| BackgroundLung cancer has the highest death rate in both sexes worldwide and is second only to prostate cancer in men and breast cancer in women,according to a study published in the journal CA-Cancer J Clin.In China,the mortality and morbidity of lung cancer rank the first among male patients and the highest among female patients.Therefore,the diagnosis and treatment of lung cancer has become an important social medical problem.Lung cancer is divided into non-small cell lung cancer(about 85%)and small cell lung cancer,while lung adenocarcinoma accounts for about 50% of lung cancer,and the incidence of nonsmoking female patients has a trend of increasing year by year.With the complex change of atmospheric environment and local adjustment of population structure,the prevention and diagnosis of lung cancer face new challenges.As the early symptoms of lung cancer patients are not obvious,patients have been in the middle and late stage of medical treatment,more than 50% of patients have multiple metastases.The five-year survival rate for patients seen early is 55%,compared with less than 20 percent for the overall lung cancer population.Therefore,early screening,early diagnosis and early treatment are important measures for the treatment of lung cancer patients.At present,the early screening of lung cancer patients mainly includes imaging examination and serological biomarkers.The specificity and sensitivity of biomarkers still need to be further verified in clinical practice.The NEJM study found that low-dose spiral CT,compared with chest radiography,improved the survival rate of patients and played an important role in the screening of early lung cancer.However,the contradiction between artificial intelligence and clinicians in reading the images,high false positive and radiation problems also reveal the shortcomings of low-dose spiral CT in early screening.With the development of big data and high-throughput sequencing,imaging combined with genome,proteome,metabolome and other biological big data has become a new direction for early lung cancer screening.Protein is the material basis of life and the main undertaker of life activities.It is mainly degraded by two pathways,including ubiquitination and lysosomal degradation.And 80-90% of proteins in cells are degraded by the ubiquitin pathway.ubiquitin is an evolutionarily conserved protein that degrades post-translational marker proteins.ubiquitin is first activated by the ubiquitin-activating enzyme E1 and then transferred to the ubiquitinconjugating enzyme E2.Subsequently,ubiquitin ligase enzyme E3 interacts with ubiquitin’s E2 binding enzyme and substrate protein simultaneously,and mediates covalently conjugated peptide bond formation between the C-terminal of ubiquitin and the substrate lysine.In addition,ubiquitination plays an important role in various diseases such as cancer and metabolic syndrome.Ubiquitination functions in cancer progression through a variety of pathways:(1)The production of proteins that promote angiogenesis and tumor development;(2)Deterioration is caused by dysregulation of cell death and inflammatory pathways;(3)Activation of PI3K-AKT signaling pathway supports tumorigenesis;(4)Dysfunctional NF-κB is associated with the development of malignant tumors;(5)Regulate signaling pathways and transcription factors related to cancer metabolism;(6)Regulate metabolic enzymes through ubiquitination and deubiquitination in cancer metabolism.There is increasing evidence that the ubiquitin-proteasome system plays an important role in the development and progression of lung adenocarcinoma.However,reliable prognostic features based on ubiquitination have not been established in lung adenocarcinoma.Objectives:To explore the potential biological role of ubiquitination in lung adenocarcinoma.Based on bioinformatics and artificial intelligence algorithm to explore its function and clinical application value.To study the differential characteristics and biological functions of ubiquitination stratification in the multiomics of lung adenocarcinoma genome,transcriptome,and methylation group,and to integrate the multiomics data to identify new biomarkers and potential targets,can improve the clinical stratification of patient management and medication.Methods:Omics data related to lung adenocarcinoma were downloaded from public databases GEO and TCGA,and principal component analysis was used to explore the characteristics of ubiquitination genes in lung adenocarcinoma and paracancer tissues.Univariate Cox regression was used to screen ubiquitin molecules associated with prognosis of lung adenocarcinoma.Multivariate cox regression and lasso regression were used to construct the optimal ubiquitination prognostic model of lung adenocarcinoma.The prognosis risk of patients with lung adenocarcinoma was evaluated quantitatively by constructing a histogram.Correlation analysis,protein network interaction and gene set enrichment analysis of ubiquitination model molecules were conducted to explore biological characteristics.R software was used to analyze the biological pathways of the ubiquitination model related molecules by GO,KEGG and GSEA.Cibersort,Quantiseq,x Cell,and ss GSEA immunoinfiltration algorithms were used to evaluate differences in ubiquitination stratification of immune cell infiltration and immune response in lung adenocarcinoma patients.R Software’s maftools package analyzes and visualizes mutation data in patients with lung adenocarcinoma.Comutation of the gene was calculated by somatic cell interaction function.Consensus Cluster Plus package based on unsupervised clustering algorithm was used to analyze the potential relationship between methylation cluster group and ubiquitination stratification among 307 selected methylation sites.Finally,the "p RRophetic" package based on the Cancer Genome Project database was used to predict drug response sensitivity in ubiquitination stratification and TMB/ immune score subgroups.Results:We screened 181 coexpressed ubiquitination genes in several lung adenocarcinoma cocogenes,which are mainly involved in the post-translational modification of ubiquitination protease hydrolysis and play roles in both cytoplasm and nucleus.Interestingly,ubiquitination genes exhibit different characteristics in lung adenocarcinoma and paracancer tissues.In the lung adenocarcinoma patients in the TCGA database,26 ubiquitination molecules related to prognosis of lung adenocarcinoma patients were screened,including14 protective genes and 12 risk factors.At the same time,a ubiquitination prognosis model of gene 9 was constructed,including USP29,MPP7,TRIM40,HERC1,TLE1,ASB2,NEDD1,USP44 and PHF1.It was found that 9 gene is involved in neurotrophic factor signaling pathway,cancer and RIG I receptor signaling pathway affect the progression of lung adenocarcinoma.In addition,with the increase of the ubiquitination model score,the survival time of lung adenocarcinoma patients was gradually shortened and the number of patients who died was gradually increased.Ubiquitination stratification has a significant difference in the survival of lung adenocarcinoma,and the area under the ROC curve of the ubiquitination model is significantly better than other clinical indicators.Meanwhile,the ubiquitination model can be used as an independent risk indicator to evaluate the prognosis of patients,and the survival of patients can be evaluated more comprehensively and accurately combined with other clinical indicators.Ubiquitination prognostic model not only has a good evaluation function in early and late-stage lung adenocarcinoma patients,but also is widely applicable to multiple external lung adenocarcinoma coorporates,with stability and universality.The risk score of the ubiquitination model was correlated with multiple clinical indicators,and the risk score gradually increased with the degree of invasion,lymph node and distant metastasis of lung adenocarcinoma.A column graph was constructed based on multiple clinical indicators such as age,gender and clinical stage to provide a basis for evaluating the survival time of patients.In addition,ubiquitination stratification may reflect the immune infiltration and response status of the patient.Patients in the low-risk group had multiple immune cells and a more active immune response,while those in the high-risk group,by contrast,reflected the immune status of patients on immunotherapy.The high-risk group with ubiquitination stratified had higher immune mutant spectrum and tumor mutant load,and combined with immune score could better evaluate the survival and prognosis of patients.Meanwhile,in the cluster of candidate methylation sites,hypermethylation showed protective characteristics for lung adenocarcinoma patients,with low-risk scores and longer survival time of patients.The difference in response levels of targeted drugs and chemotherapy drugs in different ubiquitination subgroups provides the basis for individualized treatment and precision treatment of patients,and drugs targeting ubiquitin and proteasome will be an effective drug candidate for the treatment of lung adenocarcinoma.Conclusion:In this study,we screened ubiquitination genes associated with the prognosis of lung adenocarcinoma patients,and constructed a prognostic model of ubiquitination-related genes using lasso algorithm.The performance of this model is superior to other clinical indicators,and its stratification is significantly correlated with the survival of patients,which provides an important guiding basis for the prognosis assessment of lung adenocarcinoma patients in the real world.In addition,the stratification of the ubiquitination model can reflect the level of immune cell infiltration and response of the patient,showing a variety of immune cell infiltration in the low-risk group.At the same time,the high-risk group exhibited higher mutations,and hypermethylation of candidate methylation sites demonstrated a better prognosis for lung adenocarcinoma patients.Importantly,combined with immune infiltration and mutation characteristics,methylation levels of candidate methylation sites and other omics characteristics,can provide comprehensive and accurate information feedback for the prognosis of lung adenocarcinoma patients,and play an important role in drug screening and treatment of lung adenocarcinoma patients. |
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