Clinical And Potential Mechanism Research On Constructing The Prognosis Model Of Hepatocellular Carcinoma Lased On Autophagy Related LncRNA And Systemic Inflammatory Response Markers

Hepatocellular carcinoma(HCC)is one of the most common malignant tumors in the world.Due to its biological characteristics such as high invasiveness,intrahepatic and extrahepatic recurrence and metastasis are prone to occur.The overall survival benefit of HCC patients is still limited,and it is the third cause of cancer-related death.Due to the high heterogeneity of HCC,patients are prone to chemotherapy resistance and postoperative metastasis and recurrence.Therefore,there is an urgent need to explore the molecular mechanism of HCC occurrence and find precise targets for early diagnosis and treatment to improve the prognosis and survival rate of HCC patients.It is also urgent to explore and discover reliable and accurate HCC prognostic biomarkers to improve the risk prediction ability and accuracy,so as to improve the ability of risk prediction and help clinicians formulate individualized treatment plans to improve the survival of patients.Autophagy is a multi-step lysosomal degradation process,that is,under the conditions of environmental pressure and stimulation,cells form autophagosomes to remove damaged organelles,protein aggregates and intracellular pathogens through lysosomal degradation,so as to meet their own metabolic needs and update organelles.This physiological process is crucial for cell survival,differentiation,development and regulation to maintain the stability of the intracellular environment.The autophagy process has been shown to be involved in the pathophysiology of various diseases,such as neurodegenerative diseases,aging and cancer.Especially in advanced stages of cancer,dysregulation of autophagy can promote the rapid proliferation of tumor cells.More and more research evidences show that autophagy dysregulation is closely related to the pathogenesis of liver diseases(fatty liver,cirrhosis,etc.),especially HCC.Specific autophagy-related genes can be established as potential therapeutic targets for cancer.In addition,inflammatory responses have been recognized as a cancer feature,and evidence suggests that systemic inflammatory responses play a crucial role in the initiation,progression,metastasis,treatment resistance of malignancies,and is associated with poor prognosis of tumors.Inflammatory response can induce tumor proliferation and metastasis by promoting angiogenesis,destroying DNA structure and inhibiting cell apoptosis,which can cause the upregulation of cytokines and inflammatory mediators.The degree of inflammatory cell infiltration and tumor purity in the tumor microenvironment of HCC are closely related to malignant tumor invasion and high recurrence risk.The systemic inflammatory response in patients with malignant tumors can be manifested as changes in peripheral blood cell counts,including changes in the values of neutrophils,lymphocytes,monocytes,platelets,and globulin.These inflammatory response markers have been proved to be independent prognostic factors in various malignancies and can be used to predict the prognosis of HCC patients.Long non-coding RNA(lncRNA)is defined an RNA transcript with a length of more than 200 nucleotides that cannot encode protein and is judged to have no effect at an early stage.Subsequent studies have found that lncRNA participate in a variety of signal transduction and regulation processes,play the biological functions of scaffold,decoy,guide and signal,and participate in the regulation of gene expression,RNA decay,microRNA regulation and protein folding.In recent years,the research hotspot in the field of cancer has focused on lncRNA.It has been found that a variety of lncRNA are differentially expressed in tumors,and the abnormal expression of lncRNA is closely related to the occurrence,progression and prognosis of cancer.It is involved in the regulation of various biological processes and even the regulation of key points in the occurrence and development of malignant tumors,including the effect on autophagy level and inflammatory cell infiltration.With the rapid progress of high-throughput RNA sequencing technology,the potential of using lncRNA as biomarkers to assist cancer detection,treatment,or predict cancer prognosis has gradually emerged.In the first part of this study,we first analyzed and integrated the data from the Cancer Genome Atlas(TCGA)and the International Cancer Genome Consortium(ICGC)database,screened and identified four autophagy-related lncRNA(BACE1-AS,SNHG3,MIR210HG and ZEB1-AS1)are closely related to the prognosis and survival of HCC,and based on this,a prediction model for the prognosis and survival of liver cancer was constructed.The study confirmed that the model can accurately predict the clinical outcome of HCC patients and the verification is reliable.Functional analysis showed that lncRNA expressed in high-risk patients were mainly enriched in autophagy and cancer-related pathways.The ssGSEA analysis showed that the inflammatory reaction,immune infiltration,and tumor purity in the HCC tumor microenvironment were closely related to the malignant invasion and high risk of tumor recurrence.Although the prognosis of HCC can be better assessed by means of bioinformatics analysis and molecular genetic techniques,its clinical value is often limited in practice due to invasive procedures and complex laboratory detection techniques.Therefore,in the second part of this study,we focus more on finding simple and objective preoperative indicators in clinical practice to construct a predictive model for predicting the prognosis and survival of HCC.Considering that the systemic inflammatory reaction in HCC patients can be manifested as changes in peripheral blood cell counts,including changes in neutrophils,lymphocytes,monocytes,platelets,and white/globulin values.Based on these cell counts,markers of peripheral inflammatory responses include albumin-to-globulin ratio(AGR),neutrophil-to-lymphocyte ratio(NLR),lymphocyte-to-monocyte ratio(LMR),and platelet-to-lymphocyte ratio(PLR)have been respectively proved to be independent prognostic factors in malignant tumors and can be used to predict the prognosis of HCC patients.However,previous studies only focused on one or two of the inflammatory response markers,and no studies have evaluated the clinical significance of all inflammatory markers including AGR and the prognosis of HCC,especially in HCC patients treated with MWA.The nomogram based on multiple independent risk factors is a statistical model with high reliability.Therefore,the second part of our clinical study comprehensively explored the prognostic significance and accuracy of preoperative systemic inflammatory response markers AGR,NLR,LMR and PLR in HCC,and screened out relevant independent predictors to establish a nomogram to predict acceptance overall survival of HCC patients after MWA treatment.The first and second parts of this study rely on bioinformatics analysis and clinical laboratory examination indicators respectively,based on autophagy-related lncRNA and systemic inflammatory response markers to construct a liver cancer prognosis model and verify it.In the third part,our main aim is to explore the potential target genes that play a bridging role in the regulation of associated with autophagy and inflammatory in HCC.We screened and integrated HCC patient datasets from TCGA database,ICGC database and Gene Expression Omnibus database(GEO),combined with the screening results of the first part of this study,and obtained the only autophagy-inflammation-related lncRNA ZEB1 through co-expression network analysis.It has been preliminarily confirmed in vivo and in vitro that the lncRNA ZEB1-AS1 promotes the proliferation and invasion of hepatocellular carcinoma cells through synergistic autophagy and inflammation,providing new insights for further research on the molecular mechanism of HCC and clinical immunotherapy.Part 1 Development and Validation of a Prognostic Signature Associated with Tumor Microenvironment Based on Autophagy-Related lncRNA Analysis in Hepatocellular Carcinoma.Objective:The present study aimed to establish a prognostic signature based on the autophagyrelated long non-coding RNAs(lncRNAs)analysis in patients with hepatocellular carcinoma(HCC).Methods:Patients with HCC from The Cancer Genome Atlas(TCGA)were taken as the training cohort,and patients from the International Cancer Genome Consortium(ICGC)were treated as the validation cohort.Autophagy-related lncRNAs were obtained via a co-expression network analysis.Based on the data of the experimental group,a risk scoring model was constructed by screening according to univariate and multivariate analysis.According to the median value of the score,all patients were divided into high-risk group and low risk group.The prediction of the model on the prognosis of patients was further verified in the experimental group and the validation group.The prediction ability and accuracy were evaluated by receiver operating characteristic curve(ROC)and principal component analysis(PCA).Functional analysis was used to explore its detailed function.Single sample gene set enrichment analysis(ssGSEA)score was used to evaluate the tumor microenvironment and compare the expression levels of immunotherapy and targeted therapy targets in the two risk groups.Finally,a nomogram was constructed by combining the independent prognostic significance of the clinicopathological parameters and the risk score to predict the prognosis and survival of HCC.Results:Four autophagy-related lncRNAs were identified to establish a prognostic signature,which separated patients into high-and low-risk groups.Survival analysis showed that patients in the high-risk group had a shorter survival time in both cohorts.A time-independent receiveroperating characteristic(ROC)curve and principal component analysis(PCA)confirmed that the prognostic signature had a robust predictive power and reliability in both cohorts.Functional analysis indicated that the expressed genes in the high-risk group are mainly enriched in autophagy-and cancer-related pathways.ssGSEA revealed that the different risk groups were associated with the tumor microenvironment.Moreover,the different risk groups had positive correlations with the expressions of specific mutant genes.Multivariate analysis showed that the risk score also exhibited excellent predictive power irrespective of clinicopathological characteristics in both cohorts.A nomogram was established.The nomogram showed good discrimination,with Harrell’s concordance index(C-index)of 0.739 and good calibration.Conclusion:The four autophagy-related lncRNAs could be used as biological biomarkers and therapeutic targets in HCC patients.The prognostic signature and nomogram might aid clinicians in individual treatment optimization and clinical decision-making for patients with HCC.Part 2 A clinical study of prognostic signifcance of preoperative systemic infammatory biomarkers in patients with hepatocellular carcinoma after microwave ablation and establishment of a nomogram.Objective:This study aimed to construct a prognostic model of hepatocellular carcinoma(HCC)patients based on preoperative systemic inflammatory response markers,and to evaluate its predictive value and significance in the prognosis of HCC patients treated with microwave ablation(MWA).Methods:The data of HCC patients who received MWA as initial treatment from December 2011 to September 2018 in the Department of Hepatobiliary Surgery,Jingzhou Hospital Affiliated to Yangtze University were retrospectively analyzed.A total of 276 cases were enrolled.Based on preoperative systemic inflammatory response markers including albumin/globulin ratio(AGR),neutrophils to lymphocytes ratio(NLR),lymphocyte to monocyte ratio(LMR)and platelet to lymphocyte ratio(PLR),the time-dependent receiver operating characteristic curve(ROC)was used to detect the predictive value of each index on the prognosis of patients with liver cancer.All patients were divided into high-risk and low-risk groups based on the median values of systemic inflammatory response markers.Kaplan-Meier(K-M)survival analysis and univariate Cox proportional hazards model were used to explore the relationship between inflammatory response markers and clinicopathological indicators and prognosis of patients.In multivariate analysis,each index with independent prognostic value was further screened,and a prognostic nomogram was constructed based on these independent predictors.ROC curves,Harrell index of concordance(C-index),and calibration plots were used to evaluate the performance characteristics of the nomogram.Based on the established nomogram,each enrolled patient was assigned a mortality risk stratification score.The patients were further divided into high-risk group and low-risk group according to the median value of risk score,the K-M curve was used to compare the survival of the two groups,and the difference was judged by the log rank test.In addition,all conclusions we performed external validation in the validation group.Finally,we compared the discriminative power of the nomogram model,Barcelona Clinic Liver Cancer Stage(BCLC)and tumor size in predicting 1-,3-,and 5-year survival based on ROC curves in all sample cohorts.Results:192 HCC patients who received MWA as initial treatment were included in the experimental cohort and 84 patients were included in the validation cohort.K-M method and univariate analysis showed that AGR,NLR,LMR and PLR were significantly associated with the prognosis of HCC patients in each group.Multivariate analysis of the included patients’clinicopathological characteristics screened out ascites,tumor size,tumor thrombus,AGR and PLR as independent risk factors affecting the prognosis of patients with liver cancer.Based on these independent risk factors affecting the prognosis of HCC patients,we established a nomogram for predicting OS.The C-index was 0.794 in the experimental cohort and 0.772 in the validation cohort.The calibration chart confirms that the nomogram can accurately assess the prognosis of liver cancer patients in both the experimental group and the validation group,and its performance is good.Compared with BCLC clinical liver cancer stage and tumor size alone,nomogram showed better predictive power.Finally,we also found that that compared with the combination of existing clinical models and tumor size,nomogram also has higher diagnostic accuracy in predicting postoperative clinical outcomes.Conclusion:Preoperative systemic inflammatory response markers AGR,NLR,LMR and PLR are closely related to the prognosis of HCC patients after MWA.The nomogram constructed based on this and clinicopathological characteristics of ascites,tumor size and tumor thrombus can accurately predict the prognosis of liver cancer patients,and can provide support for clinicians in individual treatment optimization and clinical decision-making of liver cancer patients after MWA treatment.Part 3 The mechanism of lncRNA ZEB1-AS1 promoting hepatocellular carcinoma cell proliferation and invasion through synergistic autophagy and inflammatory responseObjective:In this study,the lncRNA ZEB1-AS1 was screened in the prognostic model in the early stage,and it was used as the research object to explore the potential mechanism of lncRNA ZEB1-AS1 bridging synergistic autophagy and inflammatory response in regulating the proliferation of hepatoma cell through in vitro and in vivo experiments.Methods:The HCC patient datasets from TCGA,ICGC and GEO database were screened,and the autophagy-inflammation-related lncRNA ZEB1-AS1 was obtained by co-expression network analysis.The expression levels of ZEB1-AS1 in 70 HCC tissues and corresponding adjacent tissues were detected by Real-time PCR,and they were divided into high-risk and lowrisk groups according to t the median value of ZEB1-AS1 expression.K-M survival curve was used to analyze the overall survival prognosis between the two groups.Immunohistochemistry was used to analyze the tumor invasion,proliferation activity and microvascular invasion of HCC tissues in the two groups.Real-time PCR was used to detect the expression of ZEB1-AS1 in hepatocyte cell L02 and hepatoma cells Hep3B and HepG2;ZEB1-AS1 overexpression plasmid was constructed to transfect HepG2 and verify the transfection efficiency,CCK-8 and Western blot evaluated the effect of overexpression of ZEB1-AS1 on the proliferation of HepG2,and ELISA detected related inflammatory cytokines.The expression of autophagy marker protein(LC3-Ⅱ/Ⅰ)in HepG2 after overexpression of ZEB1-AS1 was analyzed by immunofluorescence assay and Western blot.HepG2 and nude mouse experiments verified the effects of ZEB1-AS1 on Atg5/7 expression and the effects of ZEB1-AS1 and Atg7 on HCC autophagy and proliferation.Results:The expression level of ZEB1-AS1 in HCC tissues was higher than that in adjacent tissues,and the difference was statistically significant(P<0.05).It was significantly correlated with inflammation,tumor invasion,proliferative activity and microvascular infiltration,and overexpression of ZEB1-AS1 significantly stimulated the proliferation ability and release of inflammatory cytokines of HepG2(P<0.05).it also increases the conversion of LC3-I to LC3Ⅱ and promotes the occurrence of autophagy(P<0.05).Overexpression of ZEB1-AS1 can upregulate the expression of Atg7,and HCC autophagy and proliferation are enhanced.Conclusion:The high expression of ZEB1-AS1 is significantly correlated with the poor prognosis of HCC.Upregulation of ZEB1-AS1 can induce the proliferation and autophagy of hepatoma cells and is closely related to the inflammatory response.ZEB1-AS1 can induce the autophagy of hepatoma cells by up-regulating the expression of Atg7.ZEB1-AS1 may play a bridging role to coordinately regulate inflammatory response and autophagy in the tumor microenvironment,and play the role as a pro-oncogene in the progression of HCC.