SiRNA for targeted knockdown of ITGbeta1 and application of siRNA

Abstract

The invention particularly discloses siRNA for targeted knockdown of ITG beta1 and application of the siRNA, and relates to the field of molecular biology and biological medicine. The siRNA disclosed by the invention has the advantages that cell transfection is carried out by constructing a siRNA nucleotide sequence, and cell proliferation experiment results prove that the siRNA disclosed by the invention can obviously interfere with expression of ITGbeta1 and obviously inhibit proliferation and migration capabilities of human hepatoma carcinoma cell lines HepG2 and LM3, so that targeted therapy of metabolic dysfunction related fatty liver diseases is realized, and the siRNA has a good application prospect. Meanwhile, the malignant transformation from MASLD to HCC is effectively inhibited.

Description

Technical Field

[0001] This invention relates to the fields of molecular biology and biomedicine, and in particular to a siRNA that targets and knocks down ITGβ1 and its applications. Background Technology

[0002] Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent chronic liver disease worldwide, particularly in Western countries, affecting approximately 20% of the global population. MASLD is a metabolic disorder primarily caused by a combination of genetic, dietary, and lifestyle factors. It begins with simple steatosis and, as the disease progresses, can develop into metabolic dysfunction-associated steatohepatitis (MASH), and further deterioration can lead to cirrhosis and even hepatocellular carcinoma (HCC). Currently, there are no effective methods to prevent MASLD; therefore, exploring its potential pathogenic mechanisms and therapeutic targets is crucial.

[0003] Under normal circumstances, the immune system plays a role in monitoring and eliminating abnormal cells. However, in the microenvironment of MASLD, this process may be disrupted, leading to immune dysregulation and allowing tumor cells to evade immune surveillance. Previous studies have shown that different T lymphocyte subsets play different roles in MASH: CD4+ T lymphocytes suppress tumor cell growth through immune surveillance, while CD8+ T lymphocytes are abundant in the MASLD microenvironment, causing liver inflammation. Regulatory T cells (Tregs), a subset of CD4+ T lymphocytes, are characterized by the expression of the major transcription factor forkhead box protein P3 (FOXP3), maintaining immune tolerance and immune homeostasis. Studies have shown that Tregs, as a subset of CD4+ T lymphocytes, not only did not show downregulation in MASLD patients but also exhibited increased infiltration. Therefore, Tregs may be a potential biomarker for the progression of MASH to HCC, and targeting Tregs may be an effective strategy for treating MASH, but a clear mechanism to explain their pathogenic potential is currently lacking.

[0004] Integrins are an important class of transmembrane proteins on the cell surface, typically composed of heterodimers of α and β subunits. They mediate interactions between cells and between cells and the extracellular matrix, playing crucial roles in cell proliferation, migration, and signal transduction. Integrin β1 (ITGβ1), a member of the integrin family, is enriched in various cell types, including immune cells and endothelial cells, and participates in cell adhesion and inflammatory responses. Previous literature has reported that ITGβ1 promotes liver inflammation in MASH mice by mediating cell adhesion, but research has primarily focused on interactions between hepatocytes, monocytes, and endothelial cells. The mechanisms underlying the interaction between ITGβ1 and immune cells are not yet fully understood.

[0005] Current research in China has reported a close relationship between Tregs and the development and progression of various cancers, including hepatocellular carcinoma, breast cancer, colorectal cancer, lung cancer, and gastric cancer. For example, in lung cancer, lung cancer cells can secrete cytokines such as transforming growth factor-β (TGF-β) and interleukin-10 (IL-10), inducing Treg proliferation and differentiation. In breast cancer, breast cancer cells secrete chemokine ligands such as C-Cmotif ligand (CCL)22 and CCL1, which bind to C-C chemokine receptors (CCR)4 and CCR8 on the surface of Tregs, respectively, guiding Tregs to migrate to tumor tissue. Recently, an increasing number of studies have shown that Tregs play an important role in the progression of metabolic-associated fatty liver disease. Foreign studies have found that the interaction between Treg cells and neutrophil extracellular traps (NETs) can enhance the mitochondrial oxidative phosphorylation (OXPHOS) pathway and induce CD4+. + The initial differentiation of T cells into Tregs suppresses immune surveillance and reduces the cytotoxicity of immune cells against tumor cells. Furthermore, the dual-regulatory protein amphiregulin (AREG) of Tregs can activate hepatic stellate cells (HSCs) through the epidermal growth factor receptor (EGFR) signaling pathway, thereby promoting liver fibrosis and insulin resistance in MASH. However, the crosstalk between Tregs and ITGβ1 in MASLD remains unknown. Summary of the Invention

[0006] The purpose of this invention is to provide a siRNA that targets and knocks down ITGβ1 and its application. By knocking down ITGβ1, the activity of Tregs and their regulation of tumor cells are inhibited, thereby reducing the proliferation and migration of tumor cells and achieving targeted treatment of fatty liver disease related to metabolic dysfunction.

[0007] The above-mentioned technical objective of the present invention is achieved through the following technical solution:

[0008] A siRNA that targets and knocks down ITGβ1, wherein the sense strand sequence of the siRNA is shown in SEQ ID NO.1, i.e., 5'-GCUCAGUCUUACUAAUAAATT-3', and the antisense strand sequence is shown in SEQ ID NO.2, i.e., 5'-UUUAUUAGUAAGACUGAGCTT-3'.

[0009] The present invention also provides the use of siRNA that targets and knocks down ITGβ1 in the preparation of a biological agent that inhibits ITGβ1 expression, the biological agent being used for targeted treatment of fatty liver disease associated with metabolic dysfunction.

[0010] The present invention also provides the use of siRNA that targets and knocks down ITGβ1 in the preparation of a drug for targeted treatment of fatty liver disease associated with metabolic dysfunction.

[0011] The present invention also provides a medicament for treating lung adenocarcinoma, comprising siRNA that targets and knocks down ITGβ1 as described above.

[0012] The present invention also provides a biological agent for targeting and knocking down ITGβ1, comprising the siRNA for targeting and knocking down ITGβ1 as described above.

[0013] The present invention also provides a drug for metabolic dysfunction-related fatty liver disease, comprising siRNA that targets and knocks down ITGβ1 as described above.

[0014] In summary, the present invention has the following beneficial effects: The present invention constructs siRNA nucleotide sequences for cell transfection, and the cell proliferation experiment results confirm that the siRNA of the present invention can significantly interfere with the expression of ITGβ1 and significantly inhibit the proliferation and migration ability of human hepatocellular carcinoma cell lines HepG2 and LM3, thereby targeting the treatment of metabolic dysfunction-related fatty liver disease, while effectively inhibiting the malignant transformation of MASLD to HCC. Attached Figure Description

[0015] Figure 1 This is a schematic diagram showing the dynamic changes in liver pathology, serum enzymes, and lipid levels in model mice;

[0016] Figure 2 This is a schematic diagram of single-cell RNA sequencing and flow cytometry revealing T lymphocytes in the liver of MASLD mice.

[0017] Figure 3 This is a schematic diagram of the composition of T lymphocytes in the spleen of a MASLD mouse;

[0018] Figure 4 This is a schematic diagram of the function of T lymphocytes in MASLD mice;

[0019] Figure 5 This is a schematic diagram of the composition of T lymphocyte subsets in MASLD mice;

[0020] Figure 6 This is a schematic diagram of the Treg structure of MASLD mice;

[0021] Figure 7 This is a schematic diagram of Treg function in MASLD mice;

[0022] Figure 8 This is a schematic diagram of the Treg structure in the spleen of a MASLD mouse.

[0023] Figure 9 This is a schematic diagram illustrating the subtype identification of Treg and its pathogenic mechanism;

[0024] Figure 10 This is a schematic diagram of the metabolic activity of Tregs and the cell adhesion-related genes in the pseudo-temporal analysis trajectory of Tregs;

[0025] Figure 11 This is a schematic diagram illustrating the significant upregulation of ITGβ1 in HCC patients, accompanied by poor prognostic outcomes.

[0026] Figure 12 This is a schematic diagram showing how ITGβ1 in MASLD mice enhances and promotes EMT by binding to FOXP3.

[0027] Figure 13 This is a schematic diagram illustrating the proliferation and migration capacity of HCC cells and the expression levels of genes related to cell adhesion. Detailed Implementation

[0028] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings. These embodiments do not constitute a limitation on the present invention.

[0029] 1. Clinical specimens

[0030] From June 2023 to July 2024, this study collected tumor tissue and adjacent normal tissue from 10 patients with MASLD confirmed by histopathological examination at the Affiliated Hospital of Nantong University. All patients had not received chemotherapy or radiotherapy prior to surgery. Collected specimens were immediately cryopreserved in liquid nitrogen until use. This study was approved by the Ethics Committee of Nantong University (No.: Tongda Lunshen (2023) 9) and conducted in accordance with the ethical principles of the Declaration of Helsinki.

[0031] 2. Cell lines

[0032] Human hepatocyte cell line THLE2 was purchased from Yimo Biotechnology (China) and cultured in THLE2-specific medium. Human HCC cell lines (HepG2 and LM3) were also purchased from Yimo Biotechnology (China) and cultured in DMEM medium (HyClone, USA) supplemented with 10% fetal bovine serum (FBS) (Gibco, USA). All cells were negative for mycoplasma. All cells were cultured in a 37°C incubator containing 5% CO2.

[0033] 3. Animals and animal models

[0034] Six-week-old male C57BL / 6 mice were purchased from Shanghai Laboratory Animal Science Co., Ltd. (China) and randomly divided into three groups: a normal diet control group, a high-fat diet group, and a high-fat diet + tumor-inducing group. The normal diet control group was fed a normal diet (ND) daily to establish a normal mouse model. The high-fat diet group was fed a high-fat diet (HFD, 1% bile acids, 4% cholesterol, 10% lard, 10% egg yolk powder, and 75% basal diet) daily to establish a MASLD mouse model. The high-fat diet + tumor-inducing group, in addition to a 60% high-fat diet, was administered a daily dose of 25 mg / kg of olive oil diluted with the liver cancer inducing drug 2-acetaminophen (2-AAF) (Sigma, USA) via gavage to establish a MASLD-HCC mouse model. Mice were placed in a sterile environment (12-hour light-dark cycle, 23±1℃, 60% relative humidity) with free access to water and food. All surgical procedures were performed in a barrier environment at the Experimental Animal Center of Nantong University and were approved by the Experimental Animal Ethics Committee of Nantong University (No.: P20230224-009).

[0035] 4. siRNA construction

[0036] The siRNA-ITGB1 nucleotide sequence: the sense strand is 5'-GCUCAGUCUUACUAAUAAATT-3', and the antisense strand is 5'-UUUAUUAGUAAGACUGAGCTT-3', provided by Suzhou Genecast Co., Ltd. (China).

[0037] 5. Experimental Procedures and Methods

[0038] 5.1 Cell Culture

[0039] 5.1.1 Cell resuscitation

[0040] (1) Take out the DMEM complete medium and THLE2 special medium and preheat them in a 37℃ water bath for 15 minutes.

[0041] (2) Remove the frozen cells from the liquid nitrogen and immediately place them in a 37°C water bath and shake them rapidly to thaw the cells within 1 minute.

[0042] (3) After the 1 ml cell suspension melts, add it to a 15 ml centrifuge tube containing 9 ml of complete culture medium and centrifuge at 500 g for 5 minutes.

[0043] (4) After centrifugation, discard the supernatant, add 1 ml of complete culture medium to resuspend the cells, slowly transfer the cell suspension into a culture flask containing 4 ml of complete culture medium, mix well in a cross shape, and then place it in a 37°C carbon dioxide incubator for culture.

[0044] 5.1.2 Cell passage (adherent cells)

[0045] (1) Use a microscope to observe the cell density and ensure that the density reaches 80%-90%.

[0046] (2) Take out DMEM complete medium, THLE2 special medium, PBS and trypsin, and put them into a 37℃ water bath for 15 minutes to preheat.

[0047] (3) Discard the culture medium in the culture flask, wash twice with PBS, then add 1 ml of trypsin to digest for 3 minutes. Observe under a microscope until the cell morphology changes from irregular to round. Add 2 ml of complete culture medium to stop digestion, pipette the cells off, transfer to a 15 ml centrifuge tube and centrifuge at 500g for 5 minutes.

[0048] (4) After centrifugation, discard the supernatant, add 1 ml of complete culture medium to resuspend the cells, adjust the cell density, transfer them to a culture flask containing 4 ml of complete culture medium, mix well, and then place them in a 37°C carbon dioxide incubator for culture.

[0049] 5.1.3 Cell cryopreservation

[0050] (1) Use a microscope to observe the cell density and ensure that the density reaches 80%-90%.

[0051] (2) Take out DMEM complete medium, THLE2 special medium, PBS and trypsin, and put them into a 37℃ water bath for 15 minutes to preheat.

[0052] (3) Discard the culture medium in the culture flask, wash twice with PBS, then add 1 ml of trypsin to digest for 3 minutes. Observe under a microscope until the cell morphology changes from irregular to round. Add 2 ml of complete culture medium to stop digestion, pipette the cells off, transfer to a 15 ml centrifuge tube and centrifuge at 500g for 5 minutes.

[0053] (4) After centrifugation, discard the supernatant, add 1 ml of cell cryopreservation solution to resuspend the cells, add them to a cell cryopreservation tube, and place them in liquid nitrogen for cryopreservation.

[0054] 5.1.4 Cell Count

[0055] (1) After routine digestion of cells, centrifuge at 500g for 5 minutes.

[0056] (2) After centrifugation, discard the supernatant and resuspend in 1 ml of complete culture medium.

[0057] (3) Take out the disposable cell counting plate, peel off the surface film, inject 20 microliters of cell suspension into the counting well, and let it stand for 1 minute.

[0058] (4) Place the cell counting chamber into an automated cell counter for counting.

[0059] 5.2 Cell Transfection

[0060] (1) Use a microscope to observe the cell density and ensure that the density reaches 80%-90%.

[0061] (2) Take out DMEM complete medium, THLE2 special medium, PBS and trypsin, and put them into a 37℃ water bath for 15 minutes to preheat.

[0062] (3) Discard the culture medium in the culture flask, wash twice with PBS, then add 1 ml of trypsin to digest for 3 minutes. Observe under a microscope until the cell morphology changes from irregular to round. Add 2 ml of complete culture medium to stop digestion, pipette the cells off, transfer to a 15 ml centrifuge tube and centrifuge at 500g for 5 minutes.

[0063] (4) After centrifugation, discard the supernatant, add complete culture medium to resuspend the cells, adjust the cell density, and then spread them into 6-well plates. Mix them in a cross pattern and then place them in a 37°C carbon dioxide incubator for culture.

[0064] (5) Observe the cell density under a microscope after 24 hours. Transfection is performed when the cell density is 60-80%.

[0065] (6) Remove the siRNA and place it on ice to thaw.

[0066] (7) Take out two 1.5 ml EP tubes, add 125 μL of basal culture medium to each tube, then add siRNA and Lipo3000 respectively, mix well and let stand for 3 minutes.

[0067] (8) Mix the two EP tubes and incubate at room temperature for 10 minutes to form a transfection complex.

[0068] (9) Discard the original culture medium in the well plate and add the basal culture medium.

[0069] (10) Add the transfection complex to a 6-well plate, mix well in a cross pattern, and then incubate in a 37°C carbon dioxide incubator.

[0070] (11) Change the medium after 6-8 hours, replace the liquid in the 6-well plate with complete culture medium and continue culturing.

[0071] (12) Harvest after 48 hours, extract RNA or protein, and detect transfection efficiency by RT-qPCR or Western blot (WB) for subsequent experiments.

[0072] 5.3 Cell proliferation experiment

[0073] (1) After routine digestion of cells to obtain cell pellet, cells are resuspended in complete culture medium. 20 μL of cell suspension is added to a disposable cell counting chamber for counting.

[0074] (2) After adjusting the cell density, the cells were seeded into a 96-well plate at a density of 2000-3000 cells per well, with a volume of 100 μL per well.

[0075] (3) Place the cells in a 37°C carbon dioxide incubator overnight, and then process the cells according to experimental requirements.

[0076] (4) Take out the 96-well plate at 24 hours, 48 ​​hours, 72 hours and 96 hours respectively, prepare CCK8 working solution in centrifuge tubes, prepare it in the dark according to the ratio of basal culture: CCK8 = 9:1, discard the original culture medium in the well, add 100 μL of CCK8 working solution to each well, and incubate in a 37℃ incubator in the dark for 1-2 hours.

[0077] (5) Set the microplate reader to 37°C for preheating. After the well plate is incubated, put it into the microplate reader and measure the absorbance at 450 nm.

[0078] (6) Calculate cell proliferation capacity (%) = (sample OD value - blank OD value) / (sample control OD value - blank OD value) × 100% to obtain the results, and finally perform statistical analysis.

[0079] 5.4 Cell invasion and migration assays (Transwell assay)

[0080] invasion

[0081] (1) Take out the 24-well plate and put the small chamber into the well.

[0082] (2) Remove the matrix gel and dilute it with basal culture medium (matrix gel: basal culture medium = 1:4).

[0083] (3) Spread the diluted matrix gel to the bottom of the chamber and place it in a 37°C carbon dioxide incubator for 20 minutes.

[0084] (4) After routine digestion of cells to obtain cell pellet, cells are resuspended in complete culture medium. 20 μL of cell suspension is added to a disposable cell counting chamber for counting.

[0085] (5) According to 1×10 per hole 5 Dilute the cells to a specific number of cells and add them to the upper chamber.

[0086] (6) Add 600 μL of complete culture medium containing 20% ​​fetal bovine serum to the lower chamber.

[0087] (7) Change the fluid in the lower chamber every other day.

[0088] (8) After 48 hours and 72 hours, the cells were fixed by immersing the chambers in paraformaldehyde for 10 minutes.

[0089] (9) Clean the chamber with PBS.

[0090] (10) Immerse the chamber in crystal violet staining solution for 10 minutes.

[0091] (11) Use a cotton swab to clean the bottom of the chamber.

[0092] (12) Observe under a microscope, take pictures of the appropriate field of view, and analyze and quantify using ImageJ software.

[0093] migrate

[0094] (1) Take out the 24-well plate and put the small chamber into the well.

[0095] (2) After routine digestion of cells to obtain cell pellet, cells are resuspended in complete culture medium. 20 μL of cell suspension is added to a disposable cell counting chamber for counting.

[0096] (3) According to 1×10 per hole 5 Dilute the cells to a specific number of cells and add them to the upper chamber.

[0097] (4) Add 600 μL of complete culture medium containing 20% ​​fetal bovine serum to the lower chamber.

[0098] (5) Change the fluid in the lower chamber every other day.

[0099] (6) After 48 hours and 72 hours, the cells were fixed by immersing the chambers in paraformaldehyde for 10 minutes.

[0100] (7) Clean the chamber with PBS.

[0101] (8) Immerse the chamber in crystal violet staining solution for 10 minutes.

[0102] (9) Use a cotton swab to clean the bottom of the chamber.

[0103] (10) Observe under a microscope, take pictures of the appropriate field of view, and analyze and quantify using ImageJ software.

[0104] 5.5 Protein Immunoblotting

[0105] (1) Tissue protein extraction: Weigh 20 mg of liver tissue into a 1.5 mL EP tube, add 500 μL of RIPA lysis buffer containing protease inhibitors and phosphatase inhibitors, add two small steel balls to the EP tube, and grind at low temperature in a tissue homogenizer at 65 Hz for 90 seconds. After removal, centrifuge at 12000 g for 15 minutes in a 4°C centrifuge, and collect the supernatant into a new EP tube. Determine the protein concentration using a BCA kit to adjust the loading volume. Add 5× protein loading buffer, mix well, boil in a water bath for 10 minutes, and store at -20°C.

[0106] (2) Cell protein extraction: After routine cell digestion to obtain cell pellet, add 500 μL of RIPA containing protease inhibitors, or directly discard the culture medium in the well plate and add 500 μL of RIPA containing both protease inhibitors and phosphatase inhibitors. Scrape off the cell pellet with a cell scraper and add it to a 1.5 mL EP tube, place on ice for 30 minutes for lysis. After lysis, centrifuge at 12000 g for 15 minutes at 4°C, and collect the supernatant in a new EP tube. Determine the protein concentration using BCA to adjust the loading volume. Add 5× protein loading buffer, mix well, boil in a water bath for 10 minutes, and store at -20°C for electrophoresis.

[0107] (3) Electrophoresis: Take out the sample and place it on ice to thaw and mix it. Put the prepared gel into the electrophoresis tank with the short plate inside and the long plate outside. After fixing it, add the prepared electrophoresis solution to cover the inner tank. Remove the gel comb and blow the sample well with a pipette to remove air bubbles. Add the marker and sample in order from left to right. After the sample is added, continue to add electrophoresis solution until the entire tank is filled. Cover the electrophoresis tank with the positive and negative terminals. Turn on the electrophoresis instrument and start it at a low voltage of 90V. After the electrophoresis stabilizes, increase the pressure to 120V until the marker reaches the bottom and disperses at the desired molecular position. Then the electrophoresis is finished.

[0108] (4) Dry transfer: Place filter paper soaked in transfer solution in the transfer tank, place the NC membrane on the filter paper, remove the gel from the electrophoresis tank, use a rocker to remove the long plate of the gel, leaving the gel on the short plate, cut off the unnecessary gel, place the required gel on the NC membrane, and cover it with another layer of filter paper soaked in transfer solution. Avoid the generation of air bubbles during this process. After leveling it with a roller, put the lid on and place it in the dry transfer instrument at 25V for 15 minutes.

[0109] (5) Sealing: Take out the dried NC membrane, wash it twice in TBST, then invert it into an incubation box containing 5% skim milk, place it on a shaker and shake it at low speed, and seal it at room temperature for 2 hours.

[0110] (6) Incubation with primary antibody:

[0111] ① Remove the sealed NC membrane and rinse it twice with TBST.

[0112] ② After diluting the antibody with antibody diluent, add it to the incubation box.

[0113] ③ Cut the bands according to the molecular weight of the target protein and invert the corresponding molecule bands into the corresponding antibody grids.

[0114] ④ Place the antibody incubation box on a shaker in a 4°C refrigerator overnight (at least 12 hours).

[0115] (7) Incubation with secondary antibody:

[0116] ① Remove the antibody incubation box, recover the primary antibody and place it in a 4°C refrigerator.

[0117] ② Reverse the membrane and perform TBST cleaning 5 times, 10 minutes each time.

[0118] ③ Dilute the secondary antibody with 5% skim milk.

[0119] ④ Add the secondary antibody to the corresponding antibody compartment according to the species of the target protein, invert the strip, place it on a shaker and shake it at low speed, and incubate at room temperature for 2 hours.

[0120] ⑤ Return the membrane to its normal position and perform TBST cleaning 5 times, 10 minutes each time.

[0121] (8) ECL color development and exposure:

[0122] ① Prepare the required amount of developer in a light-proof EP tube.

[0123] ② Turn on the automatic imaging system, place the NC film on the developing plate, evenly drop the developing solution onto the NC film and expose it for an appropriate time.

[0124] ③ Save the strip and analyze the grayscale values ​​using ImageJ software.

[0125] (9) Reagents and formulations used in WB

[0126] Prepare 1×TBST

[0127] ① Add one packet of TBS dry powder to a 2-liter beaker.

[0128] ② Add 2 liters of ddH2O.

[0129] ③ Add 2 ml of Tween20 using a pipette.

[0130] ④ Place the beaker on a magnetic stirrer and vortex to mix.

[0131] ⑤ Dispense the mixed TBST into glass bottles and store at room temperature.

[0132] Prepare 5% skim milk

[0133] ①Weigh out 5 grams of skim milk powder and add it to a 500 ml beaker.

[0134] ② Add 100 ml of ddH2O.

[0135] ③ Place the beaker on a magnetic stirrer and vortex to mix.

[0136] ④ Pour the mixed 5% skim milk into a glass bottle and store it in a refrigerator at 4°C.

[0137] Prepare 1× electrophoresis solution

[0138] ①Weigh 6.04 g Tris, 37.6 g Gly and 2 g SDS and add them to a 2-liter beaker.

[0139] ② Add 2 liters of ddH2O.

[0140] ③ Place the beaker on a magnetic stirrer and vortex to mix.

[0141] ④ Dispense the mixed electrophoresis solution into glass bottles and store at room temperature.

[0142] Prepare 1× transfer solution

[0143] ① Add 200 ml of 5× semi-dry transfer membrane solution, 200 ml of anhydrous ethanol and 600 ml of ddH2O to a 2-liter beaker.

[0144] ② Place the beaker on a magnetic stirrer and vortex to mix.

[0145] ③ Pour the mixed transfer solution into a glass bottle and store it in a 4°C refrigerator.

[0146] 5.6 BCA method for detecting protein concentration

[0147] (1) Melt the protein standard (concentration of 1 mg / mL) on ice, and prepare the required concentration of the BSA standard curve according to the table below. Take 20 μL of each of the ready-to-use BSA standard ① to ⑧ and add them to the 96-well plate.

[0148]

[0149] (2) Dilute the sample appropriately with 1×PBS (you can set several gradients, such as 2x, 4x, 8x dilution), and add 20 μL to the sample wells of the 96-well plate.

[0150] (3) Add 200 μL of colorimetric working solution to each well, mix thoroughly, cover with the 96-well plate cap, incubate at 37°C for 30 minutes, and cool to room temperature.

[0151] (4) Use an enzyme-linked immunosorbent assay (ELISA) reader to measure the absorbance at 562 nm for each sample and BSA standard.

[0152] (5) Plot a standard curve and calculate the protein concentration in the sample.

[0153] 5.7 Quantitative Real-Time PCR

[0154] (1) Tissue RNA extraction: Weigh 20 mg of liver tissue into a 1.5 mL EP tube, add 1 mL of Trizol, add two small steel balls into the EP tube, and place it in a tissue grinder for low temperature grinding at 65 Hz for 90 seconds.

[0155] (2) Cell RNA extraction: After routine digestion of cells to obtain cell pellet, place the pellet in a 1.5 mL EP tube and add 1 mL Trizol.

[0156] (3) Add 200 μL of chloroform, shake vigorously for 15 seconds, and let stand at room temperature for 3 minutes.

[0157] (4) Centrifuge at 4℃, 4000g, for 15 minutes, and take 500 μL of supernatant into a new EP tube.

[0158] (5) Add an equal amount of isopropanol, mix thoroughly, and centrifuge at 4°C for 4000g for 10 minutes.

[0159] (6) Discard the supernatant and retain the precipitate as much as possible. Add 500 μL of 75% anhydrous ethanol to wash the precipitate twice. Centrifuge at 4°C, 2500g, for 5 minutes.

[0160] (7) Discard the supernatant, retain as much of the precipitate as possible, and add 20 μL of DEPC water to dissolve the RNA.

[0161] (8) Heat in a 60℃ water bath for 10 minutes, and use a spectrophotometer to determine and record the RNA concentration.

[0162] Reverse transcription (operated on ice)

[0163] (1) Removal of genomic DNA

[0164] Prepare the following reaction system in a 200 μL EP tube:

[0165]

[0166] Gently blow and mix to avoid air bubbles, 42°C, 2 minutes.

[0167] (2) Reverse transcription into cDNA

[0168] Add 4 μL of 5×HiScript III qRT SuperMix, mix well by pipetting, and then perform PCR reaction. Store the product at -20℃.

[0169]

[0170] RT-qPCR reaction:

[0171] ①The reaction system in each well of the PCR well.

[0172]

[0173] The template cDNA was diluted with DEPC water before being added.

[0174] ②RT-qPCR reaction conditions.

[0175]

[0176] (3) The relative expression level of gene mRNA was analyzed by the 2-ΔΔCt method.

[0177] 5.8 Flow cytometry

[0178] Peripheral blood:

[0179] (1) Dilute mouse whole blood with diluent.

[0180] (2) Gently cover the diluted whole blood onto the mouse peripheral blood mononuclear cell (PBMC) separation solution and centrifuge at 650g for 30 minutes.

[0181] (3) After centrifugation, take the mononuclear cell layer of the second middle layer and transfer it to a new centrifuge tube.

[0182] liver:

[0183] (1) Wash the liver with PBS and digest it in a culture dish containing type II collagenase (Solepro).

[0184] (2) After cutting the liver into small pieces, place it in a 70μm filter (Biologix, China), grind it with a grinding rod, and add appropriate amounts of DMEM culture medium (HyClone, USA) for digestion and filtration. Centrifuge at 500g for 5 minutes.

[0185] (3) Discard the supernatant, add PBS (Solepro, China) containing 2% fetal bovine serum (Gibco, USA) to wash, centrifuge at 500g for 5 minutes to obtain mouse liver non-parenchymal cells (NPC).

[0186] (4) Dilute Percoll (Solepro, China) to 40% and 70% concentrations, resuspend NPCs in 40% Percoll, then gently cover them with 70% Percoll, and centrifuge at 650g for 30 minutes to obtain liver mononuclear cells (MNCs).

[0187] spleen:

[0188] (1) Wash the spleen with PBS.

[0189] (2) Place the spleen in a 70μm filter (Biologix, China) and cut it into pieces. Grind it with a grinding rod and add appropriate amounts of DMEM culture medium (HyClone, USA) for digestion and filtration. Centrifuge at 500g for 5 minutes.

[0190] (3) Discard the supernatant, add PBS (Solepro, China) containing 2% fetal bovine serum (Gibco, USA) to wash, centrifuge at 500g for 5 minutes.

[0191] (4) Discard the supernatant, add red blood cell lysis buffer, place on ice for 5 minutes, add PBS (Solepro, China) containing 2% fetal bovine serum (Gibco, USA) to stop the reaction, centrifuge at 300g for 10 minutes.

[0192] (5) Repeat the above steps until the cracks are completely red.

[0193] Single-cell suspensions from mouse PBMCs, liver MNCs, and spleen were stained with surface flow cytometry antibodies. The surface flow cytometry antibodies used included CD45, CD3, CD4, CD8, and CD25 (BioLegend, USA). Before nuclear antibody staining, cells were fixed and permeabilized with fixation and permeabilization buffer (BioLegend, USA). Then, nuclear staining was performed using the nuclear flow cytometry antibody FOXP3 (BioLegend, USA).

[0194] 5.9 Histopathology

[0195] (1) Take a 10 mm × 10 mm tissue block from a fresh mouse liver. One part is fixed in 4% paraformaldehyde and left for paraffin sectioning, and the other part is quick-frozen in liquid nitrogen for cryosectioning.

[0196] (2) After fixation for 24 hours, the tissues were embedded in paraffin and cut into 4-micrometer thick sections. Hematoxylin and eosin (H&E) staining was performed, and the sections were mounted with neutral resin after staining. For liquid nitrogen-frozen samples, the OCT-embedded samples were immediately cut into 8-micrometer thick sections on a cryostat and stained with Oil Red O. The sections were then mounted with glycerol gelatin after staining.

[0197] (3) Images were taken using a microscope and analyzed and quantified using ImageJ software.

[0198] 5.10 Immunohistochemistry (IHC)

[0199] Dewaxing and hydration: At room temperature, the sections were immersed in environmentally friendly dewaxing solution I for 10 minutes, environmentally friendly dewaxing solution II for 10 minutes, environmentally friendly dewaxing solution III for 10 minutes, anhydrous ethanol I for 5 minutes, anhydrous ethanol II for 5 minutes, and anhydrous ethanol III for 5 minutes. They were then washed with distilled water three times for 5 minutes each time.

[0200] (1) Antigen retrieval: Pour one packet of sodium citrate powder into 2 liters of PBS solution to prepare antigen retrieval solution, stir and heat to boiling, put the slide into the retrieval solution and boil for 15 minutes, then cool to room temperature. Wash 3 times with PBS, 5 minutes each time.

[0201] (2) Immunohistochemical circle drawing: Take out the slide, absorb the water, and draw a circle around the tissue with a pen.

[0202] (3) Inactivation of endogenous enzymes: Place the slices in a humidified chamber, add 3% hydrogen peroxide, and incubate at room temperature in the dark for 25 minutes. Wash three times with PBS for 5 minutes each time.

[0203] (4) Blocking non-specific sites: Dry the tissue, add 3% BSA evenly to the histochemistry zone, place it in a humidified box, and seal at room temperature for 30 minutes.

[0204] (5) Add primary antibody: Discard the blocking solution, add primary antibody, and place the slide flat in a humidified chamber and incubate overnight at 4°C.

[0205] (6) Rewarming: Rewarm to room temperature for 30 minutes, wash with PBS 3 times, 5 minutes each time.

[0206] (7) Add secondary antibody: blot dry, add HRP-labeled secondary antibody, and incubate at room temperature for 50 minutes. Wash 3 times with PBS for 5 minutes each time.

[0207] (8) Diaminobenzidine (DAB) color development: Blot dry the water, add freshly prepared DAB color development solution to the circle, control the color development time under the microscope, the positive color is brownish-yellow, rinse the section with tap water to stop the color development.

[0208] (9) Counterstaining cell nuclei: Counterstain with hematoxylin for 3 minutes, rinse with tap water, differentiate with hematoxylin differentiation solution for a few seconds, rinse with tap water, re-blue with hematoxylin blue solution, and rinse with tap water.

[0209] (10) Dehydration and mounting: Immerse the sections in 75% alcohol for 5 minutes, 85% alcohol for 5 minutes, anhydrous ethanol I for 5 minutes, anhydrous ethanol II for 5 minutes, n-butanol for 5 minutes, and xylene I for 5 minutes in sequence until they are dehydrated and transparent. After shaking off the water, mount the sections with mounting glue.

[0210] (11) Image acquisition: Observe under a microscope, take pictures of the appropriate field of view, and analyze and quantify using ImageJ software.

[0211] 5.11 Immunofluorescence (IF)

[0212] (1) Dewaxing and hydration: Under room temperature conditions, the sections were immersed in environmentally friendly dewaxing solution I for 10 minutes, environmentally friendly dewaxing solution II for 10 minutes, environmentally friendly dewaxing solution III for 10 minutes, anhydrous ethanol I for 5 minutes, anhydrous ethanol II for 5 minutes, and anhydrous ethanol III for 5 minutes in sequence, and washed with distilled water 3 times for 5 minutes each time.

[0213] (2) Antigen retrieval: Pour one packet of sodium citrate powder into 2 liters of PBS solution to prepare antigen retrieval solution, stir and heat to boiling, put the slide into the retrieval solution and boil for 15 minutes, then cool to room temperature. Wash with PBS 3 times, 5 minutes each time.

[0214] (3) Immunohistochemical circle drawing: Take out the slide, absorb the water, and draw a circle around the tissue with a pen.

[0215] (4) Blocking non-specific sites: Dry the tissue, add 3% BSA evenly to the histochemistry zone, place it in a humidified box, and seal at room temperature for 30 minutes.

[0216] (5) Add primary antibody: Discard the blocking solution, add primary antibody, and incubate the slides in a humidified chamber at 4°C overnight. Wash with PBS 3 times, 5 minutes each time.

[0217] (6) Add secondary antibody: Blot dry, add horseradish peroxidase (HRP) labeled secondary antibody, and incubate at room temperature for 50 minutes. Wash 3 times with PBS for 5 minutes each time.

[0218] (7) Counterstaining cell nuclei with 4',6-diamidino-2-phenylindole (DAPI): Add DAPI staining solution and incubate at room temperature in the dark for 10 minutes. Wash three times with PBS for 5 minutes each time.

[0219] (8) Quenching tissue autofluorescence: Add fluorescent quencher B solution for 5 minutes, then rinse with tap water for 10 minutes.

[0220] (9) Mounting: Mount the slide with anti-fluorescence quenching mounting medium.

[0221] (10) Image acquisition: Observe under a microscope, take pictures of the appropriate field of view, and analyze and quantify using ImageJ software.

[0222] 5.12 Detection of Serum Biochemical Indicators in Mice

[0223] (1) After anesthetizing the mice, remove the whiskers, quickly remove the eyeballs, and drip the blood from the eyeballs vertically into the anticoagulant tube and mix by inverting.

[0224] (2) After standing at room temperature, put it into a centrifuge and centrifuge at 1000g for 10 minutes.

[0225] (3) After centrifugation, take the upper serum layer into an EP tube and store it in a -80℃ refrigerator.

[0226] (4) When testing serum biochemical indicators, take out the serum and place it on ice to thaw, and then perform the test according to the instructions for each biochemical indicator.

[0227] 5.13 Single-cell RNA sequencing

[0228] Non-parenchymal cells (NPCs) extracted from the livers of 26-week-old mice in three sample groups were prepared into single-cell suspensions. The prepared single-cell suspensions were then subjected to scRNA-seq using the 10×Genomics platform (Gene Denovo). Cell Ranger version 6.1.0, Seurat version 4.1.0, and CellChat version 2.1.0 were used in the analysis.

[0229] 5.14 Bioinformatics Analysis

[0230] R language version 4.1.3 was used. Transcriptome sequencing data from 529 and 167 hepatocellular carcinoma (LIHC) patients were downloaded from the TCGA and GSE76427 databases, respectively. The TCGA database contained 369 tumor samples and 160 normal samples, while the GSE76427 database contained 115 tumor samples and 52 normal samples. The Wilcoxon rank-sum test was used to compare the differences in ITGβ1 mRNA expression levels among LIHC patients. To assess the prognostic impact of ITGβ1 in LIHC, samples with incomplete clinical information were excluded, retaining 297 samples from the TCGA database and 95 samples from the GSE76427 database with complete clinical data. Survival analysis was performed using the Kaplan-Meier method and the Log-rank test. Furthermore, Cox univariate and multivariate regression hazard models were constructed to predict the risk score associated with ITGβ1 gene-related clinical information in LIHC patients from the TCGA database. Pearson correlation analysis was used to further determine the correlation between the expression levels of Foxp3 and ITGβ1 in LIHC.

[0231] 5.15 Statistical Analysis

[0232] All statistical analyses were performed using GraphPad Prism 8.0 and SPSS software. Student's t-test, one-way ANOVA, and two-way ANOVA were used to assess differences between groups. All experiments were performed independently at least three times. Data are expressed as mean ± standard deviation (mean ± SD), and a p-value < 0.05 was considered statistically significant.

[0233] Experimental results

[0234] 1. MASLD rats showed significantly elevated liver necrosis, fibrosis, and blood lipid levels, as well as elevated levels of liver injury and liver function-related indicators. The dynamic changes in liver pathological histology, blood lipids, and liver enzymes in MASLD model rats are shown in the table below. Figure 1 According to the research plan ( Figure 1 A) C57BL / 6 mice were used to establish cancer models by feeding them a high-fat diet (HFD) and a high-fat diet plus the carcinogen 2-FAA (HCC), respectively, with normal mice as controls (ND). Figure 1 B); During the malignant transformation of hepatocytes in the model mice, the body weight of mice in each group (F=2.731, p<0.001, Figure 1 C) and rat liver (F=6.832, p<0.001, Figure 1 D) Weight exhibits dynamic changes. Figure 1E). Compared with the ND group, the model mice with alanine aminotransferase (ALT), aspartate aminotransferase (AST), blood glucose (GLU), low-density lipoprotein (LDL), triglycerides (TG), and total cholesterol (TC) were significantly elevated (ALT: F = 330.1, p < 0.001, AST: F = 286.6, p < 0.001, GLU: F = 523, p < 0.001, LDL: F = 213.7, p < 0.001, TG: F = 617.7, p < 0.001, TC: F = 184.4, p < 0.001). Figure 1 F). Pathologically, it shows changes in hepatocyte morphology, accompanied by hepatocyte necrosis, liver fibrosis, and carcinogenesis. Figure 1 G) occurred; according to NAS scores, the HFD and HCC groups were significantly higher than the ND group (F = 208.3, p < 0.001). Figure 1 H). After a high-fat diet, the liver tissue of the model mice, stained with Oil Red O, showed a large amount of fat accumulation (H). Figure 1 I); Quantitative analysis of tissue lipids showed that lipid accumulation in the HFD and HCC groups was significantly higher than that in the ND group (F = 28.24, p < 0.001). Figure 1 J). Successfully prepared a Treg for investigating the role and mechanism of malignant transformation in MASLD.

[0235] (A) MASLD mouse model preparation plan (n=3 / group); (B) HFD, HCC and ND group mice; (C) Dynamic changes in mouse body weight in each group; (D) Gross liver specimens of each group; (E) Dynamic changes in mouse liver weight; (F) Dynamic changes in mouse serum ALT, AST, GLU, LDL, TG and TC; (G) H&E staining of mouse liver tissue; (H) NAS score of model mouse liver; (I) Oil Red O staining of mouse liver lipids; (J) Quantitative comparison of oil red O staining of mouse liver. ALT: alanine aminotransferase, AST: aspartate aminotransferase, GLU: glucose, LDL: low-density lipoprotein, TG: triglycerides, TC: total cholesterol, NAS: NASH activity score. *p<0.05, **p<0.01, ***p<0.001.

[0236] 2. T cell loss during malignant progression in MASLD mice

[0237] MASLD model mouse liver single-cell RNA sequencing and flow cytometry T lymphocyte dynamic changes are shown in the figure. Figure 2 and 3 Liver samples were collected from 26-week-old MASLD model mice, dissociated into single-cell suspensions, and single-cell RNA sequencing was performed, including 24,699 cells from 9 samples. Figure 2A). Dimensionality reduction using the Unified Manifold Approximation and Projection (UMAP) yielded 29 subpopulations. These subpopulations were then divided into 13 known cell lines based on marker gene expression, including endothelial cells, T lymphocytes, neutrophils, monocytes, B lymphocytes, Kuppfer cells, hepatocytes, NK cells, dendritic cells, plasma cells, epithelial cells, hepatic stellate cells, and mast cells. Figure 2 B). Each cell subpopulation is displayed as a heatmap showing the three classic marker genes (B). Figure 2 C). The results of the proportion of each cell subset showed that the proportions of various immune cells, including B lymphocytes, T lymphocytes, Kuppfer cells, and monocytes, changed significantly, with the most significant change observed in T lymphocytes among all cell types. Figure 2 D). Flow cytometry results of peripheral blood (F=17.51, p<0.001), liver (F=59.37, p<0.001), and spleen (F=8.721, p<0.001) from MASLD mice at different cycles showed that T lymphocytes exhibited varying degrees of decline in both the HFD and HCC groups. Figure 2 EH, Figure 3 (AB). The composition of liver immune cells in MASLD mice was significantly altered, with severe loss of T lymphocytes, and this microenvironment also had corresponding effects on the peripheral blood and spleen of the mice.

[0238] (A) Schematic diagram of single-cell RNA sequencing performed on non-parenchymal liver cells from MASLD mice after preparation into single-cell suspensions (n=3 / group). (B) UMAP dimension reduction plot of 24,699 non-parenchymal liver cells from MASLD mice. (C) Heatmap showing the marker genes of all cell subpopulations, with 3 marker genes for each cell subpopulation. (D) Percentage of all cell subpopulations in the ND, HFD, and HCC groups. (E, F) Flow cytometry analysis of the percentage of liver T lymphocytes in mice at different stages in the ND, HFD, and HCC groups (n=3 / group). (G, H) Flow cytometry analysis of the percentage of peripheral blood T lymphocytes in mice at different stages in the ND, HFD, and HCC groups (n=3 / group). UMAP: Uniform Manifold Approximation and Projection; ND: Normal diet; HFD: High-fat diet; HCC: High-fat diet + carcinogenicity. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Two-way ANOVA (F, H).

[0239] (A, B) Flow cytometry analysis of the percentage of T lymphocytes in the spleen of mice in the ND, HFD, and HCC groups at different stages (n = 3 / group). (C, D) Flow cytometry analysis of CD4+ in the spleen of mice in the ND, HFD, and HCC groups at different stages. +T lymphocyte percentage (n=3 / group). (E, F) Flow cytometry analysis of CD8+ in spleens of mice in different stages of ND, HFD, and HCC groups. + T lymphocyte percentage (n=3 / group). ND: normal diet, HFD: high-fat diet, HCC: high-fat diet + carcinogenicity. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Two-way ANOVA (B, D, F).

[0240] 3. The MASLD microenvironment influences the subset composition and function of T lymphocytes.

[0241] The composition and function of hepatic T lymphocyte subsets in MASLD model mice are described in [reference needed]. Figure 3 , 4 5. GO enrichment analysis of liver T lymphocytes in MASLD model mice showed that, compared to the ND group, both the HFD and HCC groups exhibited significantly upregulated pathways related to immune system processes and leukocyte activation (especially lymphocyte activation), suggesting that the lymphocyte-dominated immune system is highly active in the MASLD environment. KEGG enrichment analysis showed significantly upregulated pathways related to lipids and atherosclerosis, consistent with the highly lipid-accumulated microenvironment of MASLD. Simultaneously, pathways such as the T lymphocyte receptor signaling pathway, TNF signaling pathway, and NFκB signaling pathway were significantly upregulated, indicating T lymphocyte activation and the occurrence of inflammatory responses. Figure 4 A). T lymphocyte clustering was used to classify T lymphocytes into CD4+. + T lymphocytes, CD8 + T lymphocytes and DN cells ( Figure 5 AB), where CD4 + T lymphocytes showed varying degrees of decrease in both the HFD and HCC groups, while CD8... + T lymphocytes showed varying degrees of increase. Figure 5 C). Flow cytometry was used to quantify T lymphocyte subsets in the peripheral blood, liver, and spleen of MASLD mice at different cell cycles. The results showed a decrease in CD4+ T lymphocytes and an increase in CD8+ T lymphocytes in the peripheral blood (CD4:F = 26.97, p < 0.001, CD8:F = 16.69, p < 0.001) and liver (CD4:F = 37.37, p < 0.001, CD8:F = 43.48, p < 0.001). In the spleen (CD4:F = 6.943, p < 0.001, CD8:F = 12.48, p < 0.001), CD8+ T lymphocytes were significantly lower. + T lymphocytes showed no significant changes, but CD4... + T lymphocytes decrease to some extent in the later stages of the disease. Figure 5 DK, Figure 3 CF). The MASLD microenvironment alters the composition of T lymphocyte subsets in peripheral blood, liver, and spleen, leading to changes in their function.

[0242] (A) GO and KEGG enrichment analysis of liver T lymphocytes from mice in the ND, HFD, and HCC groups. ND: normal diet, HFD: high-fat diet, HCC: high-fat diet + carcinogenic diet. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

[0243] (A) UMAP dimensionality reduction plot of MASLD mouse T lymphocytes, categorized by cell and sample. (B) Bubble chart showing marker genes for T lymphocyte subsets, with 3 marker genes for each subset. (C) Percentage of T lymphocyte subsets in the ND, HFD, and HCC groups. (DG) Flow cytometry analysis of CD4+ in livers of mice in the ND, HFD, and HCC groups at different stages. + T and CD8 + The percentage of T lymphocytes (n=3 / group) was measured by flow cytometry in peripheral blood of mice in the ND, HFD, and HCC groups at different stages. + T and CD8 + T lymphocyte percentage (n=3 / group). ND: normal diet, HFD: high-fat diet, HCC: high-fat diet + carcinogenicity, UMAP: uniform manifold approximation and projection. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Two-way ANOVA (E, G, I, K).

[0244] 4. MASLD microenvironment induces Treg proliferation, adhesion, and migration.

[0245] MASLD model mouse liver CD4 + The composition and function of T lymphocyte subsets are described in [link to documentation]. Figure 6 , 7 And 8. MASLD mouse CD4 + T lymphocyte subset identification includes CD4 + T lymphocytes are divided into CD4 memory T lymphocytes, CD4 activated T lymphocytes, CD4 naive T lymphocytes, and Treg cells. Figure 6 Quantitative analysis of Treg single-cell sequencing showed that Treg was significantly upregulated in the HFD group compared to the ND group, but there was no significant change in the HCC group. Figure 6C). Quantitative analysis by flow cytometry of peripheral blood (F=0.5143, p=0.7916), liver (F=3.225, p=0.0182), and spleen (F=34.26, p<0.001) in MASLD mice showed that liver Tregs were significantly upregulated in the HFD group, but there was no significant change in the HCC group. Peripheral blood Tregs showed an increasing trend in both the HFD and HCC groups, while spleen Tregs did not show a significant trend. Figure 6 DG, Figure 8 AB).

[0246] CellChat's quantitative and visualization results of cell communication between Tregs and other cells showed that, compared to the ND group, the number and intensity of communication between Tregs and endothelial cells were the most significant in the HFD and HCC groups. Figure 7 A). Receptor-ligand bubble plots of cell communication between Treg cells and other cells showed that, in comparisons between the HFD and HCC groups, the communication probability of numerous cell adhesion-related receptor pairs, such as the integrin family and laminin, was significantly upregulated in the HCC group. Figure 7 B). CD4 + A heatmap of cytokine expression levels in T lymphocyte subsets showed that vascular endothelial growth factor A (VEGFA) was significantly upregulated in the HCC group. Simultaneously, chemokine-related genes such as CXC-chemokine receptor type 4 (CXCR4) and CXC motif chemokine ligand 2 (CXCL2) were also upregulated in both the HFD and HCC groups. Figure 7 C). Given previous literature reports on endothelial cells inducing the transformation of MASH to HCC by promoting cell adhesion and migration, this study further confirms that the strong interaction between Tregs and endothelial cells can enhance the proliferation and migration capabilities of Tregs.

[0247] (A) MASLD mouse CD4 + UMAP dimensionality reduction plots of T lymphocytes, categorized by cell and sample. (B) Bubble chart showing CD4 + Marker genes for T lymphocyte subsets, with three marker genes for each subset. (C)CD4 +The proportion of T lymphocyte subsets in the ND, HFD, and HCC groups. (D, E) Flow cytometry analysis of the proportion of liver Tregs in mice at different stages in the ND, HFD, and HCC groups. The upper set of figures represents the isotype control, and the lower set represents the positive proportion (n=3 / group). (F, G) Flow cytometry analysis of the proportion of peripheral blood Tregs in mice at different stages in the ND, HFD, and HCC groups (n=3 / group). ND: normal diet, HFD: high-fat diet, HCC: high-fat diet + carcinogenic diet. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Two-way ANOVA (E, G).

[0248] (A) Number and intensity of cell communication between Tregs and other cells in the ND, HFD, and HCC groups. (B) Significant receptor-trust pair bubble diagram of cell communication between Tregs and other cells in the HFD and HCC groups. (C) CD4+ in the ND, HFD, and HCC groups. + Cytokine heatmap of T lymphocyte subsets. ND: normal diet, HFD: high-fat diet, HCC: high-fat diet + carcinogenicity. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

[0249] (A, B) Flow cytometry was used to detect the percentage of Tregs in the livers of mice in the ND, HFD, and HCC groups at different stages. The upper figure represents the isotype control, and the lower figure represents the positive percentage (n=3 / group). ND: normal diet, HFD: high-fat diet, HCC: high-fat diet + carcinogenic diet. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Two-way ANOVA (B).

[0250] 5. The Treg subset with high expression of ITGβ1 was significantly upregulated and promoted cell adhesion.

[0251] Identification and function of Treg subsets in the liver of MASLD model mice (see [link to documentation]). Figure 9 and 10 Unsupervised clustering divides Tregs into two subgroups, A and B, defined as Treg A and Treg B. Figure 9 A). Quantitative analysis of Treg subgroups showed that Treg A was more prevalent in the ND group, while Treg B was more prevalent in the HFD and HCC groups. Figure 9 B). Volcano plot of differential genes between Treg A and Treg B subgroups showed that ITGβ1 was significantly upregulated in the Treg B subgroup. Figure 9C). A violin plot showing gene expression differences revealed that ITGβ1 and Pecam1, two Treg B subsets most closely related to endothelial cells and cell adhesion, were upregulated at significantly higher levels than those of the Treg A subset. Figure 9 D). Univariate Cox regression analysis of Treg B subset upregulated genes showed that ITGβ1 was among the top 20 high-risk genes. Figure 9 E). GO enrichment analysis of differentially expressed genes in the Treg subsets showed significant upregulation of pathways such as lymphocyte activation and the immune system. KEGG enrichment analysis showed significant enhancement of numerous cell adhesion-related pathways, including cell adhesion molecule pathways and ECM receptor interaction pathways. Figure 9 F). Treg's GSVA analysis showed that among cancer-related pathways, signaling pathways such as the WNT-βcatenin pathway, E2F pathway, and epithelial-mesenchymal transition (EMT) pathway were significantly upregulated in both the HFD and HCC groups. Figure 9 G). Quantitative analysis of Treg metabolic activity using scMetabolism showed that multiple metabolic pathways, including fatty acid degradation, were significantly downregulated in both the HFD and HCC groups. Figure 10 A).

[0252] The pseudo-temporal analysis of Tregs showed that their developmental trajectory could be divided into seven states. Cells at the starting point of the developmental trajectory were mostly from the Treg A subset. As development progressed, multiple branches gradually emerged, including self-differentiation of the Treg A subset and multiple branches differentiating into the Treg B subset. The Treg A subset was mainly located on branches 1, 3, 4 and 1, 3, 5, 7, while the Treg B subset was mainly located on branches 1, 2 and 1, 3, 5, 6. In the ND group mice, most Tregs were in the early to mid-stages of their developmental trajectory, mainly located on branches 1, 3, 4. In contrast, the Tregs in the HFD and HCC groups (belonging to the disease group) were more in the mid to late stages of their developmental trajectory, located on branches 1, 3, 5, 6 and 1, 3, 5, 7. Figure 9 H). Numerous genes closely related to cell adhesion were also significantly upregulated over trajectory time (H). Figure 10 B). Branch analysis of State 1, 3, 4 and State 1, 3, 5, 6 showed that numerous pathogenicity-related genes were upregulated in the HFD and HCC branches, including ITGβ1 ( Figure 9I). The Treg B subset, characterized by high expression of ITGβ1, is the main pathogenic subset among Tregs and can promote cell adhesion and migration.

[0253] (A) UMAP dimensionality reduction plot of MASLD mouse Tregs obtained by unsupervised clustering. (B) Proportion of Treg subpopulations in ND, HFD, and HCC groups. (C) Volcano plot of differentially expressed genes in Treg subpopulations. (D) Violin plot of Treg subpopulations. (E) Forest plot of univariate regression analysis of Treg B upregulated genes. (F) GO and KEGG enrichment analysis of Treg subpopulations. (G) GSVA analysis heatmap of Treg subpopulations. (H) Pseudo-temporal analysis trajectory of Tregs, classified according to sample, cell subpopulation, pseudo-time, and state. (I) Branching analysis of Tregs State 1, 3, 4 and State 1, 3, 5, 6. UMAP: Uniform Manifold Approximation and Projection; ND: Normal diet; HFD: High-fat diet; HCC: High-fat diet + cancer-inducing diet; GSVA: Gene set variation analysis. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

[0254] (A) Quantification of Treg metabolic activity in the livers of ND, HFD, and HCC mice using the scMetabolism software package. (B) Cell adhesion-related genes in Treg pseudo-temporal analysis trajectories. ND: normal diet, HFD: high-fat diet, HCC: high-fat diet + carcinogenicity, GSVA: gene set variation analysis. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001.

[0255] 6. Treg promotes the development of MASH into HCC by upregulating ITGβ1.

[0256] ITGβ1 expression and prognosis are discussed in [link to relevant information]. Figure 11 The TCGA and GEO databases demonstrate high expression of ITGβ1 in HCC patients, and patients with high ITGβ1 expression have worse prognostic outcomes. Figure 11 AB). qPCR detection demonstrated upregulation of ITGβ1 in MASH-HCC patients (t = 3.114, p = 0.0124). Figure 11 C). qPCR results of the normal human liver cell line THLE2 and two human hepatocellular carcinoma cell lines, HepG2 and LM3, demonstrated that ITGβ1 was significantly upregulated in both hepatocellular carcinoma cell lines, especially LM3 (F = 11.72, p < 0.001). Figure 11 D). Univariate and multivariate Cox regression analyses of clinical information of HCC patients in the TCGA database showed that ITGβ1 could be a risk factor (Table 1). Figure 11 E). The HPA database also demonstrated high expression of ITGβ1 in HCC patients ( Figure 11 F). Pearson correlation analysis demonstrated a positive correlation between ITGβ1 and FOXP3 in HCC patients (R = 0.19, p < 0.001). Figure 11 G).

[0257] The correlation between ITGβ1 and FOXP3 and the expression levels of EMT-related genes are shown in the table below. Figure 12 Immunofluorescence co-localization of liver tissue from MASLD mice confirmed that the binding ability of Treg and ITGβ1 was significantly enhanced in the MASLD microenvironment. Compared with the ND group, the correlation between ITGβ1 and FOXP3 was significantly increased in the HFD and HCC groups (F = 11.92, p < 0.001). Figure 12 Immunohistochemical results of MASLD mouse liver tissue showed that ITGβ1 and FOXP3 were significantly upregulated in both the HFD and HCC groups, and EMT capacity was also enhanced (F = 207.2, p < 0.001). Figure 12 CD). There is a significant correlation between Treg and ITGβ1 in the MASLD microenvironment, and they are significantly upregulated.

[0258] (A) Validation of ITGβ1 expression levels using TCGA and GEO databases. (B) Validation of ITGβ1 clinical prognostic outcomes using TCGA and GEO databases. (C) Validation of ITGβ1 mRNA expression levels in adjacent and cancerous tissues of HCC patients (n=10). (D) Validation of ITGβ1 mRNA expression levels in hepatocellular carcinoma cell lines. (E) Univariate and multivariate regression forest plots of clinical information from HCC patients in the TCGA database. (F) Immunohistochemistry of ITGβ1 in healthy individuals and HCC patients presented in the HPA database. (G) Pearson correlation analysis of ITGβ1 and FOXP3 in the TCGA database. TCGA: Cancer Genome Atlas, GEO: Gene Expression Comprehensive Database, HPA: Human Protein Atlas. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Student t-test (C), one-way ANOVA (D).

[0259] Table 1. Clinicopathological characteristics between high and low ITGβ1 mRNA transcriptomes in the hepatocellular carcinoma group.

[0260]

[0261] Note: *p<0.05, **p<0.01

[0262] (AB) Immunofluorescence co-localization and correlation analysis of ITGβ1 and FOXP3 in MASLD mice. (CD) Immunohistochemistry of ITGβ1, FOXP3, and EMT-related genes in MASLD mice. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. One-way ANOVA (B), Two-way ANOVA (C).

[0263] 7. Knockdown of ITGβ1 inhibits Treg-induced cell adhesion and alleviates the malignant transformation of MASH to HCC. It also affects the proliferation and migration of HCC cells and the expression levels of cell adhesion-related genes. Figure 13 After knocking down ITGβ1 in HepG2 and LM3 cells with small interfering RNA (siRNA), the CCK-8 assay showed a decreased proliferation rate in both HepG2 (F = 8.467, p < 0.001) and LM3 (F = 4.43, p < 0.001) liver cancer cells. Figure 13 Transwell experiments verified that HepG2 (invasion: t = 6.614, p = 0.0027, migration: t = 3.344, p = 0.0287) and LM3 (invasion: t = 5.318, p = 0.006, migration: t = 15.53, p < 0.001) showed a significant reduction in invasion and migration abilities after ITGβ1 knockdown. Figure 13 CF). qPCR and WB validation of two types of hepatocellular carcinoma cells after ITGβ1 knockdown showed that, at both the RNA (HepG2: F=10.95, p<0.001, LM3: F=8.644, p<0.001) and protein (HepG2: F=49.1, p<0.001, LM3: F=23.21, p<0.001) levels, FOXP3 was downregulated, EMT capacity was weakened, and integrin ligand pairing was weakened. Figure 13 Knockdown of ITGβ1 can inhibit the regulatory effect of Treg and reduce cell adhesion.

[0264] (AB) CCK-8 assay to verify the proliferation capacity of HepG2 and LM3 cells. (CF) Transwell assay to verify the invasion and migration capacity of HepG2 and LM3 cells. (GI) Western blotting to detect the protein expression levels of ITGβ1 and its related ligands, FOXP3, and EMT in HepG2 and LM3 cells. (JK) qPCR to detect the mRNA expression levels of ITGβ1 and its related ligands, FOXP3, and EMT in HepG2 and LM3 cells. CCK-8: Cell counting kit-8; Western blotting; qPCR: Quantitative polymerase chain reaction; EMT: Epithelial-mesenchymal transition. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. Student's t-test (CF), two-way ANOVA (AB, HK).

[0265] This invention constructs siRNA nucleotide sequences for cell transfection. Cell proliferation experiments confirm that the siRNA of this invention can significantly interfere with the expression of ITGβ1 and significantly inhibit the proliferation and migration of human hepatocellular carcinoma cell lines HepG2 and LM3, thereby targeting the treatment of metabolic dysfunction-related fatty liver disease and effectively inhibiting the malignant transformation of MASLD to HCC.

[0266] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art can make various modifications or equivalent substitutions to the present invention within the scope of its essence and protection. Such modifications or equivalent substitutions should also be considered to fall within the protection scope of the present invention.

Claims

1. A siRNA that targets and knocks down ITGβ1, characterized in that, The sense strand sequence of the siRNA is shown in SEQ ID NO.1, and the antisense strand sequence is shown in SEQ ID NO.

2.

2. The use of the siRNA targeting and knocking down ITGβ1 as described in claim 1 in the preparation of a biological agent that inhibits ITGβ1 expression, wherein the biological agent is used for targeted treatment of metabolic dysfunction-related fatty liver disease.

3. The use of the siRNA that targets and knocks down ITGβ1 as described in claim 1 in the preparation of a medicament for the targeted treatment of metabolic dysfunction-related fatty liver disease.

4. A drug for treating fatty liver disease associated with metabolic dysfunction, characterized in that, Contains siRNA that targets and knocks down ITGβ1 as described in claim 1.

5. A biological agent that targets and knocks down ITGβ1, characterized in that, Contains siRNA that targets and knocks down ITGβ1 as described in claim 1.

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