CN-121999883-A - Method, system and equipment for evaluating methylene blue treatment effect based on stress particles

CN121999883ACN 121999883 ACN121999883 ACN 121999883ACN-121999883-A

Abstract

The invention discloses a method, a system and equipment for evaluating methylene blue treatment effect based on stress particles. The invention discovers that the methylene blue treats pancreatic cancer, liver cancer and liver fibrosis by inhibiting the expression of the stress particles for the first time, and discovers that the expression of the G3BP protein which is a core component of the stress particles is positively correlated with the treatment effect of the methylene blue on the liver fibrosis. In addition, the invention provides a method, equipment and a system for evaluating the treatment effect of methylene blue on cancer and a method, equipment and a system for evaluating the treatment effect of methylene blue on liver fibrosis, so as to assist doctors in evaluating the treatment effect of pancreatic cancer patients, liver cancer patients and liver fibrosis patients and guide clinicians to formulate personalized treatment schemes for patients.

Inventors

GE WENJIE
XUE JING
ZHAO ZHONGJUN
ZHANG WENHUI
MA LIYE
ZHU YIFU

Assignees

徐州医科大学

Dates

Publication Date: 20260508
Application Date: 20260209

Claims (10)

1. A method of evaluating the effect of methylene blue on cancer treatment, said method being performed by a computer comprising the steps of: Obtaining expression data of stress particles in a cancer patient sample after methylene blue treatment, wherein the expression data of the stress particles comprise a stress particle number proportion and a stress particle area proportion, the stress particle number proportion is a proportion of the number of cells expressed by the stress particles relative to the total number of cells in a measurement area, and the stress particle area proportion is a proportion of the total area occupied by the stress particles in an image to the total area of an analyzed area; Inputting the expression data of the stress particles into a constructed therapeutic effect evaluation model of methylene blue after cancer treatment, wherein the therapeutic effect evaluation model of the methylene blue after cancer treatment judges the therapeutic effect of the cancer patient after methylene blue treatment based on the expression data of the stress particles; And outputting a result.
2. The method of claim 1, wherein the cancer comprises pancreatic cancer, liver cancer.
3. The method according to claim 1, wherein the step of constructing the efficacy evaluation model after cancer treatment with methylene blue comprises the steps of: The method comprises the steps of obtaining expression data of stress particles, wherein the expression data of the stress particles comprise a stress particle quantity ratio and a stress particle area ratio, the expression data of the stress particles are from untreated cancer patients and cancer patients treated by methylene blue, and inputting the expression data of the stress particles into a machine learning algorithm to construct a therapeutic effect evaluation model after the cancer is treated by the methylene blue.
4. The method of claim 1, wherein the efficacy assessment model after treatment of cancer with methylene blue is obtained by: When the value of any one or more of the stress particle number ratio and the stress particle area ratio is lower than a threshold value, obtaining a classification result of the methylene blue effective for treating the cancer patient; and when the number of the stress particles and the area of the stress particles are not lower than the threshold value, obtaining a classification result that methylene blue is ineffective for treating the cancer patient.
5. A method of evaluating the effect of methylene blue on liver fibrosis treatment, the method being performed by a computer and comprising the steps of: Obtaining expression data of stress particles in a liver fibrosis patient sample after methylene blue treatment, wherein the expression data of the stress particles comprise a stress particle number proportion, a stress particle area proportion, a G3BP1 protein expression level and a G3BP2 protein expression level, the stress particle number proportion is a proportion of the number of cells expressed by the stress particles relative to the total number of cells in a measurement area, and the stress particle area proportion is a proportion of the total area occupied by the stress particles in an image to the total area of an analyzed area; inputting the expression data of the stress particles into a constructed therapeutic effect evaluation model for treating liver fibrosis by methylene blue, wherein the therapeutic effect evaluation model for treating liver fibrosis by methylene blue judges the therapeutic effect of a patient with liver fibrosis after receiving methylene blue treatment based on the expression data of the stress particles; And outputting a result.
6. The method according to claim 5, wherein the construction of the therapeutic effect evaluation model after the treatment of liver fibrosis with methylene blue comprises the following steps: the method comprises the steps of obtaining expression data of stress particles, wherein the expression data of the stress particles comprise the number of the stress particles, the area of the stress particles, the expression level of G3BP1 protein and the expression level of G3BP2 protein, the expression data of the stress particles are from untreated liver fibrosis patients and liver fibrosis patients treated by methylene blue, and inputting the expression data of the stress particles into a machine learning algorithm to construct a curative effect evaluation model after the liver fibrosis is treated by the methylene blue.
7. The method of claim 5, wherein the efficacy assessment model after treatment of liver fibrosis with methylene blue is obtained by: When the value of any one or more of the stress particle number ratio, the stress particle area ratio, the G3BP1 protein expression level and the G3BP2 protein expression level is lower than a threshold value, obtaining a classification result of methylene blue effective for treating the hepatic fibrosis patient; and when the number of the stress particles, the area of the stress particles, the expression level of the G3BP1 protein and the expression level of the G3BP2 protein are not lower than a threshold value, obtaining a classification result that methylene blue is ineffective for treating the hepatic fibrosis patient.
8. A system of any one of the following: (1) A system for evaluating the effect of methylene blue on pancreatic cancer treatment, the system comprising: The 101 data acquisition unit is used for acquiring expression data of stress particles in a pancreatic cancer patient sample after methylene blue treatment, wherein the expression data of the stress particles comprise a stress particle number proportion and a stress particle area proportion, the stress particle number proportion is a proportion of the number of cells expressed by the stress particles relative to the total number of cells in a measurement area, and the stress particle area proportion is a proportion of the total area occupied by the stress particles in an image to the total area of an analyzed area; 102, a data analysis unit, which is used for carrying out classification prediction on the data obtained in the data acquisition unit through the treatment effect evaluation model of the methylene blue after treating pancreatic cancer obtained in the construction step of claim 3, so as to obtain a classification result of whether the methylene blue is effective for treating pancreatic cancer patients; 103 a result output unit for outputting the result to the receiving unit; (2) A system for evaluating the effect of methylene blue on liver cancer treatment, the system comprising: The 201 data acquisition unit is used for acquiring expression data of stress particles in a liver cancer patient sample after methylene blue treatment, wherein the expression data of the stress particles comprise a stress particle number proportion and a stress particle area proportion, the stress particle number proportion is a proportion of the number of cells expressed by the stress particles relative to the total number of cells in a measurement area, and the stress particle area proportion is a proportion of the total area occupied by the stress particles in an image to the total area of an analyzed area; 202 a data analysis unit for classifying and predicting the data obtained by the data acquisition unit through the treatment effect evaluation model of methylene blue after treating liver cancer obtained by the construction step of claim 3 to obtain a classification result of whether the methylene blue is effective for treating liver cancer patients; 203 a result output unit for outputting the result to the receiving unit; (3) A system for evaluating the effect of methylene blue on liver fibrosis treatment, the system comprising: The 301 data acquisition unit is used for acquiring the expression data of the stress particles in the liver fibrosis patient sample after methylene blue treatment, wherein the expression data of the stress particles comprise the number proportion of the stress particles, the area proportion of the stress particles, the expression level of the G3BP1 protein and the expression level of the G3BP2 protein, the number proportion of the stress particles is the proportion of the number of the cells expressed by the stress particles relative to the total number of the cells in the measurement area, and the area proportion of the stress particles is the proportion of the total area occupied by the stress particles in the image to the total area of the analyzed area; 302 a data analysis unit for classifying and predicting the data obtained by the data acquisition unit through the treatment effect evaluation model of the methylene blue after treating the hepatic fibrosis, which is obtained by the construction step of claim 6, so as to obtain a classification result of whether the methylene blue is effective for treating the hepatic fibrosis patient; 303 a result output unit for outputting the result to the receiving unit.
9. The method of claim 3 or claim 6, wherein the machine learning algorithm comprises an algorithm model developed with 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、Spell; The algorithm model includes, but is not limited to, a linear regression model, a logistic regression model, a Lasso regression model, a Ridge regression model, a linear discriminant analysis model, a neighbor model, a decision tree model, a perceptron model, a neural network model, a support vector machine model, a naive bayes model, an AdaBoost model, GBDT model, XGBoost model, lightGBM model, catBoost model, and a random forest model.
10. A computer device and computer readable medium, the device comprising: A memory for storing program instructions, and a processor for calling program instructions, which when executed, implement the method of assessing the effect of methylene blue on a cancer treatment of any one of claims 1-4 or the method of assessing the effect of methylene blue on a liver fibrosis treatment of any one of claims 5-7; the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the method of evaluating the effect of methylene blue on cancer treatment according to any one of claims 1 to 4 or the method of evaluating the effect of methylene blue on liver fibrosis treatment according to any one of claims 5 to 7.

Description

Method, system and equipment for evaluating methylene blue treatment effect based on stress particles Technical Field The invention belongs to the field of bioinformatics, and particularly relates to a method, a system and equipment for evaluating the treatment effect of methylene blue on cancers and a method, a system and equipment for evaluating the treatment effect of methylene blue on hepatic fibrosis. Background Pancreatic cancer is a highly invasive and fatal malignancy, with rising morbidity and mortality worldwide. Since early symptoms of pancreatic cancer are not obvious, most patients are in the late stage when diagnosis is confirmed, and the optimal operation treatment time is missed, searching for effective screening targets and treatment medicines is important for improving prognosis of pancreatic cancer patients. Liver cancer has become the fifth most common cancer worldwide and the third most cancer cause of death, and in recent years, the morbidity and mortality thereof have been continuously rising. Because of limited early detection and prevention means and certain limitations of the traditional operation treatment and radiotherapy and chemotherapy methods, the problems of public health and medical burden are still continuously aggravated, and therefore, further research on pathogenesis of the patients 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 of liver cancer, and more than about 90% of liver cancers develop from liver fibrosis. Methylene blue belongs to FDA approved drugs and is used for treating methemoglobin, cyanide poisoning, central nervous system diseases (ischemic cerebral apoplexy, alzheimer's disease, other neurodegenerative diseases and the like) and simultaneously has the treatment effect on colorectal tumors, melanoma and other cancers by utilizing methylene blue photodynamic therapy. However, there is no report on the effect of Guan Ya methyl blue on stress particles in pancreatic cancer, liver cancer and liver fibrosis. Therefore, accurate evaluation of the therapeutic effect of methylene blue on pancreatic cancer, liver cancer and hepatic fibrosis patients is very important in the treatment selection, operation design and efficacy evaluation of diseases. Disclosure of Invention In view of the above, it is an object of the present invention to provide a method, system and apparatus for evaluating the effect of methylene blue on cancer treatment and a method, system and apparatus for evaluating the effect of methylene blue on liver fibrosis treatment, in order to make up for the deficiencies of the prior art. In order to achieve the above purpose, the present invention adopts the following technical scheme: In a first aspect the present invention provides a method of evaluating the effect of methylene blue on cancer treatment, the method being performed by a computer and comprising the steps of: Obtaining expression data of stress particles in a cancer patient sample after methylene blue treatment, wherein the expression data of the stress particles comprise a stress particle number proportion and a stress particle area proportion, the stress particle number proportion is a proportion of the number of cells expressed by the stress particles relative to the total number of cells in a measurement area, and the stress particle area proportion is a proportion of the total area occupied by the stress particles in an image to the total area of an analyzed area; Inputting the expression data of the stress particles into a constructed therapeutic effect evaluation model of methylene blue after cancer treatment, wherein the therapeutic effect evaluation model of the methylene blue after cancer treatment judges the therapeutic effect of the cancer patient after methylene blue treatment based on the expression data of the stress particles; And outputting a result. Further, the cancers include pancreatic tumors and liver tumors. In a specific embodiment of the present invention, the pancreatic tumor is pancreatic cancer and the liver tumor is liver cancer. In the present invention, the term "pancreatic cancer" refers to malignant tumors occurring in pancreatic tissues, including pancreatic ductal adenocarcinoma derived from pancreatic ductal epithelium, adenocarcinoma derived from pancreatic acinar or glandular glands, and rare types of neuroendocrine cancer, etc., the term "liver cancer" refers to malignant tumors occurring in liver tissues, including hepatocellular carcinoma, intrahepatic cholangiocarcinoma, and mixed liver cancer, and the term "pancreatic tumor" refers to all neoplastic lesions occurring in pancreas, including benign tumors, borderline or atypical hyperplasia lesions, and malignant tumors. The term "liver tumor" refers to all neoplastic lesions that occur in liver tissue, including benign tumors, precancerous lesions, and malignant tumors. The term is u