Pharmacodynamic evaluation method based on single-cell dynamic mechanical properties

Abstract

The present invention relates to a drug efficacy evaluation method based on the dynamic mechanical properties of single cells. A single cell is regarded as a linear time-invariant system, with mechanical stimulation as the virtual input of the system, and the continuous-time mechanical properties of the cell under the action of a drug as the output of the system. The dynamic mechanical properties of the cell are characterized according to the identified eigenvalues of the single-cell system matrix. Based on the characterization of cells with and without drug additions in the space, as well as the state of the cells during drug administration, drug efficacy evaluation based on the single-cell scale can be achieved. The present invention can characterize cells with and without drug additions in the space, as well as the state of the cells during drug addition, and establish the relationship between cell mechanical properties and cell state. In addition, compared with traditional methods, the drug testing cycle is greatly shortened, and drug efficacy evaluation based on the single-cell scale can be achieved. Therefore, it has important potential applications in the field of drug sensitivity testing based on the single-cell scale in clinical practice.

Description

Technical Field

[0001] The present invention relates to the field of drug efficacy assessment, specifically a method for noninvasive, nontoxic, and label-free single-cell-scale drug efficacy assessment. Specifically, it combines micro- and nanotechnology detection, systems science, and single-cell modeling to conduct single-cell-scale drug sensitivity testing and single-cell-scale drug efficacy assessment. This method has important potential applications in clinical drug sensitivity testing. Background Art

[0002] Clinically, the resistance of patients to chemotherapy drugs and the heterogeneity of drug responses among different people are serious problems facing current chemotherapy. In clinical practice, anticancer drug sensitivity tests and single-cell sequencing are often performed before chemotherapy, combined with multi-omics technologies to provide a reference for clinicians to make personalized medications. However, traditional in vitro drug sensitivity test methods are performed at the cell population level, which faces the problems of large cell number requirements, lengthy procedures, high false positive rates due to the involvement of additional toxic reagents, and the inability to detect heterogeneity in cell populations. Therefore, it is necessary to develop an in vitro anticancer drug sensitivity test method that can accurately assess the sensitivity of individual patients to anticancer drugs, use less toxic or non-toxic compounds, have a shorter detection procedure, and reflect tumor heterogeneity at the single-cell level.

[0003] Studies have shown that the mechanical properties of cells play a crucial role in cell development and function, human physiological activities, and disease. Cell mechanics is closely related to cell state, function, and life activities. The mechanical properties of cancer cells influence cell motility, adhesion, metastasis, epithelial-mesenchymal transition, and other processes. It has also been reported that the effects of drugs on cells often lead to structural changes, thereby altering their mechanical properties. Certain chemotherapeutic drugs reshape the cytoskeleton and cause changes in its mechanical properties. Furthermore, the density of targets on the cell surface under drug action and the molecular binding forces between the targeted drugs and the cells can also characterize the therapeutic effect of the drugs. Therefore, the study of cancer cell mechanics can advance our understanding of disease pathology and allow for the evaluation of drug efficacy in cancer treatment at the single-cell scale.

[0004] Among the many technologies for measuring cell mechanical properties, atomic force microscopy (AFM) has unique advantages in that it can measure the multifunctional mechanical properties of cells with nanometer-scale spatial resolution and millisecond temporal resolution. However, most studies on the mechanical properties of living cells under the action of drugs and their relationship with the physiological state of cells are conducted at a single time point, ignoring the dynamic evolution of the physiological state and mechanical properties of cells. Therefore, measuring the dynamic evolution of cell mechanical properties within a biologically relevant time scale (several hours) is of great significance for better understanding the structural and functional changes that cells undergo and improving the prediction of the efficacy of cancer treatment drugs. Summary of the Invention

[0005] The purpose of the present invention is to provide a non-invasive, non-toxic, label-free single-cell scale drug efficacy evaluation method to solve the problems raised in the above background technology.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for evaluating drug efficacy based on the dynamic mechanical properties of single cells, characterized in that it comprises the following steps:

[0007] 1) Express a single cell as a linear time-invariant dynamical system and construct a single-cell dynamics model based on input and output;

[0008] 2) For the same cell, characterize the cell dynamics changes based on the characteristic matrix A of the single-cell dynamics model under both drug-free and drug-treated conditions;

[0009] 3) Evaluate drug efficacy at the single-cell scale based on the characterization of kinetic changes.

[0010] The input of the single-cell dynamics model is the mechanical stimulation of the atomic force microscope, which is represented by a step function to achieve non-toxic and non-destructive detection of cells.

[0011] The output of the single-cell dynamics model is the continuous-time cell mechanical properties.

[0012] The output of the single cell dynamics model is Young's modulus or multidimensional viscoelastic parameters.

[0013] The single cell dynamics model is as follows:

[0014]

[0015] Among them, A, B, C, D, K are parameter matrices, A is the characteristic matrix, x(t) is the state of the linear time-invariant dynamic system, which represents the relative displacement between the spring and the damper when the single cell is abstracted as a spring-damper model, u(t) represents the input, y(t) represents the output, and e(t) is the noise of the linear time-invariant dynamic system.

[0016] The characterization of the kinetic changes of cells according to the characteristic matrix A of the single cell kinetic model comprises the following steps:

[0017] Using a system identification method based on subspace identification, the established parameter matrices A, B, C, D, and K are systematically identified, where the characteristic matrix A determines the state transition of a single cell and characterizes the physiological state of the cell.

[0018] The eigenvalues of the identified characteristic matrix A are obtained, and the eigenvalues of the characteristic matrix A are processed to obtain a pair of real numbers;

[0019] Based on the obtained real number pairs, the spatial representation of the cell mechanical properties is performed on the cells before and after drug addition and during drug addition.

[0020] The single-cell scale drug efficacy evaluation based on the characterization of kinetic changes includes the following steps:

[0021] Based on the spatial representation of cell mechanical properties before, during, and after drug addition, by comparing the changes in the cell system matrix before and after drug addition and under different drug action times, as well as the distribution of cells in space, single-cell-scale drug efficacy evaluation is performed based on the density of cells:

[0022] That is, for the cell group before drug addition, the cell group after drug addition, and the cell group during drug addition, find the cell in the middle position in space for each group of cells, and calculate the square of the distance between the cells in the same group and this cell. The smaller the sum of the squares of the distances, the denser the cells and the better the effect of the drug.

[0023] The drug efficacy evaluation device based on the dynamic mechanical properties of single cells includes:

[0024] Single-cell dynamics model building module, used to express a single cell as a linear time-invariant dynamics system and build a single-cell dynamics model based on input and output;

[0025] The kinetic change characterization module is used to characterize the kinetic changes of cells based on the characteristic matrix A of the single-cell kinetic model under the conditions of no drug treatment and drug treatment for the same cell;

[0026] The drug efficacy evaluation module is used to evaluate drug efficacy at the single-cell scale based on the characterization of kinetic changes.

[0027] A drug efficacy evaluation device based on the dynamic mechanical properties of single cells comprises a memory and a processor; the memory is used to store a computer program; the processor is used to implement the drug efficacy evaluation method based on the dynamic mechanical properties of single cells when executing the computer program.

[0028] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the drug efficacy evaluation method based on the dynamic mechanical properties of single cells.

[0029] The present invention has the following beneficial effects and advantages:

[0030] 1. The present invention is non-toxic and non-damaging to cells during the process of using AFM to test the mechanical properties of cells. After the continuous mechanical property test, the cells are still active and can be used for other tests.

[0031] 2. The mechanical properties of cells are a label-free biomarker. When using continuous-time mechanical properties to model single-cell systems, the changes in the physiological state inside the cell are regarded as a "black box". The system matrix A can characterize the changes in the internal dynamic state of the cell under the action of drugs. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic diagram of the principle of the present invention;

[0033] Figure 2a Schematic diagram of obtaining cell mechanical properties for indentation experiments;

[0034] Figure 2b Schematic diagram of AFM indentation experiment;

[0035] Figure 3 Force curves acquired for living cell surfaces;

[0036] Figure 4 Stress-relaxation curves and cell deformation maps obtained for living cell surfaces;

[0037] Figure 5 It is a flowchart of processing the eigenvalue of the system matrix A based on Young's modulus;

[0038] Figure 6 It is a processing flow chart based on the eigenvalue of the multi-dimensional viscoelastic parameter system matrix A;

[0039] Figure 7a It is the fitting diagram of the true experimental value of viscoelastic parameters and the system identification results;

[0040] Figure 7b The spatial representation of single cells in the control group, 100 nM PTX group, and 1000 nM PTX group based on the system identification results of MCF-7 viscoelastic parameters;

[0041] Figure 7c This is the spatial representation of single cells in the HEK293 control group, 100 nM PTX group, and 1000 nM PTX group based on the system identification results of viscoelastic parameters;

[0042] Figure 8a It is the fitting diagram of the true experimental value of viscoelastic parameters and the system identification results;

[0043] Figure 8b This is the spatial representation of single cells in the control group, 100 nM PTX group, and 1000 nM PTX group based on the Young's modulus system identification results of MCF-7;

[0044] Figure 8cThis is the spatial representation of single cells in the control group, 100 nM PTX group, and 1000 nM PTX group based on the Young's modulus system identification results of HEK293;

[0045] Figure 9a The spatial distribution of cells in MCF-7 control group and under the action of PTX_100nM from 0 to 4 hours;

[0046] Figure 9b The spatial distribution of cells in MCF-7 control group and under the action of PTX_100nM for 4 to 8 hours;

[0047] Figure 9c The spatial distribution of cells in HEK293 control group and under the action of DOX_100nM for 0 to 4 hours;

[0048] Figure 9d This is the spatial distribution of cells in the HEK293 control group and under the action of DOX_100nM for 4 to 8 hours. DETAILED DESCRIPTION

[0049] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0050] The present invention relates to a drug efficacy evaluation method based on the dynamic mechanical properties of single cells. According to the dynamic mechanical properties of cells measured by atomic force microscopy, single cells under the action of drugs are modeled and characterized based on system science. The single cell is regarded as a linear time-invariant system, with mechanical stimulation as the virtual input of the system, and the continuous-time mechanical properties of the cell under the action of the drug as the output of the system. The dynamic mechanical properties of the cell are characterized according to the identified eigenvalues of the single-cell system matrix. According to the characterization of cells with and without drug addition in space, as well as the state of cells during drug administration, drug efficacy evaluation based on the single-cell scale can be achieved. The present invention can characterize cells with and without drug addition in space, as well as the state of cells during drug addition, and establish the relationship between cell mechanical properties and cell state. In addition, compared with traditional methods, the drug testing cycle is greatly shortened, and drug efficacy evaluation based on the single-cell scale can be achieved. Therefore, it has important potential applications in the field of drug sensitivity testing based on the single-cell scale in clinical practice.

[0051] See also Figure 1The present invention provides a technical solution: treating a single cell as a linear system and using AFM to continuously monitor the mechanical properties of the cell before and during drug administration. Single-cell modeling is performed using mechanical stimulation as a virtual input and the continuous-time mechanical properties as the system output. Based on the modeling results, single cells are spatially characterized before, during, and after drug administration. Combined with confocal imaging results, drug efficacy evaluation at the single-cell scale is performed.

[0052] Specifically, use Figure 2a The AFM in the instrument was used to perform indentation experiments on the cells, and the cell force curves were recorded using the Nanoscope software. The stress-relaxation curves were recorded synchronously using an oscilloscope. Figure 2b The process of approach-stay-retract in the indentation experiment is shown in FIG.

[0053] Figure 3 The force curve recorded on the surface of living cells is fitted with the Hertz model to obtain the Young's modulus of the cell:

[0054]

[0055] Where F is the loading velocity of the AFM probe, E is the Young's modulus of the cell, δ is the indentation depth, θ is the half-opening angle of the tapered tip, and υ is the Poisson's ratio of the cell. Here, we consider the cell to be a nearly homogeneous object, so υ = 0.5. According to Hooke's law, the loading force F can be written as:

[0056] F=kx

[0057] Where k is the spring constant of the cantilever and x is the deflection of the cantilever, which can be obtained directly from the force curve.

[0058] Figure 4 The figure below shows the PZT displacement, stress-relaxation curve, and cell deformation during the stress-relaxation process recorded by the oscilloscope. The stress-relaxation curve is fitted using the generalized Maxwell model to obtain the multidimensional viscoelastic parameters of the cell:

[0059]

[0060] Among them, u and y represent the input and output of the system respectively, and the state variable x i represents the relative displacement between the spring and the damper in the i-th path. This variable is closely related to the deformation of the cell. i and b iare the elastic and viscous coefficients of the corresponding spring and damper, respectively. Here, the input signal u(t) represents the constant displacement of the PZT in the Z-axis during the stress-relaxation process, and the output signal y(t) is the stress-relaxation curve. The Hankle matrix is used to identify the system order, resulting in a system order of n = 2. The five viscoelastic parameters k0, k1, k2, b1, and b2 are then determined using the least squares method. The cells' continuous-time mechanical properties are measured, and the corresponding continuous-time mechanical characteristic curves are constructed.

[0061] The single cell is regarded as a linear time-invariant system and described by the following state-space equation:

[0062]

[0063] Here, A, B, C, D, and K are parameter matrices, x(t) represents the system state, u(t) represents the system input, y(t) represents the system output, and e(t) represents the system noise. Here, the input is a step function representing the mechanical stimulus of AFM indentation, and the output is a time-dependent cell mechanical characteristic curve of Young's modulus or viscoelastic parameters. In this model, the system matrix A determines the state transitions of the cell system and has a significant impact on the temporal changes in the cell's mechanical properties. Therefore, matrix A can represent the cell system and characterize its physiological state. Figure 5 and Figure 6 The characteristic root processing flow chart is processed based on the eigenvalues of the matrix A obtained by identifying the Young's modulus and the multidimensional viscoelastic parameter curve:

[0064] For the eigenvalues of the matrix A identified by the Young's modulus curve, when the eigenvalues are two real numbers, the two eigenvalues {a, b} are processed in descending order and represented by the real number pair {a, b} after the descending order; when the two eigenvalues are conjugate imaginary numbers {a+bi, a-bi}, the eigenvalues are processed into {a, b}, and the real number pair {a, b} is used to represent the single cell;

[0065] For the eigenvalues of the matrix A obtained by multidimensional viscoelastic parameter curve identification, when the eigenvalues are three real numbers {a, b, c}, the three eigenvalues are sorted in descending order and represented by the real number pair {a, b, c} after the sorting; when the three eigenvalues are {a, b+ci, b-ci}, the size of a and |b+ci| is judged. If a is large, it is represented by the real number pair {a, b, c}; otherwise, it is represented by the real number pair {b, c, a}.

[0066] Figures 7a to 7c This is the result of system identification based on multi-dimensional viscoelastic parameters. Figure 7a It is a fitting diagram of the true experimental values of viscoelastic parameters and the system identification results. Figure 7b to Figure 7cThe spatial representations of the two cells are based on the system identification results of viscoelastic parameters for the control group, 100nM PTX group, and 1000nM PTX group.

[0067] Figures 8a to 8c This is the result of system identification based on Young's modulus. Figure 8a It is a fitting diagram of the true experimental values of viscoelastic parameters and the system identification results. Figures 8b-8c The spatial characterization of single cells in the control group, 100nM PTX group, and 1000nM PTX group based on the Young's modulus system identification results are shown respectively.

[0068] Figures 9a to 9d Spatial characterization of single cells of two cell lines during the action of different drugs. Figure 9a and 9b This is the spatial distribution of cells in the control group, under the action of PTX_100nM for 0 to 4 hours and 4 to 8 hours. Figure 9c and 9d The spatial distribution of cells in the control group, 0-4 hours and 4-8 hours after the action of DOX_100nM;

[0069] The present invention can be used to evaluate the effect of a drug by comparing the difference in the single cell system matrix A with or without drug addition, or the distribution of different groups of cells in space during drug addition.

[0070] Example 1

[0071] 1) Cryopreserved breast cancer cells (MCF-7) and mouse fibroblasts (HEK293) were revived and cultured in 5 ml of complete cell culture medium (89% high-glucose DMEM, 10% fetal bovine serum, and 1% penicillin-streptomycin) in a 60-mm diameter cell culture dish at 37°C in a cell culture incubator with 5% CO2.

[0072] 2) Replace the cell proliferation medium daily until the cells have proliferated to cover 80% of the bottom area of the culture dish;

[0073] 3) Aspirate the cell proliferation medium in the culture dish, add 100 nM and 1000 nM paclitaxel (PTX) and 100 nM doxorubicin (DOX) culture medium to the two cell lines, respectively, and set up a control group, i.e., add the original culture medium (5 ml of complete cell culture medium).

[0074] 4) For the control group and the two cell types in the culture dishes with 100 nM and 1000 nM paclitaxel, 40 cells with similar morphology were selected and subjected to an indentation test every half an hour for 4 consecutive hours.

[0075] 5) For the two cell types in the culture dish with 100 nM paclitaxel and 100 nM doxorubicin added to the culture medium, 40 cells with similar morphology were selected and subjected to an indentation experiment every half an hour for 8 consecutive hours.

[0076] 6) The Hertz model and the generalized Maxwell model are used to calculate the Young's modulus and multidimensional viscoelastic parameters of the cells, respectively, and compose the continuous-time mechanical characteristic curves of single cells.

[0077] 7) Using mechanical stimulation as virtual input and continuous-time mechanical characteristic curve as output, a state-space equation is established.

[0078] 8) The subspace identification method is used to identify the system matrix A, and the eigenvalues are obtained and processed. Real numbers are used to spatially characterize the cells before and after drug addition, and under different drug action times.

[0079] 9) By comparing the changes in the cell system matrix before and after drug addition, and under different drug action times, as well as the distribution of cells in space, single-cell-scale drug efficacy evaluation was performed according to the density of cells: that is, find the cell in the middle position in space in the control group, 100nM PTX group, 1000nM PTX group, PTX_8h group, 1000nM PTX group, PTX_100nM action 0-4h group, PTX_100nM action 4-8h group, DOX_100nM action 0-4h group, and DOX_100nM action 4-8h group, and calculate the square of the distance between cells in the same group and this cell. The smaller the sum of the squares of the distances, the denser the cells and the better the drug effect.

Claims

1. A method for evaluating drug efficacy based on the dynamic mechanical properties of single cells, characterized in that: The following steps are involved: 1) Express a single cell as a linear time-invariant dynamical system and construct a single-cell dynamics model based on input and output; 2) For the same cell, characterize the cell dynamics changes based on the characteristic matrix A of the single-cell dynamics model under both drug-free and drug-treated conditions; 3) Evaluate drug efficacy at the single-cell scale based on the characterization of kinetic changes; The output of the single-cell dynamics model is the continuous-time cell mechanical properties; The output of the single cell dynamics model is Young's modulus or multidimensional viscoelastic parameters; The force curve was fitted using the following Hertz model to obtain the Young's modulus of the cell: Where F is the loading speed of the AFM probe, E is the Young's modulus of the cell, δ is the indentation depth, θ is the half-opening angle of the tapered tip, and υ is the Poisson's ratio of the cell; The stress-relaxation curve is fitted using the generalized Maxwell model to obtain the multidimensional viscoelastic parameters of the cell: Among them, u and y represent the input and output of the system respectively, and the state variable x i represents the relative displacement between the spring and the damper in the i-th path, k i and b i are the elastic and viscous coefficients of the corresponding spring and damper, respectively.

2. The method for evaluating drug efficacy based on single cell dynamic mechanical properties according to claim 1, characterized in that: The input of the single-cell dynamics model is the mechanical stimulation of the atomic force microscope, which is represented by a step function to achieve non-toxic and non-destructive detection of cells.

3. The method for evaluating drug efficacy based on single cell dynamic mechanical properties according to claim 1, characterized in that: The single cell dynamics model is as follows: Among them, A, B, C, D, K are parameter matrices, A is the characteristic matrix, x(t) is the state of the linear time-invariant dynamic system, which represents the relative displacement between the spring and the damper when the single cell is abstracted as a spring-damper model, u(t) represents the input, y(t) represents the output, and e(t) is the noise of the linear time-invariant dynamic system.

4. The method for evaluating drug efficacy based on single cell dynamic mechanical properties according to claim 1, wherein: The characterization of the kinetic changes of cells according to the characteristic matrix A of the single cell kinetic model comprises the following steps: Using a system identification method based on subspace identification, the established parameter matrices A, B, C, D, and K are systematically identified, where the characteristic matrix A determines the state transition of a single cell and characterizes the physiological state of the cell. The eigenvalues of the identified characteristic matrix A are obtained, and the eigenvalues of the characteristic matrix A are processed to obtain a pair of real numbers; Based on the obtained real number pairs, the spatial representation of the cell mechanical properties is performed on the cells before and after drug addition and during drug addition.

5. The method for drug efficacy evaluation based on single cell dynamic mechanical properties according to claim 1, characterized in that: The single-cell scale drug efficacy evaluation based on the characterization of kinetic changes includes the following steps: Based on the spatial representation of cell mechanical properties before, during, and after drug addition, by comparing the changes in the cell system matrix before and after drug addition and under different drug action times, as well as the distribution of cells in space, single-cell-scale drug efficacy evaluation is performed based on the density of cells: That is, for the cell group before drug addition, the cell group after drug addition, and the cell group during drug addition, find the cell in the middle position in space for each group of cells, and calculate the square of the distance between the cells in the same group and this cell. The smaller the sum of the squares of the distances, the denser the cells and the better the effect of the drug.

6. A drug efficacy evaluation device based on single cell dynamic mechanical properties, which performs a drug efficacy evaluation method based on single cell dynamic mechanical properties according to any one of claims 1 to 5, characterized in that ,include: Single-cell dynamics model building module, used to express a single cell as a linear time-invariant dynamics system and build a single-cell dynamics model based on input and output; The kinetic change characterization module is used to characterize the kinetic changes of cells based on the characteristic matrix A of the single-cell kinetic model under the conditions of no drug treatment and drug treatment for the same cell; The drug efficacy evaluation module is used to evaluate drug efficacy at the single-cell scale based on the characterization of kinetic changes.

7. A drug efficacy evaluation device based on the dynamic mechanical properties of single cells, characterized in that: It comprises a memory and a processor; the memory is used to store a computer program; the processor is used to implement the drug efficacy evaluation method based on the dynamic mechanical properties of single cells as described in any one of claims 1 to 5 when executing the computer program.

8. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by the processor, the drug efficacy evaluation method based on the dynamic mechanical properties of single cells as described in any one of claims 1 to 5 is implemented.

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