Immune classifier-based signatures provide good prognostic stratification and predict the clinical benefits of immune-based therapies for hepatocellular carcinoma

Prediction of hepatocellular carcinoma prognosis and immunotherapeutic effects based on tryptophan metabolism-related genes

Background

L-tryptophan (Trp) metabolism involved in mediating tumour development and immune suppression. However, comprehensive analysis of the role of the Trp metabolism pathway is still a challenge.

Methods

We downloaded Trp metabolism-related genes’ expression data from different public databases, including TCGA, Gene Expression Omnibus (GEO) and Hepatocellular Carcinoma Database (HCCDB). And we identified two metabolic phenotypes using the ConsensusClusterPlus package. Univariate regression analysis and lasso Cox regression analysis were used to establish a risk model. CIBERSORT and Tracking of Indels by DEcomposition (TIDE) analyses were adopted to assess the infiltration abundance of immune cells and tumour immune escape.

Results

We identified two metabolic phenotypes, and patients in Cluster 2 (C2) had a better prognosis than those in Cluster 1 (C1). The distribution of clinical features between the metabolic phenotypes showed that patients in C1 tended to have higher T stage, stage, grade, and death probability than those of patients in C2. Additionally, we screened 739 differentially expressed genes (DEGs) between the C1 and C2. We generated a ten-gene risk model based on the DEGs, and the area under the curve (AUC) values of the risk model for predicting overall survival. Patients in the low-risk subgroup tended to have a significantly longer overall survival than that of those in the high-risk group. Moreover, univariate analysis indicated that the risk model was significantly correlated with overall survival. Multivariate analysis showed that the risk model remained an independent risk factor in hepatocellular carcinoma (p < 0.0001).

Conclusions

We identified two metabolic phenotypes based on genes of the Trp metabolism pathway, and we established a risk model that could be used for predicting prognosis and guiding immunotherapy in patients with hepatocellular carcinoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02730-8.

Identification of a DNA Damage Response and Repair-Related Gene-Pair Signature for Prognosis Stratification Analysis in Hepatocellular Carcinoma

Background: Nowadays, although the cause of hepatocellular carcinoma (HCC) mortality and recurrence remains at a high level, the 5-year survival rate is still very low. The DNA damage response and repair (DDR) pathway may affect HCC patients’ survival by influencing tumor development and therapeutic response. It is necessary to identify a prognostic DDR-related gene signature to predict the outcome of patients.

Methods: Level 3 mRNA expression and clinical information were extracted from the TCGA website. The GSE14520 datasets, ICGC-LIRI datasets, and a Chinese HCC cohort were served as validation sets. Univariate Cox regression analysis and LASSO-penalized Cox regression analysis were performed to construct the DDR-related gene pair (DRGP) signature. Kaplan–Meier survival curves and time-dependent receiver operating characteristic (ROC) analysis curves were calculated to determine the predictive ability of this prognostic model. Then, a prognostic nomogram was established to help clinical management. We investigated the difference in biological processes between HRisk and LRisk by conducting several enrichment analyses. The TIDE algorithm and R package “pRRophetic” were applied to estimate the immunotherapeutic and chemotherapeutic response.

Results: We constructed the prognostic signature based on 23 DDR-related gene pairs. The patients in the training datasets were divided into HRisk and LRisk groups at median cut-off. The HRisk group had significantly poorer OS than the LRisk group, and the signature was an independent prognostic indicator in HCC. Furthermore, a nomogram of the riskscore combined with TNM stage was constructed and detected by the calibration curve and decision curve. The LRisk group was associated with higher expression of HBV oncoproteins and metabolism pathways, while DDR-relevant pathways and cell cycle process were enriched in the HRisk group. Moreover, patients in the LRisk group may be more beneficial from immunotherapy. We also found that TP53 gene was more frequently mutated in the HRisk group. As for chemotherapeutic drugs commonly used in HCC, the HRisk group was highly sensitive to 5-fluorouracil, while the LRisk group presented with a significantly higher response to gefitinib and gemcitabine.

Conclusion: Overall, we developed a novel DDR-related gene pair signature and nomogram to assist in predicting survival outcomes and clinical treatment of HCC patients. It also helps understand the underlying mechanisms of different DDR patterns in HCC.

Overexpressed or hyperactivated Rac1 as a target to treat hepatocellular carcinoma

Despite novel targeted and immunotherapies, the prognosis remains bleak for patients with hepatocellular carcinoma (HCC), especially for advanced and/or metastatic forms. The rapid emergence of drug resistance is a major obstacle in the success of chemo-, targeted-, immuno-therapies of HCC. Novel targets are needed. The prominent roles of the small GTPase Rac1 in the development and progression of HCC are discussed here, together with its multiple protein partners, and the targeting of Rac1 with RNA-based regulators and small molecules. We discuss the oncogenic functions of Rac1 in HCC, including the contribution of Rac1 mutants and isoform Rac1b. Rac1 is a ubiquitous target, but the protein is frequently overexpressed and hyperactivated in HCC. It contributes to the aggressivity of the disease, with key roles in cancer cell proliferation, tumor metastasis and resistance to treatment. Small molecule targeting Rac1, indirectly or directly, have shown anticancer effects in HCC experimental models. Rac1-binding agents such as EHT 1864 and analogues offer novel opportunities to combat HCC. We discuss the different modalities to repress Rac1 overactivation in HCC with small molecules and the combination with reference drugs to promote cancer cell death and to repress cell invasion. We highlight the necessity to combine Rac1-targeted approach with appropriate biomarkers to select Rac1 activated tumors. Our analysis underlines the prominent oncogenic functions of Rac1 in HCC and discuss the modalities to target this small GTPase. Rac1 shall be considered as a valid target to limit the acquired and intrinsic resistance of HCC tumors and their metastatic potential.

Acute-Phase Serum Amyloid A May Predict Microvascular Invasion and Early Tumor Recurrence in Patients with Hepatitis B Virus-Related Hepatocellular Carcinoma Undergoing Liver Resection

OBJECTIVE

To elucidate the impact of acute-phase protein serum amyloid A (aSAA) on microvascular invasion (MVI) and early recurrence in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC).

METHODS

HBV-related HCC patients (n = 192) undergoing liver resection were included in the study. The protein levels of aSAA were analyzed by immunohistochemical staining in 172 tumor specimens, and further detected via western blotting in HCC and their corresponding portal vein tumor thrombus (PVTT) (n = 20). Cox and logit regression analysis was performed. Exploratory subgroup analysis was used to balance the potential confounders.

RESULTS

HBV-related HCC patients with high aSAA levels tended to have high HBV-DNA loads. Logit and Cox regression analyses revealed high expression of aSAA is an independent risk factor not only for MVI (OR 5.384, 95% CI 2.286-13.301, P < 0.001) but also for early recurrence (HR 6.040, 95% CI 1.970-18.540, P = 0.002), overall recurrence (HR 3.720, 95% CI 2.140-6.450, P < 0.001), and overall survival (HR 4.15, 95% CI 2.380-7.230, P < 0.001). Subgroup analysis showed that the effects of aSAA were consistent across all subgroups examined. Additionally, the aSAA protein level was significantly higher in PVTT than that in its corresponding tumor specimen. A high HBV-DNA level and large tumor size were the independent risk factors for early HCC recurrence in patients with high levels of aSAA.

CONCLUSIONS

High expression of aSAA was an independent risk factor for MVI and early tumor recurrence in HBV-related HCC patients after liver resection. The aSAA protein level could thus be a promising biomarker for predicting MVI and early recurrence in these patients.