Medicine for preventing and treating chronic drug toxicity retina photoreceptor cell injury

Abstract

The invention discloses a medicine for preventing and treating chronic drug toxicity retinal photoreceptor cell injury. According to the invention, a chronic drug toxicity retina photoreceptor cell injury animal model constructed by MMS induction is used for exploring and understanding a regulation mechanism of DNA methylation on drug toxicity retina injury, it is clear that decitabine promotes expression of Crx and downstream retina specific genes, and decitabine is a key factor for improving chronic drug toxicity retina photoreceptor cell injury caused by MMS; decitabine can improve the morphological structure and visual function of alkylating agent induced chronic drug toxicity retinal photoreceptor cells, and has an obvious protective effect on drug toxicity retinal injury.

Description

[0001] This invention is a divisional application of the invention patent with application number 202210848767.4, entitled "Application of decitabine in the preparation of drugs for the treatment of chronic drug-toxic retinal photoreceptor cell damage", and the original application date is July 19, 2022. Technical Field

[0002] The present invention relates to the field of pharmaceutical technology, and in particular to application of decitabine in the preparation of a medicine for treating chronic drug toxicity retinal photoreceptor cell damage. Background Art

[0003] Cancer is one of the most common fatal diseases in today's society.

[0004] Surgery and radiotherapy are the main treatments for localized and non-metastatic cancers, while anticancer drug therapy is currently the preferred treatment for metastatic cancer. Since the advent of the first chemotherapy drug, the alkylating agent nitrogen mustard, different types of chemotherapy drugs have been widely used in clinical practice. Chemotherapy drugs are generally toxic compounds and are not specific. While killing cancer cells, they also produce varying degrees of irreversible toxic side effects on normal tissue cells, causing great pain to patients.

[0005] At present, studies have found that cisplatin and carmustine used to treat metastatic breast cancer and malignant glioma can cause drug-toxic retinopathy; gemcitabine used to treat non-small cell lung cancer, breast cancer, ovarian cancer or pancreatic cancer can cause retinal photoreceptor cell lesions; paclitaxel used to treat lung cancer or prostate cancer can cause retinal macular lesions, etc. With the increase in the incidence of cancer, many types of chemotherapy drugs are widely used in clinical practice. The number of patients with acute retinal damage and chronic retinal damage, the most common drug-toxic retinal photoreceptor cell damage, is increasing. Among them, the incidence of patients with chronic drug-toxic retinal photoreceptor cell damage is greater than 80%. This is related to the long-term use of anticancer drugs by patients, excessive accumulation of drug toxicity, or reduced function of organs metabolizing anticancer drugs, resulting in long-term high concentrations of anticancer drugs in the blood, which circulate in the blood to the retina and cause chronic retinal photoreceptor cell damage. At present, it is particularly important to find targets that can reduce or avoid drug-toxic retinal photoreceptor cell damage caused by chemotherapy drugs to the retina, and it is hoped that drugs that can intervene or treat drug-toxic retinal photoreceptor cell damage can be screened.

[0006] The information disclosed in this background technology section is only used to deepen the understanding of the background technology of the present disclosure, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art known to those skilled in the art. Summary of the invention

[0007] DNA alkylating agents are chemotherapy drugs that kill tumor cells by adding an alkyl group to the DNA molecule to cause DNA mutation damage. They have been widely used in clinical medicine. The inventors of this application have found that in the process of chronic drug-toxic retinal photoreceptor cell damage caused by methyl methyl sulfonate (MMS), the DNA methylation marker 5mC is significantly enhanced, and the expression of DNA methylation-related regulatory factors DNMTs and MeCP2 is upregulated, suggesting that in the process of drug-toxic retinal photoreceptor cell damage, DNMTs and MeCP2 may affect the expression of downstream specific genes by changing DNA methylation modification; RRBS and RNA-seq association analysis found that the retinal development-related transcription factor cone rod homology domain (Cone rod homology domain) in the chronic drug-toxic retinal photoreceptor cell damage model The methylation level of homeobox (Crx) increased, the mRNA expression decreased, and the expression of Crx regulatory genes Rp1 and Rhodopsin also decreased; further research results confirmed that Crx gene knockout can seriously affect the formation of retinal photoreceptor outer segments and the formation of outer plexiform layer synapses; and Crx's downstream gene Rp1 encodes doublecortin, which is an essential transcription factor for retinal photoreceptor differentiation and participates in the formation of retinal photoreceptor outer segments. It plays a key role in the correct orientation and orderly stacking of outer segment membrane discs. In this chronic drug toxicity retinal photoreceptor cell injury model, abnormalities in the morphology of retinal photoreceptor outer segments and synapses, as well as decreased retinal function, were also found, accompanied by downregulation of Crx and Rp1 gene expression. This indicates that DNA methylation modification is involved in regulating the expression of Crx, thereby affecting the morphological changes of retinal photoreceptor cells and changes in visual function.

[0008] Therefore, this application is precisely designed based on the specific pathogenesis of drug-toxic retinal photoreceptor cell damage, and uses DNA methyltransferase inhibitor decitabine (5-aza-2'-deoxycytidine, 5-aza-dC) for vitreous injection to reduce the activity of DNA methyltransferase, promote the expression of related genes, and observe and study its phenotypic effects on chronic drug-toxic retinal photoreceptor cell damage caused by MMS. The results confirmed that DNA methyltransferase inhibitors have a clear protective effect on chronic drug-toxic retinal photoreceptor cell damage caused by alkylating agents.

[0009] Specifically, according to one aspect of the present disclosure, decitabine is used in the preparation of a drug for intervening or treating chronic drug-toxic retinal photoreceptor cell damage induced by alkylating agents.

[0010] According to another aspect of the present disclosure, decitabine is used to prepare a drug for improving the morphological structure and / or visual function of retinal photoreceptor cells induced by chronic drug toxicity of alkylating agents.

[0011] In some embodiments of the present disclosure, the DNA alkylating agent is methyl methanesulfonate, N-methyl-N-nitrosourea (MNU), cyclophosphamide, chlorambucil, methyl procarbazine, camoxetine, nimoxetine, streptozocin, platinum, temozolomide, etc., which are all commonly used DNA alkylating agents in clinical practice. Drugs commonly used in specific animal models for drug toxicity of retinal photoreceptor cell damage are methyl methanesulfonamide and N-methyl-N-nitrosourea, etc.

[0012] In some embodiments of the present disclosure, the administration method of decitabine is: intravitreal injection of 2 μM 5-aza-dC solution 3 times, each injection volume is 1-200 μL, once every week, and the first injection is 24 hours before the administration of the alkylating agent. Intravitreal injection of drugs is a common method for treating retinal diseases clinically, and the injection volume of decitabine is determined according to the size of the vitreous cavity, for example, 1 μL is injected into the mouse vitreous, 2 μ is injected into the rat vitreous, 2.5-3 μL is injected into the guinea pig vitreous, 50-100 μL is injected into the rabbit vitreous, and 100-200 μL is injected into the human vitreous.

[0013] According to another aspect of the present disclosure, decitabine is used to prepare a drug that promotes the expression of Crx and downstream retinal-specific genes. 5-aza-dC is used to intervene in DNA methylation modification, while inhibiting the activity of DNA methyltransferase, changing the DNA methylation level, increasing the expression of Crx transcription factor, and regulating the transcription of downstream genes. Crx is an important regulatory transcription factor for photoreceptor cell development and gene expression, and it is determined to be a candidate gene for CORD. In addition to CORD, Crx mutations can also lead to a variety of retinal degeneration diseases such as retinitis pigmentosa (RP) and Leber congenital amaurosis (LCA).

[0014] In some embodiments of the present disclosure, decitabine or a pharmaceutically acceptable salt thereof and a pharmaceutically acceptable carrier constitute a clinically acceptable formulation.

[0015] In some embodiments of the present disclosure, the carrier is at least one of conventional diluents, excipients, fillers, binders, wetting agents, disintegrants, absorption enhancers, surfactants, adsorption carriers, lubricants, flavoring agents, and sweeteners in the pharmaceutical field.

[0016] In some embodiments of the present disclosure, the clinically acceptable preparation is any one of tablets, powders, granules, capsules, ointments, eye drops, eye ointments, gels, oral solutions and injections.

[0017] One or more technical solutions provided in the embodiments of the present application have at least any of the following technical effects or advantages:

[0018] 1. In the chronic drug-toxic retinal damage model, decitabine specifically inhibits the expression of DNMT1 and affects the methylation levels of its related genes.

[0019] 2. Decitabine can improve the morphological structure and visual function of retinal photoreceptor cells in chronic drug toxicity induced by alkylating agents, and has a significant protective effect on drug-toxic retinal damage.

[0020] 3. Decitabine promotes the expression of Crx and its target genes (such as Pdc, Pde6c, Prph2, Samd7, Lrit2, Tnrc6b, Dpagt1, Gsk3a, Rp1, Tpd52, Dixdc1, Stk35, Plekhb1, Ankrd27, Unc119, Slc38a3, Rgs9bp, Gnat2 and C2cd21, etc.), which are key target genes for improving chronic drug toxicity of MMS-induced retinal photoreceptor cell damage. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is the 5mC immunofluorescence staining in an embodiment of the present application: the 5mC fluorescence staining of the normal control group and chronic drug toxic retinal injury at weeks 1, 2, and 4. Over time, the number of 5mC-positive cells in photoreceptor cells increased significantly, and the fluorescence intensity increased, which was most obvious in week 4. One-way ANOVA was used to compare with the Normal group, ns means no significant difference, ****P<0.0001, and the line segment indicates that the two groups were compared with each other, ###P<0.001, (40×, scale 40μm).

[0022] Figure 2 The expression changes of DNA methyltransferase and DNA methylation binding protein MeCP2 in one embodiment of the present application: A is the immunoblot of protein expression of DNMT1, DNMT3a / 3b and MeCP2 at 1, 2, 3 and 4 weeks of chronic drug toxic retinal photoreceptor cell damage; B is the semi-quantitative statistical graph of protein expression of DNMT1, DNMT3a / 3b and MeCP2, respectively. One-way ANOVA was used, and compared with the normal control group, ns means no significant difference, *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001, and the line segment indicates comparison between the two groups, #P<0.05, ##P<0.01, ###P<0.001.

[0023] Figure 3The average methylation level of each sample in an embodiment of the present application: the percentage of methylation level of three sequence environments CG, CHG, and CHH of each sample is displayed respectively, and CG sequence methylation is dominant.

[0024] Figure 4 This is the Pearson correlation analysis between the samples in one embodiment of the present application.

[0025] Figure 5 This is principal component analysis and clustering of genome-wide methylation levels in one embodiment of the present application.

[0026] Figure 6 This is a violin plot of the average methylation level distribution of DMRs in one embodiment of the present application: compared with the control group, the experimental group has 402 hyper-DMRs and 424 hypo-DMRs.

[0027] Figure 7 This is a cluster diagram of differentially methylated sites in one embodiment of the present application.

[0028] Figure 8 This is a distribution ratio diagram of DMRs in different regions of the gene in one embodiment of the present application: 17% of DMRs are annotated to the promoter region of the gene, 19% to the exon region, 35% to the intron region, and 29% to the intergenic region; 68% are located in CpG islands, 26% are located on the CpG island shore, and 7% are located in other regions.

[0029] Fig. 9 This is a GO enrichment bar chart of differentially methylated genes in one embodiment of the present application: the horizontal axis represents the number of enriched genes, the vertical axis represents the enriched GO items: biological process (BP), cellular component (CC), molecular function (MF), and the scale represents the significance of the difference.

[0030] Fig.10 This is a bar graph of the enriched KEGG pathway in one embodiment of the present application: the ordinate represents the name of the enriched pathway, the abscissa represents the number of genes observed in the pathway, and the scale represents the significance of the difference.

[0031] Fig.11 This is the principal component analysis of the transcriptome sequencing data in one embodiment of the present application: the clustering effect of the experimental group and the control group is obvious.

[0032] Fig.12 This is a distribution diagram of differentially expressed genes in one embodiment of the present application.

[0033] Fig.13This is a GO enrichment bar chart of differentially expressed genes in one embodiment of the present application: the horizontal axis represents the number of enriched genes, the vertical axis represents the enriched GO items: biological process (BP), cellular component (CC), molecular function (MF), and the scale represents the significance of the difference.

[0034] Fig.14 This is a KEGG pathway bar chart of enriched differentially expressed genes in one embodiment of the present application: the ordinate represents the name of the enriched pathway, the abscissa represents the number of genes observed in the pathway, and the scale represents the significance of the difference.

[0035] Fig.15 The Venn diagram for the association analysis of RRBS and RNA-seq data in one embodiment of the present application shows that there is no intersection between hypomethylated genes and genes with upregulated mRNA expression, while there are 19 genes that intersect between hypermethylated genes and genes with downregulated mRNA expression.

[0036] Fig.16 The Cistrome DB ToolKit in one embodiment of the present application predicts the regulatory factors of Rp1.

[0037] Fig.17 The mRNA expression levels and correlation analysis of Crx, Rp1 and Rhodopsin in one embodiment of the present application: A is a statistical graph of the mRNA expression levels of Crx, Rp1 and Rhodopsin in the retina at week 4 of chronic drug-toxic retinal photoreceptor cell damage, compared with the normal group, ****P<0.0001; B shows the correlation analysis of the expression levels of Crx and Rp1, and Crx and Rhodopsin, respectively.

[0038] Fig.18 The effect of 5-aza-dC in one embodiment of the present application on the visual function of mice with MMS-induced retinal photoreceptor cell damage: A: a representative dark-adapted 3.0 maximum mixed response waveform of ffERG examination; B: the b-wave amplitude of the dark-adapted 3.0 response was analyzed by two-way ANOVA, compared with the normal group + PBS, ****P<0.0001; the line segment indicates the comparison between the two groups, ##P<0.01.

[0039] Fig.19 The retinal morphological changes of chronic drug toxicity of retinal photoreceptor cells to 5-aza-dC in one embodiment of the present application: A is a representative retinal H&E staining image (40×, scale 20 μm; square brackets indicate OS layer); BC is the thickness of ONL and IS / OS using two-way ANOVA, compared with Normal+PBS, ****P<0.0001; the line segment indicates the comparison between the two groups, ####P<0.0001.

[0040] Fig. 20 The changes of 5mC fluorescence staining in chronic drug-toxic retinal damage caused by 5-aza-dC intervention in one embodiment of the present application: A shows the changes of 5mC fluorescence staining in retinal tissue sections of each group at the 4th week of chronic drug-toxic retinal damage; B shows the comparison with the Normal group using two-way ANOVA, ****P<0.0001, and the line segment indicates the comparison between the two groups, ####P<0.0001.

[0041] Fig.21 The effect of MMS and 5-aza-dc on the protein expression of DNMTs and MeCP2 in an example of the present application: A is a representative DNMTs protein immunoblot band; BE is the protein expression level using two-way ANOVA, compared with Nomal+PBS, *P<0.05, ***P<0.001, ****P<0.0001; the line segment indicates comparison between the two groups, #P<0.05.

[0042] Fig. 22 This is the effect of MMS and 5-aza-dc on the expression of Crx, Rp1 and Rhodopsin mRNA in an embodiment of the present application: compared with Nomal+PBS, *P<0.05, **P<0.01; the line segment indicates the comparison between the two groups, ##P<0.01, ###P<0.001. DETAILED DESCRIPTION

[0043] The main experimental materials and experimental methods involved in the following examples are:

[0044] 1. Experimental Animals

[0045] Healthy SPF-grade adult C57BL / 6J male mice (purchased from Beijing Weitonglihua), 7-8 weeks old, were kept in SPF-grade standard animal rooms with a temperature of 20-25°C, a humidity of 40-60%, and a 12 / 12h alternating light and dark cycle (lights on at 8:00AM and lights off at 8:00PM), with no restrictions on food and water. The use of experimental animals complies with the relevant regulations of ARVO and my country's "Regulations on the Administration of Experimental Animals". All animal experimental procedures and animal sacrifice methods were approved by the Life Science Animal Ethics Review Committee of Zhengzhou University (ethics number ZZUIRB2021-076), in compliance with animal ethics requirements, and the experiments were conducted strictly in accordance with regulations.

[0046] 2. Pharmacological effects and preparation methods of methyl methanesulfonate:

[0047] Methyl methanesulfonate (MMS) is an SN2 alkylating agent. After entering the body, it covalently binds to biological molecules in cells, resulting in loss of activity, DNA molecule breakage, and cell death. The metabolic process of MMS in the body mainly occurs in the liver. After binding with glutathione, it is further oxidized and metabolized in the liver. The metabolites are mainly excreted through the kidneys, and about 30% are excreted in the urine within 48 hours.

[0048] MMS chemical properties: molecular formula: CH 3SO 3CH 3, density 1.3 g / mL (25°C), melting point: 20°C, chemical structure is as follows. CAS No. 66-27-3, purchased from Sigma-Aldridge Company.

[0049] MMS is dissolved in 1× phosphate buffer (PBS, pH=7.4) to prepare an MMS solution. Specific algorithm: Based on the MMS density of 1.3g / mL, calculate the MMS dose required for a concentration of 75mg / kg (body weight). Take the MMS 75mg / kg (body weight) treatment as an example, that is, 75mg / kg÷1.3g / mL×0.001×body weight of each mouse (g)×number of experimental animals. The volume of solvent required is calculated based on 7.5μL per gram of mouse body weight, that is, 7.5μL / g×body weight of each mouse (g)×number of experimental animals. For example, if the mouse weighs 20g and the number of experimental animals is 10, then the amount of MMS required for 75mg / kg (body weight) is 11.54μL, 1×PBS buffer is 988.46μL, and the total volume is 1mL, which is used for 10 animals.

[0050] 3. Preparation of decitabine solution

[0051] Decitabine (5-aza-2'-deoxycytidine, 5-aza-dC), product number CAS2353-33-5, was purchased from Sigma Company, USA, molecular formula: C8H12N4O4, molecular weight 228.21.

[0052] According to the molecular weight calculation, 5 mg of decitabine powder was dissolved in 2.19 mL of sterile 1×PBS to prepare a storage solution with a concentration of 10 mM, and stored at -80°C in the dark. When using, dilute 1000 times with sterile 1×PBS to prepare a 10 μM solution, mix well, and then dilute 5 times again to prepare a 2 μM solution; Note: The diluted solution must be prepared immediately to ensure the effect of the drug.

[0053] 4.5mC antibody immunofluorescence staining

[0054] The paraffin sections of retinal tissue were routinely dewaxed and soaked in PBS for 5 minutes. The immunohistochemistry pen was used to mark the periphery of the retinal tissue. 20 μL 4N HCl was added to each retinal tissue for DNA denaturation and incubated at room temperature for 20 minutes. PBS was fully washed for 5 minutes × 5 times. Goat serum blocking solution was added and incubated at room temperature for 45 minutes. Mouse-anti-5mC primary antibody was diluted with blocking solution at a ratio of 1:100, 20 μL was added to each retina, and incubated at 4°C overnight. The next day, it was taken out of the refrigerator, returned to room temperature, and PBS was fully washed for 5 minutes × 3 times. The fluorescently labeled secondary antibody Goat-anti-Mouse-555 (1:2000) was added, 20 μL was added to each retina, and incubated at room temperature for 45 minutes. PBS was fully washed for 5 minutes × 3 times, and the sections were sealed with anti-fluorescence quenching sealing solution, observed under a fluorescence microscope, and photographed.

[0055] 5. Western blot detection of changes in DNA methylation-related protein expression

[0056] After the mice were anesthetized, the eyeballs were removed and the retinas were quickly obtained. Four retinas were used as a specimen unit. Retinal proteins were obtained according to the methods provided by the RIPA protein extraction kit and the BCA protein concentration determination kit. The concentrations of retinal proteins in the experimental and control groups were detected. Each sample was prepared to the same concentration (1 μg / μL) and heated for 10 minutes to denature the protein. 10 μL (10 μg) of each sample protein sample was added for SDS-PAGE electrophoresis, protein transfer, blocking, antigen-antibody binding reaction (dilute the primary antibody to the corresponding concentration according to the antibody instructions, see Table 1, and incubate overnight at 4°C. Dilute the secondary antibody according to the instructions according to the corresponding species, and incubate on a shaker at room temperature for 2 hours), ECL chemiluminescence reaction, exposure, and storage for photography. The grayscale value of the protein band was determined according to the BioRad ImageLab6.0 software, and the target protein was compared with the internal reference protein GAPDH to calculate the semi-quantitative analysis results.

[0057] Table 1 List of DNA methylation related antibodies

[0058]

[0059] 6.RRBS sequencing + RNA sequencing:

[0060] 6.1 Obtaining sequencing sample retinas: The retinas of C57BL / 6J mice in the experimental group and control group with chronic drug toxicity and retinal photoreceptor cell damage were quickly obtained under a microscope. Six retinas from three mice were used as one sample. Two samples were obtained from each group. The first sample retina was used for DNA extraction and RRBS library construction, and the second sample retina was used for RNA extraction and RNA-seq library construction. The samples were placed in RNA protection solution, left to stand at 4°C for 24 hours, and transferred to -20°C for temporary storage. They were transported to Shenzhen Acegene Biological Co., Ltd. on dry ice. RRBS and RNA-seq sequencing and analysis were completed by Shenzhen Acegene, with a sequencing depth of 30x and a single sample data volume of 6-8G.

[0061] 6.2RRBS library construction, sequencing and analysis process:

[0062] (1) Genomic DNA sequencing sample preparation: The genomic DNA in each sample was obtained using the TRIzol phenol-chloroform extraction method; the quality, concentration, and purity of the DNA samples were tested, and the DNA was required to meet the standards for library construction.

[0063] (2) RRBS library construction:

[0064] (a) Restriction endonuclease MspI digests genomic DNA: MspI can specifically recognize the 5'-C^CGG-3' site and cut genomic DNA into fragments of 40 to 200 bp, which is used to enrich DNA fragments with high CG content.

[0065] (b) The DNA fragments after enzyme digestion are blunt-ended, a "polyA" tail is added, and an adapter (methylated sequencing adapter) is connected to perform a PCR reaction.

[0066] (c) The PCR product was subjected to agarose gel electrophoresis, and the gel was cut under ultraviolet light to recover DNA fragments with a length ranging from 150 to 300 bp, and then purified.

[0067] (d) Perform bisulfite conversion treatment on the purified DNA fragments: According to the instructions of EZ DNA Methylation Gold Kit, DNA denaturation and C→T conversion are completed in one step.

[0068] (e) Perform PCR amplification to complete the final DNA methylation library construction.

[0069] (3) Library quality inspection and sequencing:

[0070] (a) Quantification: Qubit 2.0 was used to measure the library concentration;

[0071] (b) Dilute the library to a final concentration of 1 ng / μL sample;

[0072] (c) Agilent 2100 detection of library fragment length distribution;

[0073] (d) Use fluorescent quantitative PCR to accurately measure the effective concentration of the library (the effective concentration of the library is required to be >2nM);

[0074] (e) Sequencing was performed on the Illumina HiSeq platform.

[0075] (4) Bioinformatics analysis:

[0076] (a) Data quality control and optimization: After obtaining the original sequencing data, the raw reads were first quality controlled using FastQC software, and the raw data were filtered using Trimmomatic software to obtain high-quality data (clean data). After quality control again, subsequent analysis was performed.

[0077] (b) Data alignment: Bsmap software was used to compare DNA methylation data to the reference genome. It is not necessary to convert the genome sequence before alignment, but both C and T in the sequence are allowed to be aligned with C on the genome, so as to achieve the alignment analysis between the bisulfite converted sequence and the normal genome sequence. Bsmap has the characteristics of simple operation, faster speed and higher sensitivity.

[0078] (c) Analysis of the percentage of methylated C sites in the total methylated C sites in different genomic sequence environments (CG, CHG, CHH) to reflect the methylation characteristics of the genome of each sample.

[0079] (d) Pearson correlation analysis to test the correlation of methylation levels between samples: This is an important indicator for evaluating the reliability of the experiment and whether the sample selection is reasonable. The closer the correlation coefficient is to 1, the higher the similarity of the methylation patterns between samples.

[0080] (e) Differentially methylated region (DMR) analysis: DMR result annotation: DMRs were annotated according to gene regions (such as promoter region, exon region, intron region, gene body region, CpG island, etc.).

[0081] (f) GO (Gene ontology) enrichment analysis: Based on the GO database established by the Gene Ontology Consortium, the description of gene products from three levels, namely cellular component (CC), biological process (BP), and molecular function (MF), can provide a more comprehensive interpretation of the function of each gene. The basic unit of GO is term, which is called an entry or node, and each term corresponds to an attribute. GO enrichment analysis was performed using GOseq software, which mainly includes the following three steps: a) First, based on the DMR annotation results, the genes that overlap with the gene body region and the promoter region were summarized to identify genes with significant methylation differences; b) By fitting the relationship between differentially expressed genes and length, the likelihood function of quantifying the relationship between differentially expressed genes and length was obtained; c) The likelihood function of the relationship between differentially expressed genes and length was incorporated into the test of enrichment analysis. A GO enrichment bar graph was drawn to analyze which gene attributes were associated with differentially methylated genes in the promoter region and differentially methylated genes in the gene body region from three levels.

[0082] (g) Pathway analysis: The KEGG pathway database was used to analyze the metabolic pathways that were significantly enriched in the differentially methylated genes and to find signal transduction pathways that may be involved in the research content.

[0083] 6.3 RNA-library construction, sequencing and analysis process

[0084] (1) Sample RNA extraction, RNA quality and concentration testing. After the concentration and purity of the RNA sample meet the requirements for library construction, transcriptome library construction is performed.

[0085] (2) RNA-sequencing library construction and sequencing:

[0086] (a) Oligo(dT)-labeled magnetic beads are used to bind to mRNA containing a polyA tail, and then the mRNA is eluted and enriched with RNase-free water.

[0087] (b) Use ultrasound to randomly break the mRNA to be tested into 200-500 bp sequence fragments, add A at the ends to convert the blunt ends into sticky ends, which is convenient for subsequent connection of primers and sequencing adapters. Add P5 and P7 oligonucleotide sequences at both ends of the small fragments, add sequencing primer binding sites and Index sequences 1 and 2.

[0088] (c) Library quality control and sequencing: a. Quantification: Qubit 2.0 was used to measure the library concentration; b. The library was diluted to a final concentration of 1 ng / μL sample; c. Agilent 2100 was used to detect the length distribution of the library fragments; d. Fluorescence quantitative PCR was used to accurately measure the effective concentration of the library (the effective concentration of the library was required to be > 2 nM). Sequencing was performed on the Illumina HiSeq platform.

[0089] (3) Bioinformatics analysis:

[0090] (a) Data quality control and optimization: After obtaining the original sequencing data, FastQC software was first used to perform quality control on the raw reads. Then Trimmomatic software was used to filter the raw data to obtain high-quality data for subsequent analysis.

[0091] (b) Data alignment: Sequencing reads were aligned with the reference genome using HISAT software.

[0092] (c) Differentially Expressed Genes (DEG) analysis:

[0093] (d) Distribution of DEGs: The up-regulated DEGs and down-regulated DEGs (experimental group relative to control group) were counted to understand the distribution of differentially expressed genes.

[0094] (e) GO enrichment analysis: The differentially expressed genes were subjected to functional enrichment analysis. GOseq software was also used for enrichment analysis, and the steps were the same as RRBS.

[0095] (f) KEGG pathway analysis: KEGG pathway analysis was performed on differentially expressed genes using the same algorithm as above.

[0096] 6.4 RRBS and RNA-seq data association analysis

[0097] The DMR annotated genes in RRBS were associated with the DEG data in RNA-seq. The genes annotated with differential methylation and negatively correlated with differentially expressed genes were intersected to obtain a collection of genes with increased DNA methylation levels and downregulated gene expression. These genes were then subjected to GO functional enrichment analysis and KEGG pathway enrichment analysis to help screen out differential genes related to retinal development, functional maintenance, and disease damage. The Cistrome DB ToolKit analysis was used to identify transcription factors that may be involved in regulating differential gene expression. The correlation between gene expression and DNA methylation in the promoter region was further verified. The effects of changes in DNA methylation modification on gene expression under pathological conditions were explored.

[0098] 7. Real-time Fluorescence Quantitative PCR Analysis

[0099] RNAeasy TM The total RNA of the retina of mice in each experimental group and control group was extracted using a kit, and the RNA concentration and purity (A260 / A280 was 1.8-2.0) were determined by Nanodrop2000 ultra-micro spectrophotometer, and the RNA integrity was detected by 1% agarose gel electrophoresis. According to the instructions of the cDNA synthesis kit (Thermo Fisher Scientific, USA), reverse transcription was performed to synthesize cDNA, and the cDNA concentration was adjusted to 1 ng / μL. Real-time fluorescence quantitative PCR analysis was performed using the PowerUp SYBR kit, and the relative mRNA expression level was calculated using the 2-ΔΔCT method.

[0100] 8. Intravitreal injection method in mice

[0101] The experimental mice were intraperitoneally injected with 5% chloral hydrate at a dose of 8 μL / g (body weight); proparacaine hydrochloride was used for surface anesthesia. The thermal blanket was turned on and adjusted to 37°C. The mice were placed on the thermal blanket and the compound tropicamide eye drops were used to dilate the pupil. The pupil distance, focal length and magnification ratio of the stereo microscope were adjusted. The 2 μM decitabine solution prepared for injection was fully mixed, wrapped with tin foil to avoid light, and 1 μL was extracted with a Hamilton microinjector (33G, 5 μL range) for use.

[0102] Wipe the mouse eye skin with iodine cotton balls, rinse the conjunctival sac with iodine solution for disinfection, and rinse the conjunctival sac with sterile saline. Hold the temporal bulbar conjunctiva with ophthalmic microtweezers in the left hand to fix the eyeball, hold the disposable infusion needle in the right hand, and insert the needle at a 45° angle 0.5mm outside the limbus of the corneosclera above the nose, and then pierce the sclera perpendicular to the eyeball wall to make a scleral tunnel incision. Replace the drug-containing Hamilton injector and enter the center of the vitreous cavity along the tunnel opening. The position of the needle tip can be seen from the pupil to avoid touching the lens in front and the retina behind. Slowly push the drug solution at a uniform speed of 0.1μL / second, stay for 20 seconds, slowly pull out the needle, and the incision closes automatically. Observe that there is no liquid reflux. Apply tobramycin dexamethasone eye ointment after injection to prevent infection. After full recovery in the incubator after surgery, return to the SPF cage.

[0103] Note: ① The creation of a scleral tunnel incision can effectively prevent the backflow of the drug solution and ensure the accuracy of the injection dose; ② Because the mouse lens is approximately spherical and the vitreous cavity is narrow, you must pay attention to the angle of needle insertion and see the position of the needle tip through the pupil and lens to avoid damaging the lens or retina and ensure the accuracy of the experimental results.

[0104] 9. Electroretinogram (ERG) test

[0105] All experimental mice were placed in a dark room in advance and dark adapted for 2 to 4 hours. Anesthesia was performed by isoflurane inhalation anesthesia. Induction anesthesia was performed at level 2, maintenance anesthesia was performed at level 1, and positive pressure ventilation was 0.2 L / min. After anesthesia, compound tropicamide eye drops were applied to dilate the pupil, and proparacaine hydrochloride eye drops were applied to the eyes for surface anesthesia. After the mice were fully anesthetized, they were fixed on the experimental operating table. Electrode placement: The ground electrode was placed subcutaneously on the right forearm of the mouse, the reference electrode was placed subcutaneously on the cheek on the same side, and the recording electrode was a circular corneal electrode, which was in full contact with the limbus of the right eye cornea and no pressure should be applied. Sodium hyaluronate eye drops were applied to keep the cornea moist. The mice were pushed into the spherical stimulator, and the full-field flash ERG detection and recording were performed using a visual electrophysiological examination system.

[0106] The experimental data were expressed as mean ± standard deviation (Mean ± SD), and statistical analysis was performed using GraphPad Prism 8.0 software. For the MMS-induced mouse retinal injury animal model, the ERG dark adaptation 3.0 maximum mixed response a wave and b wave amplitude were detected and statistically analyzed.

[0107] 10. Heart Perfusion Fixation and Sampling

[0108] The experimental animals were anesthetized by inhalation of isoflurane cotton balls and fixed on the operating table in a supine position. The skin of the precardiac area was cut open to expose the heart and part of the liver. The perfusion needle punctured into the left ventricle, and the 1×PBS (pH=7.4) perfusion solution was opened. At the same time, the right atrial appendage was cut open, and dark red blood flowed out and gradually turned colorless. The color of the liver turned grayish white, and the ends of the limbs turned white. It was changed to 4% paraformaldehyde and continued to perfuse. The tail of the mouse was observed to be upturned and hardened, indicating that the whole body tissue was well fixed. After the perfusion was completed, the ophthalmic scissors cut the inner and outer canthi, and the ophthalmic micro-curved scissors were extended into the eye socket to cut off the extraocular muscles and periorbital accessory tissues, lift the eyeball, cut off the optic nerve, and put the eyeball into the eyeball fixative. Immediately remove the brain, liver, kidney and other organs and place them in 4% paraformaldehyde. All tissues were kept in a 4°C refrigerator and continued to be fixed for 24 hours.

[0109] 11. Preparation of paraffin sections of retinal tissue and HE staining

[0110] Preparation of paraffin sections: Wash the fixed eyeball with pure water, place it in a flat dish, and operate under a stereo microscope. Cut along the corneoscleral margin with Venus scissors, remove the cornea, lens and iris tissue, and retain the optic cup. Dehydrate, make it transparent, dip it in wax, and embed it into wax blocks. The thickness of the slice is 4μm, and the slices passing through the optic nerve are selected. 3-5 slices are selected for each tissue.

[0111] HE staining: bake at 65℃ for 60min, dewax with xylene, hydrate with gradient alcohol, soak in pure water for 5min, stain with hematoxylin for 20s, wash twice with pure water, blue with ammonia for 20s, wash twice with pure water, stain with eosin for 10s, wash twice with pure water, dehydrate with gradient alcohol, make transparent with xylene, and then add neutral gum to seal the slide.

[0112] Observe under a microscope, select 200-300μm away from the optic nerve for photography under a 40x microscope; take full-circle photography under a 20x microscope, and use Photoshop CS5 software to make a full-circumference retinal section. Centered on the optic nerve, the left and right sections were divided into 9 equal parts, for a total of 18 sections. ImageJ software was used to measure the thickness of the retinal ONL and IS / OS, and statistical analysis was performed.

[0113] Example 1: Construction and evaluation of an animal model of chronic drug toxicity for retinal photoreceptor cell damage

[0114] 1. Construction of a chronic drug toxicity retinal photoreceptor cell injury model:

[0115] Weigh the mice and record the values ​​to 2 decimal places. Calculate the amount of MMS solution to be injected into each mouse based on the weight of the mice and the dose of 50 mg / kg (body weight). Place an isoflurane-soaked cotton ball in front of the mouse's nostrils. After the mouse is anesthetized, draw out the drug solution with an insulin syringe and exhaust the air. Disinfect the mouse's tail with 75% alcohol, and slowly inject into the tail vein at the lower 1 / 4 of the tail with a 32G injection needle. Then place the mouse on a 37°C constant temperature blanket and wait for the mouse to recover.

[0116] 2.5mC antibody fluorescent staining

[0117] Normal adult male C57BL / 6J mice were treated with MMS at a dose of 50 mg / kg (body weight), which caused chronic drug toxicity and specific damage to retinal photoreceptor cells. Over time, the thickness of the retinal outer nuclear layer gradually became thinner. In the fourth week, only 4 to 5 layers of cells remained in the outer nuclear layer, and the outer segments disappeared completely. The retinal morphological pathological changes were stable and consistent with the fourth week after continued observation until the 12th week. Therefore, the experiment chose to observe the retinal tissue sections 5mC antibody staining at 1, 2, and 4 weeks after retinal injury. Figure 1 As shown in A, 5mC staining was observed in the inner nuclear layer and ganglion cell layer at each time point, while the outer nuclear layer where the photoreceptor cells are located had no obvious staining in the control group and the early 1 week of drug toxic retinal injury. A large number of 5mC positive cells were observed in the 2nd and 4th weeks of drug toxic retinal injury. Although the total number of photoreceptor cells decreased, the number of 5mC positive cells increased significantly. It can be seen that as the injury gradually worsened, the one-way analysis of variance showed Figure 1As shown in B, the number of 5mC-positive cells and the fluorescence intensity were significantly increased [F FI(3,8)=1177, P<0.0001].

[0118] 2. Changes in expression of DNA methylation-related proteins

[0119] In the fourth week of chronic drug-toxic retinal photoreceptor cell damage, the retinal 5mC content increased significantly, indicating an increase in DNA methylation levels. Therefore, the expression levels of DNA methylation-related proteins in the retina were detected. Representative protein immunoblot bands, such as Figure 2 A. One-way ANOVA showed that ( Figure 2 B), at 4 weeks after drug-toxic retinal injury, the protein expressions of DNMT1 [F(4,10)=36.49, P<0.0001], DNMT3a [F(4,10)=35.04, P<0.0001], DNMT3b [F(4,10)=16.63, P<0.001] and MeCP2 [F(4,10)=32.26, P<0.0001] were significantly higher than those in the control group. The above results suggest that the expression of DNA methylation-related proteins is increased during chronic drug-toxic retinal photoreceptor cell injury.

[0120] 3. RRBS library construction, sequencing and analysis results:

[0121] (1) Quality control: FastQC software was used to perform quality control on the raw data (Raw data) and the optimized data (Clean data) after filtering out the low-quality data that did not meet the conditions. The results include the base quality of each site, the average quality of the sequence, the GC content distribution, the sequence base content, the linker sequence content, etc. The base quality of each site in the RRBS sequencing data, Q20, and Q30 refer to the correct recognition rate of the base. The correct recognition rate of Q20 bases is 99%, and the correct recognition rate of Q30 bases is 99.9%. The error rate is only 0.1%. The quality control results of each data also meet the requirements and can be used for subsequent analysis.

[0122] (2) Data comparison: The sequencing data were compared with the mouse reference genome mm10 (NCBI-Assembly), and the results are shown in Table 2. The methylation sequence mapping rate of each sample was above 90%, indicating that the methylation sequencing sequence had a high similarity with the reference genome sequence, and the MspI enzyme digestion efficiency and BS conversion rate were both greater than 99%. The sequencing data were reliable and could be used for subsequent personalized analysis.

[0123] Table 2. Comparison statistics of RRBS sequencing data and reference genome

[0124] Sample total_map_rate MspI_cut_efficiency(%) BS_conversion Control1 95.70％ 99.690 99.61579 Contro12 90.95％ 99.385 99.72606 Test1 94.60％ 99.676 99.64512 Test2 92.00％ 99.486 99.76149

[0125] (3) Average methylation level and methylation distribution of each sample: In the genome of an organism, there are three different forms of sequences that can undergo DNA methylation, namely CG, CHG, and CHH, where C is cytosine that can be methylated and H represents any base other than G (which can be A, C, or T). The average methylation levels of CG, CHG, and CHH in each sample of the experimental group and the normal control group were evaluated separately. Figure 3 As shown in the figure. As can be seen from the figure, the average DNA methylation levels within and between the sample groups are not significantly different. DNA methylation in each sample is mostly concentrated in the CG sequence environment. This is because in mammals, DNA methylation mainly occurs at CpG sites, accounting for about 70-80% of the entire genome, while in plants, any C can undergo DNA methylation. Therefore, the DNA methylation level of the mouse retinal tissue detected in this experiment uses CpG sites as the main analysis object. The DNA methylation levels of other forms of sequence environments are low and do not contribute much to the overall methylation level, so they will not be studied in depth.

[0126] (4) Correlation analysis of whole genome methylation levels: Pearson correlation analysis was performed on the whole genome methylation levels of each sample. Figure 4 As shown in Figure 2, the experimental group and the control group were divided into two groups, and the correlation coefficients between samples in the two groups were R 2 ≥ 0.98, and the correlation coefficients between samples in the two groups were R 2 ≥ 0.98. The results showed that the whole genome methylation levels of the two groups were consistent. Principal component analysis (PCA) and cluster analysis (such as Figure 5 The results show that the clustering effect of the experimental group and the control group is obvious.

[0127] (5) Differentially methylated region (DMR) analysis: refers to the region where the methylation modification difference between the two groups of samples is more than 10% and has statistical significance. Since the methylation of a single CpG site is difficult to produce an effective biological effect, DMR usually refers to a combination of multiple consecutive methylation sites contained in a region. Differential methylation analysis was performed using MethylKit software, and a total of 826 DMRs were obtained. Hyper-DMRs refer to DMRs that are highly methylated in the Test sample, and hypo-DMRs refer to DMRs that are low in methylation in the Test sample. The results showed that compared with the control group, the experimental group had 402 hyper-DMRs and 424 hypo-DMRs (such as Figure 6 shown).

[0128] A cluster heat map was drawn for the above DMR to show the methylation status and differences between groups, such as Figure 7As shown in the figure, the horizontal axis represents the group, and the vertical axis represents the clustering effect of the methylation level value. From blue to red, the methylation level is from low to high. Although the average methylation level between the two groups of samples is not much different, it can be seen from the clustering heat map that there are still obvious differences in the methylation levels of some genes between the experimental group and the control group.

[0129] (6) Distribution of DMR in gene functional regions: Under normal physiological conditions, CpG islands are in a low methylation state, which is conducive to gene expression; once the CpG island in the gene promoter region is methylated, it may inhibit the binding of transcriptional active factors to DNA, or recruit proteins involved in gene repression, thereby changing the structure of chromatin and inhibiting gene expression. 70% of gene promoters are located in CpG islands, so CpG methylation in CpG islands and promoter regions is the key to regulating gene transcription. DNA methylation not only occurs on CpG islands, but also on CpG island shores, which are regions no more than 2000 bp upstream of CGI. The density of CpG in the CpG island shore region is relatively low. Methylation occurring on the CpG island shore is generally tissue-specific methylation, so methylation differences on the CpG island shore can be used to identify different tissues. Among all CpG sites with different methylation, only 2% are located on CpG islands in the promoter region and 4% are located on CpG island shores. In order to further analyze the distribution of CpG site methylation on genes and its relationship with gene expression, the DMRs between groups were annotated according to the different functional regions of genes ( Figure 8 Most DMRs are located in introns, accounting for about 35% of the total DMRs, exons about 19%, and promoters about 17%. Intergenic regions account for about 29%, and CpG islands are the most distributed.

[0130] (7) GO enrichment analysis of DMR annotated genes: The gene promoter region is the region where transcription factors bind, so the methylation level of the CpG site in this region will affect the binding of transcription factors to the target gene DNA sequence, or affect the transcriptional expression of the gene by recruiting co-repressors. Therefore, the genes annotated to the promoter region by DMR were subjected to functional enrichment analysis, classified according to the three major functions of Gene Ontology, and a GO enrichment bar chart was drawn ( Fig. 9 As shown in the figure). The horizontal axis represents the number of enriched genes; the vertical axis represents the enriched GO items, which are displayed from top to bottom according to the three-level attributes of biological process (BP), cell component (CC), and molecular function (MF); the ruler is used to indicate the significance of the difference. As can be seen from the figure, the enriched DMR-related genes are mostly concentrated in the following aspects: ① Biological process: cell migration, growth and development regulation, etc.; ② Cell component: neuronal synapse, cell connection, cytoskeleton, etc.; ③ Molecular function: DNA binding transcription activator activity, extracellular matrix structural components, etc.

[0131] (8) KEGG pathway enrichment analysis of DMR-related genes

[0132] Pathway enrichment analysis was performed on genes with differential methylation coverage using the KEGG pathway database. The differentially methylated genes anchored to the promoter region were also used as the focus, and a KEGG pathway bar chart was drawn to display signal pathways with significant differences ( Fig.10 ). The vertical axis represents the name of the enriched pathway, the horizontal axis represents the number of genes observed in the pathway, and the scale represents the significance of the difference. As can be seen from the figure, differentially methylated genes are significantly enriched in signaling pathways such as PI3K-Akt and ECM-receptor interaction.

[0133] 4. RNA-seq library construction, sequencing and analysis

[0134] (1) Quality control, data alignment and PCA clustering: FastQC software was used to perform quality control on the raw data and filtered and optimized data. The alignment software HISAT aligned high-quality reads to the mouse reference genome mm10 (NCBI-Assembly). Principal component analysis (PCA) was performed on the sequencing data of each sample, and the clustering effect of the experimental group and the control group was obvious ( Fig.11 ), the above results suggest that the sequencing data are reliable and can be used for subsequent personalized analysis.

[0135] (2) Distribution of differentially expressed genes: In order to understand the distribution of differentially expressed genes as a whole, the distribution of differentially expressed genes is displayed in the form of a volcano plot by combining the P value and the difference fold, such as Fig.12 As shown. Differential gene screening conditions: difference multiple greater than or equal to 2 and Q-value (or FDR) less than or equal to 0.01. Each point in the figure represents a gene, and the blue and red points represent significantly differentially expressed genes. Red points represent upregulated genes (experimental group compared with control group, the same below), blue points represent downregulated genes, and gray points represent genes with no significant expression differences. The horizontal axis represents the logarithm of the difference multiple, and the vertical axis represents the logarithm of the P value. As shown in the figure, there are 651 genes upregulated in the experimental group compared with the control group, and 60 genes downregulated.

[0136] (3) GO enrichment analysis of differentially expressed genes

[0137] Next, GOseq was used to perform GO enrichment analysis on differentially expressed genes ( Fig.13 As shown in the figure, DEGs were enriched in the following aspects: ① biological process: visual system development, extracellular matrix composition, etc.; ② cellular components: extracellular matrix, basement membrane, etc.; ③ molecular function: lens structural components, extracellular matrix structural composition, etc.

[0138] (4) KEGG pathway analysis

[0139] In a specific biological function, genes usually play a certain role by interacting with each other. Pathway analysis can provide a deeper understanding of the biological function of genes. DEGs were enriched through the KEGG pathway database, and a bar chart was drawn to display the signal pathways with significant differences ( Fig.14 ). The horizontal axis represents the number of enriched genes, the vertical axis represents the name of the enriched pathway, and the scale represents the significance of the difference. As can be seen from the figure, the differentially expressed genes are significantly enriched in signaling pathways such as PI3K-Akt and ECM-receptor interaction.

[0140] 5. Association analysis between RRBS and RNA-seq

[0141] Based on the results of RRBS and RNA-seq data analysis ( Fig.15 ), there was no intersection between hypomethylated genes and genes with upregulated mRNA expression, while there were 19 genes that intersected between hypermethylated genes and genes with downregulated mRNA expression. Among them, the cone-rodhomeobox gene (Crx) is a transcription factor encoding gene that is closely related to retinal development, functional maintenance, and disease damage. Compared with the control group, the methylation level of Crx in the retina of the model group mice was increased, and its expression level was downregulated (P<0.01).

[0142] The potential target genes of transcription factor Crx in the retina were predicted by searching the Cistrome DB database, and the top 20 target genes were listed in Table 3. The predicted target gene information was interactively analyzed with the transcriptome data obtained by RNA-seq sequencing to obtain the expression of Crx target genes in the transcriptome sequencing data, as shown in Table 4. Among them, the expression of the two transcripts of retinitis pigmentosa 1 (Rp1) gene, NM_001370921.1 and NM_011283.2, was downregulated (P<0.01). The regulatory factors of gene Rp1 were reversely predicted by Cistrome DB ToolKit, and the results suggested (such as Fig.16 Among the regulatory factors of Rp1, Crx had the highest score.

[0143] Table 3 Prediction of target genes of Crx (Top 20)

[0144] Gene Score Coordinate Pdc 3.166 chr1:150319416-150333905 P6c 2.858 chr19:38132780-38183954 Prph2 2.841 chr17:46910477-46924932 Samd7 2.627 chr3:30746292-30767173 Lrit2 2.414 chr14:37068028-37073742 Crx 2.392 chr7:15865946-15879954 Tnrc6b 2.203 chr15:80798609-80941085

[0145] Dpagt1 2.132 chr9:44326565-44333599 Gsk3a 2.051 chr7:25228258-25237850 Rp1 2.035 chr1:4343506-4360313 Tpd52 2.03 chr3:8929430-8964356 Dixdcl 1.982 chr9:50662751-50699459 Stk35 1.978 chr2:129800516-129832286 Plekhb1 1.929 chr7:100643895-100662393 Ankrd27 1.922 chr7:35586246-35639236 Unc119 1.921 chr11:78345583-78349163 Slc38a3 1.915 chr9:107651154-107667398 Rgs9bp 1.912 chr7:35578992-35585581 Gnat2 1.896 chr3:108093065-108101429 C2cd21 1.886 chr9:44309236-44320281

[0146] Table 4 Crx predicted target genes and RNA-seq interactions

[0147] symbol chrom refseq score log2FoldChange pvalue padj sig Lrit2 chr14 NM_173418.4 2.411 -0.725449944 8.13E-05 0.002066 none Lrit2 chr14 XM_030247791.1 2.215 -0.725449944 8.13E-05 0.002066 none Lrit2 chr14 NM_030247792.1 2.215 -0.725449944 8.13E-05 0.002066 none Lrit2 chrl4 NM_001360134.1 2.414 -0.725449944 8.13E-05 0.002066 none Rp1 chr1 NM_001370921.1 2.034 -1.115635378 0.00505 0.048511 down Rp1 chr1 NM_011283.2 2.035 -1.115635378 0.00505 0.048511 down Samd7 chr3 NM_029489.3 2.627 -0.816070091 2.44E-22 1.98E-19 none Samd7 chr3 NM_017319791.1 2.261 -0.816070091 2.44E-22 1.98E-19 none Tpd52 chr3 NM_001025261.2 2 -0.479853246 0.00336 0.036486 none Tpd52 chr3 NM_001025262.2 2 -0.479853246 0.00336 0.036486 none Tpd52 chr3 NM_006530065.4 2.006 -0.479853246 0.00336 0.036486 none Tpd52 chr3 NM_030252551.1 2.006 -0.479853246 0.00336 0.036486 none Tpd52 chr3 NM_006530067.4 2.03 -0.479853246 0.00336 0.036486 none Tpd52 chr3 XM_006530068.4 2.013 -0.479853246 0.00336 0.036486 none

[0148] 6. Verification of the expression level of Crx and downstream genes

[0149] The mRNA expression of Crx and its downstream genes in the retina of mice with chronic drug-induced retinal photoreceptor cell damage at 4 weeks and those in the normal control group were verified by real-time fluorescence quantitative PCR detection ( Fig.17 A), unpaired t-test results showed that compared with the control group, the mRNA expression level of Crx in the retina of mice in the chronic drug-toxic retinal photoreceptor cell injury group was significantly decreased (t=10.11, P<0.0001); the expression levels of downstream genes Rp1 (t=6.268, P<0.0001) and Rhodopsin (t=8.529, P<0.0001) were also significantly decreased. Correlation analysis results suggest that ( Fig.17 B), Crx had a significant correlation with the expression of Rp1 (R=0.85, P<0.001) and Rhodopsin (R=0.95, P<0.0001).

[0150] Example 2: Application of decitabine in the treatment of chronic drug-toxic retinal photoreceptor cell damage

[0151] 1. The experimental design is as follows:

[0152] A. Chronic model group + 5-aza-dC intervention treatment group:

[0153] a. Normal control group (Normal+PBS): only 1 μL of PBS was injected into the vitreous cavity;

[0154] b. Model + sham injection group (MMS + PBS): MMS 50 mg / kg (body weight) tail vein injection + vitreous injection of PBS 1 μL;

[0155] c. Model + drug-addition group (MMS + 5-aza-dC): MMS 50 mg / kg (body weight) tail vein injection + vitreous injection of 5-aza-dC (2 μM, decitabine, 1 μL);

[0156] d. Normal+drug group (Normal+5-aza-dC): 5-aza-dC (2 μM, decitabine, 1 μL) was injected into the vitreous of normal mice.

[0157] B. Selection of the time window for the chronic model group + 5-aza-dC intervention treatment:

[0158] Each group had 15 mice. The first intravitreal injection was performed 24 hours before MMS injection, and then once every week for a total of 3 times. The experimental animals in each group were observed at the 4th week after MMS injection.

[0159] 2. Protective effect of decitabine on chronic drug-induced retinal photoreceptor cell damage

[0160] (1) Changes in retinal function after chronic drug toxicity after 5-aza-dC intervention: Retinal function testing was performed using ffERG according to the standard experimental procedures of ISCEV. The results of dark-adapted 3.0 maximum mixed response ERG showed that ( Fig.18 ), 5-aza-dC intervention treatment significantly increased the retinal b-wave amplitude in chronic drug-toxic retinal photoreceptor cell damage [F MMS (1,12) = 249.3, P < 0.0001], and 5-aza-dC significantly reduced the damage of MMS drug toxicity to retinal b-wave. The results suggest that 5-aza-dC has no obvious side effects on the visual function of normal mice, and has a significant improvement effect on the visual function of mice with chronic drug-toxic retinal photoreceptor cell damage model.

[0161] (2) Histological changes of retinal photoreceptor cells after chronic drug toxicity of 5-aza-dC intervention: HE staining results of retinal tissue sections of each group, such as Fig.19 As shown in A, in the MMS+PBS group, the retinal photoreceptor cells were arranged disorderly, with only 4 to 5 layers remaining, the ONL thickness was about 27.24±1.18μm (58.48±1.5μm in the normal group), and the photoreceptor outer segment OS structure disappeared; in the MMS+5aza-dC group, the photoreceptor cells were arranged disorderly, with about 7 to 8 layers and a thickness of about 40.5±1.92μm, which was significantly thickened compared with the drug toxicity model group at the same time point. Observing the retinal structure, the external limiting membrane (OLM) formed by the synaptic terminals of Müller cells located below the ONL was still clearly visible. Although the IS / OS layer was not as clear as the normal retina, the boundary between the inner and outer segments was clearly visible. A two-way ANOVA was performed on the thickness of the ONL and IS / OS ( Fig.19B), the results showed that 5-aza-dC had a significant effect on increasing the ONL and IS / OS layers of chronic drug-toxic retinal damage [F ONL-MMS(1,32)=2076,P<0.0001; F IS / 0S-MMS(1,32)=145.7,P<0.0001], and 5-aza-dC significantly reduced the damage of MMS to retinal photoreceptor cells (MMS+PBS vs.MMS+5-azaz-dC,P<0.0001). The results suggest that after 5-aza-dC intervention, retinal photoreceptor cells damaged by chronic drug toxicity may still have metabolic functions, which can promote the renewal of the basement membrane of the inner segment (IS) and continuously generate the outer segment (OS) structure. The existence of the outer segment may also preserve some visual sensitive proteins, which also provides a necessary premise for the recovery of retinal photosensitivity.

[0162] After intravitreal injection of 5-aza-dC in normal mice (recorded as Normal+5aza-dC group), the retinal structure was not significantly different from that of the normal group, with a thickness of approximately 58.17±1.69μm (P>0.05), and the inner and outer segment structures of the retina were not damaged.

[0163] (3) Effect of 5-aza-dC intervention on 5mC labeling in chronic drug-toxic retinal photoreceptor cell injury: At the 4th week of chronic drug-toxic retinal photoreceptor cell injury, 5mC labeling fluorescence staining was performed on retinal tissue sections of each group. Representative fluorescence staining results of each group are shown in Figure 2. Fig. 20 As shown in A. Two-way ANOVA showed that 5-aza-dC intervention had a significant effect on the retinal 5mC labeling intensity in the chronic drug-toxic retinal photoreceptor cell injury group compared with the control group [F MMS(1,8)=7797,P<0.0001; F 5-aza-dC(1,8)=105,P<0.0001]. 5-aza-dC significantly reduced the high level of 5mC in the chronic drug-toxic retinal photoreceptor cell injury group (MMS+PBS vs.MMS+5-aza-dC,P<0.0001). Fig. 20 As shown in B. The results showed that the retinal 5mC methylation mark was enhanced in the chronic drug toxic retinal photoreceptor cell damage group, indicating an increase in DNA methylation levels, while the retinal 5mC methylation mark was decreased in the 5-aza-dC intervention group, significantly inhibiting the level of high methylation.

[0164] (4) Effect of 5-aza-dC on DNA methyltransferase expression:

[0165] (a) Effect of 5-aza-dC on the expression of DNMT1: Immunoblotting bands as shown Fig.21 As shown in A, two-way ANOVA showed that ( Fig.21B), MMS toxicity can promote the upregulation of DNMT1 expression in the retina [FMMS (1,8) = 54.04, P < 0.0001], while 5-zaz-dC has no significant effect on the expression of DNMT1 [F5-aza-dC (1,8) = 2.551, P > 0.05], but there is a significant interaction between the two [FMMS × 5-aza-dC (1,8) = 8.518, P < 0.05]. Sidak multiple comparisons showed that MMS toxicity significantly increased the expression of DNMT1 in the mouse retina (Nomal + PBS vs. MMS + PBS, P < 0.001), and 5-aza-dC significantly weakened the effect of MMS toxicity on DNMT1 in the retina (MMS + PBS vs. MMS + 5-zaz-dC, P < 0.05).

[0166] (b) Effect of 5-aza-dC on the expression of DNMT3a / 3b: The results are as follows Fig.21 CD two-way ANOVA showed that both the chronic drug toxic retinal injury model group and the 5-aza-dC intervention treatment group had a significant effect on the expression of DNMT3a / 3b in the retina: DNMT3a [F MMS(1,8)=8.594,P<0.05; F5-aza-dC(1,8)=7.210,P<0.05], DNMT3b [F MMS(1,8)=82.67,P<0.0001; F5-aza-dC(1,8)=13.63,P<0.01], but there was no interaction between the two: DNMT3a: [F MMS×5-aza-dC(1,8)=1.100,P=0.3250]; DNMT3b: [F MMS×5-aza-dC(1,8)=1.585,P=0.2436]. Further analysis showed that the drug toxicity injury group and the 5-aza-dC intervention treatment group increased the expression of DNMT3a / 3b in the mouse retina, but 5-aza-dC did not change the effect of the drug toxicity injury group on DNMT3a (Nomal+PBS vs.MMS+PBS, P>0.05). The results showed that in the DNA methylation changes of the drug toxicity retinal injury group, 5-aza-dC was not involved in regulating the expression of DNMT3a / 3b in the retina after drug toxicity injury.

[0167] (c) Effect of 5-aza-dC on the expression of MeCP2: Results Fig.21As shown in Figure E, two-way ANOVA showed that the drug toxicity injury group could promote a slight upregulation of MeCP2 expression in the retina [F MMS(1,8)=98.23,P<0.0001], 5-aza-dC had an effect on the expression of MeCP2 [F 5-aza-dC(1,8)=82.29,P<0.0001], and there was a significant interaction between the two [F MMS×5-aza-dC(1,8)=120.4,P<0.0001]. Further Sidak multiple comparison analysis showed that drug toxicity injury promoted the expression of MeCP2 in the mouse retina, while 5-aza-dC did not reduce the high expression caused by MMS. The results indicate that in the DNA methylation changes of drug toxicity retinal injury, 5-aza-dC may not have a regulatory effect on the high expression of MeCP2 induced by MMS.

[0168] (5) Effects of 5-aza-dC on the expression of Crx and downstream genes

[0169] The above experiments show that 5-aza-dC affects the methylation level of genes by regulating the expression of DNMT1, thereby regulating gene transcription. Therefore, the mRNA expression level of Crx, a transcription factor related to retinal development and function maintenance, screened by sequencing, was detected. Two-way ANOVA showed that ( Fig. 22 ), MMS and 5-aza-dC both had significant effects on the expression of Crx mRNA in the retina [F MMS(1,20)=4.71,P<0.05; F5-aza-dC(1,20)=24.15,P<0.0001], and there was a significant interaction between the two [F MMS×5-aza-dC(1,20)=4.65,P<0.05]. Sidak multiple comparisons showed that MMS significantly reduced the mRNA expression of Crx in the mouse retina (Nomal+PBS vs.MMS+PBS,P<0.05), while 5-aza-dC reversed the MMS-induced low expression of Crx (MMS+PBS vs.MMS+5-aza-dC,P<0.001). As downstream genes regulated by Crx, the mRNA expression levels of Rp1 and Rhodopsin also changed with the changes of Crx. The results showed that MMS increased the methylation level of Crx, and its gene and protein expression levels were significantly downregulated, thereby affecting the expression of downstream genes Rp1 and Rhodopsin. 5-aza-dC reversed the low expression of Crx, causing the expression of Rp1 and Rhodopsin to increase, significantly improving the damage to retinal photoreceptor cells caused by chronic drug toxicity.

[0170] The above results indicate that 5-aza-dC specifically regulates the expression and activity of DNMT1, changes the methylation levels of related genes, promotes the restoration of normal expression levels of DNMT1, improves retinal function, increases the survival rate of retinal photoreceptor cells, and partially restores the outer segment structure, thereby effectively improving the morphology of chronic drug-toxic retinal damage and improving the visual function of the retina.

[0171] Although some preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0172] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of this application and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A drug for preventing and treating chronic drug toxicity retinal photoreceptor cell damage, characterized in that: The drug includes decitabine.

2. The drug according to claim 1, characterized in that The chronic drug toxicity retinal photoreceptor cell damage is chronic drug toxicity retinal photoreceptor cell damage induced by alkylating agents.

3. The drug according to claim 2, characterized in that The alkylating agents include methyl methanesulfonate, N-methyl-N-nitrosourea, cyclophosphamide, chlorambucil, procarbazine, camoxetine, nimoxetine, streptozocin, platinums and temozolomide.

4. The drug according to claim 1, characterized in that The dosage form is injection.

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