| Esophageal cancer is one of the common gastrointestinal malignancies and the eighth most common cancer worldwide.About 604,000 new cases(3.1%)of esophageal cancer were diagnosed worldwide in 2020,ranking fifth and ninth in cancer mortality among male and female patients respectively.Epidemiological studies show that more than 80% of global esophageal cancer cases and deaths occur in less developed regions,and 60% of cases originate from China.In 2020,there are about 320,000 new cases of esophageal cancer in China.Henan province has one of the highest incidence and mortality rates of esophageal cancer in China and the world,and the pathological histological type of over 90% of esophageal cancers in China is squamous cell carcinoma.Esophageal squamous cell carcinoma is characterized by high invasiveness and poor prognosis,and although multiple comprehensive treatments including surgery,radiotherapy and chemotherapy have been adopted,the five-year survival rate of patients is still less than 22%.Numerous studies have shown that the factors affecting the prognosis of patients with esophageal squamous cell carcinoma are diverse and complex.Significant geographical differences and genetic factors may play important roles in the development of esophageal carcinoma,while dietary habits,smoking,alcohol consumption,drinking water quality and even bacterial microenvironment may have an impact on the incidence and mortality of esophageal squamous cell carcinoma.The esophagus is adjacent to the oral cavity,and the epithelium is squamous epithelium,so it inevitably becomes one of the colonization sites of oral bacteria.Microbial disorders in the human digestive tract,which are composed of a variety of microorganisms,are one of the important pathogenic factors triggering the development of many diseases,and research on the microbial community of esophageal squamous cell carcinoma patients is still relatively rare.With the development of biological research,single-cell technique provides powerful technical support for analyzing the characteristics and behavior mechanism of single cell.Currently,there is still a lack of effective targeted therapy for esophageal squamous cell carcinoma.Therefore,further study of the molecular mechanism of esophageal squamous cell carcinoma and identification of specific marker molecules for esophageal squamous cell carcinoma will lay the theoretical foundation for early diagnosis and treatment of esophageal squamous cell carcinoma and development of molecular targeted therapy for esophageal squamous cell carcinoma.Therefore,it is urgent and necessary to integrate the multi-level characteristics and patterns of mRNA expression characteristics of esophageal squamous cell carcinoma,cell heterogeneity in tumor microenvironment by single cell sequencing,and microbial community composition characteristics.Therefore,a new prognostic grading system for esophageal squamous cell carcinoma is needed to make more accurate prognostic prediction,achieve more targeted treatment,and improve the prognosis of esophageal squamous cell carcinoma.To address some of the current problems in the field of esophageal squamous cell carcinoma,this paper describes the current status and biological characteristics of esophageal squamous cell carcinoma in China and abroad,and summarizes the genes,signaling pathways and biological factors involved in its development,and finds microbial markers that affect the proliferation,invasion and metastasis of ESCC.Firstly,we analyzed 16 S rDNA sequencing data of esophageal squamous cell carcinoma,identified relevant OTUs,evaluated the relative abundance and diversity of bacteria in cancer and paracancerous tissues from patients with esophageal squamous cell carcinoma and clinical samples from noncancer controls,explored the mechanisms by which bacterial microecology influences the development of ESCC,identified bacteria associated with clinicopathological features and prognostic survival of esophageal squamous cell carcinoma,and confirmed the critical role of P.gingivalis bacteria in the development of esophageal squamous cell carcinoma and are an independent influence on the prognosis of esophageal squamous cell carcinoma,and key molecules affecting the proliferation,invasion,and metastasis of ESCC were identified.The characteristics and patterns of ESCC are urgent and necessary.By analyzing single-cell RNA sequencing of seven clinical esophageal squamous cell carcinoma samples infected by P.gingivalis and uninfected controls,a total of 40,066 cells were detected,with the highest cell content being T cells;by analyzing 20,346 expressed gene profiles,1,482 differential genes were identified,with epithelial cells(26.3% in the experimental group,10% in the control group)and T cells(43.6%,49.9% in the control group)had the highest and differential content.Calculation of differentially expressed genes in P.gingivalis infected and unfected esophageal squamous cell carcinoma samples identified 1510 differentially expressed genes in epithelial cells,followed by bone marrow cells,fibroblasts and endothelial cells with 665,484 and 452 differentially expressed genes,respectively;T cells and neutrophils had fewer differentially expressed genes with only 87 and 48.T cells may be involved in and directly influence the development of esophageal squamous cell carcinoma cells through immune function,therefore,this thesis focused on the analysis of epithelial cells and T cells,and finally identified GBP1,IL6 ST,SLC20A1,and VOPP1 molecules as key molecules related to the development of esophageal squamous cell carcinoma.The main differential gene enrichment pathways were derived from the KEGG analysis of differential genes in epithelial cells and T cells,and GSEA analysis of all KEGG pathways was performed,and a total of 57 key biological pathways were identified.In addition,we performed intercellular communication analysis,and both P.gingivalis-infected and unfected esophageal squamous cell carcinoma samples had complex interactions between epithelial,fibroblastic,myeloid and endothelial cells.We then analyzed mRNA sequencing data from esophageal squamous cell carcinoma,screened differentially expressed genes using edge R software,and selected nine key genes using the rbsurv package,and subsequently focused on two of them.Finally,this study validated the expression pattern of these two genes in esophageal squamous cell carcinoma using an internal validation group including GEO database and TCGA database and two external validation groups,and found that the patients with esophageal squamous cell carcinoma with high expression of PDZK1IP1 had a worse prognosis than those with low expression,indicating that PDZK1IP1 is an unfavorable factor in the prognosis of esophageal squamous cell carcinoma.High expression of TM9SF1 had a good prognosis,suggesting that TM9SF1 is a favorable prognostic factor for esophageal squamous cell carcinoma.Then,this study applied risk factors and marker genes to construct a Nomogram model,and compared the validity and accuracy of this Nomogram model with other commonly used models.In conclusion,this study identified two key molecules PDZK1IP1 and TM9SF1 associated with the proliferation,invasion and metastasis of esophageal squamous cell carcinoma,which have clinical significance for the followup and personalized treatment of patients with esophageal squamous cell carcinoma;the Nomogram established in this study can objectively and accurately predict the prognosis of esophageal squamous cell carcinoma after esophagectomy.Finally,this study analyzed the influence and role of the cloud model algorithm in optimizing the parameter selection of LSSVM to address uncertainties.Clinical risk factors,16 S rDNA-related key molecules,key molecules derived from mRNA transcriptome data and key molecules from single-cell sequencing data sources were determined by uncertainty,and the established prognostic model of ESCC combining Cloud-LSSVM and random forest algorithm was applied and the accuracy of the model was verified.The results showed that the prognostic model of esophageal squamous cell carcinoma constructed by Cloud-LSSVM and random forest algorithm had higher prediction accuracy compared with random forest and column line graph prediction models,especially when dealing with uncertainty.In this paper,a series of studies on esophageal squamous cell carcinoma identified two key molecules associated with the development of esophageal squamous cell carcinoma,and discovered key molecules affecting the proliferation,invasion,and metastasis of esophageal squamous cell carcinoma.The results provide a theoretical basis for the prevention and control,diagnosis and treatment,and prognosis of esophageal squamous cell carcinoma,and also apply artificial intelligence algorithms to establish a prognostic model of ESCC combining CloudLSSVM and random forest algorithm,which provides new research models and methods for accurate molecular typing,clinical diagnosis and prognostic assessment of ESCC. |
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