3D HUMAN CANCER MODEL-BASED COMBINATORIAL DRUG DEVELOPMENT METHOD

Abstract

The present invention relates to a method of characterizing a composition comprising two or more active drug compounds, the method comprising the steps of: a) a composition selection screen (CSS), in which screen a candidate composition comprising two or more active drug compounds is tested against a 3D microtissue derived from one or more cell line, and b) a composition validation screen (CVS), in which screen the candidate composition of step b) is tested against a 3D microtissue derived from a primary patient sample.

Claims

1. A method for characterizing a physiological effect of a composition comprising two or more active drug compounds, the method comprising the steps of: b) a composition selection screen (CSS), in which screen a 3D microtissue derived from one or more cell lines is exposed to said composition comprising two or more active drug compounds and/or c) a composition validation screen (CVS), in which screen 3D microtissue derived from a primary patient sample is exposed to the composition of step b), so as to characterize a physiological effect of said composition on the 3D microtissue.

2. The method according to claim 1, wherein at least one parameter representing the characterized physiological effect is generated or determined in the method.

3. The method according to claim 1, which method further comprises: a) a range finding step (RFS), in which step a plurality of 3D microtissues derived from one or more cell lines are exposed to different concentrations of each compound of the composition, so as to determine suitable concentration ranges of the compounds.

4. The method according to claim 1, which method further comprises a step of obtaining a molecular profile of at least one of the 3D microtissues derived from one or more cell lines, and/or the 3D microtissues derived from a primary patient sample.

5. The method according to claim 1, wherein a step of molecular profiling is used to detect genomic aberrations, and/or mRNA or protein expression levels.

6. The method according to claim 1, in which method the parameter representing the characterized physiological effect is determined over time in at least one of step a), b) and/or c).

7. The method according to claim 1, in which method the parameter representing the characterized physiological effect is the size of the 3D microtissue.

8. The method according to claim 1, in which method actual size, relative size and/or relative size change over time is determined in at least one of step a), b) and/or c).

9. The method according to claim 7, in which method the size determination of the 3D microtissue refers to at least one parameter selected from the group consisting of: diameter perimeter volume, and area of an optical cross section.

10. The method according to claim 8, in which method the size is determined in at least one of step a), b) and/or c) over a period of >1 and <20 days.

11. The method according to claim 1, in which method the 3D microtissue is exposed to the active drug compound (step a) or to the composition comprising two or more active drug compounds (steps b and c) only once, by application of a defined bolus.

12. The method according to claim 1, in which method the 3D microtissue is exposed to the active drug compound (step a) or to the composition comprising two or more active drug compounds (steps b and c) two or more times, by application of a defined bolus each.

13. The method according to claim 1, wherein the composition comprising two or more active drug compounds is removed after the microtissue was exposed thereto for a given period of time.

14. The method according to claim 1, wherein further a step of composition toxicity testing is provided, in which step: (i) a microtissue representing connective tissue is exposed to the composition of step b), and/or (ii) a tissue specific microtissue is exposed to the composition of step c), so as to characterize a physiological effect of said composition on said microtissue.

15. The method according to claim 1, wherein at least one 3D microtissue has been produced in a hanging drop culture system or a low adhesion well culture system.

16. The method according to claim 1, wherein the molecular profile of at least one 3D microtissue is correlated with at least one parameter which characterizes the physiological effect as obtained in the composition selection screen (CSS) or the composition validation screen (CVS) of said 3D microtissue.

17. The method according to claim 16, which method further comprises the step of creating or feeding a database with datasets comprising at least the following entries each: a) at least one molecular profile of at least one 3D microtissue, and b) at least one parameter which characterizes the physiological effect as obtained in the composition selection screen (CSS) or the composition validation screen (CVS) of said 3D microtissue.

18. A method of screening a plurality of compositions comprising two or more active drug compounds, preferably from one or more libraries, which method comprises: (i) the application of two or more methods as set forth in any of the aforementioned claims, with a different composition of two or more active drug compounds in each individual method, and/or (ii) several pairs of steps b), c) and optionally a).

19. The method according to claim 18, wherein the compositions comprising two or more active drug compounds differ from one another by a) the composition of active drug compounds, or b) the dosages or concentrations of the active drug compounds in the composition.

20. The method according to claim 1, which method further comprises at least one Step selected from the group consisting of: a) synthesizing the active drug compounds that are in the compositions, b) composing the compositions comprising two or more active drug compounds, and/or c) creating a library comprising active drug compounds that are comprised in the compositions and/or compositions comprising two or more active drug compounds.

21. A method of creating a database, in which the molecular profile of at least one 3D microtissue is correlated with the result of a composition selection screen (CSS) or a composition validation screen (CVS) of said 3D microtissue.

22. The method according to claim 21, wherein the molecular profile of at least one 3D microtissue is correlated with at least one parameter which characterizes the physiological effect as obtained in the composition selection screen (CSS) or the composition validation screen (CVS) of said 3D microtissue.

Description

FIGURES

[0209] FIG. 1 shows aspects of the concept of the present invention.

[0210] FIG. 2 shows an overview of the different method Steps of the present invention. Note that the steps shown in italics are optional. Note also that the screen for toxicity effects can be done

[0211] a) simultaneously or not simultaneously with the RFS, CVS and/or CSS, and/or

[0212] b) with (i) 3D microtissues representing connective tissue and/or (ii) tissue specific microtissues taken from the same patient as the primary patient sample, or from a library of (i) 3D microtissues representing connective tissue and/or (ii) tissue specific microtissues prepared from different test person or patients. Note that the screen for toxicity effects can be done a) simultaneously or not simultaneously with the RFS, CVS and/or CSS, and/or

[0213] b) with (i) 3D microtissues representing connective tissue and/or (ii) tissue specific microtissues taken from the same patient as the primary patient sample, or from a library of (i) 3D microtissues representing connective tissue and/or (ii) tissue specific microtissues prepared from different test person or patients.

[0214] FIG. 3 shows that one aspect of the present invention is capable to mimic the clinical characterization of tumors, which is subject to the so-called RECIST criteria. The growth curve of tumor microtissues is shown for pancreatic tumor microtissues either untreated or treated with Gemcitabine (500 mg/m.sup.2). It demonstrates that the same kind of data can be generated with an in vitro assay as pre-clinical animal data and ultimately in vivo human response data. It can be seen that the size measurement of a 3D microtumor quite faithfully reflects the clinical characterization of tumors in vivo. In vivo data taken from Lee et al. 2005.

[0215] FIG. 4 shows an example of a dose to growth correlation study with Irinotecan at different concentrations, to determine which concentration range to be used for combinatorial drug testing. To assess whether the assay causes concentration-dependent effects on the growth of tumor microtissues, pancreatic microtumors were used and treated with indicated concentrations of Irinotecan. In brief, pancreatic microtumors were produced from the pancreatic cancer cell line Panc-1 (ATCC® CRL-1469™) in co-culture with the mouse fibroblast cell line NIH3T3 (ATCC® CRL-1658™). Both cells were expanded in cell culture flasks using Dulbecco's modification of Eagle medium (DMEM) supplemented with 10% fetal calf serum. After reaching confluency the were removed from the cell culture flask enzymatic digestion (Trypsin). Cell numbers of both cell types were assessed using a Neubauer chamber, and the respective cell number mixed to produce the co-culture microtumors. Seventy ul of the cell mixture was inoculated in each well of a non-adhesive 96-well plates (GravityTRAP™) using Dulbecco's modification of Eagle medium (DMEM) supplemented with 10% horse serum. Pancreatic microtumors were matured in a mammalian cell culture incubator at 37° C. with 5% CO.sub.2. Four days after the cells formed pancreatic tumor microtissues they were dosed with Irinotecan at indicated concentrations adapted according to clinical-used dosages. After 48 hours the drug was removed by changing the culture medium with drug-free medium. The size of the pancreatic microtumors was monitored prior dosing and continuously after dosing using bright field microscopy. Growth is presented relative to the size of the pancreatic tumor microtissue prior compound treatment t.sub.0 (adapted from the RECIST criteria). A clear correlation of dose to growth can be observed.

[0216] FIG. 5 shows single and combinatorial effects applying pancreatic microtumors (production described in FIG. 4). All drugs used were dissolved according to the manufactures protocol. Gemcitabine (approved against PC), Docetaxel (approved against PC) and Pemetrexed (not approved), inhibiting DNA and RNA synthesis, were dosed for 8h with a 48h gap (FIG. 5A). In contrast to the two approved drugs Gemcitabine and Docetaxel, Pemetrexed did not affect tumor growth demonstrating the specificity of the method. Whereas Gemcitabine unfolds its effect quickly, the response to Docetaxel was much slower. However, after day 10 the microtumors treated with Gemcitabine relapsed whereas Docetaxel treatment was more sustainable (FIG. 5A). Combining the two drugs lead to a fast and sustainable response (FIG. 5B).

[0217] FIG. 6 shows single and combinations treatment applying non-small cell lung cancer (NSCLC) model. The NSCLC model was produced by mixing A549 NSCLC cells (ATCC® CCL-18S™) with human lung fibroblasts (Wi38, ATCC® CCL-7S™) in a non-adhesive 96-well plate (GravityTRAP™). Drugs were dosed 2× for 8h with 48h gap. While Pemetrexed was not active against pancreatic microtumors we observed tumor remission of NSCLC microtumors (FIG. 6A). A combinatorial effect was observed combing Gemcitabine and Irinotecan resulting in slightly higher efficiency as compared to the single drug doses.

[0218] FIG. 7 shows basic steps of the method according to the invention, and optional embodiments (shown in italics). The entire package allows the generation of a data bank comprising individual data sets based on 3D method-specific functional data for efficacy and toxicity of given drug combinations with the corresponding genetic profiles of [0219] 3D microtissues derived from one or more cancer cell lines, [0220] 3D microtissues derived from primary patient sample, [0221] 3D microtissues representing connective tissue, and/or [0222] tissue specific microtissues.

[0223] FIG. 8: Key for efficient combinatorial drug discovery is to maintain high throughput capabilities without losing biological relevance. FIG. 8 exemplifies the hit selection and lead validation stage with the associated decreasing number of data points of each stage. “B” refers to step b) in claim 1 (CSS), while “C” refers to step c) in claim 1 (CVS).

[0224] FIG. 9 shows the drug serum titer as a function of time following eight infusions every 21 days. Between the different administrations, the serum titer quickly decreases again. Due to the clearance of drugs in the body the tumor tissue retention time is mostly in the range of hours. Figure taken from Cartron et al, 2007.

[0225] FIG. 10 demonstrates combinatorial drug testing in mice using xenografts from two different non-small cell lung cancer (NSCLC) cell lines (A549 and FICC827) and a patient-derived xenograft (HCC4087). The data demonstrates that single treatments of Erlotinib (approved against NSCLC), a tyrosine kinase inhibitor, and Thalidomide (not approved), an immunomodulatory drug, in the mouse model have a clear synergistic effect. The work done by Gong and coworkers was the basis to evaluate whether the 3D in vitro test method can recapitulate the in vivo results [Gong et al. 2018] shown in FIGS. 11 and 12.

[0226] FIG. 11 demonstrates single and combination treatment using the cell line-based non-small cell lung cancer model (A549, Wi38) as described in FIG. 6. Single and drug combinations were dosed 2× for 8h with a gap of 48h and growth monitored over time. Drug concentrations were adapted from Gong et al. As shown already by Gong et al. in vivo Thalidomide has no significant impact on tumor growth remission, whereas Erlotinib leads to reduced growth but growth relapses after 7 days. Applying 2× less concentrated drugs in the combination a clear superior response was observed over time confirming pre-clinical animal-based results published by Gong et al.

[0227] FIG. 12 exemplifies that a similar outcome as shown in FIGS. 10 and 11 can be achieved with non-small cell cancer (NSCLC) cells directly derived from patients. A NSCLC resection was dissociated, and the cell Suspension used to produce microtumors in a multi-well format (FIG. 12A). Drugs were dosed 2× for 8h with a 48h gap. Whereas Erlotinib and Thalidomide single doses had hardly an impact on tumor growth a clear response was reached with both drugs in combination 3× less concentrated. FIG. 12B displays quantitative values of the relative sizes of day 0 and 9, normalized to day 0 according to the RECIST criteria.

[0228] FIG. 13 exemplifies tox testing of single drugs using connective/stromal microtissues (Wi38) and efficacy testing on non-small cell tumor microtissues (A549; Wi38). Vinorelbin and Docetaxel, both disrupting microtubule, were dosed 2× for 8h with an 8h gap. As compared to the untreated control of the stromal microtissues high dose of Vinorelbin (0.68 ug/ml) displayed elevated cytotoxicity in contrast to Docetaxel (4.05 ug/ml) (FIGS. 13A and C). Comparing efficacy Vinorelbin in high concentration result in less impact on tumor growth compared to low and high concentrated Docetaxel (FIGS. 13B and D). In the framework of compound classification Docetaxel would be favored due to less toxicity and higher efficacy for further development.

EXAMPLES

[0229] The present invention allows for a harmonized analysis starting from a screening to a test using patient material. This makes it possible to align the screening data retrospectively with patient data. In the following, two examples are summarized in tables 6 and 7.

TABLE-US-00005 TABLE 4 RECIST criteria to evaluate therapy outcome (Eisenhower et al. 2009 European Journal of Cancer) Complete Disappearance of all target lesions. Any pathological lymph nodes Response (whether target or non-target) must have reduction in short axis to <10 (CR) mm. Partial At least a 30% decrease in the sum of diameters of target lesions, Response (PR) taking as reference the baseline sum diameters. Progressive At least a 20% increase in the sum of diameters of target lesions, Disease (PD) taking as reference the smallest sum on study (this includes the baseline sum if that is the smallest on study). In addition to the relative increase of 20%, the sum must also demonstrate an absolute increase of at least 5 mm. (Note: the appearance of one or more new lesions is also considered progression). Stable Disease Neither sufficient shrinkage to qualify for PR nor sufficient increase to (SD) qualify for PD, taking as reference the smallest sum diameters while on study. Relapse-free Length of time after primary treatment for a cancer ends that the survival (RFS) patient survives without any signs or symptoms of that cancer

TABLE-US-00006 TABLE 5 Clinically-adapted test-based criteria to evaluate therapy success Remission ≥20% decrease in microtumor size, (RE) Reference: Size t.sub.0 Progression ≥20%-100% increase in microtumor size (PR) Reference: Untreated Control and t.sub.0 Stable +/−20% increase/decrease in size Response Reference: t.sub.0 (SR) Time to Time to re-entry into the growth phase Relapse Reference: Size e.sub.max (TR)* Maximal Maximum increase in size response Reference: Size t.sub.0 (MR)* Time to MR Time until MR is reached (TMR)* Reference: Size MR Potency Lowest concentration to reach MR relative (PO)* to cmax (c.sub.MR/c.sub.max) Reference: c.sub.max of the respective drug ΔT/ΔC Ratio of treatment effect (ΔT) to untreated control (ΔC) Time window: 14 days Concentration-dependent outcome analysis *Indicates criteria to indicate effective therapies

TABLE-US-00007 TABLE 6 Case example 1 Pancreatic cancer treated with Gemcitabine and Irinotecan Pancreatic Cancer (Panc-1) Indication Gemcitabine Irinotecan Drug (median c.sub.max = 20 ug/ml) (median c.sub.max = 5 ug/ml) Potency 0.675 13.5 (PO) [c.sub.MR/c.sub.max] Concentration 0.1 0.5 13.5 0.675 6.75 67.5 [ug/ml] Response SR SR RE PR SR RE Time until 10 10 — — 7 — relapse (TR) [d] Maximal 0.82 0.68 0.56 — 0.86 0.72 response (MR) [%] Time to 10 10 14 — 7 14 MR (TMR) [d] ΔT.sub.14/ΔC.sub.14 −0.25 −0.23 −0.68 1.04  0.06 −0.36

TABLE-US-00008 TABLE 7 Case example II Lung cancer treated with Gemcitabine and Irinotecan and a combination thereof Lung Cancer (A549) Indication Gemcitabine Irinotecan Drug (median c.sub.max = 20 ug/ml) (median c.sub.max = 5 ug/ml) Gemcitabine:Irinotecan Potency 0.015 1.35 0.025:1.35 (PO) [c.sub.MR/c.sub.max] Concentration 0.1 0.3 0.5 6.75 13.5 27 0.5:27.0 0.5:6.75 0.1:27.0 0.1:6.75 0.3:27.0 0.3:13.5 [ug/ml] Response RE RE RE ST RE RE RE RE RE RE RE RE Time until — — — 5 7 — — — — — — — relapse (TR) [d] Maximal 0.77 0.66 0.67 0.88 0.93 0.74 0.55 0.70 0.69 0.71 0.66 0.65 response (MR) [%] Time to 14 14 14 4 7 14 14 14 9 11 14 14 MR (TMR) [d] ΔT.sub.14/ΔC.sub.14 −2.72 −4.04 −3.87 −0.60 −0.32 −3.09 −5.29 −3.49 −3.62 −3.45 −4.03 −4.13

REFERENCES

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