Application of competitive inhibitor of SQLE enzyme in preparation of medicine for treating osteosarcoma

Abstract

The invention discloses an application of a competitive inhibitor of SQLE enzyme in preparation of a medicine for treating osteosarcoma. The competitive inhibitor comprises FR194738. The invention also discloses an application of the composition in preparation of drugs for treating osteosarcoma. The composition comprises a competitive inhibitor of SQLE enzyme and a chemotherapeutic drug having a synergistic effect with the competitive inhibitor. The invention verifies that the progress of osteosarcoma can be inhibited by inhibiting the SQLE through a drug for the first time, and also verifies that the SQLE inhibitor has a synergistic effect when being combined with chemotherapeutic drugs such as methotrexate, adriamycin and cis-platinum for use, thereby providing a new target and a new treatment strategy for treating osteosarcoma.

Description

Technical Field

[0001] The present invention relates to the field of biomedicine technology, and in particular to application of a competitive inhibitor of SQLE enzyme in preparing a medicine for treating osteosarcoma. Background Art

[0002] Osteosarcoma (OSA) is the most common primary malignant bone tumor, especially in adolescents, and its five-year survival rate remains at a relatively low level of 60% to 70%. For patients with metastatic or recurrent osteosarcoma, the prognosis is even worse. This is mainly due to the high heterogeneity of osteosarcoma, which leads to significant differences in its response to existing treatment options. Although significant progress has been made in the techniques of limb-salvage surgery and the MAP systemic chemotherapy regimen consisting of high-dose methotrexate (MTX), adriamycin (ADM) and cisplatin (DDP), some patients with high-grade osteosarcoma still face the challenge of chemotherapy resistance.

[0003] Therefore, verifying new therapeutic targets or treatment methods through experiments is a technical problem that technical personnel in this field urgently need to solve. Summary of the invention

[0004] The purpose of the present invention is to provide a competitive inhibitor of SQLE enzyme for use in preparing a drug for treating osteosarcoma in view of the deficiencies in the prior art.

[0005] To achieve the above object, the technical solution adopted by the present invention is:

[0006] The first aspect is to provide the use of a competitive inhibitor of SQLE enzyme in the preparation of a drug for treating osteosarcoma.

[0007] Furthermore, the competitive inhibitor comprises FR194738.

[0008] Furthermore, the competitive inhibitor also includes a pharmaceutically acceptable excipient.

[0009] The second aspect is to provide an application of a composition in the preparation of a drug for treating osteosarcoma, wherein the composition comprises a competitive inhibitor of SQLE enzyme and a chemotherapeutic drug having a synergistic effect with the competitive inhibitor.

[0010] Furthermore, the competitive inhibitor comprises FR194738 and pharmaceutically acceptable excipients.

[0011] Furthermore, the chemotherapy drug is one or more of methotrexate, doxorubicin, and cisplatin.

[0012] Furthermore, the chemotherapy drug is cisplatin.

[0013] The present invention adopts the above technical solution, and has the following technical effects compared with the prior art:

[0014] The present invention verifies for the first time that drug inhibition of SQLE can inhibit the progression of osteosarcoma, and also verifies that SQLE inhibitors have a synergistic effect when used in combination with chemotherapy drugs such as methotrexate, doxorubicin and cisplatin, providing new targets and treatment strategies for the treatment of osteosarcoma. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 The overexpression of SQLE in osteosarcoma is correlated with tumor progression; (ac) box plots show the expression level of SQLE; (a) osteosarcoma tissues are compared with their adjacent normal control tissues; (b) osteosarcoma cell lines (OSACell) are compared with osteoblasts (OB) and mesenchymal stem cells (MSC); (c) Saos2 cells with different Huvos grades and methotrexate resistance (Saos2 / MTX) are compared with their parental strain (Saos2); (de) scatter plots show the relationship between the gene copy number of SQLE and its mRNA expression level in osteosarcoma samples and osteosarcoma cell lines; (fg) scatter plots describe the correlation between the gene copy number of MYC and SQLE in osteosarcoma samples and osteosarcoma cell lines; (h) scatter plots show the correlation between the gene copy number of MYC and SQLE in the indicated numbers =Correlation between MYC and SQLE mRNA expression levels was analyzed; (ip) Kaplan-Meier survival analysis of SQLE expression levels was performed in multiple human and canine osteosarcoma cohorts to evaluate the relationship between SQLE expression levels and patient survival; (q) Representative immunohistochemistry (IHC) staining images show the protein expression abundance of SQLE in tissue microarrays; (r) Kaplan-Meier survival analysis using tissue microarray to detect SQLE protein abundance, including 26 osteosarcoma patients with low SQLE expression and 51 osteosarcoma patients with high SQLE expression; (s) Forest plot shows the results of multivariate Cox regression analysis; Exp: expression; MTX: methotrexate; CN: copy number; *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001, p values ​​were corrected by Wilcoxon rank sum test (a, c) and using Holm's method (b).

[0016] Figure 2(a) Immunofluorescence images show the subcellular localization of SQLE protein in U2OS; (bc) Box plots show the copy number (b) and mRNA expression level (c) of SQLE gene in cancer cell lines and non-cancer cells (Non-CA); Wilcoxon rank sum test was used to test whether the differences between osteosarcoma cell lines and non-cancer cells were significant, **p<0.01; ****p<0.0001; (d) Scatter plot illustrates the relationship between SQLE mRNA and the abundance of infiltrating immune cells and stromal cells in tumor tissues in the TARGET-OSA dataset.

[0017] Figure 3 (a) The expression level of SQLE mRNA was evaluated by real-time quantitative polymerase chain reaction to verify the interference effect of the four shRNAs; **p<0.01; ***p<0.001; ****p<0.0001, using t-test and adjusted by Holm's method; (b) The expression abundance of SQLE protein in six osteosarcoma cell lines was determined by Western blot analysis, and the histogram shows the relative intensity normalized to the 143B group; (ce) The dose-effect curves of specific drugs in the annotated cells were used to calculate the half inhibitory concentration (IC 50 ).

[0018] Figure 4 The results show that silencing SQLE can inhibit the progression of osteosarcoma; (a) Western blot experiments show the abundance of SQLE protein expression in cells transfected with shSQLE or shControl; (bc) Comparative analysis of cell proliferation, clone formation, migration and invasion abilities; (fg) Flow cytometric analysis of Annexin V-APC / 7-AAD staining was used to evaluate the proportion of apoptotic cells without drug treatment or after doxorubicin treatment; apoptotic cells are Annexin V-APC-positive cells, shown in the upper right and lower right quadrants; (hj) Histograms compare the sensitivity of different cells to the indicated drugs; (k) Tumors formed by subcutaneous transplantation of U2OS cells stably transfected with shControl or shSQLE; (l) Tumor growth curves of the indicated groups; (m) Comparison of tumor mass weight and intratumoral cholesterol level; (n) Representative images of SQLE and Ki-67 staining of tumor tissues; (o) Histograms compare the abundance of SQLE protein and the percentage of Ki-67-positive cells; AOD: average optical density, mean optical density; *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001, all histograms used t-test, cell proliferation curves and tumor growth curves used Tukey HSD test.

[0019] Figure 5(a) PCA plot shows the differences between U2OS-shControl cells and U2OS-shSQLE cells at the transcriptome level; (b) Volcano plot highlights the significant downregulation of SQLE mRNA in the U2OS-shSQLE group; (c) Enrichment plot arranges the enriched terms into a network and connects terms with shared genes; (d) Heat map shows the correlation analysis results between the sensitivity of osteosarcoma cell lines to different drugs (expressed as AAC values) and the expression level of SQLE mRNA; (e) Scatter plot shows the relationship between IC50 values ​​and AAC values ​​of four specific drugs in osteosarcoma cell lines; Ncell: number of osteosarcoma cell lines in the dataset; AAC: area above curve, area on the dose-response curve; *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001.

[0020] Figure 6 The results show that silencing SQLE inhibits osteosarcoma by reducing cholesterol levels and inhibiting the FAK / PI3K / Akt / mTOR signaling pathway; (a and d) GSEA plots show the enrichment trend of the gene set shown, and the genes are arranged in descending order of their log2FoldChange values; (b) The bar graph compares the cholesterol levels in the cells shown; (c) The bubble graph shows the KEGG enrichment results of differentially expressed genes; (e) The scatter plot shows the correlation between the SQLE expression level and the AAC values ​​of three antagonists of the PI3K / mTOR signaling pathway in osteosarcoma cell lines; (f g) Protein expression profiles in the labeled cell groups and subsequent quantitative analysis; (hk) Cell malignant phenotype detection results of different cell groups, including cell proliferation ability (h), clone formation ability (i), migration ability (j) and invasion ability (k); Cho: Cholesterol; For experiments involving multiple group comparisons, we compared the shSQLE group with other groups; ns: p>0.05; *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001, all cell proliferation curves used Tukey HSD test, other charts used t test and the p value was corrected by Holm's method.

[0021] Figure 7 (ab) Determination of the IC of two SQLE inhibitors, FR194738 and naftifine, on the indicated cells at the indicated treatment times. 50 (c) Comparison of IC values ​​of naftifine, terbinafine and FR194738 on U2OS after 48 hours of administration 50 Values; (de) IC values ​​of FR194738 against the specified cells were evaluated within 72 hours 50Value (d) and GR 50 (e) Bar graph showing the log-transformed IC values ​​of FR194738 in the indicated OSA cell lines. 50 Value and GR 50 Comparison of values; (g) The bar graph compares the growth rate (GR) and cell survival rate of the osteosarcoma cell lines shown after 72 hours of treatment with different concentrations of FR194738; (h) The bar graph shows the number of divisions of specific cells under standard culture conditions within 72 hours; (i) The bar graph shows the effect of two doses of FR194738 on intracellular cholesterol levels; (j) The heat map intuitively shows the dose-response results of the U2OS cell line after 48 hours of exposure to a series of drug combinations; ns: p>0.05; *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001, the data in all bar graphs were subjected to t-test, and the p-value correction in multiple testing was performed by Holm's method.

[0022] Figure 8 The present invention shows the inhibitory effect of pharmacological squalene epoxidase (SQLE) inhibition on osteosarcoma (OSA) progression and enhances chemotherapy efficacy; (A and B) experiments show the effects of two concentrations of FR194738 on cell proliferation (A) and clonogenicity (B) compared with the solvent control group; (C) images of tumors isolated from subcutaneous xenograft models that were treated with solvent or FR194738; (D) tumor growth curves of each group; (E) bar graphs showing the mass and cholesterol levels of tumors in each group; (F) weight change curves of each group; (G) representative immunohistochemical images of Ki-67 and cleaved caspase-3 staining in tumor sections; ( H) Bar graphs compare the percentage of Ki-67 and cleaved caspase-3 positive cells; (I) Heat maps provide visualization of the dose-response of MNNG to a range of drug combinations; (J and K) Heat maps show the synergy scores when FR194738 is used in combination with the indicated drugs in the indicated OSA cell lines; (LM) Scatter plots show the sensitivity and synergy indicators in the indicated OSA cell lines; (N) shows possible ways to apply the artificial intelligence derived prognostic index (AIDPI) in clinical practice; p>0.05; *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001, all line graphs were subjected to Tukey HSD test, and the data in all bar graphs were subjected to t-test, and the p-values ​​were corrected for multiple testing by Holm's method. DETAILED DESCRIPTION

[0023] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments, but is not intended to be limiting of the present invention. It should be noted that the embodiments and features in the embodiments of the present invention may be combined with each other without conflict.

[0024] 1. Methods for experimental validation of therapeutic targets

[0025] 1.1 Cells and cell culture related operations

[0026] The osteosarcoma cell lines used in the present invention include U2OS (RRID: CVCL_0042), MNNG / HOS (MNNG) (RRID: CVCL_0439), 143B (RRID: CVCL_2270), Saos2 (RRID: CVCL_0548), KHOS / NP (KHOS) (RRID: CVCL_2546) and MG63 (RRID: CVCL_0426). These cell lines are all from the cell bank of the Chinese Academy of Sciences. All cell lines were verified by short tandem repeats (STR) identification. The cell lines were cultured in Dulbecco's modified Eagle's medium (DMEM) containing 10% fetal bovine serum (FBS), 100U / mL penicillin and 100μg / mL streptomycin, and placed in a constant temperature of 37°C, humidified, and containing 5% CO 2 Cell culture incubator.

[0027] 1.2 Plasmid construction

[0028] In order to precisely regulate the expression of SQLE gene in osteosarcoma cells, short hairpin RNA (shRNA) targeting SQLE mRNA was specially designed, with the purpose of reducing the expression level of SQLE gene by RNA interference (RNAi) technology, so as to study its role in the development of osteosarcoma. At the same time, in order to ensure the reliability of the experimental results, the present invention also constructed a control group, i.e., non-targeted random sequence (shControl). Such a design allows accurate evaluation of the effect of specific gene silencing on cell behavior while excluding the possibility of non-specific interference. Specific targeting sequences can be found in Table 1 below. These targeted and non-targeted shRNA sequences were cloned into pGIPZ plasmid vectors. In order to verify the accuracy and integrity of the recombinant plasmid, the Sanger sequencing method was used.

[0029] Table 1

[0030]

[0031] 1.3 Preparation and transfection of lentivirus

[0032] In a 10 cm culture dish, 1 × 10 7 HEK293T cells were cultured at a density of 10 cells / dish. According to the instructions, Lipofectamine 3000 was used for transfection, and the corresponding plasmid and lentiviral packaging plasmid were used to prepare lentivirus. New culture medium was replaced 6 hours after transfection, and the viral supernatant was collected 48 hours later and then used to infect osteosarcoma cell lines.

[0033] Osteosarcoma cell lines with good growth status were digested and inoculated into 24-well plates for culture. After 24 hours, the cells were washed with PBS and replaced with fresh serum-free medium. Lentivirus and Lipofectamine 3000 transfection reagent were added according to the MOI value of each cell (MOI = virus titer / cell number). After 4 hours of culture, the culture medium was replaced with complete medium, and the fluorescence intensity was observed under a microscope for another 48 hours to estimate the infection efficiency.

[0034] 1.4 Screening of stable transfected cell lines

[0035] 72 hours after lentiviral transfection, 2 μg / mL of puromycin was added to the culture medium for a two-week screening process to establish a stably transfected cell line. The effect of gene silencing was verified by real-time fluorescence quantitative PCR (qPCR) or Western blotting technology.

[0036] 1.5 RNA extraction and qPCR experimental procedures

[0037] Total RNA was extracted using TRIzol reagent and then reverse transcribed using the TransScript All-in-One First-StrandcDNA Synthesis SuperMix for qPCR kit to generate cDNA. qPCR experiments were performed using QuantStudio5 and 2×RealStar Fast SYBR qPCR Mix. The experimental procedure followed the manufacturer's guidelines, and the primer sequences can be found in Table 2 below.

[0038] Table 2

[0039]

[0040] 1.6 Western blotting experiments

[0041] 1) Protein extraction: First, use RIPA lysis buffer containing protease and phosphatase inhibitors to extract intracellular proteins. This step is crucial because protease and phosphatase inhibitors can prevent protein degradation and changes in phosphorylation status during the extraction process, thereby ensuring that the extracted proteins better reflect the true state of the cell.

[0042] 2) Protein electrophoresis: Cell homogenate samples with equal protein content are separated by SDS-PAGE. SDS-PAGE can effectively separate proteins according to their size, providing a basis for subsequent membrane transfer and detection. The configuration system of separation gel and concentrated gel of different concentrations can be seen (Table 3).

[0043] 3) Protein transfer: The proteins separated by electrophoresis are transferred to a 0.45 μm pore size polyvinylidene fluoride (PVDF) membrane. PVDF membrane is widely used in western blotting experiments due to its high protein binding capacity and chemical stability.

[0044] 4) Membrane blocking: To block non-specific binding sites, the transferred membrane is blocked in TBST containing 5% bovine serum albumin (for detecting phosphorylated proteins) or in TBST containing 5% skim milk (for detecting non-phosphorylated proteins). This step is crucial for increasing specific signals and reducing background noise.

[0045] 5) Antibody incubation: The blocked membrane is then incubated with the primary antibody overnight at 4°C to ensure that the antibody is fully bound to the target protein. After that, the membrane is incubated with a secondary antibody cross-linked with HRP. The choice of the secondary antibody depends on the host species of the primary antibody.

[0046] 6) Signal detection: Use SuperSignal West Pico chemiluminescent reagent or similar luminescent reagent to treat the membrane to make the HRP-labeled secondary antibody bound to the target protein emit light, thereby displaying the protein band by chemiluminescence.

[0047] 7) Image acquisition and analysis: Use a fluorescent imaging system to capture the signal on the membrane, and use ImageJ software (v1.53a) or other quantitative software to perform quantitative analysis of the bands. By comparing the protein band intensities between different samples, the expression level changes of the target protein can be evaluated.

[0048] Table 3 Separation gel and concentration gel configuration system

[0049]

[0050]

[0051] 1.7 Preparation of drug and cholesterol solutions

[0052] 1) Preparation of stock solutions: First, according to the physical and chemical properties of FR194738, terbinafine, naftifine, methotrexate, doxorubicin, cisplatin and cholesterol, and the solvents recommended in their respective instructions (such as DMSO, ethanol, PBS, etc.), accurately prepare the stock solutions of each drug for subsequent dilution and use. When preparing the stock solutions, ensure that the operation is carried out under sterile conditions to prevent microbial contamination.

[0053] 2) Preparation of working solutions: Dilute the stock solution to different working concentrations according to the experimental design. During the dilution process, pay attention to choosing the appropriate diluent (such as sterile PBS, culture medium, etc.), and dilute strictly according to the calculated ratio to ensure that the concentration of each working solution is accurate. When preparing the working solution, pay special attention not to exceed the maximum allowable concentration of DMSO or other organic solvents in the final system to avoid adverse effects on cells.

[0054] 3) Labeling and storage: After each solution is prepared, immediately label the drug name, concentration, preparation date and expiration date on the EP tube or other storage container to avoid confusion or incorrect use. Depending on the stability of the drug, store the stock solution and working solution under recommended conditions, such as -20°C or 4°C, and keep away from light (if necessary).

[0055] 4) Inspection before use: Before experimental use, check the color and clarity of the solution to ensure there is no precipitation or color change, which may be a sign of drug degradation or contamination.

[0056] 1.8 Cell proliferation assay

[0057] The cells were seeded in a 96-well plate at a density of 2000 cells per well, and the cell viability was evaluated at different set time points. Before evaluation, the old culture medium was removed, and 100 μL of fresh culture medium containing 10% CCK-8 reagent was added to each well, and then incubated at 37°C for 30 minutes. Next, the absorbance value at 450nm was detected using a microplate reader. In order to obtain relative cell viability, the absorbance value at each time point was divided by the average value of the initial time point.

[0058] 1.9 Drug sensitivity testing

[0059] Cells were seeded at a density of 5000 cells per well in 96-well plates and exposed to different concentrations of drugs for at least 48 hours after 24 hours. Cell survival was then assessed using CCK-8 reagent as described above. In some experiments, cell survival was also measured at the time of drug addition (time 0) to calculate GR 50 The value represents the drug concentration required to halve the cell growth rate. This new metric helps correct for confounding factors in cancer drug sensitivity assessment, such as differences in the natural proliferation rates of different cancer cells. The dose-response data were analyzed and visualized using the GRmetrics package.

[0060] 1.10 Drug synergistic effect detection

[0061] Cells were seeded at a density of 5000 per well in 96-well plates and treated with different drug concentration combinations for 48 hours after 24 hours. Subsequently, cell viability was assessed with CCK-8 reagent as described above, and the data were preprocessed using the ReshapeData function in the synergyfinder package in R language (v4.3.0), and the CalculateSynergy function was used to calculate and visualize the synergy score according to four major synergy score models, including Highest Single Agent (HSA), Loewe Additivity (Loewe), Bliss Independence (Bliss), and Zero Interaction Potency (ZIP), and the CalculateSensitivity function was used to calculate the combination sensitivity score (CSS).

[0062] 1.11 Colony formation assay

[0063] The cells were seeded at a density of 1000 cells per well in a 6 cm dish and cultured for 14 days, with the medium changed every five days. The cells were fixed with ice-cold methanol and stained with crystal violet solution. We counted colonies consisting of 50 cells or more.

[0064] 1.12 Migration and invasion assay

[0065] In the Transwell migration assay, cells were pretreated with 10 μg / ml mitomycin C for two hours, and then 5 × 10 4 Cells were seeded in The upper chamber of the chambers was filled with 600 μL of culture medium containing 10% FBS, and the lower chamber was added. After 24 hours of culture, the cells on the upper side of the Transwell membrane were removed with a cotton swab, and the cells that passed through the membrane to the lower chamber were fixed with 4% paraformaldehyde, stained with 1% crystal violet and photographed, and finally the crystal violet was eluted with 33% glacial acetic acid, and the absorbance at 590 nm was measured.

[0066] For the Matrigel invasion assay, cells were pretreated with 10 μg / ml mitomycin C for two hours, and then 2 × 10 5 Cells were seeded into BioCoat TM The cells were placed in the upper chamber of the Matrigel invasion chamber, and 600 μL of culture medium containing 10% FBS was added to the lower chamber. After 24 hours of culture, the cells on the upper side of the Transwell membrane were removed with a cotton swab, and the cells that passed through the membrane to the lower chamber were fixed with 4% paraformaldehyde, stained with 1% crystal violet and photographed, and finally the crystal violet was eluted with 33% glacial acetic acid, and the absorbance at 590 nm was measured.

[0067] 1.13 Xenograft Model

[0068] Female BALB / c nude mice aged 4 to 5 weeks were purchased from Hangzhou Ziyuan Experimental Animal Technology Co., Ltd., with a maximum of five mice per cage, and were kept in the SPF barrier facility of the animal room of the Shanghai Tenth People's Hospital affiliated to Tongji University, with an ambient temperature of 23-25°C, a relative humidity of 40%, a 12-hour day and night cycle, irradiated feed, and autoclaved drinking water. Animals were free to eat and drink. The animal experiments in the present invention were approved by the Experimental Animal Welfare and Ethics Committee of the Shanghai Tenth People's Hospital affiliated to Tongji University.

[0069] To evaluate the effect of SQLE on the growth of osteosarcoma xenograft models, 2 × 10 6 U2OS cells were injected into nude mice (n=5 per group) with 0.1 mL PBS as the injection solution. Tumor growth was measured every three days, and tumor volume was calculated using the following formula: volume = 0.5 × length × width × width. After 26 days, mice were euthanized and used for further analysis, including tumor photography, weighing, immunohistochemistry (IHC) analysis, and detection of cholesterol levels in tissues.

[0070] To evaluate the efficacy and safety of FR194738, MNNG cells suspended in 0.1 mL of Matrigel were inoculated subcutaneously into nude mice (5 × 10 6 / mouse). Tumor growth and mouse body weight were monitored every three days. Nine days after inoculation, when the average tumor volume reached about 60 mm 3 At 14:00, mice were randomly divided into two groups (n=5 per group). One group received daily intraperitoneal injection of 10% DMSO, and the other group received daily intraperitoneal injection of 100 mg / kg FR194738. On the 16th day after inoculation, mice were euthanized and used for further analysis as described above. In addition, tumor growth inhibition (TGI) was calculated based on the average tumor weight using the following formula: TGI=[1-(FR194738 group tumor weight / control group tumor weight)]×100.

[0071] 1.14 Tissue microarray and immunohistochemical staining analysis

[0072] A tissue microarray (TMA) containing 79 samples was purchased from Shanghai Xiabukang Biotechnology Co., Ltd. to analyze the correlation between SQLE protein expression and prognosis in osteosarcoma patients. Two samples without sarcoma cells were excluded from the analysis, so 77 samples were actually analyzed. The antibody we used was Squalene epoxidaseantibody (H-6) (Santa Cruz Biotechnology, Cat# sc-271651), and IHC staining was performed with standard procedures. All slides were scanned by a Pannoramic Midi II digital slide scanner. The demographic characteristics and clinical data of the patients in the TMA are listed in Table 4 below.

[0073] Table 4

[0074]

[0075] All tumor tissues obtained from mice were fixed in 4% glutaraldehyde for subsequent paraffin embedding and then cut into 5 μm thick sections for immunohistochemical staining of SQLE, Ki-67, and cleaved caspase-3 using standard procedures.

[0076] The staining results were analyzed using HALO image analysis software, and the average optical density (AOD) was defined as the integrated optical density (IOD) divided by the area of ​​the region of interest (ROI), and was used to represent the expression abundance of SQLE protein.

[0077] 2. Statistical and computational analysis methods

[0078] All results are from at least three independent experiments, and the data we show are from one representative experiment. The sample size of all in vivo and in vitro experiments was chosen empirically.

[0079] All statistical analyses were performed using R software (v4.2.3) unless otherwise specified, and data were assessed for normality using the shapiro_test function in the rstatix ​​package. For correlation analysis, Pearson correlation coefficients and p-values ​​were calculated when both variables met the assumption of normality, otherwise, the Spearman method was used. Levene's test was applied to assess the homogeneity of variance between groups using the levene_test function in the rstatix ​​package. Parametric statistical tests were used when the data met the assumptions of normality and homogeneity of variance, otherwise, nonparametric tests were used. All experiments were performed with at least three technical replicates unless otherwise specified. If parametric statistical tests were available, data were presented as bar-dot plots with horizontal lines representing the mean and error bars representing standard deviations (SD), otherwise, data were presented using box plots. For two independent groups, comparisons were performed using the Student's t test (parametric test) or the Wilcoxon rank sum test (nonparametric test). Comparisons of multiple groups were performed using one-way ANOVA (parametric test) or Kruskal-Wallis rank sum test (nonparametric test), and p values ​​were corrected using Holm's method when performing multiple comparisons.

[0080] For the analysis of cell proliferation and tumor growth curves, repeated measures ANOVA was performed using the anova_test function in the rstatix ​​software package, with Greenhouse-Geisser correction and Tukey's method for post hoc multiple comparisons. Unless otherwise stated, all p values ​​were derived from two-sided statistical tests, and p values ​​or corrected p values ​​less than 0.05 were considered statistically significant.

[0081] 3. Experimental Results Analysis

[0082] 3.1 SQLE overexpression is associated with osteosarcoma progression

[0083] The association between MYC overexpression and osteosarcoma progression has been widely reported. We also observed that SQLE expression was significantly increased in osteosarcoma tissues and cell lines compared with normal adjacent tissues and putative osteosarcoma precursor cells (osteoblasts and mesenchymal stem cells). Figure 1 ab). It is noteworthy that SQLE expression was significantly upregulated in Huvos Grade I / II osteosarcoma specimens (poor response to neoadjuvant chemotherapy) and in the methotrexate-resistant Saos2 cell line ( Figure 1 c) These results suggest that SQLE may play an important role in the initiation of osteosarcoma and the formation of drug resistance.

[0084] The present invention further studied the potential molecular mechanism of SQLE overexpression in osteosarcoma and found that there was a significant positive correlation between the SQLE gene copy number and its mRNA expression level in osteosarcoma tissues and cell lines ( Figure 1 de). The oncogene MYC, which is often amplified in osteosarcoma, is located close to SQLE in the genome (SQLE is located at 8q24.13 and MYC is located at 8q24.21). Their gene copy numbers ( Figure 1 fg) and mRNA expression levels ( Figure 1 h) The strong correlation between the two groups suggests that the co-amplification of SQLE and MYC in osteosarcoma may be responsible for their high expression in osteosarcoma.

[0085] KMSA in multiple cohorts confirmed that elevated SQLE expression was associated with poor prognosis in human or canine osteosarcoma patients, including overall survival (OS) and event-free survival (EFS) ( Figure 1 In addition, we also detected the abundance of SQLE protein in 77 human osteosarcoma tissues in tissue microarray (TMA) and showed representative IHC staining images of SQLE protein low and high expression ( Figure 1 q), the results confirmed that the overall survival rate of patients in the high-expression group of SQLE protein was significantly lower (p = 0.037) ( Figure 1 r). Multivariate Cox regression analysis in the Meta-OSA cohort showed that even after correction for clinical factors such as age, MSTS stage, and primary tumor site, the expression of SQLE and MYC were independent indicators for predicting the risk of death in osteosarcoma patients ( Figure 1 s).

[0086] Although MYC protein has been found to be a key target in osteosarcoma, strategies that directly target MYC protein still face challenges due to its nuclear localization and lack of a clear pocket structure. Figure 1 q and Figure 2 As shown in a, SQLE protein is located in the cytoplasm and is more likely to become a potential therapeutic target due to its nature as a metabolic enzyme. In CCLE, the SQLE copy number and mRNA expression level in osteosarcoma cells are much higher than those in normal cells ( Figure 2bc), which suggests that targeting SQLE protein in vivo may be more effective in inhibiting osteosarcoma cells without affecting normal cells. In addition, in the TARGET-OSA dataset, the expression of SQLE was negatively correlated with the infiltration of CD4-positive T lymphocytes ( Figure 2 d), which revealed that SQLE may play a role in the regulation of the immune microenvironment of osteosarcoma.

[0087] These results indicate that the co-amplification of SQLE and MYC at the DNA level may lead to the overexpression of SQLE in osteosarcoma and promote the progression of osteosarcoma by promoting chemotherapy resistance of osteosarcoma cells and inhibiting the infiltration of immune cells.

[0088] 3.2 Knockdown of SQLE significantly inhibits osteosarcoma in vitro and in vivo

[0089] In order to further explore the function of SQLE in osteosarcoma, the present invention designed four shRNAs and screened out the one with the best effect ( Figure 3 a) was used to express SQLE in MNNG and U2OS cells with high endogenous expression of SQLE protein ( Figure 3 b) Conduct SQLE gene silencing experiments ( Figure 4 a). It was found that knocking down SQLE could effectively inhibit the malignant phenotype of these cells, including inhibiting cell proliferation ability (4b), reducing colony formation ability ( Figure 4 c) Reduce cell migration ( Figure 4 d) and invasion ( Figure 4 e). In addition, SQLE gene knockdown can also increase the proportion of apoptotic cells under normal culture conditions and after drug treatment ( Figure 4 fg), and significantly increased the sensitivity of cells to MAP regimen (MTX, ADM, and DDP), as shown by the IC 50 It can be clearly seen from the decrease in the value ( Figure 4 hj and Figure 3 In xenograft models, we observed that silencing SQLE could significantly inhibit tumor growth, reduce tumor weight and intratumoral cholesterol levels ( Figure 4 km). Immunohistochemical staining experiments further confirmed the significant decrease in SQLE protein abundance and the number of Ki-67 positive cells after SQLE knockdown ( Figure 4 no). These findings suggest that targeting SQLE protein could effectively inhibit osteosarcoma.

[0090] Silencing SQLE inhibits osteosarcoma by reducing cholesterol levels to inhibit the FAK-PI3K-Akt-mTOR signaling pathway

[0091] After confirming that silencing SQLE has an inhibitory effect on osteosarcoma, we further explored the molecular mechanism behind it. Transcriptome sequencing analysis was performed on U2OS cells stably expressing shSQLE and shControl. The PCA plot ( Figure 5 a) shows the significant difference between the two groups of samples at the transcriptome level. We used the volcano plot to show that in the shSQLE group, the expression level of SQLE mRNA decreased significantly ( Figure 5 b). From the results of gene set enrichment analysis, we can see that after silencing SQLE, the cholesterol homeostasis-related gene set was significantly inhibited ( Figure 6 This is consistent with our observation that cholesterol levels in MNNG and U2OS cells were reduced after SQLE knockdown ( Figure 6 b). KEGG enrichment analysis of differentially expressed genes (DEGs) revealed that the PI3K-Akt signaling pathway was significantly enriched ( Figure 6 c). Using the enrichment map, the related terms were combined into a network showing the connection between the PI3K-Akt signaling pathway, focal adhesion, and ECM-receptor interaction ( Figure 5 c). In fact, in the WikiPathways database, these pathways are merged into a broader gene set, the FAK-PI3K-Akt-mTOR pathway gene set (WP3932). After we silenced SQLE in U2OS cells, this pathway was also significantly inhibited ( Figure 6 d). Further drug-gene association analysis found that in osteosarcoma cell lines, SQLE expression was positively correlated with the area above curve (AAC) of various drugs, especially GSK1059615 ( Figure 5 d) A higher AAC value means a higher drug sensitivity because it is related to IC 50 The value is inversely proportional ( Figure 5 e). It is noteworthy that the expression level of SQLE was significantly positively correlated with the AAC values ​​of the three PI3K / mTOR pathway antagonists ( Figure 6 e), which emphasizes that SQLE may affect the activation of this pathway in osteosarcoma cell lines.

[0092] Considering the role of SQLE protein in cholesterol synthesis and the key regulatory function of cholesterol in regulating cell signaling pathways through lipid rafts, we hypothesized that silencing SQLE would reduce intracellular cholesterol levels, thereby inhibiting the FAK / PI3K / Akt / mTOR signaling pathway and ultimately suppressing osteosarcoma progression. Consistent with this hypothesis, silencing SQLE in MNNG and U2OS cells resulted in decreased phosphorylation levels of key proteins including FAK, PI3K, Akt, and mTOR. However, supplementation with cholesterol (100 μg / mL) restored the phosphorylation levels of these proteins ( Figure 6 fg), and counteracted the inhibitory effect of SQLE knockdown on the malignant phenotype of these osteosarcoma cells ( Figure 6 hk). These findings suggest that SQLE silencing may suppress osteosarcoma by reducing cholesterol levels and subsequently inhibiting the FAK / PI3K / Akt / mTOR pathway.

[0093] 3.4 Drug inhibition of SQLE can inhibit osteosarcoma progression and enhance the effect of chemotherapy

[0094] After discovering that silencing SQLE can have an inhibitory effect on osteosarcoma, the present invention further studied its potential as a therapeutic target. It is known that fungal SQLE protein inhibitors (such as naftifine and terbinafine) have inhibitory effects on a variety of malignant tumor cell lines, but have no significant effect on normal fibroblasts. However, since these inhibitors are mainly developed for fungal SQLE proteins, their potential for application in the treatment of human osteosarcoma may be limited. In comparison, FR194738 is considered to be a more effective mammalian SQLE inhibitor, which is superior to its precursor compound in both efficacy and bioavailability. It is worth noting that preclinical studies have confirmed the effectiveness of FR194738 in the treatment of prostate cancer. We found that the IC of FR194738 in MNNG and U2OS cells 50 The values ​​were significantly lower than those of naftifine and terbinafine ( Figure 7 ac), which inspired us to continue studying the therapeutic potential of FR194738 in osteosarcoma.

[0095] In a preliminary evaluation, we examined the responses of four osteosarcoma cell lines to FR194738. Compared with MG63 and 143B cells, MNNG and U2OS cells were more sensitive to FR194738, with an IC 50 Value and GR 50 The values ​​were significantly lower ( Figure 7 df). After exposure to 4 μM FR194738 for 72 h, the growth rate and survival rate of MNNG and U2OS cells were significantly decreased, while MG63 and 143B cells were not significantly affected ( Figure 7g). This may be due to the lower expression level of SQLE protein in MG63 and 143B cells ( Figure 3 b), indicating that FR194738 has a specific inhibitory effect on cells with high expression of SQLE protein. It is worth mentioning that the number of divisions of MG63 cells within 72 hours was the lowest ( Figure 7 h), indicating that they also have a lower requirement for cholesterol, which also partly explains their low sensitivity to FR194738. Based on these results, it is inferred that FR194738 may have a weaker inhibitory effect on cells with low SQLE protein expression or low growth rate.

[0096] In subsequent analysis, we found that FR194738 exhibited a significant dose-dependent inhibitory effect on the proliferation and colony formation of U2OS and MNNG cells ( Figure 8 ab). After receiving FR194738 treatment, the intracellular cholesterol level decreased significantly ( Figure 7 i). In vivo efficacy evaluation in a xenograft model of MNNG cells further confirmed our in vitro results. FR194738 not only inhibited tumor growth and intratumoral cholesterol content, but also did not cause significant weight loss in the test animals ( Figure 8 cf). Comparison of the tumor weights after dissection revealed that the tumor inhibition rate reached 59.67% ( Figure 8 e). In addition, immunohistochemical staining results of Ki-67 and cleaved caspase-3 also confirmed that cell proliferation was attenuated and the proportion of apoptotic cells was increased in osteosarcoma xenografts after FR194738 treatment ( Figure 8 gh), highlighting the potential value of pharmacological inhibition of SQLE in osteosarcoma treatment.

[0097] Based on the finding that silencing SQLE leads to inactivation of the FAK / PI3K / Akt / mTOR signaling pathway and the fact that osteosarcoma cells are more sensitive to methotrexate, doxorubicin, and cisplatin when this signaling pathway is inhibited, we speculated that FR194738 may have a synergistic effect with these first-line chemotherapeutic drugs in the treatment of osteosarcoma. Figure 8 i) and U2OS( Figure 7 j) Responses of cell lines to different drug combinations. Most synergy scores indicated significant synergy ( Figure 8jk). In addition to the synergy score, we also used the combination sensitivity score (CSS) to evaluate the therapeutic effect of the drug combination. We show the CSS values ​​and synergy scores of all tested drug combinations. Of particular note, the combination of FR194738 and cisplatin showed the best synergistic effect ( Figure 8 lm). These findings suggest that targeted inhibition of SQLE by FR194738 may significantly improve the efficacy of chemotherapy in osteosarcoma patients (especially when cisplatin is used for chemotherapy). Based on our results, we believe that AIDPI has the potential to stratify the mortality risk of osteosarcoma patients. Although conventional therapy may be sufficient for patients with low AIDPI, patients with high AIDPI may benefit from combined therapy with conventional therapy and SQLE inhibitors such as FR194738. This combined treatment strategy provides a new treatment avenue for osteosarcoma patients in the high AIDPI group, thereby hopefully improving the clinical prognosis of this subgroup of patients ( Figure 8 n).

[0098] The above description is only a preferred embodiment of the present invention, and does not limit the implementation mode and protection scope of the present invention. For those skilled in the art, it should be aware that all solutions obtained by equivalent substitutions and obvious changes made using the contents of the specification and illustrations of the present invention should be included in the protection scope of the present invention.

Claims

1. Application of competitive inhibitors of SQLE enzyme in the preparation of drugs for treating osteosarcoma.

2. The use according to claim 1, characterized in that: The competitive inhibitors include FR194738.

3. The use according to claim 2, characterized in that: The competitive inhibitor also includes pharmaceutically acceptable excipients.

4. Use of a composition in the preparation of a drug for treating osteosarcoma, characterized in that: The composition comprises a competitive inhibitor of SQLE enzyme and a chemotherapeutic drug having a synergistic effect with the competitive inhibitor.

5. The use according to claim 4, characterized in that: The competitive inhibitor comprises FR194738 and pharmaceutically acceptable excipients.

6. The use according to claim 4, characterized in that: The chemotherapy drug is one or more of methotrexate, doxorubicin and cisplatin.

7. The use according to claim 6, characterized in that: The chemotherapy drug is cisplatin.

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