CN-121980995-A - Blood flow velocity prediction method for breast pad in-situ tumor animal model

CN121980995ACN 121980995 ACN121980995 ACN 121980995ACN-121980995-A

Abstract

The invention belongs to the technical field of biomedicine, and provides a blood flow velocity prediction method for an in-situ tumor animal model of a breast pad, which aims at solving the problem that the existing blood flow velocity detection method for solid tumor of tumor is difficult to be widely applied to conventional researches, and blood flow velocity and tumor volume of in-situ tumor blood vessels are continuously acquired; and fitting the morphological characteristics of tumor tissues, the cytokine concentration and the blood flow velocity of tumor blood vessels to construct a blood flow velocity prediction model based on tumor volume and a blood flow velocity prediction model based on the plasma cytokine concentration. Through the constructed prediction model, researchers can conveniently obtain only tumor volume data or certain plasma cytokine concentration data, and the blood flow velocity of tumor blood vessels can be predicted through the obtained data without additional animal experiments for measurement, so that the method can be widely applied to conventional researches.

Inventors

YANG WENJING
YANG GUOWANG
ZHANG HONGKAI
You jiafeng
WU JUNFA
GUO XINRAN

Assignees

首都医科大学附属北京中医医院

Dates

Publication Date: 20260505
Application Date: 20260108

Claims (6)

1. A blood flow velocity prediction method for a breast pad in situ tumor animal model, comprising the steps of: Constructing a TNBC breast pad in-situ tumor animal model; respectively measuring the tumor volume, the blood flow velocity of in-situ tumor blood vessels and the plasma cytokine concentration of the constructed TNBC emulsion pad in-situ tumor animal model to obtain tumor volume data, blood flow velocity data of in-situ tumor blood vessels and plasma cytokine concentration data; Performing data regression curve fitting on the obtained blood flow velocity data of the in-situ tumor blood vessel and tumor volume data to obtain a blood flow velocity prediction model based on tumor volume; Performing data regression curve fitting on the obtained blood flow velocity data of the in-situ tumor blood vessel and the blood plasma cytokine concentration data to obtain a blood flow velocity prediction model based on the blood plasma cytokine concentration; And inputting the tumor volume data and/or the blood plasma cytokine concentration data of the obtained breast pad in-situ tumor animal model into a blood flow velocity prediction model based on the tumor volume and/or a blood flow velocity prediction model based on the blood plasma cytokine concentration to obtain a blood flow velocity prediction result.
2. The method for predicting blood flow velocity of an in situ tumor breast pad animal model according to claim 1, wherein the TNBC in situ tumor breast pad animal model is constructed by: Exposing the 4 th breast pad on the right side of the experimental animal, so as to facilitate the subsequent breast pad inoculation; fixing and sterilizing the experimental animal, then supporting the 4 th pair of breast pads on the right side, injecting the fully mixed cell suspension into the breast pads, observing the central depression of the breast pads and the color of the surrounding skin to become white, and prompting success of inoculation to obtain the TNBC breast pad in-situ tumor animal model.
3. The method for predicting blood flow velocity in an animal model of breast pad in situ tumor according to claim 2, wherein the cell suspension is 4T1 cell suspension and the injection amount of the cell suspension is 100ul.
4. The method of claim 1, wherein the plasma cytokines comprise vascular endothelial growth factor a, basic fibroblast growth factor, thrombin-sensitive protein 1 and platelet factor 4.
5. The method for predicting blood flow velocity of an animal model for breast pad in situ tumor according to claim 1, wherein the expression of the model for predicting blood flow velocity based on tumor volume is: V Blood flow velocity =0.180×lnV Tumor volume +0.252 Wherein V Blood flow velocity is the blood flow velocity of the in situ tumor vessel and V Tumor volume is the tumor volume.
6. The method for predicting blood flow velocity in an animal model for breast pad in situ tumor according to claim 1, wherein the expression of the blood flow velocity prediction model based on plasma cytokine concentration is: V Blood flow velocity =-0.012×C VEGFA +1.586,R 2 =0.969 lnV Blood flow velocity =0.997×C bFGF +1.640,R 2 =0.866 V Blood flow velocity =0.125×lnC TSP-1 +1.035,R 2 =0.990 lnV Blood flow velocity =1.083×C PF4 +1.161,R 2 =0.777 Wherein V Blood flow velocity is the blood flow velocity of the tumor vessel in situ, C VEGFA is the vascular endothelial growth factor a concentration, C bFGF is the basic fibroblast growth factor concentration, C TSP-1 is the thrombin-sensitive protein 1 concentration, and C PF4 is the platelet factor 4 concentration.

Description

Blood flow velocity prediction method for breast pad in-situ tumor animal model Technical Field The invention belongs to the technical field of biomedicine, and particularly relates to a blood flow velocity prediction method for a breast pad in-situ tumor animal model. Background Abnormal vascular network of solid tumor and hemodynamic abnormality induced by the same are one of key factors affecting tumor growth, metastasis and therapeutic effect of drugs. Tumor vessels exhibit significant differences in both structure and function. In terms of structure, endothelial cells of tumor blood vessels are arranged in disorder, the number of smooth muscle cells is obviously reduced or even completely lost, the basal membrane of the blood vessels is incomplete, the blood vessel wall is relatively thin, the mechanical strength and elasticity of the blood vessel wall are obviously reduced, and the support structure of the normal blood vessel wall is lacked. These vessels often exhibit morphological distortion, multiple branches, varying diameters, non-smooth anastomotic sites, lack of innervation, and exhibit a high degree of irregularity and complexity. Functionally, blood flow velocity and direction become unstable due to structural disturbance of blood vessels and lack of regulatory mechanisms, and the blood vessel perfusion amount is low, resulting in formation of anoxic microenvironment in tumor tissues. The anoxic state stimulates tumor cells to secrete angiogenesis promoting factors to promote the formation of new blood vessels and continuously invade surrounding tissues, and reduces the delivery efficiency of medicines on the other hand, so that the medicine resistance of tumors is easily induced. In addition, the tumor blood vessel wall is thinner and has incomplete structure, which provides favorable conditions for tumor cells to penetrate the blood vessel wall, so that the tumor cells can realize remote metastasis through blood circulation, thereby promoting the progress of the tumor. At present, the main method for detecting tumor vascular abnormalities comprises an invasive detection technology for acquiring fluorescence expression intensity in tumor tissues by injecting fluorescent microspheres, wherein the method needs to carry out slice staining after animal model sacrifice, cannot realize continuous monitoring and violates the 3R principle in animal rendition, adopts a traditional imaging technology to detect the axial average blood flow velocity of larger blood vessels in situ tumor, is noninvasive but needs multiple anesthesia in the operation process to influence the life quality of experimental animals, and adopts a high-resolution optical imaging technology to directly observe the flow velocity of red blood cells in a living animal tumor window model, so that the technology is complex, equipment is expensive, and is difficult to be widely applied to conventional researches. Therefore, a technical scheme for predicting the blood flow velocity in a tumor based on the traditional image detection result and combining with a conventional research method is needed to optimize the drug administration strategy in basic research. Disclosure of Invention The invention aims to overcome the defects of the prior art and provides a blood flow velocity prediction method for an in-situ tumor animal model of a breast pad. The invention utilizes the small animal ultrasonic technology to measure the blood flow velocity of in-situ tumor blood vessels, combines the morphological characteristics of tumor tissues, the concentration of cytokines and other multidimensional data, and provides a simple and convenient tumor solid tumor blood flow velocity prediction method which is suitable for the conventional laboratory conditions from multiple angles. The method not only can provide quantitative data support for optimizing the drug delivery scheme in basic research and tumor blood flow dynamics, but also can effectively make up for the defects of the prior detection technology in the aspects of continuity monitoring, operation economy and practicality, and provides powerful technical support for deep research of tumor blood vessel biology and development of novel treatment strategies. In order to achieve the above purpose, the invention adopts the following technical scheme: A blood flow velocity prediction method for a breast pad in situ tumor animal model, comprising the steps of: Constructing a TNBC breast pad in-situ tumor animal model; respectively measuring the tumor volume, the blood flow velocity of in-situ tumor blood vessels and the plasma cytokine concentration of the constructed TNBC emulsion pad in-situ tumor animal model to obtain tumor volume data, blood flow velocity data of in-situ tumor blood vessels and plasma cytokine concentration data; Performing data regression curve fitting on the obtained blood flow velocity data of the in-situ tumor blood vessel and tumor volume data to obtain a blood flow velo