A Seven-Gene Signature to Predict Prognosis of Patients With Hepatocellular Carcinoma

Unleashing the potential of gene signatures as prognostic and predictive tools: A step closer to personalized medicine in hepatocellular carcinoma (HCC)

Hepatocellular carcinoma (HCC) is one of the growing malignancies globally, affecting a myriad of people and causing numerous cancer-related deaths. Despite therapeutic improvements in treatment strategies over the past decades, HCC still remains one of the leading causes of person-years of life lost. Numerous studies have been conducted to assess the characteristics of HCC with the aim of predicting its prognosis and responsiveness to treatment. However, the identified biomarkers have shown limited sensitivity, and the translation of these findings into clinical practice has faced challenges. The development of sequencing techniques has facilitated the exploration of a wide range of genes, leading to the emergence of gene signatures. Although several studies assessed differentially expressed genes in normal and HCC tissues to find the unique gene signature with prognostic value, to date, no study has reviewed the task, and to the best of our knowledge, this review represents the first comprehensive analysis of relevant studies in HCC. Most gene signatures focused on immune-related genes, while others investigated genes related to metabolism, autophagy, and apoptosis. Even though no identical gene signatures were found, NDRG1, SPP1, BIRC5, and NR0B1 were the most extensively studied genes with prognostic value. Finally, despite challenges such as the lack of consistent patterns in gene signatures, we believe that comprehensive analysis of pertinent gene signatures will bring us a step closer to personalized medicine in HCC, where treatment strategies can be tailored to individual patients based on their unique molecular profiles.

Integrated analysis to identify the prognostic and immunotherapeutic roles of coagulation-associated gene signature in clear cell renal cell carcinoma

The coagulation system is closely related to the physiological status and immune response of the body. Recent years, studies focusing on the association between coagulation system abnormalities and tumor progression have been widely reported. In clear cell renal cell carcinoma (ccRCC), poor prognosis often occurs in patients with venous tumor thrombosis and coagulation system abnormalities, and there is a lack of research in related fields. Significant differences in coagulation function were also demonstrated in our clinical sample of patients with high ccRCC stage or grade. Therefore, in this study, we analyzed the biological functions of coagulation-related genes (CRGs) in ccRCC patients using single-cell sequencing and TCGA data to establish the 5-CRGs based diagnostic signature and predictive signature for ccRCC. Univariate and multivariate Cox analyses suggested that prognostic signature could be an independent risk factor. Meanwhile, we applied CRGs for consistent clustering of ccRCC patients, and the two classes showed significant survival and genotype differences. The differences in individualized treatment between the two different subtypes were revealed by pathway enrichment analysis and immune cell infiltration analysis. In summary, we present the first systematic analysis of the significance of CRGs in the diagnosis, prognosis, and individualized treatment of ccRCC patients.

Prognostic-Related Biomarkers in Pancreatic Ductal Adenocarcinoma Correlating with Immune Infiltrates Based on Proteomics

BACKGROUND Pancreatic ductal adenocarcinoma (PDAC) accounts for 85% of pancreatic carcinoma cases. Patients with PDAC have a poor prognosis. The lack of reliable prognostic biomarkers makes treatment challenging for patients with PDAC. Using a bioinformatics database, we sought to identify prognostic biomarkers for PDAC. MATERIAL AND METHODS Using proteomic analysis of the Clinical Proteomics Tumor Analysis Consortium (CPTAC) database, we were able to identify core differential proteins between early and advanced pancreatic ductal adenocarcinoma tissue, and then we used survival analysis, Cox regression analysis, and area under the ROC curves to screen for more significant differential proteins. Additionally, the Kaplan-Meier plotter database was utilized to determine the relationship between prognosis and immune infiltration in PDAC. RESULTS We identified 378 differential proteins in early (n=78) and advanced stages (n=47) of PDAC (P<0.05). PLG, COPS5, FYN, ITGB3, IRF3, and SPTA1 served as independent prognostic factors of patients with PDAC. Patients with higher COPS5 expression had shorter overall survival (OS) and recurrence-free survival, and those with higher PLG, ITGB3, and SPTA1, and lower FYN and IRF3 expression had shorter OS. More importantly, COPS5, IRF3 were negatively associated with macrophages and NK cells, but PLG, FYN, ITGB3, and SPTA1 were positively related to the expression of CD8+ T cells and B cells. COPS5 affected the prognosis of PDAC patients by acting on B cells, CD8+ T cells, macrophages, and NK cells immune infiltration, while PLG, FYN, ITGB3, IRF3, and SPTA1 affected PDAC patient prognosis through some immune cells. CONCLUSIONS PLG, COPS5, FYN, IRF3, ITGB3 and SPTA1 could be potential immunotherapeutic targets and valuable prognostic biomarkers of PDAC.

Hepatocellular carcinoma subtypes based on metabolic pathways reveals potential therapeutic targets

Introduction

Hepatocellular carcinoma (HCC) is an aggressive malignancy with steadily increasing incidence rates worldwide and poor therapeutic outcomes. Studies show that metabolic reprogramming plays a key role in tumor genesis and progression. In this study, we analyzed the metabolic heterogeneity of epithelial cells in the HCC and screened for potential biomarkers.

Methods

The hepatic single-cell RNA sequencing (scRNA-seq) datasets of HCC patients and healthy controls were obtained from the Gene Expression Omnibus (GEO) database. Based on data intergration and measurement of differences among groups, the metabolic epithelial cell subpopulations were identified. The single-cell metabolic pathway was analyzed and the myeloid subpopulations were identified. Cell-cell interaction analysis and single-cell proliferation analysis were performed. The gene expression profiles of HCC patients were obtained from the GSE14520 dataset of GEO and TCGA-LIHC cohort of the UCSC Xena website. Immune analysis was performed. The differentially expressed genes (DEGs) were identified and functionally annotated. Tumor tissues from HCC patients were probed with anti-ALDOA, anti-CD68, anti-CD163, anti-CD4 and anti-FOXP3 antibodies. Results We analyzed the scRNA-seq data from 48 HCC patients and 14 healthy controls. The epithelial cells were significantly enriched in HCC patients compared to the controls (p = 0.011). The epithelial cells from HCC patients were classified into two metabolism-related subpopulations (MRSs) - pertaining to amino acid metabolism (MRS1) and glycolysis (MRS2). Depending on the abundance of these metabolic subpopulations, the HCC patients were also classified into the MRS1 and MRS2 subtype distinct prognoses and immune infiltration. The MRS2 group had significantly worse clinical outcomes and more inflamed tumor microenvironment (TME), as well as a stronger crosstalk between MRS2 cells and immune subpopulations that resulted in an immunosuppressive TME. We also detected high expression levels of ALDOA in the MRS2 cells and HCC tissues. In the clinical cohort, HCC patients with higher ALDOA expression showed greater enrichment of immunosuppressive cells including M2 macrophages and T regulatory cells.

Discussion

The glycolytic subtype of HCC cells with high ALDOA expression is associated with an immunosuppressive TME and predicts worse clinical outcomes, providing new insights into the metabolism and prognosis of HCC.

Downregulation of Indolethylamine N-methyltransferase is an early event in the rat hepatocarcinogenesis and is associated with poor prognosis in hepatocellular carcinoma patients

Hepatocellular carcinoma (HCC) is one of the deadliest cancers worldwide, often preceded by cirrhosis and usually diagnosed at advanced stages; therefore, identifying molecular changes at early stages is an attractive strategy for detection and timely treatment. Here, we investigated the progressive transcriptomic changes during experimental hepatocarcinogenesis to identify novel early tumor markers in an HCC model induced by chronic administration of sublethal doses of diethylnitrosamine. An analysis of differentially expressed genes showed that four processes associated with oxidation-reduction and detoxification were significantly overrepresented during hepatocarcinogenesis progression, of which the Nuclear Factor, Erythroid 2 Like 2 (NRF2) pathway showed several dysregulated genes. Interestingly, we also identified 91 genes dysregulated at early HCC stages, but the expression of the indolethylamine N-methyltransferase gene (Inmt), as well as the level of its encoding protein, were strongly downregulated. INMT was increased in perivenular hepatocytes of normal livers but decreased in livers of experimental HCC. Furthermore, a gene expression and survival analysis performed using data from the liver hepatocellular carcinoma project of The Cancer Genome Atlas Program revealed that INMT is also significantly downregulated in human HCC and is associated with poor overall survival. In conclusion, by performing a transcriptome analysis of the HCC progression, we identified that INMT is early downregulated in the rat hepatocarcinogenesis and is associated with poor prognosis in human HCC, suggesting that INMT downregulation may be a promising prognostic marker for HCC in high-risk populations.