Use of reagents for detecting markers in the manufacture of a product for predicting the prognosis of a breast cancer patient

Abstract

The application belongs to the technical field of detection markers, and particularly relates to application of a reagent for detecting a marker in preparation of a product for predicting prognosis of breast cancer patients, wherein the marker is MFAP1K324 lactoylation modification. It is shown by ROC curve evaluation of MFAP1K324 lactoylation on prognosis results of breast cancer patients that the AUC value can reach 0.711, indicating that the MFAP1K324 lactoylation can be used as a marker for prognosis of breast cancer patients.

Description

Technical Field

[0001] This invention belongs to the field of biomarker technology, specifically relating to the application of a biomarker reagent in the preparation of products for predicting the prognosis of breast cancer patients. Background Technology

[0002] Breast cancer, as the most common malignant tumor among women worldwide, exhibits significant prognostic heterogeneity, significantly impacting the precision of clinical treatment decisions. Current prognostic assessments primarily rely on histopathological grading, TNM staging, and traditional molecular markers (such as CEA and CA19-9). However, these indicators suffer from limitations such as insufficient sensitivity and weak dynamic monitoring capabilities, failing to accurately reflect individualized prognostic risks and leading to missed opportunities for early intervention in advanced-stage patients. Therefore, the development of specific prognostic biomarkers based on novel molecular mechanisms is an urgent clinical need for achieving stratified management of breast cancer and optimizing treatment strategies.

[0003] Protein lactylation, a key mechanism of metabolic regulation, has been increasingly linked to malignant phenotypes such as tumor microenvironment acidification and enhanced glycolytic activity. Studies have found that lactylation can influence tumor cell metabolic reprogramming by regulating signaling pathways such as HIF-1α and is closely related to the suppression of immune cell function. In recent years, advancements in lactylogomics have enabled high-throughput screening of tumor-associated modified proteins; for example, HSP90 lactylation has been found to be associated with liver cancer metastasis, and PKM2 modification levels have been shown to predict chemotherapy resistance in colorectal cancer. However, these studies have largely focused on the overall abundance of modified proteins, with insufficient attention paid to the functional analysis of site-specific modifications and their clinical translation.

[0004] As a crucial regulatory protein for extracellular matrix remodeling, previous research on MFAP1 has primarily focused on its mechanism of influencing tumor invasion through fibrin crosslinking, while the dynamic regulatory role of its post-translational modifications has long been neglected. Although literature reports that high expression of MFAP1 in breast cancer may be associated with shortened patient survival, the specific types of modifications and sites of action regulating its function remain unclear. Current research on MFAP1 lactylation modifications is limited to in vitro generalized modification detection, lacking functional validation of specific modification sites (such as K324) in clinical samples and prognostic correlation analysis. Summary of the Invention

[0005] To address the aforementioned technical bottlenecks, this invention reveals that the level of lactylation modification at the K324 site of the MFAP1 protein is significantly negatively correlated with the prognosis of breast cancer patients, and can serve as a prognostic marker for breast cancer patients.

[0006] To achieve the above objectives, the present invention can adopt the following technical solutions:

[0007] In one aspect, this invention provides the application of a reagent for detecting a biomarker in the preparation of a product for predicting the prognosis of breast cancer patients, wherein the biomarker is MFAP1 K324 lactylated modification.

[0008] Preferably, in the above applications, the reagents for detecting biomarkers can be reagents based on immunohistochemical staining, reagents based on specific antibody detection, reagents based on mass spectrometry, reagents based on metabolic marker detection, or reagents based on molecular biology detection.

[0009] Preferably, in the above applications, reagents for immunohistochemical staining detection methods may include buffer solutions or staining reagents; reagents for specific antibody detection methods may include anti-MFAP1 antibodies or anti-lactylated lysine antibodies; reagents for mass spectrometry detection methods may include trypsin, reducing agents, alkylating agents, or desalting columns; and reagents for metabolic marker detection methods may include... 13 C3-lactic acid, alkynyllactic acid, biotin-azide, TBTA, or CuSO4; reagents based on molecular biology detection methods may include K324R mutant plasmids, CRISPR / Cas9 editing tools, or transfection reagents.

[0010] Preferably, in the above application, the prognosis of breast cancer patients refers to the prognosis of breast cancer patients.

[0011] Preferably, in the above applications, the product is a detection reagent or a detection kit.

[0012] The beneficial effects of this invention include at least the following: The results of ROC curve evaluation of the prognostic effect of MFAP1 K324 lactylation on breast cancer patients show that the AUC value can reach 0.711, indicating that MFAP1 K324 lactylation can be used as a prognostic marker for breast cancer patients. Attached Figure Description

[0013] Figure 1 To organize the chip manufacturing process;

[0014] Figure 2 This is a schematic diagram of the array arrangement;

[0015] Figure 3 Immunohistochemical staining of 159 sites in 131 breast cancer patients;

[0016] Figure 4 Immunohistochemical staining comparison of MFAP K324 lactylated modification in cancerous tissue and normal tissue;

[0017] Figure 5 Differential expression analysis of MFAP1 K324 lactylation in cancer and adjacent normal tissues;

[0018] Figure 6 Correlation analysis of MFAP1 K324 lactylation and prognosis in breast cancer patients;

[0019] Figure 7 This is a classic forest plot for binary variables; A represents the univariate analysis, and B represents the multivariate analysis.

[0020] Figure 8 The subject working curves for MFAP1 K324 lactylation in breast cancer patients. Detailed Implementation

[0021] The embodiments described are provided to better illustrate the present invention, but are not intended to limit the scope of the invention to the embodiments described. Therefore, non-essential improvements and adjustments made to the embodiments by those skilled in the art based on the above description are still within the scope of protection of the present invention.

[0022] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. Singular expressions include plural expressions unless they have a distinct meaning in the context. As used herein, it should be understood that terms such as “comprising,” “having,” “including,” are intended to indicate the presence of features, numbers, operations, components, parts, elements, materials, or combinations thereof. The terminology of the invention is disclosed in the specification and is not intended to exclude the possibility that one or more other features, numbers, operations, components, parts, elements, materials, or combinations thereof may be present or added. As used herein, “ / ” may be interpreted as “and” or “or,” depending on the context.

[0023] To better understand the present invention, specific examples are provided below to further illustrate the content of the present invention, but the content of the present invention is not limited to the examples below.

[0024] In the following example, the fabrication process of tissue chips is as follows: Figure 1 As shown, the details are as follows:

[0025] (1) Obtain HE-stained sections from breast cancer patients for pathological diagnosis and mark the extent of the lesion tissue;

[0026] (2) Design the tissue type and arrangement of the tissue chip array according to the experimental purpose;

[0027] (3) Select the appropriate tissue case number from the tissue database;

[0028] (4) Take out the tissue paraffin block and the corresponding HE-stained section from the tissue bank according to the tissue case number;

[0029] (5) Prepare suitable blank receptor wax blocks using a tissue embedding machine (brand: Presstar, model: PBM-A, place of origin: China);

[0030] (6) Using a tissue array instrument, extract the core of the pathological paraffin block according to the array design and arrange it regularly on the blank recipient paraffin block;

[0031] (7) The tissue array blocks are heated and fused in a constant temperature oven at 52°C so that the tissue core and the receptor wax block are tightly connected;

[0032] (8) Use a fully automatic tissue slicer (brand: Leica, RM2445, country of origin: Germany) to trim the wax block of the tissue array at a feed speed of 20 micrometers / revolution until 80% of the tissue core is fully exposed.

[0033] (9) The tissue array block was sectioned using a fully automatic tissue slicer at a feed speed of 4 micrometers / revolution, and the sections were mounted on imported glass slides treated to prevent detachment.

[0034] (10) Place the arrayed slices in a 60℃ constant temperature oven and bake for 16 hours;

[0035] (11) Every 10 tissue microarrays are randomly selected for HE staining. The pathologist performs a follow-up quality inspection on each tissue sample from the randomly selected tissue microarrays, and the results are entered into the tissue microarray database by the information department;

[0036] (12) Tissue microarray experimental slides were stored in a slide box and kept in a refrigerator at 5°C.

[0037] (13) Seal the used pathological tissue paraffin blocks with wax and return them and the corresponding HE-stained sections to the paraffin block cabinet and section box.

[0038] In the following examples, the immunohistochemical staining method for tissue microarrays is as follows:

[0039] (1) Reagent preparation

[0040] (2) Baking the slides: Place the tissue chips in an oven, set the temperature to 63 degrees Celsius, and bake for one hour;

[0041] (3) Dewaxing: After the film is baked, it is removed from the oven and placed in a fully automatic dyeing machine (brand: Leica, ST5020, made in Germany) for dewaxing; the dewaxing process is as follows:

[0042] 1) Two cylinders for xylene, 15 minutes per cylinder (according to the instrument's set time);

[0043] 2) Two cylinders of anhydrous ethanol, 7 minutes per cylinder (according to the instrument's set time);

[0044] 3) One tank of 90% alcohol, 5 minutes (according to the instrument's set time);

[0045] 4) 80% alcohol, 1 tank, 5 minutes (according to the instrument's set time);

[0046] 5) 70% alcohol, 1 tank, 5 minutes (according to the instrument's set time);

[0047] (4) Antigen retrieval: Take the slides out of the fully automatic staining machine and rinse them with pure water 3 times, each time for no less than 1 minute; during the rinsing process, put the citric acid retrieval solution on an induction cooker and start heating; after the citric acid retrieval solution boils, put the slides into a pressure cooker, cover the pressure cooker lid, and start timing after the steam is released, 5 minutes; after the time is up, stop heating, open the pressure cooker lid, and let it cool naturally for more than 30 minutes.

[0048] (5) Blocking: Use a commercially available ready-to-use blocking agent (Agilent (made in the USA), peroxidase blocker (SM801) in the Dako EnVision FLEX+ kit), drop the blocking agent onto the tablet, and time for 10-15 minutes;

[0049] (6) Add primary antibody: Take out the slide and rinse it 3 times with PBS buffer for 1 minute each time; take out Anti-Lactyl-MFAP1(K324)RabbitpAb (Cat#CO0426) produced by Hangzhou Jingjie Biotechnology Co., Ltd. (rabbit polyclonal antibody for detecting lactation modification of lysine (K324) at position 324 of MFAP1 protein) from the refrigerator, put it into a centrifuge and centrifuge at 7200 rpm for no less than 30 seconds, add Anti-Lactyl-MFAP1(K324)RabbitpAb dropwise at a dilution of 1:500, incubate at room temperature, and freeze overnight at -4 degrees Celsius;

[0050] (7) Add secondary antibody: Rinse the slides three times with PBS buffer, one minute each time; for slides that have been kept at 4°C overnight, the slides need to be warmed to room temperature for more than 30 minutes before the experiment, and then rinsed with PBS buffer; add the secondary antibody (Agilent (made in the USA), peroxidase marker (goat anti-rabbit secondary antibody) (SM802) from the Dako EnVision FLEX+ kit) using the working solution, incubate at room temperature for 30 minutes; after the time is up, rinse three times with PBS, each time for no less than one minute;

[0051] (8) DAB staining: Take the substrate buffer out of the refrigerator, add 1 drop of DAB staining agent, mix thoroughly to prepare the DAB substrate working solution (Agilent (made in the USA), DAB staining solution and substrate buffer from the Dako EnVision FLEX+ kit); add the diluted DAB to the slide, observe the staining intensity, the longest staining time is 5 minutes, and then rinse with tap water for 5 minutes after that;

[0052] (9) Hematoxylin counterstaining and mounting: Add Agilent hematoxylin to the slide for 1 minute, then immerse it in 0.25% hydrochloric acid alcohol for at least 2 seconds, rinse with tap water for more than 2 minutes, air dry at room temperature, and then mount the slide.

[0053] (10) Interpretation method

[0054] 1) Staining intensity score: 0 (negative), 0.5 (0.5+), 1 (1+), 2 (2+), 3 (3+);

[0055] 2) Staining positivity rate score: 0%-100%;

[0056] 3) Total score: the product of "staining intensity score" and "staining positivity rate" (0-300%).

[0057] I. Screening of MFAP1K324 Lactylation as a Marker

[0058] Three pairs of breast cancer tissues and adjacent normal tissues from three breast cancer patients at the Affiliated Hospital of Guangdong Medical University between 2010 and 2013 were subjected to lactylation sequencing. The results indicated that MFAP1 K324 lactylation was highly expressed in breast cancer, and clinical validation was subsequently performed.

[0059] II. Verification of the relationship between MFAP1K324 lactylation and clinicopathological features

[0060] HE-stained slides from 131 breast cancer patients at the Affiliated Hospital of Guangdong Medical University between 2010 and 2013 were used for pathological diagnosis and the extent of cancerous tissue was marked. Then, tissue microarrays (a total of 159 sites) were prepared according to the above method. Subsequently, the microarrays were subjected to immunohistochemical staining and analysis. The general information of the patients at the microarray sites is shown in Table 1 below.

[0061] Table 1. Information from 159 loci in 1131 breast cancer patients.

[0062]

[0063]

[0064]

[0065]

[0066]

[0067] Additionally, the array arrangement diagram is as follows: Figure 2 As shown, the arrangement of the 159 sites in the chip; in addition, the immunohistochemical staining of the 159 sites in 131 breast cancer patients is shown below. Figure 3 As shown, the expression of MFAP1 K324 lactylation at 159 sites in breast cancer tissue and adjacent normal tissue after immunohistochemical staining (shown under a 4x microscope); in addition, the comparison of immunohistochemical staining of MFAP1 K324 lactylation modification in cancer tissue and normal tissue is shown below. Figure 4 As shown, MFAP1 K324 lactylation is expressed higher in breast cancer tissue than in adjacent breast cancer tissue (as shown under a 40x microscope).

[0068] (I) Differential expression analysis of genes in cancerous and adjacent tissues

[0069] The immunohistochemical staining results were analyzed using the Wilcoxon test (the expression of MFAP1 K324 lactylation in breast cancer tissue and normal tissue was verified and scored by pathologists; relevant data were entered into SPSS software (version: 25.0.0.2), nonparametric tests were selected, two independent samples were chosen, and the Wilcoxon test was checked) to analyze the difference in gene expression between cancerous and adjacent normal tissues (p < 0.05 was considered statistically significant). The results are as follows: Figure 5 As shown in the figure, the results indicate that the expression of MFAP1K324 lactylated tissues was higher than that in adjacent normal tissues (P = 0.0002), which was statistically significant.

[0070] (II) Correlation analysis between MFAP1K324 lactylation and clinical indicators

[0071] The immunohistochemical staining results were analyzed using Fisher's test (grouping was set up in SPSS software (version: 25.0.0.2), relevant data were entered, data weighting was selected, and then Fisher's test was performed) to analyze the correlation between MFAP1K324 lactylation expression in breast cancer tissue and clinical indicators. A P value < 0.05 was considered statistically significant. The results are shown in Table 2. The results show that MFAP1 K324 lactylation expression is related to the molecular subtype of breast cancer. In triple-negative breast cancer, MFAP1 K324 lactylation expression is higher than that in non-triple-negative breast cancer (P = 0.039), which is statistically significant.

[0072] Table 2. Correlation analysis of MFAP1 K324 lactylation and clinical indicators in breast cancer patients.

[0073]

[0074]

[0075] (III) Correlation analysis between MFAP1K324 and patient prognosis

[0076] This analysis used Kaplan-Meier survival analysis and log-rank statistical test for univariate analysis of survival (in SPSS software (version: 25.0.0.2), grouping was set up, and the survival time and status of follow-up patients were entered (0 represents survival, 1 represents death). Then, click "Analysis" - "Survival Analysis" - "Kaplan-Meier", drag "Time" into "Time", "Survival Outcome" into "Status", and "Expression Status" into "Factors", and select Log-rank). A p-value < 0.05 was considered statistically significant. Results after 12 years of follow-up were as follows... Figure 6 As shown in the results, the overall survival of breast cancer patients with high expression of MFAP1 K324 lactylation was lower than that of breast cancer patients with low expression of MFAP1 K324 lactylation (P = 0.029), which was statistically significant.

[0077] (iv) Cox Multivariate Regression Analysis

[0078] Variables statistically significant in univariate analysis were included in the Cox multivariate survival regression analysis. Specifically, the following steps were performed: In SPSS software (version 25.0.0.2), groupings were set up, and the survival time and status of follow-up patients (0 for survival, 1 for death) were entered. Then, the process was clicked "Analysis" - "Survival Analysis" - "COX Regression," and the variable "Duration" was dragged into "Time." The variable "Survival Status" was dragged into "Status." The variable "Survival Status" was defined by clicking "Define Event," selecting "Single Value," and entering "1," meaning "1" represents the outcome event (death) has occurred. The independent variables to be included in the Cox regression were dragged into "Covariates." A p-value < 0.05 was considered statistically significant. The analysis results are shown in Table 3. The results show that among the five variables (Expression, TNM, ER, PR, and Classification) with p-values ​​less than 0.05 in the univariate Cox analysis, the p-value for TNM was 0.00746, indicating that TNM negatively impacts patient survival time and can be considered an independent prognostic factor.

[0079] Table 3 shows the results of the Cox multivariate survival regression analysis.

[0080]

[0081]

[0082] (V) Mori Chart Analysis

[0083] Use the forestplotter package in R (version 4.2.3) to visualize Cox regression model data by plotting forest plots. A classic binary variable forest is shown below. Figure 7As shown, the hazard ratio (HR) is used as an indicator of the magnitude of the clinical factor effect size. In the forest plot, the effect size point estimate = 1 is used as the invalidity line. It is assumed that factor A (as a reference) is to the left of the invalidity line, and factor B is to the right of the invalidity line. When the 95% CI of the effect size includes 1, that is, when the horizontal line segment in the forest plot intersects the invalidity line, it indicates that the difference in the incidence of the outcome event between the two groups is not statistically significant, and it cannot be concluded that factors A and B have different effects on the risk of the outcome event. When the 95% CI of the effect size is greater than 1, that is, when the horizontal line segment in the forest plot does not intersect the invalidity line, and the invalidity line is within the range of 1, the effect size is considered to be within the range of 1. On the right, it can be assumed that the incidence of the outcome event in factor B group is greater than that in factor A group. Generally, if the outcome event is an adverse event such as morbidity or death, it suggests that factor B can increase the incidence of the outcome event compared to factor A, and is therefore a risk factor. Conversely, when the 95% CI of the effect size is less than 1, that is, when the horizontal line segment in the forest plot does not intersect with the null line and is to the left of the null line, it can be assumed that the incidence of the outcome event in factor B group is less than that in factor A group. Generally, if the outcome event is an adverse event such as morbidity or death, it suggests that factor B can reduce the incidence of the event compared to factor A, and is therefore a protective factor.

[0084] The results showed that, Figure 7 In A, univariate analysis revealed that TNM stage increased the incidence of MFAP1 K324 lactylation, threatening patient survival, while ER, PR, and Classification decreased the incidence of MFAP1 K324 lactylation and improved patient survival. Figure 7 In B, multivariate analysis revealed that TNM stage increases the occurrence of MFAP1 K324 lactylation, threatening patient survival.

[0085] (VI) ROC curve evaluation of the prognosis of breast cancer patients by MFAP1K324 lactylation

[0086] The efficacy of MFAP1 K324 lactylation in prognostic assessment of breast cancer patients is as follows: Figure 8 As shown in the figure. The results showed that the AUC value reached 0.711, indicating that MFAP1 K324 lactylation can serve as a prognostic marker for breast cancer patients.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. Use of a reagent for detecting a marker in the preparation of a product for predicting the prognosis of a breast cancer patient, the marker being a MFAP1 K324 lactylation modification.

2. Use according to claim 1, characterized in that, The reagent for detecting a marker is a reagent based on an immunohistochemical staining detection method, a reagent based on a specific antibody detection method, a reagent based on a mass spectrometric analysis detection method, a reagent based on a metabolic marker detection method, or a reagent based on a molecular biology detection method.

3. Use according to claim 2, characterized in that, The reagent based on an immunohistochemical staining detection method includes a buffer or a staining reagent; the reagent based on a specific antibody detection method includes an anti-MFAP1 antibody or an anti-lactylated lysine antibody; the reagent based on a mass spectrometric analysis detection method includes pancreatin, a reducing agent, an alkylating agent, or a desalting column; the reagent based on a metabolic marker detection method includes C3-lactic acid, alkynyl lactic acid, biotin-azide, TBTA, or CuSO4; the reagent based on a molecular biology detection method includes a K324R mutant plasmid, a CRISPR / Cas9 editing tool, or a transfection reagent.

4. Use according to any one of claims 1 to 3, characterized in that, The product is a detection reagent or a detection kit.

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