A tissue section detection platform based on a three-dimensional gel electrophoresis device

Abstract

The application is suitable for the pathological diagnosis field and provides a tissue slice detection platform based on a three-dimensional gel electrophoresis device, which comprises an in-situ lysis platform, a three-dimensional gel electrophoresis device, a processing platform and a tissue automatic analyzer. The tissue composition is analyzed through the distribution of tissue proteins or nucleic acids. Compared with clinical pathological examination, the application is not limited to the specificity of a targeted marker, and the tissue composition is analyzed through imaging of proteins and nucleic acids. The analysis time of the application on the tissue is about 40 minutes, and the application can be applied to intraoperative tissue analysis. The application reduces the dependence of visual diagnosis of pathological analysis on frozen sections in operation and the dependence on experience of pathologists, and effectively improves the accuracy of intraoperative diagnosis of pathological tissues.

Description

Technical Field

[0001] This invention belongs to the field of pathological diagnosis, and in particular relates to a tissue section detection platform based on a three-dimensional gel electrophoresis device. Background Technology

[0002] Surgery remains the cornerstone of solid tumor treatment, with the key being achieving tumor-free margins within the resected tumor. Despite histological differences, tumor tissue is often indistinguishable from healthy tissue in the operating room. Intraoperative real-time techniques have proven effective in delineating tumors from coexisting benign tissues. Fluorescence-guided surgery uses contrast agents targeting tumor cells to visualize the tumor and surgical margins. However, the overexpression of tumor cells in coexisting benign tissues leads to insufficient sensitivity and selectivity of FGS, thus limiting its clinical application. The emergence of several mass spectrometry-based techniques, including rapid evaporation ionization mass spectrometry and mass spectrometry combining ultraviolet and infrared lasers, has also been used to achieve tumor-free margins intraoperatively. However, these techniques are operationally limited by specific surgical procedures and heavily reliant on specialized equipment. Therefore, traditional histopathological analysis of frozen sections remains the gold standard for intraoperative assessment of positive tumor margins.

[0003] In intraoperative pathological analysis, pathologists identify tumors from coexisting benign tissues based on the characteristics of various tissues to achieve complete tumor resection. Rapidly and accurately assessing tumor margins during surgery through pathological analysis of frozen sections remains challenging. Studies have shown that for certain diagnostic tasks, determining the subtle boundaries between tumors and normal tissues may exceed human visual capabilities, leading to less than ideal diagnostic reproducibility among pathologists. Therefore, surgical margin specimens are often treated as permanent specimens postoperatively. However, if positive margins are found in postoperative pathological evaluation, the patient requires additional surgery to ensure complete resection of the lesion. This not only increases medical costs but also exposes the patient to additional risks of surgical complications, discomfort, and anxiety. Immunohistochemistry (IHC) protocols targeting protein biomarkers and gene sequencing technologies that identify specific gene mutations and chromosomal translocations are designed to assist and complement pathological diagnosis of tissue sections, but both methods are often time-consuming and labor-intensive, making them difficult to apply to intraoperative pathological diagnosis. This clinical challenge highlights the need for rapid, accurate, and automated analysis of the composition of surgically removed tissues. Summary of the Invention

[0004] The purpose of this invention is to provide a tissue section detection platform based on a three-dimensional gel electrophoresis device. This platform aims to address the problem that immunohistochemistry (IHC) for protein biomarkers and gene sequencing technology for identifying specific gene mutations and chromosomal translocations are intended to assist and supplement the pathological diagnosis of tissue sections. However, these two methods are usually time-consuming and labor-intensive, making them difficult to apply to intraoperative pathological diagnosis.

[0005] The present invention is implemented as follows: a tissue section detection platform based on a three-dimensional gel electrophoresis device, the tissue section detection platform based on the three-dimensional gel electrophoresis device comprising:

[0006] In-situ lysis platform, used for in-situ lysis of tissue sections;

[0007] Three-dimensional gel electrophoresis apparatus is used for in-situ separation of proteins or nucleic acids within tissue sections;

[0008] A processing platform for processing and analyzing gel media;

[0009] An automated tissue analyzer is used to automatically analyze tissue composition.

[0010] As a further embodiment of the present invention, the in-situ lysis of the tissue sections specifically includes the following steps:

[0011] Step 1: Rapidly freeze-embed the surgically removed tissue;

[0012] Step 2: Process the embedded tissue into tissue sections for analysis using a frozen tissue microtome;

[0013] Step 3: Attach the tissue sections to the surface of the microwell array sample plate;

[0014] Step 4: Use lysis buffer to lyse the tissue.

[0015] As a further embodiment of the present invention, the thickness of the tissue section to be analyzed in step 2 is 3-100 micrometers.

[0016] As a further embodiment of the present invention, the micropore array sample plate described in step 3, wherein the height of each micropore is 0.5 cm, and the number of micropores contained per square centimeter is 10-100.

[0017] As a further embodiment of the present invention, the lysis solution in step 4 is a mixed solution used for tissue lysis.

[0018] As a further embodiment of the present invention, the three-dimensional gel electrophoresis apparatus includes:

[0019] The cathode plate, microporous array sample plate, separation gel medium and anode plate, and power supply and outer electrostatic pool.

[0020] As a further embodiment of the present invention, the gel medium, after being cut, is a gel layer of uniform thickness perpendicular to the direction of the electric field, and the signals of proteins or nucleic acids in the gel layer are read by an imaging device. The read signals include: signal intensity value, molecular weight range, and xy-direction position information.

[0021] As a further aspect of the present invention, the processing and analysis of the gel medium specifically includes:

[0022] Step 1: Convert the protein or nucleic acid intensity matrix with positional information in the xy direction into a tissue composition probability matrix, and calculate the mathematical expectation of the tissue composition probability matrix of different gel layers;

[0023] Step 2: Analyze tissue composition by comparing the expected values ​​of the probability matrices of different gel layer tissue compositions;

[0024] Step 3: The high-probability regions in the layer with the highest expected value of the probability matrix of the tissue composition are segmented into ROIs, and the contour of the ROI is the predicted contour of the tissue composition.

[0025] The tissue section detection platform based on a three-dimensional gel electrophoresis device provided in this invention has the following beneficial effects:

[0026] This invention analyzes tissue composition by examining the presence and distribution of tissue proteins or nucleic acids, and further predicts the contours of each component. Compared to clinical pathological examination, this invention effectively addresses the issue of insufficient specificity of targeted markers for certain types of tumors by imaging certain tissue proteins or nucleic acids to delineate tissue edges. Simultaneously, it reduces the reliance on visual diagnosis of frozen sections during surgery and the dependence on the pathologist's experience, effectively improving the accuracy of intraoperative diagnosis of lesions. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the workflow of the platform for automatic diagnosis and contour prediction of tissue composition within tissue sections based on a three-dimensional gel electrophoresis device in this invention.

[0028] Figure 2 This is a schematic diagram illustrating the separation and analysis of proteins or nucleic acids within tissue sections using a three-dimensional gel electrophoresis apparatus.

[0029] Figure 3 This is a rendering of the results of using the present invention to determine the contour of a 4T1 tumor.

[0030] Figure 4 This is a schematic diagram of the algorithm used by the tissue autoanalyzer to determine the contour of a 4T1 tumor.

[0031] Figure 5 This is a rendering of the results of using the present invention to determine the contours of HepG2 tumor, C6 tumor, MCF-7 tumor and U87 tumor.

[0032] Figure 6 This is a schematic diagram of an automated analyzer used to determine the profile of sentinel lymph nodes in 4T1 metastasis.

[0033] Figure 7 This is a rendering of an automated tissue analyzer used to determine the contours of human breast cancer tumors.

[0034] Figure 8 This is a rendering of an automated tissue analyzer used to determine the contours of human ovarian cancer tumors. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0036] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0037] like Figure 1 As shown in this embodiment of the invention, a tissue section detection platform based on a three-dimensional gel electrophoresis apparatus is provided, the tissue section detection platform based on the three-dimensional gel electrophoresis apparatus comprising:

[0038] In-situ lysis platform, used for in-situ lysis of tissue sections;

[0039] Three-dimensional gel electrophoresis apparatus is used for in-situ separation of proteins or nucleic acids within tissue sections;

[0040] A processing platform for processing and analyzing gel media;

[0041] An automated tissue analyzer is used to automatically analyze tissue composition.

[0042] In this embodiment of the invention, the in-situ lysis of the tissue sections specifically includes the following steps:

[0043] Step 1: Rapidly freeze-embed the surgically removed tissue;

[0044] Step 2: Process the embedded tissue into tissue sections for analysis using a frozen tissue microtome;

[0045] Step 3: Attach the tissue sections to the surface of the microwell array sample plate;

[0046] Step 4: Use lysis buffer to lyse the tissue.

[0047] In this embodiment of the invention, the thickness of the tissue section to be analyzed in step 2 is 3-100 micrometers.

[0048] In this embodiment of the invention, the micropore array sample plate described in step 3 has a height of 0.5 cm for each micropore and contains 10-100 micropores per square centimeter.

[0049] In this embodiment of the invention, the lysis solution mentioned in step 4 is a mixed solution used for tissue lysis.

[0050] In this embodiment of the invention, the three-dimensional gel electrophoresis apparatus includes:

[0051] The cathode plate, microporous array sample plate, separation gel medium and anode plate, and power supply and outer electrostatic pool.

[0052] As a further embodiment of the present invention, the gel medium, after being cut, is a gel layer of uniform thickness perpendicular to the direction of the electric field, and the signals of proteins or nucleic acids in the gel layer are read by an imaging device. The read signals include: signal intensity value, molecular weight range, and xy-direction position information.

[0053] In this embodiment of the invention, the processing and analysis of the gel medium specifically includes the following steps:

[0054] Step 1: Convert the protein or nucleic acid intensity matrix with positional information in the xy direction into a tissue composition probability matrix, and calculate the mathematical expectation of the tissue composition probability matrix of different gel layers;

[0055] Step 2: Analyze tissue composition by comparing the expected values ​​of the probability matrices of different gel layer tissue compositions;

[0056] Step 3: The high-probability regions in the layer with the highest expected value of the probability matrix of the tissue composition are segmented into ROIs, and the contour of the ROI is the predicted contour of the tissue composition.

[0057] Example 1:

[0058] This embodiment describes the application of the present invention for the diagnosis of positive tumor margins in mouse (or rat) xenograft samples. Specifically, it involves the separation and analysis of proteins from 4T1, HepG2, C6, MCF-7, and U87 tumor samples using a three-dimensional gel electrophoresis platform, and the prediction of tumor contours. A schematic diagram of the separation and analysis of tissue samples is attached. Figure 2 As shown.

[0059] Specifically, let's take the diagnosis of 4T1 tumors as an example. By using approximately 2×10... 6 Four 4T1 cells were seeded onto the second mammary fat pad of Balb / c mice to establish in situ breast cancer tumors. To sacrifice all tumor-bearing mice on day 35, primary breast cancer tissue was surgically collected.

[0060] Next, the inventors embedded the 4T1 tumor and muscle tissue into frozen tissue embedding medium (OCT) to simulate the tight connection between the breast cancer tumor and coexisting benign tissue. Simultaneously, a negative control group consisting only of muscle tissue was constructed.

[0061] Subsequently, the frozen tumor tissue was sliced ​​(thickness: 60 micrometers) and transferred to the surface of the microporous array template, and the slices were lysed.

[0062] Preferably, the thickness of the tissue sections to be analyzed after being processed by a frozen tissue slicer can be 3-100 micrometers.

[0063] Preferably, the specifications of the microporous array sample plate are adjustable according to the number and quantity of samples. The number of micropores contained in the microporous array sample plate ranges from approximately 10 to 100 per square centimeter.

[0064] Preferably, the lysis solution includes, but is not limited to, mixed solutions such as RIPA that can be used for tissue lysis.

[0065] Specifically, the volume of the lysis buffer is 5 ml per slice.

[0066] Specifically, the lysis is achieved by incubation at room temperature.

[0067] After lysis of the tissue sections to be analyzed, the present invention uses a three-dimensional gel electrophoresis device to separate and analyze the proteins in the tissue sections in situ.

[0068] Specifically, the three-dimensional gel electrophoresis device is characterized by, from top to bottom, a cathode plate, a microporous array sample plate, a separation gel medium and an anode plate, and a power source and an outer electrophoresis pool.

[0069] Specifically, the separation gel medium can be agarose and polyacrylamide gel. The concentration range of agarose is approximately 0.3%-2%, and the concentration range of polyacrylamide is approximately 4%-20%. The separation gel can be prepared by directly curing a fixed concentration of agarose or polyacrylamide gel, or by curing 2-4 gels of different concentrations layer by layer.

[0070] Specifically, the voltage is constant during electrophoretic separation.

[0071] Specifically, the separation of proteins within the tissue section begins and ends simultaneously. After electrophoresis, protein molecules separate along the z-axis, while also retaining positional information in the x and y directions.

[0072] This invention obtains signals of dye-labeled proteins in all gel layers by processing and analyzing the gel medium.

[0073] Specifically, the monolithic gel medium containing tissue protein information is frozen. The frozen monolithic gel is then divided into gel layers of uniform thickness perpendicular to the electric field direction (z-direction). All gel layers are imaged and analyzed. The read signals contain protein signal intensity values, molecular weight ranges (i.e., gel layers), and xy-direction position information (i.e., corresponding one-to-one with the microwell coordinates of the microwell array sample plate).

[0074] Preferably, the number of slits is about 10-20, and the thickness of the gel layer is 200-600 micrometers.

[0075] Preferably, all gel layers are imaged, and the imaging device includes, but is not limited to, a scanner.

[0076] As attached Figure 3 As shown, in Figure 3 In the diagram, A represents the initial contour images of negative and positive samples; B represents the imaging and signal analysis results of gel layers 1 to 7 corresponding to negative samples; and C represents the imaging and signal analysis results of gel layers 1 to 7 corresponding to positive samples. The contour of a 4T1 tumor can be determined by the distribution of protein signals within the gel layer corresponding to the molecular weight positions of 4T1 tumor-specific proteins.

[0077] Specifically, the molecular weight of the 4T1 tumor-specific protein is approximately 60-75 kilodaltons.

[0078] Specifically, the gel layers corresponding to the molecular weight position of the 4T1 tumor-specific protein are layers 2 to 4.

[0079] Next, this invention processes the aforementioned protein signals using an automated tissue analyzer. The algorithm script for the automated tissue analyzer is written in Matlab. In this embodiment, the algorithm determines the presence of a tumor by checking for the presence of tumor-specific proteins, and then predicts the tumor contour based on the signal contours of these tumor-specific proteins.

[0080] As attached Figure 4 As shown, the specific judgment process is as follows:

[0081] The protein signal intensity matrix with positional information in the xy direction is converted into a tumor probability matrix, and the mathematical expectation of the tumor probability matrix for different gel layers is calculated.

[0082] The presence of the tumor-specific protein can be determined by comparing the expected value of the gel layer (one or more layers) containing the target tumor-specific protein with the expected value of the gel layer.

[0083] If the tumor-specific protein is absent, the tumor is determined not to exist, and the algorithm ends; if the tumor-specific protein is present, the tumor is determined to exist, and the algorithm continues.

[0084] In the gel layer where tumor-specific proteins are located, the high-probability tumor region is segmented into a Region of Interest (ROI), and the outline of the ROI is the predicted tumor outline.

[0085] Proteins from HepG2, C6, MCF-7, and U87 tumor samples were isolated and analyzed, and tumor contour prediction was performed, as shown in the attached figure. Figure 5 As shown.

[0086] Example 2:

[0087] This embodiment describes the application of the present invention for the diagnosis of positive margins in mouse lymph nodes with 4T1 metastases. By using approximately 2 × 10 6 4T1 cells were inoculated into the second mammary fat pad of Balb / c mice to establish in situ breast cancer tumors. Thirty-five days post-inoculation, sentinel lymph nodes carrying 4T1 tumors were surgically collected from the mice.

[0088] The inventors embedded 4T1-transferred sentinel lymph nodes and muscle tissue into frozen tissue embedding medium (OCT) and processed them into frozen sections with a thickness of 60 micrometers, following the same steps as described in Example 1. In this example, a three-dimensional gel electrophoresis device was used to separate and analyze proteins within the sections, and an automated tissue analyzer was used to determine the contours of tumor-invading lymph nodes (as shown in the attached figure). Figure 6 As shown in the figure, this invention demonstrates that it can reliably identify lymph nodes invaded by tumor cells. Even tumor micrometastases occurring in small tissues such as mouse lymph nodes can be accurately and rapidly identified. This demonstrates the promising clinical translational potential of this platform.

[0089] Example 3:

[0090] This embodiment describes the application of the present invention for the diagnosis of positive margins in human breast and ovarian cancer tumors. The inventors collected breast cancer tumors from 10 patients and ovarian cancer tumors from 4 patients (including corresponding adjacent normal tissues), patient information is shown in Table 1. Next, the inventors embedded the tumor tissue and its corresponding adjacent normal tissues into frozen tissue embedding medium (OCT) and processed them into frozen sections with a thickness of 60 micrometers, the specific steps being consistent with those described in Example 1.

[0091] Table 1: Patient Information

[0092]

[0093] Next, in this embodiment, proteins within the slices are separated and analyzed using a three-dimensional gel electrophoresis apparatus, and the tumor contour is determined by an automated tissue analyzer (as shown in the attached figure). Figure 7As shown in Figure 8, this invention demonstrates that it can reliably determine the edges of malignant tissue in surgically removed tissue. Notably, the inventors compared the tumor contours predicted by the automated tissue analyzer with those diagnosed by clinicopathology and found that the similarity between the two was over 95%.

[0094] Specifically, the contour comparison algorithm script is written in Matlab.

[0095] This embodiment demonstrates that, compared to clinical pathological examination, this platform can be operated by researchers without pathological diagnostic experience in a shorter time, thus helping to improve the speed and accuracy of intraoperative decision-making.

[0096] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A tissue section detection platform based on a three-dimensional gel electrophoresis apparatus, characterized in that, The tissue section detection platform based on a three-dimensional gel electrophoresis device includes: In-situ lysis platform, used for in-situ lysis of tissue sections; The in-situ lysis of the tissue sections specifically includes the following steps: Step 1: Rapidly freeze-embed the surgically removed tissue; Step 2: The embedded tissue is processed into tissue sections to be analyzed using a frozen tissue microtome. The thickness of the tissue sections to be analyzed is 3-100 micrometers. Step 3: Attach tissue sections to the surface of a microwell array template, wherein each microwell in the microwell array template is 0.5 cm high and contains 10-100 microwells per square centimeter. Step 4: Lyse the tissue using a lysis buffer, wherein the lysis buffer is a mixed solution for tissue lysis; A three-dimensional gel electrophoresis apparatus is used for in-situ separation of proteins or nucleic acids within tissue sections. The three-dimensional gel electrophoresis apparatus includes: Cathode plate, micropore array sample plate, separation gel medium and anode plate, power supply and outer electrostatic pool; A processing platform for processing and analyzing gel media; The specific steps for processing and analyzing the gel medium include the following: Step 1: Convert the protein or nucleic acid intensity matrix with positional information in the xy direction into a tissue composition probability matrix, and calculate the mathematical expectation of the tissue composition probability matrix of different gel layers; Step 2: Analyze tissue composition by comparing the expected values ​​of the probability matrices of different gel layer tissue compositions; Step 3: The high-probability regions in the layer with the highest expected value of the probability matrix of the tissue composition are divided into ROIs, and the contour of the ROI is the contour of the predicted component tissue. An automated tissue analyzer is used to automatically analyze tissue composition.

2. The tissue section detection platform based on a three-dimensional gel electrophoresis device according to claim 1, characterized in that, The gel medium, after being cut, forms a gel layer of uniform thickness perpendicular to the direction of the electric field. The signals of proteins or nucleic acids within the gel layer are read by an imaging device. The read signals include: signal intensity value, molecular weight range, and xy-direction position information.

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