Use of lama5 gene or protein in preparation of drugs for treating benign prostatic hyperplasia

Abstract

The application discloses application of LAMA5 gene or protein in preparation of a drug for treating benign prostatic hyperplasia, and relates to the technical field of biological medicine. The application discloses application of LAMA5 gene or protein in preparation of a drug for treating benign prostatic hyperplasia. It is first discovered and proved that the LAMA5 gene or protein can be used as a specific treatment target of BPH, preferably collagen deposition type BPH. Target point screening is carried out based on proteomics data, and double verification is carried out in combination with 'drugability' and 'function significance', so that the candidate drug is converted into a clinical drug; a complete evidence chain of in-vivo and in-vitro function verification is provided, and the intervention effectiveness of the target point is fully proved.

Description

Technical Field

[0001] This invention relates to the field of biomedical technology, and in particular to the application of a LAMA5 gene or protein in the preparation of a drug for treating benign prostatic hyperplasia. Background Technology

[0002] Benign prostatic hyperplasia (BPH) is a common degenerative urological disease in middle-aged and elderly men. Its heterogeneity has been clearly confirmed through proteomic molecular typing. Among them, the collagen deposition type (SI subtype) is an important subtype with unique pathological features and clinical needs. This subtype accounts for 25.7% of the BPH population, and its core pathological features are significant collagen deposition, severe inflammatory cell infiltration, and a high prevalence of diabetes (57.9%). The response to traditional treatment regimens is significantly limited.

[0003] Current clinical treatment of benign prostatic hyperplasia (BPH) focuses on relieving lower urinary tract symptoms and reducing prostate volume, primarily relying on drugs such as alpha-receptor blockers and 5α-reductase inhibitors, or surgical procedures such as transurethral laser enucleation. However, treatment for BPH with collagen deposition has significant shortcomings: ① Existing drugs lack targeted intervention on collagen deposition and inflammatory infiltration, making it difficult to improve the interstitial fibrosis state in this subtype of patients, resulting in incomplete symptom relief and recurrence in some patients; ② Although surgical treatment can remove hyperplastic tissue, it cannot reverse the established interstitial fibrosis and inflammatory microenvironment, and there is still a risk of poor bladder function recovery and symptom recurrence after surgery; ③ There is a lack of specific intervention targets for this subtype in clinical practice, causing treatment to remain at the level of "symptomatic treatment" without achieving precise targeting of the core pathological mechanisms of the disease.

[0004] From a pathological perspective, collagen deposition and inflammatory infiltration are key drivers of the progression of collagen deposition-type benign prostatic hyperplasia (BPH): excessive collagen deposition leads to increased prostate tissue rigidity and exacerbates bladder outlet obstruction, while inflammatory cell infiltration further intensifies tissue damage and fibrosis, forming a vicious cycle of inflammation and fibrosis. Therefore, screening key molecular targets that regulate collagen deposition and inflammatory infiltration, and developing targeted intervention drugs, has become a core need to address the treatment challenges of this subtype of patients.

[0005] In the field of target screening, although existing studies have focused on the role of extracellular matrix-related proteins in BPH, specific therapeutic targets for collagen deposition-type BPH have not yet been identified: ① The lack of target screening based on subtype-specific proteomics data leads to insufficient targeting of potential targets; ② The failure to combine "drugability" and "functional significance" for dual verification makes it difficult for some candidate molecules to be transformed into clinical drugs; ③ The lack of a complete chain of evidence for in vitro and in vivo functional verification means that the intervention effectiveness of the targets has not been fully confirmed. Summary of the Invention

[0006] To address the technical problems existing in the prior art, this invention provides an application of the LAMA5 gene or protein in the preparation of a drug for treating benign prostatic hyperplasia. The technical solution is as follows:

[0007] Application of the LAMA5 gene or protein in the preparation of drugs for the treatment of benign prostatic hyperplasia.

[0008] Optionally, the benign prostatic hyperplasia is collagen deposition type benign prostatic hyperplasia.

[0009] Application of reagents that inhibit LAMA5 gene expression or LAMA5 protein activity in the preparation of drugs for treating benign prostatic hyperplasia.

[0010] Optionally, the benign prostatic hyperplasia is collagen deposition type benign prostatic hyperplasia.

[0011] Optionally, the reagent for inhibiting LAMA5 gene expression includes siRNA; wherein the sequence of the sense strand of the siRNA is shown in SEQ ID No. 1 and the sequence of the antisense strand is shown in SEQ ID No. 2; or the sequence of the sense strand of the siRNA is shown in SEQ ID No. 3 and the sequence of the antisense strand is shown in SEQ ID No. 4.

[0012] A pharmaceutical composition for treating benign prostatic hyperplasia, the pharmaceutical composition comprising: an agent that inhibits LAMA5 gene expression or an agent that inhibits LAMA5 protein activity.

[0013] Optionally, the benign prostatic hyperplasia is collagen deposition type benign prostatic hyperplasia.

[0014] Optionally, the reagent for inhibiting LAMA5 gene expression includes siRNA; wherein the sequence of the sense strand of the siRNA is shown in SEQ ID No. 1 and the sequence of the antisense strand is shown in SEQ ID No. 2; or the sequence of the sense strand of the siRNA is shown in SEQ ID No. 3 and the sequence of the antisense strand is shown in SEQ ID No. 4.

[0015] A siRNA for inhibiting LAMA5 gene expression, wherein the sequence of the sense strand of the siRNA is shown in SEQ ID No. 1 and the sequence of the antisense strand is shown in SEQ ID No. 2; or the sequence of the sense strand of the siRNA is shown in SEQ ID No. 3 and the sequence of the antisense strand is shown in SEQ ID No. 4.

[0016] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0017] Based on a previously established stable molecular subtyping system, this invention focuses on the core pathological features of benign prostatic hyperplasia (BPH), such as collagen deposition type BPH, and conducts targeted target screening and validation, filling a technological gap in this field. This invention is the first to discover and demonstrate that the LAMA5 gene or protein can serve as a specific therapeutic target for BPH, preferably collagen deposition type BPH. Based on proteomics data, this invention screens targets and combines "drugability" and "functional significance" for dual validation, enabling candidate drugs to be transformed into clinical drugs; it possesses a complete chain of evidence for in vitro and in vivo functional validation, fully demonstrating the interventional effectiveness of the target.

[0018] Specifically, this invention, through a series of functional verification experiments, demonstrates that intervention (e.g., knockdown) of the LAMA5 gene or protein can produce significant beneficial therapeutic effects: First, it can effectively inhibit the migration ability of BPH-related cells, reduce the invasion and spread of abnormal cells, thereby curbing the proliferation and infiltration of diseased tissues and blocking the pathological progression of BPH at the cellular level; Second, it can significantly inhibit the abnormal production of extracellular matrix, avoiding tissue fibrosis caused by excessive accumulation of extracellular matrix; Third, it can effectively reduce collagen deposition, improve the fibrotic microenvironment of diseased tissues in patients with collagen deposition type BPH, and alleviate core clinical symptoms such as urethral compression. These beneficial effects precisely match the core pathological mechanism of collagen deposition type BPH. Targeting LAMA5 can achieve precise intervention for this type of BPH. Compared with traditional non-specific treatments, it has advantages such as clear target, high treatment efficiency, and few side effects, providing a new and effective solution for the clinical treatment of collagen deposition type BPH, further enhancing the clinical application value and translational prospects of this invention. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a graph of drug target screening provided in Embodiment 1 of the present invention, including the influence of candidate drug targets on subtypes: a box scatter plot showing the abundance distribution of sample proteins, a linear regression forest plot showing the influence of differentially expressed proteins on clinical or pathological features, and a bar chart showing -log 10 (P-value);

[0021] Figure 2This is a diagram of the drug target distribution verification provided in Example 1 of the present invention, wherein the pathological verification of the target protein is as follows: the left figure is the immunohistochemical distribution of LAMA5 in the normal control group and collagen deposition type BPH, and the right figure is the immunohistochemical quantitative statistical diagram of tissue microarray.

[0022] Figure 3 This is a diagram illustrating the functional verification of the drug target provided in Example 1 of this invention. After siRNA knockdown, qPCR and Western blot were used to detect the mRNA and protein expression levels of LAMA5 in BPH-1, WPMY-1, and RWPE-1 cell lines. i. Sirius Red staining was used to detect collagen deposition in WPMY-1 cells after LAMA5 knockdown (scale bar 1.5 mm). j. A scratch assay was used to assess the migration ability of WPMY-1 cells after LAMA5 knockdown (scale bar 1.5 mm). Here, scramble refers to the blank control, Si-LAMA5-#1 is LAMA5 gene knockdown (repeat 1), and Si-LAMA5-#2 is LAMA5 gene knockdown (repeat 2). Detailed Implementation

[0023] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0024] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0025] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0026] Unless otherwise specified, the experimental methods described in the following embodiments are conventional experimental methods well known to those skilled in the art, and are performed according to the techniques or conditions described in the literature in this field or according to the product instructions. Where specific conditions are not specified in the experimental methods, they are generally operated under conventional conditions.

[0027] Unless otherwise specified, all materials and reagents described in the following examples are commercially available.

[0028] Example 1

[0029] 1. Clinical Sample Collection

[0030] Prostate tissue samples (74 cases) were obtained from a cohort of 74 patients with benign prostatic hyperplasia (BPH) who underwent transurethral laser enucleation of the prostate at the First Medical Center of the General Hospital of the Chinese People's Liberation Army (Cohort 1). Additionally, complete prostate tissue samples were obtained from 31 cadaveric donors at the 924th Hospital of the Chinese People's Liberation Army (17 BPH cases, BPH Cohort 2; 14 normal cases, healthy cohort). Total prostate volume (TPV) was calculated by ultrasound: transverse diameter × anteroposterior diameter × superior-inferior diameter × 0.52; transition zone (TZ) volume was measured using the water displacement method. The inclusion and exclusion criteria for clinical samples were: pathologically confirmed benign prostatic hyperplasia with signed informed consent; and exclusion of patients diagnosed with prostate cancer.

[0031] Tissue samples were rapidly frozen in liquid nitrogen within 30 minutes of resection and then stored at -80°C for later use. Urine samples were collected by centrifugation to obtain the supernatant. Clinical information such as patient age, prostate volume, and imaging data were extracted from medical records. This study was approved by the Ethics Committee of the General Hospital of the Chinese People's Liberation Army (Ethics No.: S2021-463-01) and only included samples from surgical patients who had signed written informed consent forms.

[0032] 2. Data-independent acquisition (DIA) mass spectrometry analysis

[0033] (1) Sample preparation

[0034] Tissue samples were processed separately. In brief, urine samples were thawed and centrifuged at high speed to remove insoluble fragments, followed by total protein enrichment using acetone precipitation. Tissue samples were homogenized in lysis buffer, then sonicated in an ice-water bath, and the supernatant was collected by centrifugation to obtain the total protein extract.

[0035] All protein samples were denatured, reduced, and alkylated using 100 mmol / L Tris buffer (pH 8.5) containing 1% sodium deoxycholate (DOC), 10 mmol / L tris(2-carboxyethyl)phosphine (TCEP), and 40 mmol / L 2-chloroacetamide (CAA). Trypsin was then added, and the mixture was digested overnight at 37°C. The resulting peptides were desalted, purified, vacuum-dried, and stored at -80°C for subsequent mass spectrometry analysis.

[0036] (2) Liquid chromatography and mass spectrometry analysis

[0037] Peptide samples were separated using a nanofluidic liquid chromatography system (EASY-nLC1200, Thermo Fisher Scientific). The chromatographic system consisted of a reversed-phase C18 pre-column (2 cm × 100 μm, 3 μm) and an analytical column (25 cm × 150 μm, 1.9 μm). The mobile phase consisted of solvent A (0.1% aqueous formic acid) and solvent B (0.1% formic acid in 80% acetonitrile), with a linear gradient elution over 120 minutes: the proportion of solvent B increased from 7% to 95%, and the flow rate was maintained at 600 nanoliters / minute.

[0038] The separated peptides were analyzed using a QExactive HF-X mass spectrometer (Thermo Fisher Scientific) in data-independent acquisition (DIA) mode. The electrospray ionization voltage was set to 2.2 kV. Full-scan MS1 ​​was acquired in the orbital trap mass analyzer at a resolution of 120,000 (m / z 200), with a mass range of 398–1002 m / z; the automatic gain control (AGC) target was set to 3e6, and the maximum injection time (MIT) was 80 ms. DIA fragmentation scans were performed using 45 variable windows. MS2 spectra were acquired in the orbital trap at a resolution of 30,000; the peptide precursors were fragmented in a high-energy collisional dissociation (HCD) cell with a normalized collision energy of 28%; the AGC target and maximum injection time for MS2 were both set to automatic mode.

[0039] (3) Proteomics data processing based on DIA-NN

[0040] Raw DIA-MS data were processed using DIA-NN software (version 1.8). First, a virtual spectral library was generated within the software based on the standard human proteome database (UniProt2021_03 version). The library generation parameters were set as follows: enzyme digestion specificity was set to trypsin / P, allowing a maximum of one missed cleavage site; peptide length ranged from 7 to 30 amino acids; precursor charge ranged from 1 to 4; the mass-to-charge ratio (m / z) of precursor ions and fragment ions ranged from 300 to 1800 and 200 to 1800, respectively; cysteine ​​carbamoyl methylation was set as a fixed modification, and methionine oxidation was set as a variable modification.

[0041] The spectral library was then used to perform spectral-based analysis on all DIA data. To improve identification performance, deep learning-based spectral prediction and retention time calibration were enabled, and run-by matching (MBR) was applied to increase identification depth. A strict 1% false discovery rate (FDR) was applied at both the peptide and protein levels. Protein inference employed a heuristic algorithm based on shared spectra. All computations utilized 12 parallel threads to optimize processing efficiency.

[0042] (4) Quality control of mass spectrometry platform

[0043] To assess instrument stability and data reproducibility, human embryonic kidney 293T (HEK293T) cell lysates were analyzed every 3 days as quality control standards. Pairwise Spearman correlation coefficients for all quality control data were calculated using R4.4.1 software. The average correlation coefficient between standards was 0.95, with a maximum and minimum of 0.97 and 0.93, respectively, indicating stable consistency of the mass spectrometry platform. A total of 7047 proteins were identified in the quality control samples.

[0044] (5) Preprocessing of prostate and urine proteomics datasets

[0045] In quantitative proteomics analysis, the raw quantitative values ​​of two batches of samples were extracted from the DIA-NN output file and converted into intensity-based absolute quantification (iBAQ) intensity, representing the final expression level of a specific protein in each sample. The resulting expression matrix is ​​as follows: 9396×74 (protein × sample) for prostate tissue samples in Cohort 1, 6429×55 for paired urine samples, and 10093×31 for prostate tissue samples in Cohort 2 and the healthy cohort.

[0046] To compare cohort 1 with the healthy cohort, the two matrices were merged into a 9036×88 integrated expression matrix. Principal component analysis (PCA) was performed using R4.4.1 software to assess batch effects in the integrated data, and the results showed that the effect of batch origin was negligible. This analysis only included proteins expressed in at least 25% of BPH or healthy prostate samples.

[0047] All expression matrices were quantile-normalized using the `normalizeBetweenArrays` function (method="quantile") from the `R / Bioconductorlimma` package. The normalized iBAQ intensities were then log2-transformed and used in all subsequent quantitative analyses. For algorithms that do not allow missing values, missing values ​​were filled with the minimum value for that protein across the entire dataset. Only proteins with expression levels above the quartile of total protein expression were retained for downstream statistical and bioinformatics analyses.

[0048] 3. Tissue microarray (TMA) and immunohistochemistry (IHC)

[0049] TMA was constructed from 100 prostate transition zone tissue samples from cohorts 1, 2, and a healthy cohort. Patient prostate tissues were formalin-fixed, paraffin-embedded, and sectioned according to standard procedures. Sections were incubated overnight at 4°C with primary antibodies (including CD45, CD4, CD8, CD68, Ki67, AR, PCP4, LAMA5, CALD1, and TP63), diluted to recommended concentrations (see Table 1), and then incubated with enzyme-labeled secondary antibodies at 37°C for 20 minutes. Color development was performed using a DAB substrate kit, followed by hematoxylin counterstaining. All IHC-stained sections were digitized at 20-40x magnification using an Olympus VS200 slide scanner to generate high-resolution whole-slide images (WSI), stored in .vsi format for subsequent microscopic observation and scoring.

[0050] Table 1 Primary Antibody List

[0051]

[0052] Digital IHC slides (WSI) were independently evaluated by two experienced pathologists using Aperio ImageScope software on a standard computer monitor. Observers were blinded for clinical data, grouping information, and other potential biases. ImageJ software was used for IHCH scoring quantification and Masson trichrome staining analysis. The H score was calculated as: (percentage of cells with 0 intensity) × 0 + (percentage of cells with 1+ intensity) × 1 + (percentage of cells with 2+ intensity) × 2 + (percentage of cells with 3+ intensity) × 3, ultimately yielding a continuous protein expression value from 0 to 300.

[0053] 4. Drug target screening

[0054] The target protein selection criteria for drug target screening are defined as follows: S-I upregulated proteins must meet the following conditions: S-II / S-I logFC < -2 (BH-corrected P < 0.05), S-I / Normal tissue (N) logFC > 1 (BH-corrected P < 0.05), and S-II not exceeding N; S-II upregulated proteins must meet the following conditions: S-II / S-I logFC > 3 (BH-corrected P < 0.05), S-II / N logFC > 2.5 (BH-corrected P < 0.05), and S-I not exceeding N. Additional criteria include: upregulated protein abundance above the lower quartile, belonging to the GSEA frontier subset genes, and druggability combined_LR > 1.

[0055] To investigate the impact of target protein expression levels on the pathophysiological state of patients, a linear regression model was used to analyze the association between relative protein abundance and multiple biological indicators. Relative target protein abundance was used as the independent variable, while the dependent variables included: a) collagen deposition area (the percentage of collagen fibers in the total field of view obtained through Masson's trichrome staining); and b) immune cell infiltration (expressed as the H score of CD45-positive cells). Univariate linear regression analysis was used to fit the relationship between each dependent variable and protein abundance, outputting standardized regression coefficients (β), 95% confidence intervals, t-values, and corresponding p-values ​​(statistical significance was defined as P < 0.05).

[0056] 5. In vitro experiments

[0057] (1) Cell culture

[0058] Human benign prostatic hyperplasia cell line BPH-1 (Pronosai, CL-0865), human prostatic myofibroblast immortalized cell line WPMY-1 (Pronosai, CL-0467), and human non-tumorigenic epithelial cell line RWPE-1 (Pronosai, CL-0143) were all cultured in a humidified incubator at 37°C and 5% CO2. BPH-1 and RWPE-1 cells were cultured in RPMI-1640 medium (Pronosai, PM150110), and WPMY-1 cells were cultured in DMEM medium (Pronosai, PM150210). Both media were supplemented with 10% fetal bovine serum (FBS, Pronosai, 164210-50) and 1% penicillin-streptomycin (Pronosai, PB180120). When cell confluence reached 80%-90%, cells were passaged using 0.25% trypsin-EDTA (Pronosai, PB180225) and routinely screened for mycoplasma contamination using the MycoAlert PLUS assay kit (Lonza, LT07-710). All experiments used cells with ≤20 passages.

[0059] (2) Transient transfection with small interfering RNA

[0060] Small interfering RNA (siRNA) was synthesized by Gemma Gene and transfected into prostate cells using jetPRIME (Polyplus) (available from Wuhan Pronosei Life Sciences Co., Ltd.) according to the manufacturer's instructions. Specific siRNA sequences are shown in Table 2. This invention uses two sequences designed for the same gene. To ensure successful knockdown, this is a standard procedure in the research field, similar to duplication, to exclude selection bias.

[0061] Table 2

[0062]

[0063] (3) Scratch healing test

[0064] Cell migration ability was assessed using a scratch healing assay. Cells were seeded in 6-well plates and cultured to 100% confluence. Scratches were created using 200 μL pipette tips. Cells were then cultured in serum-free RPMI 1640 medium, and images were taken at 0, 12, and 24 hours using an inverted microscope. The scratch healing index was analyzed using ImageJ software.

[0065] (4) Migration and invasion experiments

[0066] Cells were seeded in 24-well Transwell chambers (8 μm pores, Corning). 5 × 10⁶ cells / well 4 Cells were suspended in 200 μL of serum-free RPMI 1640 medium and seeded into the upper chamber; 600 μL of RPMI 1640 medium containing 10% FBS was added to the lower chamber. In the invasion assay, the chamber membrane was coated with 20 μL of matrix gel (Kornig) before seeding. After 24 hours of incubation, unmigrated / invaded cells in the upper chamber were gently removed with a cotton swab. The chamber membrane was fixed with 4% paraformaldehyde for 15 minutes and stained with 0.1% crystal violet for 30 minutes. Five fields of view were randomly selected under an inverted microscope to count the number of cells that had penetrated the membrane.

[0067] (5) Sirius red staining

[0068] Cells were fixed with 4% paraformaldehyde (PFA) at room temperature for 15 minutes and washed three times with PBS. They were then stained with modified Sirius red staining solution (Solarbio, catalog number: G1473) at 37°C for 20 minutes, briefly rinsed with distilled water, dehydrated with graded ethanol, cleared with xylene, and mounted with neutral resin. Collagen fibers appeared red under bright field.

[0069] (6) RNA extraction and real-time quantitative PCR

[0070] Total RNA was extracted from cells using the FastPure Cell / Tissue Total RNA Extraction Kit V2 (Novizumab) according to the manufacturer's instructions. RNA was then reverse transcribed into cDNA using the HiScript III RT SuperMix (Novizumab). Real-time quantitative PCR was performed using the CFX96 real-time PCR system (Bio-Rad) and the ChamQ Universal SYBR qPCR Master Mix (Novizumab). Relative RNA levels were calculated using the 2-ΔΔCt method and corrected using human peptidylprolyl isomerase A (PPIA) rRNA expression as an internal control. All mRNA values ​​in this study are averages of three replicates. Primer sequences are shown in Table 3.

[0071] Table 3

[0072]

[0073] (7) Protein blot analysis

[0074] Total protein from cells or tissues was extracted on ice for 30 min using RIPA lysis buffer (Solarbio) containing 1× protease inhibitor mixture (Solarbio) and benzyl sulfonyl fluoride (PMSF, Solarbio). The lysis buffer was centrifuged at 14,000×g for 15 min at 4 °C, and the supernatant was collected. Protein concentration was determined using a BCA protein quantification kit (Solarbio). An equal volume of protein (20 μg / lane) was mixed with 5× loading buffer, boiled at 95 °C for 10 min, and separated by 7.5%–12.5% ​​SDS-PAGE (NCMBiotech, Express Cast PAGE) in Tris-glycine electrophoresis buffer (Yeasen, TF101). Proteins were transferred to a 0.22 μm polyvinylidene fluoride (PVDF) membrane (Millipore, IPFL00010) and blocked at room temperature with TBST containing 5% skim milk for 1 h. The membranes were incubated overnight at 4°C with primary antibodies (Table 1), including anti-LAMA5 (Abmart, PU606235M; 1:2000), anti-TP63 (Abmart, T55659S; 1:2000), and anti-GAPDH (Proteintech, 60004-1-Ig; 1:50,000). After washing with TBST, the membranes were incubated for 1 hour at room temperature with horseradish peroxidase (HRP)-labeled secondary antibody (1:3000; Cell Signaling Technology). Protein bands were visualized using ECL substrate (Abbkine), and density analysis was performed using ImageJ software for quantification.

[0075] (8) Quantitative analysis of fluorescent staining and special staining

[0076] EdU-positive cell quantification: ImageJ was used to process dual-channel fluorescence images, separating the red (EdU) and blue (DAPI-stained cell nuclei) channels, setting thresholds for each, and counting the cells. The EdU positivity rate was defined as the ratio of the red fluorescent area to the blue cell nucleus area, reflecting the proportion of proliferating cells.

[0077] Semi-quantitative analysis using Sirius red staining: Images were analyzed using ImageJ, and collagen fibers (red channel) were separated using the "color deconvolution" plugin. The average optical density and positive area of ​​the red channel were measured across the entire region of interest. The product of the average optical density and the positive area was defined as the integrated optical density (IOD), serving as a semi-quantitative indicator of collagen content.

[0078] 6. Statistical Analysis

[0079] Statistical analyses were performed using GraphPad Prism (version 9.5.1) or R Studio (version 4.2.2). Sample sizes were determined based on previous studies to ensure adequate statistical power, and all experiments were independently repeated at least three times. Normality of continuous variables was assessed using the Shapiro-Wilk test. For comparisons between two groups: unpaired t-tests were used for normally distributed continuous variables; the Mann-Whitney U test was used for non-normally distributed continuous variables; and chi-square (χ²) was used for categorical variables when the number of positive cases was ≥5. 2 The correlation coefficient (ρ) and p-value were compared. Fisher's exact test was used when the p-value was less than 5. Spearman's rank correlation analysis was used to assess the association between non-normally distributed or ordered variables, and the correlation coefficient (ρ) and p-value were reported. Statistical significance was defined as two-tailed p-value < 0.05. Data were expressed as mean ± standard deviation (SD) or median (interquartile range).

[0080] Experimental results:

[0081] To enable precise intervention for BPH, this invention screened subtype-specific proteins that were significantly upregulated compared to normal samples. Based on drug availability, six candidate target proteins for BPH were identified: LAMA5, COL4A2, COL7A1, COL4A1, COL6A3, and COL6A1.

[0082] See the experimental results. Figure 1 .

[0083] Figure 1 This is a graph showing drug target screening, including the impact of candidate drug targets on subtypes: a box scatter plot showing the protein abundance distribution of the samples, a linear regression forest plot showing the impact of differentially expressed proteins on clinical or pathological features, and a bar chart showing -log 10 (P-value).

[0084] from Figure 1 As can be seen, LAMA5 had the most significant effect on collagen deposition (CVF, β=7.8031 [6.498-9.108], P<0.001) and CD45 cell infiltration (CD45H score, β=20.8057 [13.780-27.831], P<0.001).

[0085] Considering the important role of LAMA5 in the signaling function of key structural molecules in the extracellular matrix, we selected LAMA5 as a candidate intervention target for BPH.

[0086] Figure 2 This is a diagram validating the distribution of drug targets, including pathological validation of target proteins: the left image shows the immunohistochemical distribution of LAMA5 in the normal control group and collagen-deposited BPH, and the right image shows the quantitative statistical diagram of immunohistochemical analysis on a tissue microarray.

[0087] from Figure 2 As can be seen from the TMA test, LAMA5 in BPH was significantly higher than in normal tissue.

[0088] Figure 3 This is a diagram for validating the function of the drug target. After siRNA knockdown, qPCR and Western blot were used to detect the mRNA and protein expression levels of LAMA5 in BPH-1 / WPMY-1 / RWPE-1 cells; i. Sirius Red staining was used to detect collagen deposition in WPMY-1 cells after LAMA5 knockdown (scale bar 1.5 mm); j. Scratch assay was used to assess the migration ability of WPMY-1 cells after LAMA5 knockdown (scale bar 1.5 mm).

[0089] from Figure 3 It can be seen that knocking down LAMA5 in BPH-1, WPMY-1 and RWPE-1 cell lines can inhibit collagen deposition (Sirius red staining) and cell migration (scratch assay).

[0090] This invention, through a series of functional verification experiments, demonstrates that intervention (e.g., knockdown) of the LAMA5 gene or protein can produce significant beneficial therapeutic effects, and these effects are supported by clear experimental data: such as... Figure 3 As shown, in the three cell lines BPH-1, WPMY-1, and RWPE-1, which are closely related to the pathological progression of BPH, the Sirius red staining and scratch assay results after LAMA5 knockdown clearly showed that the collagen deposition level and cell migration ability of the LAMA5 knockdown group were significantly reduced compared with the control group. The Sirius red staining results directly indicated that LAMA5 knockdown effectively reduced the synthesis and deposition of collagen fibers in the above three cell lines, significantly improving the abnormal fibrotic state of the extracellular matrix. The scratch assay results confirmed that LAMA5 knockdown significantly inhibited the migration ability of BPH-1, WPMY-1, and RWPE-1 cells, reduced the invasion and spread of abnormal cells, thereby inhibiting the proliferation and infiltration of diseased tissues and blocking the pathological progression of BPH at the cellular level. In addition, LAMA5 knockdown also significantly inhibited the abnormal production of extracellular matrix, avoiding tissue fibrosis caused by excessive extracellular matrix accumulation, further synergistically improving the fibrotic microenvironment of diseased tissues in patients with collagen deposition-type BPH, and alleviating core clinical symptoms such as urethral compression.

[0091] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. Application of LAMA5 gene or protein in the preparation of drugs for the treatment of benign prostatic hyperplasia.

2. The application according to claim 1, characterized in that, The benign prostatic hyperplasia mentioned is collagen deposition type benign prostatic hyperplasia.

3. The application of reagents that inhibit LAMA5 gene expression or LAMA5 protein activity in the preparation of drugs for treating benign prostatic hyperplasia.

4. The application according to claim 3, characterized in that, The benign prostatic hyperplasia mentioned is collagen deposition type benign prostatic hyperplasia.

5. The application according to claim 3, characterized in that, The reagent for inhibiting LAMA5 gene expression includes siRNA; wherein the sequence of the sense strand of the siRNA is shown in SEQ ID No. 1 and the sequence of the antisense strand is shown in SEQ ID No. 2; or the sequence of the sense strand of the siRNA is shown in SEQ ID No. 3 and the sequence of the antisense strand is shown in SEQ ID No.

4.

6. A pharmaceutical composition for treating benign prostatic hyperplasia, characterized in that, The pharmaceutical composition comprises: a reagent that inhibits LAMA5 gene expression or a reagent that inhibits LAMA5 protein activity.

7. The pharmaceutical composition according to claim 6, characterized in that, The benign prostatic hyperplasia mentioned is collagen deposition type benign prostatic hyperplasia.

8. The pharmaceutical composition according to claim 6, characterized in that, The reagent for inhibiting LAMA5 gene expression includes siRNA; wherein the sequence of the sense strand of the siRNA is shown in SEQ ID No. 1 and the sequence of the antisense strand is shown in SEQ ID No. 2; or the sequence of the sense strand of the siRNA is shown in SEQ ID No. 3 and the sequence of the antisense strand is shown in SEQ ID No.

4.

9. A siRNA that inhibits LAMA5 gene expression, characterized in that, The sequence of the sense strand of the siRNA is shown in SEQ ID No. 1, and the sequence of the antisense strand is shown in SEQ ID No. 2; or the sequence of the sense strand of the siRNA is shown in SEQ ID No. 3, and the sequence of the antisense strand is shown in SEQ ID No. 4.

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