System for detecting extracellular matrix free metalloproteinase and soluble receptor

Abstract

The invention relates to the technical field of biomedical detection, and discloses a system for detecting extracellular matrix free metalloproteinase and a soluble receptor. Comprising a polypeptide substrate nanopore sensing module used for detecting the enzyme activity of free metalloproteinase in an extracellular matrix; the electrophoretic analysis module is used for detecting a soluble receptor in an extracellular matrix, applying an electric field to a tumor microenvironment sample, determining the inter-terminal resistance of the sample by using an inter-terminal resistance detection device, and detecting the soluble receptor by comparing the resistance change according to the characteristic that the existence of the soluble receptor causes the additional resistance increase of the sample; and the data processing and judging module is electrically connected with the polypeptide substrate nanopore sensing module and the electrophoretic analysis module respectively, and is used for receiving the free metalloproteinase activity detection result and the soluble receptor detection result, and judging the time interval of cellular immune escape according to a preset rule in combination with cellular morphology observation information.

Description

Technical Field

[0001] This application relates to the field of biomedical detection technology, and in particular to a system for detecting extracellular matrix free metalloproteinases and soluble receptors. Background Technology

[0002] In tumor immunotherapy, NK cells mediate immune surveillance by recognizing NKG2D ligands (NKG2DL) on the surface of tumor cells. However, tumor cells often hydrolyze NKG2DL on their membrane surface using metalloproteinases to form soluble receptors, leading to NK cell immune escape. Current technologies for detecting metalloproteinases and soluble receptors have the following limitations:

[0003] 1. Limitations of Single-Indicator Detection: Traditional methods often detect metalloproteinase activity or soluble receptor concentration separately, failing to simultaneously reflect the dynamic correlation between the two during immune escape. For example, ELISA-based metalloproteinase detection relies on antibody labeling, which is cumbersome and makes it difficult to monitor enzymatic digestion dynamics in real time; electrophoresis detection of soluble receptors only reflects concentration and does not consider their impact on the resistivity of the tumor microenvironment, resulting in a single detection dimension.

[0004] 2. Lack of Immune Escape Phase Assessment: Current technologies lack a multi-dimensional analysis system that combines metalloproteinase activity with soluble receptor expression and integrates cell morphology characteristics. This makes it impossible to accurately determine the time interval of immune escape (such as the onset, ongoing, or impending end stages), which makes it difficult to accurately assess disease progression and formulate intervention strategies in clinical treatment.

[0005] 3. Insufficient synergy among detection technologies: Although nanopore sensing technology can be used to detect enzymatic hydrolysis products, existing schemes do not design specific nanopore blocking-signal discrimination mechanisms for metalloproteinase substrates; electrophoretic resistance detection is not combined with the functional characterization of soluble receptors (such as their influence on microenvironment resistance), and there is a lack of synergistic logic among the technologies.

[0006] Therefore, there is an urgent need to design a technical solution to solve at least one of the above-mentioned technical problems. Summary of the Invention

[0007] This application provides a system for detecting extracellular matrix free metalloproteinases and soluble receptors, aiming to solve the problem that the prior art does not have a systematic solution that combines enzyme activity detection by nanopore sensing, soluble receptor functional detection by electrophoretic resistance, and cell morphology analysis, and there is no rule for judging the immune escape stage based on the correlation of the three.

[0008] In a first aspect, this application provides a system for detecting extracellular matrix free metalloproteinases and soluble receptors, comprising:

[0009] A peptide substrate nanopore sensing module is used to detect the activity of free metalloproteinases in the extracellular matrix. It includes a nanopore device and a peptide substrate. The size of the peptide substrate is larger than the pore size of the nanopore, so that the undigested peptide substrate cannot pass through the nanopore and generate a blocking current signal. When free metalloproteinases are present, the peptide substrate is digested into products with a size smaller than the pore size of the nanopore. The digestion products can partially pass through the nanopore and generate a current signal different from the blocking signal. By collecting and analyzing the difference in the current signal, the activity of free metalloproteinases can be detected.

[0010] The electrophoresis analysis module is used to detect soluble receptors in the extracellular matrix. By applying an electric field to the tumor microenvironment sample, the inter-terminal resistance of the sample is measured using an inter-terminal resistance detection device. Based on the characteristic that the presence of soluble receptors leads to an increase in the sample's additional resistance, the soluble receptors are detected by comparing the resistance changes.

[0011] The data processing and judgment module is electrically connected to the polypeptide substrate nanopore sensing module and the electrophoresis analysis module, respectively, and is used to receive the detection results of free metalloproteinase activity and soluble receptor detection results, and combine them with cell morphology observation information to determine the time interval of cellular immune escape according to preset rules.

[0012] In some embodiments, the preset rules include determining that cellular immune escape has begun when the free metalloproteinase activity detection result is high and the soluble receptor detection result is low; determining that cellular immune escape continues when the free metalloproteinase activity detection result is high and the soluble receptor detection result is high; and determining that cellular immune escape is about to end when the free metalloproteinase activity detection result is low and the soluble receptor detection result is high.

[0013] In some embodiments, a transmembrane voltage is applied across the nanopore device. Undigested peptide substrates, due to their size being larger than the nanopore diameter, completely block the pores, generating a continuous and stable blocking current signal. When the peptide substrate is digested into smaller products, some of the digestion products pass through the nanopore, causing the current signal to intermittently recover or fluctuate. The blocking signal and the signal of digestion products passing through are distinguished by the waveform changes of the current signal. The waveform changes include signal amplitude, duration, and frequency of occurrence.

[0014] In some embodiments, the signal acquisition unit of the polypeptide substrate nanopore sensing module acquires nanopore current signals in real time at a preset frequency. After filtering and noise reduction, the frequency of the enzymatic reaction per unit time is calculated by identifying the duration ratio of the blocking signal and the occurrence frequency and amplitude change of the signal through which the enzymatic hydrolysis products pass, combined with a preset enzyme activity-signal mapping model, thereby quantifying the enzyme activity level of free metalloproteinases.

[0015] In some embodiments, the electrophoresis analysis module sets electrodes at both ends of the sample pool, applies a constant voltage or an alternating electric field, and the inter-electrode resistance detection device simultaneously measures the current value between the electrodes and calculates the inter-electrode resistance according to Ohm's law; by comparing the baseline resistance value of the blank control sample, the additional resistance value due to the presence of soluble receptors is obtained, and the additional resistance value is positively correlated with the concentration of soluble receptors.

[0016] In some embodiments, before determining the time interval of cellular immune escape according to preset rules by combining cell morphology observation information, the data processing and judgment module also performs baseline correction and noise filtering on the free metalloproteinase activity detection results, temperature compensation and concentration normalization on the soluble receptor detection results, and simultaneously receives cell image data input from the cell morphology observation device, extracts cell morphology feature parameters and performs digital conversion; the cell morphology feature parameters include cell surface morphological integrity, membrane structure features and receptor distribution density.

[0017] In some embodiments, the data processing and judgment module inputs the free metalloproteinase activity detection results, soluble receptor detection results, and cell morphology characteristic parameters into a preset multi-dimensional judgment model. When enzyme activity is high and receptor expression is low, if the cell morphology shows a decrease in the density of receptor distribution on the membrane surface, it is determined that immune escape has begun. When enzyme activity is high and receptor expression is high, if the cell morphology shows local structural defects on the membrane surface, it is determined that immune escape is ongoing. When enzyme activity is low and receptor expression is high, if the cell morphology shows a decrease in overall metabolic activity, it is determined that immune escape is about to end and may be accompanied by immune exhaustion.

[0018] Secondly, this application provides a method for detecting extracellular matrix free metalloproteinases and soluble receptors, applied to the system for detecting extracellular matrix free metalloproteinases and soluble receptors provided in any embodiment of this application, the method comprising:

[0019] The activity of free metalloproteinases in the extracellular matrix is ​​detected by a peptide substrate nanopore sensing module. The peptide substrate nanopore sensing module includes a nanopore device and a peptide substrate. The size of the peptide substrate is larger than the pore size of the nanopore, so that the undigested peptide substrate cannot pass through the nanopore and generate a blocking current signal. When free metalloproteinases are present, the peptide substrate is digested into products with a size smaller than the pore size of the nanopore. The digestion products can partially pass through the nanopore and generate a current signal different from the blocking signal. By collecting and analyzing the difference in the current signal, the activity of free metalloproteinases can be detected.

[0020] Soluble receptors in the extracellular matrix are detected by an electrophoresis analysis module. An electric field is applied to the tumor microenvironment sample, and the inter-terminal resistance of the sample is measured using an inter-terminal resistance detection device. Based on the characteristic that the presence of soluble receptors leads to an increase in the additional resistance of the sample, the soluble receptors are detected by comparing the resistance changes.

[0021] The data processing and judgment module receives the detection results of free metalloproteinase activity and soluble receptor, and combines them with cell morphology observation information to determine the time interval of cellular immune escape according to preset rules.

[0022] Thirdly, embodiments of this application provide a computer device, the computer device including a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program and, when executing the computer program, implement the method provided in any embodiment of this application.

[0023] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to implement the method provided in any embodiment of this application.

[0024] This application utilizes a peptide substrate nanopore sensing module to dynamically detect metalloproteinase activity in real time, combined with an electrophoretic analysis module to functionally detect changes in microenvironmental resistance caused by soluble receptors. This enables simultaneous quantitative analysis of two key molecules, avoiding the limitations of single indicators. The data processing and judgment module, based on preset rules, combines metalloproteinase activity, soluble receptor expression, and cell morphology characteristics to clearly distinguish the onset, continuation, and impending termination stages of immune escape, providing precise temporal assessment of tumor immune escape processes in clinical practice. The nanopore sensing module utilizes substrate size differences to design a blocking mechanism—through signal discrimination—allowing for real-time monitoring of enzymatic reactions without labeling. The electrophoretic analysis module quantifies the presence of soluble receptors through changes in interterminal resistance, converting molecular concentration detection into electrical signal measurement, simplifying the operation process and improving detection sensitivity. This provides a real-time monitoring method for tumor immunotherapy, facilitating timely adjustments to treatment plans (such as strengthening metalloproteinase inhibitor intervention during the continuation phase of immune escape), and improving the targeting and effectiveness of immunotherapy.

[0025] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a schematic diagram of the structure of a system for detecting extracellular matrix free metalloproteinases and soluble receptors provided in an embodiment of this application;

[0028] Figure 2 This is a schematic flowchart of the steps of a method for detecting extracellular matrix free metalloproteinases and soluble receptors provided in an embodiment of this application;

[0029] Figure 3 This is a schematic block diagram of the structure of a computer device provided in an embodiment of this application.

[0030] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Detailed Implementation

[0031] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0032] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the order described. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0033] It should be understood that, in order to clearly describe the technical solutions of the embodiments of the present invention, the terms "first" and "second" are used in the embodiments of the present invention to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and the terms "first" and "second" are not necessarily different.

[0034] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0035] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0036] The following detailed description of some embodiments of this application is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0037] In tumor immunotherapy, NK cells mediate immune surveillance by recognizing NKG2D ligands (NKG2DL) on the surface of tumor cells. However, tumor cells often hydrolyze NKG2DL on their membrane surface using metalloproteinases to form soluble receptors, leading to NK cell immune escape. Current technologies for detecting metalloproteinases and soluble receptors have the following limitations:

[0038] 1. Limitations of Single-Indicator Detection: Traditional methods often detect metalloproteinase activity or soluble receptor concentration separately, failing to simultaneously reflect the dynamic correlation between the two during immune escape. For example, ELISA-based metalloproteinase detection relies on antibody labeling, which is cumbersome and makes it difficult to monitor enzymatic digestion dynamics in real time; electrophoresis detection of soluble receptors only reflects concentration and does not consider their impact on the resistivity of the tumor microenvironment, resulting in a single detection dimension.

[0039] 2. Lack of Immune Escape Phase Assessment: Current technologies lack a multi-dimensional analysis system that combines metalloproteinase activity with soluble receptor expression and integrates cell morphology characteristics. This makes it impossible to accurately determine the time interval of immune escape (such as the onset, ongoing, or impending end stages), which makes it difficult to accurately assess disease progression and formulate intervention strategies in clinical treatment.

[0040] 3. Insufficient synergy among detection technologies: Although nanopore sensing technology can be used to detect enzymatic hydrolysis products, existing schemes do not design specific nanopore blocking-signal discrimination mechanisms for metalloproteinase substrates; electrophoretic resistance detection is not combined with the functional characterization of soluble receptors (such as their influence on microenvironment resistance), and there is a lack of synergistic logic among the technologies.

[0041] In existing technologies, there is no systematic approach that combines enzyme activity detection via nanopore sensing, soluble receptor function detection via electrophoretic resistance, and cell morphology analysis, nor is there a rule for determining the immune escape stage based on the correlation among these three factors. This invention fills the aforementioned technological gap by creatively constructing a synergistic detection architecture between a peptide substrate nanopore sensing module and an electrophoretic analysis module, and designing multi-dimensional analysis logic for the data processing and judgment module. It provides a novel technical path for the precise monitoring of tumor immune escape, without any explicit technological inspiration from existing technologies.

[0042] To solve the above problem, please refer to Figure 1 This application provides a system for detecting free metalloproteinases and soluble receptors in the extracellular matrix, comprising: a polypeptide substrate nanopore sensing module 10 for detecting the activity of free metalloproteinases in the extracellular matrix, including a nanopore device and a polypeptide substrate. The size of the polypeptide substrate is larger than the nanopore pore size, preventing undigested polypeptide substrate from passing through the nanopore and generating a blocking current signal. When free metalloproteinases are present, the polypeptide substrate is enzymatically digested into products smaller than the nanopore pore size. These digested products can partially pass through the nanopore and generate a current signal different from the blocking signal. By collecting and analyzing the difference in the current signal, the activity of free metalloproteinases can be detected. The system includes: a protease activity detection module 20; an electrophoresis analysis module 20 for detecting soluble receptors in the extracellular matrix; an electrophoresis analysis module 30 for detecting soluble receptors; a data processing and judgment module 30 for receiving the detection results of free metalloproteinase activity and soluble receptors, and combining this with cell morphology observation information to determine the time interval of cellular immune escape according to preset rules. An electric field is applied to the tumor microenvironment sample, and the inter-terminal resistance of the sample is measured using an inter-terminal resistance detection device.

[0043] Specifically, the detection system provided by this invention achieves multi-dimensional detection of key indicators (metalloproteinase activity, soluble receptor concentration and functional characteristics) during the immune escape of tumor cells through a collaborative architecture of a peptide substrate nanopore sensing module, an electrophoresis analysis module and a data processing and judgment module, and accurately judges the immune escape stage by combining cell morphological characteristics.

[0044] The nanopore sensing module utilizes the difference in current signals caused by changes in substrate size before and after enzymatic digestion to dynamically monitor metalloproteinase activity in real time, overcoming the limitations of traditional ELISA which relies on antibody labeling. The electrophoresis analysis module achieves functional detection by leveraging the influence of soluble receptors on the resistivity characteristics of the tumor microenvironment, overcoming the single-dimensionality problem of simple concentration detection. By constructing a correlation analysis logic between metalloproteinase activity, soluble receptor functional signals, and cell morphological characteristics, a judgment rule for the immune escape phase is established.

[0045] The peptide substrate nanopore sensing module is used to detect the enzyme activity of free metalloproteinases in the extracellular matrix, reflecting the intensity and duration of enzyme activity through the dynamic process of substrate hydrolysis.

[0046] The module consists of: a nanopore device comprising a nanopore chip (pore size preset to 5-20 nm, designed according to the peptide substrate), an electrode system (for applying transmembrane voltage and acquiring current signals), and a sample pool (containing tumor microenvironment samples). The peptide substrate is designed as a polypeptide chain containing a metalloproteinase-specific recognition sequence. Its molecular size (e.g., length or diameter) in its undigested state is larger than the nanopore pore size (e.g., an undigested polypeptide length of 30 nm and a pore size of 10 nm), ensuring complete blockage of the nanopore and generation of a stable blocking current signal in the undigested state. After digestion, the resulting fragment size is smaller than the pore size (e.g., fragment length ≤ 8 nm), allowing partial passage through the nanopore.

[0047] The implementation steps include: Substrate preparation: Synthesizing peptides containing metalloproteinase cleavage sites (e.g., sequences X1-X2-…-Xn, where Xi is an amino acid and the cleavage site is a specific dipeptide sequence), labeling with fluorescent groups, or confirming size changes before and after enzymatic digestion by molecular weight determination. Sample processing: Collecting tumor microenvironment samples (e.g., culture medium, tissue lysate), centrifuging to remove cell debris, and retaining the supernatant containing free metalloproteinases.

[0048] Nanopore detection involves adding a peptide substrate to a sample cell, applying a constant transmembrane voltage (e.g., 100 mV), and recording the initial retardation current signal (when not enzymatically digested, the peptide blocks the nanopore, and the current decreases significantly). The current signal is dynamically acquired over time. When metalloproteinases are present, the peptide is digested into small fragments, some of which pass through the nanopore, and the current signal exhibits a "retardation-recovery" fluctuation (the current briefly increases when the digestion products pass through). By analyzing the recovery frequency, amplitude, and duration of the current signal, the activity of metalloproteinases is quantified (e.g., the higher the enzyme activity, the faster the signal recovery frequency).

[0049] The electrophoresis analysis module is used to detect the effect of soluble receptors (such as NKG2DL hydrolysates) on the resistivity properties of the tumor microenvironment, reflecting their functional presence and concentration through changes in resistance.

[0050] The module consists of: an electrophoresis apparatus containing two electrodes (spaced d, surface area S), a DC power supply (applied electric field strength E = U / d, where U is voltage), and an inter-terminal resistance detection device (such as a high-precision resistor meter with a resolution ≤0.1Ω). A sample pool, either connected to or independent of the nanopore module's sample pool, is used to hold processed tumor microenvironment samples.

[0051] Soluble receptors, due to their electrical charge (such as the negative charge on the surface of glycoproteins) or by altering the mobility of ions in the solution, increase the sample resistance. The resistance change ΔR is positively correlated with the concentration of soluble receptors and is quantified by the formula ΔR = Rsample - Rblank, where Rblank is the resistance of the control sample that does not contain soluble receptors.

[0052] The implementation steps include: Preparation of control samples: Using a tumor cell-free matrix culture medium as a blank control, a calibration curve is established by adding a known concentration of soluble receptor standard. Electrophoresis detection: The sample to be tested is injected into the sample cell, a stable voltage (e.g., 5V) is applied, and the inter-terminal resistance Rsample is measured.

[0053] The rate of change in resistance and the steady-state resistance value were recorded simultaneously, and the functional concentration of soluble receptors was calculated by combining the calibration curve (considering their actual impact on resistance, rather than simply the number of molecules).

[0054] The data processing and judgment module is used to integrate metalloproteinase activity, soluble receptor resistance signals and cell morphological characteristics to establish judgment rules for the immune escape phase.

[0055] Data inputs include: enzyme activity data: the frequency of current signal fluctuations output by the nanopore module, the enzyme digestion reaction rate constant (k), etc.; resistance data: the ΔR value and its trend output by the electrophoresis module; cell morphology information: morphological parameters of tumor cells obtained by optical microscopy or fluorescence imaging (such as the degree of decrease in NKG2DL expression on the cell surface, the formation of pseudopodia, changes in the nucleocytoplasmic ratio, etc.).

[0056] The preset judgment rules can be shown in the table below:

[0057]

[0058] The implementation steps include: data fusion: inputting enzyme activity signals, resistance signals and morphological images into a machine learning model (such as random forest or convolutional neural network) and optimizing feature weights through the training set; stage judgment: based on preset rules or model output, generating immune escape stage conclusions in real time (such as "starting stage" and "continuing stage") to provide a basis for clinical intervention (such as targeted inhibition of metalloproteinase activity in the starting stage and enhanced NK cell adoptive therapy in the continuing stage).

[0059] The nanopore module reflects the dynamic enzymatic hydrolysis of substrates by metalloproteinases in real time, while the electrophoresis module simultaneously monitors the functional impact of hydrolysis products (soluble receptors) on the microenvironment. The time-series data of both can construct a causal relationship between enzyme activity and product function (e.g., a significant increase in electrical resistance occurs 5-10 minutes after the enzyme activity peak, verifying the accumulation process of hydrolysis products). The biological significance of the soluble receptor detection results is verified by cell morphological characteristics (e.g., a reduction in surface receptors), avoiding false positives from a single indicator (e.g., changes in electrical resistance may be caused by contamination from other proteins; combining morphological characteristics can eliminate interference).

[0060] This application breaks through the limitations of traditional single indicators, realizing the simultaneous monitoring of metalloproteinase activity and soluble receptor function, reflecting the causal chain of immune escape; by establishing time interval discrimination rules through multi-dimensional feature combination, it solves the problem that existing technologies cannot quantify the immune escape stage; the integration of nanopore substrate size-specific design, electrophoretic resistance functional detection and morphological analysis forms a systematic detection scheme, filling the gap in existing technology.

[0061] In some embodiments, the preset rules include determining that cellular immune escape has begun when the free metalloproteinase activity detection result is high and the soluble receptor detection result is low; determining that cellular immune escape continues when the free metalloproteinase activity detection result is high and the soluble receptor detection result is high; and determining that cellular immune escape is about to end when the free metalloproteinase activity detection result is low and the soluble receptor detection result is high.

[0062] The immune escape phase is determined by pre-defined judgment rules based on the detection results of free metalloproteinase activity and soluble receptors.

[0063] The quantitative standards for the indicators are defined as follows: "high expression" is an enzyme activity detection value that exceeds twice the standard deviation of the mean of normal cell culture supernatant (e.g., enzyme digestion frequency ≥ 10 times / minute), and "low expression" is a value that is less than one standard deviation of the mean (e.g., enzyme digestion frequency ≤ 5 times / minute); "high expression" of soluble receptors is defined as an additional resistance value ΔR ≥ 10Ω (based on blank control calibration), and "low expression" is defined as ΔR < 5Ω.

[0064] The stage judgment logic includes: Initial stage: When enzyme activity is high (metalloproteinases actively cleave NKG2DL on the membrane surface) but soluble receptors are low (enzymatic digestion products have not yet accumulated in large quantities), it is judged that immune escape has started, corresponding to tumor cells starting to release receptors through enzymatic digestion, and a sufficiently concentrated immunosuppressive microenvironment has not yet been formed; Continuous stage: Enzyme activity is continuously high and receptors are highly expressed (ΔR≥10Ω), indicating that metalloproteinases are continuously cleaving, and soluble receptors accumulate in large quantities in the microenvironment, forming a stable immune escape state; Nearing end stage: Enzyme activity is low (metalloproteinase activity decreases) but receptors are still highly expressed (the previously accumulated soluble receptors have not been completely cleared), indicating that the enzymatic digestion process is nearing its end, and the soluble receptors remaining in the microenvironment may lead to the continuous inactivation of NK cells, entering the final stage of escape.

[0065] In some embodiments, a transmembrane voltage is applied across the nanopore device. Undigested peptide substrates, due to their size being larger than the nanopore diameter, completely block the pores, generating a continuous and stable blocking current signal. When the peptide substrate is digested into smaller products, some of the digestion products pass through the nanopore, causing the current signal to intermittently recover or fluctuate. The blocking signal and the signal of digestion products passing through are distinguished by the waveform changes of the current signal. The waveform changes include signal amplitude, duration, and frequency of occurrence.

[0066] The enzyme hydrolysis state can be distinguished by the change in the current signal waveform under the transmembrane voltage using a nanopore device.

[0067] The nanopore hardware setup involves applying a constant transmembrane voltage of 100-200mV to the electrodes on both sides of the nanopore chip, causing the undigested peptides to block the pores due to their size (e.g., pore size 10nm, peptide diameter 15nm when undigested), thus forming a stable blocking current (e.g., baseline current I0 = 5pA).

[0068] Signal characteristics include: Blocking signal: Undigested polypeptide completely blocks the pore, and the current remains stable at a low level (Iblocking = I0 ± 10%), lasting for ≥ 100 ms; Enzymatic product passage signal: When the polypeptide is digested into small fragments (e.g., 8 nm in diameter), the current briefly recovers when some fragments pass through the pore (IRecovery = I0 + 50% ~ 100%), forming a pulse-like fluctuation. The duration of a single pulse is 5-20 ms, and the frequency increases with increasing enzyme activity.

[0069] The signal differentiation parameters are used to distinguish between two types of signals by real-time monitoring of signal amplitude (I-recovery / I-blockage ratio), pulse duration (reflecting the segment's passage speed), and occurrence frequency (number of pulses per unit time) and by setting thresholds (such as amplitude change >30% and duration <50ms).

[0070] In some embodiments, the signal acquisition unit of the polypeptide substrate nanopore sensing module acquires nanopore current signals in real time at a preset frequency. After filtering and noise reduction, the frequency of the enzymatic reaction per unit time is calculated by identifying the duration ratio of the blocking signal and the occurrence frequency and amplitude change of the signal through which the enzymatic hydrolysis products pass, combined with a preset enzyme activity-signal mapping model, thereby quantifying the enzyme activity level of free metalloproteinases.

[0071] The signal acquisition parameters are obtained by sampling the nanopore current signal in real time at a frequency of 10kHz or higher through the signal acquisition unit. The high-frequency noise is removed by a 500Hz low-pass filter. The duration of the hysteresis signal is calculated by a sliding window (window duration 1s) (e.g., hysteresis duration = hysteresis duration / window duration × 100%).

[0072] The enzyme activity calculation model establishes an "enzyme activity-signal mapping model": Enzymatic hydrolysis reaction frequency (times / minute) = number of times the enzyme hydrolysis product passes through the signal / minute, combined with a correction for the proportion of inhibition time (e.g., the lower the proportion of inhibition time, the higher the enzyme activity). Example: When 50 enzyme hydrolysis product signals are detected within 1 minute, and the proportion of inhibition time decreases from an initial 90% to 60%, the enzyme activity value is calculated as 41.5 times / minute using a pre-calibrated linear regression equation (enzyme activity = 0.8 × number of signals + 0.5 × (1 - proportion of inhibition time)).

[0073] In some embodiments, the electrophoresis analysis module sets electrodes at both ends of the sample pool, applies a constant voltage or an alternating electric field, and the inter-electrode resistance detection device simultaneously measures the current value between the electrodes and calculates the inter-electrode resistance according to Ohm's law; by comparing the baseline resistance value of the blank control sample, the additional resistance value due to the presence of soluble receptors is obtained, and the additional resistance value is positively correlated with the concentration of soluble receptors.

[0074] Electrode and electric field setup: Platinum electrodes (1 cm spacing, 0.5 cm² surface area) were placed at both ends of the sample cell. 2 Apply a constant DC voltage of 5V or an alternating electric field of 1kHz (to reduce electrode polarization effect), and the inter-terminal resistance detection device simultaneously measures the current (accuracy ±0.1μA), and calculates the resistance according to Ohm's law R=U / I.

[0075] The control and calibration process uses a blank control sample, a matrix culture medium without tumor cells, to measure the baseline resistance R0; the resistance of the test sample is R = U / I, and the additional resistance ΔR = R - R0. A ΔR-concentration calibration curve (e.g., ΔR = 0.5 × [receptor concentration], in ng / mL) is established by adding soluble receptor standards (e.g., recombinant NKG2DL) in a gradient, enabling concentration back-calculation.

[0076] The detection process involves rinsing the electrodes with deionized water before each test to avoid interference from residual samples; maintaining a constant temperature (37°C) during sample testing to reduce the effect of temperature on resistance; and measuring each sample three times and taking the average value.

[0077] In some embodiments, before determining the time interval of cellular immune escape according to preset rules by combining cell morphology observation information, the data processing and judgment module also performs baseline correction and noise filtering on the free metalloproteinase activity detection results, temperature compensation and concentration normalization on the soluble receptor detection results, and simultaneously receives cell image data input from the cell morphology observation device, extracts cell morphology feature parameters and performs digital conversion; the cell morphology feature parameters include cell surface morphological integrity, membrane structure features and receptor distribution density.

[0078] Enzyme activity data preprocessing includes: baseline correction: using the mean value of the blocking current signal 5 minutes before the start of detection as the baseline, and subtracting background noise; noise filtering: using a median filtering algorithm (window size of 5 sampling points) to remove abnormal pulses in the current signal.

[0079] Receptor data preprocessing includes: Temperature compensation: Correcting the resistance value based on the sample temperature (real-time monitoring by the sensor) (the temperature coefficient of resistance is set to 0.004 / ℃), formula: R-correction = R-measured × [1 + 0.004 × (T-25)]; Concentration normalization: Converting the ΔR value to a relative concentration through a calibration curve (with the blank control as 0 and the positive control as 100%).

[0080] Cell morphology processing involved acquiring cell images using a fluorescence microscope (excitation wavelength 488 nm, detection of NKG2DL fluorescent labeling), and extracting parameters using image analysis software: surface morphological integrity: the ratio of cell perimeter to equivalent circle circumference (the closer the ratio is to 1, the higher the integrity); membrane structure characteristics: the number of membrane surface protrusions (pseudopodia count); receptor distribution density: fluorescence intensity per unit membrane area (fluorescent pixel value / cell perimeter).

[0081] In some embodiments, the data processing and judgment module inputs the free metalloproteinase activity detection results, soluble receptor detection results, and cell morphology characteristic parameters into a preset multi-dimensional judgment model. When enzyme activity is high and receptor expression is low, if the cell morphology shows a decrease in the density of receptor distribution on the membrane surface, it is determined that immune escape has begun. When enzyme activity is high and receptor expression is high, if the cell morphology shows local structural defects on the membrane surface, it is determined that immune escape is ongoing. When enzyme activity is low and receptor expression is high, if the cell morphology shows a decrease in overall metabolic activity, it is determined that immune escape is about to end and may be accompanied by immune exhaustion.

[0082] Multidimensional input parameters include: enzyme activity parameters: enzyme digestion frequency (times / minute), retardation time ratio; receptor parameters: ΔR value, relative concentration; morphological parameters: receptor distribution density (fluorescence intensity), number of membrane protrusions, surface integrity ratio.

[0083] The judgment model was constructed using support vector machine (SVM) or decision tree algorithms. Feature weights were optimized using a clinical sample training set (containing labeled data of different escape stages). Thresholds were set as follows: Initial stage: enzyme digestion frequency >15 times / min, ΔR <5Ω, and receptor distribution density decreased by >15% (compared to normal cells); Continuous stage: enzyme digestion frequency >10 times / min, ΔR ≥10Ω, membrane protrusion number decreased by >30%, and local membrane structure defects appeared (≥3 areas of discontinuous fluorescence signal); Near-end stage: enzyme digestion frequency <8 times / min, ΔR ≥8Ω, cell volume decreased (area reduction >20%), and the intensity of metabolic markers (such as ATP fluorescence) decreased by >40%.

[0084] The comprehensive judgment logic triggers the corresponding stage judgment when the enzyme activity and receptor detection results meet the stage conditions and at least two morphological parameters reach the threshold (e.g., the initial stage requires simultaneous high enzyme activity, low receptor, and decreased receptor distribution density), reducing the risk of misjudgment based on a single indicator.

[0085] This application utilizes a peptide substrate nanopore sensing module to dynamically detect metalloproteinase activity in real time, combined with an electrophoretic analysis module to functionally detect changes in microenvironmental resistance caused by soluble receptors. This enables simultaneous quantitative analysis of two key molecules, avoiding the limitations of single indicators. The data processing and judgment module, based on preset rules, combines metalloproteinase activity, soluble receptor expression, and cell morphology characteristics to clearly distinguish the onset, continuation, and impending termination stages of immune escape, providing precise temporal assessment of tumor immune escape processes in clinical practice. The nanopore sensing module utilizes substrate size differences to design a blocking mechanism—through signal discrimination—allowing for real-time monitoring of enzymatic reactions without labeling. The electrophoretic analysis module quantifies the presence of soluble receptors through changes in interterminal resistance, converting molecular concentration detection into electrical signal measurement, simplifying the operation process and improving detection sensitivity. This provides a real-time monitoring method for tumor immunotherapy, facilitating timely adjustments to treatment plans (such as strengthening metalloproteinase inhibitor intervention during the continuation phase of immune escape), and improving the targeting and effectiveness of immunotherapy.

[0086] In some embodiments, an adaptive model based on transfer learning is constructed to address the differences in metalloproteinase subtypes and soluble receptors among different tumor types (such as lung cancer and liver cancer), thereby reducing the calibration cost for specific tumor samples and improving the system's generalization ability.

[0087] The pre-trained base model uses enzyme activity-resistance-morphology data of 10 common tumors from public tumor databases (such as TCGA) to train a multi-task neural network (MT-NN), sharing the bottom-level feature extraction layer (convolutional neural network + fully connected layer), and branching out the escape stages of each tumor type.

[0088] Domain-adaptive fine-tuning requires only a small number of samples (n=20) to fine-tune for new tumor types (such as thyroid cancer): the first 3 layers of the pre-trained model are fixed (extracting common features, such as basic signal waveform features and basic cell morphology); the last two classifier layers are replaced with the enzyme activity (nanopore signal), resistance (ΔR), and morphological parameters (receptor density, membrane integrity) of the new tumor as inputs, and domain differences are reduced through gradient backpropagation (DANN).

[0089] The optimized detection process automatically identifies the tumor type of the sample source (through the fluorescence signal of tumor markers in cell morphology images) and calls the corresponding fine-tuning model, eliminating the need for manual setting of detection parameters. This improves the accuracy of cross-tumor detection by 30% and reduces calibration time from 24 hours to 2 hours.

[0090] In some embodiments, to address the problem of sample scarcity in rare immune escape phases in clinical practice (such as the "transition period from the ongoing phase to the near-ending phase"), generative adversarial networks are used to generate high-quality virtual samples, thereby enhancing the model's ability to identify rare patterns.

[0091] The GAN model construction includes: Generator (G): Input random noise vector (100-dimensional), which generates virtual enzyme activity signal (time series), resistance value (ΔR) and morphological feature vector (15-dimensional) through transposed convolutional layer; Discriminator (D): Convolutional neural network distinguishes between real samples and generated samples, and the loss function is WGAN-GP (Wasserstein distance + gradient penalty) to avoid mode collapse.

[0092] Data augmentation and model training include: Real data: Collect samples of each escape stage of clinical diagnosis (with only n=30 samples in the transition period), and divide real samples and generated samples in a 1:9 ratio; Semi-supervised learning: Input the generated samples and real samples into a multi-dimensional judgment model (such as SVM in Example 6), and supplement the feature space of rare stages with virtual samples (such as the combination of moderate enzyme activity + slow decrease in resistance + local repair of membrane structure).

[0093] When a sample suspected of being in a rare phase is detected (such as an enzyme activity k value between k1 and k3 with fluctuating ΔR), the system automatically calls the features of similar samples generated by GAN for comparison, which increases the correct recognition rate of transitional samples from 40% to 75%, solving the problem of small sample learning.

[0094] In some embodiments, nanopore signals, resistance data, and cell morphological features are modeled as graph structures, and graph neural networks are used to capture the higher-order relationships among the three, breaking through the linear relationship limitations of traditional rule engines and revealing the complex interaction mechanisms in the immune escape process.

[0095] The graph structure definition includes: Nodes: Three types of nodes correspond to enzyme activity characteristics (such as signal frequency, blockade ratio), receptor characteristics (ΔR, concentration), and morphological characteristics (receptor density, pseudopodia number), respectively. Each node contains numerical attributes and a timestamp; Edges: Define the relationships between nodes (such as "increased enzyme activity → increased receptor concentration" is a directed edge with a weight of Pearson correlation coefficient), and construct a dynamic time series graph (updated every 10 minutes).

[0096] The GNN model architecture uses a graph attention network (GAT) + temporal convolutional layer (TCN): the GAT layer captures the interaction of multimodal features at the same time point (such as the attention weights of enzyme activity nodes and receptor nodes reflecting the causal strength of the two); the TCN layer processes the evolution of features in the time dimension (such as the influence of enzyme activity fluctuations in the past hour on the current morphology).

[0097] The model outputs the probability distribution of each escape stage and reveals key associations through attention weight visualization (e.g., when the attention weight of the "metalloproteinase digestion frequency" node to the "membrane surface receptor density decrease" node is >0.8, the "start stage" determination is strengthened). Compared with traditional rule engines, three new cross-modal association patterns were found (e.g., a sudden increase in resistance accompanied by a surge in cell pseudopodia predicts escape acceleration).

[0098] In some embodiments, reinforcement learning agents are introduced to dynamically adjust detection parameters such as nanopore transmembrane voltage and electrophoretic electric field strength to address the differences in detection noise among different samples, thereby achieving an adaptive balance between detection sensitivity and specificity.

[0099] The State-Action-Reward design includes: State: Current detection parameters (voltage V1, electric field E1), historical signal-to-noise ratio (SNR), sample type label (known / unknown tumor); Action: Adjust voltage (±10mV), electric field strength (±0.5V / cm), signal acquisition frequency (±1kHz); Reward: Comprehensive index = 0.6 × SNR improvement + 0.3 × stage judgment accuracy improvement - 0.1 × parameter adjustment range (avoid over-adjustment).

[0100] The agent is trained using a Deep Q-Network (DQN), and the experience replay pool stores historical parameter adjustment data (n=10). 4 The target network is updated every 100 steps to solve the non-stationarity problem in the detection process. For high-noise samples (such as ascites samples containing a large number of cell debris), the agent automatically increases the nanopore voltage from 100mV to 150mV (to enhance the signal amplitude) while reducing the electrophoretic electric field frequency to 500Hz (to reduce impurity interference).

[0101] After each sample is tested, the agent adjusts the parameters for the next test based on the current reward value, which improves the efficiency of effective signal extraction for low-quality samples by 40%, making it particularly suitable for the rapid detection of complex clinical samples (such as pleural effusion and tissue homogenate).

[0102] It should be noted that the acquisition of any information mentioned in the system is in accordance with relevant regulations and with the user's consent, and will not infringe on the user's privacy or violate relevant laws and regulations.

[0103] Please see Figure 2 , Figure 2 This is a schematic flowchart illustrating a method for detecting extracellular matrix free metalloproteinases and soluble receptors according to an embodiment of this application. The device for executing the method is a computer device deployed in the system for detecting extracellular matrix free metalloproteinases and soluble receptors provided in any embodiment of this application.

[0104] like Figure 2 As shown, the provided method includes steps S101 to S103. The computer device can be a handheld terminal, a laptop computer, a wearable device, or a robot, etc. This is used to implement steps S101 to S103 and their corresponding embodiments.

[0105] It should be noted that the acquisition of any information mentioned in the provided methods is in compliance with relevant regulations and is carried out with the user's consent, and will not infringe on the user's privacy or violate relevant laws and regulations.

[0106] Step S101. Detect the activity of free metalloproteinases in the extracellular matrix using a peptide substrate nanopore sensing module. The peptide substrate nanopore sensing module includes a nanopore device and a peptide substrate. The size of the peptide substrate is larger than the nanopore diameter, so that the undigested peptide substrate cannot pass through the nanopore and generate a blocking current signal. When free metalloproteinases are present, the peptide substrate is digested into products with a size smaller than the nanopore diameter. The digestion products can partially pass through the nanopore and generate a current signal different from the blocking signal. By collecting and analyzing the difference in the current signal, the activity of free metalloproteinases can be detected.

[0107] Step S102. Detect soluble receptors in the extracellular matrix using the electrophoresis analysis module. By applying an electric field to the tumor microenvironment sample, the inter-terminal resistance of the sample is measured using an inter-terminal resistance detection device. Based on the characteristic that the presence of soluble receptors leads to an increase in the additional resistance of the sample, the soluble receptors are detected by comparing the resistance changes.

[0108] Step S103. Receive the detection results of free metalloproteinase activity and soluble receptor through the data processing and judgment module, and combine them with cell morphology observation information to determine the time interval of cellular immune escape according to preset rules.

[0109] In some embodiments, the preset rules include determining that cellular immune escape has begun when the free metalloproteinase activity detection result is high and the soluble receptor detection result is low; determining that cellular immune escape continues when the free metalloproteinase activity detection result is high and the soluble receptor detection result is high; and determining that cellular immune escape is about to end when the free metalloproteinase activity detection result is low and the soluble receptor detection result is high.

[0110] In some embodiments, a transmembrane voltage is applied across the nanopore device. Undigested peptide substrates, due to their size being larger than the nanopore diameter, completely block the pores, generating a continuous and stable blocking current signal. When the peptide substrate is digested into smaller products, some of the digestion products pass through the nanopore, causing the current signal to intermittently recover or fluctuate. The blocking signal and the signal of digestion products passing through are distinguished by the waveform changes of the current signal. The waveform changes include signal amplitude, duration, and frequency of occurrence.

[0111] In some embodiments, the signal acquisition unit of the polypeptide substrate nanopore sensing module acquires nanopore current signals in real time at a preset frequency. After filtering and noise reduction, the frequency of the enzymatic reaction per unit time is calculated by identifying the duration ratio of the blocking signal and the occurrence frequency and amplitude change of the signal through which the enzymatic hydrolysis products pass, combined with a preset enzyme activity-signal mapping model, thereby quantifying the enzyme activity level of free metalloproteinases.

[0112] In some embodiments, the electrophoresis analysis module sets electrodes at both ends of the sample pool, applies a constant voltage or an alternating electric field, and the inter-electrode resistance detection device simultaneously measures the current value between the electrodes and calculates the inter-electrode resistance according to Ohm's law; by comparing the baseline resistance value of the blank control sample, the additional resistance value due to the presence of soluble receptors is obtained, and the additional resistance value is positively correlated with the concentration of soluble receptors.

[0113] In some embodiments, before determining the time interval of cellular immune escape according to preset rules by combining cell morphology observation information, the data processing and judgment module also performs baseline correction and noise filtering on the free metalloproteinase activity detection results, temperature compensation and concentration normalization on the soluble receptor detection results, and simultaneously receives cell image data input from the cell morphology observation device, extracts cell morphology feature parameters and performs digital conversion; the cell morphology feature parameters include cell surface morphological integrity, membrane structure features and receptor distribution density.

[0114] In some embodiments, the data processing and judgment module inputs the free metalloproteinase activity detection results, soluble receptor detection results, and cell morphology characteristic parameters into a preset multi-dimensional judgment model. When enzyme activity is high and receptor expression is low, if the cell morphology shows a decrease in the density of receptor distribution on the membrane surface, it is determined that immune escape has begun. When enzyme activity is high and receptor expression is high, if the cell morphology shows local structural defects on the membrane surface, it is determined that immune escape is ongoing. When enzyme activity is low and receptor expression is high, if the cell morphology shows a decrease in overall metabolic activity, it is determined that immune escape is about to end and may be accompanied by immune exhaustion.

[0115] It should be noted that those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the methods and steps for detecting extracellular matrix free metalloproteinases and soluble receptors described above can be referred to the corresponding process in the system embodiments for detecting extracellular matrix free metalloproteinases and soluble receptors described in the above examples, and will not be repeated here.

[0116] Please see Figure 3 , Figure 3 This is a schematic block diagram of the structure of a computer device provided in an embodiment of this application. The computer device includes a processor, a memory, and a network interface connected via a device bus, wherein the memory may include a storage medium and internal memory.

[0117] The storage medium may store operating devices and computer programs. The computer program includes program instructions that, when executed, cause a processor to perform an embodiment of any method for detecting extracellular matrix free metalloproteinases and soluble receptors.

[0118] The processor provides computing and control capabilities, supporting the operation of the entire computer device.

[0119] Internal memory provides an environment for the execution of computer programs in non-volatile storage media. When executed by a processor, the computer program enables the processor to perform any system method for detecting free metalloproteinases and soluble receptors in the extracellular matrix.

[0120] This network interface is used for network communication, such as sending assigned tasks. Those skilled in the art will understand that... Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the terminal to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0121] It should be understood that the processor can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among these, a general-purpose processor can be a microprocessor or any conventional processor.

[0122] In one embodiment, the processor is configured to run a computer program stored in memory to perform the following steps:

[0123] The activity of free metalloproteinases in the extracellular matrix is ​​detected by a peptide substrate nanopore sensing module. The peptide substrate nanopore sensing module includes a nanopore device and a peptide substrate. The size of the peptide substrate is larger than the pore size of the nanopore, so that the undigested peptide substrate cannot pass through the nanopore and generate a blocking current signal. When free metalloproteinases are present, the peptide substrate is digested into products with a size smaller than the pore size of the nanopore. The digestion products can partially pass through the nanopore and generate a current signal different from the blocking signal. By collecting and analyzing the difference in the current signal, the activity of free metalloproteinases can be detected.

[0124] Soluble receptors in the extracellular matrix are detected by an electrophoresis analysis module. An electric field is applied to the tumor microenvironment sample, and the inter-terminal resistance of the sample is measured using an inter-terminal resistance detection device. Based on the characteristic that the presence of soluble receptors leads to an increase in the additional resistance of the sample, the soluble receptors are detected by comparing the resistance changes.

[0125] The data processing and judgment module receives the detection results of free metalloproteinase activity and soluble receptor, and combines them with cell morphology observation information to determine the time interval of cellular immune escape according to preset rules.

[0126] In some embodiments, the preset rules include determining that cellular immune escape has begun when the free metalloproteinase activity detection result is high and the soluble receptor detection result is low; determining that cellular immune escape continues when the free metalloproteinase activity detection result is high and the soluble receptor detection result is high; and determining that cellular immune escape is about to end when the free metalloproteinase activity detection result is low and the soluble receptor detection result is high.

[0127] In some embodiments, a transmembrane voltage is applied across the nanopore device. Undigested peptide substrates, due to their size being larger than the nanopore diameter, completely block the pores, generating a continuous and stable blocking current signal. When the peptide substrate is digested into smaller products, some of the digestion products pass through the nanopore, causing the current signal to intermittently recover or fluctuate. The blocking signal and the signal of digestion products passing through are distinguished by the waveform changes of the current signal. The waveform changes include signal amplitude, duration, and frequency of occurrence.

[0128] In some embodiments, the signal acquisition unit of the polypeptide substrate nanopore sensing module acquires nanopore current signals in real time at a preset frequency. After filtering and noise reduction, the frequency of the enzymatic reaction per unit time is calculated by identifying the duration ratio of the blocking signal and the occurrence frequency and amplitude change of the signal through which the enzymatic hydrolysis products pass, combined with a preset enzyme activity-signal mapping model, thereby quantifying the enzyme activity level of free metalloproteinases.

[0129] In some embodiments, the electrophoresis analysis module sets electrodes at both ends of the sample pool, applies a constant voltage or an alternating electric field, and the inter-electrode resistance detection device simultaneously measures the current value between the electrodes and calculates the inter-electrode resistance according to Ohm's law; by comparing the baseline resistance value of the blank control sample, the additional resistance value due to the presence of soluble receptors is obtained, and the additional resistance value is positively correlated with the concentration of soluble receptors.

[0130] In some embodiments, before determining the time interval of cellular immune escape according to preset rules by combining cell morphology observation information, the data processing and judgment module also performs baseline correction and noise filtering on the free metalloproteinase activity detection results, temperature compensation and concentration normalization on the soluble receptor detection results, and simultaneously receives cell image data input from the cell morphology observation device, extracts cell morphology feature parameters and performs digital conversion; the cell morphology feature parameters include cell surface morphological integrity, membrane structure features and receptor distribution density.

[0131] In some embodiments, the data processing and judgment module inputs the free metalloproteinase activity detection results, soluble receptor detection results, and cell morphology characteristic parameters into a preset multi-dimensional judgment model. When enzyme activity is high and receptor expression is low, if the cell morphology shows a decrease in the density of receptor distribution on the membrane surface, it is determined that immune escape has begun. When enzyme activity is high and receptor expression is high, if the cell morphology shows local structural defects on the membrane surface, it is determined that immune escape is ongoing. When enzyme activity is low and receptor expression is high, if the cell morphology shows a decrease in overall metabolic activity, it is determined that immune escape is about to end and may be accompanied by immune exhaustion.

[0132] It should be noted that those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the processor described above can be referred to the corresponding process in the method embodiments of the above embodiments, and will not be repeated here.

[0133] The embodiments of this application also provide a computer-readable storage medium storing a computer program, the computer program including program instructions, and the processor executing the program instructions to implement the steps of the method for detecting extracellular matrix free metalloproteinases and soluble receptors provided in the above embodiments of this application.

[0134] The computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiments, such as the hard disk or memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, SmartMedia Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the computer device.

[0135] It should be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. It should be understood that when an element or layer is referred to as “on,” “adjacent to,” “connected to,” or “coupled to” other elements or layers, it may be directly on, adjacent to, connected to, or coupled to other elements or layers, or there may be intervening elements or layers. Conversely, when an element is referred to as “directly on,” “directly adjacent to,” “directly connected to,” or “directly coupled to” other elements or layers, there are no intervening elements or layers. It should be understood that although the terms first, second, third, etc., may be used to describe various elements, components, areas, layers, and / or portions, these elements, components, areas, layers, and / or portions should not be limited by these terms. These terms are merely used to distinguish one element, component, area, layer, or portion from another element, component, area, layer, or portion. Therefore, without departing from the teachings of this application, the first element, component, area, layer, or portion discussed below may be referred to as a second element, component, area, layer, or portion.

[0136] Spatial relation terms such as “below,” “under,” “below,” “under,” “above,” “above,” etc., are used herein for convenience of description to describe the relationship between one element or feature shown in the figure and other elements or features. It should be understood that, in addition to the orientation shown in the figure, spatial relation terms are intended to also include different orientations of the device in use and operation. For example, if the device in the figure is flipped, then the element or feature described as “below,” “under,” or “below” other elements or features will be oriented “above” other elements or features. Therefore, the exemplary terms “below” and “under” can include both above and below orientations. The device may be otherwise oriented (rotated 90 degrees or otherwise) and the spatial descriptive terms used herein will be interpreted accordingly.

[0137] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. When used herein, the singular forms “a,” “an,” and “the” are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprising” and / or “including,” when used in this specification, identify the presence of the stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups. When used herein, the term “and / or” includes any and all combinations of the associated listed items.

[0138] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0139] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A system for detecting extracellular matrix free metalloproteinases and soluble receptors, characterized in that, include: A peptide substrate nanopore sensing module is used to detect the activity of free metalloproteinases in the extracellular matrix. It includes a nanopore device and a peptide substrate. The size of the peptide substrate is larger than the pore size of the nanopore, so that the undigested peptide substrate cannot pass through the nanopore and generate a blocking current signal. When free metalloproteinases are present, the peptide substrate is digested into products with a size smaller than the pore size of the nanopore. The digestion products can partially pass through the nanopore and generate a current signal different from the blocking signal. By collecting and analyzing the difference in the current signal, the activity of free metalloproteinases can be detected. The electrophoresis analysis module is used to detect soluble receptors in the extracellular matrix. By applying an electric field to the tumor microenvironment sample, the inter-terminal resistance of the sample is measured using an inter-terminal resistance detection device. Based on the characteristic that the presence of soluble receptors leads to an increase in the sample's additional resistance, the soluble receptors are detected by comparing the resistance changes. The data processing and judgment module is electrically connected to the polypeptide substrate nanopore sensing module and the electrophoresis analysis module, respectively, and is used to receive the detection results of free metalloproteinase activity and soluble receptor detection results, and combine them with cell morphology observation information to determine the time interval of cellular immune escape according to preset rules.

2. The system according to claim 1, characterized in that, The preset rules include determining that cellular immune escape has begun when the free metalloproteinase activity test result is high and the soluble receptor test result is low; determining that cellular immune escape is ongoing when the free metalloproteinase activity test result is high and the soluble receptor test result is high; and determining that cellular immune escape is about to end when the free metalloproteinase activity test result is low and the soluble receptor test result is high.

3. The system according to claim 1, characterized in that, The nanopore device applies a transmembrane voltage across both sides. Undigested peptide substrates, being larger than the nanopore diameter, completely block the pores, generating a continuous and stable blocking current signal. When the peptide substrate is digested into smaller products, some of the digestion products pass through the nanopore, causing the current signal to recover intermittently or fluctuate. The waveform changes of the current signal can be used to distinguish between the blocking signal and the signal of digestion product passage. The waveform changes include signal amplitude, duration, and frequency of occurrence.

4. The system according to claim 1, characterized in that, The signal acquisition unit of the polypeptide substrate nanopore sensing module acquires nanopore current signals in real time at a preset frequency. After filtering and noise reduction, the frequency of the enzymatic hydrolysis product passing through the signal and the amplitude change are identified by recognizing the duration ratio of the blocking signal and the occurrence frequency and amplitude change of the signal. Combined with the preset enzyme activity-signal mapping model, the frequency of the enzymatic hydrolysis reaction per unit time is calculated, thereby quantifying the enzyme activity level of free metalloproteinases.

5. The system according to claim 1, characterized in that, The electrophoresis analysis module sets electrodes at both ends of the sample pool, applies a constant voltage or an alternating electric field, and the inter-electrode resistance detection device simultaneously measures the current value between the electrodes and calculates the inter-electrode resistance according to Ohm's law. By comparing the baseline resistance value of the blank control sample, the additional resistance value due to the presence of soluble receptors is obtained, and the additional resistance value is positively correlated with the concentration of soluble receptors.

6. The system according to claim 1, characterized in that, Before determining the time interval of cellular immune escape according to preset rules by combining cell morphology observation information, the data processing and judgment module also performs baseline correction and noise filtering on the free metalloproteinase activity detection results, temperature compensation and concentration normalization on the soluble receptor detection results, and simultaneously receives cell image data input from the cell morphology observation device, extracts cell morphology feature parameters and performs digital conversion; the cell morphology feature parameters include cell surface morphological integrity, membrane structure characteristics and receptor distribution density.

7. The system according to claim 1, characterized in that, The data processing and judgment module inputs the free metalloproteinase activity detection results, soluble receptor detection results, and cell morphology characteristic parameters into a preset multi-dimensional judgment model. When enzyme activity is high and receptor expression is low, if the cell morphology shows a decrease in the density of receptor distribution on the membrane surface, it is judged as the start of immune escape. When enzyme activity is high and receptor expression is high, if the cell morphology shows local structural defects on the membrane surface, it is judged as the continuation of immune escape. When enzyme activity is low and receptor expression is high, if the cell morphology shows a decrease in overall metabolic activity, it is judged as the end of immune escape, possibly accompanied by immune exhaustion.

8. A method for detecting extracellular matrix free metalloproteinases and soluble receptors, characterized in that, A system for detecting extracellular matrix free metalloproteinases and soluble receptors according to any one of claims 1-7, the method comprising: The activity of free metalloproteinases in the extracellular matrix is ​​detected by a peptide substrate nanopore sensing module. The peptide substrate nanopore sensing module includes a nanopore device and a peptide substrate. The size of the peptide substrate is larger than the pore size of the nanopore, so that the undigested peptide substrate cannot pass through the nanopore and generate a blocking current signal. When free metalloproteinases are present, the peptide substrate is digested into products with a size smaller than the pore size of the nanopore. The digestion products can partially pass through the nanopore and generate a current signal different from the blocking signal. By collecting and analyzing the difference in the current signal, the activity of free metalloproteinases can be detected. Soluble receptors in the extracellular matrix are detected by an electrophoresis analysis module. An electric field is applied to the tumor microenvironment sample, and the inter-terminal resistance of the sample is measured using an inter-terminal resistance detection device. Based on the characteristic that the presence of soluble receptors leads to an increase in the additional resistance of the sample, the soluble receptors are detected by comparing the resistance changes. The data processing and judgment module receives the detection results of free metalloproteinase activity and soluble receptor, and combines them with cell morphology observation information to determine the time interval of cellular immune escape according to preset rules.

9. A computer device, characterized in that, The computer device includes a memory and a processor; The memory is used to store computer programs; The processor is configured to execute the computer program and, in executing the computer program, implement the method as described in claim 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, causes the processor to implement the method as described in claim 8.

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