Method, system and equipment for evaluating methylene blue treatment effect based on stress particles

Abstract

The invention discloses a method, a system and equipment for evaluating the treatment effect of methylene blue based on stress particles. It is found for the first time that methylene blue treats pancreatic cancer, liver cancer and hepatic fibrosis by inhibiting expression of the stress particles, and it is found that expression of the core component G3BP protein of the stress particles is positively correlated with the treatment effect of methylene blue on hepatic fibrosis. Besides, the invention provides a method, equipment and system for evaluating the cancer treatment effect of methylene blue and a method, equipment and system for evaluating the hepatic fibrosis treatment effect of methylene blue, so that doctors are assisted in evaluating the treatment effects of pancreatic cancer patients, liver cancer patients and hepatic fibrosis patients. And a clinician is guided to formulate a personalized treatment scheme for the patient.

Description

Technical Field

[0001] This invention belongs to the field of bioinformatics, specifically relating to a method, system, and apparatus for evaluating the therapeutic effect of methylene blue on cancer and a method, system, and apparatus for evaluating the therapeutic effect of methylene blue on liver fibrosis. Background Technology

[0002] Pancreatic cancer is a highly aggressive and deadly malignant tumor, with its incidence and mortality rates rising globally. Because early symptoms of pancreatic cancer are often subtle, most patients are diagnosed at an advanced stage, missing the optimal window for surgical treatment. Therefore, identifying effective screening targets and therapeutic drugs is crucial for improving the prognosis of pancreatic cancer patients. Liver cancer has become the fifth most common cancer and the third leading cause of cancer death worldwide, and its incidence and mortality rates continue to rise in recent years. Due to limited early detection and prevention methods, coupled with the limitations of traditional surgical treatments and radiotherapy / chemotherapy, which are not suitable for all patients, the resulting public health problems and medical burden continue to increase. Therefore, further research into its pathogenesis is urgently needed to develop new and more effective prevention and treatment methods. Liver fibrosis is one of the important risk factors for the development and progression of liver cancer, with approximately 90% of liver cancers developing from liver fibrosis.

[0003] Methylene blue is an FDA-approved drug used to treat methemoglobinemia, cyanide poisoning, and central nervous system disorders (ischemic stroke, Alzheimer's disease, and other neurodegenerative diseases). It also has therapeutic effects on colorectal cancers and melanoma using photodynamic therapy. However, the role of methylene blue in stress granulation in pancreatic cancer, liver cancer, and liver fibrosis has not been reported.

[0004] Therefore, accurately evaluating the therapeutic effects of methylene blue on patients with pancreatic cancer, liver cancer, and liver fibrosis plays a very important role in treatment selection, surgical design, and efficacy assessment. Summary of the Invention

[0005] In view of this, in order to overcome the shortcomings of the prior art, the purpose of the present invention is to provide a method, system and apparatus for evaluating the therapeutic effect of methylene blue on cancer and a method, system and apparatus for evaluating the therapeutic effect of methylene blue on liver fibrosis.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A first aspect of the present invention provides a method for evaluating the therapeutic effect of methylene blue on cancer, the method being performed by a computer and comprising the following steps: Data Acquisition: Acquire the expression data of stress particles in cancer patient samples after methylene blue treatment. The expression data of stress particles includes the proportion of stress particle number and the proportion of stress particle area. The proportion of stress particle number is the ratio of the number of cells expressing stress particles to the total number of cells in the measurement area. The proportion of stress particle area is the ratio of the total area occupied by stress particles in the image to the total area of ​​the analyzed area. Data processing: The expression data of the stress particles are input into the constructed efficacy evaluation model for methylene blue treatment of cancer. The efficacy evaluation model for methylene blue treatment of cancer is based on the expression data of the stress particles to determine the treatment effect of the cancer patients after receiving methylene blue treatment. Output results.

[0007] Furthermore, the cancers include pancreatic tumors and liver tumors.

[0008] In a specific embodiment of the present invention, the pancreatic tumor is pancreatic cancer, and the liver tumor is liver cancer.

[0009] In this invention, the term "pancreatic cancer" refers to a malignant tumor occurring within the pancreatic tissue, including pancreatic ductal adenocarcinoma originating from the pancreatic duct epithelium, adenocarcinoma originating from pancreatic acini or glands, and rare types of neuroendocrine carcinoma; the term "liver cancer" refers to a malignant tumor occurring within the liver tissue, including hepatocellular carcinoma, intrahepatic cholangiocarcinoma, and mixed-type liver cancer; the term "pancreatic tumor" refers to all neoplastic lesions occurring within the pancreas, including benign tumors, borderline or dysplastic lesions, and malignant tumors. This term is a general term used to encompass all pathological proliferations forming new growths within the pancreas; the term "liver tumor" refers to all neoplastic lesions occurring within the liver tissue, including benign tumors, precancerous lesions, and malignant tumors. This term is used to represent the general term for all tumors or mass-like lesions within the liver. In this invention, the specific usage of the stress particle quantity ratio and the stress particle area ratio depends on the type of tissue / cell used. The term "stress particle quantity ratio" refers to the proportion of cells expressing stress particles per unit area or per unit cell relative to the total number of cells in the measurement area. In some embodiments of this invention, this indicator is typically obtained through immunofluorescence (e.g., labeling with G3BP1, TIA-1, eIF3, etc.) or high-resolution imaging, with image analysis software automatically calculating the expression of stress particles in each cell or field of view. The term "stress particle area ratio" refers to the ratio of the total area occupied by stress particles in the image to the total area of ​​the analyzed region (e.g., a single cell region or the entire field of view). In some embodiments of this invention, after labeling SG-related proteins (e.g., G3BP1) with immunofluorescence, the image is thresholded and segmented, the area of ​​SG-positive signals is extracted, and divided by the corresponding cell area or field of view area to obtain the relative proportion of the stress particle area.

[0010] Furthermore, the steps for constructing the efficacy evaluation model for methylene blue treatment of cancer are as follows: The expression data of stress particles are obtained, including the number and area of ​​stress particles; the expression data of stress particles are obtained from untreated cancer patients and cancer patients treated with methylene blue; the expression data of stress particles are input into a machine learning algorithm to construct an efficacy evaluation model for methylene blue treatment of cancer.

[0011] Furthermore, the efficacy evaluation model for methylene blue treatment of cancer was obtained using the following criteria: When the value of any one or more of the stress particle quantity ratio and stress particle area ratio is lower than the threshold, a classification result is obtained that methylene blue is effective in treating cancer patients; when the value of the stress particle quantity ratio and stress particle area ratio is not lower than the threshold, a classification result is obtained that methylene blue is ineffective in treating cancer patients.

[0012] In this invention, the term "threshold" refers to a representative value of a sample of cancer populations that have not received any relevant treatment, including but not limited to the maximum value, the third quartile, and the mean.

[0013] Furthermore, the machine learning algorithm includes algorithmic models developed using various development tools.

[0014] Furthermore, the development tools include, but are not limited to, TensorFlow, Scikit-Learn, and PyTorch. OpenNN, RapidMiner, Azure Machine Learning, Apache Mahout, Shogun, KNIME, Vertex AI, H2Oai, Anaconda, Keras, Tableau, Fast.ai, Catalyst, Amazon ML, MLJAR, Spell.

[0015] Furthermore, the algorithm models include, but are not limited to, linear regression models, logistic regression models, Lasso regression models, Ridge regression models, linear discriminant analysis models, nearest neighbor models, decision tree models, perceptron models, neural network models, support vector machine models, Naive Bayes models, AdaBoost models, GBDT models, XGBoost models, LightGBM models, CatBoost models, and random forest models.

[0016] Furthermore, the term "patient" refers to any animal, including both human and non-human animals. Non-human animals include all vertebrates, such as mammals like non-human primates (especially higher primates), sheep, dogs, rodents (such as mice or rats), guinea pigs, goats, pigs, cats, rabbits, cattle, and any livestock or pets; as well as non-mammals such as amphibians, reptiles, etc.

[0017] Furthermore, the samples include tissue samples, blood, serum, plasma, or exosome samples.

[0018] A second aspect of the present invention provides a method for evaluating the therapeutic effect of methylene blue on liver fibrosis, the method being performed by a computer and comprising the following steps: Data Acquisition: Acquire the expression data of stress particles in liver fibrosis patient samples after methylene blue treatment. The expression data of stress particles includes the proportion of stress particle number, the proportion of stress particle area, the expression level of G3BP1, and the expression level of G3BP2. The proportion of stress particle number is the ratio of the number of cells expressing stress particles to the total number of cells in the measurement area. The proportion of stress particle area is the ratio of the total area occupied by stress particles in the image to the total area of ​​the analyzed area. Data processing: The expression data of the stress particles are input into the constructed efficacy evaluation model of methylene blue treatment for liver fibrosis. The efficacy evaluation model of methylene blue treatment for liver fibrosis is based on the expression data of the stress particles to judge the treatment effect of the liver fibrosis patients after receiving methylene blue treatment. Output results.

[0019] Furthermore, the expression levels of G3BP1 and G3BP2 include mRNA expression levels or protein expression levels.

[0020] Furthermore, the mRNA expression level includes, but is not limited to, levels obtained through RT-mediated expression. PCR method, qRT Data obtained by PCR, in situ hybridization and RNA sequencing.

[0021] Furthermore, the protein expression level data includes, but is not limited to, data obtained by immunoblotting, immunohistochemistry, enzyme-linked immunosorbent assay (ELISA), and mass spectrometry.

[0022] In a specific embodiment of the present invention, the protein expression level is data obtained by immunoblotting.

[0023] In this invention, the term "liver fibrosis" refers to the abnormal proliferation of fibrous tissue in the liver caused by the activation of hepatic stellate cells and excessive deposition of collagen and extracellular matrix under chronic inflammation or injury. Liver fibrosis can progress, eventually leading to cirrhosis. This term is not limited to a specific cause and can be caused by viral hepatitis, alcoholic injury, metabolic / fatty liver disease, or toxic injury, etc.

[0024] Furthermore, the steps for constructing the efficacy evaluation model for methylene blue treatment of liver fibrosis are as follows: The expression data of stress particles were obtained, including the number of stress particles, the area of ​​stress particles, the expression level of G3BP1, and the expression level of G3BP2. The expression data of stress particles came from untreated liver fibrosis patients and liver fibrosis patients treated with methylene blue. The expression data of stress particles were input into a machine learning algorithm to construct an efficacy evaluation model for methylene blue treatment of liver fibrosis.

[0025] Furthermore, the efficacy evaluation model for methylene blue treatment of liver fibrosis was obtained using the following criteria: When any one or more of the values ​​of the proportion of stress particle number, the proportion of stress particle area, the expression level of G3BP1, and the expression level of G3BP2 are lower than the threshold, a classification result is obtained that methylene blue is effective in treating patients with liver fibrosis; when the values ​​of the proportion of stress particle number, the proportion of stress particle area, the expression level of G3BP1, and the expression level of G3BP2 are all higher than the threshold, a classification result is obtained that methylene blue is ineffective in treating patients with liver fibrosis.

[0026] The third aspect of the present invention provides any of the following systems: (1) A system for evaluating the therapeutic effect of methylene blue on pancreatic cancer, the system comprising: 101 Data Acquisition Unit: Used to acquire the expression data of stress particles in pancreatic cancer patient samples after methylene blue treatment. The expression data of stress particles includes the proportion of stress particle number and the proportion of stress particle area. The proportion of stress particle number is the ratio of the number of cells expressing stress particles to the total number of cells in the measurement area. The proportion of stress particle area is the ratio of the total area occupied by stress particles in the image to the total area of ​​the analyzed area. 102 Data Analysis Unit: Used to classify and predict the efficacy evaluation model of methylene blue treatment for pancreatic cancer obtained by the data acquisition unit through the construction steps described in the first aspect of the present invention, and to obtain the classification result of whether methylene blue is effective in treating pancreatic cancer patients; 103 Result Output Unit: Used to output the result to the receiving unit; (2) A system for evaluating the therapeutic effect of methylene blue on liver cancer, the system comprising: 201 Data Acquisition Unit: Used to acquire the expression data of stress particles in liver cancer patient samples after methylene blue treatment. The expression data of stress particles includes the proportion of stress particle number and the proportion of stress particle area. The proportion of stress particle number is the ratio of the number of cells expressing stress particles to the total number of cells in the measurement area. The proportion of stress particle area is the ratio of the total area occupied by stress particles in the image to the total area of ​​the analyzed area. 202 Data Analysis Unit: Used to classify and predict the efficacy evaluation model of methylene blue treatment for liver cancer obtained by the data acquisition unit through the construction steps described in the first aspect of the present invention, and to obtain the classification result of whether methylene blue is effective in treating liver cancer patients; 203 Result Output Unit: Used to output the result to the receiving unit.

[0027] (3) A system for evaluating the therapeutic effect of methylene blue on liver fibrosis, the system comprising: 301 Data Acquisition Unit: Used to acquire the expression data of stress particles in liver fibrosis patient samples after methylene blue treatment. The expression data of stress particles includes the proportion of stress particle number, the proportion of stress particle area, the expression level of G3BP1, and the expression level of G3BP2. The proportion of stress particle number is the ratio of the number of cells expressing stress particles to the total number of cells in the measurement area. The proportion of stress particle area is the ratio of the total area occupied by stress particles in the image to the total area of ​​the analyzed area. 302 Data Analysis Unit: Used to classify and predict the efficacy evaluation model of methylene blue treatment for liver fibrosis obtained by the data acquisition unit through the construction steps described in the second aspect of the present invention, and to obtain the classification result of whether methylene blue is effective in treating patients with liver fibrosis. 303 Result Output Unit: Used to output the result to the receiving unit.

[0028] Furthermore, the receiving unit includes a display screen, a computer client, a mobile client, or a tablet.

[0029] In this invention, the data acquisition unit can support multiple detection sources and data types. The data acquisition unit may include a data interface module for receiving numerical values ​​or images output by the detection instrument; a sample information management module for entering the basic information of the subject (number, gender, age, pathological source, etc.); and a data preprocessing module for standardizing, background subtracting, or numerical conversion of the original detection results.

[0030] Furthermore, the data analysis unit can use statistical algorithms (such as Z-score judgment, t-test) or machine learning algorithms (such as logistic regression, support vector machine SVM) to perform pattern recognition on the acquired data; when the input is multidimensional data, the analysis unit can realize multimodal fusion judgment to improve diagnostic accuracy.

[0031] Furthermore, the output results of the result output unit include, but are not limited to, qualitative judgments, graphical displays, and suggestive prompts (such as "further review is recommended"); the output unit can transmit the results to the clinical information system via a display screen, printed report, or electronic interface, and can generate a PDF format result report containing patient number, testing method, result interpretation, and data traceability information; the output unit supports cloud storage and multi-center data sharing to enable AI training and model updates.

[0032] Furthermore, the machine learning algorithm includes algorithmic models developed using various development tools.

[0033] Furthermore, the development tools include, but are not limited to, TensorFlow, Scikit-Learn, and PyTorch. OpenNN, RapidMiner, Azure Machine Learning, Apache Mahout, Shogun, KNIME, Vertex AI, H2Oai, Anaconda, Keras, Tableau, Fast.ai, Catalyst, Amazon ML, MLJAR, Spell.

[0034] Furthermore, the algorithm models include, but are not limited to, linear regression models, logistic regression models, Lasso regression models, Ridge regression models, linear discriminant analysis models, nearest neighbor models, decision tree models, perceptron models, neural network models, support vector machine models, Naive Bayes models, AdaBoost models, GBDT models, XGBoost models, LightGBM models, CatBoost models, and random forest models.

[0035] A fourth aspect of the present invention provides a computer device and a computer-readable storage medium.

[0036] Furthermore, the computer device includes a memory and a processor.

[0037] Furthermore, the memory is used to store program instructions; the processor is used to invoke the program instructions, and when the program instructions are executed, to implement the method for evaluating the therapeutic effect of methylene blue on cancer as described in the first aspect of the present invention or the method for evaluating the therapeutic effect of methylene blue on liver fibrosis as described in the second aspect of the present invention.

[0038] Furthermore, the computer-readable storage medium stores a computer program that, when executed by a processor, implements the method for evaluating the therapeutic effect of methylene blue on cancer as described in the first aspect of the present invention or the method for evaluating the therapeutic effect of methylene blue on liver fibrosis as described in the second aspect of the present invention.

[0039] The advantages and beneficial effects of this invention are as follows: This invention is the first to discover that methylene blue treats pancreatic cancer, liver cancer, and liver fibrosis by regulating stress granules, and also finds a positive correlation between G3BP expression levels and the therapeutic effect of methylene blue on liver fibrosis. Based on this, this invention provides a method, system, and device for evaluating the therapeutic effect of methylene blue on pancreatic cancer and liver cancer, as well as a method, system, and device for evaluating the therapeutic effect of methylene blue on patients with liver fibrosis. This assists doctors in evaluating the treatment effects of pancreatic cancer, liver cancer, and liver fibrosis, and guides clinicians in developing individualized treatment plans for patients. Attached Figure Description

[0040] Figure 1 A flowchart of a method for evaluating the therapeutic effect of methylene blue on cancer provided by the present invention; Figure 2 The flowchart of the method for evaluating the therapeutic effect of methylene blue on liver fibrosis provided by the present invention; Figure 3 A schematic diagram of the system structure provided by this invention for evaluating the therapeutic effect of methylene blue on pancreatic cancer; Figure 4 A schematic diagram of the system structure provided by this invention for evaluating the therapeutic effect of methylene blue on liver cancer; Figure 5 A schematic diagram of the system structure provided by this invention for evaluating the therapeutic effect of methylene blue on liver fibrosis; Figure 6 A schematic diagram of the structure of the computer device provided by the present invention; Figure 7 The distribution of G3BP1-labeled stress granules in pancreatic cancer cells in different states is shown in Figure A. Figure A shows the distribution of stress granules in pancreatic cancer cells under normal conditions. Figure B shows the distribution of stress granules in pancreatic cancer cells after 1 hour of NaAsO2 stimulation. Figure C shows the distribution of stress granules in pancreatic cancer cells after 1 hour of co-treatment with methylene blue and NaAsO2. Figure 8 The distribution of G3BP1-labeled stress granules in pancreatic tissues of mice in different treatment groups is shown in Figure A. Figure B shows the distribution of stress granules in pancreatic tissues of WT mice under normal feeding conditions. Figure C shows the distribution of stress granules in pancreatic tissues of KC mouse models of pancreatic cancer under normal feeding conditions. Figure 9 The distribution of G3BP1-labeled stress granules in hepatocellular carcinoma cells in different states is shown in Figure A. Figure A shows the distribution of stress granules in hepatocellular carcinoma cells under normal conditions. Figure B shows the distribution of stress granules in hepatocellular carcinoma cells after 1 h of NaAsO2 stimulation. Figure C shows the distribution of stress granules in hepatocellular carcinoma cells after 1 h of co-treatment with methylene blue and NaAsO2. Figure 10 The distribution of G3BP1-labeled stress granules in the liver tissue of mice with liver fibrosis in different treatment groups is shown in Figure A. Figure B shows the distribution of stress granules in the liver tissue of WT mice under normal feeding conditions. Figure C shows the distribution of stress granules in the liver tissue of a mouse model with liver fibrosis under normal feeding conditions. Figure 11 Figure 1 shows the expression of G3BP protein in different samples treated with methylene blue. Figure A shows the expression of G3BP1 protein in two types of human pancreatic cancer cells after 1 hour of co-treatment with methylene blue and NaAsO2. Figure B shows the expression of G3BP1 protein in pancreatic tissue of pancreatic cancer KC mouse models under normal and methylene blue water feeding conditions. Figure C shows the expression of G3BP protein in liver tissue of liver fibrosis mouse models under normal and methylene blue water feeding conditions. Figure 12 The percentage of acinar cells in pancreatic tissue of pancreatic cancer KC mouse models fed with normal and methylene blue water. Figure 13 The effect of co-treatment with methylene blue and NaAsO2 for 1 h on the proliferation of liver cancer cells; Figure 14 The degree of fibrosis in liver tissue of mouse models of liver fibrosis fed with normal and methylene blue water; Figure 15 Sections of different tissues from WT mice fed with methylene blue water showed no drug toxicity. Detailed Implementation

[0041] To enable those skilled in the art to better understand the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0042] The present invention describes the operational flow in the specification, drawings, and claims, which includes multiple operational procedures. It should be clearly understood that these operational procedures may not be executed in the order they appear in this document or the drawings, or may be executed in parallel. The labels for the operational steps, such as 101, 102, 103, etc., are only used to distinguish different operations and do not represent any execution order. Furthermore, operations not indicated by the labels may also be added to the operational procedures of the present invention and may be executed sequentially or in parallel. Additionally, all operations mentioned herein may be omitted when necessary. It should be noted that the descriptions such as "first," "second," etc., mentioned in this invention are only used to distinguish different operations, devices, modules, messages, etc., and do not limit the order or specific type.

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] Figure 1 This is a schematic flowchart of a method for evaluating the therapeutic effect of methylene blue on cancer provided by the present invention. Specifically, the method includes: Data Acquisition: Acquire the expression data of stress particles in cancer patient samples after methylene blue treatment. The expression data of stress particles includes the percentage of stress particle quantity and the percentage of stress particle area. In some embodiments of the present invention, through extensive and in-depth research, it was found that after methylene blue treatment of pancreatic cancer cells, the expression level of stress granules in pancreatic cancer cells decreased. After methylene blue treatment of a mouse model of pancreatic cancer, the proportion of acinar cells in the pancreatic tissue of the mice increased, and the expression level of stress granules also decreased. This suggests that stress granules can serve as a good biomarker to evaluate the therapeutic effect of methylene blue on pancreatic cancer.

[0045] In some embodiments, the patient may be human or non-human and may include, for example, animal strains or species used as a “model system” for research purposes. Similarly, the patient may include adults or adolescents (e.g., children). Furthermore, the patient may refer to any living organism that can benefit from the methylene blue described herein, preferably mammals (e.g., humans or non-humans). Examples of mammals include, but are not limited to, any member of the mammalian class: humans, non-human primates (e.g., chimpanzees) and other apes and monkeys; livestock, such as cattle, horses, sheep, goats, pigs; domestic animals, such as rabbits, dogs, and cats; laboratory animals including rodents, such as rats, mice, and guinea pigs. Examples of non-mammals include, but are not limited to, birds, fish, etc.

[0046] In the context of this invention, the term "sample" as used refers to a composition obtained from or derived from a patient / subject that contains cells and / or other molecular entities to be characterized and / or identified based on, for example, physical, biochemical, chemical, and / or physiological characteristics. For example, a sample refers to any sample derived from a patient / subject that is expected or known to contain cells and / or molecular entities to be characterized. Samples include, but are not limited to, tissue samples, primary or cultured cells or cell lines, cell cultures, cell supernatants, cell lysates, platelets, serum, plasma, vitreous fluid, lymph, synovial fluid, follicular fluid, semen, pancreatic juice, amniotic fluid, milk, whole blood, blood-derived cells, urine, cerebrospinal fluid, saliva, sputum, tears, sweat, mucus, tissue culture fluid, tissue extracts, homogenized tissue, cell extracts, and combinations thereof.

[0047] In a specific embodiment of the present invention, the samples include the spontaneous pancreatic cancer classic model KC mouse and wild-type (WT) mice. The KC mice were obtained by mass mating of LSL-K-Ras G12D mice (conditionally overexpressing the KRAS G12D gene) and Pdx-Cre mice (pancreas-specific Cre expression mice), all purchased from Shanghai Nanmo Biotechnology Co., Ltd. The cells used were the human pancreatic cancer cell line PANC-1 and the human pancreatic cancer cell line Mia-PaCa2. The cells were placed in DMEM medium containing 10% fetal bovine serum and 1% penicillin / streptomycin and cultured in an incubator at 37°C and 5% CO2. When the cells reached approximately 80%-95% confluence, they were passaged. The specific procedure was as follows: cells were digested with 0.25% trypsin-EDTA solution at 37°C for 3 min, digestion was stopped by adding complete culture medium, and the cells were seeded into new culture dishes for further culture. Take 20 μL of the digested cell suspension, mix it with an equal volume of trypan blue, incubate for 3 minutes, and then count the cells. Seed 80,000 cells per well into a 24-well plate with a climbing slide.

[0048] In some specific embodiments of the present invention, methylene blue (MCE:HY-B1359) powder was dissolved in PBS to prepare a 50 mM methylene blue stock solution, which was then aliquoted and stored at -80 °C to avoid repeated freeze-thaw cycles. Different concentrations of methylene blue solution were selected to treat human pancreatic cancer cells. For example, 0 μM, 5 μM, 25 μM, 50 μM, 75 μM, and 100 μM concentrations were selected to detect G3BP1 protein expression levels; a 10 μM drug concentration was selected to detect stress granule inhibition. Different treatment times of 24 h, 48 h, and 72 h were selected. After cell viability testing, protein levels were detected after 24 h of treatment; stress granule inhibition was detected after 1 h of treatment. Sodium arsenite (NaAsO2) is a common oxidative stress drug. After treating pancreatic cancer cells with 1 mM NaAsO2 for 1 h, the cells were stressed and produced well-defined stress granules. Pancreatic cancer cells were seeded in 24-well plates with 80,000 cells per well that had been pre-filled with a climbing slide and cultured for 24 h to allow them to fully extend. The experiment was divided into three groups: PBS as the negative control group, NaAsO2 and PBS as the positive control group, and NaAsO2 and methylene blue added simultaneously as the experimental group. Methylene blue stock solution and sodium arsenite stock solution were prepared together in complete culture medium, with a final concentration of 10 μM for methylene blue and 1 mM for NaAsO2. After thorough mixing, 500 μL was added to each well and incubated at 37°C in a CO2 incubator for 1 h. The samples were then washed three times with PBS, fixed with 4% paraformaldehyde at room temperature for 15 min, washed three times with PBS, permeabilized on ice with 0.2% Triton X-100 for 10 min, washed three times with PBS, and blocked with 3% BSA at room temperature for 1 h. The G3BP1 antibody was diluted 1:200 with 3% BSA and incubated at room temperature for 2 h (or overnight at 4°C). The samples were washed three times with PBS, 10 min each time, and the corresponding species' fluorescent secondary antibody was diluted 1:200 with PBS and incubated at room temperature for 1 h. h; Hoechst dye was used to counterstain cell nuclei at room temperature for 30 min, followed by washing three times with PBS for 10 min each time; the slides were mounted with anti-quenching agent and prepared, and images were taken using a Zeiss LSM880 confocal microscope. (See attached image.) Figure 7 The results showed that methylene blue significantly inhibited stress granules in pancreatic cancer cells.

[0049] In a specific embodiment of this invention, wild-type (WT) mice and KC mice were each divided into two groups: WT and KC mice fed normally for 6 months served as the control group, and WT and KC mice fed methylene blue solution continuously for 5 months after 1 month of age served as the experimental group. Methylene blue powder was dissolved in ddH2O to prepare a 2 mg / mL methylene blue stock solution, which was aliquoted and stored at -80°C to avoid repeated freeze-thaw cycles. The methylene blue stock solution was diluted with drinking water for mice, and 1-month-old mice were fed methylene blue solution at a rate of 10 mg / kg, with the solution changed weekly for 5 consecutive months. Pancreatic tissue from WT and KC mice in the control and experimental groups, as well as liver, lung, spleen, and spleen tissue from WT mice in the control and experimental groups, were collected. The tissues were fixed overnight in 4% paraformaldehyde, embedded in paraffin, and cut into 3.5 μm tissue sections. The slides were heated at 60°C for 2 h, dewaxed with xylene, and rehydrated with gradient concentrations of alcohol. The sections were antigen-retrieved in a microwave oven with sodium citrate buffer for 5 min, and then cooled for 7 minutes. min, repeated 3 times; 3% H2O2 at room temperature to block tissue endogenous peroxidase for 1 h, wash 3 times with PBS, 5 min each time; 0.2% Triton X-100 permeabilization at 4℃ for 10 min, wash 3 times with PBS, 5 min each time; Tissue was blocked with 3% BSA at room temperature for 1 h; G3BP1 antibody was diluted 1:200 with blocking solution and incubated overnight at 4°C; the tissue was washed 3 times with PBS for 5 min each time, and the same species fluorescent secondary antibody was diluted 1:200 with PBS and incubated at room temperature for 1 h; the tissue was washed 3 times with PBS for 5 min each time, and the cell nuclei were counterstained with DAPI at room temperature for 10 min; the tissue was washed 5 times with PBS for 5 min each time, and mounted with anti-fluorescence quenching mounting solution; the slides were prepared and images were taken using a Leica SP5 laser confocal microscope.

[0050] In other embodiments of the present invention, H&E staining analysis was performed on pancreatic tissues from the experimental and control groups of KC mice. The specific steps were as follows: slides were baked overnight at 65°C, dewaxed with xylene, and rehydrated with graded ethanol; hematoxylin staining was performed at room temperature for 5 min; tissues were differentiated and lifted twice with 1% differentiation solution; eosin staining was performed for 20 s; the tissues were dehydrated with graded ethanol, cleared with xylene, and mounted with neutral resin; images were acquired using an Olympus tissue wave scanner; acinar cells and the total pancreatic area were manually plotted using Olympus OlyVIA 4.2 software; and the acinar cell percentage was statistically analyzed and plotted using Graphpad Pism 9.5 software. Figure 8 and Figure 12 As shown, these results collectively demonstrate that methylene blue has a therapeutic effect on pancreatic cancer and significantly inhibits stress granules in the pancreatic tissue of the KC mouse model.

[0051] In specific embodiments of this invention, a suitable human hepatocellular carcinoma cell line, HepG2, is selected. Subsequent culture conditions and immunofluorescence detection of stress granules follow the steps described above for pancreatic cancer cells. In other embodiments, CCK8 is used to detect the proliferation of hepatocellular carcinoma cells. The specific steps are as follows: treated hepatocellular carcinoma cells are digested, counted, and seeded in 96-well plates. The medium is changed at different time points with a CCK8 to complete medium ratio of 1:10. The plates are incubated for 1 hour, and the absorbance at 450 nm is detected using a microplate reader. Figure 9 and Figure 13 As shown, these results collectively demonstrate that methylene blue can significantly inhibit the proliferation of liver cancer cells and has a significant inhibitory effect on stress granules in liver cancer cells.

[0052] In some embodiments of the present invention, Western blotting was used to detect G3BP1 expression in pancreatic cancer cells and pancreatic tissue. The specific steps were as follows: Pancreatic cancer cells or pancreatic tissue cut into small pieces were lysed at 4°C using RIPA lysis buffer (1:100 with 100x cooktail protease inhibitor) via sonication; cell or tissue proteins were extracted by centrifugation at 20,000 rcf for 15 min at 4°C; the samples were prepared with 5x loading buffer and denatured at 95°C for 5 min; the protein samples were electrophoresed at 80 V for 30 min, then adjusted to 120 V for 90 min; the electrophoresed proteins were transferred to a PVDF membrane and transferred at 110 V for 100 min; the bands were incubated overnight at 4°C with G3BP1 antibody and internal control HSP90 antibody. Specific secondary antibody was incubated at room temperature for 1 h; the bands were then incubated with developing solution to detect G3BP1 protein expression. Figure 11 A and Figure 11 Results B showed that the expression of G3BP1 protein, a core component of stress granules, in pancreatic cancer cells and mouse pancreatic tissue was not affected by methylene blue.

[0053] Data processing: The expression data of the stress particles are input into the constructed efficacy evaluation model for methylene blue treatment of cancer. The efficacy evaluation model for methylene blue treatment of cancer is based on the expression data of the stress particles to determine the treatment effect of the cancer patients after receiving methylene blue treatment. In some embodiments of the present invention, the method for constructing the efficacy evaluation model after methylene blue treatment for cancer is known to those skilled in the art, and the steps of associating the expression level of stress particles with a certain probability or risk can be implemented and realized in different ways.

[0054] In the context of this invention, the term "machine learning" refers to the use of computers to simulate or implement human learning activities, and technicians typically use various development tools to build machine learning algorithmic models. These development tools include, but are not limited to, TensorFlow, Scikit-Learn, PyTorch, OpenNN, RapidMiner, Azure Machine Learning, Apache Mahout, Shogun, KNIME, Vertex AI, H2Oai, Anaconda, Keras, Tableau, Fast.ai, Catalyst, Amazon ML, MLJAR, and Spell. The algorithmic models include, but are not limited to, linear regression models, logistic regression models, Lasso regression models, Ridge regression models, linear discriminant analysis models, nearest neighbor models, decision tree models, perceptron models, neural network models, support vector machine models, Naive Bayes models, AdaBoost models, GBDT models, XGBoost models, LightGBM models, CatBoost models, or random forest models.

[0055] Output the prediction results.

[0056] Figure 2 This is a schematic flowchart of a method for evaluating the therapeutic effect of methylene blue on liver fibrosis provided by the present invention. Specifically, the method includes: Data Acquisition: Acquire the expression data of stress particles in liver fibrosis patient samples after methylene blue treatment. The expression data of stress particles includes the proportion of stress particle number, the proportion of stress particle area, the expression level of G3BP1, and the expression level of G3BP2. In a specific embodiment of the present invention, wild-type (WT) mice were divided into four groups: a normal feeding group and WT mice that were given methylene blue water starting at 8 weeks of age as the control group; and WT mice that were given normal drinking water starting at 8 weeks of age and those that were given methylene blue water starting at 8 weeks of age as the experimental group. Methylene blue powder was dissolved in ddH2O to prepare a 2 mg / mL methylene blue stock solution, which was dispensed and stored at -80 °C to avoid repeated freeze-thaw cycles. The methylene blue stock solution was diluted with drinking water for mice, and 8-week-old mice were fed methylene blue water at a rate of 40 mg / kg, with the solution changed twice a week. The model was established and the mice were fed water for 4 consecutive weeks. Liver tissue from modeled WT mice and heart, lung, spleen, and kidney tissue from non-modeled WT mice were collected. The subsequent immunofluorescence detection steps were the same as those for the pancreatic tissue described above.

[0057] In other embodiments of the present invention, Western blotting was used to detect G3BP expression in mouse liver tissue. The specific steps were the same as those described above for detecting G3BP1 expression in pancreatic tissue using Western blotting, except that the primary antibody used was G3BP1, G3BP2 antibody, and the internal control β-actin antibody, and the secondary antibody was a specific secondary antibody. In other embodiments, Sirius red was used to stain liver tissue sections of the experimental group and control group of CCl4 liver fibrosis mouse model. The specific steps were as follows: baking the slides overnight at 65°C, dewaxing with xylene, rehydrating with graded ethanol; soaking in Sirius red staining solution for 20 min; dehydrating with graded ethanol, clearing with xylene, and mounting with neutral resin; acquiring images using an Olympus tissue wave scanner, calculating the area ratio of red regions using ImageJ software, and plotting the data using Graphpad Pism 9.5 software. Figure 14 and Figure 15 Studies have shown that methylene blue can effectively alleviate the degree of liver fibrosis in mice, and this therapeutic effect has no drug toxicity. Figure 10 and Figure 11 As shown in Figure C, these results collectively demonstrate that methylene blue inhibits the formation of stress granules in liver fibrosis tissue and simultaneously suppresses the protein expression of G3BP.

[0058] Data processing: The expression data of the stress particles are input into the constructed efficacy evaluation model of methylene blue treatment for liver fibrosis. The efficacy evaluation model of methylene blue treatment for liver fibrosis is based on the expression data of the stress particles to judge the treatment effect of the liver fibrosis patients after receiving methylene blue treatment. In some embodiments of the present invention, the method of constructing the prediction model is known to those skilled in the art and can be implemented and realized in different ways to associate the number of stress particles, the area of ​​stress particles, the expression level of G3BP1, the expression level of G3BP2 with a certain probability or risk.

[0059] Output results.

[0060] Figure 3 This is a schematic diagram of the system structure provided by the present invention for evaluating the therapeutic effect of methylene blue on pancreatic cancer.

[0061] The system includes a data acquisition unit (101), a data analysis unit (102), and a result output unit (103), which are programmed or otherwise configured. Data acquisition unit: used to acquire the expression data of stress particles in pancreatic cancer patient samples after methylene blue treatment, the expression data of stress particles including the proportion of stress particle number and the proportion of stress particle area; Data analysis unit: used to classify and predict the efficacy evaluation model of methylene blue treatment for pancreatic cancer obtained by the data acquisition unit through the construction steps described in the first aspect of the present invention, and to obtain the classification result of whether methylene blue is effective in treating pancreatic cancer patients; Result output unit: Used to output the result to the receiving unit.

[0062] Figure 4 This is a schematic diagram of the system structure provided by the present invention for evaluating the therapeutic effect of methylene blue on liver cancer.

[0063] The system includes a data acquisition unit (201), a data analysis unit (202), and a result output unit (203), which are programmed or otherwise configured as follows: Data acquisition unit: used to acquire the expression data of stress particles in liver cancer patient samples after methylene blue treatment, the expression data of stress particles including the proportion of stress particle number and the proportion of stress particle area; Data analysis unit: used to classify and predict the efficacy evaluation model of methylene blue treatment for liver cancer obtained by the data acquisition unit through the construction steps described in the first aspect of the present invention, and to obtain the classification result of whether methylene blue is effective in treating liver cancer patients; Result output unit: Used to output the result to the receiving unit.

[0064] Figure 5 This is a schematic diagram of the system structure provided by the present invention for evaluating the therapeutic effect of methylene blue on liver fibrosis.

[0065] The system includes a data acquisition unit (301), a data analysis unit (302), and a result output unit (303), which are programmed or otherwise configured as follows: Data acquisition unit: used to acquire the expression data of stress particles in liver fibrosis patient samples after methylene blue treatment. The expression data of stress particles includes the proportion of stress particle number, the proportion of stress particle area, the expression level of G3BP1, and the expression level of G3BP2. Data analysis unit: used to classify and predict the efficacy evaluation model of methylene blue treatment for liver fibrosis obtained by the data acquisition unit through the construction steps described in the second aspect of the present invention, and to obtain the classification result of whether methylene blue is effective in treating patients with liver fibrosis; Result output unit: Used to output the result to the receiving unit.

[0066] The system may be a user's electronic device or a computer system remotely located relative to that electronic device.

[0067] Figure 6 A schematic diagram of the structure of the computer device provided by the present invention.

[0068] The computer device includes a processor and a memory coupled to the processor, the memory storing program instructions that, when executed by the processor, cause the processor to perform the method described above for predicting the efficacy of antithrombotic drugs in treating thrombosis.

[0069] The processor can also be called a CPU (Central Processing Unit). A processor may be an integrated circuit chip with signal processing capabilities. A processor can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor. Computer equipment can be a mobile electronic device.

[0070] It should be understood that the systems, apparatuses, and methods described in this invention can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the couplings or direct couplings or communication connections shown or discussed may be indirect couplings or communication connections through some interfaces, apparatuses, or modules, and may be electrical, mechanical, or other forms.

[0071] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0072] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0073] The above description of the embodiments is only for understanding the method and core ideas of the present invention. It should be noted that those skilled in the art can make various improvements and modifications to the present invention without departing from the principles of the invention, and these improvements and modifications will also fall within the protection scope of the claims of the present invention.

Claims

1. A method for evaluating the therapeutic effect of methylene blue on cancer, characterized in that, The method is performed by a computer and includes the following steps: Data Acquisition: Acquire the expression data of stress particles in cancer patient samples after methylene blue treatment. The expression data of stress particles includes the proportion of stress particle number and the proportion of stress particle area. The proportion of stress particle number is the ratio of the number of cells expressing stress particles to the total number of cells in the measurement area. The proportion of stress particle area is the ratio of the total area occupied by stress particles in the image to the total area of ​​the analyzed area. Data processing: The expression data of the stress particles are input into the constructed efficacy evaluation model for methylene blue treatment of cancer. The efficacy evaluation model for methylene blue treatment of cancer is based on the expression data of the stress particles to determine the treatment effect of the cancer patients after receiving methylene blue treatment. Output results.

2. The method according to claim 1, characterized in that, The cancers mentioned include pancreatic cancer and liver cancer.

3. The method according to claim 1, characterized in that, The steps for constructing the efficacy evaluation model for methylene blue treatment of cancer are as follows: The expression data of stress particles are obtained, including the proportion of stress particle quantity and the proportion of stress particle area; the expression data of stress particles comes from untreated cancer patients and cancer patients treated with methylene blue; the expression data of stress particles is input into a machine learning algorithm to construct an efficacy evaluation model for methylene blue treatment of cancer.

4. The method according to claim 1, characterized in that, The efficacy evaluation model for methylene blue treatment of cancer was obtained using the following criteria: When the value of any one or more of the stress particle quantity ratio and stress particle area ratio is lower than the threshold, a classification result is obtained that methylene blue is effective in treating cancer patients; when the value of the stress particle quantity ratio and stress particle area ratio is not lower than the threshold, a classification result is obtained that methylene blue is ineffective in treating cancer patients.

5. A method for evaluating the therapeutic effect of methylene blue on liver fibrosis, characterized in that, The method is performed by a computer and includes the following steps: Data Acquisition: Acquire the expression data of stress particles in liver fibrosis patient samples after methylene blue treatment. The expression data of stress particles includes the proportion of stress particle number, the proportion of stress particle area, the expression level of G3BP1 protein, and the expression level of G3BP2 protein. The proportion of stress particle number is the ratio of the number of cells with stress particle expression to the total number of cells in the measurement area. The proportion of stress particle area is the ratio of the total area occupied by stress particles in the image to the total area of ​​the analyzed area. Data processing: The expression data of the stress particles are input into the constructed efficacy evaluation model of methylene blue treatment for liver fibrosis. The efficacy evaluation model of methylene blue treatment for liver fibrosis is based on the expression data of the stress particles to judge the treatment effect of the liver fibrosis patients after receiving methylene blue treatment. Output results.

6. The method according to claim 5, characterized in that, The steps for constructing the efficacy evaluation model of methylene blue treatment for liver fibrosis are as follows: The expression data of stress particles were obtained, including the number of stress particles, the area of ​​stress particles, the expression level of G3BP1 protein, and the expression level of G3BP2 protein. The expression data of stress particles came from untreated liver fibrosis patients and liver fibrosis patients treated with methylene blue. The expression data of stress particles were input into a machine learning algorithm to construct an efficacy evaluation model for methylene blue treatment of liver fibrosis.

7. The method according to claim 5, characterized in that, The efficacy evaluation model for methylene blue treatment of liver fibrosis was obtained using the following criteria: When any one or more of the values ​​of the proportion of stress particle number, the proportion of stress particle area, the expression level of G3BP1 protein, and the expression level of G3BP2 protein are lower than the threshold, a classification result is obtained that methylene blue is effective in treating patients with liver fibrosis; when the values ​​of the proportion of stress particle number, the proportion of stress particle area, the expression level of G3BP1 protein, and the expression level of G3BP2 protein are all higher than the threshold, a classification result is obtained that methylene blue is ineffective in treating patients with liver fibrosis.

8. Any of the following systems: (1) A system for evaluating the therapeutic effect of methylene blue on pancreatic cancer, the system comprising: 101 Data Acquisition Unit: Used to acquire the expression data of stress particles in pancreatic cancer patient samples after methylene blue treatment. The expression data of stress particles includes the proportion of stress particle number and the proportion of stress particle area. The proportion of stress particle number is the ratio of the number of cells expressing stress particles to the total number of cells in the measurement area. The proportion of stress particle area is the ratio of the total area occupied by stress particles in the image to the total area of ​​the analyzed area. 102 Data Analysis Unit: Used to classify and predict the efficacy evaluation model of methylene blue treatment for pancreatic cancer obtained by the data acquisition unit through the construction steps described in claim 3, and obtain the classification result of whether methylene blue is effective in treating pancreatic cancer patients; 103 Result Output Unit: Used to output the result to the receiving unit; (2) A system for evaluating the therapeutic effect of methylene blue on liver cancer, the system comprising: 201 Data Acquisition Unit: Used to acquire the expression data of stress particles in liver cancer patient samples after methylene blue treatment. The expression data of stress particles includes the proportion of stress particle number and the proportion of stress particle area. The proportion of stress particle number is the ratio of the number of cells expressing stress particles to the total number of cells in the measurement area. The proportion of stress particle area is the ratio of the total area occupied by stress particles in the image to the total area of ​​the analyzed area. 202 Data Analysis Unit: Used to classify and predict the efficacy evaluation model of methylene blue treatment for liver cancer obtained by the data acquisition unit through the construction steps described in claim 3, and obtain the classification result of whether methylene blue is effective in treating liver cancer patients; 203 Result Output Unit: Used to output the result to the receiving unit; (3) A system for evaluating the therapeutic effect of methylene blue on liver fibrosis, the system comprising: 301 Data Acquisition Unit: Used to acquire the expression data of stress particles in liver fibrosis patient samples after methylene blue treatment. The expression data of stress particles includes the proportion of stress particle number, the proportion of stress particle area, the expression level of G3BP1 protein, and the expression level of G3BP2 protein. The proportion of stress particle number is the ratio of the number of cells with stress particle expression to the total number of cells in the measurement area. The proportion of stress particle area is the ratio of the total area occupied by stress particles in the image to the total area of ​​the analyzed area. 302 Data Analysis Unit: Used to classify and predict the efficacy evaluation model of methylene blue treatment for liver fibrosis obtained by the data acquisition unit through the construction steps described in claim 6, and obtain the classification result of whether methylene blue is effective in treating patients with liver fibrosis; 303 Result Output Unit: Used to output the result to the receiving unit.

9. The method according to claim 3 or claim 6, characterized in that, The machine learning algorithms include algorithm models developed using various development tools; The development tools include, but are not limited to, TensorFlow, Scikit-Learn, PyTorch, OpenNN, RapidMiner, Azure Machine Learning, Apache Mahout, Shogun, KNIME, Vertex AI, H2Oai, Anaconda, Keras, Tableau, Fast.ai, Catalyst, Amazon ML, MLJAR, and Spell. The algorithm models include, but are not limited to, linear regression models, logistic regression models, Lasso regression models, Ridge regression models, linear discriminant analysis models, nearest neighbor models, decision tree models, perceptron models, neural network models, support vector machine models, Naive Bayes models, AdaBoost models, GBDT models, XGBoost models, LightGBM models, CatBoost models, and random forest models.

10. A computer device and a computer-readable medium, characterized in that, The device includes: A memory and a processor, wherein the memory is used to store program instructions; the processor is used to invoke the program instructions, which, when executed, implement the method for evaluating the therapeutic effect of methylene blue on cancer as described in any one of claims 1-4 or the method for evaluating the therapeutic effect of methylene blue on liver fibrosis as described in any one of claims 5-7. The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method for evaluating the therapeutic effect of methylene blue on cancer as described in any one of claims 1-4, or the method for evaluating the therapeutic effect of methylene blue on liver fibrosis as described in any one of claims 5-7.

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