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

Abstract

The invention belongs to the technical field of biomedicine, and provides a breast pad in-situ tumor animal model blood flow velocity prediction method for solving the problem that an existing solid tumor blood flow velocity detection method is difficult to be widely applied to conventional research, and the method comprises the steps that the blood flow velocity and the tumor volume of in-situ tumor blood vessels are continuously collected; analyzing the animal plasma sample to obtain the plasma cell factor concentration related to the blood vessel function; and fitting the morphological characteristics of the tumor tissue, the cell factor concentration and the blood flow velocity of the tumor blood vessel to construct a blood flow velocity prediction model based on the tumor volume and a blood flow velocity prediction model based on the plasma cell factor concentration. Through the constructed prediction model, a researcher can conveniently predict the blood flow velocity of the tumor blood vessel through the obtained data only by obtaining tumor volume data or concentration data of a certain plasma cell factor, additional animal experiments are not needed for measurement, and the method can be widely applied to conventional research.

Description

Technical Field

[0001] This invention belongs to the field of biomedical technology, specifically relating to a method for predicting blood flow velocity in an animal model of in situ breast pad tumors. Background Technology

[0002] Abnormal vascular networks in solid tumors and the resulting hemodynamic abnormalities are key factors influencing tumor growth, metastasis, and the effectiveness of drug treatment. Tumor vessels exhibit significant differences in both structure and function. Structurally, tumor vessels show disordered endothelial cell arrangement, a significantly reduced or even absent number of smooth muscle cells, an incomplete basement membrane, and relatively thin vessel walls, resulting in significantly reduced mechanical strength and elasticity, and a lack of the supporting structures found in normal vessel walls. These vessels typically exhibit distorted shapes, numerous branches, varying diameters, uneven anastomoses, and a lack of nerve innervation, demonstrating high irregularity and complexity. Functionally, due to the structural disorder and lack of regulatory mechanisms, blood flow velocity and direction become unstable, resulting in low vascular perfusion and the formation of a hypoxic microenvironment within the tumor tissue. This hypoxic state stimulates tumor cells to secrete pro-angiogenic factors, promoting angiogenesis and continuous invasion of surrounding tissues; it also reduces drug delivery efficiency, easily leading to tumor drug resistance.

[0003] Furthermore, the thin walls and incomplete structure of tumor blood vessels provide favorable conditions for tumor cells to penetrate the vessel walls, enabling them to metastasize to distant sites via the bloodstream and thus promoting tumor progression. Currently, the main methods for detecting abnormal tumor vasculature include: invasive detection techniques using injected fluorescent microspheres to obtain fluorescence intensity within tumor tissue; however, this method requires post-mortem staining of animal sections, making continuous monitoring impossible and violating the 3R principle of animal ethics; traditional imaging techniques for detecting the axial mean blood flow velocity of larger vessels within in situ tumors, which, although non-invasive, requires multiple anesthesias, impacting the survival quality of experimental animals; and high-resolution optical imaging techniques for directly observing the flow velocity of red blood cells in live animal tumor window models. This technique is complex, the equipment is expensive, and it is difficult to widely apply in routine research. Therefore, there is an urgent need for a technical solution that predicts intratumoral blood flow velocity based on traditional imaging results combined with conventional research methods to optimize drug delivery strategies in basic research. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for predicting blood flow velocity in an animal model of in situ breast pad tumors.

[0005] This invention utilizes small animal ultrasound technology to measure blood flow velocity in in situ tumor vessels. Combined with multi-dimensional data such as tumor tissue morphology and cytokine concentration, it provides a simple and practical method for predicting blood flow velocity in solid tumors under standard laboratory conditions. This method not only provides quantitative data support for optimizing drug delivery protocols in basic research but also effectively overcomes the shortcomings of existing detection technologies in continuous monitoring, operational economy, and practicality. It provides strong technical support for in-depth research in tumor vascular biology and the development of novel treatment strategies.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for predicting blood flow velocity in an animal model of in situ breast pad tumors includes the following steps: Constructing an animal model of TNBC in situ breast pad tumor; The tumor volume, blood flow velocity of the in situ tumor vessels, and plasma cytokine concentration of the constructed TNBC breast pad in situ tumor animal model were measured to obtain tumor volume data, blood flow velocity data of the in situ tumor vessels, and plasma cytokine concentration data. The blood flow velocity data of the in situ tumor vessels were fitted with the tumor volume data to obtain a blood flow velocity prediction model based on tumor volume. The blood flow velocity data of the in situ tumor vessels were fitted with the plasma cytokine concentration data to obtain a blood flow velocity prediction model based on plasma cytokine concentration. The tumor volume data and / or plasma cytokine concentration data of the animal model of the breast pad in situ tumor to be predicted are input into the blood flow velocity prediction model based on tumor volume and / or the blood flow velocity prediction model based on plasma cytokine concentration to obtain the blood flow velocity prediction results.

[0007] Preferably, the TNBC breast pad in situ tumor animal model is constructed using the following method: The fourth pair of mammary pads on the right side of the experimental animal were exposed to facilitate subsequent mammary pad inoculation; The experimental animals were fixed and the breast pads were disinfected. Then, the fourth pair of breast pads on the right side was lifted, and the well-mixed cell suspension was injected into the breast pad. The observation showed that the center of the breast pad was depressed and the surrounding skin turned white, indicating that the inoculation was successful and a TNBC breast pad in situ tumor animal model was obtained.

[0008] Preferably, the cell suspension is a 4T1 cell suspension, and the injection volume of the cell suspension is 100 μL.

[0009] Preferably, plasma cytokines include vascular endothelial growth factor A (VEGFA), basic fibroblast growth factor (bFGF), thrombin-sensitive protein 1 (TSP-1), and platelet factor 4 (PF4).

[0010] The preferred expression for the blood flow velocity prediction model based on tumor volume is: V 血流速度 =0.180×lnV 肿瘤体积 +0.252 Among them, V 血流速度 V represents the blood flow velocity in the in situ tumor vessels. 肿瘤体积 This represents the tumor volume.

[0011] Preferably, the expression for the blood flow velocity prediction model based on plasma cytokine concentration is: V 血流速度 =-0.012×C VEGFA +1.586, R 2 =0.969 lnV 血流速度 =0.997×C bFGF +1.640, R 2 =0.866 V 血流速度 =0.125×lnC TSP-1 +1.035, R 2 =0.990 lnV 血流速度 =1.083×C PF4 +1.161, R 2 =0.777 Among them, V 血流速度 C represents the blood flow velocity in the in situ tumor vessels. VEGFA The concentration of vascular endothelial growth factor A, C bFGF The concentration of basic fibroblast growth factor, C TSP-1 The concentration of thrombin-sensitive protein 1, C PF4 This refers to the concentration of platelet factor 4.

[0012] Compared with the prior art, the advantages of this invention are as follows: This invention continuously collects blood flow velocity and tumor volume from in situ tumor vessels; and obtains plasma cytokine concentrations related to vascular function by analyzing animal plasma samples. By fitting tumor tissue morphology and cytokine concentrations with tumor vessel blood flow velocity from multiple perspectives, two blood flow velocity prediction models are constructed: one based on tumor volume and the other based on plasma cytokine concentration. These prediction models allow researchers to easily predict blood flow velocity in patients with solid tumors using only tumor volume data or a single plasma cytokine concentration data, without requiring additional animal experiments. Therefore, this invention can be widely applied in routine research, providing strong technical support for in-depth research in tumor vascular biology and the development of novel treatment strategies. Attached Figure Description

[0013] Figure 1 The blood flow velocity versus tumor volume fitting curve of in situ tumor vessels provided by the present invention; Figure 2 The fitting curve of blood flow velocity in in situ tumor vessels and concentration of plasma cytokine VEGFA provided by the present invention; Figure 3 The fitting curve of blood flow velocity in in situ tumor vessels and concentration of plasma cytokine bFGF provided by the present invention; Figure 4 The fitting curve of blood flow velocity in in situ tumor vessels and concentration of plasma cytokine TSP-1 provided by the present invention; Figure 5 The fitting curve of blood flow velocity in in situ tumor vessels and plasma cytokine PF4 concentration provided by the present invention. Detailed Implementation

[0014] The following will be described in conjunction with embodiments of the present invention. Figures 1 to 5 The technical solutions in the embodiments of the present invention are clearly and completely described herein. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention. Example 1

[0015] 1. Construction of an animal model of TNBC (tissue-needle-cell-sized breast pad tumor) in situ 1.1 Animal Preparation SPF-grade Balb / c mice, 6 weeks old, female, weighing 17 - 18 g, were purchased from Spebefu (Beijing) Biotechnology Co., Ltd. The mice were introduced and housed in the SPF-grade animal room of the Beijing Institute of Traditional Chinese Medicine [SYXK(Beijing) 2021 - 0048] 3 days before inoculation to adapt to the feeding environment in advance. They were weighed one day before inoculation, the skin of the right 4th pair of mammary pads of the mice was prepared by shaving, and ear tags were used for marking, with 5 mice in each group.

[0016] 1.2. Preparation of materials Put insulin syringes, ophthalmic forceps, 75% alcohol degreasing cotton balls, 200 μl sterilized gun tips, 200 μl pipettes, electronic vernier calipers, A4 blank papers, marker pens, medical tapes, table lamps, respiratory anesthesia machines, and isoflurane in the transfer window inside the animal room barrier. After ultraviolet irradiation for 30 min, they can be brought into the barrier environment.

[0017] 1.3. Preparation of cells After the 4T1 cells were recovered, cultured, digested, and passaged according to the standard, the amount of cells required for inoculation was initially calculated based on the inoculation amount of 1×10 6 / 100 μl / per mouse, and cells were prepared at 1.5 times the amount of cells required for inoculation. When the cell amount met the inoculation requirement, the 4T1 cells in the logarithmic growth phase were digested, the supernatant was discarded, the cell pellet was resuspended with PBS, and pipetted until a uniform single-cell suspension was obtained. Trypan blue staining was used to determine that the cell viability > 95%, and cell counting was performed to adjust the cell concentration to 1×10 7 / ml. The cell suspension was aliquoted at 1 ml / tube, and then the centrifuge tubes were inserted into crushed ice and placed in the transfer window inside the animal room barrier. After ultraviolet irradiation for 30 min, they can be brought into the barrier environment.

[0018] 1.4. Mammary pad inoculation By adjusting the oxygen and isoflurane intake of the anesthesia machine to control the anesthesia depth (isoflurane content was 2% - 3%), after the mice were induced to anesthesia in the anesthesia box, they were placed supine, and their four limbs were fixed to the operating table with medical tape, and mask inhalation anesthesia was used to maintain the anesthesia depth. The right 4th pair of mammary pads of the mice were selected as the injection target site, and the mammary pads were disinfected with 75% alcohol cotton balls. The cell suspension was gently pipetted with a 200 μl pipette until it was fully mixed. 100 μl of the cell suspension was aspirated with an insulin syringe, and the air bubbles in the syringe were exhausted to ensure that the volume of the cell suspension in the syringe was 100 μl. With the left hand, hold the right mammary pad of the 4th pair of mammary pads of the mouse gently and steadily with ophthalmic forceps, and with the right hand, hold the insulin syringe and insert the needle horizontally. When the tip of the needle reaches the nipple, inject 100 μl of the cell suspension smoothly and evenly into the mammary pad. Observing that the center of the mammary pad is sunken and the surrounding skin color turns white indicates successful inoculation. The insulin syringe was withdrawn smoothly, and a sterilized cotton ball was used to gently press the injection site to prevent leakage, obtaining a TNBC mammary pad orthotopic tumor animal model.

[0019] 2. Measurement of breast pad tumor volume Starting from the 5th day after inoculation of the breast pad in situ tumor, the length (mm) and width (mm) of the tumor in situ were measured every 2 days using vernier calipers. The tumor volume was then calculated using the formula (mm). 3 = Length × Width 2 ×0.5, calculate the in situ tumor volume of the breast pad for each mouse at different time points after inoculation.

[0020] 3. Ultrasound examination of blood supply within mammary pad tumor tissue in small animals 3.1. Efluphenazine gas anesthesia The depth of anesthesia (isoflurane content 2%–3%) was controlled by adjusting the oxygen and isoflurane intake of the anesthesia machine. After induction anesthesia in the anesthesia box, the mice were placed in a supine position, their limbs were fixed to the testing table with medical tape, and inhalation anesthesia was maintained using a face mask. The mice's vital signs were observed after anesthesia, and testing was only performed after the anesthesia was stable.

[0021] 3.2 Ultrasonic testing After the mice were properly anesthetized, they were placed supine on the testing platform, and their limbs were secured with medical tape. Coupling agent was applied to the surface of the in-situ tumor in the mouse's breast pad, and the probe height was adjusted to contact the coupling agent surface before starting the test. Directional blood flow was detected within the in-situ tumor in Doppler mode; red indicates blood flow signals facing the probe, and blue indicates blood flow signals away from the probe. Blood flow velocity in the main blood vessels supplying the tumor was detected in pulsed Doppler mode; the peak height was directly proportional to the blood flow velocity, thus obtaining the blood flow velocity of the in-situ tumor vessels. After the ultrasound examination, the mice's vital signs were observed, and observation was terminated only after the anesthetic drugs had metabolized and the mice's activity returned to normal.

[0022] 4. ELISA detection of mouse plasma cytokine (VEGFA, bFGF, TSP-1, PF4) concentrations 4.1 Blood collection from the retroorbital venous plexus of mice The researcher stabilized the mouse with their left hand, pinching the skin of the mouse's head as tightly as possible with their thumb and forefinger to cause the eyeballs to protrude and the retro-orbital venous plexus to become congested. Holding a capillary blood collection tube in their right hand, the researcher inserted it at a 45° angle from the inner corner of the mouse's eye, rotating it downwards until it penetrated the retro-orbital venous plexus. The tube was then withdrawn outwards while aspirating. Once 0.2 ml of blood had been collected, the pressure on the mouse's neck was released, and the capillary blood collection tube was withdrawn to prevent bleeding from the puncture site. The mouse's survival status was observed, and the observation was terminated only after the mouse's activity returned to normal. Blood collection could be repeated within a short period. The blood was collected into a 3.8% sodium citrate anticoagulant tube, gently inverted to mix, ensuring adequate anticoagulation, and allowed to stand at room temperature for 30 minutes.

[0023] 4.2 Whole blood centrifugation After the whole blood was allowed to stand at room temperature for 30 minutes, it was centrifuged at 1000g for 15 minutes at 4°C. The supernatant plasma was then transferred to a new centrifuge tube and aliquoted into 0.2ml centrifuge tubes at 50ul each. The tubes were then frozen at -80°C for use in ELISA testing.

[0024] 4.3. Sample and related solution dilution Incubate the mouse plasma samples and ELISA kit at room temperature for 30 min. Dilute the plasma samples and reagents according to the ELISA instruction manual.

[0025] Plasma sample dilution: Dilute at a ratio of plasma sample to sample diluent of 1:1.2. Mouse plasma cytokine standards should be prepared according to the instructions, ensuring thorough mixing at each concentration gradient during dilution. Biotin-labeled anti-mouse (VEGFA, bFGF, TSP-1, PF4) antibody working solution preparation: Prepare the working solution at a ratio of biotin-labeled anti-mouse (100X) to antibody diluent of 1:99. Avidin-peroxidase complex (ABC) working solution preparation: Prepare the working solution at a ratio of avidin-peroxidase complex (ABC) to ABC diluent of 1:99. Wash buffer dilution: Pipette 2 ml of concentrated wash buffer into 48 ml of ultrapure water, mix thoroughly, and prepare the wash buffer working solution.

[0026] 4.4 ELISA reaction Following the pre-designed plate arrangement, add 100 μL of standard, control, and sample sequentially, setting up one replicate well. Cover the plate with sealing film and incubate at 37°C for 90 min. After the reaction, discard the liquid from the plate without washing. Add 100 μL of biotin-anti-mouse antibody working solution to each well, cover the plate with sealing film, and incubate at 37°C for 60 min. After the reaction, discard the liquid from the plate and wash each well three times with 200 μL of 1X wash buffer, soaking for 1 min each time. After washing, add 100 μL of ABC working solution to each well, cover the plate with sealing film, and incubate at 37°C for 30 min. After the reaction, discard the liquid from the plate and add 200 μL of 1X wash buffer to each well. Wash 5 times with 1X washing buffer, soaking for 1 min each time; after washing, add 90 μL of TMB chromogenic solution that has been equilibrated at 37°C for 30 min to each well, and react at 37°C in the dark for 15 min; after the reaction, add 100 μL of stop solution to each well, and measure the absorbance at 450 nm using an ELISA reader. Calculate the expression levels of angiogenic factors (VEGFA, bFGF, TSP-1, PF4) in each mouse plasma sample based on the absorbance values ​​of the standards. Example 2

[0027] 1. Data Fitting and Mathematical Model Construction 1.1 Fitting of blood flow velocity in in situ tumor vessels to tumor volume like Figure 1 As shown, the blood flow velocity and tumor volume data of in situ tumor vessels obtained in the experiment were imported into SPSS 27.0 for data regression curve fitting, and the blood flow velocity prediction model based on tumor volume was obtained as follows: V 血流速度 =0.180×lnV 肿瘤体积 +0.252, R 2 =0.511 Among them, V 血流速度 V represents the blood flow velocity in the in situ tumor vessels. 肿瘤体积 This represents the tumor volume.

[0028] 1.2 Fitting of blood flow velocity in in situ tumor vessels with plasma cytokine (VEGFA, bFGF, TSP-1, PF4) expression levels like Figures 2 to 5 As shown, the blood flow velocity and plasma cytokine (VEGFA, bFGF, TSP-1, PF4) concentration data of the in situ tumor vessels obtained in the experiment were imported into SPSS 27.0 for data regression curve fitting, and the blood flow velocity prediction model based on plasma cytokine concentration was obtained as follows: V 血流速度 =-0.012×C VEGFA +1.586, R 2 =0.969; lnV 血流速度 =0.997×C bFGF +1.640, R 2 =0.866; V 血流速度 =0.125×lnC TSP-1 +1.035, R 2 =0.990; lnV 血流速度 =1.083×C PF4 +1.161, R 2 =0.777.

[0029] Among them, V 血流速度 C represents the blood flow velocity in the in situ tumor vessels. VEGFA The concentration of vascular endothelial growth factor A, C bFGF The concentration of basic fibroblast growth factor, C TSP-1 The concentration of thrombin-sensitive protein 1, C PF4 This refers to the concentration of platelet factor 4.

[0030] The tumor volume data and / or plasma cytokine concentration data of the animal model of the breast pad in situ tumor to be predicted are input into the blood flow velocity prediction model based on tumor volume and / or the blood flow velocity prediction model based on plasma cytokine concentration to obtain the blood flow velocity prediction results.

[0031] This invention continuously collects blood flow velocity and tumor volume from in situ tumor vessels; analyzes animal plasma samples to obtain plasma cytokine concentrations related to vascular function; and fits tumor tissue morphology, cytokine concentration, and blood flow velocity from multiple perspectives with tumor vessel blood flow velocity to construct blood flow velocity prediction models based on tumor volume and plasma cytokine concentration. The constructed prediction models allow researchers to easily predict blood flow velocity in the vessels of patients with solid tumors using only tumor volume data or a single plasma cytokine concentration data, without requiring additional animal experiments. Therefore, this invention can be widely applied in routine research, providing strong technical support for in-depth research in tumor vascular biology and the development of novel treatment strategies.

[0032] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for predicting blood flow velocity in an animal model of in situ breast pad tumors, characterized in that, Includes the following steps: Constructing an animal model of TNBC in situ breast pad tumor; The tumor volume, blood flow velocity of the in situ tumor vessels, and plasma cytokine concentration of the constructed TNBC breast pad in situ tumor animal model were measured to obtain tumor volume data, blood flow velocity data of the in situ tumor vessels, and plasma cytokine concentration data. The blood flow velocity data of the in situ tumor vessels were fitted with the tumor volume data to obtain a blood flow velocity prediction model based on tumor volume. The blood flow velocity data of the in situ tumor vessels were fitted with the plasma cytokine concentration data to obtain a blood flow velocity prediction model based on plasma cytokine concentration. The tumor volume data and / or plasma cytokine concentration data of the obtained animal model of breast pad in situ tumor are input into the blood flow velocity prediction model based on tumor volume and / or the blood flow velocity prediction model based on plasma cytokine concentration to obtain the blood flow velocity prediction results.

2. The method for predicting blood flow velocity in an animal model of in situ breast pad tumors according to claim 1, characterized in that, The TNBC (tuberculous endothelial neoplasm) animal model was constructed using the following methods: The fourth pair of mammary pads on the right side of the experimental animal were exposed to facilitate subsequent mammary pad inoculation; The experimental animals were fixed and the breast pads were disinfected. Then, the fourth pair of breast pads on the right side was lifted, and the well-mixed cell suspension was injected into the breast pad. The observation showed that the center of the breast pad was depressed and the surrounding skin turned white, indicating that the inoculation was successful and a TNBC breast pad in situ tumor animal model was obtained.

3. The method for predicting blood flow velocity in an animal model of in situ breast pad tumors according to claim 2, characterized in that, The cell suspension was a 4T1 cell suspension, and the injection volume of the cell suspension was 100 μL.

4. The method for predicting blood flow velocity in an animal model of in situ breast pad tumors according to claim 1, characterized in that, Plasma cytokines include 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 in an animal model of in situ breast pad tumors according to claim 1, characterized in that, The expression for the blood flow velocity prediction model based on tumor volume is: In 血流速度 =0.180×lnV 肿瘤体积 +0.252 Among them, V 血流速度 V represents the blood flow velocity in the in situ tumor vessels. 肿瘤体积 This represents the tumor volume.

6. The method for predicting blood flow velocity in an animal model of in situ breast pad tumors according to claim 1, characterized in that, The expression for the blood flow velocity prediction model based on plasma cytokine concentration is: V 血流速度 =-0.012×C VEGFA +1.586,R 2 =0.969 lnV 血流速度 =0.997×C bFGF +1.640,R 2 =0.866 V 血流速度 =0.125×lnC TSP-1 +1.035,R 2 =0.990 lnV 血流速度 =1.083×C PF4 +1.161,R 2 =0.777 Among them, V 血流速度 C represents the blood flow velocity in the in situ tumor vessels. VEGFA The concentration of vascular endothelial growth factor A, C bFGF The concentration of basic fibroblast growth factor, C TSP-1 The concentration of thrombin-sensitive protein 1, C PF4 This refers to the concentration of platelet factor 4.

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