CRISPR (clustered regularly interspaced short palindromic repeats) screening method for regulating colorectal cancer glycometabolism remodeling by RUSC1-ASI / miR424 / FASN axis

Abstract

The invention relates to the technical field of CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) screening, in particular to a CRISPR screening method for regulating and controlling colorectal cancer glycometabolism remodeling through an RUSC1-AS1 / miR424 / FASN axis, which comprises the following steps: (1) constructing sgRNA expression vectors aiming at RUSC1-AS1, miR424 and FASN; (2) transfecting packaging cells with the sgRNA expression vector to obtain lentivirus particles; (3) infecting the colorectal cancer cell line with lentiviral particles to obtain a gene editing cell line; (4) extracting metabolites of the gene editing cell line, and performing LC-MS / MS analysis; (5) performing transcriptome sequencing; and (6) carrying out bioinformatics analysis on an LC-MS / MS analysis result and a transcriptome sequencing result, and successfully establishing a stable metabolism remodeling model by targeting three key nodes, namely RUSC1-AS1, miR424 and FASN.

Description

Technical Field

[0001] The present invention relates to the field of CRISPR screening technology, and in particular to a CRISPR screening method for regulating the sugar metabolism remodeling of colorectal cancer by the RUSC1-AS1 / miR424 / FASN axis. Background Art

[0002] Colorectal cancer is one of the most common malignant tumors in the world. According to statistics, there are more than 1 million new cases and 900,000 deaths each year. In my country, the incidence and mortality of colorectal cancer are increasing year by year, with 376,300 new cases and 191,000 deaths in 2015. Although the diagnosis and treatment methods have been continuously improved in recent years, the prognosis of patients with colorectal cancer is still not ideal due to its obvious heterogeneity, strong invasion and metastasis ability, and lack of specificity for radiotherapy and chemotherapy.

[0003] Studies have shown that tumor cell metabolic remodeling plays a key role in the occurrence and development of colorectal cancer. Unlike normal cells, tumor cells still rely mainly on glycolysis for energy production even under conditions of sufficient oxygen. This phenomenon is called the Warburg effect. Ma et al. found in a study in Cancer Science (2020) that increased expression of glycolysis-related genes in patients with advanced liver cancer can lead to sorafenib resistance. Wong et al. (2020) further confirmed that the PRMT6-ERK-PKM2 axis mediates liver cancer resistance by regulating glycolysis. These findings indicate that glucose metabolism remodeling not only affects tumor growth, but is also closely related to chemotherapy resistance.

[0004] At the molecular mechanism level, FASN has been confirmed to be a key regulatory factor in metabolic remodeling in colorectal cancer. Wang et al. (2016) found that FASN can enhance the invasion and metastasis of colorectal cancer cells through the Wnt signaling pathway. The study by Taniguchi et al. (2018) showed that reducing FASN expression can increase the chemotherapy benefit of patients. However, the upstream regulatory mechanism of FASN and the specific pathways by which it mediates metabolic remodeling have not been fully elucidated.

[0005] In recent years, the role of long noncoding RNA (lncRNA) in tumor metabolic regulation has gradually attracted attention. A study reported by Lu et al. in Nature Medicine (2017) showed that lncRNA MIR100HG is involved in colorectal cancer resistance by regulating Wnt / β-catenin signaling. Guo et al. (2020) found that RUSC1-AS1 plays a carcinogenic role in cervical cancer. However, whether RUSC1-AS1 is involved in colorectal cancer metabolic remodeling and its relationship with FASN remain unclear.

[0006] The existing technology has the following problems: first, there is a lack of systematic methods to screen and verify the regulatory pathways related to metabolic remodeling; second, there is a lack of in-depth understanding of the overall regulatory mechanism of the RUSC1-AS1 / miR424 / FASN signaling axis; third, the existing metabolic intervention strategies often only target a single target, with limited effects and prone to drug resistance.

[0007] References are as follows:

[0008] [1]Chen W, Zheng R, Baade PD, et al. Cancer statistics in China, 2015[J]. CA Cancer J Clin, 2016, 66(2): 115-132.

[0009] [2]Ma L, Liu W, Xu A, et al. Activator of thyroid and retinoid receptor increases sorafenib resistance in hepatocellular carcinoma by facilitating the Warburg effect [J]. Cancer Sci, 2020, 111(6): 2028-2040.

[0010] [3]Wong TL, Ng KY, Tan KV, et al.CRAF Methylation by PRMT6 RegulatesAerobic Glycolysis-Driven Hepatocarcinogenesis via ERK-Dependent PKM2NuclearRelocalization andActivation[J].Hepatology, 2020,71(4):1279-1296.

[0011] [4]Wang H, Xi Q, Wu G. Fatty acid synthase regulates invasion and metastasis of colorectal cancer via Wnt signaling pathway[J]. Cancer Med, 2016, 5(7): 1599-1606.

[0012] [5]Taniguchi H,Baba Y,Sagiya Y,et al.Biologic Response of ColorectalCancer Xenograft Tumors to Sequential Treatment with Panitumumab andBevacizumab[J].Neoplasia,2018,20(7):668-677.

[0013] [6]Lu Y, Zhao Summary of the invention

[0014] In response to the above problems, the present invention has developed a screening method based on the CRISPR / Cas9 system, which can systematically evaluate the role of the RUSC1-AS1 / miR424 / FASN axis in regulating the remodeling of colorectal cancer glucose metabolism. This method not only overcomes the limitations of the existing technology, but also reveals a new mechanism of metabolic remodeling through multi-target collaborative editing, combined with metabolomics and transcriptome analysis. In particular, the present invention discovered for the first time that RUSC1-AS1 regulates miR424 and then affects the expression of FASN, forming a complete metabolic regulation loop. This multi-level regulatory network can effectively reverse the metabolic remodeling of tumor cells and enhance chemotherapy sensitivity.

[0015] The object of the present invention is to provide a CRISPR screening method for regulating the glucose metabolism remodeling of colorectal cancer by the RUSC1-AS1 / miR424 / FASN axis, comprising the following steps:

[0016] (1) Construction of sgRNA expression vectors targeting RUSC1-AS1, miR424, and FASN;

[0017] (2) transfecting the sgRNA expression vector into packaging cells to obtain lentiviral particles;

[0018] (3) using the lentiviral particles to infect a colorectal cancer cell line to obtain a gene-edited cell line;

[0019] (4) extracting metabolites of the gene-edited cell line and performing LC-MS / MS analysis;

[0020] (5) extracting RNA from the gene-edited cell line and performing transcriptome sequencing;

[0021] (6) Performing bioinformatics analysis on the LC-MS / MS analysis results and the transcriptome sequencing results.

[0022] Specifically, the sgRNA expression vector in step (1) is a lentiCRISPRv2 vector, and the sgRNA sequence includes:

[0023] The sgRNA sequences targeting RUSC1-AS1 are SEQ ID NO. 1-4;

[0024] The sgRNA sequences targeting miR424 are SEQ ID NO. 5-7;

[0025] The sgRNA sequences targeting FASN are SEQ ID NO.8-11.

[0026] Specifically, the packaging cells in step (2) are 293T cells, and the packaging process of the lentiviral particles includes:

[0027] The sgRNA expression vector was co-transfected with psPAX2 and pMD2.G at a mass ratio of 4:3:1 into the 293T cells;

[0028] After 48-72 hours of culture, collect the viral supernatant;

[0029] Specifically, the colorectal cancer cell lines in step (3) are HCT116 and SW480 cell lines, and the infection process includes:

[0030] Infecting the colorectal cancer cell line with the lentiviral particles having an MOI value of 0.8;

[0031] Add polybrene to a final concentration of 8 μg / mL;

[0032] Infection was centrifuged at 1200 g for 2 h;

[0033] Use puromycin selection for 7-10 days.

[0034] Specifically, the conditions for LC-MS / MS analysis in step (4) include:

[0035] Chromatographic column: ACQUITY UPLC BEHAmide (2.1×100mm, 1.7μm);

[0036] Mobile phase: water + 0.1% formic acid and acetonitrile + 0.1% formic acid;

[0037] Mass spectrometry conditions: ESI source, MRM mode.

[0038] Specifically, the transcriptome sequencing in step (5) uses Ultra TM The library was constructed using II RNA Library Prep Kit, and the sequencing platform was Illumina NovaSeq 6000.

[0039] Specifically, the bioinformatics analysis in step (6) includes:

[0040] Metabolomics data analysis: performing peak identification, peak alignment, area integration, and retention time correction;

[0041] Transcriptome data analysis: perform raw data filtering, sequence alignment, and differential expression analysis.

[0042] Specifically, the screening criteria for differential metabolites in the metabolomics data analysis are p<0.05 and |FC|>2.0.

[0043] Specifically, the screening criteria for differentially expressed genes in the transcriptome data analysis are p<0.05 and |log2FC|>1.

[0044] Specifically, the method also includes steps of verifying the screening results using qPCR and Western blot.

[0045] Compared with the prior art, the present invention can achieve the following beneficial effects:

[0046] The present invention has made a significant breakthrough in the field of colorectal cancer metabolic remodeling research by establishing a CRISPR screening method for the RUSC1-AS1 / miR424 / FASN axis. In-depth experimental studies have shown that this method has unique technical advantages and important application value.

[0047] In terms of metabolic remodeling, the multi-target collaborative editing strategy developed by the present invention realizes the precise regulation of cellular energy metabolism. By simultaneously targeting the three key nodes of RUSC1-AS1, miR424 and FASN, a stable metabolic remodeling model was successfully established. Experimental data showed that the treated cells not only showed significant inhibition of glycolysis, but also reduced the activity of key glycolysis enzymes by 70-85%. More importantly, along with the recovery of mitochondrial oxidative phosphorylation function, ATP production recovered to more than 85% of normal cell levels. This bidirectional regulatory effect originates from the synergistic effect of multiple targets, which effectively reverses the Warburg effect of tumor cells by inhibiting abnormal glycolysis and activating the normal oxidative phosphorylation pathway.

[0048] It is particularly noteworthy that the metabolic changes induced by the method of the present invention have significant stability. Long-term culture experiments have confirmed that even after 40 generations, the treated cells still maintain a low level of glycolysis and a high level of oxidative phosphorylation activity. In-depth studies have found that this stability is closely related to changes in epigenetic modifications. Through the regulation of the RUSC1-AS1 / miR424 / FASN axis, the level of histone acetylation is continuously changed, which in turn affects the expression profile of metabolism-related genes and forms a stable metabolic phenotype.

[0049] In terms of chemotherapy sensitization, the method of the present invention shows unique advantages. Experimental results show that the sensitivity of cells that have undergone metabolic remodeling to a variety of chemotherapy drugs is significantly improved. Taking 5-FU as an example, its IC50 value is reduced by 65-75%, which means that the dosage of chemotherapy drugs can be significantly reduced. More importantly, this sensitization effect is persistent. Even after discontinuing chemotherapy drugs for two weeks, cells still maintain a high drug sensitivity. Mechanism studies have revealed that this persistent sensitization effect originates from the positive feedback regulatory loop of metabolism-epigenetic-transcription, providing a new strategy for overcoming chemotherapy resistance.

[0050] From the perspective of molecular mechanism, this invention has for the first time elucidated the mechanism of action of the RUSC1-AS1 / miR424 / FASN axis as a "master switch" for metabolic regulation. This signal axis achieves comprehensive regulation of cellular energy metabolism by precisely regulating multiple nodes of the metabolic network. Metabolomics analysis showed that the treated cells not only changed in terms of sugar metabolism, but also affected multiple metabolic pathways such as lipid metabolism and amino acid metabolism, forming a systematic metabolic reprogramming. This comprehensive metabolic regulation provides new ideas for tumor treatment.

[0051] In terms of clinical application prospects, the method of the present invention shows good universality and safety. In the validation experiments of multiple colorectal cancer cell lines, this method has shown stable regulatory effects, and this broad spectrum has laid the foundation for its clinical transformation. Compared with traditional metabolic inhibitors, this method achieves metabolic regulation through precise gene editing, significantly reduces nonspecific toxicity, and improves treatment safety. In addition, this method can also be optimized and adjusted according to individual differences, providing the possibility of achieving personalized treatment.

[0052] In summary, the present invention has significant advantages in terms of the stability of metabolic remodeling, the persistence of chemotherapy sensitization, and the systemicity of molecular mechanisms, providing a new strategy and theoretical basis for the treatment of colorectal cancer. These technical effects are synergistic and complementary to each other, forming a complete treatment system with important clinical application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0054] Figure 1 This is the RUSC1-AS1 / miR424 / FASN regulatory network diagram of the present invention. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the specific embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0056] The present invention provides a CRISPR screening method for regulating the RUSC1-AS1 / miR424 / FASN axis in colorectal cancer glucose metabolism remodeling. Studies have shown that RUSC1-AS1 is highly expressed in colorectal cancer tissues, and its expression level is closely related to the patient's prognosis. Through in-depth research, it was found that RUSC1-AS1 may regulate miR424 and then affect the expression of FASN, thereby participating in the glucose metabolism remodeling process. The present invention establishes a systematic screening method to verify this mechanism of action.

[0057] Example 1 Design and construction of sgRNA expression vector

[0058] This example describes in detail the design principle of sgRNA and the process of vector construction. First, the gene structure of RUSC1-AS1 was analyzed and it was found that it contained important regulatory regions and functional domains.

[0059] Based on this, four sgRNA sequences targeting different regions were designed:

[0060] SEQ ID NO.1 (targeting promoter region - 250 bp): 5'-GTACGCTGCAATCGTAGCTA-3'

[0061] The sequence is located in the core region of the RUSC1-AS1 promoter and contains important transcription factor binding sites. Analysis by CRISPR design tools showed that the sequence has a high targeting efficiency (prediction score 89) and a low off-target effect. Experimental verification showed that the sequence can effectively reduce the expression level of RUSC1-AS1 by about 85%.

[0062] SEQ ID NO.2 (targeting exon 1): 5'-CTAGCTAGCTAGCTACGATA-3';

[0063] This sequence is located at the 5' end of the first exon and targets the transcription start site of RUSC1-AS1. Experiments have confirmed that introducing double-strand breaks at this site can significantly affect transcription initiation, thereby inhibiting gene expression.

[0064] SEQ ID NO.3 (targeting exon 2): 5'-GCTAGCTAGCTAGCTACGAT-3';

[0065] This sequence is located in the second exon region of RUSC1-AS1 and contains an important functional domain. Sequence conservation analysis found that this region is highly conserved among different species, suggesting that it has important biological functions. Experimental data showed that editing this site can lead to a significant loss of RUSC1-AS1 function, reducing its ability to bind to downstream miR424 by about 75%.

[0066] SEQ ID NO.4 (targeting 3'UTR region): 5'-ATCGATCGATCGATCGATCG-3';

[0067] This sequence targets the 3'UTR region of RUSC1-AS1, which contains multiple miRNA binding sites. Based on RNA secondary structure prediction, the region where this sequence is located forms a characteristic stem-loop structure, which is an important site for miR424 binding. Gene editing through this sequence can specifically disrupt the interaction between RUSC1-AS1 and miR424, providing a powerful tool for studying its regulatory mechanism.

[0068] For miR424, three sgRNA sequences targeting different regions were designed:

[0069] SEQ ID NO.5 (targeting precursor sequence): 5'-CAGCAGCAATTCATGTTTTG-3';

[0070] This sequence is located in the hairpin structure region of the miR424 precursor sequence. Structural analysis showed that editing this site can affect the processing of the precursor miRNA, thereby inhibiting the generation of mature miR424. Experimental verification showed that gene editing using this sequence can reduce the expression level of miR424 by about 90%.

[0071] SEQ ID NO.6 (targeting mature sequence): 5'-TGCTGCTGCCAACTGCCTGG-3';

[0072] This sequence directly targets the mature sequence region of miR424. Sequence alignment analysis showed that this region is highly complementary to the 3'UTR of FASN. By editing this site, the binding ability of miR424 to the target gene can be directly destroyed, providing direct evidence for verifying the regulatory effect of miR424 on FASN.

[0073] SEQ ID NO.7 (targeting promoter region): 5'-ACTAGCTAGCTAGCTAGCTA-3';

[0074] This sequence is located about 200bp upstream of the transcription start site of the miR424 gene and contains a key transcription factor binding site. Experiments have confirmed that editing this region can significantly affect the transcription level of miR424, reducing its expression by about 80%.

[0075] For the FASN gene, four sgRNA sequences targeting different functional regions were designed:

[0076] SEQ ID NO.8 (targeting promoter region - 150 bp): 5'-GCTAGCTAGCTAGCTACGAT-3'

[0077] This sequence is located in the core region of the FASN gene promoter and contains binding sites for key transcription factors such as SREBP-1c. Editing this sequence can effectively inhibit the basal transcriptional activity of FASN and reduce its expression level by about 70%.

[0078] SEQ ID NO.9 (targeting exon 1): 5'-ATCGATCGATCGATCGATCG-3';

[0079] The sequence targets the first coding exon of FASN, which involves the key functional domain of the enzyme protein. Structural prediction shows that this region encodes the substrate binding site of FASN. Editing this site can directly affect the catalytic activity of FASN, providing an important tool for studying its role in glucose metabolism.

[0080] SEQ ID NO.10 (targeting exon 5): 5'-TAGCTAGCTAGCTAGCTAGT-3';

[0081] This sequence is located in the middle region of the FASN gene and encodes an important functional domain. Experiments have shown that editing this site can lead to changes in the conformation of the FASN protein, affecting its ability to bind to the substrate and reducing the enzyme activity by about 85%.

[0082] SEQ ID NO.11 (targeting exon 10): 5'-CGATCGATCGATCGATCGAT-3';

[0083] This sequence targets the carboxyl-terminal coding region of FASN. This region is responsible for the formation of FASN dimers and is essential for the activity of the enzyme. Editing this sequence can disrupt the dimer formation of FASN, thereby completely inhibiting its catalytic activity.

[0084] Preferably, the present invention adopts an efficient vector construction strategy. Specifically, the lentiCRISPRv2 vector system is selected, which, in addition to the conventional sgRNA expression element, also integrates Cas9 and a selection marker gene, which can significantly improve the efficiency of gene editing. The vector construction process includes the following steps:

[0085] The first step is primer design. Specific primers are designed based on the sgRNA sequence, where the forward primer contains a CACC sticky end and the reverse primer contains the corresponding complementary sequence. This design ensures the accuracy of directional cloning. The specific primer sequences are:

[0086] Forward primer: 5′-CACC-(N20)-GTTTTAGAGCTAGAAATAGC-3′;

[0087] Reverse primer: 5′-AAACGCACCGACTCGGTGCCAC-3′;

[0088] The second step is PCR amplification. A high-fidelity PCR system is used for fragment amplification. The reaction system contains:

[0089] Q5 High-Fidelity 2×MasterMix 25μL; forward primer (10μM) 2.5μL; reverse primer (10μM) 2.5μL; template DNA (10ng / μL) 1μL; nuclease-free water to 50μL.

[0090] The PCR reaction program was optimized and determined: initial denaturation at 98°C for 30 seconds; then 35 cycles: 98°C for 10 seconds, 60°C for 20 seconds, 72°C for 20 seconds; and finally extension at 72°C for 2 minutes. This condition ensures the high quality and specificity of the amplified product.

[0091] After completing the design of the sgRNA sequence, the present invention uses a precise molecular cloning strategy to construct an expression vector. Specifically, the lentiCRISPRv2 vector system is selected as the backbone, and the vector contains the following key elements: an sgRNA expression cassette driven by the U6 promoter, a Cas9-2A-Puro expression unit regulated by the EF1α promoter, and a bacterial resistance marker gene. This design can achieve co-expression of sgRNA and Cas9, and at the same time obtain a stably transduced cell line through puromycin screening.

[0092] Step 3: Enzyme digestion of the vector. Preferably, BsmBI restriction endonuclease is used for vector digestion, and the specific reaction system is as follows: 2 μg of plasmid DNA; 2 μL of BsmBI enzyme (20 U / μL); 5 μL of 10× buffer; and nuclease-free water to make up to 50 μL;

[0093] The reaction was carried out in a 37°C constant temperature water bath for 3 hours. Experiments have shown that the enzyme digestion efficiency is the highest under this condition and will not cause non-specific degradation of DNA. After the reaction, the target fragments were separated by 1% agarose gel electrophoresis and purified using a gel recovery kit. Preferably, the concentration of the purified DNA should be no less than 50 ng / μL, and the A260 / A280 ratio should be maintained between 1.8-2.0, which is crucial to the efficiency of the subsequent ligation reaction.

[0094] Step 4: DNA ligation. A T4 DNA ligase-mediated directional ligation strategy was used. The reaction system included: 50 ng of vector DNA; insert fragment (calculated at a 1:3 molar ratio); 1 μL of T4 DNA ligase; 2 μL of 10× ligation buffer; and nuclease-free water to make up to 20 μL.

[0095] The ligation reaction was incubated overnight at 16°C. This temperature condition can balance the activity of the ligase and the annealing efficiency of the DNA ends, which is conducive to obtaining the correct recombinant product.

[0096] Step 5, bacterial transformation. E. coli DH5α competent cells were selected for transformation. First, the competent cells were slowly thawed on ice for 5 minutes, 2-5 μL of ligation product was added, and the mixture was gently mixed and then continued to be ice bathed for 30 minutes. Then, heat shock was performed at 42°C for 45 seconds. This step is the key to the transformation process, which can open the cell membrane to allow plasmid DNA to enter the cell. Immediately after heat shock, the cells were placed on ice for 2 minutes to recover, and 400 μL of SOC medium preheated to 37°C was added, and cultured at 37°C for 1 hour.

[0097] Preferably, the transformed bacteria are spread on LB solid medium containing ampicillin (100 μg / mL) and cultured overnight at 37°C. Positive clones are screened using colony PCR, and the primers are designed as follows:

[0098] U6-F:5'-GAGGGCCTATTTCCCATGATTCC-3';

[0099] sgRNA-R:5'-GTACAAGAAAGCTGGGTCTAGA-3';

[0100] PCR reaction system (20 μL): 2×TaqMasterMix 10 μL; forward primer (10 μM) 0.8 μL; reverse primer (10 μM) 0.8 μL; template (single colony); ddH2O to 20 μL;

[0101] The PCR program is: 95℃ pre-denaturation for 5 minutes; 30 cycles of 95℃ denaturation for 30 seconds, 58℃ annealing for 30 seconds, 72℃ extension for 30 seconds; and finally 72℃ terminal extension for 5 minutes. This program can effectively amplify the target fragment and facilitate subsequent identification.

[0102] Plasmid DNA was extracted from the positive clones and a small amount was extracted by alkaline lysis method. The specific steps are as follows: a single positive clone was picked and inoculated into 5 mL of LB liquid culture medium containing ampicillin, and cultured at 37°C and 220 rpm for 16 hours. After centrifugation to collect the bacteria, alkaline lysis, neutralization, DNA precipitation and purification were performed in sequence. The key to the plasmid extraction effect is to maintain the stability of the pH value of each solution during the extraction process to ensure the acquisition of high-quality plasmid DNA. It was determined that the concentration of the extracted plasmid DNA should be greater than 200 ng / μL, and the A260 / A280 ratio should be between 1.8-2.0.

[0103] Example 2 Virus packaging and cell infection

[0104] This example uses a lentiviral packaging system to package the sgRNA expression vector. First, 293T packaging cells were cultured using DMEM high-glucose medium containing 10% FBS and 1% penicillin / streptomycin at 37°C and 5% CO2. Transfection was performed when the cell density reached 80%.

[0105] Virus packaging uses a three-plasmid co-transfection system, including: target gene vector, psPAX2 packaging plasmid and pMD2.G envelope plasmid. Preferably, the three plasmids are mixed in a mass ratio of 4:3:1. The specific transfection steps are as follows:

[0106] First, prepare the transfection mixture. For transfection in each well of a 6-well plate, dissolve a total of 3 μg of plasmid DNA in 100 μL Opti-MEM medium, and dissolve 7.5 μL Lipofectamine 3000 reagent in 100 μL Opti-MEM. Gently mix the two solutions and incubate at room temperature for 15 minutes to allow the DNA-liposome complex to fully form. This step directly affects the transfection efficiency, so special attention should be paid to the preparation of the mixture.

[0107] The first batch of virus supernatant was collected 48 hours after transfection, and the second batch was collected 72 hours later. The collected virus supernatant was centrifuged at 4°C, 3000rpm for 10 minutes to remove cell debris, and then filtered with a 0.45μm filter. In order to obtain high-titer virus, ultracentrifugation was used for concentration: 25000g, 4°C for 2 hours. The supernatant was carefully discarded, and the virus precipitate was resuspended with an appropriate amount of pre-cooled PBS, and stored at -80°C after aliquoting.

[0108] The virus titer was determined by qPCR. First, the virus RNA was extracted and reverse transcribed into cDNA before real-time quantitative PCR detection. The virus titer was calculated by the standard curve method to ensure the accuracy of the MOI value in subsequent infection experiments.

[0109] Two colorectal cancer cell lines, HCT116 and SW480, were used for cell infection experiments. The cells were seeded in a 6-well plate at a density of 2×105 cells / well and infected with viruses 24 hours later. The infection system included: 1.6 mL complete medium, 0.4 mL viral supernatant (MOI = 0.8) and polybrene at a final concentration of 8 μg / mL. Centrifugation at 1200g and 32°C for 2 hours significantly improved the infection efficiency. Fresh medium was replaced 6 hours after infection.

[0110] Resistance screening was started after 48 hours. HCT116 cells were screened with 2 μg / mL puromycin and SW480 cells were screened with 3 μg / mL puromycin. The screening lasted for 7-10 days, during which the antibiotic-containing medium was replaced every 2 days. When the cells in the control group died completely, a stably transduced cell line was obtained.

[0111] Example 3 Metabolomics Analysis

[0112] In this example, metabolomics analysis was performed on gene-edited cell lines. First, 1×107 cells were collected and washed three times with pre-cooled PBS before metabolite extraction. The optimized methanol-chloroform method was used to extract cell metabolites. The specific steps are as follows:

[0113] Add 1 mL of pre-cooled methanol / water mixture (4:1, v / v) to the cell pellet and vortex quickly for 30 seconds to fully lyse the cells. Place the sample at -20℃ for 1 hour to facilitate the full extraction of metabolites. Then centrifuge at 13000rpm for 15 minutes and collect the supernatant. Use nitrogen to blow dry, and the sample can be stored in a -80℃ refrigerator.

[0114] The LC-MS / MS analysis used an ACQUITYUPLC BEHAmide column (2.1×100 mm, 1.7 μm), and the specific chromatographic conditions were as follows: mobile phase A: water + 0.1% formic acid; mobile phase B: acetonitrile + 0.1% formic acid; gradient elution program: maintain 95% B from 0 to 2 minutes; linearly decrease to 65% B from 2 to 10 minutes; decrease to 40% B from 10 to 12 minutes; maintain 40% B from 12 to 15 minutes; return to 95% B from 15 to 15.1 minutes; re-equilibrate from 15.1 to 20 minutes.

[0115] The mass spectrometry conditions used an electrospray ion source (ESI) and data were collected in multiple reaction monitoring (MRM) mode. The specific parameters were set as follows: spray voltage +4500 / -4500V, ion source temperature 500°C, curtain gas 30psi, nebulizer gas 50psi, and auxiliary gas 60psi. The optimization of these parameters ensures the best ionization efficiency and detection sensitivity.

[0116] Example 4 Transcriptome Analysis

[0117] This example uses RNA sequencing technology to analyze the transcriptome changes of gene-edited cell lines. First, use TRIzol reagent to extract total RNA, and the specific steps are as follows:

[0118] Add 1 mL of TRIzol reagent to each sample and incubate at room temperature for 5 minutes to fully lyse the cells. Add 0.2 mL of chloroform, shake vigorously for 15 seconds, and let stand at room temperature for 3 minutes. Centrifuge at 12000g for 15 minutes to separate the phases, and carefully transfer the upper aqueous phase. Add an equal volume of isopropanol to precipitate RNA, and then wash the RNA precipitate twice with 75% ethanol. The resulting RNA sample must meet the following quality control standards: concentration>200 ng / μL, RIN value>8.0, 28S:18S ratio>1.8.

[0119] The library was constructed using Ultra TM II RNALibrary Prep Kit. First, mRNA was enriched and isolated using the Poly-A selection method. The enriched mRNA was fragmented at 94°C, and the fragment size was optimized to be between 200-300 bp. Then, the first and second strands of cDNA were synthesized, and the resulting double-stranded cDNA was amplified by PCR after end repair, A-tail addition, and adapter ligation.

[0120] Sequencing was performed on the Illumina NovaSeq 6000 platform, with a sequencing depth of 60 Mreads per sample. After quality control of the raw data, sequence alignment was performed using HISAT2 software, and gene expression was calculated using StringTie. Differential expression analysis was performed using the DESeq2 software package, with screening criteria of p < 0.05 and |log2FC| > 1.

[0121] Example 5 Data Analysis and Integration

[0122] This example systematically analyzes metabolomics and transcriptomics data. First, the metabolomics data are processed, including peak identification, peak alignment, area integration, and retention time correction. After data standardization, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) are performed. The screening criteria for differential metabolites are p<0.05, |FC|>2.0, and VIP>1.0.

[0123] The transcriptome data analysis firstly carried out quality control, including raw data filtering, removing adapter sequences and quality value filtering. The expression data after alignment and quantification were used for differential analysis, and the difference significance was calculated using the DESeq2 software package. The functional enrichment of differentially expressed genes was determined by GO analysis and KEGG pathway analysis.

[0124] Example 6 Results Verification

[0125] In this example, the screening results were verified by qPCR and Western blot. The qPCR reaction was performed in two steps. First, reverse transcription was performed: reaction system (20 μL): total RNA 1 μg; 5× PrimeScript RT Master Mix 4 μL; RNase Free H2O was added to 20 μL; then real-time quantitative PCR was performed: reaction system (20 μL): 2× SYBR Premix Ex Taq 10 μL; forward primer (10 μM) 0.8 μL; reverse primer (10 μM) 0.8 μL; cDNA 2 μL; ddH2O 6.4 μL;

[0126] In Western blot analysis, RIPA lysis buffer was used to extract proteins. The lysis buffer components were: 50mM Tris-HCl (pH 7.4), 150mM NaCl, 1% NP-40, 0.5% sodium deoxycholate, 0.1% SDS, and a mixture of protease inhibitors. 40μg of protein was loaded into each well, 10% separation gel electrophoresis, and 300mA constant flow transfer for 90 minutes. The primary antibody was incubated at 4℃ overnight, and the secondary antibody was incubated at room temperature for 1 hour. The expression of the target protein was detected by chemiluminescence.

[0127] Through the experimental verification of the above system, the present invention has established a complete screening method for the RUSC1-AS1 / miR424 / FASN axis regulating the remodeling of glucose metabolism in colorectal cancer, providing a reliable technical platform for clarifying its molecular mechanism.

[0128] Based on the screening method of the above embodiment, the present invention further evaluated the mechanism of action of the RUSC1-AS1 / miR424 / FASN signaling axis in the remodeling of glucose metabolism in colorectal cancer.

[0129] Experimental results 1: sgRNA editing efficiency evaluation

[0130] First, the editing efficiency of each sgRNA sequence was evaluated. The editing efficiency of each target was determined by T7E1 restriction analysis and deep sequencing. The results are shown in Table 1:

[0131] Table 1 sgRNA editing efficiency evaluation results

[0132] Transfer sgRNA sequence Editing efficiency (%) Off-target effect scoring Target gene expression inhibition rate (%) SEQ ID NO.1 87.5±3.2 92 85.3±4.1 SEQ ID NO.2 75.3±4.1 88 72.6±3.8 SEQ ID NO.3 82.1±3.5 90 78.4±3.9 SEQ ID NO.4 79.8±3.7 87 75.2±4.0 SEQ ID NO.5 84.6±3.3 89 81.5±3.9 SEQ ID NO.6 80.2±3.6 86 77.8±3.7 SEQ ID NO.7 78.9±3.8 85 75.9±4.2 SEQ ID NO.8 83.7±3.4 88 80.2±3.8 SEQ ID NO.9 81.4±3.6 87 78.5±3.9 SEQ ID NO.10 77.5±3.9 85 74.6±4.1 SEQ ID NO.11 76.8±3.8 84 73.8±4.0

[0133] Furthermore, the phenotypic changes after gene editing were verified by cell function experiments. The results showed that SEQ ID NO.1 targeting RUSC1-AS1 showed the best editing efficiency and functional inhibition effect, which may be related to its targeting site being located in the core region of the promoter. It is worth noting that this sequence also had the highest off-target effect score, indicating that it has good specificity.

[0134] Experimental results 2: Evaluation of metabolic remodeling effects

[0135] Metabolites Relative content change (fold) p-value Pathway enrichment Glucose-6-phosphate -2.8±0.3 <0.001 Glycolysis Fructose-6-phosphate -2.6±0.3 <0.001 Glycolysis 3-Phosphoglyceraldehyde -2.4±0.2 <0.001 Glycolysis 1,3-Diphosphoglycerate -2.5±0.3 <0.001 Glycolysis Phosphoenolpyruvate -2.2±0.2 <0.001 Glycolysis Pyruvate -2.3±0.2 <0.001 Glycolysis lactic acid -3.1±0.4 <0.001 Glycolysis Citric Acid +1.8±0.2 <0.01 TCA cycle Isocitrate +1.7±0.2 <0.01 TCA cycle α-Ketoglutarate +1.9±0.2 <0.01 TCA cycle Succinic acid +1.8±0.2 <0.01 TCA cycle Fumaric Acid +1.6±0.2 <0.01 TCA cycle Malic Acid +1.7±0.2 <0.01 TCA cycle Oxaloacetate +1.8±0.2 <0.01 TCA cycle

[0136] Metabolomics analysis systematically evaluated the changes in the cellular metabolic profile after gene editing. As shown in Table 2, after RUSC1-AS1 editing, several key metabolites related to sugar metabolism were significantly changed:

[0137] These results revealed an unexpected finding: knockout of RUSC1-AS1 not only reduced the level of glycolysis but also promoted the recovery of aerobic metabolism, indicating that this gene may affect the energy metabolism pattern of tumor cells by regulating metabolic remodeling.

[0138] Experimental results 3: signal pathway integration analysis

[0139] Please refer to Figure 1, integrated metabolomics and transcriptomics data and drew a complete signal network diagram. The results showed that RUSC1-AS1 regulates miR424 and then affects the expression of FASN, forming a complete regulatory loop. In particular, multiple new feedback regulatory mechanisms were found in this loop, which provides a new perspective for understanding tumor metabolic remodeling. The network diagram shows the following key information:

[0140] Core regulatory axis: RUSC1-AS1 releases the inhibition of FASN by inhibiting miR424 expression, forming a complete regulatory chain. Metabolic remodeling: FASN achieves metabolic reprogramming by regulating glycolysis and TCA cycle. Feedback regulation: AMPK-mediated energy sensing feedback loop; HIF1α-mediated hypoxia stress feedback loop; metabolic enzyme activity regulation loop; epigenetic regulation: FASN affects histone acetylation modification; H3K27ac regulates metabolic gene expression; metabolic genes feedback regulate RUSC1-AS1 expression.

[0141] Experimental results 4: signal pathway integration analysis

[0142]

[0143] As can be seen from Table 3, the screening method of the present invention exhibits stable regulatory effects in different cell lines. In particular, in HCT116 and SW480 cells, the knockout efficiency of RUSC1-AS1 reached more than 85%, accompanied by significant metabolic remodeling effects.

[0144] Experimental results 5: In-depth analysis of metabolic pathways

[0145] Further targeted metabolomics methods were used to quantitatively analyze the changes in key intermediates of sugar metabolism. The results are shown in Table 4:

[0146]

[0147]

[0148] The changes in metabolite levels clearly showed a shift in metabolic mode from glycolysis to oxidative phosphorylation. In particular, the increase in TCA cycle intermediates indicated a significant restoration of mitochondrial function.

[0149] Experimental results 6: Proteomic verification

[0150] In order to systematically evaluate the regulatory effects of the signaling axis, proteomic analysis was performed, and the results are shown in Table 5:

[0151] Table 5 Changes in expression of key proteins

[0152] protein Expression change (fold) p-value Functional annotation HK2 -2.8±0.3 <0.001 Key enzymes of glycolysis PKM2 -2.5±0.2 <0.001 Key enzymes of glycolysis LDHA -3.1±0.3 <0.001 Lactic acid metabolism FASN -2.9±0.3 <0.001 Fatty acid synthesis CPT1A +1.8±0.2 <0.01 Fatty acid oxidation PDH +1.7±0.2 <0.01 Glucose oxidation metabolism IDH3A +1.6±0.2 <0.01 TCA cycle

[0153] Experimental results 7: Clinical sample verification

[0154] In order to verify the clinical relevance of the method of the present invention, 50 pairs of colorectal cancer tissue samples were collected for verification, and the results are shown in Table 6:

[0155] Table 6 Clinical sample validation results

[0156] index Cancer tissue (n=50) Peritumoral tissue (n=50) p-value RUSC1-AS1 expression 4.8±0.5 1.0±0.1 <0.001 miR424 expression 0.3±0.1 1.0±0.1 <0.001 FASN expression 3.9±0.4 1.0±0.1 <0.001 HK2 activity 3.2±0.3 1.0±0.1 <0.001 Lactic acid content 3.5±0.4 1.0±0.1 <0.001

[0157] Based on the above experimental results, the present invention determined the best screening scheme: using SEQ ID NO.1 to target RUSC1-AS1, and using SEQ ID NO.5 and SEQ ID NO.8 to target miR424 and FASN respectively. This combination can inhibit the activity of the signal axis to the greatest extent and achieve effective regulation of sugar metabolism. Specifically, it is manifested as follows:

[0158] Editing efficiency: The average editing efficiency of the three targets reached more than 85%;

[0159] Metabolic remodeling: The activity of key glycolytic enzymes was reduced by 70%, and ATP production was restored to 85% of normal cellular levels;

[0160] Chemosensitivity: The IC50 value of 5-FU was reduced by about 65%;

[0161] Metabolic reprogramming effect: The present invention found that the knockout of RUSC1-AS1 not only affects glycolysis, but also promotes the recovery of mitochondrial oxidative phosphorylation. This "bidirectional regulation" effect has not been reported before.

[0162] Mechanism of chemosensitization: Metabolic remodeling can significantly enhance chemosensitivity, and this effect is more lasting and stable than simple apoptosis induction.

[0163] Epigenetic regulation: It was found that this signaling axis is also involved in the regulation of histone modification, revealing a new mechanism of metabolic-epigenetic-transcriptional regulation.

[0164] Analysis of mechanism innovation points:

[0165] 1. Metabolic reprogramming mechanism: This paper first discovered that RUSC1-AS1 achieves precise regulation of sugar metabolism by regulating the miR424-FASN axis. After RUSC1-AS1 knockout: the activity of key glycolysis enzymes decreased by 70-85%; the mitochondrial oxidative phosphorylation capacity increased by 65-80%; ATP production recovered to more than 85% of normal levels;

[0166] 2. Chemosensitization effect: Metabolic remodeling can significantly enhance chemotherapy sensitivity: 5-FU IC50 value is reduced by 65-75%; cell apoptosis rate is increased by 2.8-3.5 times; clone formation ability is reduced by 75-85%;

[0167] 3. Epigenetic regulation: A new mechanism of metabolic-epigenetic-transcriptional regulation was discovered: histone acetylation levels increased by 1.8-2.2 times; DNA methylation levels decreased by 25-35%; and epigenetic modifications in the promoter regions of metabolic-related genes changed significantly.

[0168] The experimental data of these systems fully confirm the reliability and innovation of the method of the present invention, and provide a new strategy for the treatment of colorectal cancer.

[0169] The above description is only an embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A CRISPR screening method for regulating the glucose metabolism remodeling of colorectal cancer by the RUSC1-AS1 / miR424 / FASN axis, characterized in that: The following steps are involved: (1) Construction of sgRNA expression vectors targeting RUSC1-AS1, miR424, and FASN; (2) transfecting the sgRNA expression vector into packaging cells to obtain lentiviral particles; (3) using the lentiviral particles to infect a colorectal cancer cell line to obtain a gene-edited cell line; (4) extracting metabolites of the gene-edited cell line and performing LC-MS / MS analysis; (5) extracting RNA from the gene-edited cell line and performing transcriptome sequencing; (6) Performing bioinformatics analysis on the LC-MS / MS analysis results and the transcriptome sequencing results.

2. The screening method according to claim 1, characterized in that The sgRNA expression vector in step (1) is a lentiCRISPRv2 vector, and the sgRNA sequence includes: The sgRNA sequences targeting RUSC1-AS1 are SEQ ID NO. 1-4; The sgRNA sequences targeting miR424 are SEQ ID NO. 5-7; The sgRNA sequences targeting FASN are SEQ ID NO.8-11.

3. The screening method according to claim 1, characterized in that The packaging cells in step (2) are 293T cells, and the packaging process of the lentiviral particles includes: The sgRNA expression vector was co-transfected with psPAX2 and pMD2.G at a mass ratio of 4:3:1 into the 293T cells; After 48-72 hours of culture, collect the viral supernatant; The virus was concentrated by centrifugation at 25,000 g for 2 h.

4. The screening method according to claim 1, characterized in that The colorectal cancer cell lines in step (3) are HCT116 and SW480 cell lines, and the infection process includes: Infecting the colorectal cancer cell line with the lentiviral particles having an MOI value of 0.8; Add polybrene to a final concentration of 8 μg / mL; Infection was centrifuged at 1200 g for 2 h; Use puromycin selection for 7-10 days.

5. The screening method according to claim 1, characterized in that The conditions for LC-MS / MS analysis in step (4) include: Chromatographic column: ACQUITY UPLC BEHAmide (2.1×100mm, 1.7μm); Mobile phase: water + 0.1% formic acid and acetonitrile + 0.1% formic acid; Mass spectrometry conditions: ESI source, MRM mode.

6. The screening method according to claim 1, characterized in that The transcriptome sequencing described in step (5) uses Ultra TM The library was constructed using II RNA Library Prep Kit, and the sequencing platform was Illumina NovaSeq6000.

7. The screening method according to claim 1, characterized in that The bioinformatics analysis in step (6) includes: Metabolomics data analysis: performing peak identification, peak alignment, area integration, and retention time correction; Transcriptome data analysis: perform raw data filtering, sequence alignment, and differential expression analysis.

8. The screening method according to claim 7, characterized in that The screening criteria for differential metabolites in the metabolomics data analysis were p<0.05 and |FC|>2.

0.

9. The screening method according to claim 7, characterized in that The screening criteria for differentially expressed genes in the transcriptome data analysis were p<0.05 and |log2FC|>1.

10. The screening method according to any one of claims 1 to 9, characterized in that: Steps to validate the screening results using qPCR and Western blot are also included.

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