or can be variable during the duration of treatment. As with the effective amount, various factors can influence the actual frequency of administration used for a particular application. For example, the effective amount, duration of treatment, use of multiple treatment agents, and / or route of administration may require an increase or decrease in administration frequency.

[0096] In some cases, when treating a mammal (e.g., a human) having a brain cancer (e.g., a glioma) as described herein (e.g., by administering (a) any one or more of the compounds set forth in Table 1 or (b) any combination of compounds set forth in Table 2), the one or more compounds can be administered to a mammal (e.g., a human) having brain cancer (e.g., a glioma) for any appropriate duration. An effective duration can be any duration that can treat a mammal having cancer without producing significant toxicity7to the mammal. For example, the effective duration can vary from several weeks to several months, from several months to several years, or from several years to a lifetime. Multiple factors can influence the actual effective duration used for a particular treatment. For example, an effective duration can vary with the frequency^ of administration, effective amount, use of multiple treatment agents, and / or route of administration.

[0097] In some cases, the methods and materials provided herein can include monitoring the mammal (e.g., the human) being treated as described herein (e.g.. by administering (a) any one or more of the compounds set forth in Table 1 or (b) any combination of compounds set forth in Table 2). For example, the size of the cancer (e.g., the number of cancer cells and / or the volume of one or more tumors) present within a mammal can be monitored. Any appropriate method can be used to determine whether or not the size of the cancer present within a mammal is reduced. For example, imaging techniques can be used to assess the size of the cancer present within a mammal (e.g., a human).

[0098] In some cases, when treating a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) as described herein, the treatment can be effective to treat the cancer. For example, the number of cancer cells present within a mammal can be reduced using the methods and materials described herein. In some cases, the methods and materials described herein can be used to reduce the number of cancer cells present within a mammal (e.g.. a human) having a cancer (e g., a brain cancer such as glioma) by, for example, 10, 20, 30, 40, 50, 60, 70, 80, 90, 95, or more percent. In some cases, when treating a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) as described herein, the treatment can be elfective to prevent an increase in the number of cancer cells present within the mammal receiving the treatment. In some cases, the number of cancer cells present within a mammal (e.g., a human) having a cancer (e.g., glioma) and being treated as described herein can be monitored. Any appropriate method can be used to determine whether or not the number of cancer cells present within a mammal is reduced. For example, imaging techniques can be used to assess the number of cancer cells present within a mammal.

[0099] In some cases, when treating a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) as described herein, the treatment can be effective to reduce the size of a tumor present in the mammal receiving the treatment. In some cases, the methods and materials described herein can be used to reduce the size of one or more tumors present within a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) by, for example, 10, 20, 30, 40, 50, 60, 70, 80, 90, 95, or more percent. In some cases, the size (e.g., volume) of one or more tumors present within a mammal does not increase. Any appropriate method can be used to determine whether or not the size of the tumor present within a mammal is reduced. For example, imaging techniques can be used to assess the size of the tumor present within a mammal.

[0100] In some cases, when treating a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) as described herein, the treatment can be effective to improve survival of the mammal. For example, the methods and materials described herein can be used to improve disease-free survival (e.g., relapse-free survival). For example, the methods and materials described herein can be used to improve overall survival. For example, the methods and materials described herein can be used to improve the survival of a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) by, for example, 10. 20. 30. 40. 50, 60, 70, 80, 90, 95, or more percent. For example, the methods and materials described herein can be used to improve the survival of a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) by, for example, at least 4 months (e.g., about 4 months, about 6 months, about 8 months, about 10 months, about 1 year, about 1.5 years, about 2 years, about 2.5 years, or about 3 years).

[0101] In some cases, when treating a mammal (e.g., a human) having a cancer (e.g.. a brain cancer such as glioma) as described herein, the treatment can be effective to reduce or eliminate one or more symptoms of the cancer (e.g.. the ghoma). Examples of symptoms of a cancer (e g., a brain cancer such as glioma) that can be reduced or eliminated using the methods and materials described herein can include, without limitation, headache, nausea, vomiting, confusion, a decline in brain function, problems with thinking and understanding information, memory loss, personality changes, irritability, vision problems, blurred vision, double vision, loss of peripheral vision, speech difficulties, and seizures. For example, the methods and materials described herein can be used to reduce one or more symptoms of a cancer (e g., a brain cancer such as ghoma) within a mammal (e.g., a human) by, for example, 10, 20, 30, 40, 50, 60, 70, 80, 90, 95, or more percent.

[0102] In some cases, the number of cancer cells present within a mammal (e.g., a human) having a cancer (e.g., a brain cancer such as glioma) and being treated as described herein can be monitored. For example, imaging techniques can be used to assess the number of cancer cells present within a mammal.

[0103] The invention will be further described in the following examples, which do not limit the scope of the invention described in the claims.

[0104] EXAMPLES

[0105] Example 1: Generation and characterization of patient-derived microcancer models

[0106] This example describes the generation and characterization of microcancer models derived from glioma patients for use in functional drug screening and for the rapid interrogation of potential vulnerabilities to targeted treatments.

[0107] Materials and Methods

[0108] Study design

[0109] A portion of resected tumor measuring 1-2 cubic cm from each patient was selected by the pathologist and equally split into two pieces. One w as immediately flash frozen for nucleotide sequencing and one cryopreserved for microcancer generation and drug screening. Pathological characterization was performed to ensure disease histology. A pre-defined single (n=16) and combination (n=7) drug screen panel was tested in microcancers of all gliomas with sufficient tissue, except for vorasidenib, which was only tested in IDH-mut cases. The top five most effective agents were subjected to further statistical and bioinformatical analyses for discovery of predictive biomarkers. The increased efficacy of drug combinations was quantified by calculating the differential drug efficacy of combination treatment over that of corresponding single agents at their Cmax.

[0110] Patient enrollment

[0111] Patients with HGG who sought consultation with clinical investigators participating in this study were offered participation in the ex vivo study. Patient consent and sample donation and processing were reviewed and approved by the Mayo Clinic Institutional Review Board.

[0112] Multi-omic sequencing pipeline and bioinformatic processing

[0113] MPseq, WES, and RNAseq were performed after isolation of DNA and RNA from flash-frozen tumor tissue and analyzed (Vasmatzis et al. , Mayo Clin Proc, 95: 306 (2020)). Tumor was identified by gross and frozen section microscopic examination in the Mayo Clinic Frozen Section Laboratory. Fresh tumor in excess of diagnostic clinical material was placed in a plastic cassette and snap frozen in isopentane. A secondary review by an experienced surgical pathologist was performed using a toluidine blue-stained frozen section. A tumor cellularity of >40% in the sample was obtained that included the use of macrodissection or laser capture microdissection as needed (Murphy et al., DNA Res, 19: 395 (2012)). DNA was extracted with the Qiagen AllPrep DNA / RNA mini kit (80204, Qiagen) or Qiagen DNeasy Blood and Tissue Kit (69504. Qiagen) following the manufacturer’s protocol. In cases where laser capture microdissection was done or initial DNA yield was too low' for sequencing (e g., PT427), whole genome amplification was performed using the Repli-G mini kit (150023, Qiagen) (Murphy et al., DNA Res, 19: 395 (2012)).

[0114] Whole genome sequencing w as performed on all tumor tissue samples using Nextera Mate-Pair Kit (FC-132-1001, Illumina) and MPseq. a low-pass whole-genome DNA sequencing method. All libraries were sequenced at an average depth of 71.5 bridged- coverage, sufficient for DNA junction detection. The sequencing fragment data were mapped to reference genome GRCh38 by BIMA w ith junctions and CNAs called by SVAtools (Drucker et al.. Bioinformatics, 30: 1627 (2014); Johnson et al., Cancer Genet. 221 : 1 (2018)). Junctions were detected from clusters of discordant (based on the mapped location and / or orientation of the reads in each fragment) fragments spanning tw o breakpoints (Johnson et al.. Cancer Genet, 221: 1 (2018)). CNAs were called based on read-depth of concordant fragments (Smadbeck et al., Genes Chromosomes Cancer, 57: 459 (2018)).

[0115] CNAs were determined by the comparison with the genome ploidy for each case. Shallow deletion events included clonal hemizygous deletion and various degrees of subclonal hemizy gous or homozy gous deletion. Deep deletion indicated clonal homozy gous deletion. Amplification was called when a significant copy number gain was observed (e.g., >7n for a diploid genome). Molecular alterations were deemed pathogenic when TSGs exhibited LoF mutation(s) or double-hit, or when oncogenes exhibited GoF mutation(s), copy number amplification, and / or oncogenic fusion transcripts (N. Cancer Genome Atlas Research, Nature, 455: 1061 (2008)). pTERT genotyping by PCR

[0116] The TERT promoter sequence at the two known pathogenic sites C228 and C250 was amplified with M13-TERT genotype primers using Q5® high-fidelity DNA polymerase (M0492S, NEB) (Bell et al. . Science, 348: 459 (2018)). Amplified PCR segments were then gel purified for Sanger sequencing using standard Ml 3 sequencing forward and reverse primers (Genewiz). The PCR primers and their sequences are shown in Table 3.

[0117] Table 3. pTERT Primer Sequences

[0118] Ki-67 staining

[0119] Paraffin-embedded GBM8 xenograft tissue expressing NT-sh virus and microcancers in 5 pm sections were stained for human Ki-67 (M7240, Dako) following standard autostainer (Link 48, Dako) protocol (Lewis-Tuffin et al. , Molecular Oncology), 9: 1783 (2015)). Images were acquired using the Aperio AT2 slide scanner (Leica Biosystems).

[0120] Microcancer generation, data analysis and quality control for drug testing

[0121] Tissue processing was performed using Human Tumor Dissociation Kit (130-095- 929, Miltenyi Biotec) following the manufacturer’s instructions. Dissociated cells were resuspended in microcancer medium, which contains DMEM / F12 media 1143 (SH30023.01, HyClone) supplemented with 10% heat-inactivated horse serum (16050-122. Gibco), 1% penicillin-streptomycin (MT30002CI, Coming), Y-27632 (10 pM; ALX-270-333, Enzo Life Sciences or S1049. Selleckchem), human EGF (10 ng / ml; AF-100-15, PeproTech) and insulin (5 pg / ml; 11882, Sigma). An equal number of cells (5x103) was seeded in 40 pl per well of 96-well Akura™ PLUS hanging drop plates (CS-03-1148 001-00, InSphero) and cultured for 6 days allowing for microcancer generation. Glioblastoma organoid (GBO) medium contained 50% advanced-DMEM:F12 (12634-010, ThermoFisher), 50% Neurobasal (10888022, ThermoFisher), 1X N-2 supplement (17502048, ThermoFisher), 1X B-27 supplement minus vitamin A (12587010, ThermoFisher). IX GlutaMax (35050-06, ThermoFisher), 1% penicillin-streptomycin (MT30002CI, Coming), 50 pM 2- mercaptoethanol (31350010, ThermoFisher), human insulin (2.5 pg / mL; 11882, Sigma), and Y-27632 (10 pM; ALX-270-333, Enzo Life Sciences). Neurosphere medium (5) contained Neurobasal (10888022, ThermoFisher) supplemented with 1X N-2 supplement (17502048, ThermoFisher), IX B-27 supplement minus vitamin A (12587010, ThermoFisher), IX GlutaMax (35050-06, ThermoFisher), 1% penicillin-streptomycin (MT30002CI, Coming), Y-27632 (10 pM; ALX-270-333, Enzo Life Sciences), EGF (25 ng / mL; AF-100-15, PeproTech), and bFGF (25 ng / mL; AF-100-18B, Peprotech) (Jacob et al., Cell. 180: 188 (2020)). Established microcancers were transferred to the corresponding well of 96-well clear round bottom ultra-low attachment microplates (7007, Coming), cultured for 6 days in the presence of drug treatments, and assessed for cell viability using the CellTiter-Glo luminescent assay (G7570, Promega). The luminescence output was interpolated and transformed into nM ATP by comparison to an ATP standard curve. Data were then transformed into LoglO, and the dose response curves were fitted on the basis of four parameter logistic regression with occasional use of three-parameter logistic regression for cases with insufficient points to establish a top and bottom plateau. Upward curves were deemed 0% grow th inhibition. Cases with low ATP values (<10 nM) and poor curve fit were deemed quality control failures.

[0122] Results

[0123] ExVivo-Glioma functional multi-omic workflow

[0124] To identify potential therapeutic vulnerabilities and predictive biomarkers, a functional multi-omics workflow called ‘ExVivo-Glioma’ (Figure 1) w as developed. In this platform, resected tumor tissues were examined by a neuropathologist and divided into two, with one half immediately flash-frozen for subsequent multi-omic profiling and the other half cryopreserved for drug screening. Study population and clinical characteristics

[0125] A total of 47 glioma cases were initially enrolled with 4 being excluded due to patient withdrawal (Figure 2 and Figure 3). Five cases were removed due to lack of adequate tissue. Eight cases failed to establish cancer models or did not pass viability quality control assessments. Therefore, a total of 30 cases proceeded with subsequent studies and are reported here. The overall microcancer culture success rate was 78.9% (30 of 38 cultures). These 30 cases include twenty grade 4 glioblastomas, five grade 3 or grade 4 IDH-mut astrocytomas, and five grade 3 oligodendrogliomas (Table 2). One case (PT448) was complex with a low-grade IDH-mut component and a high-grade component that had lost the IDH-mut. Additionally, the study focused primarily on the recurrent setting (n=22) with inclusion of some newly diagnosed cases (n=8). Patients with recurrent disease received 1-5 prior treatments including chemoradiation, bevacizumab, and tumor-treating fields. The cohort included more female patients (n=14) than males (n=6) in glioblastoma and exclusively males in astrocytomas and oligodendrogliomas (Figure 4) (Table 4). Gliomas were located in the supratentorial region of the brain, including the frontal lobe (n=12), parietal lobe (n=3), temporal lobe (n=5), occipital lobe (n=l), or with involvement of two lobes (n=9). MGMT promoter methylation was present in 9 glioblastoma cases, absent in 9, and not tested or indeterminate in 2 cases (Table 4).

[0126] Table 4. Glioma clinical characteristics

[0127]

[0128] Multi-omic characterization

[0129] Pathology review of frozen sections was first performed before DNA and RNA isolation. MPseq was used to produce whole-genome profiles to identify structural aberrations, including DNA rearrangements, CNAs, and loss of heterozygosity (LOH). Somatic and germline WES were performed to identify mutations. Gene expression was investigated by RNAseq, while gene fusions were investigated by RNA-seq and MPseq (Vasmatzis et al., Mayo Clin Proc, 95: 308 (2020)).

[0130] Most glioblastomas (11 of 20, 55%) in the cohort exhibited the combined gain of the entire chromosome 7 (+7) and loss of the entire chromosome 10 (-10) (Figure 4). Examining core signaling pathways that are frequently deregulated in glioma (N. Cancer Genome Atlas Research, Nature, 455: 1061 (2008)), dysfunction of the p53 / apoptosis pathway was observed in 90% of cases (Figure 4), with TP53 biallelic inactivation observed in 30% of glioblastomas and all IDH-mut astrocytomas. Further, despite high rates of reported MDM2 (11-14%) and MDM4 (4-7%) amplifications in glioblastoma (N. Cancer Genome Atlas Research. Nature, 455: 1061 (2008), the cohort contained no cases with MDM2 amplification, 3 cases with low- level copy number gains of MDM2, and 1 containing co-amplification of MDM4 and EGFR.

[0131] Biallelic inactivation of CDKN2A and CDKN2B were the most frequent alterations related to cell cycle signaling, present in 70% of glioblastomas and 30% of IDH-mut gliomas. Low level copy number gain of CDK6 was present in most glioblastomas (80%), largely due to its location to the frequently gained chromosome 7. Amplification of CCND1 was observed in one case, while RBI double-hit was found in three cases. Combined, deregulation of cell cycle signaling was observed in 73% of cases.

[0132] EGFR amplification was found in 5 cases with one expressing wild-type EGFR, one expressing an ectodomain p. A289D mutation, and the remaining expressing EGFRvIII variant. Two EGFRvIII+ cases concurrently exhibited ectodomain mutations. Further, the cohort included 2 amplified PTPRZ1-MET fusion glioblastomas and 2 F’DGFT -positive astrocytomas, one amplified and one expressing a / .AA / -PDGF A fusion transcript. Downstream of receptor tyrosine kinases (RTKs), 3 cases exhibited NF1 double hits, 1 expressed an oncogenic KRAS mutation, and several exhibited gains in BRAF, which resides in chromosome 7. In general, genomic alterations related to PI3K signaling occurred more frequently (47%) than MEK pathway alterations (20%). with double hits of PTEN being the most common alterations (9 out of 30 cases). Overall, genomic alterations in RTK / MEK / PI3K signaling were observed in 73% of cases.

[0133] Patient-derived pCancer establishment and maintenance of parental tumor features

[0134] To minimize tumor evolution, subcl onal selection, and loss of genomic and cellular heterogeneity, a short-term 3D culture model that can be rapidly established from fresh or cryopreserved tumor tissues was developed. Bulk tumor was disaggregated to individual cells and subsequently allowed to re-aggregate for 6 days in hanging drops of culture media to form 100-300 pm sized 3D microcancers (Vasmatzis et al.. Mayo Clin Proc, 95: 308 (2020)). Using single-cell RNAseq, it was previously reported that microcancers derived from GBM8 PDX tumors maintain the cellular diversity of the original tumor including the presence of glioma stem cells, differentiated glioma cells, and murine stroma (Ganguli et al., Sci Adv, 7 (2021)). GBM8 microcancers also maintained a similar Ki-67 proliferation index to parental orthotopic tumors (Figure 5A). Furthermore, microcancers derived from human glioblastomas maintained proliferative capacity, exhibiting a cell doubling time of ~7 days (Figure 5B). This rate of growth suggests that both cytotoxic and cytostatic effects can be interrogated in microcancers over a 6-day drug treatment, and that short-term culture would minimize selective pressure, thus maintaining the genomic profile of the original tumor.

[0135] To test whether microcancers maintain the genomic profile of parental tumors, MPseq and WES were performed on PT311 -derived microcancers cultured for 6 days (Figure 6 and Figures 7A-7C). Microcancers faithfully retained the +7 / -10 signature, as well as the focal amplification of EGFR on extrachromosomal DNA. an event frequently lost during cell culture (Figure 6) (Nikolaev et al., Nat Commun, 5 5690 (2014); Schulte et al., Clin Cancer Res, 18: 1901 (2012)). Further, parental tumor and resulting microcancers exhibited similar heterozygosity and the same single base substitution signature SBS1 (Figure 6), as well as key oncogenic events, including homozygous 9p21 deletions involving CDKN2A and CDKN2B, and PTEN double hit, with similar allele frequencies (Figure 7A). Microcancers also preserved all 28 mutations identified in the original tumor with one subclonal de novo variant of unknown significance (VUS) found (Figures 7B-7C) (Table 5). Whole genome copy number alterations and DNA rearrangements (95 of 98 events; 96.9%) were also preserved (Figure 8A). Minor subclonal molecular alterations, including mutations and DNA rearrangements, are likely due to the inherent spatial heterogeneity of these tumors, as sequencing for the parental tissue and corresponding microcancers was performed in adjacent but distinct segments of the same tumor (one flash-frozen and the other cryopreserved).

[0136] Finally, the microcancer TERT promoter mutation status was identical to that of the parental tumor (Figure 8B). Overall, several lines of evidence indicate that microcancers recapitulate the genomic landscape of parental tumors with high fidelity. Table 5. Full gene list identified by WES for PT311

[0137] Example 2: Functional drug screen in patient-derived pCancers

[0138] This example describes functional drug screening conducted in patient-derived microcancer models (also referred to as pCancers) as a method for interrogating potential vulnerabilities of cancers to targeted treatments and for identifying new7treatment strategies.

[0139] Materials and Methods uCancer generation and drug screening

[0140] Apportioned fresh tissue specimen was cryopreserved in CryoStor® CS10 cell freezing medium (C2874, Sigma). Thawed tissues were subjected to mechanical and enzymatic dissociation and dissociated cells (5x103per well) were cultured as hanging drops for 6 days to allow microcancer generation (Vasmatzis el al., Mayo Clin Proc, 95: 306 (2020)). Established microcancers were transferred to the corresponding well of 96-well clear round bottom ultra-low attachment microplates (7007, Coming) and subjected to microscopic evaluation to ensure size similarity across wells, before drug testing at eight serial dilutions with corresponding drug solvents (DMSO or media) as vehicle controls. After 6-days of drug treatment, cell viability was quantified using the CellTiter-Glo luminescent assay (G7570, Promega). Cases with inconsistent microcancer sizes and low ATP values were excluded from subsequent analysis. Drug efficacy was represented as percentage of reduced viability at Cmax compared to the baseline vehicle control. Drug combinations were considered more effective when yielding >9.5% increased efficacy than both corresponding single agents.

[0141] Transcription signature subtyping

[0142] RNA-seq data were processed through the MAP-Rseq pipeline (Kalari et al. , BMC Bioinformatics, 15:224 (2014)) to generate “.count’' files which w ere then processed by the edgeR package in R to generate log 2 normalized gene expression values. Normalized enrichment score (NES) for each sample was obtained by the “gsva” function (in GSVA R package) using single sample GSEA (ssgsea) method. To determine the subtype classification of a tumor, the NES for gene sets based on either TCGA (Wang et al. , Cancer Cell, 32: 42 e46 (2017)) or biological pathways (Garofano et al., Nat Cancer, 2: 141 (2021)) were calculated and the subtype with the highest score was assigned to that tumor. The "simplicity score" was computed as the difference between the highest NES and the average of the NES in other subtypes (Wang et al.. Cancer Cell, 32: 42 e46 (2017)). The function ‘geneData’ in the ‘gage’ R package was used to generate heatmaps of differentially expressed genes (p<0.05). Finally, Sankey diagrams were generated by the "sankey" package in R.

[0143] Statistical analysis

[0144] Drug data processing and statistical analysis were performed using the GraphPad Prism software. Unpaired t-test was performed when assessing the impact of pTERT status on microcancer response to JQ1. Correlation analysis was performed using the Spearman and / or Pearson methods as indicated in figure legends. Astrocytomas and glioblastomas with >50% of tumor purity were included for statistical correlation analyses. Tumor purity was inferred based on DNA content (mutation allele fraction and ploidy) and / or RNA expression data (ESTIMATE algorithm, (Y oshihara et al., Nat Commun 4: 2612 (2013)). Correlation analysis was performed using the “contest” function 595 in R software package with Pearson’s correlation coefficient outputs. Statistical significance was assessed at p-value <0.05.

[0145] Results

[0146] Functional drug screen

[0147] Following tissue processing, dissociated tumor cells were allowed to reaggregate for 6 days to form microcancers prior to drug treatment (Figure 9). Initially, the effect of different media formulations on cell viability and drug responses of microcancers from PT303 were compared (Figures 10A-10D). Overall metabolic activity, reflecting cell viability, was higher in the microcancer media, although response to pimasertib, capivasertib, or navitoclax was similar regardless of media formulation (Figures 10A-10D). Pimasertib, capivasertib, and navitoclax were tested for their ability to target key glioma signaling pathways, including MEK, PI3K / AKT, and apoptosis / senescence, respectively. Drug response between repeats of the same cryopreserved sample performed at different times and observed a good correlation was also compared (Pearson’s correlation rp=0.70 and Spearman’s correlation rs=0.72) (Figure 11).

[0148] A total of 116 single agents and 183 drug combinations were tested based on the presence of actionable alterations and included a pre-selected drug panel that targets frequently deregulated HGG pathways (N. Cancer Genome Atlas Research, Nature, 455: 1061 (2008)). The panel included 16 agents targeting deregulated RTK signaling, p53 / apoptosis, cell cycle, DNA damage and repair (DDR), IDH, and telomere maintenance mechanisms (Figure 12), along with 7 drug combination strategies that will be discussed later. When possible, drugs in each class were selected based on their ability to penetrate the central nervous system (CNS) (Table 6). Alternatively, compounds targeting key pathways and / or approved for use in other clinical settings were chosen.

[0149] Following microcancer generation and drug testing, drug efficacy was represented by the percentage of reduced vi abi 1 i ty (% inhibition) at the maximum serum concentration of the drug achieved after dosing (Cmax) (Figures 13A-13B). Cmax values were acquired from human clinical trial data or animal studies (e.g., JQ1) (Table 6). Given the paucity of CNS pharmacokinetics information for the majority of these drugs, available serum Cmax values represent a more physiologically relevant reference concentration for evaluating drug efficacy than an arbitrary unit (e.g., 1 pM). To facilitate result interpretation, response profiles were segregated into three categories: <35%, 35-70%, and > 70% of inhibition at Cmax that were defined as minimal response, partial response, and strong response, respectively (Figure 14). Samples with sufficient tissue were subjected to testing with all the drugs in the panel.

[0150] Table 6. Pharmacokinetic measures and key clinical trial findings of panel drugs used

[0151] ExVivo vulnerabilities ofHGGs to single agent treatments

[0152] Glioma microcancers showed in general minimal response to RTK targeted agents, including the EGFR inhibitor osimertinib, pan-ERBB inhibitor neratinib, and multi-RTK inhibitors foretinib and sunitinib (Figures 13A-13B, Figure 14, and Figure 15A-15C). Similar results were also obtained by testing select cases with additional EGFR-related inhibitors, alone or in combination, except for PT431, an EGFRvIII amplified tumor that exhibited a partial response to erlotinib and a strong response to the combination of erlotinib with the dual PI3K / mT0R inhibitor paxalisib. Efficacy to foretinib treatment was unrelated to molecular alterations of its targets MET and KDR (Figure 4), with 3 microcancer samples (PT301, PT417, PT440) exhibiting partial response (Figure 14). Similarly, 1 strong microcancer response to sunitinib (PT426) was unrelated to molecular alterations of its targets KDR. PDGFRA, or KIT, in agreement with clinical data (Table 4).

[0153] To inhibit RTK signaling by targeting downstream effectors, the MEK inhibitor pimasertib, MAPK / ERK inhibitor ulixertinib, PI3K7mTOR dual inhibitor paxalisib, pan-AKT inhibitor capivasertib, and mTOR / DNA-PK dual inhibitor CC-115 were utilized. In general, this strategy was more effective than targeting upstream RTKs. Pimasertib achieved 1 strong and 5 partial responses, while ulixertinib achieved 4 partial responses (Figure 14). Inhibitors targeting the PI3K pathway were overall more effective, with paxalisib achieving 8 partial responses, capivasertib 1 strong and 19 partial responses, and CC-115 2 strong and 11 partial responses. The extent to which the DNA-PK (DDR kinase) inhibitor activity of CC-115 contributes significantly to these responses is currently unclear, although another DDR- targeting agent, the PARP inhibitor niraparib exhibited no effect in the microcancer cohort.

[0154] Despite common activation of the cell cycle pathway in gliomas via CDKN2A / 'Q homozygous deletion (Figure 12), microcancer treatment with the CDK4 / 6 inhibitor abemaciclib was largely ineffective, achieving 1 strong and 2 partial responses (Figure 14). Notably PT306, which responded strongly to abemaciclib, exhibited focal amplifications of CCND1 and CDK4-MYEOV fusion (Figure 4), a potential oncogenic driver. In agreement with its low efficacy in microcancers, abemaciclib w as largely ineffective in recurrent glioblastoma (Table 4).

[0155] Idasanutlin, an MDM2 inhibitor used to restore p53 pathway activation also showed limited effect in microcancers, with 1 strong and 1 partial response (Figure 14). None of the tumors in the cohort exhibited MDM2 amplification (Figure 4), which was associated with response to MDM2 inhibitors in PDX models (Kim et al. , Mol Cancer Ther, 17: 1893 (2018)). Moreover, PT431 exhibiting amplification of MDM4 also did not respond to idasanutlin. In contrast, the pan-Bcl-2 inhibitor navitoclax was effective, exhibiting 7 strong and 11 partial responses ex vivo (Figure 14). Navitoclax can eliminate senescent glioblastoma cells that are normally resistant to apoptosis (Rahman et al. , Mol Cancer Res, 20:938 (2022)). The data argue that agents that restore apoptosis and also act as senolytics may have strong activity in glioma. Vorasidenib, a dual inhibitor of mutant IDH1 / IDH2, increased PFS in patients with recurrent low-grade gliomas with no prior treatments except for surgery (INDIGO study) (Table 4). However, no evidence to date has supported its efficacy in the HGG setting, where no effect on the viability of IDH-mut derived microcancers was observ ed (Figure 14). All IDH-mut tumors in the cohort were high-grade and most of them (7 of 10) were pretreated recurrent cases (Table 2).

[0156] Multiple studies argue that the epigenome is largely altered during gliomagenesis and disease progression (Stepniak et al., Nat Commun, 12: 3621 (2021); Mack et al., J Ex Med, 216: 1071 (2019)). Here, the epigenome was targeted by testing the activity of histone deacetylase (HD AC) and bromodomain and extraterminal domain (BET) inhibitors, both shown to modulate chromatin structure organization and to globally affect gene expression (Manzotti et al.. Cancers (Basel) 11 (2019)). HD AC inhibition by vorinostat resulted in moderate activity’ with 10 partial responses (Figure 14). JQ1, a preclinical BET inhibitor, was more effective, exhibiting 4 strong and 18 partial responses. Similar responses were observed when 3 clinically relevant BET inhibitors, birabresib, mivebresib. and trotabresib (the latter been actively explored in gliomas) (Moreno et al. , IntJMol Set, 20 (2019)) were tested in select cases (Figure 16). These inhibitors are particularly active against the BET protein BRD4 and can displace it from chromatin leading to anti-tumor activity via gene expression modulation (Manzotti el al., Cancers (Basel) 11 (2019)).

[0157] Overall, although most of the panel drugs had limited single agent activity, we observed partial responses in at least 50% of cases for five agents, namely navitoclax, JQ1, capivasertib, CC-115, and vorinostat were observed. Moreover, 14 out of 30 cases (46.6%) responded strongly (>70% inhibition at Cmax) to at least one of the 16 agents in the panel (Figure 14).

[0158] Genomic alterations and Cancer drug efficacy

[0159] Next, whether the effects of the five most effective single agents identified above correlate with specific genomic alterations was explored. Drug response to capivasertib or CC-1 15 showed no correlation to alterations in PIK3Cs. AKT2. PTEN. and TSC2. which were found to be differentially altered across cases (Figures 17A-17D). For navitoclax, treatment response with oncogenic alterations in the p53 / apoptosis signaling pathway was compared and no direct correlation was found. No correlation was also observed between genomic alterations in the p53 / apoptosis pathway and microcancer responses to vorinostat. tested here because HD AC inhibition can increase p53 stability and activate p21-mediated apoptosis in a p53-independent manner (Mrakovcic et aL. IntJMol Sci, 20 (2019)).

[0160] Effects of epigenetic drugs are likely attributed to overall changes in gene expression, through their action on chromatin and super-enhancer occupancy (Manzotti et al. , Cancers (Basel) 11 (2019)). However, BRD4 inhibition by JQ1 was shown to regulate telomere maintenance (Figure 12) by decreasing TERT expression in cells with pTERT mutations, including glioblastoma stem cells (Cheng et al.. Clin Cancer Res. 19: 1748 (2013)), and by suppressing telomere elongation (Wang et al., Nucleic Acids Res, 45: 8403 (2017)). In agreement, cases with pTERT mutation tended to respond better to JQ1 (Figure 18), without reaching statistical significance in the cohort (p=0.0539; n=23).

[0161] Transcriptional mechanisms underlying Cancer drug sensitivity

[0162] The general lack of correlation between specific molecular alterations 296 and drug efficacy ex vivo may reflect the molecular complexity and cellular plasticity of human gliomas (Chaligne et al.. Nat Genet, 53: 1469 (2021); Neftel et al., Cell, 178: 835 e821 (2019)). As both complexity and plasticity7are associated with changes in the overall trans criptome, it was next determined whether specific transcriptomic profiles correlate with microcancer drug responses. According to The Cancer Genome Atlas (TCGA) glioma transcription subtyping (Wang et al. , Cancer Cell. 32: 42 e46 (2017)), the cohort included 15 proneural (PN) cases, 11 classical (CL) cases, and 4 mesenchymal (MES) cases (Figure 19A). Further, to quantify transcriptional heterogeneity, which could affect response to treatment, a well-established ‘simplicity scoring’ (Wang et al. , Cancer Cell, 32: 42 e46 (2017)) w'as applied onto the classification. This scoring system ranges from 0 to 1 with 1 showing the simplest tumor that contains solely one subtype and 0 presenting multiple subtypes being present in a single tumor. The average simplicity score (SPL) of the cohort was 0.50±0. 18 (mean±SD) with the lowest and highest scores being 0.18 and 0.86, respectively. SPL of less than 0.5 were observed in 14 out of 30 (46.7%) cases, indicating that multiple subtypes are present in most cases in the cohort.

[0163] A pathway-based transcriptomic classifier was recently developed for glioblastoma subgrouping, proposed to predict biological activities underlining drug responses (Garofano et al., Nat Cancer, 2: 141 (2021)). According to this classification, the cohort consisted of 10 glycolytic / plurimetabolic (GPM) cases, 4 mitochondrial (MTC) cases, 9 neuronal (NEU) cases, and 7 proliferative / progenitor (PPR) cases (Figure 19B), with MTC and GPM representing the best and worst prognostic subtypes, respectively (Garofano et al, Nat Cancer, 2: 141 (2021)). Further, SPL applied to this classification indicated that 19 of 30 cases (63.3%) exhibited SPL of less than 0.5, with the lowest and highest scores being 0.19 and 0.91, respectively. Comparing TCGA and pathway-based subtypes, all TCGA-MES gliomas in the cohort aligned with the GPM subtype (Figures 20A-20B). While approximately half of the CL gliomas (6 of 11) also exhibited a GPM state, there were no PN gliomas assigned to this subtype. Similar to previous reports (Garofano et al., Nat Cancer, 2: 141 (2021)), PN tumors included MTC. NEU. and PPR subtypes.

[0164] To assess whether transcriptional subtypes provide predictive insight into response to microcancer treatment, the analyses were limited to glioblastoma and astrocytoma because these two histologies are biologically closer to each other than to oligodendroglioma (Reifenberger et al. , Nat Rev Clin Oncol, 14: 434 (2017)). Further, cases with tumor percentages less than 50% (i.e., PT417 and PT429), determined by DNA (based on ploidy and mutation fraction) and RNA (using the ESTIMATE algorithm) methods, were excluded. Therefore, 23 cases in total were subjected to the "response versus transcriptional subtypes’ analysis. The five most effective monotherapies in the drug panel, JQL vorinostat, CC-115, capivasertib, and navitoclax (Figure 14) were included in this analysis.

[0165] A statistically significant positive association was observed between MES gliomas and microcancer response to JQ1 (p=0.043; rp=0.45) and CC-115 (p=0.007; rp=0.59), and a similar trend was observed for vorinostat (p=0. 123; rp=0.38) (Figure 21 A). Conversely, a negative correlation was observed between PN gliomas and microcancer response to vorinostat (p=0.042; rp=-0.48) and CC-115 (p=0.04; rp=-0.48), with a similar trend observed for JQ1 (p=0.066; rp=-0.41). These opposing response profiles between PN and MES tumors are consistent with the well-established "PN-to-MES switching' concept with these two subtypes showing differences in biological characteristics and therapy responses (Segerman et al.. Cell Rep, 17: 2994 (2016)). Moreover, these findings suggest an enrichment or convergence of signaling netw orks involving PI3K signaling, epigenetic regulation, and potentially DNA-PK signaling (Bhat et al., Neuro Oncol, 24: vii91 (2022)) in MES tumors, rendering increased sensitivity of MES-derived microcancers to these targeted agents.

[0166] Similar to MES cases, GPM gliomas exhibited a positive correlation with microcancer response to JQ1 (p=0.023; rp=0.49), vorinostat (p=0.027; rp=0.52), and CC-115 (p=0.028; rp=0.5) (Figure 21B). No strong correlations between these drug responses and the MTC or PPR gliomas was observed in the cohort. Instead, a trend towards negative correlation was observed between these three agents and NEU glioma with only vorinostat attaining statistical significance (p=0.03; rp=-0.51 ). For capivasertib, a negative correlation was only observed between microcancer response and the CL glioma subtype (Figure 21B). Navitoclax, which exhibited effective responses across most microcancers, did not show any response preference to the transcription subtypes tested. This suggests that Bcl-2 family proteins represent an important node of vulnerability in the majority of gliomas.

[0167] Next, genes that are differentially expressed between responders and non-responders for drug-subtype pairs that showed significant correlation were interrogated. By removing cases with responses between responders and non-responders (Figures 22A-22D), this analysis reduced sample size and statistical power, but allowed identification of genes that differentiate the two groups. For JQ1, the most significantly differentially expressed genes in the MES signature were matrix metalloproteinase MMP7 and glioma pathogenesis-related protein 1 (GLIPR1) (Rosenzweig et al., Cancer Res, 66: 4139 (2006)) (Figures 23A-23D), while progranulin (GRN) and putative GTPase activator protein (TBC1D22A) were most highly differentially expressed in the GPM signature (Figures 24A-24D). For vorinostat, a set of PN and NEU associated genes were downregulated, whereas GPM genes were upregulated in the responder group (Figures 23A-23D, Figures 24A-24D). Microcancers derived from PN glioma with high expression of ERBB3 appeared to be less 365 responsive to vorinostat (Figures 23A-23D). Response to CC-115 correlated with higher expression of MES and GPM associated genes, with extracellular matrix remodelers (COL15A1, LUM, COL1A1) topping the list (Figures 23A-23D, Figures 24A-24D). Response to the pan-AKT inhibitor capivasertib was negatively correlated to the expression of CL associated genes (Figures 23A-23D). The data suggest that CL-enriched tumors, which encompass most of the EGFR altered gliomas (Wang et al., Cancer Cell. 32: 42 e46 (2017)), are less likely to respond to capivasertib.

[0168] Correlation of YAP NAZ signaling with gCancer drug response

[0169] To explore common mechanisms that could underlie microcancer responses to the three drugs (JQ1, vorinostat. CC-115) associated with MES and GPM tumor features, the potential activation of the YAP / TAZ signaling pathway was examined. Inhibition of Hippo signaling promotes the transcriptional coactivator function of YAP / TAZ and drives tumorigenesis and progression via regulation of gene expression (Moroishi et al. , Nat Rev Cancer, 15: 73 (2015)) (Figure 25). YAP / TAZ is a master regulator driving MES characteristics in glioma and a key regulator of glioblastoma sternness and plasticity (Castellan et al. , Nat Med, 24: 1599 (2018)). Additionally, the targets of these three drugs are linked to Hippo-YAP / TAZ signaling. The effect of JQ1 and other BET inhibitors on YAP / TAZ signaling may be direct, as their main target BRD4 is recruited by YAP / TAZ to chromatin to enhance gene expression and drive tumorigenesis (Zanconato et al., Nat Med, 24: 1599 (2018)). Moreover, vorinostat’s target HDACs can facilitate transcriptional repression of tumor suppressor genes by YAP / TAZ (Kim et al. , Cell Rep, 11 : 270). Finally, CC-115 may affect YAP / TAZ signaling by inhibiting DNA-PK, which reportedly forms a functional complex with YAP / TAZ (Bhat et al.. Neuro Oncol, 24: vii91 (2022)). or by suppressing mTOR activity, which is upregulated by YAP signaling (Tumaneng etal., Nat Cell Biol, 14: 1322 (2012)).

[0170] Utilizing the “positive regulation of Hippo signaling” gene set from 388 the Gene Ontology Biological Process (GOBP) class in the Molecular Signature Database (MSigDB), it was observed that gliomas enriched for this Hippo activator gene set (corresponding to downregulation of YAP / TAZ signaling), were negatively correlated with microcancer response to JQ1 (p=0.017; rp=-0.5) and CC-115 (p=0.009; rp=-0.58) (Figures 26A-26C). A negative trend between this gene set and response to vorinostat was also observed. The data suggest that YAP / TAZ activation confers microcancer sensitivity to JQ1 and CC-115, and possibly to vorinostat.

[0171] Treatment resistance is a key mediator of poor prognosis in gliomas and is largely driven by glioma stem cells (GSCs). It is well-established that YAP / TAZ promote GSC cellular states and hinder GSC transition to differentiation states (Castellan et al.. Nat Cancer, . 174 (2021)). To assess the role of GSC and differentiation states in microcancer responses to these agents, each treatment response was compared to the differentiated glioblastoma cell (DGC) and G-STEM signatures (Castellan et al., Nat Cancer, 2: 174 (2021)) (Figures 26A- 26C). A negative correlation was observed between enrichment for the DGC signature and microcancer response to JQ1 and CC-115, with response to CC-115 achieving statistical significance (p=0.002; rp=-0.66). Moreover, enrichment for the G-STEM signature correlated positively with response to all three agents, with vorinostat achieving significance (p=0.024; rp=0.53). These data are consistent with the hypothesis that YAP / TAZ signaling is an important target of these agents, regulating both glioma differentiated and sternness cellular states.

[0172] Finally, while no correlation was observed between microcancer response to CC-115 and specific genomic alterations related to the PI3K pathway (Figure 16), a significant correlation was observed between CC-115 response and the “activation of mTORCl signaling” gene set score (p=0.036) (Figure 27). The data are consistent with the 411 upregulation of mTOR activity by increased YAP signaling (Tumaneng et al., Nat Cell Biol, 14: 1322 (2012)), and argue that in tumors with high molecular complexity, transcriptomic signatures correlate better with response to treatment than specific genomic alterations.

[0173] Combination treatment strategies with strong efficacy across glioma subtypes

[0174] Gliomas are molecularly complex and highly heterogeneous tumors, arguing that single agent treatment strategies will rapidly be overcome by resistance mechanisms. Despite potential for increased toxicity7, combination treatments are more likely to overcome resistance and increase efficacy (Settleman et al., Cancer Discov, 11 : 1016 (2021); Plana et al. , Cancer Discov, 12: 606 (2022)). Therefore, rational drug combination strategies that are more effective than single-agent treatment were sought.

[0175] Seven drug combination treatments were included in the pre-selected drug panel and run in parallel with single agents. Given the common activation of the RTK pathway in gliomas, downstream signaling by combining the PI3K / mTOR inhibitor paxalisib with the MEK inhibitor pimasertib was targeted. Moreover, by targeting transcriptomic-epigenomic landscapes, epigenetic drugs (epi-drugs; i.e., HD AC, BET inhibitors) can improve sensitivity' to other targeted agents (Morel et al., Nat Rev Clin Oncol, 17; 91 (2020)). Therefore, combinations of paxalisib with either vorinostat or JQ1, and pimasertib with JQ1 were included. Given the known functional interactions between BET and HDAC proteins (Manzotti et al., Cancers (Basel), 11 (2019)), a combination of JQ1 with vorinostat was also included. Further, “apoptosis-inducing agents” (i.e., navitoclax and idasanutlin) can provide therapeutic benefit by triggering cytotoxicity' in cancers (Cameiro et al., Nat Rev Clin Oncol, 17; 395 (2020)). Navitoclax with idasanutlin were thus combined to promote apoptosis by distinct mechanisms, and vorinostat with navitoclax to simultaneously target gene expression and eliminate senescent cells.

[0176] Drug combinations can significantly increase therapeutic benefit without necessarily exhibiting pharmacologically additive or synergistic effects (Settleman et al. , Cancer Discov, 11: 1016 (2021 ); Plana et al. , Cancer Discov, 12: 606 (2022)). Here, % inhibition at each drug’s Cmax was used to compare the effect of single agent treatment versus that of drug combination. In the example provided (Figure 28), single agent A exhibited 20% inhibition at its Cmax value, while agent B exhibited 62% inhibition at its Cmax. Combination of the two resulted in 77% and 83% inhibition at Cmax for drug A and drug B, respectively. For data visualization, % inhibition at Cmax for drug A (x axis) was plotted versus that of drug B (y axis), assigning (Mrakovcic, Int J Mol Sci, 20 (2019); Galanis et al., J Clin Oncol, 27: 2052 (2009)) to single agent effects and (Wen et al., Clin Cancer Res, 26: 3135 (2020); Sigaud et al.. Neuro Oncol, 25: 566 (2023)) to combination treatment. Arrows were then added from single to combination treatment points (Figure 28, middle and right plots), with diagonal arrows from left bottom to upper right indicating drug combinations with stronger efficacy than both single agents. Among seven combinations tested, 6 combination strategies exhibited stronger effects than both of their corresponding single agents, while the combination of navitoclax with idasanuthn was slightly more effective than navitoclax alone (Figure 29).

[0177] The combination of paxalisib with pimasertib was more effective than single agent treatments in 20 of 26 tested cases (77%) (Figure 30A). Combining a molecularly targeted therapy and an epi-drug (i.e., paxalisib plus vorinostat, paxalisib plus JQ1, and pimasertib plus JQ1) similarly resulted in overall stronger effects than monotherapy in 15 of 24 (63%), 17 of 28 (61%), and 18 of 27 (67%) cases, respectively. These results suggest that epi-drugs JQ1 and vorinostat, which inhibit BET and HD AC, respectively, can increase microcancer sensitivity to MEK and PI3K pathway targeted agents. Combining the two epi-drugs JQ1 and vorinostat was more effective than single agent treatments in 18 of 24 (75%) cases. Similarly increased efficacy was also observed when the clinically relevant BET inhibitor trotabresib was combined with other agents (Figures 30B). While increased efficacy of navitoclax plus idasanutlin was observed in 10 of 26 cases (38%). combining navitoclax and vorinostat was more effective than single agents in 14 of 24 cases (58%). Strong responses (>70% inhibition at Cmax) to combination treatment were observed in 19 to 81% of cases tested, with vorinostat plus JQ1 or navitoclax being the most effective strategies. Altogether, the 7 drug combinations produced at least one strong response in 25 out of 28 cases (89%).

[0178] Example 3: Treating glioma

[0179] A tissue sample containing cancer cells is obtained from a human having brain cancer (e.g., a brain cancer such as glioma). The tissue sample is used to generate a collection of microcancer models. One or more of the human’s microcancer models is contacted with a potential anti-cancer treatment. The cell viability in one or more of the human’s microcancer models contacted with the anti-cancer treatment is assessed.

[0180] If the cell viability in one or more of the human’s microcancer models is reduced, the anti-cancer treatment is administered to the human. The treatment can delay relapse, reduce the number of cancerous cells in the human having the brain cancer, reduce the size of the tumor, or reduce the rate of increase in the size of the tumor. Example 4: Treating glioma follow ing development of anti-cancer treatment resistance

[0181] A tissue sample containing cancer cells is obtained from a human having brain cancer (e.g., a brain cancer such as glioma). The tissue sample is used to generate a collection of microcancer models. One or more of the human’s microcancer models is contacted with a potential anti-cancer treatment. The cell viability' in one or more of the human’s microcancer models contacted with the potential anti-cancer treatment is assessed.

[0182] If the cell viability in one or more of the human’s microcancer models is reduced, the anti-cancer treatment is administered to the human. The treatment can delay relapse, reduce the number of cancerous cells in the human having the brain cancer, reduce the size of the tumor, or reduce the rate of increase in the size of the tumor.

[0183] While treatment of the human having cancer with the anti-cancer treatment is ongoing, contact of one or more of the human’s microcancer models with the anti-cancer treatment is continued. One or more of the microcancer models is assessed to determine whether resistance to the anti-cancer treatment has developed.

[0184] If resistant cancer cells are observed as remaining and / or emerging across some, most, or all of the human’s microcancer models contacted with the anti-cancer treatment, the clinician stops or tappers off the administration of that anti-cancer treatment in the human. At that time, or after a period of time, one or more of the human's microcancer models is contacted with an alternative potential anti-cancer treatment. The cell viability in one or more of the human’s microcancer models contacted with the alternative potential anti-cancer treatment is assessed.

[0185] If the cell viability in one or more of the human’s microcancer models is reduced, the alternative potential anti-cancer treatment is administered to the human. The alternative treatment can delay relapse, reduce the number of cancerous cells in the human having the brain cancer, reduce the size of the tumor, or reduce the rate of increase in the size of the tumor.

[0186] Example 5: Characterization of microcancer models

[0187] This example describes the further characterization of microcancer models and the elucidation of underlying drug response mechanisms in these models.

[0188] The potential utility of microcancer models was explored, focusing on JQ1, a BET inhibitor, as it was the most effective single agent in previous studies (see, Example 1) and is particularly effective in the most aggressive mesenchymal (MES) enriched high-grade glioma (HGG) cases. The analysis utilized microcancer models that previously exhibited a response to JQ1 treatment (R; PT440) or no response to JQ1 treatment (NR; PT431). RNA-seq analysis was performed before (time 0), during (Day 2). and after (Day 4) treatment with JQ1. Temporal changes in gene expression and pathway enrichment were subsequently assessed to elucidate the underlying molecular programs.

[0189] Subtype-specific effects of JQ1 were assessed, and, consistent with the observed positive correlation between JQ1 response and the MES glioma cell state (see, Example 1), JQ1 treatment led to a temporal reduction in MES and its related GPM subtypes in both microcancer models, regardless of response status (Figures 31 A and 32A). This change was accompanied by a progressive increase in proneural (PN) subty pe enrichment, supporting the widely accepted opposing roles of MES and PN subtypes in glioma behavior and therapeutic response (Ozawa et al., Cancer Cell. 26:288-300 (2014); and Segerman et al., Cell Rep, 17:2994-3009 (2016)) (Figure 31A). Increased classical (CL) subtype enrichment was observed during JQ1 treatment in the responding (PT440) microcancer models, although levels remained lower than in the non-responding (PT431) microcancer models where enrichment remained constant. These results suggest that responsive (PT440) microcancer models may ultimately acquire treatment-induced resistance through gradual expansion of the PN and CL subtypes. The CL subtype is frequently associated with EGFR genomic alterations, and crosstalk between BET and EGFR signaling pathways has been implicated in reciprocal resistance to BET and EGFR monotherapies (Verhaak el al., Cancer Cell, 17:98- 110 (2010); Jermakowicz et al., Sci. Rep.. 14:9284 (2024); Stratikopoulos et al., Cancer Cell, 27:837-851 (2015); and Zanca et al.. Genes Dev., 31 : 1212-1227 (2017)). These results suggest that achieving a durable response to BET inhibition may require either upfront combination or sequential administration of JQ1 and an EGFR or other RTK pathway inhibitor, particularly in tumors with emerging CL subtype enrichment over time.

[0190] Looking beyond the established subtyping system, shared gene expression changes and associated pathways in both non-responding (PT431) and responding (PT440) microcancer models were assessed to broadly examine how JQ1 treatment impacts transcriptomic programs. As a first step, a lenient threshold was applied to select genes showing at least 10% downregulation or upregulation at Day 2 (versus DMSO) and an additional 10% decrease or increase at Day 4 (versus Day 2) in both non-responding (PT431) and responding (PT440) microcancer models (Figure 3 IB). Genes were analyzed using g:Profiler (Kolberg et al., Nucleic Acids Res., 5LW207-W212 (2023)), and the top five Gene Ontology (GO) molecular functions (MF) and top ten biological processes (BP) terms - either downregulated or upregulated - were visualized. Consistent with the reduction in MES enrichment observed in both cases (Figure 31 A), downregulated GO:MF terms included those related to extracellular matrix (ECM) remodeling, a process often linked to the mesenchymal phenotype (Figure 31 B) (Kim et al. , Acta Neurophathol. Commun, 9: 50 (2021); and Marino et al., Cancers (Basel), 15 (2023)). Stress response-related GO:BP terms were also downregulated. In contrast, upregulated GO terms included gene expression machinery-related MF and neural development-related BP. These findings suggest that the developmental-injury response axis described elsewhere (Richards et al.. Nat. Cancer. 2A51- 173 (2021)) not only defines the transcriptomic states of glioblastoma stem cells (GSCs) but also exhibits opposing expression patterns in response to treatment, implicating this axis in therapeutic vulnerability.

[0191] Why non-responding (PT431) and responding (PT440) microcancer models responded differently to JQ1, despite both showing downregulation of MES and stress response programs along with upregulation of neurogenesis, was assessed (Figure 3 IB). To explore potential adaptive responses that may bypass BET epigenetic inhibition in the nonresponding (PT431) microcancer models, the expression fold-change stringency was increased and limited to OncoKB / COSMIC-defined cancer genes that were persistently upregulated and showed at least a two-fold increase over the four-day JQ1 treatment (Figure 31C). These genes were analyzed using the STRING webtool (Szklarczyk et al., Nucleic Acids Res., 51 :D638-D646 (2023)) to examine enriched pathways and visualize proteinprotein interaction networks. The top five GO:BP and top three GO:cellular component (GO:CC) terms as well as top five WikiPathways were visualized (Figure 31C). These analyses suggested that upregulation of anti -apoptosis processes and activation of PI3K and RTK pathways may represent bypass mechanisms that contribute to the limited response of PT431 to JQ1. Supporting this, the inhibition of the PI3K pathway by paxalisib largely enhanced JQ1 sensitivity in PT431 microcancer models while having limited effect on PT440 microcancer models (Figure 3 IE) which did not exhibit PI3K signaling enrichment in the STRING analysis (Figures 3 ID and 3 IE).

[0192] With the same threshold (Figure 31 C), neurogenesis-related GO terms and pathways w ere particularly upregulated in responding (PT440) microcancer models following JQ1 treatment (Figures 3 ID and 32B). A similar finding was observed in non-responding (PT431) microcancer models under more relaxed thresholds (Figure 3 IB). These findings suggest that, like radiotherapy -induced remodeling of neuron-glioma interactions as show n elsewhere (Tetzlaff et al.. Cell, 17:98-110 (2025), targeted therapies such as JQ1 may influence neurontumor netw ork formation and signaling. In cases like PT431 and PT440, which exhibit an increased neurogenic response upon JQ1 treatment, future co-treatment strategies incorporating inhibitors that suppress neuronal activity or neuron-tumor connectivity may help enhance therapeutic response. OTHER EMBODIMENTS

[0193] It is to be understood that while the invention has been described in conjunction with the detailed description thereof, the foregoing description is intended to illustrate and not limit the scope of the invention, which is defined by the scope of the appended claims. Other aspects, advantages, and modifications are within the scope of the following claims.

Claims

WHAT IS CLAIMED IS:

1. A method for identifying a candidate anti-cancer treatment likely to be effective in treating a mammal having cancer, wherein said method comprises:(a) culturing a cell suspension of a sample of said cancer in each of a plurality of individual locations of a culture vessel in the presence of culture medium that does not contain hydrocortisone to generate a microcancer model of said cancer in each of said plurality of individual locations,(b) contacting one or more of said microcancer models with a potential anti-cancer treatment, and(c) identifying said potential anti-cancer treatment as having the ability to reduce cell viability of said microcancer model contacted with said potential anti-cancer treatment as compared to cell viability of one or more control microcancer models of said cancer not contacted with said potential anti-cancer treatment, thereby identifying said potential anticancer treatment as being said candidate anti-cancer treatment.

2. The method of claim 1, wherein the mammal is a human.

3. The method of any one of claims 1-2, wherein the cancer is a brain cancer.

4. The method of claim 3, wherein the brain cancer is a glioma.

5. The method of any one of claims 1-4, wherein the culture vessel is an ultra-low attachment plate.

6. The method of any one of claims 1-4, wherein the culture vessel is a hanging drop plate.

7. The method of any one of claims 1-6, wherein the culture medium does not contain a ROCK inhibitor.

8. The method of any one of claims 1-6, wherein the culture medium contains a ROCK inhibitor.

9. The method of claim 8, wherein the culture medium is removed from the culture vessel and replaced with a culture medium that does not contain a ROCK inhibitor during the contacting step (b).

10. The method of any one of claims 1-9, wherein the potential anti-cancer treatment comprises a single compound.

11. The method of claim 10, wherein the single compound is selected from the compounds set forth in Table 1.

12. The method of any one of claims 1-9, wherein the potential anti-cancer treatment comprises a combination of two compounds, a combination of three compounds, a combination of four compounds, a combination of five compounds, or a combination of six compounds.

13. The method of claim 12, wherein the combination is selected from the combinations of compounds set forth in Table 2.

14. A method for identifying a candidate anti-cancer treatment likely to be effective in treating a mammal having cancer, wherein said method comprises:(a) dispensing a cell suspension of a sample of said cancer into each of a plurality' of individual locations of a culture vessel in the presence of culture medium and culturing said cell suspension to generate a microcancer model of said cancer in each of said plurality of individual locations, wherein said cell suspension dispensed into each of said plurality of individual locations contained less than 4000 cells,(b) contacting one or more of said microcancer models with a potential anti-cancer treatment, and(c) identifying said potential anti-cancer treatment as having the ability to reduce cell viability of said one or more microcancer models contacted with said potential anti-cancer treatment as compared to cell viability' of one or more control microcancer models of said cancer not contacted with said potential anti-cancer treatment, thereby identifying said potential anti-cancer treatment as being said candidate anti-cancer treatment.

15. The method of claim 14, wherein the mammal is ahuman.

16. The method of any one of claims 14-15, wherein the cancer is a brain cancer.

17. The method of claim 16, wherein the brain cancer is a glioma.

18. The method of any one of claims 14-17, wherein the culture vessel is an ultra-low attachment plate.

19. The method of any one of claims 14-17, wherein the culture vessel is a hanging drop plate.

20. The method of any one of claims 14-19, wherein each of the plurality of individual locations contains 500 to 30.000 cells prior to said step (b).

21. The method of any one of claims 14-20, wherein the culture medium does not contain hydrocortisone.

22. The method of claim 21, wherein the culture medium does not contain a ROCK inhibitor.

23. The method of claim 21, wherein the culture medium contains a ROCK inhibitor.

24. The method of claim 23, wherein the culture medium is removed from the culture vessel and replaced with a culture medium that does not contain a ROCK inhibitor during the contacting step (b).

25. The method of any one of claims 14-24. wherein the potential anti-cancer treatment comprises a single compound.

26. The method of claim 25, wherein the single compound is selected from the compounds set forth in Table 1.

27. The method of any one of claims 14-24, wherein the potential anti-cancer treatment comprises a combination of two compounds, a combination of three compounds, a combination of four compounds, a combination of five compounds, or a combination of six compounds.

28. The method of claim 27. wherein the combination is selected from the combinations of compounds set forth in Table 2.

29. A method for identifying a candidate anti-cancer treatment likely to be effective in treating a mammal having cancer, wherein said method comprises:(a) obtaining a culture vessel comprising a plurality of locations, wherein each of said plurality of locations comprises a microcancer model of said cancer,(b) identifying a potential anti-cancer treatment that involves administering a single drug at a set dose to said mammal.(c) contacting one or more of said microcancer models with said single drug at a concentration within 5 percent of Cmax of said set dose in plasma or at the location of said cancer within said mammal, and(d) identifying said contacting of step (c) as having the ability to reduce cell viability of said one or more microcancer models contacted with said single drug as compared to cell viability of one or more control microcancer models of said cancer not contacted with said single drug, thereby identifying said potential anti-cancer treatment as being said candidate anti-cancer treatment.

30. The method of claim 29, wherein the mammal is a human.

31. The method of any one of claims 29-30, wherein the cancer is a brain cancer.

32. The method of claim 31. wherein the brain cancer is a glioma.

33. The method of any one of claims 29-32, wherein the culture vessel is an ultra-low attachment plate.

34. The method of any one of claims 29-32, wherein the culture vessel is a hanging drop plate.

35. The method of any one of claims 29-34, wherein the single compound is selected from the compounds set forth in Table 1.

36. A method for identifying a candidate anti-cancer combination treatment likely to be effective in treating a mammal having cancer, wherein said method comprises:(a) obtaining a culture vessel comprising a plurality of locations, wherein each of said plurality of locations comprises a microcancer model of said cancer,(b) identifying a potential anti-cancer treatment that involves administering a combination of two drugs, each at a set dose, to said mammal,(c) contacting one or more of said microcancer models with a first drug of said two drugs at a concentration within 5 percent of Cmax of said set dose of said first drug in plasma or at the location of said cancer within said mammal,(d) contacting one or more of said microcancer models with a second drug of said two drugs at a concentration w ithin 5 percent of Cmax of said set dose of said second drug in plasma or at the location of said cancer within said mammal,(e) contacting one or more of said microcancer models with said first drug at a concentration within 5 percent of Cmax of said set dose of said first drug in plasma or at the location of said cancer within said mammal and with said second drug at a concentration within 5 percent of Cmax of said set dose of said second drug in plasma or at the location of said cancer within said mammal, and(f) identifying said contacting of step (e) as having the ability to reduce cell viability of said one or more microcancer models contacted to a greater extent than that of said contacting of said step (c) and that of said contacting of said step (d), thereby identifying said potential anti-cancer treatment as being said candidate anti-cancer treatment.

37. The method of claim 36. wherein said identifying step (f) comprises using a plot, where the x axis is the percent inhibition of cell viability of said first drug at said concentration of step (c) and the y axis is the percent inhibition of cell viability of said second drug at said concentration of step (d), wherein a first x,y data point is plotted based on the percent inhibition of cell viability of step (c) for (x) and the percent inhibition of cell viabilityof step (d) for (y), and wherein a second X,Y data point is plotted based on the percent inhibition of cell viability of step (e) for the combined exposition to the first drug for (X) and second drug for (Y) at said concentrations of step (e).

38. The method of any one of claims 36-37, wherein the mammal is a human.

39. The method of any one of claims 36-38. wherein the cancer is a brain cancer, or wherein the cancer is a glioma.

40. The method of any one of claims 36-39, wherein the culture vessel is an ultra-low7attachment plate.

41. The method of any one of claims 36-39, wherein the culture vessel is a hanging drop plate.

42. The method of any one of claims 36-41, wherein the combination is selected from the combinations of compounds set forth in Table 2.

43. A method for identifying a candidate anti-cancer treatment likely to be effective in treating a mammal having cancer, wherein said method comprises:(a) obtaining a culture vessel comprising a plurality of locations, wherein each of said plurality of locations comprises a microcancer model of said cancer,(b) contacting one or more of said microcancer models with a potential anti-cancer treatment,(c) conducting whole genome sequencing of a sample of said cancer or of said microcancer model to identify genetic mutations within said cancer, and optionally conducting whole genome sequencing of a germline sample of said mammal, and optionally conducting RNAseq of a sample of said cancer or of said microcancer model to identify expression profiles of said cancer.(d) identifying said potential anti-cancer treatment as having the ability to reduce cell viability of said one or more microcancer models contacted with said potential anti-cancer treatment as compared to cell viability of one or more control microcancer models of saidcancer not contacted with said potential anti-cancer treatment, thereby identifying said potential anti-cancer treatment as being said candidate anti-cancer treatment, and(e) confirming that said genetic mutations of said cancer are not a counter indication for use of said candidate anti-cancer treatment in said mammal.

44. The method of claim 43, wherein the mammal is a human.

45. The method of any one of claims 43-44, wherein the cancer is a brain cancer.

46. The method of claim 45, wherein the brain cancer is a glioma.

47. The method of any one of claims 43-46, wherein the culture vessel is an ultra-low attachment plate.

48. The method of any one of claims 43-46, wherein the culture vessel is a hanging drop plate.

49. The method of any one of claims 43-48, wherein the potential anti-cancer treatment comprises a single compound.

50. The method of claim 49, wherein the single compound is selected from the compounds set forth in Table 1.

51. The method of any one of claims 43-48, wherein the potential anti-cancer treatment comprises a combination of two compounds, a combination of three compounds, a combination of four compounds, a combination of five compounds, or a combination of six compounds.

52. The method of claim 51. wherein the combination is selected from the combinations of compounds set forth in Table 2.

53. The method of any one of claims 43-52, wherein the potential anti-cancer treatment is selected based on the genetic mutations identified within the cancer.

54. A method for identifying a candidate anti-cancer treatment likely to be effective in treating a mammal having cancer, wherein said method comprises:(a) obtaining a culture vessel comprising a plurality of locations, wherein each of said plurality7of locations comprises a microcancer model of said cancer,(b) contacting one or more of said microcancer models with a potential anti-cancer treatment in the presence of one or more dyes that stain cells for cell death or cell death by apoptosis, autophagic cell death, or necrosis,(c) conducting live imaging of said one or more microcancer models to observe cell death,(d) identifying said potential anti-cancer treatment as having the ability to reduce cell viability of said one or more microcancer models contacted with said potential anti-cancer treatment as compared to cell viability of one or more control microcancer models of said cancer not contacted with said potential anti-cancer treatment, thereby identifying said potential anti-cancer treatment as being said candidate anti-cancer treatment, and(e) confirming death of cells during said live imaging.

55. The method of claim 54, wherein the mammal is a human.

56. The method of any one of claims 54-55, wherein the cancer is a brain cancer.

57. The method of claim 56, wherein the brain cancer is a glioma.

58. The method of any one of claims 54-57, wherein the culture vessel is an ultra-low attachment plate.

59. The method of any one of claims 54-57, wherein the culture vessel is a hanging drop plate.

60. The method of any one of claims 54-59, wherein the potential anti-cancer treatment comprises a single compound.

61. The method of claim 60, wherein the single compound is selected from the compounds set forth in Table 1.

62. The method of any one of claims 54-59, wherein the potential anti-cancer treatment comprises a combination of two compounds, a combination of three compounds, a combination of four compounds, a combination of five compounds, or a combination of six compounds.

63. The method of claim 62, wherein the combination is selected from the combinations of compounds set forth in Table 2.

64. The method of any one of claims 54-63, wherein the one or more dyes is selected from the group consisting of annexin V fluorescent conjugates, caspase 3 / 7 specific fluorescent dyes, Fluorescent Premo™ Autophagy Tandem Sensor RFP-GFP-LC3B, Autophagy LC3 HiBiT Reporter Assay System, propidium iodide, SYTOX™ green fluorescent dye, Deep Red fluorescent dye, and RealTime-Glo™ Annexin V Apoptosis and Necrosis Assay.

65. A method for treating a mammal having a brain cancer, wherein said method comprises administering a compound set forth in Table 1 to said mammal.

66. The method of claim 65, wherein the mammal is a human.

67. The method of any one of claims 65-66, wherein the cancer is a brain cancer.

68. The method of claim 67, wherein the brain cancer is a glioma.

69. A method for treating a mammal having a brain cancer, wherein said method comprises administering a combination of compounds set forth in Table 2 to said mammal.

70. The method of claim 69, wherein the mammal is a human.

71. The method of any one of claims 69-70, wherein the cancer is a brain cancer.

72. The method of claim 71, wherein the brain cancer is a glioma.

73. A method for treating a mammal having a brain cancer with a candidate anti-cancer combination treatment identified as being likely to be effective in treating said mammal, wherein said method comprises:(a) obtaining a culture vessel comprising a plurality of locations, wherein each of said plurality of locations comprises a microcancer model of said cancer,(b) identifying a potential anti-cancer treatment that involves administering a single drug at a set dose, to said mammal,(c) contacting one or more of said microcancer models with said single drug at a concentration within 5 percent of Cmax of said set dose in plasma or at the location of said cancer within said mammal,(d) identifying said contacting of step (c) as having the ability to reduce cell viability of said one or more microcancer models contacted with said single drug as compared to cell viability of one or more control microcancer models of said cancer not contacted with said single drug, thereby identifying said potential anti-cancer treatment as being said candidate anti-cancer treatment, and(e) administering said candidate anti-cancer treatment to said mammal.

74. The method of claim 73, wherein the mammal is a human.

75. The method of any one of claims 73-74, wherein the cancer is a brain cancer.

76. The method of claim 75, wherein the brain cancer is a glioma.

77. The method of any one of claims 73-76, wherein the culture vessel is an ultra-low' attachment plate.

78. The method of any one of claims 73-76, wherein the culture vessel is a hanging drop plate.

79. The method of any one of claims 73-78, wherein the single compound is selected from the compounds set forth in Table 1.

80. A method for treating a mammal having a brain cancer wi th a candidate anti-cancer combination treatment identified as being likely to be effective in treating said mammal, wherein said method comprises:(a) obtaining a culture vessel comprising a plurality of locations, wherein each of said plurality of locations comprises a microcancer model of said cancer,(b) identifying a potential anti-cancer treatment that involves administering a combination of two drugs, each at a set dose, to said mammal,(c) contacting one or more of said microcancer models with a first drug of said two drugs at a concentration within 5 percent of Cmax of said set dose of said first drug in plasma or at the location of said cancer within said mammal,(d) contacting one or more of said microcancer models with a second drug of said two drugs at a concentration within 5 percent of Cmax of said set dose of said second drug in plasma or at the location of said cancer within said mammal,(e) contacting one or more of said microcancer models with said first drug at a concentration w ithin 5 percent of Cmax of said set dose of said first drug in plasma or at the location of said cancer within said mammal and with said second drug at a concentration within 5 percent of Cmax of said set dose of said second drug in plasma or at the location of said cancer within said mammal,(f) identifying said contacting of step (e) as having the ability to reduce cell viability of said one or more microcancer models contacted to a greater extent than that of said contacting of said step (c) and that of said contacting of said step (d), thereby identifying said potential anti-cancer treatment as being said candidate anti-cancer treatment, wfierein said candidate anti-cancer treatment is a combination treatment set forth in Table 2, and(g) administering said candidate anti-cancer treatment to said mammal.

81. The method of claim 80. wherein said identifying step (f) comprises using a plot, where the x axis is the percent inhibition of cell viability of said first drug at said concentration of step (c) and the y axis is the percent inhibition of cell viability' of said second drug at said concentration of step (d), wherein a first x,y data point is plotted based on the percent inhibition of cell viability of step (c) for (x) and the percent inhibition of cell viabilityof step (d) for (y), and wherein a second X,Y data point is plotted based on the percent inhibition of cell viability of step (e) for the combined exposition to the first drug for (X) and second drug for (Y) at said concentrations of step (e).

82. The method of any one of claims 80-81, wherein the mammal is a human.

83. The method of any one of claims 80-82. wherein the cancer is a brain cancer, or wherein the cancer is a glioma.

84. The method of any one of claims 80-83, wherein the culture vessel is an ultra-low7attachment plate.

85. The method of any one of claims 80-83, wherein the culture vessel is a hanging drop plate.

86. The method of claim 80-85, wherein the combination is selected from the combinations of compounds set forth in Table 2.

87. A method for identifying a candidate anti-cancer treatment likely to be effective in treating a mammal having cancer and previously treated with a prior anti-cancer treatment, wherein said method comprises:(a) obtaining a culture vessel comprising a plurality of locations, wherein each of said plurality of locations comprises a microcancer model of said cancer, wherein each of said microcancer models was exposed to said prior anti-cancer treatment while said mammal was receiving said prior anti-cancer treatment,(b) contacting one or more of said microcancer models with a potential anti-cancer treatment, and(c) identifying said potential anti-cancer treatment as having the ability to reduce cell viability of said one or more microcancer models contacted with said potential anti-cancer treatment as compared to cell viability of one or more control microcancer models of said cancer not contacted with said potential anti -cancer treatment, thereby identifying said potential anti-cancer treatment as being said candidate anti-cancer treatment.

88. The method of claim 87, wherein the mammal is a human.

89. The method of any one of claims 87-88, wherein the cancer is a brain cancer.

90. The method of claim 89, wherein the brain cancer is a glioma.

91. The method of any one of claims 87-90. wherein the culture vessel is an ultra-low attachment plate.

92. The method of any one of claims 87-90, wherein the culture vessel is a hanging drop plate.

93. The method of any one of claims 87-92, wherein the potential anti-cancer treatment comprises a single compound.

94. The method of claim 93, wherein the single compound is selected from the compounds set forth in Table 1.

95. The method of any one of claims 87-92, wherein the potential anti-cancer treatment comprises a combination of two compounds, a combination of three compounds, a combination of four compounds, a combination of five compounds, or a combination of six compounds.

96. The method of claim 95, wherein the combination is selected from the combinations of compounds set forth in Table 2.

Images