Anti-breast cancer drug and application

Abstract

The present invention relates to the field of biotechnology, in particular to an anti-breast cancer drug and its application. Specifically disclosed is an anti-breast cancer drug comprising an active ingredient, wherein the active ingredient is a DECR1 inhibitor or a DECR1 binder; application of the DECR1 inhibitor or the DECR1 binder in preparing a drug for treating or preventing breast cancer; and application of the DECR1 inhibitor or the DECR1 binder in preparing a drug for improving the sensitivity or therapeutic effect of anti-breast cancer drugs in the treatment or prevention of breast cancer; wherein the DECR1 binder is Erigoster B. The present invention inhibits the expression of DECR1 in breast cancer tissue cells through Erigoster B, thereby reducing the proliferation, migration and invasion abilities of breast cancer and increasing the probability of ferroptosis of breast cancer cells, thereby providing a new therapeutic strategy and idea for breast cancer treatment.

Description

Technical Field

[0001] The present invention relates to the field of biotechnology, and in particular to an anti-breast cancer drug and its application. Background Art

[0002] Breast cancer is the most common cancer in women, with consistently high morbidity and mortality. Despite extensive research, treatment options for patients with advanced breast cancer are limited and ineffective. Therefore, identifying new and effective breast cancer therapeutic targets and developing potential anti-tumor drug candidates is of great clinical and scientific significance.

[0003] Metabolic reprogramming is considered a hallmark of tumors and encompasses glycolysis, oxidative phosphorylation, amino acid metabolism, and fatty acid metabolism. Typically, rapidly proliferating tumor cells require large quantities of fatty acids to synthesize phospholipids and promote cell membrane formation. Furthermore, fatty acids serve as a raw material for mitochondrial ATP production and regulate protein function. Therefore, fatty acids play a crucial role in tumor development and progression, and interfering with fatty acid metabolism in tumor cells may be an effective strategy for tumor treatment.

[0004] Cell membranes and organelle membranes are rich in polyunsaturated fatty acids. However, the reaction of polyunsaturated fatty acids to generate excessive ROS can lead to cell damage and accumulation of lipid peroxides, resulting in ferroptosis of the cells. Ferroptosis plays a vital role in various diseases, such as tumors, osteoporosis, and cardiovascular diseases. It is well known that lipid peroxidation induced by cellular oxidative stress is the basis for the occurrence of ferroptosis. Although tumor cells are more susceptible to oxidative stress, tumor cells can usually produce NADPH, GSH and other reducing agents to reduce cellular ROS levels and maintain cellular redox homeostasis, thereby avoiding ferroptosis. Strategies targeting tumor ferroptosis have shown exciting results, but their clinical application is still subject to many limitations due to the lack of clarity and depth of related research. Summary of the Invention

[0005] In view of the above-mentioned deficiencies in the prior art, the present invention aims to provide an anti-breast cancer drug and its application, thereby providing a new approach for the treatment of breast cancer.

[0006] In order to solve the above problems, the present invention adopts the following technical solutions:

[0007] An anti-breast cancer drug comprises an active ingredient, wherein the active ingredient is a DECR1 inhibitor or a DECR1 binder.

[0008] Use of a DECR1 inhibitor or a DECR1 binder in preparing a drug for treating or preventing breast cancer.

[0009] Use of a DECR1 inhibitor or a DECR1 binder in preparing a drug for improving the sensitivity or therapeutic effect of anti-breast cancer drugs in the treatment or prevention of breast cancer.

[0010] As an embodiment, the DECR1 is highly expressed in breast cancer tissue; and the high expression of DECR1 is associated with poor prognosis of breast cancer.

[0011] As an embodiment, knocking down the expression level of DECR1 in breast cancer reduces the proliferation, migration and invasion abilities of breast cancer cell lines.

[0012] As an embodiment, knocking down the expression level of DECR1 in breast cancer can reduce the mitochondrial ROS and Fe 2+ The levels and MDA content increased.

[0013] As an implementable method, knocking down the expression level of DECR1 in breast cancer increases the probability of ferroptosis in breast cancer tissue cells.

[0014] As an embodiment, knocking down the expression level of DECR1 in breast cancer reduces the PC content in breast cancer cells; knocking down the expression level of DECR1 in breast cancer increases the AA content in breast cancer cells; knocking down the expression level of DECR1 in breast cancer increases the PLA2G12A expression level in breast cancer cells;

[0015] The expression level of PLA2G12A in breast cancer cells is negatively correlated with the PC content in breast cancer cells, and positively correlated with the AA content in breast cancer cells; the expression level of PLA2G12A in breast cancer cells is positively correlated with the probability of ferroptosis in breast cancer cells.

[0016] In one embodiment, the DECR1 binder is Erigoster B.

[0017] As an embodiment, the ErigosterB forms hydrogen bonds with THR69, ASN144, THR196, LYS214, ILE243 and SER250, and binds to the DECR1.

[0018] The beneficial effects of the present invention are: the present invention evaluates the specific role of DECR1 in the progression of breast cancer, identifies it as a therapeutic target for breast cancer, reveals that the regulatory effect on ferroptosis is the key mechanism of action of DECR1 in promoting the progression of breast cancer, inhibits the expression of DECR1 in breast cancer tissue cells by Erigoster B, reduces the proliferation, migration and invasion ability of breast cancer, and increases the probability of ferroptosis of breast cancer tissue cells, providing new treatment strategies and ideas for the treatment of breast cancer. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is the expression of fatty acid metabolism-related genes in breast cancer tissues and normal tissues in the TCGA-BRCA-1096 dataset in Example 2 of the present invention.

[0020] Figure 2 A is a Kaplan-Meier curve diagram of patients with DECR1 expression above and below the critical value (calculated by the "bestssurv" algorithm) in Example 2 of the present invention; B is the relationship between DECR1 expression and survival probability estimated by data in the TCGA-BRCA-1096 dataset (n=788); C is the relationship between DECR1 expression and survival probability estimated by data in the GEO96058 dataset.

[0021] Figure 3 Representative images of IHC staining of DECR1 in breast cancer tissues (n=140) and normal breast tissues (n=77) in Example 2 of the present invention.

[0022] Figure 4 This is a diagram showing the protein expression of DECR1 in breast cancer tissue and normal breast tissue based on the IHC staining results in Example 2 of the present invention.

[0023] Figure 5 This is a Kaplan-Meier curve diagram of OS for patients whose DECR1 expression is above and below the critical value according to the IHC staining results in Example 2 of the present invention.

[0024] Figure 6 This is a graph showing the probability of OS prediction for cancer patients using the nomogram in Example 2 of the present invention; relevant factors, including age, site, pathological T stage (T), pathological N stage (N), American Joint Committee on Cancer (AJCC) stage, and DECR1 expression, are listed on the dotted axes. The 5-year and 10-year OS probabilities were plotted to calculate the OS incidence rate. *P < 0.05, **P < 0.01.

[0025] Figure 7 This is a graph showing the proliferation of MDA-MB-231 cells after DECR1 knockdown in Example 2 of the present invention.

[0026] Figure 8 This is a graph showing the proliferation of BT474 cells after DECR1 knockdown in Example 2 of the present invention.

[0027] Figure 9 This is a diagram of cell migration observed in the scratch wound test of breast cancer cells (MDA-MB-231 and BT474) after knockdown of DECR1 in Example 2 of the present invention.

[0028] Figure 10FIG2 is a diagram of an invasion assay using a Transwell chamber with a Matrigel-coated membrane in DECR1 knockdown MDA-MB-231 and BT474 cells in Example 2 of the present invention.

[0029] Figure 11 This figure shows the number of cells that have invaded into DECR1-knockdown MDA-MB-231 and BT474 cells using a Transwell chamber with a Matrigel-coated membrane in Example 2 of the present invention.

[0030] Figure 12 This figure shows the effect of knocking down DECR1 on the tumorigenicity of breast cancer cells in a subcutaneous xenograft model established in NOD-SCID mice in Example 2 of the present invention; tumors derived from MDA-MB-231 and BT474 (NC, shDECR1-1, shDECR1-2) cells were isolated (n=5 per group).

[0031] Figure 13 The tumor volume of the tumor derived from MDA-MB-231 cells in Example 2 of the present invention is about 50 mm 3 Growth graphs were drawn every two days thereafter; *P<0.05, **P<0.01.

[0032] Figure 14 The tumor volume of the BT474 cells in Example 2 of the present invention is about 50 mm 3 Growth graphs were drawn every two days thereafter; *P<0.05, **P<0.01.

[0033] Figure 15 This is a diagram of mitochondrial morphology observed using TEM after DECR1 knockout in Example 2 of the present invention.

[0034] Figure 16 This is a diagram showing the quantification of mitochondrial ROS levels using MitoSOX staining in MDA-MB-231 cells with stable knockdown of DECR1 in Example 2 of the present invention; the fluorescence intensity was quantified using flow cytometry, and the mitochondrial ROS level was expressed as the mean fluorescence intensity value.

[0035] Figure 17 In Example 2 of the present invention, MitoSOX staining was used to quantify mitochondrial ROS levels in BT474 cells with stable knockdown of DECR1; flow cytometry was used to quantify fluorescence intensity, and mitochondrial ROS levels were expressed as mean fluorescence intensity values.

[0036] Figure 18 The intracellular Fe in MDA-MB-231 cells after knocking down DECR1 was determined using the FerroOrange assay kit in Example 2 of the present invention. 2+Horizontal flow cytometry analysis diagram.

[0037] Figure 19 The intracellular Fe in BT474 cells after knocking down DECR1 was determined using the FerroOrange assay kit in Example 2 of the present invention. 2+ Horizontal flow cytometry analysis diagram.

[0038] Figure 20 This is a graph showing the measurement of MDA content in MDA-MB-231 cells with stable DECR1 knockdown in Example 2 of the present invention, *P<0.05, **P<0.01.

[0039] Figure 21 This is a graph showing the measurement of MDA content in BT474 cells with stable DECR1 knockdown in Example 2 of the present invention, *P<0.05, **P<0.01.

[0040] Figure 22 This is a volcano plot of non-targeted metabolomics to identify dysregulated metabolites in DECR1 knockdown compared with negative control MDA-MB-231 and BT474 cells in Example 2 of the present invention.

[0041] Figure 23 This is an expression diagram of the metabolism-related gene PLA2G12A after knocking down DECR1 in Example 2 of the present invention.

[0042] Figure 24 This is a graph showing the PLA2G12A content after knocking down DECR1 in breast cancer cells in Example 2 of the present invention.

[0043] Figure 25 This is a graph showing the content of seven PCs in MDA-MB-231 cells with stably knocked-down DECR1 determined by mass spectrometry in Example 2 of the present invention.

[0044] Figure 26 This is a graph showing the content of seven PCs in BT474 cells with stably knocked-down DECR1 determined by mass spectrometry in Example 2 of the present invention.

[0045] Figure 27 This is a graph showing the intracellular AA content measured after DECR1 knockdown using ELISA in Example 2 of the present invention.

[0046] Figure 28 This is a graph showing the AA content measured after further knockout of PLA2G12A using stable DECR1 knockout in breast cancer cells in Example 2 of the present invention.

[0047] Figure 29This is a graph showing mitochondrial ROS levels quantified using MitoSOX staining in MDA-MB-231 cells with stable DECR1 knockout and further PLA2G12A knockout in Example 2 of the present invention; fluorescence intensity was quantified using flow cytometry, and mitochondrial ROS levels were expressed as mean fluorescence intensity values.

[0048] Figure 30 This is a graph showing quantification of mitochondrial ROS levels using MitoSOX staining in BT474 cells with stable DECR1 knockout and further PLA2G12A knockout in Example 2 of the present invention; fluorescence intensity was quantified using flow cytometry, and mitochondrial ROS levels were expressed as mean fluorescence intensity values.

[0049] Figure 31 The intracellular Fe2 + Horizontal flow cytometry analysis; *P<0.05, **P<0.01.

[0050] Figure 32 The intracellular Fe2 + Horizontal flow cytometry analysis; *P<0.05, **P<0.01.

[0051] Figure 33 This is a diagram of the binding pattern of DECR1 and erigoster B in the 2D model in Example 2 of the present invention.

[0052] Figure 34 This is a diagram of the binding pattern of DECR1 and erigoster B in the 3D model in Example 2 of the present invention.

[0053] Figure 35 This is a comparison diagram of the binding modes between DECR1 and NADP and between DECR1 and ErigosterB in Example 2 of the present invention.

[0054] Figure 36 This is an SPR analysis chart of the DECR1-Erigoster-B binding affinity in Example 2 of the present invention.

[0055] Figure 37 This is a diagram showing that Erigoster B treatment damages the proliferation of MDA-MB-231 and BT474 cells in Example 2 of the present invention.

[0056] Figure 38Graphs showing the migration of MDA-MB-231 and BT474 cells with and without Erigoster B treatment in wound healing assays in Example 2 of the present invention.

[0057] Figure 39 Graph showing the invasion assay in MDA-MB-231 and BT474 cells with and without Erigoster B treatment in Example 2 of the present invention (performed in a transwell chamber with a Matrigel-coated membrane).

[0058] Figure 40 This figure shows the number of invaded cells measured in MDA-MB-231 and BT474 cells treated with and without Erigoster B in Example 2 of the present invention.

[0059] Figure 41 This is a diagram showing the effect of Erigoster B on breast cancer progression in a subcutaneous xenograft model established in NOD-SCID mice in Example 2 of the present invention; the tumors were derived from 4T1 cells (n=5 per group).

[0060] Figure 42 The tumor volume in Example 2 of the present invention is about 50 mm 3 Afterwards, tumor growth was plotted every two days; *P<0.05, **P<0.01.

[0061] Figure 43 This is a schematic diagram of the evaluation of MDA-MB-231 cell death induced by 25 μM Erigoster B treatment using a ferroptosis inhibitor (ferrostatin-1, 1 μM), an autophagy inhibitor (3-MA, 1 μM), and an apoptosis inhibitor (Z-VAD-FMK, 5 μM) in Example 2 of the present invention.

[0062] Figure 44 This is a schematic diagram of the evaluation of BT474 cell death induced by 25 μM Erigoster B treatment using a ferroptosis inhibitor (ferrostatin-1, 1 μM), an autophagy inhibitor (3-MA, 1 μM), and an apoptosis inhibitor (Z-VAD-FMK, 5 μM) in Example 2 of the present invention.

[0063] Figure 45 This is a quantitative graph of mitochondrial ROS levels in MDA-MB-231 cells treated with or without Erigoster B in Example 2 of the present invention using MitoSOX staining; the fluorescence intensity was quantified using flow cytometry, and the mitochondrial ROS level was expressed as the mean fluorescence intensity value.

[0064] Figure 46This is a quantitative graph of mitochondrial ROS levels in BT474 cells treated with or without Erigoster B in Example 2 of the present invention using MitoSOX staining; the fluorescence intensity was quantified using flow cytometry, and the mitochondrial ROS level was expressed as the mean fluorescence intensity value.

[0065] Figure 47 The intracellular Fe in MDA-MB-231 cells treated with or without Erigoster B was determined using the FerroOrange assay kit in Example 2 of the present invention. 2+ Horizontal flow cytometry analysis graph.

[0066] Figure 48 The intracellular Fe in BT474 cells treated with or without Erigoster B was determined using the FerroOrange assay kit in Example 2 of the present invention. 2+ Horizontal flow cytometry analysis graph.

[0067] Figure 49 This is a graph showing the measurement of AA content in breast cancer cells treated with or without Erigoster B using ELISA in Example 2 of the present invention.

[0068] Figure 50 This is a graph showing the contents of seven PCs measured by mass spectrometry in MDA-MB-231 cells treated with or without Erigoster B in Example 2 of the present invention; *P<0.05, **P<0.01.

[0069] Figure 51 This is a graph showing the contents of seven PCs measured by mass spectrometry in BT474 cells treated with or without Erigoster B in Example 2 of the present invention; *P<0.05, **P<0.01. DETAILED DESCRIPTION

[0070] The present invention will be further described in detail below with reference to specific embodiments.

[0071] It should be noted that these embodiments are only used to illustrate the present invention, rather than to limit the present invention. Simple improvements to the method based on the concept of the present invention fall within the scope of protection claimed by the present invention.

[0072] Example 1 Methods and Materials

[0073] 1.1 Bioinformatics analysis

[0074] Fatty acid metabolism (FAM)-related genes were obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG; https: / / www.genome.jp / kegg / ). Data from an independent cohort (TCGA-BRCA) consisting of 1096 cases were downloaded from The Cancer Genome Atlas (TCGA) and imported into R (version 4.1) (https: / / bioconductor.org / bioclite.r). Within this cohort, 1045 cases with complete clinical follow-up data were retained for further analysis. A dataset (GSE96058) consisting of 3409 cases was obtained from the GEO database to validate the gene expression and prognostic value of DECR1 in breast cancer patients. Survival analysis involved normalizing gene expression data and centering them to the mean, and plotting Kaplan-Meier curves to demonstrate the value of FAM-related genes in predicting overall survival (OS). The outcome event was defined as "death." The optimal separation algorithm was used to estimate the cutoff expression level for each gene using the R package "surfminer." The log-rank test was used to analyze the data of the Kaplan-Meier plots and the results of the univariate Cox regression analysis. The correlation between DECR1 expression and OS rate was further evaluated by multivariate Cox regression analysis, and a nomogram was generated with the “rms” package based on the results of the multivariate Cox regression analysis.

[0075] Protein-protein interaction network: FAM-related genes were imported into the STRING database (https: / / cn.string-db.org / ) to obtain a protein-protein interaction network diagram. The degree, topological coefficient, and neighborhood connectivity of the genes were then scored using Cytoscape (version 3.7.0), and genes with all three scores higher than the median score were selected.

[0076] 1.2 Tissue microarray and immunohistochemical staining

[0077] A total of 140 breast cancer tissues and 77 adjacent adjacent tissues were collected based on the completeness of clinical and pathological information and the availability of follow-up information. The diagnoses of these specimens were further verified by a pathologist. To construct the tissue microarray, a representative region was selected from the paraffin tissue of each specimen. Furthermore, microarray sections were obtained from the paraffin blocks of the tissue microarray. The Medical Ethics Committee of Shanghai Aoduo Biotechnology Co., Ltd. granted ethical approval for this project (approval numbers: SHYJC-CP-1901002; SHYJC-CP-1607006). Tissue microarrays were incubated with a rabbit monoclonal anti-DECR1 antibody (Abcam, ab198848) at a dilution of 1:100 at 4°C. The EnVision system was used for immunohistochemical staining. Diaminobenzidine (Dako, Glostrup, Denmark) was used to visualize antibody binding. DECR1 staining intensity was calculated using Image ProPlus (version 6.0.0.260, USA).

[0078] 1.3 Cell culture

[0079] Cell culture: Human breast cancer cell lines MDA-MB-231 and BT474 were purchased from the American Type Culture Collection (ATCC). All cells were maintained in Dulbecco's modified Eagle's medium (DMEM) or RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS) (Gibco, 10437028) and 1% penicillin / streptomycin (Gibco, 10378016) at 37°C in a humidified atmosphere of 5% CO2.

[0080] Construction of shDECR1 cell line.

[0081] 1.4 Cell function assay (cell viability, cell migration, cell invasion)

[0082] Cell viability: Breast cancer cell viability was assessed using a cell counting kit-8 (CCK-8) cell proliferation assay kit (Solarbio, CA1210). 5 The density of individual cells / mL is seeded in 96-well plates and cultivated. After incubation for 48 hours with DMSO, 10 μ L CCK-8 solutions are added into culture medium, and cells are incubated for another 2 hours. OD is then measured at 450nm using a multi-well spectrophotometer (microplate reader). Cell viability is represented by the percentage of control (untreated) cell viability.

[0083] Cell migration: When MDA-MB-231 and BT474 cells reached 100% confluency, a wound was created in the center of each well using a 200 μL pipette tip. The wounded area was photographed at 0 and 24 hours. Each experiment was repeated three times.

[0084] Cell invasion: Breast cancer cells were cultured in serum-free medium for 12 h. The cell concentration was adjusted to 4-5×10 5 Cells / mL. A Transwell chamber (Corning, NY, USA) with a Matrigel coating membrane is placed in a 24-well plate. RPMI-1640 medium (500 μL) is placed in the bottom compartment, and a cell suspension of 200 μL is placed in the upper compartment. Then, the cells are incubated for 24 hours. The cells on the lower surface of the membrane are fixed with glacial acetic acid for 15-30 minutes, stained with crystal violet for 30 minutes, and the cells are counted. The experiment was repeated three times independently.

[0085] 1.5 Transmission electron microscopy

[0086] Transmission electron microscopy was used to observe the morphological characteristics of breast cancer cells undergoing ferroptosis. The main steps were fixation: samples were pre-fixed with 3% glutaraldehyde and then post-fixed with 1% osmium tetroxide; dehydration: dehydration in acetone in a stepwise manner, with a dehydrating agent concentration gradient of 30% → 50% → 70% → 80% → 90% → 95% → 100% (with 100% concentration changed three times); infiltration and embedding: dehydrating agent and Epon812 embedding medium were used in ratios of 3:1, 1:1, and 1:3, respectively, and finally Ep812 embedding. Ultrathin sections of approximately 60 to 90 nm were prepared using an ultrathin microtome, which was then spread and placed on a copper grid. Staining was performed using uranyl acetate for 10 to 15 min, followed by lead citrate for 1 to 2 min at room temperature. Electron microscopy was performed using a JEM-1400FLASH transmission electron microscope produced by JEOL. Each copper grid was first observed at 6000x magnification, and images of the desired area were captured to observe the specific morphology of cells and organelles.

[0087] 1.6 Transcriptomic Analysis

[0088] Transcriptome sequencing was performed using previously constructed MDA-MB-231 and BT474 cell lines with stable DECR1 knockdown. First, 1 × 107 cells were collected from each group, with three replicates per group. Total RNA was then extracted using the Trizol method. Transcriptome sequencing libraries were then constructed using the Illumina RNA Library Preparation Kit (NEB, USA). Next, the libraries were sequenced on the Illumina NovaSeq platform. Raw reads were processed in fastq format. Read counts for each gene were then calculated using the featureCounts (version 1.5.0) software package.

[0089] 1.7 Non-targeted metabolomics analysis

[0090] For non-targeted metabolomics, 1 × 10 7The cells were placed in EP tubes and the samples were resuspended in pre-cooled 80% methanol by vortexing. Then, the samples were thawed on ice and centrifuged for 30 seconds. After ultrasonic treatment for 6 minutes, the samples were centrifuged at 5000 rpm, 4°C for 1 minute. The supernatant was freeze-dried and dissolved in 10% methanol. Finally, the solution was injected into the LC-MS / MS system for analysis. UHPLC-MS / MS analysis was performed using a Vanquish UHPLC system (ThermoFisher, Germany) coupled to an Orbitrap Q ExactiveTM HF mass spectrometer (ThermoFisher, Germany) from Novogene Co., Ltd. (Beijing, China). The raw data files generated by UHPLC-MS / MS were processed using Compound Discoverer 3.1 (CD3.1, ThermoFisher) to perform peak alignment, peak picking and quantification of each metabolite. The KEGG database, the Human Metabolome Database (HMDB; https: / / hmdb.ca / metabolites ), and the LIPIDMaps database ( http: / / www.lipidmaps.org / ) were used.

[0091] 1.8 Mass spectrometry analysis

[0092] The control or DECR1 knockdown MDA-MB-231 or BT474 cells were collected, and the cell number was approximately 1×10 7 Five replicates per group were collected and then ground and pulverized in a 70% methanol / water solution. Metabolites were then extracted with chloroform. Chloroform-containing metabolites were further concentrated in a concentrator. The concentrate was further dissolved in 300 μL of a 1:1 isopropanol:methanol solution containing 100 ng / mL of the internal standard PC (15:0 / 18:1-7) and centrifuged for 15 minutes. The supernatant was retained for analysis. Additionally, a PC (16:0-18:1) standard solution (500 ng / mL) was analyzed, with an internal standard concentration of 100 ng / mL. Chromatographic analysis was performed on a Waters Acquity UPLC using an Acquity UPLC BEH Amide column (1.7 μm, 2.1 mm × 100 mm). Chromatographic separation conditions were: column temperature 45°C; flow rate 0.300 mL / min. Metabolomic analysis was performed using mobile phase A (H2O: acetonitrile 5 mM; NH4AC, 95 / 5, v / v) and mobile phase B (H2O: methanol 5 mM; NH4AC 50 / 50, v / v, pH adjusted to 8.0 with aqueous ammonia) with the following elution gradient: 0–1 min, 0% B; 1–2 min, 50% B; 2–4 min, 100% B; 4–6 min, 0% B.

[0093] In addition, mass spectrometry analysis was performed on an AB SCIEX 5500 triple quadrupole (QQQ) mass spectrometer using an electrospray ionization (ESI) source. Mass spectrometry was performed under the following conditions: curtain gas, 35 arb; collision gas, 9 arb; ion spray voltage, 4500 V; temperature, 450°C; ion source gas 1, 50 arb; and ion source gas 2, 50 arb. The final results were integrated using MultiQuant software, and metabolite content was calculated using the internal standard method.

[0094] 1.9 Arachidonic acid content detection

[0095] MDA-MB-231 and BT474 cells were collected after DECR1 knockdown or treatment with Erigoster B (5 μM, 48 h). 150-200 μL of PBS was then added to each 106 breast cancer cells for resuspending. The cells were lysed by sonication, and the supernatant was tested using an enzyme-linked immunosorbent assay (ELISA) kit according to the manufacturer's instructions. The arachidonic acid (AA) assay kit (E-EL-0051c) was purchased from Elabscence.

[0096] 1.10qRT-PCR

[0097] Total RNA was extracted and purified using TRIzol reagent (Magen, R4801-01). Next, reverse transcription was performed using a transcription kit (Vazyme, R122-01). Quantitative RT-PCR was performed using an ABI 7900 real-time PCR system. Finally, the data were analyzed using the 2-ΔΔCt method. The mRNA levels of the target genes were normalized to the levels of β-actin or GAPDH.

[0098] 1.11 Animal Experimentation

[0099] NOD-SCID mice were purchased from Hunan SJA Laboratory Animal Co., Ltd. The animals were housed in cages at 23 ± 2°C and fed with standard laboratory diet and tap water throughout the experiment.

[0100] Orthotopic xenograft model: Mice were anesthetized with 4% chloral hydrate and 100 μL of 1x10 7 Cancer breast cell suspensions of cells were injected into the mammary fat pad to establish an orthotopic xenograft model. For tumorigenesis assays, negative control (NC) MDA-MB-231 and BT474 cells, DECR1 knockdown (shDECR1) MDA-MB-231 and BT 474 cells, and 4T1 cells were injected. Tumors were measured every two days, and tumor volume was calculated as follows: tumor volume = (length × width) 2 ) / 2.

[0101] 1.12 Detection of ferroptosis-related indicators

[0102] In order to evaluate the ferroptosis of each group, MDA, ROS and Fe 2+ The lipid peroxidation (MDA) assay kit (Beyotime Biotechnology, S0131S) was used according to the kit instructions.

[0103] 1.13 Computer-Assisted Virtual Screening

[0104] Receptors for virtual screening: Using the Protein Preparation Wizard Panel ( 2021) optimized the protein structure of DECR1 by correcting the bond order, adding hydrogen atoms, distributing charges, and predicting the protonation state (pH 7.0). Constrained energy optimization was performed using the OPLS4 force field to eliminate atomic conflicts in the structure, and the root mean square deviation (RMSD) of heavy atoms converged to And optimize the side chain position to obtain a reasonable side chain structure.

[0105] Preparation of compound library: Using LigPrep panel ( 2021) were used to treat compounds from L6020. First, the compounds were protonated and desalted using the Epik program at pH 7.0 ± 2.0 to generate tautomers while preserving the original atomic chirality. To ensure conformational diversity of the small molecules during the virtual screening process, a maximum of 32 conformations were generated for each small molecule.

[0106] The screening was carried out in the following manner: Glide HTVS [High-Throughput Virtual Screening mode] → GGlide SP [Standard Precision mode] → GGlide XP [Extra Precision]. The protein structure was set to rigid, the small molecules were set to flexible, and other parameters were set to default values. The docked structures were energy-optimized, and the structures within the top 50% of the docking scores were retained for the next round of screening. Visual inspection was performed after removing duplicates and filtering for drug-like properties. After the initial screening, approximately 15,000 small molecule compounds were obtained. After removing duplicate structures, 2,497 compounds were retained. QikProp was used to filter based on predicted absorption, distribution, metabolism, and excretion (ADME) properties (specified criteria: 0 < H-bond donors < 6, 150 < Mol Weight < 725). Compounds with a molecular weight greater than 725 and more than 6 H-bond donors were removed, resulting in a final set of 1,258 compounds. Then, Canvas was used to generate binary fingerprints for these 1,258 compounds, and hierarchical clustering was performed based on the Tanimoto similarity metric. Compounds with the highest docking score (in kcal / mol, where a lower value indicates a higher affinity between the receptor and ligand) were selected from each cluster. This process yielded a final set of 100 small molecule compounds representing different chemical structures

[0107] 1.1 Surface Plasmon Resonance (SPR) assay

[0108] The interaction between the analyte and the ligand was evaluated at room temperature using an OpenSPR instrument (Nicoya, Canada). First, according to the standard procedure, a COOH sensor chip was installed in the OpenSPR instrument. The buffer was run at maximum flow rate and degassing bubble parameters after reaching the signal baseline. Then, 10 mM glycine HCl (pH 7.4) was injected onto the surface of the sensor chip. The chip was activated, and the prepared EDC and NHS solutions were injected to complete the functionalization of the chip surface. Then, the sample was injected at a flow rate of 20 μL / min

[0109] Finally, different concentrations of the analyte were separately injected onto the surface of the ligand chip (specific concentrations are provided in the experimental results), and the analyte was sampled at a rate of 20 μL / min. The binding time of the analyte to the ligand was 240 s, and the natural dissociation time was 360 s. In each cycle, a 200 μL volume of the sample flowed over the chip at a constant flow rate of 20 μL / min for 240 s. The bound compounds were dissociated from the coated surface by treatment with acidic and basic solutions. After each measurement, the small molecules and the target protein were separated by treatment with 10 mM glycine-HCl (pH 1.5). Finally, the kinetic parameters of the binding reaction were calculated and analyzed using Trace Drawer software (Ridgeview Instruments AB, Sweden)

[0110] Example 2 Analysis Results

[0111] 2.1DECR1 is overexpressed in clinical breast cancer samples and is associated with poor prognosis in patients

[0112] See also Figure 1-6 , analyzed the expression of 84 fatty acid metabolism-related genes in breast cancer and adjacent tissues. First, by constructing a protein-protein interaction network and screening 19 key genes based on Dgree and Neibo ranking, expression analysis of these 19 key genes revealed that only DECR1 was expressed at a statistically significant higher level in breast cancer tissue compared to adjacent tissues. Furthermore, both the TCGA and GEO96058 datasets showed that high DECR1 expression was associated with poor patient prognosis, suggesting that DECR1 has the potential to serve as a therapeutic target for breast cancer.

[0113] To further clarify the role of DECR1 in breast cancer, immunohistochemical staining analysis was performed on tissue microarrays constructed from 140 breast cancer clinical samples and 77 adjacent normal breast tissues. The results showed that compared with adjacent tissues, DECR1 was highly expressed in breast cancer tissues, and high expression of DECR1 was positively correlated with poor prognosis of patients.

[0114] 2.2 Effect of DECR1 on the malignant phenotype of tumor cells

[0115] Bioinformatics analysis was used to identify whether DECR1 has the potential to be a therapeutic target for breast cancer. A breast cancer cell line with stable DECR1 knockdown was constructed by lentiviral transfection to clarify the effect of inhibiting DECR1 expression on the malignant phenotype of breast cancer cells. Figure 7-14 Compared with the control group, the proliferation, migration, and invasion abilities of the DECR1 knockdown cell lines were inhibited. In addition, an orthotopic xenograft model of breast cancer was constructed by injecting breast cancer cells from different treatment groups into the mammary fat pad of NOD-SCID mice to determine the role of DECR1 in vivo. The results showed that after DECR1 expression was inhibited, the growth rate of tumor transplants decreased, and the tumor volume and size were significantly lower than those in the control group. In summary, these results suggest that DECR1 promotes the progression of breast cancer both in vivo and in vitro.

[0116] 2.3 Targeting DECR1 to induce ferroptosis in breast cancer cells

[0117] The protein encoded by DECR1 is an auxiliary enzyme for fatty acid β-oxidation. The degradation of PUFA requires the help of multiple auxiliary enzymes, including δ2,δ3-enoyl-CoA isomerase and NADPH-dependent 2,4-dienoyl-CoA reductase (DECR1). DECR1 can act as a negative regulator of the androgen receptor in prostate cancer. Inhibition of DECR1 can lead to the accumulation of PUFA in cells, triggering cellular oxidative stress and lipid peroxidation, thereby inducing cell ferroptosis. PUFA-related lipid peroxidation is a characteristic and driving factor of ferroptosis. The aim of this study was to investigate whether the expression level of DECR1 in breast cancer cells would interfere with cell ferroptosis. Figure 15-21 First, transmission electron microscopy was used to observe whether the morphological changes of cells after DECR1 knockdown were consistent with the characteristics of ferroptosis. Electron microscopy results showed that after DECR1 knockdown, the mitochondrial membrane density was concentrated, the number of mitochondrial cristae was reduced or absent, the mitochondrial outer membrane was ruptured, and the cell nucleus size was normal. The above characteristics are consistent with the characteristics of breast cancer cells undergoing ferroptosis. Therefore, inhibition of DECR1 expression will induce ferroptosis in breast cancer cells. In addition, mitochondrial ROS and Fe in DECR1 knockdown MDA-MB-231 and BT474 cells were detected. 2+ The levels of mitochondrial ROS and Fe in DECR1 knockdown MDA-MB-231 and BT474 cells were compared with those in negative control cells. 2+ The levels of DECR1 were significantly increased. In addition, the content of MDA, a product of cellular lipid oxidation, was detected and found to be increased in breast cancer cells with stable DECR1 knockdown. These findings suggest that DECR1 knockdown may induce ferroptosis in breast cancer cells.

[0118] 2.4 Targeting DECR1 induces ferroptosis in breast cancer cells by promoting phosphatidylcholine metabolism

[0119] To further explore the potential mechanism by which DECR1 promotes cancer progression by interfering with ferroptosis, transcriptome sequencing was performed on DECR1-knockdown MDA-MB-231 and BT474 cells to identify genes dysregulated after DECR1 knockdown. Given the key role of DECR1 in fatty acid oxidation and its profound impact on cellular metabolism, metabolomics analysis was also performed to identify metabolites with significant changes. Figure 22-32Through multi-omics combined analysis, it was found that after DECR1 knockdown, PC metabolism was activated, PC content decreased, and conversely, AA content increased. At the same time, increased PLA2G12A expression levels were observed in DECR1 knockdown breast cancer cells. In addition, the content of various phospholipids in DECR1 knockdown breast cancer cells was measured using mass spectrometry. The results showed that inhibiting DECR1 expression significantly reduced the content of various PCs and increased the content of AA.

[0120] AA is an omega-6 PUFA with the widest distribution and important biological activities in the body. Under physiological conditions, AA is primarily bound to PC or phosphatidylethanolamine glycerol. Under certain stimuli, phospholipase A2 (PLA2) is activated and catalyzes the hydrolysis of phospholipid diacyl groups, resulting in the release of AA into the cell in a free form. The AA metabolic pathway in the KEGG database indicates that PC hydrolysis, catalyzed by PLA2G12A, produces a large amount of AA. DECR1 knockdown cells showed increased PLA2G12A levels. In cells with stable DECR1 knockdown, further knockdown of PLA2G12A was accompanied by a decrease in intracellular AA content, protecting breast cancer cells from ferroptosis. These results suggest that targeting the DECR1-PLA2G12A signaling axis in breast cancer can promote AA production by regulating phospholipid metabolism, activate cellular ferroptosis, and thus inhibit tumor progression.

[0121] 2.5DECR1 inhibitor Erigoster B exhibits anti-tumor activity

[0122] It has been shown that inhibition of DECR1 may be a promising strategy for treating breast cancer. Therefore, computer-assisted virtual screening and molecular docking methods were used to search for small molecules targeting DECR1 to preliminarily explore their potential as drug candidates. Figure 33-42After screening and molecular docking scoring, the compound Erigoster B was found to be the most suitable for binding to the DECR1 protein. The main amino acid residues for the interaction between DECR1 and Erigoster B are GLY66, THR69, GLY70, LEU71, GLY72, ASN144, ALA145, ALA146, ASN148, ILE150, ILE195, THR196, THR197, LYS214, PRO240, GLY241, PRO242, ILE243, THR245, and ARG251. In addition, Erigoster B forms hydrogen bonds with THR69, ASN144, THR196, LYS214, ILE243, and SER250, which play a crucial role in the binding between DECR1 and Erigoster B. In vitro SPR experiments verified the binding ability of Erigoster B to DECR1. The results showed that DECR1 captured on the COOH chip could bind to Erigoster B with an affinity constant of 40.5 μM. In addition, the anti-tumor effect of Erigoster B was evaluated and found to inhibit the proliferation of breast cancer cells.

[0123] The effects of Erigoster B on the malignant phenotype of breast cancer cells were examined. The results showed that after 48 hours of Erigoster B treatment, the migration and invasion abilities of breast cancer cells were significantly inhibited. Preliminary evaluation of drug treatment revealed that the IC50 of Erigoster B was 17.12 μM in MDA-MB-231 cells and 16.36 μM in BT474 cells. Erigoster B treatment also effectively inhibited tumor growth in vivo, with an effect comparable to that of paclitaxel. These findings suggest that Erigoster B has the potential to treat breast cancer and warrants further investigation as a candidate anti-breast cancer drug.

[0124] 2.6 Erigoster B induces ferroptosis in breast cancer cells

[0125] Erigoster B is a phenolic acid compound that was first identified during a systematic study of the phytochemistry and active components of Erigosterone. This compound has been shown to have antioxidant activity comparable to that of baicalin. Figure 43 In an attempt to rescue Erigoster B-induced cell death, different cell death inhibitors were applied and it was found that ferroptosis was the main mechanism of Erigoster B-induced breast cancer cell death. As expected, Erigoster B treatment reduced mitochondrial ROS and Fe 2+levels, suggesting that Erigoster B may exert its anti-tumor effects by inducing ferroptosis in breast cancer cells. Furthermore, we found that Erigoster B treatment of breast cancer cells decreased intracellular PC content and increased AA content. These findings suggest that Erigoster B has anti-tumor activity and induces ferroptosis by regulating PC metabolism and increasing AA content.

[0126] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described with reference to the preferred embodiments of the present invention, it should be understood by those skilled in the art that various changes can be made in form and details without departing from the spirit and scope of the present invention as defined in the appended claims.

Claims

1. Use of a DECR1 binder as the sole active ingredient in the preparation of a drug for treating or preventing breast cancer, wherein the DECR1 binder is Erigoster B.

2. Use of a DECR1 binder as the sole active ingredient in the preparation of a drug for improving the sensitivity or therapeutic effect of anti-breast cancer drugs in the treatment or prevention of breast cancer, wherein the DECR1 binder is Erigoster B.

3. The use according to claim 1 or 2, characterized in that The DECR1 is highly expressed in breast cancer tissue; and the high expression of DECR1 is associated with poor prognosis of breast cancer.

4. The use according to claim 1 or 2, characterized in that The ErigosterB forms hydrogen bonds with THR69, ASN144, THR196, LYS214, ILE243 and SER250, and binds to the DECR1.

Images