Dataset Information

Diagnosis and prognosis models for hepatocellular carcinoma patient's management based on tumor mutation burden.

ABSTRACT:

Introduction

The development and prognosis of HCC involve complex molecular mechanisms, which affect the effectiveness of its treatment strategies. Tumor mutational burden (TMB) is related to the efficacy of immunotherapy, but the prognostic role of TMB-related genes in HCC has not yet been determined clearly.

Objectives

In this study, we identified TMB-specific genes with good prognostic value to build diagnostic and prognostic models and provide guidance for the treatment of HCC patients.

Methods

Weighted gene co-expression network analysis (WGCNA) was applied to identify the TMB-specific genes. And LASSO method and Cox regression were used in establishing the prognostic model.

Results

The prognostic model based on SMG5 and MRPL9 showed patients with higher prognostic risk had a remarkedly poorer survival probability than their counterparts with lower prognostic risk in both a TCGA cohort (P < 0.001, HR = 1.93) and an ICGC cohort (P < 0.001, HR = 3.58). In addition, higher infiltrating fractions of memory B cells, M0 macrophages, neutrophils, activated memory CD4 + T cells, follicular helper T cells and regulatory T cells and higher expression of B7H3, CTLA4, PD1, and TIM3 were present in the high-risk group than in the low-risk group (P < 0.05). Patients with high prognostic risk had higher resistance to some chemotherapy and targeted drugs, such as methotrexate, vinblastine and erlotinib, than those with low prognostic risk (P < 0.05). And a diagnostic model considering two genes was able to accurately distinguish patients with HCC from normal samples and those with dysplastic nodules. In addition, knockdown of SMG5 and MRPL9 was determined to significantly inhibit cell proliferation and migration in HCC.

Conclusion

Our study helps to select patients suitable for chemotherapy, targeted drugs and immunotherapy and provide new ideas for developing treatment strategies to improve disease outcomes in HCC patients.

SUBMITTER: Tang B

PROVIDER: S-EPMC8463909 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundHepatocellular carcinoma (HCC) was the sixth common malignancies characteristic with highly aggressive in the world. It was well established that tumor mutation burden (TMB) act as indicator of immunotherapeutic responsiveness in various tumors. However, the role of TMB in tumor immune microenvironment (TIME) is still obscure.MethodThe mutation data was analyzed by employing "maftools" package. Weighted gene co-expression network analysis (WGCNA) was implemented to determine candidate module and significant genes correlated with TMB value. Differential analysis was performed between different level of TMB subgroups employing R package "limma". Gene ontology (GO) enrichment analysis was implemented with "clusterProfiler", "enrichplot" and "ggplot2" packages. Then risk score signature was developed by systematical bioinformatics analyses. K-M survival curves and receiver operating characteristic (ROC) plot were further analyzed for prognostic validity. To depict comprehensive context of TIME, XCELL, TIMER, QUANTISEQ, MCPcounter, EPIC, CIBERSORT, and CIBERSORT-ABS algorithm were employed. Additionally, the potential role of risk score on immune checkpoint blockade (ICB) immunotherapy was further explored. The quantitative real-time polymerase chain reaction was performed to detect expression of HTRA3.ResultsTMB value was positively correlated with older age, male gender and early T status. A total of 75 intersection genes between TMB-related genes and differentially expressed genes (DEGs) were screened and enriched in extracellular matrix-relevant pathways. Risk score based on three hub genes significantly affected overall survival (OS) time, infiltration of immune cells, and ICB-related hub targets. The prognostic performance of risks score was validated in the external testing group. Risk-clinical nomogram was constructed for clinical application. HTRA3 was demonstrated to be a prognostic factor in HCC in further exploration. Finally, mutation of TP53 was correlated with risk score and do not interfere with risk score-based prognostic prediction.ConclusionCollectively, a comprehensive analysis of TMB might provide novel insights into mutation-driven mechanism of tumorigenesis further contribute to tailored immunotherapy and prognosis prediction of HCC.

Project description:Introduction: Tumor mutation burden (TMB) is an emerging biomarker for immunotherapy of hepatocellular carcinoma (HCC), but its value for clinical application has not been fully revealed.Materials and methods: We used the Wilcox test to identify the differentially expressed immune-related genes (DEIRGs) in groups with high and low TMB as well as screened the immune gene pairs related to prognosis using univariate Cox regression analysis. A LASSO Cox regression prognostic model was developed by combining The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) with the International Cancer Genome Consortium (ICGC) LIRI-JP cohort, and internal (TCGA, ICGC) and external (GSE14520) validation analyses were conducted on the predictive value of the model. We also explored the relationship between the prognostic model and tumor microenvironment via the ESTIMATE algorithm and performed clinical correlation analysis by the chi-square test, revealing its underlying molecular mechanism with the help of Gene Set Enrichment Analysis (GSEA).Results: The prognostic model consisting of 15 immune gene pairs showed high predictive value for short- and long-term survival of HCC in three independent cohorts. Based on univariate multivariate Cox regression analysis, the prognostic model could be used to independently predict the prognosis in each independent cohort. The immune score, stromal score, and estimated score values were lower in the high-risk group than in the low-risk group. As shown by the chi-square test, the prognostic model exhibited an obvious correlation with the tumor stage [American Joint Committee on Cancer tumor-node-metastasis (AJCC-TNM) (p < 0.001), Barcelona Clinic Liver Cancer (BCLC) (p = 0.003)], histopathological grade (p = 0.033), vascular invasion (p = 0.009), maximum tumor diameter (p = 0.013), and background of liver cirrhosis (p < 0.001). GSEA revealed that the high-risk group had an enrichment of many oncology features, including the cell cycle, mismatch repair, DNA replication, RNA degradation, etc.Conclusion: Our research developed and validated a reliable prognostic model associated with TMB for HCC, which may help to further enrich the therapeutic targets of HCC.

Project description:IntroductionGlobally, the incidence, as well as mortality, related to hepatocellular carcinoma (HCC) is on the rise, owing to relatively few curative options. Underlying cirrhosis is the most common etiology leading to HCC, but risk factors of cirrhosis show great regional variability. Over the years, there has been a steady development in the diagnostic and therapeutic modalities of HCC, including the availability of a wide range of systemic chemotherapeutic agents. We aim to review the recent advancements in the diagnostic and therapeutic strategies for HCC.MethodologyThe literature search was done using databases PubMed, Cochrane, and Science Direct, and the latest relevant articles were reviewed.FindingsScreening of HCC is a pivotal step in the early diagnosis of the disease. Current guidelines recommend using ultrasound and alfa fetoprotein but various new biomarkers are under active research that might aid in diagnosing very small tumors, not picked up by the current screening methods. Treatment options are decided based upon the overall performance of the patient and the extent of the disease, as per the Barcelona classification. There are very few options that offer a cure for the disease, ranging from liver resection and transplantation to tumor ablation. Downstaging has proven to have a significant role in the course of the disease. An attempt to control the disease can be made via radiological interventions, such as transarterial chemoembolization, transarterial radioembolization, or radiation therapy. For advanced disease, sorafenib used to be the only option until a couple of years ago. Recently, many other systemic agents have received approval as first-line and second-line therapies for HCC. Genomics is an area of active clinical research as understanding the mutations and genomics involved in the evolution of HCC might lead to a breakthrough therapy.How to cite this articleRaees A, Kamran M, Özkan H, et al. Updates on the Diagnosis and Management of Hepatocellular Carcinoma. Euroasian J Hepato-Gastroenterol 2021;11(1):32-40.