Nucleic acid interference pharmaceutical composition and medicine for treating colorectal cancer, gastric cancer and prostate cancer

Abstract

The present invention discloses a nucleic acid interference pharmaceutical composition and a drug for treating colorectal cancer, gastric cancer and prostate cancer. The present invention targets two targets (TGF-β1 and MyD88) related to the tumor microenvironment and tumor metastasis of colorectal cancer, gastric cancer and prostate cancer, designs and screens out a dual-target MyD88 / TGF-β1 nucleic acid interference pharmaceutical composition (composition number STP500), which includes an active ingredient and a pharmaceutically acceptable carrier, and the active ingredient includes a first active ingredient capable of inhibiting and silencing MyD88 gene expression and a second active ingredient capable of inhibiting and silencing TGF-β1 gene expression. In vitro and in vivo experiments show that the dual-target MyD88 / TGF-β1 nucleic acid interference pharmaceutical composition of the present invention can effectively inhibit the growth of colorectal cancer, gastric cancer and prostate cancer tumor cells, and has potential application prospects in the treatment of colorectal cancer, gastric cancer and prostate cancer.

Description

Technical Field

[0001] The present invention relates to the field of biomedicine technology, and in particular to a nucleic acid interference pharmaceutical composition and a drug for treating colorectal cancer, gastric cancer and prostate cancer. Background Art

[0002] According to data from the World Health Organization (WHO) (https: / / gco.iarc.fr / ), the top five new cancer incidence rates in the world in 2020 were breast cancer (11.7%), lung cancer (11.4%), colorectal cancer (10%), prostate cancer (7.3%) and stomach cancer (5.6%); the top five mortality rates were lung cancer (18%), colorectal cancer (9.4%), liver cancer (8.3%), stomach cancer (7.7%) and breast cancer (6.9%).

[0003] Colorectal cancer has a high incidence in my country and ranks third among all malignant tumors worldwide. The main cause of death is cancer invasion and metastasis. Due to the lack of early diagnosis and effective screening methods, most patients are diagnosed at an advanced or locally advanced stage, resulting in a poor prognosis. Tumor metastasis involves multiple, multi-stage steps, involving numerous genes and a complex process. For example, tumor cells detach from the primary site and fuse with the surrounding stroma. Tumor cells enter the circulatory and lymphatic systems, adhere to the endothelial cell wall, and gradually spread to blood vessels or larger areas, causing angiogenesis and ultimately the formation of new metastases. The gastrointestinal system possesses the largest and most complex microbiome in the human body. Gastrointestinal cancer ranks among the top five cancers in terms of both morbidity and mortality. Treatment of this type of cancer is extremely challenging, requiring both maintaining the highly complex and dynamic microbial balance of the gastrointestinal tract and eradicating cancer cells. A recent study showed that cachexia-prone patients with gastrointestinal cancer begin experiencing significant weight loss at least six months before diagnosis; regardless of pre-diagnosis weight change or disease stage, most gastrointestinal cancer patients develop cachexia upon diagnosis. Current treatment options for gastrointestinal tumors are limited. According to the 2021 Guidelines for the Diagnosis and Treatment of Colorectal Cancer (CSCO), the current treatment for colorectal cancer is still primarily based on traditional surgical treatment, combined with adjuvant chemotherapy and monoclonal antibody therapy (such as cetuximab (targeting EGFR) and bevacizumab (targeting VEGF)). For patients with postoperative recurrence, only chemotherapy with oxaliplatin or palliative care can be used. The current primary treatment strategy for gastric cancer is comprehensive therapy, primarily surgical resection. Although surgical and chemotherapy regimens have improved, the prognosis for gastric cancer patients remains poor. While some immune checkpoint or targeted drugs, such as those targeting PD-1 / PD-L1, HER2, EGFR, and CLDN18.2, are undergoing clinical trials, many uncertainties remain. There is currently no better dual-target combined targeted therapy, so new treatments are urgently needed to fill the gap.

[0004] Prostate cancer is one of the most common malignant tumors of the male genitourinary system. In 2020, its global incidence ranked fourth, after breast cancer, lung cancer, and colorectal cancer. According to the 2015 malignant tumor morbidity and mortality data released by the National Cancer Center of my country in 2019, prostate cancer ranked sixth and tenth, respectively. Its etiology involves multiple factors, including genetics, age, and excessive alcohol intake. Currently, there are no clear medications or dietary interventions to prevent prostate cancer. Common prostate cancer pathological types include adenocarcinoma, intraductal carcinoma, ductal adenocarcinoma, urothelial carcinoma, squamous cell carcinoma, and basal cell carcinoma, among others. Prostate adenocarcinoma accounts for the majority of these types, and the term "prostate cancer" often refers to prostate adenocarcinoma. Currently, primary treatment options are limited to radical surgical resection, radical external beam radiotherapy, surgical or medical castration, combined chemotherapy or other combined treatments, and castration combined with new endocrine drugs. There are no effective first-line targeted drugs, immunotherapies, or new nucleic acid-based drugs.

[0005] Small nucleic acid drugs have inherent advantages over small molecule drugs and antibody drugs, and are expected to treat many diseases that are not treatable with traditional small molecule and antibody drugs. Currently, there are five marketed nucleic acid interference drugs, including Onpattro (Patisiran), Givlaari (Givosiran), Oxlumo (Lumasiran), and Amvuttra (Vutrisiran) from Alnylam in the United States, and Leqvio (Inclisiran) from Novartis in Switzerland. Onpattro (Patisiran) is the world's first siRNA small nucleic acid drug. It was approved by the United States and the European Union in August 2018 for the treatment of Phase 1 or Phase 2 polyneuropathy in adult patients with hereditary ATTR (hATTR) amyloidosis; on February 21, 2023, Alnylam announced that the FDA has accepted Patisiran's new indication application for the treatment of transthyretin-mediated amyloid cardiomyopathy; Givlaari (Givosiran) was approved in November 2019 for the treatment of adolescents and adults aged 12 years and above with acute hepatic porphyria (AHP); Oxlumo (Lumasiran) was approved by the FDA in November 2020 for the treatment of patients with primary hyperoxaluria type I (PH1) of all ages; Leqvio (Inclisiran) was approved by the European Commission in December 2020 for the treatment of hypercholesterolemia and mixed dyslipidemia in adults. In September 2022, the European Commission approved Amvuttra (Vutrisiran) for marketing, for subcutaneous injection once every three months, for the treatment of stage 1 and 2 polyneuropathy in adult patients with hereditary transthyretin (hATTR)-mediated amyloidosis. Although small nucleic acids hold broad application prospects in drug development, their development and application are hampered by inherent limitations and technical bottlenecks, such as susceptibility to degradation, interferon reactivity, off-target effects, weak penetration, and the lack of suitable drug delivery systems. Consequently, no nucleic acid interference drug targeting cancer has yet been developed. Once these challenges are overcome, the field of nucleic acid drugs will usher in tremendous opportunities and a vast market.

[0006] Targeting cancers with high incidence, developing nucleic acid drugs that can treat one or more of these cancers is a current research focus and has huge potential application prospects. Summary of the Invention

[0007] The purpose of the present invention is to provide a nucleic acid interference pharmaceutical composition capable of inhibiting the growth of at least one of colorectal cancer cells, gastric cancer cells and prostate cancer cells.

[0008] Another object of the present invention is to provide a drug for treating colorectal cancer and / or gastric cancer and / or prostate cancer.

[0009] In order to achieve the above object, the technical solution adopted by the present invention is:

[0010] A nucleic acid interference pharmaceutical composition comprises active ingredients and a pharmaceutically acceptable carrier, wherein the active ingredients comprise a first active ingredient capable of inhibiting and silencing MyD88 gene expression and a second active ingredient capable of inhibiting and silencing TGF-β1 gene expression.

[0011] Specifically, the first active ingredient is one or more of siRNA molecules, miRNA molecules or antisense oligonucleotide molecules that can bind to the mRNA encoding the MyD88 protein and inhibit its expression.

[0012] Specifically, the second active ingredient is one or more of siRNA molecules, miRNA molecules or antisense oligonucleotide molecules that can bind to the mRNA encoding TGF-β1 protein and inhibit its expression.

[0013] Preferably, the present invention provides a TGF-β1 / MyD88 dual-target nucleic acid interference pharmaceutical composition, which comprises an active ingredient and a pharmaceutically acceptable carrier, wherein the active ingredient consists of a first active ingredient capable of inhibiting and silencing MyD88 gene expression and a second active ingredient capable of inhibiting and silencing TGF-β1 gene expression.

[0014] Furthermore, the active ingredient consists of siRNA molecules targeting the MyD88 gene and siRNA molecules targeting the TGF-β1 gene.

[0015] Preferably, the siRNA molecule targeting the MyD88 gene is an oligonucleotide having a chain length of 17 to 28 base pairs, for example, the siRNA molecule has a chain length of 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27 or 28 base pairs.

[0016] Preferably, the siRNA molecule targeting the TGF-β1 gene is an oligonucleotide with a chain length of 17 to 28 base pairs, for example, the siRNA molecule has a chain length of 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27 or 28 base pairs.

[0017] According to some embodiments, the first active ingredient is a siRNA molecule targeting the MyD88 gene, which includes one or more groups of the following oligonucleotides:

[0018] Justice chain: CGUUGUAGGAGGAAUCUGUdTdT,

[0019] Antisense strand: ACAGAUUCCUCCUACAACGdTdT;

[0020] Justice chain: GAGGAAUCUGUGCUCUACUdTdT,

[0021] Antisense strand: AGUAGAGCACAGAUUCCUCdTdT;

[0022] Justice chain: GGAAUCUGUGCUCUACUUAdTdT,

[0023] Antisense strand: UAAGUAGAGCACAGAUUCCdTdT;

[0024] Justice chain: GCUCUACUUACCUCUCAAUdTdT,

[0025] Antisense strand: AUUGAGAGGUAAGUAGAGCdTdT;

[0026] Justice chain: GCAUACACACGUUUUUCUAdTdT,

[0027] Antisense strand: UAGAAAAACGUGUGUAUGCdTdT;

[0028] Justice chain: CCCAAUGUACCAGUAUUUAdTdT,

[0029] Antisense strand: UAAAUACUGGUACAUUGGGdTdT;

[0030] Justice chain: GCUUAAACUCACACAACAAdTdT,

[0031] Antisense strand: UUGUUGUGUGAGUUUAAGCdTdT;

[0032] Justice chain: GACCCUAAAUCCAAUAGAAdTdT,

[0033] Antisense strand: UUCUAUUGGAUUUAGGGUCdTdT;

[0034] Justice chain: CUUGUUGAGGCAUUUAGCUdTdT,

[0035] Antisense strand: AGCUAAAUGCCUCAACAAGdTdT;

[0036] Justice chain: GGCAUCUUCUACAUGUUUUdTdT,

[0037] Antisense strand: AAAACAUGUAGAAGAUGCCdTdT;

[0038] Justice chain: CUGAGAAAAGCCGAUAUUUdTdT,

[0039] Antisense strand: AAAUAUCGGCUUUUCUCAGdTdT;

[0040] Justice chain: GAGAAGCCUUUACAGGUGGdTdT,

[0041] Antisense strand: CCACCUGUAAAGGCUUCUCdTdT;

[0042] Justice chain: AGGAGAUGAUCCGGCAACUdTdT,

[0043] Antisense strand: AGUUGCCGGAUCAUCUCCUdTdT;

[0044] Justice chain: CAGAGCAAGGAAUGUGACUdTdT,

[0045] Antisense strand: AGUCACAUUCCUUGCUCUGdTdT;

[0046] Justice chain: GCAAGGAAUGUGACUUCCAdTdT,

[0047] Antisense strand: UGGAAGUCACAUUCCUUGCdTdT;

[0048] Justice chain: GAAUGUGACUUCCAGACCAdTdT,

[0049] Antisense strand: UGGUCUGGAAGUCACAUUCdTdT;

[0050] and / or,

[0051] The second active ingredient is a siRNA molecule targeting the TGF-β1 gene, which includes one or more groups of the following oligonucleotides:

[0052] Justice chain: CCCAAGGGCUACCAUGCCAACUUCU,

[0053] Antisense strand: AGAAGUUGGCAUGGUAGCCCUUGGG;

[0054] Justice chain: AACUAUUGCUUCAGCUCCAdTdT,

[0055] Antisense strand: UGGAGCUGAAGCAAUAGUUdTdT;

[0056] Justice chain: GCAGAGUACACACAGCAUAdTdT,

[0057] Antisense strand: UAUGCUGUGUGUACUCUGCdTdT.

[0058] Preferably, the carrier is one or more of a polycationic binder, a cationic liposome, a cationic micelle, a cationic polypeptide, a cationic polyacetal, a grafted hydrophilic polymer, a polysaccharide molecule, a multivesicular body, an antibody, a polypeptide molecule or a nucleic acid aptamer.

[0059] According to some embodiments, the carrier is a pharmaceutically acceptable histidine-lysine polymer.

[0060] More preferably, the carrier is an H3K4b-type histidine-lysine polymer.

[0061] According to some embodiments, the carrier is HKP or HKP(+H).

[0062] The present invention also provides use of the nucleic acid interference pharmaceutical composition in preparing a drug for preventing and treating colorectal cancer and / or gastric cancer and / or prostate cancer.

[0063] The present invention also provides a medicine for treating colorectal cancer and / or gastric cancer and / or prostate cancer, which comprises the nucleic acid interference pharmaceutical composition.

[0064] Preferably, the mass ratio of the first active ingredient to the second active ingredient is 1:0.8 to 1.2, for example, 1:0.8, 1:0.9, 1:1, 1:1.1, or 1:1.2.

[0065] According to some embodiments, the mass ratio of the siRNA molecule targeting the MyD88 gene to the siRNA molecule targeting the TGF-β1 gene is 1:0.8-1.2.

[0066] Preferably, the N / P ratio of the carrier and the active ingredient is 2 / 1 to 6 / 1, for example, 2 / 1, 3 / 1, 4 / 1, 5 / 1, or 6 / 1.

[0067] Preferably, the colorectal cancer includes adenocarcinoma, adenosquamous carcinoma and undifferentiated carcinoma.

[0068] Preferably, the gastric cancer includes adenocarcinoma, signet ring cell carcinoma, adenosquamous carcinoma, medullary carcinoma, carcinoid and undifferentiated cell carcinoma.

[0069] Preferably, the prostate cancer includes adenocarcinoma, intraductal carcinoma, ductal adenocarcinoma, urothelial carcinoma, squamous cell carcinoma, and basal cell carcinoma.

[0070] Preferably, the drug is a nanoparticle.

[0071] Furthermore, the size of the nanoparticles is 50 to 200 nm, for example, 50 nm, 55 nm, 60 nm, 65 nm, 70 nm, 75 nm, 80 nm, 85 nm, 90 nm, 95 nm, 100 nm, 105 nm, 110 nm, 115 nm, 120 nm, 125 nm, 130 nm, 135 nm, 140 nm, 145 nm, 150 nm, 155 nm, 160 nm, 165 nm, 170 nm, 175 nm, 180 nm, 185 nm, 190 nm, 195 nm, and 200 nm.

[0072] According to a specific embodiment, the drug is STP500, wherein the siRNA molecule targeting the MyD88 gene is:

[0073] Sense strand: GAAUGUGACUUCCAGACCAdTdT;

[0074] Antisense strand: UGGUCUGGAAGUCACAUUCdTdT,

[0075] The siRNA molecules targeting the TGF-β1 gene are:

[0076] Justice chain: CCCAAGGGCUACCAUGCCAACUUCU;

[0077] Antisense strand: AGAAGUUGGCAUGGUAGCCCUUGGG,

[0078] The carrier is HKP(+H).

[0079] Preferably, the drug is administered by subcutaneous injection and / or intravenous injection.

[0080] Preferably, the subject of administration of the drug is a mammal.

[0081] Due to the use of the above technical solution, the present invention has the following advantages compared with the prior art:

[0082] The present invention targets two targets (TGF-β1 and MyD88) related to the tumor microenvironment and tumor metastasis of colorectal cancer, gastric cancer or prostate cancer, designs and screens a dual-target MyD88 / TGF-β1 combined nucleic acid interference drug composition. In vivo experiments show that it can effectively inhibit the growth of colorectal cancer, gastric cancer or prostate cancer cells, and has great application prospects in the treatment of colorectal cancer, gastric cancer or prostate cancer. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 Schematic diagram of the MyD88-Toll-like receptor signaling pathway;

[0084] Figure 2 is the expression of MyD88 gene in cell lines;

[0085] Figure 3 is the knockdown effect of MyD88 siRNA on the expression level of target gene MyD88 mRNA;

[0086] Figure 4 EC50 data (the concentration of siRNA that achieves half the effective knockdown effect) of candidate MyD88 siRNA;

[0087] Figure 5 The knockdown effect of candidate MyD88 siRNA and combined TGF-β1 siRNA on target gene protein levels in cell lines;

[0088] Figure 6 In vitro cell scratch assay for candidate MyD88 siRNA;

[0089] Figure 7 The effect of candidate siRNA on the secretion of cytokine IL-6 at the cellular level;

[0090] Figure 8 Preparation of candidate MyD88 siRNA and combined TGF-β1 siRNA formulations;

[0091] Figure 9 The results show that the candidate MyD88 siRNA and the combined TGF-β1 siRNA inhibited the growth of subcutaneous transplanted tumors in mice with colorectal cancer cells (MC38) (A: tumor growth curves of each group in the MC38 cell subcutaneous transplanted tumor model, B: tumor weight statistics of each group in the MC38 cell subcutaneous transplanted tumor model, C: tumor photos of each group in the MC38 cell subcutaneous transplanted tumor model, D: tumor weight statistics of each group in the MC38 cell subcutaneous transplanted tumor model);

[0092] Figure 10The inhibitory effect of the drug candidate STP500 on the growth of subcutaneous xenograft tumors of human gastric cancer cells (MKN45) (A: Tumor growth curves of each group in the MKN45 cell subcutaneous xenograft model, B: Body weight change curves of each group in the MKN45 cell subcutaneous xenograft model, C: Tumor photos of each group in the MKN45 cell subcutaneous xenograft model, D: Tumor weight statistics of each group in the MKN45 cell subcutaneous xenograft model);

[0093] Figure 11 The inhibitory effect of the drug candidate STP500 on the growth of subcutaneous xenografts of mouse prostate cancer cells (RM-1); (A: Tumor growth curves of each group in the RM-1 cell subcutaneous xenograft model; B: Body weight change curves of each group in the RM-1 cell subcutaneous xenograft model; C: Tumor photos of each group in the RM-1 cell subcutaneous xenograft model; D: Tumor weight statistics of each group in the RM-1 cell subcutaneous xenograft model);

[0094] Figure 12 The inhibitory effect of the drug candidate STP500 on the growth of subcutaneous transplanted tumors of mouse colorectal cancer cells (MC38), and the comparison of transcriptome analysis data (A: tumor growth curves of each group in the MC38 cell subcutaneous transplanted tumor model, B: survival rate curves of each group in the MC38 cell subcutaneous transplanted tumor model, C: transcriptome data of the MC38 cell subcutaneous transplanted tumor model, up-regulated / down-regulated genes in the drug-treated group (STP500) versus the control group (NC) (volcano plot), D: transcriptome data of the MC38 cell subcutaneous transplanted tumor model, up-regulated / down-regulated genes in the drug-treated group (STP500) versus the control group (NC) (heat map)). DETAILED DESCRIPTION

[0095] The present invention is further described below with reference to the following examples. However, the present invention is not limited to the following examples. The implementation conditions used in the examples may be further adjusted according to the specific requirements of the application. Unspecified implementation conditions are conventional conditions in the industry. The technical features involved in the various embodiments of the present invention may be combined with each other as long as they do not conflict with each other.

[0096] Myeloid Differentiation Factor 88 (MyD88) is a key adaptor molecule in the Toll-like receptor (TLR) signaling pathway, playing a role in the signaling pathways of all TLRs except TLR3. MyD88 plays a crucial role in transmitting upstream information, in the development and progression of diseases, and in mediating innate immune responses. The TLR family is the most studied pattern recognition receptor (PRR), specifically recognizing pathogen-associated molecular patterns (PAMPs) to transmit signals into cells and regulate downstream signaling cascades. MyD88 is located on the short arm of chromosome 3. Multiple studies have found that the most common point mutation is the replacement of leucine (Leu) with proline (Pro) at position 265, known as the MYD88 L265P mutation. This mutation leads to abnormal activation of downstream signaling pathways such as NF-κB. In addition to the NF-κB pathway, MyD88 also regulates multiple key downstream molecules through the TLR family, such as mitogen-activated protein kinase (MAPK), Janus kinase and transcription factor 3 (Jak-Stat3), to regulate immune cells, cytokines (such as IL-6, TNF-α, IL-1β, etc.) and chemokines, thereby affecting the tumor microenvironment. Figure 1 , Image source: https: / / doi.org / 10.1007 / s11523-018-0589-7).

[0097] Currently, studies by Zhang J. et al. in mouse models have demonstrated that MyD88 in myofibroblasts promotes osteopontin (OPN) secretion and M2 polarization of macrophages, leading to activation of the STAT3 / PPARγ signaling pathway and the development of colorectal cancer (CRC). Another study demonstrated that direct administration of the MyD88 inhibitor TJ-M2010-5 prevented the development of colitis-associated CRC by impairing myeloid-derived suppressor cells (MDSCs), suggesting that the MyD88 signaling pathway is involved in regulating the immunosuppressive function of MDSCs. Furthermore, many researchers believe that MyD88 plays a dual role in the development and progression of CRC: a) by enhancing cancer inflammation and intestinal microbiota imbalance, inducing tumor invasion and tumor cell self-renewal, thereby promoting tumor growth; and b) by maintaining host-microbiota homeostasis, thereby inducing tumor cell cycle arrest and immune responses against cancer cells, resulting in anti-tumor effects. TLR / IL-1R signaling has also been shown to play a key role in intestinal homeostasis, intestinal inflammation, and colitis-related tumorigenesis by maintaining microbial tolerance in the colonic epithelium. The MyD88 protein acts as a bridge between TLR / IL-1R inflammation and the Ras signaling pathway. Activation of the MyD88 / TLR / IL-1R signaling pathway leads to Ras / ERK activation and promotes tumor cell proliferation. Based on this, the inventors conducted a series of preliminary experiments to confirm that MyD88 is a potential target for the treatment of colorectal cancer.

[0098] The transforming growth factor-β (TGF-β) signaling pathway plays a key role in the growth, development, and differentiation of cells and tissues through a series of signaling processes it mediates. It plays a crucial role in regulating cell proliferation, extracellular matrix production, differentiation, apoptosis, embryonic development, organ formation, immune function, inflammatory responses, and wound repair. Currently, 33 TGF-β family proteins are known to exist in humans, including three TGF-βs (TGF-β1 / 2 / 3), 10 bone morphogenetic proteins (BMPs), 11 growth and differentiation factors (GDFs), as well as activins, nodals, and inhibins. In cancer cells, the TGF-β signaling pathway is involved in regulating multiple cellular functions, including cell cycle progression, apoptosis, adhesion, and differentiation. In the late stages of tumor development, TGF-β promotes cell proliferation, induces angiogenesis, and suppresses immune responses within the tumor microenvironment. As an immunosuppressive cytokine, TGF-β inhibits the development, proliferation, and activation of immune cells, including T cells (CD4 + Effector T cells and CD8 + TGF-β also stimulates the proliferation of regulatory T cells (Tregs), which in turn inhibit the activation of effector T cells, NK cells, and macrophages. This suggests that TGF-β, by suppressing the innate and adaptive immune systems, creates an immune-tolerant microenvironment that favors tumor development and enhances the ability of cancer cells to migrate and invade adjacent tissues, promoting tumor metastasis.

[0099] In summary, the TGF-β1 signaling pathway is intricately linked to tumorigenesis and metastasis, while the MyD88 protein is a key molecule connecting upstream inflammatory signaling pathways such as the TLR family and the cancer RAS pathway. Currently, there are no studies investigating the combined use of these two pathways for the treatment of gastrointestinal and prostate cancers. The inventors believe that the development of a dual-target drug that effectively targets both TGF-β1 and MyD88 would have significant potential in the treatment of colorectal, gastric, and prostate cancers.

[0100] Therefore, after a lot of research and experimental verification, the inventors found that the combination of TGF-β1 target and MyD88 target has a positive effect on inhibiting the growth of colorectal cancer cells, gastric cancer cells and prostate cancer cells compared with the use of MyD88 target alone or the combination of MyD88 target with other targets. They then proposed a dual-target nucleic acid interference drug composition that can simultaneously target the tumor microenvironment target (MyD88) and the tumor transformation and metastasis-related target (TGF-β1). After a large number of in vivo experiments, it was verified that the dual-target nucleic acid interference drug composition performed well in the treatment of rectal cancer, gastric cancer and prostate cancer and was safer, and has great application prospects.

[0101] Specifically, the nucleic acid interference pharmaceutical composition provided by the present invention includes active ingredients and pharmaceutically acceptable carriers, wherein the active ingredients include a first active ingredient capable of inhibiting and silencing MyD88 gene expression and a second active ingredient capable of inhibiting and silencing TGF-β1 gene expression.

[0102] Wherein, the first active ingredient is one or more of siRNA molecules, miRNA molecules or antisense oligonucleotide molecules that can bind to the mRNA encoding the MyD88 protein and inhibit its expression.

[0103] The second active ingredient is one or more of siRNA molecules, miRNA molecules or antisense oligonucleotide molecules that can bind to the mRNA encoding TGF-β1 protein and inhibit its expression.

[0104] RNA interference (RNAi) is a potent gene silencing process ubiquitous in the biological world, occurring extensively within eukaryotic cells, including plants and animals. RNAi refers to the phenomenon in which double-stranded RNA (dsRNA) is introduced into cells, causing mRNA degradation, thereby leading to specific gene silencing of genes with sequence homology. When exogenous genes, such as transposons, artificially introduced genes, and viral genes, are randomly integrated into the host cell genome and transcribed by the host cell, they often produce dsRNA, typically larger than 30 base pairs. Host cells rapidly respond to these dsRNAs, cleaving endogenous or exogenous dsRNAs into small double-stranded fragments of 21 to 23 base pairs in length by specific ribonucleases (Dicer). These small double-stranded fragments are called small interfering RNAs (siRNAs). The double-stranded siRNA can be linked to the RNA-induced Silencing Complex (RISC). After binding to RISC, it targets and cuts specific mRNA, thereby interrupting the translation process of specific mRNA and inhibiting and silencing the expression of the target gene.

[0105] Unlike siRNA, mature microRNA (miRNA) is a single-stranded RNA. Pri-miRNA (primary miRNA) is processed in the cell nucleus to produce pre-miRNA (precursor miRNA). Exportin-5 protein then transports the pre-miRNA from the nucleus to the cytoplasm, where it is processed by the RNase III enzyme Dicer into mature miRNA. In vivo, miRNA degrades target gene mRNA, regulating its transcriptional level without affecting mRNA stability. Its mRNA binding specificity is lower than that of siRNA.

[0106] Antisense oligonucleotides (ASOs) are single-stranded DNA molecules that bind to target gene mRNA through the principle of base complementarity, and then block protein translation through steric hindrance, or cause mRNA degradation through RNase H cleavage, or change pre-mRNA splicing by interfering with cis-splicing elements, ultimately blocking the expression of the target gene.

[0107] According to an embodiment, the active ingredient includes siRNA molecules targeting MyD88 gene and siRNA molecules targeting TGF-β1 gene.

[0108] Among them, the siRNA sequence targeting the MyD88 gene can theoretically bind to and degrade MyD88 mRNA in target cells through the RNAi mechanism, thereby blocking the translation level of its protein and inhibiting the protein expression of MyD88.

[0109] The siRNA sequence targeting the TGF-β1 gene can theoretically bind to and degrade TGF-β1 mRNA in target cells through the RNAi mechanism, thereby blocking the translation level of the protein and inhibiting the protein expression of TGF-β1.

[0110] The present invention adopts a specific algorithm and programming containing several parameter conditions to design a series of siRNA sequences for the target genes TGF-β1 and MyD88. The siRNA molecules targeting the MyD88 gene and the siRNA molecules targeting the TGF-β1 gene are oligonucleotide sequences with a length of 19 to 25 base pairs, respectively.

[0111] Preferably, the lengths of the siRNA molecules targeting the MyD88 gene and the siRNA molecules targeting the TGF-β1 gene are 21 to 25 base pairs, respectively.

[0112] The main limitation of nucleic acid interference drugs in clinical application is the need for an effective transport carrier (called an introduction / delivery system). This delivery system must be able to effectively protect and transport its cargo. After reaching the outside of the target cell, it must also be able to cross the cytoplasmic membrane and finally enter the cytoplasm to enable the active ingredients of the nucleic acid interference drug to exert their effects. Currently, there are many delivery systems for targeted or enhanced delivery of small nucleic acid drugs, such as polycationic binders, cationic liposomes, cationic micelles, cationic polypeptides, cationic polyacetals, grafted hydrophilic polymers, polysaccharide molecules (forming polysaccharide-RNA monoconjugates with RNA molecules), multivesicular bodies, antibodies, polypeptide molecules (self-assembled to form polypeptide nanoparticle carrier introduction systems), nucleic acid aptamers, etc.

[0113] According to the embodiments, the present invention uses a polypeptide nanoparticle carrier delivery system for which the applicant has independent intellectual property rights, a histidine-lysine-rich polypeptide delivery system, for details see patent: Compositions and methods of controllable coupled polypeptide nanoparticle delivery systems for nucleic acid therapy (patent number: CN 112703196 A).

[0114] Specifically, the delivery vector is HKP or HKP(+H).

[0115] Specifically, siRNA molecules targeting the MyD88 gene and siRNA molecules targeting the TGF-β1 gene were encapsulated into HKP or HKP+H (histidine-lysine polymer) carriers through peptide nanoparticle (PNP) technology to prepare nanoparticle preparations.

[0116] Specifically, the feeding mass ratio of the siRNA molecule targeting the MyD88 gene to the siRNA molecule targeting the TGF-β1 gene is 1:0.8-1.2, and the N / P ratio of the carrier to the active ingredient is 2 / 1-4 / 1.

[0117] The present invention uses PNP technology to encapsulate and introduce siRNA that jointly targets MyD88 (MD8) and TGF-β1 (TF1). The combined use can significantly inhibit the growth of colorectal cancer, gastric cancer and prostate cancer, and shows potential application prospects in the treatment of colorectal cancer, gastric cancer and prostate cancer.

[0118] The technical solutions and effects of the present invention are described in detail below through examples.

[0119] Example 1:

[0120] Design of siRNA sequences for two targets (MyD88 and TGF-β1)

[0121] Using a specific algorithm and programming with several parameters, we designed a series of siRNA sequences targeting the target genes TGF-β1 and MyD88, including oligonucleotides of 25 and 21 base pairs in length. Table 1 lists the siRNA sequences targeting TGF-β1 and MyD88. Characteristics of these sequences include, but are not limited to, targeting gene coding sequences, reasonable thermodynamic stability, and low expected toxic side effects.

[0122] Among them, the siRNA sequence targeting the MyD88 gene can theoretically bind to and degrade MyD88 mRNA in target cells through the RNAi mechanism, thereby downregulating the protein expression of MyD88.

[0123] Among them, the siRNA sequence targeting the TGF-β1 gene can theoretically bind to and degrade TGF-β1 mRNA in target cells through the RNAi mechanism, thereby downregulating the protein expression of TGF-β1.

[0124] Table 1. Candidate MyD88 siRNAs for related experiments, combined with TGF-β1 siRNA sequences and other control group siRNA sequences

[0125]

[0126]

[0127] Example 2:

[0128] In vitro screening of MyD88 gene expression in cell lines

[0129] The expression of MyD88 gene was identified by RT-PCR in a variety of human and mouse cell lines. The expression results of MyD88 gene in cell lines are shown in Figure 2 The selected cell lines include human (Homo): U87-MG, T98G, MKN-45, BxPC3, RKO, DLD-1, SW480, HCT116, MDA-MB-231; mouse (Mus): L1210, Raw264.7, PANC02, MC38, 4T1, RM-1, Renca.

[0130] according to Figure 2 The data were collected and candidate cell lines with Ct values ​​between 20 and 25 were selected for subsequent in vitro screening (cell level), including breast cancer cell line (MDA-MB-231), glioma cell line (U87-MG), human brain glioma cell line (T98G), human colorectal cancer epithelial cell line (DLD-1) and human colon cancer cell line (RKO).

[0131] Example 3:

[0132] In vitro screening of siRNA sequences targeting the MyD88 gene (cellular level)

[0133] The siRNA sequences shown in Table 1 were carried and transfected into cells using a commercial cell transfection reagent (Lipo2000). After the transfected cells were cultured for 24 hours, a series of in vitro cell-level experimental methods (including QRT-PCR, cell proliferation activity, and protein expression level detection such as WB) were used to screen the siRNA sequences selected in Example 2 at the cell level. The general process includes: (1) initial screening of siRNA sequences; (2) EC50 (concentration with half effective target gene knockdown) detection, and finally confirming the candidate siRNA sequences that can be used for in vivo pharmacodynamic studies. The candidate cell lines selected in Example 2 were selected for in vitro siRNA screening, including breast cancer cell line (MDA-MB-231), glioma cell line (U87-MG), human brain glioma cell line (T98G), human colorectal cancer epithelial cell line (DLD-1), and human colon cancer cell line (RKO). The initial screening of the sequences and the detection of EC50 were both performed using RT-PCR technology to detect the mRNA expression level of the target gene.

[0134] RT-PCR technology was used to detect the knockdown of MyD88 mRNA expression level by MyD88 siRNA. The results are shown in Figure 3 Based on the test results, the candidate sequences screened were numbered: MD8-21-hm3#, MD8-21-hm4#, MD8-21-hm5#, and MD8-21-h5#. Considering the use of subsequent in vivo animal experiments, the human-mouse homologous (hm) sequences MD8-21-hm3# (KD = 88%), MD8-21-hm4# (KD = 86%), and MD8-21-hm5# (KD = 86%) were subsequently selected.

[0135] Afterwards, for these three candidate siRNA sequences, multiple concentration gradients were set for cell transfection to obtain their EC50 values. The results were ( Figure 4 ) showed that the EC50 of MD8-21-hm5# among the three candidate sequences in mouse prostate cancer (RM-1) cells and colorectal cancer (MC38) cells were all less than 10nM, namely 5.59nM and 7.41nM, respectively, and can be used as candidate sequences for in vivo experiments.

[0136] Example 4:

[0137] In vitro screening of siRNA sequences targeting TGF-β1 gene (cellular level)

[0138] Because TGF-β1 is a widely expressed target gene, only a few tumor cell lines were selected for in vitro cell-level screening. These included cholangiocarcinoma, breast cancer, lung cancer, pancreatic cancer, colorectal cancer, and glioma cells. The experimental methods used were the same as for MyD88. The TGF-β1 siRNA sequences shown in Table 1 are the candidate sequences obtained after screening.

[0139] Example 5:

[0140] Detection of knockdown effects of candidate siRNA sequences on target gene protein levels in in vitro cell lines

[0141] By Western Blot analysis, we completed the detection of siRNA sequence knockdown of target genes at the cellular level for TGF-β1 and MyD88. The specific method is as follows: one day before the experiment, cells were plated at 10 6Cells were seeded in 6-well plates and cultured overnight. The next day, siMD8 and siTF1 were transfected into the cells at doses of 100 nM and 10 nM, respectively. 48 hours after transfection, cells were collected into centrifuge tubes, and RIPA lysis buffer was added to each tube to extract total cellular protein. Total cellular protein concentration was then quantified using the BCA protein quantification method. All protein samples were then analyzed by Western blot using the following antibodies: MyD88 primary antibody (ab219413, 1:1000), TGF-β1 primary antibody (ab215715, 1:1000), and goat anti-rabbit IgG H&L (HRP) (ab205718, 1:10,000). At the conclusion of the experiment, images were captured using a chemiluminescence imaging system (ChemiDoc™ MP Imaging System, BIO-RAD).

[0142] Western Blot was used to detect the protein expression of candidate MyD88 siRNA (MD8-21-hm5#) combined with TGF-β1 siRNA (TF1-21-h1#) in human breast cancer cell line (MDA-MB-231), human colon cancer cell line (RKO) and mouse prostate cancer (RM-1) cells in vitro. Figure 5 The results showed that the candidate MyD88 siRNA (MD8-21-hm5#) had a significant knockdown effect in all three cell lines; TGF-β1 siRNA (TF1-21-h1#) had a significant knockdown effect in the RKO cell line; the candidate MyD88 siRNA (MD8-21-hm5#) combined with TGF-β1 siRNA (TF1-21-h1#) had a significant knockdown effect on the corresponding target proteins in all three cell lines.

[0143] Example 6:

[0144] In vitro detection of the effect of candidate siRNA on the migration ability of human colorectal cancer epithelial cell line DLD-1

[0145] One day before the experiment, take a 12-well plate and place the wound healing 2-hole plug (ibidi, 80209) in the center of the culture dish. 4The cells were inoculated into 2-well plugs and cultured overnight. The next day, siMD8 was transfected into the cells at doses of 100nM and 10nM to complete the transfection experiment. 24 hours after transfection, the wound healing 2-well plug was gently removed with tweezers (to avoid cell shedding), and culture medium containing 1% serum was added to the 12-well plate to continue culturing the cells. At the same time, photos were taken under a microscope as 0h cell migration data. Culture was continued for 24h and 96h, and cell migration was recorded under a microscope. Cell migration was judged by comparing the wound distance at the initial streak (0h) and the later observation points (24h and 96h). The experimental results showed that ( Figure 6 ), the candidate MyD88 siRNA single drug (MD8-21-hm5#) had a significant inhibitory effect on the in vitro migration ability of DLD-1 cells within 96 hours, and had a dose-dependent effect.

[0146] Example 7:

[0147] In vitro detection of the effect of candidate siRNA on the secretion of IL-6 cytokine in mouse prostate cancer cell line RM1

[0148] One day before the experiment, cells were plated at 1×10 5 The cells were seeded in a 24-well plate and cultured overnight. The next day, siMD8 and siTF1 were transfected into the cells at doses of 100nM and 10nM, respectively. 48 hours after transfection, the cell culture supernatant was taken for Elisa detection. The cell culture supernatant was centrifuged at 300×g for 10 minutes to remove the precipitate (usually no precipitate), and then tested immediately or aliquoted and stored at -20°C. The detection was performed with reference to the Mouse IL-6 ELISA Kit (Lianke Bio, EK206 / 3-96), with 2 replicates set for the standard sample and 3 replicates set for the experimental group. After the experiment was completed, the ELISACalc software was used to draw the standard curve and calculate the concentration of the experimental group. The results show ( Figure 7 ), IL-6 levels in RM-1 cells were significantly reduced 48 hours after transfection in the high-concentration single-drug and dual-drug groups. This result indicates that both siMD8 and siTF1 inhibit downstream IL-6 expression in a dose-dependent manner.

[0149] Example 8:

[0150] Preparation and identification of nanopharmaceutical preparations

[0151] Through in vitro screening, we completed the siRNA sequence screening work for the targets TGF-β1 and MyD88 at the cellular level. Then, we used the candidate siRNA sequences of the two targets to prepare nanoparticle preparations. In this example, MD8-21-hm5# and TF1-25-hm5# were mixed in a mass ratio of 1:1 and then formed into a stable nanoparticle preparation with a polypeptide carrier (HKP or HKP(+H)) (refer to patent CN 112703196 A). The prepared nanoparticle preparation was labeled STP500 and used for in vivo pharmacodynamic verification. In this example, the information on raw materials and preparation parameters is shown in Tables 2 and 3. The finished product is shown in Table 3. Figure 8 The upper picture is the lyophilized preparation (the left picture is the MyD88 siRNA preparation, and the right picture is the MyD88 siRNA+TGF-β1 siRNA preparation), and the lower picture is the reconstituted preparation (the left picture is the MyD88 siRNA preparation, and the right picture is the MyD88 siRNA+TGF-β1 siRNA preparation).

[0152] Table 2. Candidate MyD88 siRNAs for experiments related to this patent, and the preparation of MyD88 siRNA combined with TGF-β1 siRNA formulation (STP500).

[0153]

[0154] The N / P in the table is the N / P of the polypeptide vector and the siRNA raw material.

[0155] Table 3. Parameters of candidate MyD88 siRNAs and MyD88 siRNA combined with TGF-β1 siRNA formulations related to the experiments of this patent.

[0156]

[0157]

[0158] Example 9:

[0159] In vivo pharmacodynamics validation (colorectal cancer MC38 cell subcutaneous transplant tumor model in mice)

[0160] Based on previous in vitro experimental data, we mixed two siRNAs (MD8-21-hm5# and TF1-25-hm5# in this example) at a mass ratio of 1 / 1 and encapsulated them into a HKP(+H) (histidine-lysine polymer) carrier using patented PNP technology to prepare a nanoparticle preparation (the nanodrug preparation STP500 prepared in Example 8). The tumor growth inhibitory activity of the candidate siRNA sequence was verified using a mouse transplant tumor model (colorectal cancer cell MC38).

[0161] C57BL / 6 mice were subcutaneously inoculated with 1×10 6 MC38 cells, when the average tumor volume reached about 100mm 3 The mice were randomly divided into groups and the administration information was as follows: STP500, 2 mg / kg, administered intravenously via the tail vein, once every 2 days (Q2D); small nucleic acid single drug MD8 (MyD88 siRNA, also referred to as siMyD88), 1 mg / kg, administered intravenously via the tail vein, once every 2 days (Q2D); positive control group (Sorafenib), 30 mg / kg, administered orally via gavage, once a day (QD). After the first administration, the body weight and tumor volume of the mice were recorded every 2 days. The tumor volume was calculated as follows: V = 0.5 × (Dmax × Dmin 2 ). After the experiment, a tumor volume curve was drawn. The mice were euthanized and the tumors were removed and weighed. The tumor weight change rate TGItw (tumor weight change) was calculated using the formula:

[0162]

[0163] Mean TW treat: the mean tumor weight of mice in the treatment group at the end point of treatment;

[0164] Mean TW vehicle: the mean tumor weight of mice in the Vehicle group at the end point of treatment.

[0165] The experimental results are shown in Figure 9 The results showed that compared with the control group, after 8 doses, the MyD88 and TGF-β1 combined group (MD8+TF1) nanoparticle drug could significantly inhibit the growth of mouse colorectal cancer transplanted tumors (MC38 cell line), and the effect was better than other groups (MyD88 siRNA alone group (MD8)) and the positive control group (Sorafenib); and compared with the model group (Vehicle), the tumor volume of the combined drug group was reduced and there was a statistical difference (*P<0.05)( Figure 9 A); The tumor weight of the combined drug group was reduced and the difference was statistically significant (**P<0.01) ( Figure 9 B). The tumors in the candidate combination drug group (STP500) had a 62% tumor inhibition rate compared to the control group (Vehicle). Figure 9 C, Figure 9 D, Table 4), and the difference in tumor weight was statistically significant (*P<0.05).

[0166] Table 4. Tumor inhibition rates of siMD8 monotherapy and STP500 in colorectal cancer (MC38) xenograft models

[0167]

[0168] Example 10:

[0169] In vivo pharmacodynamics validation (gastric cancer MKN45 cell subcutaneous xenograft mouse model)

[0170] Next, we established another xenograft tumor model to further validate the pharmacodynamics of the candidate drug against the growth of human gastric cancer MKN45 cell xenografts in mice. The nanodrug formulation method was the same as above. The MKN45 subcutaneous tumor-bearing mouse model was established as follows: BALB / c-Nude mice were subcutaneously inoculated with 5×10 6 MKN45 cells. When the average tumor volume reaches 100-120 mm 3 The mice were randomly divided into groups at approximately 4 weeks. The dosing information is as follows: STP500, 3 mg / kg, administered intravenously via the tail vein, once every 2 days (Q2D); the positive control group (Oxaliplatin, 7.5 mg / kg, administered intraperitoneally, once daily (QD). After the first dose, the body weight and tumor volume of the mice were recorded every 2 days. The tumor volume was calculated as follows: V = 0.5 × (Dmax × Dmin 2 ). After the experiment, a tumor volume curve was drawn. The mice were euthanized and the tumors were removed and weighed. The tumor weight change rate TGItw (tumor weight change) was calculated using the formula:

[0171]

[0172] Mean TW treat: the mean tumor weight of mice in the treatment group at the end point of treatment;

[0173] Mean TW vehicle: the mean tumor weight of mice in the Vehicle group at the end point of treatment.

[0174] The experimental results are shown in Figure 10 The results showed that after 7 doses, the MyD88 and TGF-β1 combined group (STP500) nanoparticle drug could significantly inhibit the growth of human gastric cancer transplanted tumors (MKN45 cell line) compared with the control group ( Figure 10 A), and at this dose, the siRNA nanoparticle drug had no significant effect on the weight of mice; in contrast, the positive drug Oxaliplatin had a better tumor inhibition effect, and only one tumor sample was obtained at the end of the experiment, but it also showed certain toxicity, and the weight of mice in the group decreased ( Figure 10 B). The tumors in the candidate combination drug group (STP500) had a 50% tumor inhibition rate compared to the control group (Vehicle). Figure 10 C, Figure 10D, Table 5), and the difference in tumor weight was statistically significant (*P<0.05).

[0175] Table 5. Tumor inhibition rate of STP500 in gastric cancer (MKN45) xenograft tumor model.

[0176]

[0177] Example 11:

[0178] In vivo pharmacodynamics validation (prostate cancer RM-1 cell subcutaneous transplant tumor model in mice)

[0179] Next, we established another xenograft model to further validate the pharmacodynamics of the candidate drug against the growth of mouse prostate cancer RM-1 cell xenografts. The nanodrug formulation method was the same as above. RM-1 subcutaneous tumor-bearing mice were modeled as follows: C57BL / 6J mice were subcutaneously inoculated with 5×10 6 When the average tumor volume reaches 100-120 mm 3 The mice were divided into groups at about 1:10 pm and randomly divided into groups. The dosing information is as follows: STP500, 3 mg / kg, administered intravenously through the tail vein, once every 2 days (Q2D); the positive control group (Docetaxel, docetaxel), 15 mg / kg, administered intraperitoneally, once a week (QW). After the first dose, the body weight and tumor volume of the mice were recorded every 2 days. The tumor volume was calculated as follows: V = 0.5 × (Dmax × Dmin 2 ). After the experiment, a tumor volume curve was drawn. The mice were euthanized and the tumors were removed and weighed. The tumor weight change rate TGItw (tumor weight change) was calculated using the formula:

[0180]

[0181] Mean TW treat: the mean tumor weight of mice in the treatment group at the end point of treatment;

[0182] Mean TW vehicle: the mean tumor weight of mice in the Vehicle group at the end point of treatment.

[0183] The experimental results are shown in Figure 11 The results showed that after 8 doses, the MyD88 and TGF-β1 combined group (STP500) nanoparticle drug could significantly inhibit the growth of mouse prostate cancer (RM-1 cell line) compared with the control group ( Figure 11A), on the 12th day after the first administration, the tumor volume of the STP500 group was significantly reduced compared with the vehicle group, and the effect was statistically significant (*P<0.05); on the 14th day after the first administration, the tumor volume of the STP500 group was significantly reduced compared with the vehicle group, and the effect was statistically significant (**P<0.01); and at this dose (3 mg / kg, Q2D), the siRNA nanoparticle drug had no significant effect on the weight of the mice; in contrast, the commonly used chemotherapy drug Docetaxel did not show any tumor-killing effect in this experiment, showing certain clinical limitations. There was no significant difference in the weight changes of mice within the group ( Figure 11 B). The tumors in the candidate combination drug group (STP500) had a 45% tumor inhibition rate compared to the control group (Vehicle). Figure 11 C, Figure 11 D, Table 6), the difference in tumor weight was statistically significant (**P<0.01).

[0184] Table 6. Tumor inhibition rate of STP500 in prostate cancer (RM-1) xenograft tumor model.

[0185]

[0186] Example 12:

[0187] In vivo pharmacodynamic validation (colorectal cancer MC38 cell subcutaneous transplantation tumor model in mice - independent parallel experiment)

[0188] In parallel, we repeated the pharmacodynamic evaluation of the candidate drug STP500 in subcutaneous xenografts of the colorectal cancer cell line MC38 in another independent parallel experiment, and compared the transcriptome sequencing data of the drug-treated group (STP500) and the siRNA drug negative control group (NC). The nanomedicine formulation method was the same as above. The MC38 subcutaneous tumor-bearing mouse model was as follows: C57BL / 6 mice were subcutaneously inoculated with 1×10 6 MC38 cells, when the average tumor volume reached about 100mm 3 The mice were randomly divided into groups and the administration information was as follows: STP500, 2 mg / kg, administered intravenously via the tail vein, once every 3 days (Q3D); positive control group (mPD-L1, PD-L1 antibody), 5 mg / kg, administered intraperitoneally ip, once every 3 days (Q3D). After the first administration, the body weight and tumor volume of the mice were recorded every 2 days. The tumor volume was calculated as follows: V = 0.5 × (Dmax × Dmin 2 ), after the experiment, the tumor volume curve was drawn, the mice were euthanized, the tumors were removed, and the tumor weight was weighed.

[0189] The experimental results are shown in Figure 12 The results showed that after 7 doses, the MyD88 and TGF-β1 combined group (STP500) nanoparticle drug could significantly inhibit the growth of mouse colorectal cancer (MC38 cell line) compared with the control group ( Figure 12 A), which confirms our previous conclusion. On the 14th day after the first administration, the tumor volume of the STP500 group was significantly reduced compared with the Vehicle group, and it was statistically significant (*P<0.05); the survival curve of mice in the same group also showed the corresponding conclusion ( Figure 12 B).

[0190] At the end of the experiment (day 18 after the first dose), three mice were randomly selected from each of the STP500-treated group and the small nucleic acid-treated negative control group (NC) for transcriptome sequencing of tumor samples. Sequencing was performed by Suzhou Jinweizhi Biotechnology Co., Ltd. Sequencing data were then processed and analyzed. The genomic sequences were indexed using Hisat2 (v2.0.1). Finally, the clean data were aligned to the reference genome using Hisat2 (v2.0.1). Fasta-formatted text was converted from a known gff annotation file and properly indexed. HTSeq (v0.6.1) then used this file as a reference gene file to estimate gene and isoform expression levels from the paired-end clean data. Differential expression analysis was performed using the DESeq2 Bioconductor package, a model based on the negative binomial distribution. Data-driven prior distributions were used for estimates of dispersion and log-fold change. Genes with |log2(FoldChange)| > 1 and a p-value < 0.05 were considered differentially expressed. The protein interaction network of differentially expressed genes was constructed using the STRING database (https: / / string-db.org / ), with an InteractionScore > 0.4 as the threshold. The results were imported into Cytoscape software (v3.9.1). The betweenness centrality was analyzed and plotted using the Cytoscape plug-in CytoNCA. The R package clusterProfiler (v4.4.4) was used to perform GO (Gene Ontology) functional enrichment analysis and KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis on the differentially expressed genes, and the R package ggplot was used. 2 (v3.3.6) Plot the results.

[0191] The statistical results are shown in Figure 12 (C&D), Compared with the gene expression in the NC group, we detected 101 up-regulated genes and 207 down-regulated genes in the STP500-treated group samples ( Figure 12C), such as the expression of some tumor-related genes (Claudin-5, Vtn, Ambp, Col1a1, etc.) was downregulated, while the expression of immune activation-related genes (such as CD28, etc.) was increased. The upregulated and downregulated gene expression of the two groups of samples are shown in the heat map ( Figure 12 Table 7 lists some candidate genes and their related biological functions. The transcriptome data provide support for subsequent studies of target gene-related pathways and interactions between this target and other targets, and provide data support for the future development of other related small nucleic acid drugs or combination drug strategies.

[0192] Table 7. Transcriptome analysis data - representative candidate target-related genes.

[0193]

[0194]

[0195] CytoNCA: a Cytoscape plugin for centrality analysis and evaluation of protein interaction networks.

[0196] clusterProfiler: An R package for comparing biological themes across gene clusters.

[0197] Based on the experimental data of the above examples, it can be seen that the use of PNP technology to encapsulate and introduce siRNA combination drugs (STP500) that jointly target MyD88 (MD8) and TGF-β1 (TF1) has potential application prospects in the treatment of digestive system cancers such as colorectal cancer and gastric cancer, as well as prostate cancer.

[0198] The above embodiments are intended only to illustrate the technical concepts and features of the present invention. Their purpose is to enable those skilled in the art to understand the contents of the present invention and implement them accordingly. They are not intended to limit the scope of protection of the present invention. Any equivalent changes or modifications made in accordance with the spirit of the present invention are intended to be covered by the scope of protection of the present invention.

Claims

1. A nucleic acid interference pharmaceutical composition, characterized in that: The nucleic acid interference pharmaceutical composition comprises an active ingredient and a pharmaceutically acceptable carrier. The active ingredient comprises a first active ingredient capable of inhibiting and silencing the expression of the MyD88 gene and a second active ingredient capable of inhibiting and silencing the expression of the TGF-β1 gene. The first active ingredient is an siRNA molecule targeting the MyD88 gene, and its oligonucleotide sequence is: Justice chain: GAAUGUGACUUCCAGACCAdTdT, Antisense strand: UGGUCUGGAAGUCACAUUCdTdT; The second active ingredient is a siRNA molecule targeting the TGF-β1 gene, and its oligonucleotide sequence is: Justice chain: CCCAAGGGCUACCAUGCCAACUUCU, Antisense strand: AGAAGUUGGCAUGGUAGCCCUUGGG, The carrier is an H3K4b-type histidine-lysine polymer.

2. The nucleic acid interference pharmaceutical composition according to claim 1, characterized in that The carrier is HKP or HKP(+H).

3. Use of the nucleic acid interference pharmaceutical composition according to claim 1 or 2 in the preparation of a drug for treating colorectal cancer, gastric cancer, or prostate cancer.

4. A drug for treating colorectal cancer, gastric cancer, and prostate cancer, characterized in that: The medicine includes the nucleic acid interference pharmaceutical composition according to claim 1 or 2.

5. The drug according to claim 4, characterized in that The mass ratio of the first active ingredient to the second active ingredient is 1:0.8-1.2; and / or, the drug is a nanoparticle; and / or, the drug is administered by subcutaneous injection and / or intravenous injection; And / or, the subject of administration of the drug is a mammal.

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