Systematic Characterization of Novel Immune Gene Signatures Predicts Prognostic Factors in Hepatocellular Carcinoma

Abstract

Background: The prognosis of patients with hepatocellular carcinoma (HCC) is negatively affected by the lack of effective prognostic indicators. The change of tumor immune microenvironment promotes the development of HCC. This study explored new markers and predicted the prognosis of HCC patients by systematically analyzing immune characteristic genes.Methods: Immune-related genes were obtained, and the differentially expressed immune genes (DEIGs) between tumor and para-cancer samples were identified and analyzed using gene expression profiles from TCGA, HCCDB, and GEO databases. An immune prognosis model was also constructed to evaluate the predictive performance in different cohorts. The high and low groups were divided based on the risk score of the model, and different algorithms were used to evaluate the tumor immune infiltration cell (TIIC). The expression and prognosis of core genes in pan-cancer cohorts were analyzed, and gene enrichment analysis was performed using clusterProfiler. Finally, the expression of the hub genes of the model was validated by clinical samples.Results: Based on the analysis of 730 immune-related genes, we identified 64 common DEIGs. These genes were enriched in the tumor immunologic related signaling pathways. The first 15 genes were selected using RankAggreg analysis, and all the genes showed a consistent expression trend across multi-cohorts. Based on lasso cox regression analysis, a 5-gene signature risk model (ATG10, IL18RAP, PRKCD, SLC11A1, and SPP1) was constructed. The signature has strong robustness and can stabilize different cohorts (TCGA-LIHC, HCCDB18, and GSE14520). Compared with other existing models, our model has better performance. CIBERSORT was used to assess the landscape maps of 22 types of immune cells in TCGA, GSE14520, and HCCDB18 cohorts, and found a consistent trend in the distribution of TIIC. In the high-risk score group, scores of Macrophages M1, Mast cell resting, and T cells CD8 were significantly lower than those of the low-risk score group. Different immune expression characteristics, lead to the different prognosis. Western blot demonstrated that ATG10, PRKCD, and SPP1 were highly expressed in cancer tissues, while IL18RAP and SLC11A1 expression in cancer tissues was lower. In addition, IL18RAP has a highly positive correlation with B cell, macrophage, Neutrophil, Dendritic cell, CD8 cell, and CD4 cell. The SPP1, PRKCD, and SLC11A1 genes have the strongest correlation with macrophages. The expression of ATG10, IL18RAP, PRKCD, SLC11A1, and SPP1 genes varies among different immune subtypes and between different T stages.Conclusion: The 5-immu-gene signature constructed in this study could be utilized as a new prognostic marker for patients with HCC.

Identification and Validation of Nicotinamide metabolism-Related Gene Signatures as a Novel Prognostic Model for hepatocellular carcinoma

“…Dendritic cells (DCs) are pivotal in orchestrating T-cell immune reactions, with the antigen presentation by resting DCs to CD8+ T cells potentially elevating tolerance (Probst, McCoy et al 2005, Ouyang, Wu et al 2016. Furthermore, metabolism stands as a cornerstone in the dynamic between immune and cancer cells within the tumor milieu, influencing both immune surveillance and evasion mechanisms (Xie, Bai et al 2020, Xu, Wang et al 2021. In sum, our research underscores NAM's paramount influence on the immune landscape of HCC.…”

Ubiquitin-proteasome system-based signature to predict the prognosis and drug sensitivity of hepatocellular carcinoma

“…The risk model exhibited a strong performance in survival prediction. Previous studies have identified that ATG10 was associated with autophagy, immune response, and tumor metastasis in HCC ( Zhang J. et al, 2021 ; Chen et al, 2021 ; Xu et al, 2021 ), which suggested that UPS-related genes might contribute to HCC development through regulating biological process. FBXL7, an F-box protein that binds to substrates via SKP1-Cullin-1-F-box (SCF) E3 ubiquitin ligase, could enhance polyubiquitylation and degradation of substrates in tumor occurrence and aggression ( Wang et al, 2022 ).…”

Constructing and validating a risk model based on neutrophil‐related genes for evaluating prognosis and guiding immunotherapy in colon cancer

“…Both SLC11A1 and SLC2A3 are members of the solute carrier family and are responsible for encoding membrane transport proteins 50,51 . Reportedly, SLC11A1 not only predicts the prognosis of colorectal cancer and hepatocellular carcinoma 52,53 but also serves as a stratification indicator for immunotherapy or chemotherapy in glioma patients 54 . SLC2A3 exerts multiple biological functions in different cancers, including tumor EMT, ferroptosis, glycolytic reprogramming, drug resistance and immunity 55–59 .…”