Application of RPN1 gene in diagnosis and treatment of lung cancer

Abstract

The invention discloses application of an RPN1 gene in diagnosis and treatment of lung cancer, and belongs to the technical field of biological diagnosis and biological medicine. Specifically, through comparison of differential genes of healthy individuals and different subtype lung cancer patients in a database, it is found that RPN1 gene RNA and protein expression are ubiquitous and significantly up-regulated, and through verification of different data sets and the like, it is proved that the target spot can be used as a lung cancer detection target spot. The RPN1 gene in the cancer cells is knocked down, it is found that RPN1 knock-down promotes aging of the lung cancer cells, it is shown through in-vivo experiments that reduction of RPN1 expression can improve the severity of the lung cancer, and it is proved that RPN1 can serve as a treatment target of the lung cancer. The invention provides a new diagnosis and treatment target, and provides a new thought and direction for developing a treatment strategy aiming at lung cancer, especially lung adenocarcinoma and lung squamous cell carcinoma in the future.

Description

Technical Field

[0001] The present invention relates to the application of RPN1 gene in the diagnosis and treatment of lung cancer, belonging to the fields of biodiagnosis and biopharmaceuticals. Background Art

[0002] Lung cancer remains one of the leading causes of cancer-related deaths globally, and non-small cell lung cancer (NSCLC) is the most common and aggressive form. Despite progress in early detection and targeted therapies, lung cancer continues to pose significant therapeutic challenges due to its metastatic potential, late diagnosis, and resistance to existing therapies. Cellular senescence is an irreversible cell cycle arrest state that plays a dual role in tumorigenesis. On the one hand, senescence acts as a tumor suppressor mechanism by restricting the proliferation of damaged or malignant cells. On the other hand, senescent cells can secrete pro-inflammatory cytokines and other factors, thereby creating a microenvironment conducive to tumor progression and treatment resistance. This paradoxical behavior complicates therapeutic strategies targeting senescence in cancer treatment. The regulation of cellular senescence is controlled by multiple signaling pathways, including the p53 / p21, p16INK4a / RB, and mTOR pathways, which coordinate the activation, maintenance, and potential reversal of cellular senescence. In the case of cancer, the complex balance between these pathways is often disrupted, leading to inhibition of tumor growth and promotion of resistance to chemotherapy and targeted therapies. Therefore, exploring the molecular mechanisms regulating cellular senescence is crucial for developing effective therapeutic strategies.

[0003] Glycosylation is a fundamental post-translational modification in which carbohydrate moieties are added to proteins and lipids, thereby altering their structure, stability, and function. In cancer, altered glycosylation patterns are commonly observed and are often associated with tumor progression, metastasis, and treatment resistance. Glycosylation affects various cellular processes, including protein stability, cell signaling, adhesion, and immune escape. N-glycosylation and O-glycosylation are the most common glycosylation modifications, and abnormal N -glycosylation significantly affects cancer processes and clinical targeted therapies. Increasing evidence indicates that abnormal glycosylation modifications of cell surface proteins (such as transmembrane proteins and growth factor receptors) lead to tumor cell growth, invasion, and metastasis through the activation of signaling cascades and alter the tumor microenvironment, promoting tumor progression.

[0004] RPN1 is a key subunit of the 26S proteasome, which can mediate the binding of ubiquitin-like domains to the proteasome, participate in the processing and degradation of misfolded or damaged proteins, and its phosphorylation contributes to this binding process. In addition to its role in proteasomal degradation, RPN1 is also involved in the regulation of protein glycosylation, which is crucial for cellular functions such as protein folding and quality control. The role of RPN1 in glycosylation may affect various cell surface receptors and intracellular signaling pathways, thereby influencing processes such as cell survival, stress response, and cellular senescence. Understanding the molecular link between RPN1, glycosylation, and senescence can provide new insights into the mechanisms driving lung cancer progression and treatment resistance.

[0005] This study aimed to investigate how RPN1-mediated glycosylation regulates lung cancer cell senescence through in vitro and in vivo experiments, further understand the complex interactions between glycosylation, cellular senescence, and tumorigenesis, and provide new avenues for therapeutic intervention in lung cancer. Summary of the Invention

[0006] To solve the above problems, the present invention conducted in-depth research and found that there are significant differences in the expression levels of RPN1 between normal individuals and lung cancer patients, which is manifested in both lung adenocarcinoma and squamous cell carcinoma of the lung, and is also true in datasets from different sources. At the same time, verification through cell experiments found that this target can be used as a biomarker for lung cancer detection. Based on this, by reducing the expression of RPN1 in vitro and in vivo, it was found that the proliferation of cancer cells and the growth of tumors were both inhibited, thus providing a new target for the treatment of lung cancer.

[0007] The first object of the present invention is to provide the use of a reagent for reducing the expression level of the RPN1 gene in the preparation of a product for preventing or treating lung cancer.

[0008] Furthermore, the reagent for reducing the expression level of the RPN1 gene contains: shRNA, lentivirus, or an inhibitor of RPN1 gene expression.

[0009] Furthermore, the sequences of the shRNA are as shown in SEQ ID NO.1-2.

[0010] Furthermore, the lung cancer is lung adenocarcinoma and / or squamous cell carcinoma of the lung.

[0011] The second object of the present invention is to provide a product for preventing or treating lung cancer, which contains a reagent for reducing the expression level of the RPN1 gene.

[0012] Furthermore, the product also contains a pharmaceutically acceptable carrier (such as for delivery) or excipient.

[0013] Furthermore, the excipients include one or more of a filler, a shaping agent, a stabilizer, a diluent, a binder, a disintegrant, a lubricant, a glidant, a wetting agent, an effervescent agent, a colorant, a sweetener, an aromatic, a preservative, a dispersant, a film-forming agent, a plasticizer, a pore-forming agent, a light-shielding agent, a retardant, and a solvent.

[0014] Furthermore, the product is composed of 0.1 - 100% of the active ingredient (a reagent for reducing the expression level of the RPN1 gene) and 99.9 - 0% of a carrier or excipients.

[0015] The third object of the present invention is to provide a pharmaceutical composition for treating lung cancer, which contains a reagent for reducing the expression level of the RPN1 gene.

[0016] Furthermore, according to actual needs, it can be used in combination with other anti-cancer products for treatment.

[0017] The fourth object of the present invention is to provide the use of a reagent for detecting the expression level of the RPN1 gene in the preparation of a lung cancer detection product.

[0018] The fifth object of the present invention is to provide a kit for lung cancer prediction, which contains a reagent for detecting the expression level of the RPN1 gene.

[0019] Furthermore, the reagent for detecting the expression level of the RPN1 gene contains primers for amplifying the RPN1 gene.

[0020] Furthermore, the detection steps include: S1. Extract genomic DNA from the sample to be tested and quantify the RPN1 gene therein; S2. Judge the risk of suffering from lung cancer or the prognosis risk according to the expression level of the RPN1 gene.

[0021] The sixth object of the present invention is to provide an aging lung cancer cell model, which is obtained by reducing the expression level of the RPN1 gene in lung cancer cells and culturing them.

[0022] The seventh object of the present invention is to provide a method for promoting the aging of lung cancer cells in vitro (or a method for preparing aging lung cancer cells), which includes the step of knocking out the RPN1 gene in lung cancer cells.

[0023] The beneficial effects of the present invention: By comparing the differential genes between healthy individuals and lung cancer patients of different subtypes in the database, the present invention obtains the significantly differential gene RPN1 by taking the intersection, confirms the influence of knocking out this gene on the progression of lung cancer, and shows through in vivo experiments that reducing the expression of RPN1 will improve the severity of lung cancer, thus proving that RPN1 can be used as a therapeutic target for lung cancer and has great application prospects in the prevention and treatment of lung cancer. Description of the Drawings

[0024] Figure 1 RPN1 is highly expressed in lung cancer and has important clinical significance. (A) Analysis of the expression of RPN1 in LUAD and LUSC using the TCGA database combined with the GTEx database. (B) Analysis of the expression of RPN1 in LUAD and LUSC in the TCGA database. (C) Analysis of the expression changes of RPN1 in multiple lung cancer datasets based on the GEO database. Analysis of the changes in the transcriptional level (D) and protein level (E) of LUAD and LUSC in the CPTAC database using the PCAS tool. Representative pictures (F) and Image J semi-quantitative results (G) of immunohistochemical staining of RPN1 protein expression in a lung cancer tissue microarray. Differences in the positive staining rates after grouping the lung cancer tissues in the tissue microarray according to T stage (H), tumor diameter (I), and tumor stage (J). (K) Differences in RPN1 expression after grouping according to smoking history in the lung adenocarcinoma dataset of the TCGA database. Detection of changes in the RNA and protein expression of RPN1 in a smoking-induced BEAS-2B cell malignant transformation model by qPCR (L) and WB (M).

[0025] Figure 2 For the relationship between RPN1 and the prognosis and tumor stemness of lung cancer patients. (A) Survival curves of patients with high and low expression of RPN1 in the TCGA lung cancer dataset. Analysis of the impact of RPN1 on OS (B) and PPS (C) of lung cancer patients using the KM Plotting online tool. (D-E) Scatter plots showing the correlation between RPN1 and tumor stemness in the TCGA LUAD and LUSC datasets. TCGA: The Cancer Genome Atlas. OS: Overall Survival. PPS: Post-Progress Survival. KM: Kaplan Meier.

[0026] Figure 3RPN1 is related to the biological functions of lung cancer. The scatter plots show the correlations between RPN1 and the expression of oncogenes in the TCGA LUAD (A), TCGA LUSC (B), and GSE30219 (C) datasets. (D) The scatter plot shows the correlation between RPN1 expression and TFG expression in the lung adenocarcinoma and lung squamous cell carcinoma datasets of the TCGA database. (E) The heatmap shows the intersection of oncogenes related to RPN1 expression in the three datasets. The heatmap shows the intersection of biological functions (F) and KEGG pathways (G) in the results of the single-gene enrichment analysis of RPN1 based on the TCGA_LUAD and TCGA_LUSC datasets. The scatter plots show the correlations between RPN1 and the expression of cell senescence-related genes in the TCGA LUAD (H), TCGALUSC (I), and GSE30219 (J) datasets. (K) The scatter plot shows the correlation between RPN1 expression and PDCD10 expression in the lung adenocarcinoma and lung squamous cell carcinoma datasets of the TCGA database. (L) The heatmap shows the intersection of senescence-related genes related to RPN1 expression in the three datasets.

[0027] Figure 4 It is about the relationship between RPN1 expression and immune cell infiltration and anti-tumor drug sensitivity. On the TCGA LUAD (A) and LUSC (B) datasets, the correlation results between RPN1 and immune cell infiltration scores were calculated using xCell. In the TCGA LUAD (C), TCGA LUSC (D), and GSE30219 (E) datasets, the scatter plots of the correlations between RPN1 and anti-tumor drug sensitivity were calculated through the oncopredict package. (F) The heatmap shows the intersection of drugs related to RPN1 expression in the three datasets. TCGA: The Cancer Genome Atlas. LUAD: Lung adenocarcinoma. LUSC: Lung squamous cell carcinoma.

[0028] Figure 5RPN1 promotes cell proliferation and inhibits cell senescence. CCK-8 assay was used to analyze the changes in the proliferation ability of A549 (A) and H1299 (B) cells after knocking down RPN1. Representative images (C) and statistical results (D) of the proliferation ability of A549 and H1299 cells after knocking down RPN1 were analyzed by EdU assay. Representative images (E) and statistical results (F) of DNA damage in A549 and H1299 cells after knocking down RPN1 were analyzed by γ-H2AX immunofluorescence. Representative images (G) and statistical results (H) of cell senescence in A549 and H1299 cells after knocking down RPN1 were analyzed by β-galactosidase staining. ELISA method was used to analyze the concentrations of IL6 (I) and IL8 (J) in the culture supernatants of A549 and H1299 cells after knocking down RPN1. qPCR was used to detect the expression changes of CDKN1A (K) and CDKN2A (L) in A549 and H1299 cells after knocking down RPN1. Representative images and quantitative results of the expression changes of RPN1, P21, and P16 in A549 and H1299 cells after knocking down RPN1 were analyzed by Western blot (M-P).

[0029] Figure 6 The SRAMP online tool was used to predict the m6A modification sites on RPN1 mRNA.

[0030] Figure 7IGF2BP2 regulates RPN1 through m6A modification. The m6A modification of three high-confidence sites obtained based on SRAMP was verified by meRIP qPCR in A549 (A) and H1299 (B) cells, with anti-IgG antibody as a control. Compared with the IgG control group, **P < 0.01, ***P < 0.001. Correlation analysis of IGF2BP2 protein and RPN1 RNA expression in the LUAD (C) and LSCC (D) datasets in the CPTAC database was analyzed based on the PCAS tool. (E) qPCR was used to detect the change in RPN1 expression after overexpressing IGF2BP2 in lung cancer cells. Representative images (F) and quantitative results (G-H) of the changes in IGF2BP2 and RPN1 protein expression after overexpressing IGF2BP2 in lung cancer cells were analyzed by Western blot. RNA stability experiments were performed to explore the effect of IGF2BP2 overexpression on the stability of RPN1 RNA in A549 (I) and H1299 (J) cells. (K) The change in the half-life of RPN1 after overexpressing IGF2BP2 in lung cancer cells was calculated based on the RNA stability experiment. qPCR was used to detect the relative expression level of RPN1 after treating with 3-DAA (global methylation inhibitor) or MA (FTO inhibitor) in A549 (L) and H1299 (M) cells. Compared with the DMSO group, *P < 0.05, **P < 0.01, ***P < 0.001. qPCR was used to detect the relative expression level of RPN1 after 3-DAA treatment and IGF2BP2 overexpression in A549 (N) and H1299 (O) cells. Compared with the DMSO / blank group, **P < 0.01. Compared with the DMSO / pYTHDC2 group, #P < 0.05 and P < 0.001.

[0031] Figure 8RPN1 regulates cellular senescence through the AKT2 / FOXO3 pathway. (A) Results of correlation analysis between RPN1 protein expression and AKT2 phosphorylation sites in LUAD and LUSC of the CPTAC database based on the PCAS tool. (B) Scatter plot showing the correlation between RPN1 protein expression and AKT2:t451 phosphorylation level in the LUAD and LUSC datasets of the CPTAC database. (C) Results of correlation analysis between RPN1 protein expression and FOXO3 phosphorylation sites in LUAD and LUSC of the CPTAC database based on the PCAS tool. (D) Scatter plot showing the correlation between RPN1 protein expression and FOXO3:s284 phosphorylation level in the LUAD and LUSC datasets of the CPTAC database. Representative pictures (E) and quantitative results (F-J) of Western blot analysis of the expression changes of PIK3CB, AKT2, p-AKT2, FOXO3, and p-FOXO3 after knocking down RPN1 in lung cancer cells. Representative pictures (K) and quantitative results (L-M) of Western blot analysis of the expression changes of p-AKT2, FOXO3, and p-FOXO3 after knocking down RPN1 and treating with the AKT agonist SC79 in lung cancer cells. (N-O) β-galactosidase staining analysis of the regulation of lung cancer cell senescence by knocking down RPN1 and SC79 treatment and quantitative results.

[0032] Figure 9FOXO3 targets CDKN1A to regulate cellular senescence. (A) Analysis of the correlation between CDKN1A and FOXO3 expression in LUAD and LUSC based on the TCGA database. (B) Analysis of the correlation between CDKN1A and FOXO3 expression in LUAD and LUSC in the CPTAC database based on PCAS. (C) Analysis of the correlation between the phosphorylation level of FOXO3 phosphorylation sites and CDKN1A RNA expression in LUAD and LUSC in the CPTAC database based on PCAS. (D) Scatter plot showing the correlation between the phosphorylation level of FOXO3:s284 and CDKN1A RNA expression in lung cancer. (E) qPCR was used to detect the change in CDKN1A expression after knocking down RPN1 and treating with SC79 in lung cancer cells. (F-G) Western blot analysis of the change in P21 expression and quantitative results after knocking down RPN1 and treating with SC79 in lung cancer cells. qPCR was used to detect the change in FOXO3 (H) and CDKN1A (I) expression after transfection with shFOXO3 in lung cancer cells. (J-K) Western blot was used to detect the change in P21 expression after transfection with shFOXO3 in lung cancer cells. (L) qPCR was used to detect the change in CDKN1A expression after overexpressing FOXO3 in lung cancer cells. (M) Prediction of the FOXO3 binding site on the CDKN1A promoter sequence based on JASPAR2024. (N-Q) Dual-luciferase reporter gene assay was used to verify the binding of FOXO3 to the promoter sequence in two lung cancer cells.

[0033] Figure 10 RPN1 regulates EGFR membrane localization and stability through N-glycosylation modification. (A) Analysis of the correlation between EGFR protein expression and glycosyltransferases including RPN1 in lung cancer based on the PCAS tool. (B) Western blot analysis of the molecular weight and expression change of EGFR after treatment with the deglycosylase PNGase. (C) Quantitative analysis results of the EGFR band without PNGase. (D-E) Immunofluorescence analysis of the membrane localization of EGFR after knocking down RPN1 in lung cancer cells. Western blot analysis of the degradation of EGFR and quantitative results after treatment with the protein synthesis inhibitor CHX and the N-glycosylation inhibitor Tunicamycin in lung cancer cells A549 (F-G) and H1299 (H-I).

[0034] Figure 11The in vivo tumorigenicity assay in nude mice was performed to verify the ability of RPN1 to regulate the tumorigenicity of lung cancer cells. (A) Subcutaneous tumor formation in nude mice by A549 lung cancer cells stably transfected with shNC and shRPN1 (n = 3). (B) Growth curves of subcutaneous tumors in nude mice; (C) Differences in tumor weights between the two groups of mice at the end of the experiment. (D) Immunohistochemical staining analysis of the protein expression of RPN1, p-FOXO3, P21, Ki67, EGFR, and CD31 in tumor tissues of the two groups of mice. (E) AOD statistical results of RPN1, P21, p-FOXO3, and EGFR in immunohistochemical images. (F) Statistical results of the proportion of Ki67-positive cells in immunohistochemical staining images. (G) Statistical results of the proportion of vascular areas in CD31 immunohistochemical staining. (H-I) Representative immunohistochemical staining images and AOD statistical results of P21, p-FOXO3, and EGFR in subcutaneous tumors formed by H1299 cells with stable knockdown of RPN1 in previous studies. Detailed implementation manners

[0035] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, so that those skilled in the art can better understand the present invention and be able to implement it, but the specific embodiments cited shall not be construed as limiting the present invention.

[0036] The solutions involved in the present invention are as follows: Currently, there are no effective detection, prevention, and treatment methods for lung cancer, especially lung adenocarcinoma and squamous cell carcinoma, which limits clinical intervention.

[0037] The present invention reveals the multi-dimensional regulatory role of RPN1 in the occurrence and development of lung cancer and elaborates its molecular mechanism in detail. Through the integration of multi-omics data and the analysis of clinical samples, we found that the high expression of RPN1 in lung cancer tissues is closely related to the malignant phenotype of tumors, the poor prognosis of patients, and the smoking history. Notably, long-term cigarette smoke exposure experiments showed that environmental carcinogenic factors directly induced the upregulation of RPN1 expression, providing a new perspective and entry point for the etiological mechanism of lung cancer. Mechanistically, RPN1 mediates the N-glycosylation modification of the EGFR receptor, affects the stability of its membrane localization, and on this basis, continuously activates the PI3K / AKT2 / FOXO3 signaling pathway, thereby inhibiting the transcriptional repression of CDKN1A and further inhibiting the cellular senescence phenotype.

[0038] In the present invention, the decrease in EGFR N-glycosylation modification caused by RPN1 knockdown leads to a decrease in its stability and a reduction in membrane localization, thereby inhibiting its downstream cascade reaction and promoting the senescence of lung cancer cells. Our current research, based on the combined analysis of multi-omics and experimental verification in vitro and in vivo, has confirmed the regulation of RPN1 on EGFR N-glycosylation, and then regulates cell senescence through the downstream cascade PI3K / AKT2 / FOXO3 pathway. In addition, we also found that CDKN1A is a downstream target gene of FOXO3, which may be an important mechanism for its regulation of cell senescence.

[0039] In terms of the upstream regulatory mechanism, we further explored the potential mechanism of its upregulation in lung cancer. Based on bioinformatics analysis, it was found that it is regulated by m6A modification and the reader protein IGF2BP2. Experiments verified that the m6A methylated reader protein IGF2BP2 positively regulates the expression of RPN1 by enhancing the stability of RPN1 mRNA. IGF2BP2 is considered to play an important role in a wide range of biological and disease processes, including embryonic development, neurogenesis, metabolism, and cancer progression. More and more studies have shown that m6A regulation plays an important role in cell senescence or senescence-related processes. The genetic association study of metabolic syndrome and metabolic-related traits in the Chinese elderly population also explains the association between IGF2BP2 and senescence symptoms, which is consistent with the findings of this study.

[0040] Generally speaking, the present invention not only reveals the role of RPN1 in the senescence of lung cancer cells at the cellular level, but also provides new insights into RPN1 as a potential therapeutic target. By further exploring the role and mechanism of RPN1 in lung cancer, future research may provide new strategies for cancer treatment, especially in inhibiting tumor progression by regulating cell senescence or immune escape. In particular, targeted therapy against RPN1 and its downstream signaling pathways may provide new ideas and intervention means for the treatment of lung cancer clinically.

[0041] Specifically: The present invention found that there are significant differences in the expression levels of the RPN1 gene between healthy individuals and patients, so it also has certain potential in the detection of lung cancer. RPN1 is expected to be a new indicator for the evaluation and diagnosis of lung cancer.

[0042] Therefore, the present invention provides a kit for predicting the risk of lung cancer or predicting the prognosis risk of lung cancer, and the kit can detect the expression level of the RPN1 gene. The higher its level in the body, the higher the risk of disease or the more difficult the prognosis. Clinically, corresponding preventive and therapeutic measures can be taken for patients with high RPN1 expression levels.

[0043] Preferably, the kit contains substances necessary for quantifying the RPN1 gene, such as primers for amplifying the RPN1 gene.

[0044] Preferably, the detection step includes but is not limited to: S1. Extract genomic DNA of the sample and quantify the RPN1 gene therein; S2. Determine the risk of lung cancer or the risk of lung cancer prognosis according to the expression level of the RPN1 gene.

[0045] Preferably, the quantification method includes but is not limited to real-time fluorescence quantitative PCR (qPCR), etc.

[0046] Preferably, the kit or primer of the present invention can detect the RPN1 gene in different species as needed, preferably human, and the Gene ID of human RPN1 is: 6184. When the kit or primer of the present invention is needed to detect other target species, those skilled in the art can find the sequence homologous to the gene listed in the present invention in the target species and set the primer according to the conventional method to achieve detection.

[0047] Based on the above findings, the present invention provides a composition for preventing or treating lung cancer. Preferably, the composition is a pharmaceutical composition, which contains a substance that reduces the expression of the RPN1 gene, may also contain other active ingredients, and a pharmaceutically acceptable carrier. Usually, these substances can be formulated in a non-toxic, inert and pharmaceutically acceptable aqueous carrier medium, wherein the pH is usually about 5-8, preferably about 6-8, and the pH value can vary with the nature of the formulated substance, and those skilled in the art can adjust it as needed. The prepared pharmaceutical composition can be administered by conventional routes, including (but not limited to): intravenous, topical administration.

[0048] The pharmaceutical composition of the present invention contains a safe and effective amount (such as 0.001-99 wt%, preferably 0.01-90 wt%, more preferably 0.1-80 wt%) of the above substance that reduces the expression of the RPN1 gene, and a pharmaceutically acceptable carrier. Such carriers include (but are not limited to): fillers, excipients, stabilizers, diluents, binders, lubricants, surfactants or combinations thereof. The pharmaceutical preparation should match the administration method. The pharmaceutical composition of the present invention can be made into an injection form, for example, prepared by a conventional method with physiological saline or an aqueous solution containing glucose and other adjuvants. Pharmaceutical compositions such as injections and solutions should be manufactured under sterile conditions. The dosage of the active ingredient is a therapeutically effective amount. In addition, the preparation of the present invention can also be used together with other therapeutic agents.

[0049] When using the pharmaceutical composition, a safe and effective amount of the drug is administered to an individual, and the specific dosage should also consider factors such as the administration route and the health status of the patient, which are all within the scope of skills of a skilled physician. Examples

[0050] 1. Database and Tools The data was sourced from The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases. TCGA and CPTAC are internationally recognized cancer research databases that provide rich genomic and proteomic data, which are widely used in cancer research.

[0051] We analyzed data on Lung Adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LUSC) from the TCGA and CPTAC databases.

[0052] TPM-normalized GTEx and TCGA pan-cancer data, along with relevant sample annotation information, were downloaded from the Xena browser (https: / / xenabrowser.net / ).

[0053] The ProteoCancer Analysis Suite (PCAS) is an R package developed based on CPTAC multi-omics data, which utilizes these resources to facilitate in-depth analysis of proteomics, phosphoproteomics, and transcriptomics, enhancing our understanding of the tumor microenvironment through functions such as immune infiltration and drug sensitivity analysis. This tool helps to identify key signaling pathways and therapeutic targets, especially through its detailed phosphoproteomics analysis.

[0054] 2. Expression Correlation Analysis Based on TCGA lung cancer data, the Spearman correlation coefficients between the expression levels of RPN1 and oncogenes, immune checkpoint genes, and senescence genes, as well as immune cell infiltration and anti-tumor drug sensitivity, were calculated using the R language.

[0055] Oncogenes were obtained from the ONGene database (http: / / www.ongene.bioinfo-minzhao.org). Genes related to cellular senescence were obtained from the CellAge database (https: / / genomics.senescence.info / cells / ). A total of 11 immune checkpoint genes (ICGs) were extracted, which were from previous studies. Immune cell infiltration scores were from the TIMER2.0 database (http: / / timer.cistrome.org / ). Data from the Genomics of Drug Sensitivity in Cancer (GDSC, https: / / www.cancerrxgene.org / ) were used to evaluate drug sensitivity by "oncoPredict". Correlation analysis was performed using the Spearman method (using the "psych" package).

[0056] 3. Single Gene Set Enrichment Analysis (GSEA) Gene Set Enrichment Analysis (GSEA) was performed using the "ClusterProfiler" R package to explore the gene set enrichment based on correlation analysis. Specifically, two gene set collections were used: c2.cp.kegg.v2023.2.entrez.gmt for signaling pathway analysis and c5.go.bp.v2023.2.entrez.gmt for biological process analysis related to RPN1. This analysis covered multiple cancer types and aimed to identify consistently enriched pathways and biological processes. After performing GSEA for each cancer type, the commonly enriched gene sets were extracted and visualized to highlight their importance.

[0057] 4. Tissue Microarray Immunohistochemistry Analysis Human lung cancer tissue microarrays (serial numbers: LAC-1402 and LAC-1403) were purchased from Wuhan Servicebio Technology Co., Ltd. (China). These two tissue microarrays contained 70 pairs of lung cancer tissues and adjacent normal tissues. The expression of RPN1 in lung cancer and paired normal tissues was detected and analyzed using immunohistochemistry (IHC) with an RPN1 antibody. Quantitative analysis of IHC staining was performed using ImageJ and its plugin IHCprofiler. The proportion of positive staining was expressed as the sum of high, low, and positive rates. In terms of group comparison, the staining intensity was analyzed according to T stage, tumor diameter, and clinical stage to evaluate the expression differences of RPN1 under different clinical characteristics. This will help us understand the potential role of RPN1 in the development of lung cancer and provide basic data for subsequent studies.

[0058] 5. Cell Culture The human lung adenocarcinoma cell lines H1299 and A549 were both purchased from the American Type Culture Collection (ATCC, Manassas, VA, USA). These cells were cultured in Dulbecco's Modified Eagle Medium (DMEM) containing 10% fetal bovine serum (FBS) in a humidified incubator at 37°C with 5% CO2. In addition, we also used the human immortalized bronchial epithelial cell line BEAS-2B to establish a malignant transformation model induced by cigarette smoke exposure, and obtained cells continuously exposed for 10, 20, and 30 generations (S10, S20, S30).

[0059] 6. Gene manipulation The shRNA sequences of RPN1 were designed using different tools. The annealed shRNA double-stranded fragments were cloned into the pGreen vector. After evaluating the knockdown efficiency of multiple candidate shRNAs targeting RPN1, an optimal shRNA was selected for subsequent experiments. Its sense strand sequence was GGAGATTCTTCACAGTCAA (SEQ ID NO.1), and the antisense strand sequence was TTGACTGTGAAGAATCTCC (SEQ ID NO.2). In addition, a random non-specific control shRNA (shNC) was also cloned into the same vector and used as a negative control. Lentiviruses were generated according to the manufacturer's protocol. Briefly, the RPN1 lentiviral supernatant from HEK-293T cells was collected 48 hours and 72 hours after transfection. The full-length coding sequence (CDS) of RPN1 was amplified using 2×EasyPfu PCR SuperMix (TransGen, China) and cloned into the pCDH vector. The recombinant plasmid was named pCDH-RPN1.

[0060] The results are as follows: 1. RPN1 is highly expressed in lung cancer and has important clinical significance Through the combined analysis of the TCGA and GTEx databases, it was found that the expression of RPN1 in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) tissues was significantly higher than that in normal lung tissues ( Figure 1 A). Further analysis of the TCGA database alone supported this finding ( Figure 1 B), and the high expression of RPN1 in lung cancer was also verified through the analysis of different lung cancer datasets in the GEO database ( Figure 1 C). In addition, using the analysis results of PCAS, it was found that in the lung cancer datasets in the CPTAC database, the transcriptional level and protein level of RPN1 were both significantly upregulated in LUAD and LUSC tissues ( Figure 1 D, E). Further confirmation of the high expression of RPN1 in lung cancer tissues was achieved based on immunohistochemical staining of 70 pairs of commercialized lung cancer and adjacent tissues ( Figure 1F, G), and the positive rate of RPN1 was closely related to the clinicopathological features of tumors (Table 1), especially in tumors with higher T stage ( Figure 1 H), larger tumor diameter ( Figure 1 I), and advanced ( Figure 1 J) tumor tissues. Based on the lung cancer data in the TCGA database, the expression of RPN1 was higher in tumors of male patients than in female patients, higher in patients older than 60 years than in patients ≤ 60 years, and the expression level of RPN1 was significantly higher in lung cancer tissues of smoking patients (Table 2, Figure 1 K). In the established model of malignant transformation of BEAS-2B cells induced by long-term cigarette smoke exposure, both the RNA and protein expressions of RPN1 were significantly increased ( Figure 1 L - M).

[0061] Table 1 Correlation between the positive rate of RPN1 and clinicopathological features in 70 lung cancer tissues in the tissue microarray

[0062] Table 2 Correlation analysis of RPN1 and clinicopathological features in the TCGA lung cancer dataset

[0063] 2. RPN1 has important biological functions and clinical significance in lung cancer Based on the lung cancer dataset in the TCGA database, the survival period of lung cancer patients with high expression of RPN1 was significantly lower than that of patients with low expression of RPN1 ( Figure 2 A). Further analysis by the online tool KM plotter found that RPN1 had a significant negative impact on the overall survival (OS) and progression-free survival (PPS) of lung cancer patients ( Figure 2 B, C). The expression of RPN1 was also found to be closely related to tumor stemness in lung adenocarcinoma and lung squamous cell carcinoma ( Figure 2 D, E). Based on the TCGA LUAD ( Figure 3 A), TCGA LUSC ( Figure 3 B), and GSE30219 ( Figure 3 C) datasets, correlation analysis showed that there was a significant positive correlation between the expression of RPN1 and the expression levels of multiple oncogenes, especially the highest correlation with the TFG gene ( Figure 3 D), and in addition, there were also oncogenes such as CDC6, CCNE1, CDC25C, CCNB2, etc. ( Figure 3E). The single-gene enrichment analysis results of RPN1 revealed its association with multiple important biological functions and KEGG pathways, including recombinational repair, cell cycle checkpoint, double strand break repair, DNA replication, as well as nucleotide excision repair, mismatch repair, cell cycle, etc. ( Figure 3 F, G). Meanwhile, the expression of RPN1 in three lung cancer datasets also showed a significant correlation with genes related to cellular senescence in the CellAge database ( Figure 3 H-J), and the most prominent was the PDCD10 gene (r = 0.596, Figure 3 K). In addition, genes related to cellular senescence associated with RPN1 expression also included FCR1, FOXM1, CDK1, CDK4, and CHEK1, etc. ( Figure 3 L). In addition, the expression of RPN1 was also significantly associated with immune microenvironment scores, stromal scores, immune scores, and infiltration of various immune cells ( Figure 4 A, B). Further analysis showed that RPN1 had a significant correlation with the sensitivity to anti-tumor drugs, mainly including Foretinib, Mitoxantrone, Oxaliplatin, and Fludarabine, etc. ( Figure 4 C-F).

[0064] 3. RPN1 promotes cell proliferation and inhibits cell senescence The CCK-8 assay showed that knockdown of RPN1 significantly inhibited the proliferation of A549 and H1299 cells, indicating that RPN1 has a promoting effect on cell proliferation ( Figure 5 A, B). The EdU assay further verified this result. After knockdown of RPN1, the proportion of EdU-positive cells in A549 and H1299 cells decreased significantly ( Figure 5 C, D). γ-H2AX immunofluorescence analysis showed that after knockdown of RPN1, DNA damage in A549 and H1299 cells increased significantly ( Figure 5 E, F). In addition, through β-galactosidase staining analysis, we found that after knockdown of RPN1, the proportion of senescence-related β-galactosidase-positive cells in A549 and H1299 cells increased significantly ( Figure 5 G, H). ELISA results showed that knockdown of RPN1 significantly increased IL6 ( Figure 5 I) and IL8 ( Figure 5J). At the molecular level, qPCR and Western blot analyses showed that after knocking down RPN1, the expressions of CDKN1A and CDKN2A in A549 and H1299 cells were significantly upregulated ( Figure 5 K-L), and the protein expressions of their protein products P21 and P16 were also upregulated ( Figure 5 M-P). These results indicate that knocking down RPN1 promotes the senescence of lung cancer cells. Example

[0065] 1. Drug treatment: Methylation regulation: To explore the role of methylation regulation in lung cancer cells, we used two drug treatment strategies. First, 3-DAA (global m6A inhibitor) was applied to inhibit m6A methylation. 3-DAA specifically interferes with m6A methylation, reduces the RNA modification level, and then studies its effects on the growth, migration, and metastatic potential of lung cancer cells. Second, MA (FTO inhibitor) treatment was used to inhibit the activity of FTO (demethylase) to further explore the regulation of the demethylation process on the biological behavior of lung cancer cells.

[0066] AKT activation: To explore the role of the AKT signaling pathway in lung cancer cells, SC79 treatment was used. SC79 is a known AKT activator that can specifically activate AKT phosphorylation and enhance the activity of its downstream signaling pathway. By treating lung cancer cells with SC79, the effects of AKT activation on cell proliferation, survival, migration, and invasion abilities were evaluated. In this experiment, the treatment concentration and time of SC79 were set according to the conditions optimized based on previous literature and preliminary experiments.

[0067] 2. N-glycosylation analysis To study the N-glycosylation modification in lung cancer cells, we used Tunicamycin treatment and PNGase F deglycosylation experiments. Tunicamycin is a drug that inhibits N-glycosylation. By inhibiting the activity of glucosamine transferase, it blocks the N-glycosylation reaction. In this experiment, after cell treatment, Tunicamycin was used for intervention to explore the effects of N-glycosylation levels on the phenotypes and functions of lung cancer cells.

[0068] To further analyze the specific effects of glycosylation modification, we used PNGase F enzyme for deglycosylation treatment. PNGase F can remove N-linked glycans on the sugar chain, thereby revealing the potential effects of glycosylation modification on protein functions and interactions. Through Western blot and mass spectrometry analyses, combined with the protein changes before and after deglycosylation, the specific roles of N-glycosylation modification on the biological functions of lung cancer cells were evaluated.

[0069] 3. Cell proliferation CCK-8 assay: To quantitatively detect the effects of RPN1 knockdown or overexpression on the proliferation of A549 and H1299 lung cancer cells, the CCK-8 assay was used to detect cell viability. Cells were treated with CCK-8 reagent at different time points, and then their absorbance (OD value) was measured by a spectrophotometer to reflect the proliferation ability of the cells. Each experiment was set up with three biological replicates, and three technical replicates were performed at each time point.

[0070] EdU staining: To further investigate the effects of RPN1 knockdown or overexpression on de novo DNA synthesis in A549 and H1299 cells, we used the EdU staining method to label and count the proliferation rate of the cells. EdU is a nucleoside that mimics thymidine and can be incorporated by actively dividing cells during DNA synthesis. After treating the cells, the operation was carried out according to the instructions of the EdU staining kit, and images were observed and taken by a fluorescence microscope. The EdU-positive cells were counted using ImageJ software, and the cell proliferation rate was calculated.

[0071] 4. β-Galactosidase staining To evaluate the effects of RPN1 knockdown or overexpression on the senescence of A549 and H1299 cells, we used the β-galactosidase staining method. β-Galactosidase is an enzyme that is upregulated in senescent cells, and its activity is pH-dependent and can be visualized by a chromogenic substrate in an environment with a pH of 6.0. The treated cells were stained using a β-galactosidase staining kit and operated according to the manufacturer's instructions. By observing and imaging under a microscope, the proportion of stained positive cells was counted to evaluate the degree of cell senescence in different treatment groups.

[0072] 5. γ-H2AX immunofluorescence To evaluate the effects of RPN1 knockdown or overexpression on DNA damage in A549 and H1299 cells, we used γ-H2AX immunofluorescence staining. After treating the cells, immunofluorescence staining was performed using a specific antibody against γ-H2AX, and then the formation of γ-H2AX foci was observed by a fluorescence microscope. By quantitatively analyzing the number of γ-H2AX positive foci, the degree of DNA damage in cells of different treatment groups was evaluated.

[0073] 6. RNA stability experiment The RNA degradation experiment was carried out according to the method in the literature. H1299 cells transfected with pIGF2BP2 or empty vector were seeded in 6-well plates, and actinomycin D with a final concentration of 10 μg / ml was added to the culture medium. After adding actinomycin D, cells were collected at 0, 1, 2, 3, 4, and 5 hours. RNA was extracted and quantified by RT-qPCR. The RPN1 mRNA level was detected using the same primers. The Ct value was normalized to the Ct value at t = 0 to obtain the ∆Ct value (∆Ct = average Ct value at each time point - average Ct value at t = 0), and the relative abundance at each time point was calculated (mRNA abundance = 2^-∆CT).

[0074] 7. Western blot analysis To evaluate the effect of RPN1 knockdown or overexpression on the expression of related proteins in A549 and H1299 cells, we performed Western blot analysis. In the experiment, total cell proteins were extracted using RIPA lysis buffer, and the protein concentration was determined by the BCA method. Equal amounts of protein samples (usually 20 - 40 μg) were separated on a 12% SDS-PAGE gel and then transferred to a PVDF membrane. The membrane was first blocked with 5% non-fat milk powder and then incubated with specific primary antibodies against target proteins such as RPN1, IGF2BP2, PIK3CB, AKT2 / p-AKT2, FOXO3 / p-FOXO3, and P21. Then, a secondary antibody was used for detection, and chemiluminescence (ECL) imaging was performed. The relative expression levels of proteins were evaluated by quantitative analysis of the membrane images using ImageJ software.

[0075] 8. qPCR analysis To further verify the effect of RPN1 knockdown or overexpression on the gene transcription level, we used qPCR (real-time quantitative PCR) to analyze the expression of related genes. First, total RNA of cells was extracted using TRIzol reagent, and cDNA was synthesized using a reverse transcription kit. Next, real-time PCR amplification was performed using specific primers and SYBR Green PCR reagents, and appropriate amplification conditions were set. The qPCR reaction was carried out using an ABI 7500 system, and β-actin was used as an internal reference for data normalization. By comparing the Ct values (threshold cycle number) of different treatment groups, the relative expression levels of target genes were calculated.

[0076] 9. Immunofluorescence analysis To detect the effect of RPN1 knockdown or overexpression on the localization of EGFR in A549 and H1299 cells, we performed immunofluorescence analysis. First, the cells were fixed with 4% paraformaldehyde and permeabilized with 0.1% Triton X-100. Subsequently, the cells were incubated with a specific primary antibody against EGFR and detected with a fluorescently labeled secondary antibody. To analyze the membrane localization of EGFR, we used a fluorescence microscope to observe and record the intracellular distribution of EGFR. The immunofluorescence images were analyzed using ImageJ software to quantitatively analyze the membrane expression level of EGFR and evaluate whether the change in RPN1 expression affected the cell membrane localization of EGFR.

[0077] 10. Prediction of promoter binding sites To predict the binding sites of FOXO3 in the CDKN1A promoter region, we used the JASPAR 2024 database for analysis. JASPAR is a widely used tool for predicting transcription factor binding sites, which predicts the binding sites of transcription factors in the promoter regions of specific genes by calculating the affinity between transcription factors and DNA sequences. First, we extracted the promoter sequence of the CDKN1A gene from the Ensembl database and used JASPAR 2024 to predict the FOXO3 binding sites in this region.

[0078] 11. Dual-luciferase reporter gene assay To verify whether FOXO3 can bind to the CDKN1A promoter region and regulate its transcription, we performed a dual-luciferase reporter gene assay. First, a reporter plasmid containing the CDKN1A promoter region was constructed, and A549 and H1299 cells with overexpressed or knocked-down FOXO3 were transfected with this plasmid. After transfection, the luciferase activity in the cells was detected using a luciferase reporter system. By comparing the ratio of Renilla luciferase to Firefly luciferase, we evaluated the effect of FOXO3 binding to the CDKN1A promoter.

[0079] 12. meRIP-qPCR The m6A distribution in the ZNRD1-AS1 sequence was predicted using the SRAMP algorithm, a sequence-based RNA N6-methyladenosine site prediction tool. Specific primers for MeRIP analysis were designed based on high-confidence fragments. The Magna MeRIP m6A Kit (17–10499) from Millipore was used to analyze m6A modification in H1299 cells, and the specific operations followed the manufacturer's recommendations. Briefly, 150 μg of total RNA was first extracted and randomly fragmented into approximately 100-bp fragments. Then, the RNA samples were immunoprecipitated with magnetic beads coated with anti-m6A or anti-mouse IgG antibodies. Subsequently, the m6A-modified RNA fragments were eluted and analyzed by PCR and RT-qPCR. The relative enrichment of m6A was normalized to the input samples.

[0080] The results are as follows: 1. IGF2BP2 regulates RPN1 expression through m6A modification Further studies aimed to reveal the possible mechanisms underlying the upregulation of RPN1 in lung cancer cells. Through prediction using the SRAMP online tool, we identified three high-confidence m6A modification sites on RPN1 mRNA ( Figure 6 ). The results of further meRIP qPCR analysis showed that m6A modification existed at these sites, suggesting that m6A modification is involved in the regulation of RPN1 expression ( Figure 7 A,B). Based on the analysis of the correlation between the protein expression of m6A regulatory genes and the RNA expression of RPN1 in the lung cancer dataset of the CPTAC database using the PCAS tool, the results suggested that RPN1 was correlated with the m6A reader proteins YTHDF1 / 2 and IGF2BP2, especially with the highest correlation with IGF2BP2, and the correlation coefficients in LUAD and LUSC were 0.204 and 0.352, respectively ( Figure 7 C-D). qPCR experiments showed that after overexpressing IGF2BP2, the expression of RPN1 increased significantly ( Figure 7 E), and Western blot analysis further confirmed the changes in the proteins of IGF2BP2 and RPN1 ( Figure 7 F-H). In addition, the RNA stability experiment showed that overexpressing IGF2BP2 significantly prolonged the half-life of RPN1 RNA ( Figure 7 I-K). After treatment with the global methylation inhibitor 3-DAA, the expression of RPN1 was significantly downregulated, while after treatment with the FTO inhibitor MA, the expression of RPN1 was upregulated ( Figure 7 L, M). Treatment with 3-DAA rescued the upregulation of RPN1 expression caused by overexpressing IGF2BP2 ( Figure 7N, O). These results indicate that the upregulation of RPN1 in lung cancer cells is regulated by m6A modification and its reader protein IGF2BP2.

[0081] 2. RPN1 regulates cellular senescence through the AKT2 / FOXO3 pathway To further explore the downstream molecular mechanism of RPN1 in regulating cellular senescence in lung cancer cells. By analyzing the LUAD and LUSC datasets in the CPTAC database using the PCAS tool, we found that the protein expression of RPN1 was significantly correlated with the phosphorylation levels of phosphorylation sites of AKT2 ( Figure 8 A), especially the t451 phosphorylation site of AKT2 (r = 0.334, Figure 8 B). Further analysis based on the PCAS tool found that the expression of RPN1 was correlated with the phosphorylation levels of multiple phosphorylation sites of FOXO3 ( Figure 8 C), especially the s284 site (r = 0.575, Figure 8 D), indicating that RPN1 may regulate cellular senescence through AKT2 / FOXO3. Next, we analyzed the effects of knocking down RPN1 on the expression of PIK3CB, AKT2, p-AKT2, FOXO3, and p-FOXO3 in lung cancer cells by Western blot ( Figure 8 E). The results showed that knocking down RPN1 did not affect the protein levels of PIK3CB, AKT2, and FOXO3, but significantly reduced the phosphorylation levels of AKT2 and FOXO3 ( Figure 8 F-J), further supporting that RPN1 regulates cellular function through the AKT2 / FOXO3 pathway. In addition, we further verified the regulatory effect of RPN1 on the AKT2 / FOXO3 pathway using the AKT agonist SC79. The results showed that SC79 treatment significantly rescued the downregulation of p-AKT2 and p-FOXO3 caused by RPN1 knockdown ( Figure 8 K-M). Finally, the β-galactosidase staining experiment showed that SC79 treatment could partially reverse the promoting effect of knocking down RPN1 on cellular senescence ( Figure 8 N-O). In summary, RPN1 regulates cellular senescence through the AKT2 / FOXO3 signaling pathway.

[0082] 3. FOXO3 targets CDKN1A to regulate cellular senescence By analyzing the expression correlation between CDKN1A and FOXO3 in LUAD and LUSC using the TCGA database, the results showed a significant positive correlation between their expressions (r = 0.687, Figure 9A). Further analysis by the PCAS tool revealed a significant positive correlation between the expression of CDKN1A and FOXO3 in the lung cancer data of the CPTAC database (r = 0.388, Figure 9 B). In addition, based on PCAS analysis, we found a significant positive correlation between the phosphorylation levels of multiple phosphorylation sites of FOXO3 and CDKN1A RNA expression ( Figure 9 C), especially the s284 phosphorylation site (r = -0.560, Figure 9 D). Further qPCR experiments showed that knocking down RPN1 promoted the expression of CDKN1A, and SC79 treatment significantly rescued this change ( Figure 9 E). Western blot analysis further confirmed the expression changes of P21 after knocking down RPN1 and SC79 treatment, further supporting the role of FOXO3 in regulating CDKN1A expression ( Figure 9 F - G). After knocking down FOXO3 by transfecting shFOXO3, the qPCR and Western blot results showed that knocking down FOXO3 significantly inhibited the expression of CDKN1A in lung cancer cells ( Figure 9 H - K). In addition, after overexpressing FOXO3, the expression of CDKN1A was also significantly upregulated ( Figure 9 L). Through JASPAR2024 prediction analysis, we found that there were multiple binding sites of FOXO3 on the CDKN1A promoter sequence ( Figure 9 M). The further dual - luciferase reporter gene assay results showed that FOXO3 could target and bind to the CDKN1A promoter sequence, demonstrating that FOXO3 regulates its transcription by directly binding to the CDKN1A promoter ( Figure 9 N - Q). In summary, we propose that FOXO3 can regulate cellular senescence by targeting CDKN1A.

[0083] 4. RPN1 regulates EGFR membrane localization and stability through N - glycosylation modification The present invention further explored the pathway by which RPN1 regulates the AKT2 / FOXO3 pathway. First, by analyzing the CPTAC lung cancer dataset using the PCAS tool, it was found that the expression of the EGFR protein was related to multiple glycosyltransferases ( Figure 10 A), including RPN1, STT3A, MGAT1, and STT3B, suggesting that EGFR may be regulated by RPN1 glycosylation modification. To verify this hypothesis, we treated EGFR with the deglycosylase PNGase, and Western blot analysis showed that when PNGase was not treated, the EGFR band showed obvious glycosylation characteristics, and the molecular weight of EGFR changed significantly after deglycosylation treatment ( Figure 10B). Quantitative analysis results showed that knockdown of RPN1 downregulated the expression level of EGFR protein ( Figure 10 C), further demonstrating that the glycosylation modification of EGFR plays an important role in its stability and molecular weight. In addition, through immunofluorescence analysis, we found that after knockdown of RPN1, the membrane localization of EGFR was significantly reduced ( Figure 10 D-E), further supporting that RPN1 regulates the membrane localization of EGFR through glycosylation modification. After treatment with the protein synthesis inhibitor CHX and the N-glycosylation inhibitor Tunicamycin, the degradation rate of non-glycosylated EGFR was significantly accelerated, suggesting that N-glycosylation modification plays an important role in EGFR stability ( Figure 10 F-I). Collectively, the above results indicate that RPN1 regulates the membrane localization and stability of EGFR through N-glycosylation modification, thereby regulating the AKT2 / FOXO3 signaling pathway. Examples

[0084] 1. Xenograft model Five-week-old male BALB / c-nude mice were purchased from Vital River Laboratory Animal Technology Co., Ltd. (Beijing, China). All animals were housed in the Experimental Animal Center of Soochow University and managed in accordance with the NIH Guide for the Care and Use of Laboratory Animals. The experimental protocol has been approved by the Ethics Committee of the Experimental Animal Center of Soochow University. Stable knockdown A549 cells transfected with shRPN1 (about 5×10 6 cells) were subcutaneously implanted into the right abdomen of these mice (3 mice per group). At 30 days after implantation, the animals were euthanized, and the tumors were collected and photographed.

[0085] 2. Immunohistochemistry (IHC) Tissue samples were fixed with 4% paraformaldehyde, dehydrated through a series of gradient ethanol, and embedded in paraffin. 3-μm sections were deparaffinized, rehydrated, and stained with hematoxylin and eosin (H&E). For immunohistochemistry, the sections were blocked with 5% goat serum and incubated overnight at 4°C with the primary antibody. The sections were incubated with goat anti-rabbit secondary antibody at room temperature for 20 minutes, and then incubated with streptavidin-HRP for 30 minutes. After diaminobenzidine (DAB) staining, the sections were stained with hematoxylin again and dehydrated. The primary antibodies used in this immunohistochemistry experiment were from Abcam (RPN1) and other manufacturers, including p-FOXO3, P21, Ki67, EGFR, and CD31.

[0086] 3. Statistical analysis Data analysis was performed using appropriate statistical methods, specifically including Student’s t-test (for comparison between two groups) and ANOVA (for comparison among multiple groups). For two sets of data, Student’s t-test was used to test for differences, and a P-value less than 0.05 was considered statistically significant; for multiple sets of data, ANOVA was used, and post hoc tests were performed to determine differences between groups. Data visualization was carried out using GraphPad Prism for the drawing of bar charts and scatter plots, immunohistochemistry (IHC) quantitative analysis was completed through ImageJ software, and R language was used for gene set enrichment analysis (GSEA) and heat map drawing. All experiments were performed with at least three biological replicates, and the data were presented as mean ± standard deviation (Mean ± SD). The specific statistical results are shown in the figures and supplementary data.

[0087] The results showed that knocking down RPN1 inhibited the tumorigenesis of lung cancer cells The role of RPN1 in the tumorigenic ability of lung cancer cells was further verified through subcutaneous tumorigenesis experiments in nude mice. The results showed that the tumor volume formed by A549 cells with knocked-down RPN1 in nude mice was significantly smaller than that of the shNC group ( Figure 11 A). The tumor growth curve showed that the tumor growth rate of the A549 cell population with knocked-down RPN1 was significantly lower than that of the control group ( Figure 11 B). At the end point of the experiment, we compared the tumor weights of the two groups of mice, and the results showed that the tumor weight of the shRPN1 group was significantly smaller ( Figure 11 C). Immunohistochemical analysis showed that the expressions of RPN1, p-FOXO3, and EGFR proteins in the tumor tissues of the shRPN1 group were significantly lower than those of the shNC group, while P21 was significantly higher than that of the shNC group ( Figure 11 D-E). Meanwhile, the proportion of Ki67-positive cells in the tumor tissues of the shRPN1 group was significantly lower than that of the control group ( Figure 11 F). In terms of tumor angiogenesis, CD31 immunohistochemical analysis showed that the proportion of the vascular area in the tumors of the shRPN1 group was significantly lower than that of the control group ( Figure 11 G). In addition, we also constructed a subcutaneous tumorigenesis model of H1299 cells with stable knockdown of RPN1 in nude mice. The results of immunohistochemical analysis of tissue sections were consistent with those in A549. The expressions of p-FOXO3 and EGFR in the tumor tissues of the shRPN1 group were significantly lower than those of the control group, while P21 was increased ( Figure 11 H-I). Collectively, these results indicate that RPN1 promotes the tumorigenic ability of lung cancer cells by regulating cell proliferation and senescence.

[0088] Obviously, the above embodiments are merely examples given for clear illustration and are not limitations on the implementation manners. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to enumerate all the implementation manners here. And the obvious changes or modifications derived therefrom still fall within the protection scope of the present invention.

Claims

1. Use of a reagent for reducing the expression level of the RPN1 gene in the preparation of a product for preventing or treating lung cancer.

2. The application according to claim 1, wherein Comprising at least one of the following features: (1) The reagent for reducing the expression level of the RPN1 gene contains shRNA, lentivirus or an inhibitor of RPN1 gene expression; (2) The lung cancer is adenocarcinoma of the lung and / or squamous cell carcinoma of the lung; (3) The Gene ID of the RPN1 gene is 6184.

3. The application according to claim 2, characterized in that The sequence of the shRNA is as shown in SEQ ID NO.1-2.

4. A product for preventing or treating lung cancer, characterized in that, The product contains a reagent for reducing the expression level of the RPN1 gene.

5. A pharmaceutical composition for treating lung cancer, characterized in that, The pharmaceutical composition contains a reagent for reducing the expression level of the RPN1 gene.

6. Use of a reagent for detecting the expression level of the RPN1 gene in the preparation of a lung cancer detection product.

7. The application according to claim 6, wherein The reagent for detecting the expression level of the RPN1 gene contains primers for amplifying the RPN1 gene.

8. The application according to claim 6, wherein The application includes: S1. Extract genomic DNA from the sample to be tested and quantify the RPN1 gene therein; S2. Judge the risk of developing lung cancer or the prognosis risk according to the expression level of the RPN1 gene.

9. An aging lung cancer cell model, characterized in that, Obtained by reducing the expression level of the RPN1 gene in lung cancer cells and culturing them.

10. A method for promoting the senescence of lung cancer cells in vitro, characterized in that, Comprising the step of knocking out the RPN1 gene in lung cancer cells.

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