A TOPSIS-based method for evaluating drug sensitivity of tumor organoids

Abstract

The present invention provides a method for evaluating the drug sensitivity of tumor organoids based on the TOPSIS method. According to the drug sensitivity reaction of tumor organoids after drug administration, the key evaluation indicators are screened and determined as IC50, AUC and cell survival rate, and the TOPSIS algorithm is further used to convert qualitative and quantitative data into comparable values, which is convenient for systematic analysis and ranking and reduces the influence of subjective factors. By calculating the relative proximity, a ranking of the sensitivity of drugs to tumor organoids is formed, and it is clear which drugs have greater therapeutic potential in specific tumor types, thereby providing a scientific basis for clinicians and researchers, helping them make more accurate decisions in drug selection and treatment plan formulation.

Description

Technical Field

[0001] The present invention belongs to the technical field of drug sensitivity evaluation, and relates to a method for evaluating drug sensitivity of tumor organoids based on the TOPSIS method. Background Art

[0002] In recent years, the number of drugs for treating cancer patients has increased. With the increase in drug categories, choosing the right drug for cancer patients has become a new problem for cancer patients and clinicians. Although some clinical studies and guidelines recommend and guide the use of drugs for cancer patients, there are great individual differences among cancer patients, the cost of anti-cancer drugs is high, and treatment is urgent. There is an urgent need for technologies and methods to accurately predict the drug response of cancer patients.

[0003] As an emerging in vitro model, organoid technology uses tissues from tumor patients to construct tumor organoids, which can replicate the compositional complexity and genetic characteristics of patient tumors to the greatest extent, providing an available and accurate model for the precision treatment of cancer patients. On the one hand, tumor organoids can fully simulate the patient's tumor microenvironment, and on the other hand, they can accurately evaluate the drug responsiveness and safety of tumor patients. However, in actual applications, there are still multiple drugs or drug combinations that are effective for organoids, and the best medication regimen needs to be selected. Therefore, a more effective drug sensitivity evaluation method is needed to reflect the sensitivity of drugs in the process of tumor organoid drug screening, so as to guide patients' clinical medication. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention provides a method for evaluating drug sensitivity of tumor organoids based on the TOPSIS method.

[0005] In order to achieve the technical purpose, the technical solution adopted by the present invention is:

[0006] A method for evaluating drug sensitivity of tumor organoids based on the TOPSIS method, comprising: obtaining the IC50, AUC and cell survival rate of a drug or drug combination in tumor organoids according to the drug sensitivity response of tumor organoids after drug administration, and using the TOPSIS method to comprehensively rank multiple numerical results to obtain a ranking that best reflects the therapeutic effect of the drug on tumor organoids.

[0007] Preferably, the above method specifically includes:

[0008] 1) According to the phenotypic changes of tumor organoids after drug exposure, the evaluation indicators are determined as IC50, AUC and cell survival rate to form original data;

[0009] 2) Organize the collected raw data into a decision matrix and standardize the decision matrix;

[0010] 3) Assign weights to each evaluation indicator and determine the ideal solution and negative ideal solution;

[0011] 4) Calculate the proximity of the tumor organoids to each drug based on the distance of each evaluation indicator from the ideal solution and the negative ideal solution;

[0012] 5) Sort each tumor organoid according to relative proximity, where the higher the value, the better the sensitivity of the drug to the tumor organoid.

[0013] Preferably, step 1) comprises: detecting cell proliferation and apoptosis using the CCK-8 method, and detecting cell viability using dead-alive immunofluorescence staining.

[0014] Preferably, in step 2), the decision matrix is:

[0015]

[0016] The rows represent different tested drugs and the columns represent the evaluation indicators.

[0017] Preferably, step 2) comprises: linearly normalizing the benefit-type indicator cell survival rate and AUC value:

[0018]

[0019] Among them, z ij represents the value of the i-th row and j-th column after matrix standardization, x ij represents the value of the i-th row and j-th column in the original matrix, min(x *j ) and max(x *j ) are the minimum and maximum values ​​of each column in the matrix.

[0020] More preferably, step 2) comprises: performing reverse standardization on the cost-based indicator IC50 value:

[0021]

[0022] Among them, z ij represents the value of the i-th row and j-th column after matrix standardization, x ij represents the value of the i-th row and j-th column in the original matrix, min(x *j ) and max(x *j ) are the minimum and maximum values ​​of each column in the matrix.

[0023] Preferably, in step 3), the weights are determined by expert consultation to ensure that the sum of the weights is 1.

[0024] Preferably, in step 3), determine the ideal solution A + and negative ideal solution A - The formula is:

[0025] A + ={(maxv ij |j∈J),(minv ij |j∈J 0 ),j=1,2…n;

[0026] A - ={(minv ij |j∈J),(maxv ij |j∈J 0 ),j=1,2…n;

[0027] Among them, v ij represents the jth evaluation index of the i-th evaluation target, J 0 is a cost-based indicator set; J is a benefit-based indicator set.

[0028] More preferably, in step 4), each indicator is equal to the ideal solution A + Distance The calculation formula is:

[0029]

[0030] Each index and negative ideal solution A - Distance The calculation formula is:

[0031]

[0032] in, represents the ideal solution of the jth evaluation index, represents the negative ideal solution of the j-th evaluation index.

[0033] More preferably, the proximity C of the tumor organoids to each drug i The calculation formula is:

[0034]

[0035] The beneficial effects of the present invention are:

[0036] According to the drug sensitivity reaction of tumor organoids after medication, the present invention screens and determines that key evaluation indicators are closely related to tumor biological characteristics, such as IC50, AUC and cell survival rate, and further uses the TOPSIS algorithm to convert qualitative and quantitative data into comparable values, which is convenient for systematic analysis and ranking, and reduces the influence of subjective factors. By calculating the relative proximity, the sensitivity ranking of drugs to tumor organoids is formed, and it is clear which drugs have more therapeutic potential in specific tumor types. Provide a scientific basis for clinicians and researchers to help them make more accurate decisions in drug selection and treatment plan formulation. Identify drugs that are effective for specific tumor types, promote the development of new drugs and the re-evaluation of existing drugs, and promote the progress of personalized medicine. The TOPSIS method can consider multiple evaluation indicators at the same time, avoid the deviation that may be caused by a single indicator, and improve the accuracy and reliability of the evaluation. In the actual clinical use process, the method is simple and convenient, and is consistent with the actual reaction of the patient after medication, has better clinical relevance, effectively improves the accuracy of guiding medication after organoid evaluation, and provides a proven evaluation means and method for guiding the clinical medication of patients by tumor organoids. The TOPSIS algorithm is relatively simple, easy to understand and implement, and is suitable for researchers from different backgrounds. This method can flexibly adjust indicators and weights according to research needs and adapt to different types of tumors and drug evaluations. The final results are presented in charts, allowing researchers and clinicians to intuitively understand the drug sensitivity rankings and facilitate communication and discussion. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 .IC50 test results of drugs in liver cancer organoids in the examples of the present invention.

[0038] Figure 2 .The imaging results after treatment with lenvatinib in the application examples of the present invention.

[0039] Figure 3 .The TOPSIS method and the single index method in the application examples of the present invention guide the results of the medication after the patient takes the medication. DETAILED DESCRIPTION

[0040] In order to explain the present invention more clearly, the present invention is further described in detail below in conjunction with the embodiments and drawings. It should be understood by those skilled in the art that the content described below is illustrative rather than restrictive, and should not be used to limit the scope of protection of the present invention.

[0041] Example

[0042] 1. Tumor Organoid Culture

[0043] Fresh tissue samples were obtained from tumor tissues of liver cancer patients (all of whom had signed informed consent forms in accordance with regulations) for organoid culture. Fat and blood stains on the surface of the tissue were removed using surgical scissors and tweezers under sterile conditions, and the tissue was washed with PBS until the washing solution was clear. The tissue was cut into pieces of about 2 mm and added to a centrifuge tube containing 5 mL of digestion solution (20 mg collagenase and 20 μL DNase dissolved in 10 mL of DMEM / F12 medium containing 1% BSA), and incubated at 200 rpm on a shaker at 37°C for 15-30 minutes. Subsequently, 2.5 mL of culture medium containing 10% serum was added to terminate the digestion.

[0044] The tissue suspension obtained above was centrifuged at 300g for 10 minutes at 4°C, and the supernatant was discarded. Then, 5 mL of PBS containing 1% PSA was added to resuspend the precipitate, and filtered through a 70 μm cell mesh. The collected tissue filtrate was centrifuged at 300g for 10 minutes at 4°C, and the supernatant was discarded. The precipitate was collected to obtain the desired tissue sample.

[0045] Prepare the culture medium for liver cancer organoids: add 1% Glutamax, 10nM Gastrin, 1%-5% Penicillin-Streptomycin, 1% N2, 10μM SB202190, 5ng / mL FGF-2, 100ng / mL FGF-10, 5ng / mL EGF, 100ng / mL Noggin, 100ng / mL R-Spondin-1, 10mM Nicotinamide, 500nM-800nM A83-01, 25ng / mL HGF, 10μM-20μM Forskolin, 5μM Y-27632, and 1% B27 to DMEM / F12 culture medium.

[0046] After the filtered cells are resuspended in the culture medium of liver cancer organoids, they are inoculated into a culture dish containing matrix gel at an appropriate cell density (about 2×10^6 / ml), incubated in a 37°C incubator for 30 minutes to 1 hour to solidify the matrix and form a support structure. The cells are cultured in a constant temperature incubator at 37°C and 5% CO2, and the culture medium is replaced regularly (usually every 2-3 days). When the organoids reach about 200μm, they are subcultured. The organoids are cut into small pieces and inoculated into new matrices for expansion and subculture.

[0047] 2. Drug sensitivity testing of tumor organoids

[0048] The drugs to be tested were prepared at different concentrations (such as 1, 10, 100 μM, etc.), and the culture dish wells for culturing organoids were set as drug groups (respectively treated with sorafenib, bevacizumab, and lenvatinib) and control groups (no treatment). Different concentrations of drugs were added to the organoid culture wells of the drug groups, and the cell viability was determined by fluorescence staining 24 hours after drug treatment, and the drug half-inhibitory concentration (IC50), AUC value and cell survival rate at the same concentration were calculated. The results are shown in Tables 1 and Figure 1 shown.

[0049] Table 1. Antitumor effects of three antitumor drugs in liver cancer organoids

[0050]

[0051] According to the test results, the IC50, AUC and cell survival rate of the drug (100 μM) in liver cancer organoids were calculated, as shown in Table 2:

[0052] Table 2. IC50, AUC and cell survival rate of three anti-tumor drugs in liver cancer organoids

[0053]

[0054] 3. Build a decision matrix

[0055] The collected data are organized into a decision matrix D, where rows represent different test drugs, m=3 in this embodiment, and columns represent evaluation indicators.

[0056]

[0057] 4. Standardized decision matrix

[0058] Since the smaller the IC50 value, the higher the drug sensitivity, while the cell survival rate and AUC value are effect-type indicators, these two types of indicators need to be treated differently.

[0059] Linear normalization was performed for benefit indicators (cell survival rate and AUC value):

[0060]

[0061] Among them, z ij represents the value of the i-th row and j-th column after matrix standardization, x ij represents the value of the i-th row and j-th column in the original matrix, min(x *j ) and max(x *j ) are the minimum and maximum values ​​of each column in the matrix.

[0062] For cost-based indicators (IC50 values), reverse normalization is performed:

[0063]

[0064] Among them, z ij represents the value of the i-th row and j-th column after matrix standardization, x ij represents the value of the i-th row and j-th column in the original matrix, min(x *j ) and max(x *j ) are the minimum and maximum values ​​of each column in the matrix.

[0065] 5. Determine weights: Assign weights to each indicator. The weights can be determined by expert consultation to ensure that the sum of the weights is 1. In this embodiment, the weights of IC50, cell viability, and AUC are set to 0.5, 0.3, and 0.2, respectively.

[0066] 6. Determine the ideal solution A + and negative ideal solution A - :

[0067] A + ={(maxv ij |j∈J),(minv ij |j∈J 0 ),j=1,2…n;

[0068] A - ={(minv ij |j∈J),(maxv ij |j∈J 0 ),j=1,2…n;

[0069] Among them, v ij represents the jth evaluation index of the i-th evaluation target, J 0 is a cost-based indicator set; J is a benefit-based indicator set.

[0070] Calculate each indicator and the ideal solution A + Distance

[0071]

[0072] And each index and the negative ideal solution A - Distance

[0073]

[0074] in, represents the ideal solution of the jth evaluation index, represents the negative ideal solution of the j-th evaluation index.

[0075] 7. Calculate the proximity of the tumor organoids to each drug based on the distance to the ideal solution and the negative ideal solution

[0076] Degree C i :

[0077]

[0078] 8. According to the relative proximity C i The tumor organoids were ranked by the values, and the results are shown in Table 3. The higher the value, the better the sensitivity of the drug to the tumor organoid.

[0079] Table 3. TOPSIS method compares the ranking of the effects of three anti-tumor drugs in liver cancer organoids

[0080]

[0081] The results showed that lenvatinib ranked first in relative proximity, sorafenib ranked second, and bevacizumab ranked third, indicating that this type of organ has the best sensitivity to lenvatinib.

[0082] Application Examples

[0083] According to the drug ranking of the TOPSIS test, it is recommended that the liver cancer patients in the above test be treated with lenvatinib (12 mg per day). The drug treatment is evaluated every month, and the patient's treatment response after drug treatment is evaluated according to the mRECIST standard. The specific evaluation criteria are as follows: Complete remission (CR): All lesions disappear. Partial remission (PR): The maximum diameter of the tumor decreases by 30% or more. Stable disease (SD): The maximum diameter of the tumor changes between -30% and +20%. Progressive disease (PD): The maximum diameter of the tumor increases by 20% or more. After the patient was treated with lenvatinib, the tumor showed a significant remission. The specific imaging results are as follows: Figure 2 shown.

[0084] According to the above evaluation method, the use of TOPSIS method and single indicator method to guide patients' organoid medication were compared. A total of 43 liver cancer patients were included. Two groups of patients were divided into two groups according to whether the medication was guided by TOPSIS method or not and whether the medication was guided by a single indicator. Among them, 21 patients were included in the TOPSIS method-guided medication group, of which 17 patients had effective treatment (CR+PR) after drug treatment, and the overall effective rate was 81%. A total of 22 patients were included in the single indicator-guided medication group, of which 14 patients had effective treatment (CR+PR) after drug treatment, and the overall effective rate was 63.6%. The effectiveness of TOPSIS method-guided medication in patients was significantly higher than that of the single indicator-guided medication group.

[0085] Table 4. Clinical effect results of 43 patients using TOPSIS method and single index method to guide medication

[0086]

[0087] Obviously, the above embodiments of the present invention are merely examples to more clearly illustrate the present invention, and are not limitations on the implementation methods of the present invention. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made on the basis of the above description. It is impossible to list all the implementation methods here. All obvious changes or modifications derived from the technical solution of the present invention are still within the protection scope of the present invention.

Claims

1. A method for evaluating drug sensitivity of tumor organoids based on TOPSIS method, comprising: Based on the phenotypic changes of tumor organoids after drug exposure, the IC50, AUC and cell survival rate of the drug or drug combination in tumor organoids are obtained. The TOPSIS method is used to comprehensively rank multiple numerical results to obtain a ranking that best reflects the therapeutic effect of the drug on tumor organoids.

2. The method for evaluating drug sensitivity of tumor organoids based on TOPSIS method according to claim 1, characterized in that: Specifically include: 1) According to the drug sensitivity response of organoids after drug administration, the evaluation indicators are determined as IC50, AUC and cell survival rate to form original data; 2) Organize the collected raw data into a decision matrix and standardize the decision matrix; 3) Assign weights to each evaluation indicator and determine the ideal solution and negative ideal solution; 4) Calculate the proximity of the tumor organoids to each drug based on the distance of each evaluation indicator from the ideal solution and the negative ideal solution; 5) Sort each tumor organoid according to relative proximity, where the higher the value, the better the sensitivity of the drug to the tumor organoid.

3. The method for evaluating drug sensitivity of tumor organoids based on TOPSIS method according to claim 2, characterized in that: Step 1) includes: using CCK-8 method to detect cell proliferation and apoptosis, and using dead-live immunofluorescence staining to detect cell viability.

4. The method for evaluating drug sensitivity of tumor organoids based on TOPSIS method according to claim 2, characterized in that: In step 2), the decision matrix is: The rows represent different tested drugs and the columns represent the evaluation indicators.

5. The method for evaluating drug sensitivity of tumor organoids based on TOPSIS method according to claim 2, characterized in that: Step 2) includes: linearly normalizing the benefit indicator cell survival rate and AUC value: Among them, z ij represents the value of the i-th row and j-th column after matrix standardization, x ij represents the value of the i-th row and j-th column in the original matrix, min(x *j ) and max(x *j ) are the minimum and maximum values ​​of each column in the matrix.

6. The method for evaluating drug sensitivity of tumor organoids based on TOPSIS method according to claim 5, characterized in that: Step 2) includes: performing reverse standardization on the cost-based indicator IC50 value: Among them, z ij represents the value of the i-th row and j-th column after matrix standardization, x ij represents the value of the i-th row and j-th column in the original matrix, min(x *j ) and max(x *j ) are the minimum and maximum values ​​of each column in the matrix.

7. The method for evaluating drug sensitivity of tumor organoids based on TOPSIS method according to claim 2, characterized in that: In step 3), the weights are determined by expert consultation to ensure that the sum of the weights is 1.

8. The method for evaluating drug sensitivity of tumor organoids based on TOPSIS method according to claim 2, characterized in that: In step 3), determine the ideal solution A + and negative ideal solution A - The formula is: A + ={(maxv ij |j∈J),(minv ij |j∈J 0 ),j=1,2…n; A - ={(minv ij |j∈J),(maxv ij |j∈J 0 ),j=1,2…n; Among them, v ij represents the jth evaluation index of the i-th evaluation target, J 0 is a cost-based indicator set; J is a benefit-based indicator set.

9. The method for evaluating drug sensitivity of tumor organoids based on TOPSIS method according to claim 8, characterized in that: In step 4), each indicator is compared with the ideal solution A + Distance The calculation formula is: Each index and negative ideal solution A - Distance The calculation formula is: in, represents the ideal solution of the jth evaluation index, represents the negative ideal solution of the j-th evaluation index.

10. The method for evaluating drug sensitivity of tumor organoids based on TOPSIS method according to claim 9, characterized in that: The proximity C of tumor organoids to each drug i The calculation formula is:

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