Analysis Of Clinical Characteristics Of Hepatocellular Carcinoma And The Establishment And Validation Of Nomogram For Discriminating Between Intrahepatic Cholangiocarcinoma And Hepatocellular Carcinoma

BackgroundLiver cancer is the sixth most common cancer and the third leading cause of cancer-related death worldwide.Hepatitis B virus infection is a common cause of liver cancer.There are more patients with hepatitis B in China,and more than half of the new cases of liver cancer around the world occur in China each year.Therefore,the situation of prevention and treatment of liver cancer is more severe,with the fourth prevalence rate and the second death rate in our country.Liver cancer includes Hepatocellular carcinoma(HCC)and Intrahepatic cholangiocarcinoma(ICC),as well as mixed hepatocellular-cholangiocarcinoma carcinoma according to different cell origin.Among them,HCC is the main type,accounting for 75%to 85%.While ICC derived from the epithelial cell of intrahepatic bile duct which is the second common liver malignancy,making up about 10%to 15%.We have long been committed to the diagnosis,evaluation and differential diagnosis of HCC and other diseases.Regarding the diagnosis of HCC,some researchers in our research group have obtained some results and published them publicly.As a member of the research group,I mainly focus on the evaluation of HCC and the effective distinction between HCC and ICC.The tumor differentiation and microvascular invasion(MVI)of hepatocellular carcinoma are closely related to the severity and prognosis of the disease.The diagnosis of tumor differentiation and MVI mainly depends on pathological examination.Moreover,because the treatment methods and prognosis of ICC and HCC are different but the clinical symptoms are similar,it is very important to effectively distinguish ICC and HCC before operation.Based on the above research background,our study is divided into four parts.Part 1.The Correlation between Tumor Markers and Tumor Differentiation of Hepatocellular CarcinomaObjective:To investigate the relationship between tumor markers commonly used in the diagnosis of hepatocellular carcinoma and tumor differentiation.Methods:A total of 1188 patients with HCC who received curative surgery at Shandong Provincial Hospital between January 2016 and August 2021 were included in this study.The inclusion criteria entailed pathologically confirmed HCC patients without preoperative treatments.The degree of tumor differentiation was divided into four grades according to Edmondson-Steiner grading method.The clinical features and blood test results of HCC were analyzed.The differences of tumor markers(such as AFP,AFP-L3%,PIVKA-Ⅱ,CA199,CA125 and CEA)in hepatocellular carcinoma with different differentiation were analyzed.The correlation between tumor markers and the differentiation of hepatocellular carcinoma was analyzed by ordered logistic regression analysis.At the same time,through smooth curve fitting,study whether there was a nonlinear relationship between tumor markers and tumor cell differentiation.If there was a nonlinear relationship,the threshold effect or saturation effect was further analyzed.Results:The risk factors related to the tumor differentiation included log AFP,log AFP-L3%logarithm(log AFP-L3%)and log PIVKA-Ⅱ.The effect values OR(95%CI)were 1.27(1.2,1.34)、1.15(1.06,1.26)and 1.15(1.09,1.22)respectively;The patients were divided into early stage and moderately advanced stage liver cancer according to the international staging standard of hepatocellular carcinoma-BCLC(Barcelona Clinic Liver Cancer)staging.The results showed that log AFP and log PIVKA-Ⅱ were risk factors affecting the malignancy of liver cancer regardless of the stage of liver cancer;Log AFP-L3%was only the risk factor affecting the differentiation degree of early hepatocellular carcinoma;There was a nonlinear relationship and threshold effect between tumor differentiation and log AFP and log PIVKA-Ⅱ.Conclusion:This study found various independent risk factors affecting tumor differentiation,which provided a basis for the follow-up evaluation of tumor condition.Part 2.Establish and Verify the Diagnosis Model of Microvascular Invasion in Hepatocellular Carcinoma Based on TCGA Database GenomicsObjective:Microvascular invasion(MVI)is highly correlated with poor prognosis of hepatocellular carcinoma(HCC)patients,and there is no ideal method for the diagnosis of MVI at present.At the same time,there are few studies on genetic changes of HCC patients with MVI.Based on TCGA data,this study screened the key genes that affect the occurrence of MVI in hepatocellular carcinoma and established a genomic diagnostic model to assess the risk of MVI.Methods:The gene expression profile and clinical data of HCC patients were downloaded from TCGA database.Wilcoxon test combined with Cox regression analysis were used to screen the genes differentially expressed between HCC patients with and without MVI and affecting tumor prognosis.For these differential genes,the LASSO regression analysis was used to screen the key genes and build a diagnostic model.The subjects were divided into the development group and validation group according to 3:1.The differentiation and clinical application value of the diagnostic model were evaluated using the ROC curve and DCA curve,and the stability of the diagnostic model was evaluated using bootstrap(resampling 500 times)for internal validation.Finally,combined with the results of gene enrichment analysis,we selected two genes,namely HOXD9 and TFAP2A,from the key genes affecting the occurrence of MVI,and used 100 tumor tissues with or without MVI to verify their protein expression level.Results:This study screened 36 differentially expressed genes between HCC patients with and without MVI,which all affected the survival time of HCC patients.The area under the ROC curve(AUC)in training cohort and validation cohort was 0.827(95%CI 0.768～0.886)and 0.857(95%CI 0.756～0.957)respectively.Clinical decision curve analysis(DCA)revealed that the diagnostic model had important clinical application value.The score calculated by the diagnostic model significantly affected the survival time of HCC patients.Finally,the expression of two key genes,HOXD9 and TFAP2A,was verified using tumor tissues from 100 HCC patients.The results showed that compared with HCC patients without MVI,HOXD9 was highly expressed in tumor tissues of patients with MVI,which was consistent with the trend of gene expression in TCGA database.Conclusion:Based on TCGA database genomics,this study established and verified the diagnostic model for preoperative evaluation of the MVI risk in HCC patients.The prognostic value of the key genes affecting the occurrence of MVI on HCC patients was studied.This has important reference value for further study of the pathogenesis of MVI.Part 3.Establishment and Validation of Diagnostic Model of Microvascular Invasion in Hepatocellular Carcinoma Based on Clinical DataObjective:We aimed to establish a preoperative diagnostic model of microvascular invasion(MVI)for hepatocellular carcinoma based on the clinical characteristics and serum detectors of liver cancer patients.Methods:A total of 1027 patients with HCC hospitalized at Shandong Provincial Hospital between January 2016 and August 2021 were included and randomly divided into development and validation groups in a ratio of 3-to-1.Independent sample t test,Mann-Whitney U test,Chi-square test and Fisher exact test were applied to assess the difference of clinical characteristics and serum index results between the two cohorts.Univariate and multivariate analyses were performed to determine the independent risk factors of HCC patients with and without microvascular invasion.By using these independent risk factors,the preoperative diagnostic nomogram of MVI was established and verified.The discrimination and clinical application of the nomogram were estimated by using receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis(DCA).In addition,the value of this diagnostic model in diagnosing microvascular invasion in different stages of hepatocellular carcinoma was further discussed.Results:Through multivariate and multivariate analyses,independent risk factors for MVI of HCC involved Hepatitis B virus infection(HBV),large tumor diameter,higher logarithm of Alpha-fetoprotein(Log AFP),logarithm of protein induced by vitamin K absence or antagonist-Ⅱ(Log PIVKA-Ⅱ),logarithm of AFP-L3%(Log AFP-L3%)and logarithm of Carbohydrate antigen 125(Log CA125).A nomogram incorporating these six independent risk factors was finally established.The areas under the ROC curve(AUC)assessed by the nomogram for MVI of HCC in training cohort and validation cohort were 0.806(95%CI,0.773～0.839)and 0.818(95%CI,0.763～0.874)respectively.The calibration curve showed that the evaluation of MVI for hepatocellular carcinoma using our established diagnostic model was highly consistent with the postoperative pathological results.The decision curve analysis(DCA)revealed promising clinical application of the diagnostic nomogram.Moreover,we also found that this diagnostic model had better application value in hepatocellular carcinoma with higher malignancy.Conclusion:An effective preoperative diagnostic model based on clinical characters and tumor markers for MVI of HCC has been established,which is of great significance for MVI diagnosis.Part 4.The Establishment and Validation of Nomogram for Discriminating Intrahepatic Cholangiocarcinoma from Hepatocellular CarcinomaObjective:To establish a nomogram and provide a simple and effective method to distinguish between intrahepatic cholangiocarcinoma(ICC)and hepatocellular carcinoma(HCC).Methods:A total of 1591 patients with HCC or ICC hospitalized at Shandong Provincial Hospital between January 2016 and August 2021 were included and randomly divided into development and validation groups in a ratio of 3-to-1.Univariate and multivariate analyses were performed to determine the independent differential factors between HCC and ICC patients in the development cohort.By combining these independent differential factors,the nomogram was established for discriminating ICC from HCC.The accuracy of the nomogram was estimated by using receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis(DCA).Furthermore,the value of this diagnostic model distinguishing between ICC and HCC was assessed in different stages of hepatocellular carcinoma.Results:Through multivariate analysis,independent differential factors between HCC and ICC involved Hepatitis B virus(HBV),logarithm of Alpha-fetoprotein(Log AFP),logarithm of protein induced by vitamin K absence or antagonist-Ⅱ(Log PIVKA-Ⅱ),logarithm of Carbohydrate antigen 199(Log CA199)and logarithm of Carbohydrate antigen 125(Log CA125).A nomogram was finally established by incorporating these five independent differential factors.Comparing a model of conventional tumor biomarkers including AFP and CA199,the nomogram showed a better distinction between ICC and HCC.The area under the ROC curve(AUC)of ICC diagnosis was 0.951(95%CI,0.938～0.964)for the nomogram.The results were consistent in the validation cohort with an AUC of 0.958(95%CI,0.938～0.978).The calibration curves of the development and validation groups showed that using the nomogram we established to distinguish ICC and HCC had high consistency with the actual pathological results.After integrating patient preferences into the analysis,the DCA showed that using this nomogram to distinguish ICC and HCC increased more benefit compared with the conventional model.In addition,it was found that the diagnostic model was not affected by the stage of liver cancer and had high application value in all stages of liver cancer.Conclusion:An efficient nomogram has been established for the differential diagnosis between ICC and HCC,which may facilitate the detection and diagnosis of ICC.This conclusion has been confirmed in different stages of liver cancer.