The growth rate of hepatocellular carcinoma is different with different TNM stages at diagnosis

Predictive Prognostic Model for Hepatocellular Carcinoma Based on Seven Genes Participating in Arachidonic Acid Metabolism

BACKGROUND

The occult onset and rapid progression of hepatocellular carcinoma (HCC) lead to an unsatisfactory overall survival (OS) rate. Established prognostic predictive models based on tumor-node-metastasis staging and predictive factors do not report satisfactory predictive efficacy. Arachidonic acid plays pivotal roles in biological processes including inflammation, regeneration, immune modulation, and tumorigenesis. We, therefore, constructed a prognostic predictive model based on seven genes linked to arachidonic acid metabolism, using samples of HCC patients from databases to analyze the genomic profiles. We also assessed the predictive stability of the constructed model.

METHODS

Sample data of 365 patients diagnosed with HCC were extracted from The Cancer Genome Atlas (TCGA, training set) and HCCDB18, GSE14520, and GSE76427 databases (validation sets). Patient samples were clustered using ConsensusClusterPlus analysis based on the expression levels of 12 genes involved in arachidonic acid metabolism that were significantly associated with HCC prognosis. Differentially expressed genes (DEGs) within different clusters were distinguished and compared using WebGestaltR. Immunohistochemistry (IHC) analysis was performed using a human HCC tissue microarray (TMA). Tumor immune microenvironment assessment was performed using ESTIMATE, ssGSEA, and TIDE.

RESULTS

Samples of patients with HCC were classified into three clusters, with significant differences in OS. Cluster 2 showed the best prognosis, whereas cluster 1 presented the worst. The three clusters showed significant differences in immune infiltration. We then performed Cox and LASSO regression analyses, which revealed CYP2C9, G6PD, CDC20, SPP1, PON1, TRNP1, and ADH4 as prognosis-related hub genes, making it a simplified prognostic model. TMA analysis for the seven target genes showed similar results of regression analyses. The high-risk group showed a significantly worse prognosis and reduced immunotherapy efficacy. Our model showed stable prognostic predictive efficacy.

CONCLUSIONS

This seven-gene-based model showed stable outcomes in predicting HCC prognosis as well as responses to immunotherapy.

Identification and validation of a prognostic model based on four genes related to satellite nodules in hepatocellular carcinoma

Satellite nodules is a key clinical characteristic which has prognostic value of hepatocellular carcinoma (HCC). Currently, there is no gene-level predictive model for Satellite nodules in liver cancer. For the 377 HCC cases collected from the dataset of Cancer Genome Atlas (TCGA), their original pathological data were analyzed to extract information regarding satellite nodules status as well as other relevant pathological data. Then, this study employed statistical modeling for prognostic model establishment in TCGA, and validation in International Cancer Genome Consortium (ICGC) cohorts and GSE76427. Through rigorous statistical analyses, 253 differential satellite nodules-related genes (SNRGs) were identified, and four key genes related to satellite nodules and prognosis were selected to construct a prognostic model. The high-risk group predicted by our model exhibited an unfavorable overall survival (OS) outlook and demonstrated an association with adverse worse clinical characteristics such as larger tumor size, higher alpha-fetoprotein, microvascular invasion and advanced stage. Moreover, the validation of the model's prognostic value in the ICGC and GSE76427 cohorts mirrored that of the TCGA cohort. Besides, the high-risk group also showed higher levels of resting Dendritic cells, M0 macrophages infiltration, alongside decreased levels of CD8+ T cells and γδT cells infiltration. The prognostic model based on SNRGs can reliability predict the OS of HCC and is likely to have predictive value of immunotherapy for HCC.

Integration of meta-analysis and network pharmacology analysis to investigate the pharmacological mechanisms of traditional Chinese medicine in the treatment of hepatocellular carcinoma

Background: This study will explore the therapeutic value of traditional Chinese medicine (TCM) in Hepatocellular Carcinoma (HCC) through meta-analysis, combined with network pharmacology analysis. Methods: The results of randomized controlled trials on TCM and HCC were retrieved and summarized from multiple databases. The effective active com-pounds and target genes of the high-frequency TCM were obtained using the TCMSP database, and disease targets of HCC were acquired through the public disease database. The network pharmacology analysis was used to get the core genes and investigate the potential oncogenic molecular mechanism. Results: A total of 14 meta-analysis studies with 1,831 patients suggested that therapy combined TCM is associated with better clinical efficacy and survival prognosis, as well as avoiding many adverse events. A total of 156 compounds, 247 herbal target genes and 36 core genes were identified. The function analysis suggested above genes may participate development in HCC through regulating some pathways, such as HIF-1 pathway and PD-L1 immune-related pathway. Conclusion: TCM, as a novel, safe, and effective multi-mechanism therapy, holds greater value in the treatment of HCC.

Establishment and validation of a cholesterol metabolism-related prognostic signature for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) represents the most important type of liver cancer, the 5-year survival rate for advanced HCC is 2%. The heterogeneity of HCC makes previous models fail to achieve satisfactory results. The role of Cholesterol-based metabolic reprogramming in cancer has attracted more and more attention. In this study, we screened cholesterol metabolism-related genes (CMRGs) based on a systematical analysis from TCGA and GEO database. Then, we constructed a prognostic signature based on the screened 5 CMRGs: FDPS, FABP5, ANXA2, ACADL and HMGCS2. The clinical value of the five CMRGs was validated by TCGA database and HPA database. HCC patients were assigned to the high-risk and low-risk groups on the basis of median risk score calculated by the five CMRGs. We evaluated the signature in TCGA database and validated in ICGC database. The results revealed that the prognostic signature had good prognostic performance, even among different clinicopathological subgroups. The function analysis linked CMRGs with KEGG pathway, such as cell adhesion molecules, drug metabolism-cytochrome P450 and other related pathways. In addition, patients in the high-risk group exhibited characteristics of high TP53 mutation, high immune checkpoints expression and high immune cell infiltration. Furthermore, based on the prognostic signature, we identified 25 most significant small molecule drugs as potential drugs for HCC patients. Finally, a nomogram combined risk score and TNM stage was constructed. These results indicated our prognostic signature has an excellent prediction performance. This study is expected to provide a potential diagnostic and therapeutic strategies for HCC.

Evaluation of Hepatocellular Carcinoma Patients: Interim Analysis of Cases from a Tertiary Referral Center in Craiova, Romania

Although medicine is constantly evolving, hepatocellular carcinoma remains a pathology with a poor prognosis due to the frequent delayed diagnosis and the aggressiveness of the disease.

AIM

Our objective was to evaluate liver function and stage of disease of newly diagnosed HCC patients.

METHODS

We conducted a retrospective study between July 2016 and January 2021 and we included hospitalized patients within the Department of Gastroenterology of the Emergency County Hospital of Craiova. We identified 119 newly diagnosed patients and we collected data from patient history, contrast-enhanced imaging and laboratory analysis.

RESULTS

81 patients were diagnosed in BCLC Stage A and B. Liver function was not significantly modified, despite 91.5% of the patients presented with elevated AST levels. Because of the cirrhotic liver already affected, 73 patients had thrombocytopenia. Contrast-enhanced ultrasound was performed in 79 patients, as a complementary imaging exploration. Alfa-fetoprotein values could not be correlated with the severity of disease.

CONCLUSIONS

Early diagnosis was mostly established. It is mandatory for treatment management and overall survival to follow a rigorous surveillance of patients at risk for HCC.