RNA sequencing analysis of hepatocellular carcinoma identified oxidative phosphorylation as a major pathologic feature

Mongolian HCC vs. Caucasian HCC: The Metabolic Reprogramming Process in Mongolian HCC is an Interesting Difference

Racial/ethnic and region disparities in incidence and mortality are obviously in liver cancer. Mongolia has the highest reported incidence and mortality of hepatocellular carcinoma (HCC) in the world, while the incidence of HCC is relatively low in the United States, but differences in their molecular characteristics remain largely elusive. Here we report differentially expressed genes (DEGs) in Mongolian hepatocellular carcinoma and in Caucasian HCC and their intersection DEGs, as well as their corresponding signaling pathways in Mongolian and Caucasian hepatocellular carcinoma patients based on the transcriptome sequences from Gene Expression Omnibus (GEO) database. We got 908 up-regulated genes and 1946 down-regulated genes in Mongolian HCC, 1244 up-regulated genes and 1912 down-regulated genes in Caucasian HCC, 254 Co-upregulated genes and 1035 co-downregulated genes in Mongolian and Caucasian. The results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that most of the genes with altered expression levels in Mongolian HCC participate in biological processes that involve metabolic reprogramming of various substances, accounting for about one-third of all biological processes. In particular, multiple amino acid biosynthesis and metabolic processes appear to be specific in Mongolian HCC compared with Caucasian HCC. The biological processes they share include those in which most immune cells are involved and cell cycle-related biological processes. In addition, we also found the genes UPP2, PCK1, GLYAT, GNMT, ADH1B and HPD, encode for key metabolic enzymes, whose expression level up-regulated or down-regulated more than 5 times in Mongolian HCC and was dramatically correlated with survival in Mongolian HCC (p value < 0.01), More importantly, these molecules are potential targets for some metabolic antitumor drugs. This study not only makes up for the shortcomings of previous studies on liver cancer, which paid more attention to its commonality, but ignored the specificity of liver cancer in different races and regions. More importantly, the purpose of this study is to identify robust molecular subclasses and information with underlying unique tumor biology. And this study may have important implications for the study of the pathogenic factors and molecular mechanisms of hepatocellular carcinoma and the precise therapy of Mongolian HCC.

Interplay of oxidative stress, cellular communication and signaling pathways in cancer

Cancer remains a significant global public health concern, with increasing incidence and mortality rates worldwide. Oxidative stress, characterized by the production of reactive oxygen species (ROS) within cells, plays a critical role in the development of cancer by affecting genomic stability and signaling pathways within the cellular microenvironment. Elevated levels of ROS disrupt cellular homeostasis and contribute to the loss of normal cellular functions, which are associated with the initiation and progression of various types of cancer. In this review, we have focused on elucidating the downstream signaling pathways that are influenced by oxidative stress and contribute to carcinogenesis. These pathways include p53, Keap1-NRF2, RB1, p21, APC, tumor suppressor genes, and cell type transitions. Dysregulation of these pathways can lead to uncontrolled cell growth, impaired DNA repair mechanisms, and evasion of cell death, all of which are hallmark features of cancer development. Therapeutic strategies aimed at targeting oxidative stress have emerged as a critical area of investigation for molecular biologists. The objective is to limit the response time of various types of cancer, including liver, breast, prostate, ovarian, and lung cancers. By modulating the redox balance and restoring cellular homeostasis, it may be possible to mitigate the damaging effects of oxidative stress and enhance the efficacy of cancer treatments. The development of targeted therapies and interventions that specifically address the impact of oxidative stress on cancer initiation and progression holds great promise in improving patient outcomes. These approaches may include antioxidant-based treatments, redox-modulating agents, and interventions that restore normal cellular function and signaling pathways affected by oxidative stress. In summary, understanding the role of oxidative stress in carcinogenesis and targeting this process through therapeutic interventions are of utmost importance in combating various types of cancer. Further research is needed to unravel the complex mechanisms underlying oxidative stress-related pathways and to develop effective strategies that can be translated into clinical applications for the management and treatment of cancer. Video Abstract.

Diet-induced rewiring of the Wnt gene regulatory network connects aberrant splicing to fatty liver and liver cancer in DIAMOND mice

Several preclinical models have been recently developed for metabolic associated fatty liver disease (MAFLD) and associated hepatocellular carcinoma (HCC) but comprehensive analysis of the regulatory and transcriptional landscapes underlying disease in these models are still missing. We investigated the regulatory and transcriptional landscape in fatty livers and liver tumours from DIAMOND mice that faithfully mimic human HCC development in the context of MAFLD. RNA-sequencing and ChIP-sequencing revealed rewiring of the Wnt/β-catenin regulatory network in DIAMOND tumours, as manifested by chromatin remodelling and associated switching in the expression of the canonical TCF/LEF downstream effectors. We identified splicing as a major mechanism leading to constitutive oncogenic activation of β-catenin in a large subset of DIAMOND tumours, a mechanism that is independent on somatic mutations in the locus and that has not been previously shown. Similar splicing events were found in a fraction of human HCC and hepatoblastoma samples.

RNA-Seq and Immune Repertoire Analysis of Normal and Hepatocellular Carcinoma Relapse After Liver Transplantation

Background

Hepatocellular carcinoma (HCC) relapse is the main reason for the poor prognosis of HCC after Liver transplantation (LT). This study aimed to explore the molecular mechanisms and immune repertoire profiles of HCC relapse.

Material and Methods

RNA-seq of blood samples from patients with normal (n=12) and HCC relapse (n=6) after LT was performed to identify differentially expressed genes (DEGs) and key signalling pathways. The DEGs and immune genes were further analyzed by bioinformatics. TRUST4 was used to analyze the differences in the immune repertoire between the two groups. Another 11 blood samples from patients with HCC who had received LT were collected for RT-qPCR verification of key genes.

Results

A total of 131 upregulated and 157 downregulated genes were identified using RNA-seq, and GO enrichment analysis revealed that the top 15 pathways were immune-related. The PPI network identified 10 key genes. Immune infiltration analysis revealed a significant difference in the five immune cell types between the two groups. A total of 83 intersecting genes were obtained by intersecting DEGs and immune genes. 6 key genes, including MX1, ISG15, OAS1, PRF1, SPP1, and THBS1 were obtained according to the intersection of DEGs, PPI network top 10 genes and immune intersecting genes. Immune repertoire analysis showed that the usage frequency of variable (V) and joining (J) genes in the normal group was higher than that in the relapse group. RT-qPCR validation showed that the expression levels of key genes were consistent with the RNA-seq results.

Conclusion

Our study identified key pathways and genes that could help determine whether transplant recipients are more prone to HCC relapse. Immune repertoire analysis revealed a difference in the usage frequency of VJ genes between the normal and relapse groups, providing a research direction for immunotherapy in patients with HCC relapse after liver transplantation.

Five Critical Gene-Based Biomarkers With Optimal Performance for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most fatal cancers in the world. There is an urgent need to understand the molecular background of HCC to facilitate the identification of biomarkers and discover effective therapeutic targets. Published transcriptomic studies have reported a large number of genes that are individually significant for HCC. However, reliable biomarkers remain to be determined. In this study, built on max-linear competing risk factor models, we developed a machine learning analytical framework to analyze transcriptomic data to identify the most miniature set of differentially expressed genes (DEGs). By analyzing 9 public whole-transcriptome datasets (containing 1184 HCC samples and 672 nontumor controls), we identified 5 critical differentially expressed genes (DEGs) (ie, CCDC107, CXCL12, GIGYF1, GMNN, and IFFO1) between HCC and control samples. The classifiers built on these 5 DEGs reached nearly perfect performance in identification of HCC. The performance of the 5 DEGs was further validated in a US Caucasian cohort that we collected (containing 17 HCC with paired nontumor tissue). The conceptual advance of our work lies in modeling gene-gene interactions and correcting batch effect in the analytic framework. The classifiers built on the 5 DEGs demonstrated clear signature patterns for HCC. The results are interpretable, robust, and reproducible across diverse cohorts/populations with various disease etiologies, indicating the 5 DEGs are intrinsic variables that can describe the overall features of HCC at the genomic level. The analytical framework applied in this study may pave a new way for improving transcriptome profiling analysis of human cancers.

A gut bacterial signature in blood and liver tissue characterizes cirrhosis and hepatocellular carcinoma

BACKGROUND

HCC is the leading cause of cancer in chronic liver disease. A growing body of experimental mouse models supports the notion that gut-resident and liver-resident microbes control hepatic immune responses and, thereby, crucially contribute to liver tumorigenesis. However, a comprehensive characterization of the intestinal microbiome in fueling the transition from chronic liver disease to HCC in humans is currently missing.

METHODS

Here, we profiled the fecal, blood, and liver tissue microbiome of patients with HCC by 16S rRNA sequencing and compared profiles to nonmalignant cirrhotic and noncirrhotic NAFLD patients.

RESULTS

We report a distinct bacterial profile, defined from 16S rRNA gene sequences, with reduced α-and β-diversity in the feces of patients with HCC and cirrhosis compared to NAFLD. Patients with HCC and cirrhosis exhibited an increased proportion of fecal bacterial gene signatures in the blood and liver compared to NAFLD. Differential analysis of the relative abundance of bacterial genera identified an increased abundance of Ruminococcaceae and Bacteroidaceae in blood and liver tissue from both HCC and cirrhosis patients compared to NAFLD. Fecal samples from cirrhosis and HCC patients both showed a reduced abundance for several taxa, including short-chain fatty acid-producing genera, such as Blautia and Agathobacter. Using paired 16S rRNA and transcriptome sequencing, we identified a direct association between gut bacterial genus abundance and host transcriptome response within the liver tissue.

CONCLUSIONS

Our study indicates perturbations of the intestinal and liver-resident microbiome as a critical determinant of patients with cirrhosis and HCC.

Transcriptome analysis creates a new era of precision medicine for managing recurrent hepatocellular carcinoma

The high incidence of hepatocellular carcinoma (HCC) recurrence negatively impacts outcomes of patients treated with curative intent despite advances in surgical techniques and other locoregional liver-targeting therapies. Over the past few decades, the emergence of transcriptome analysis tools, including real-time quantitative reverse transcription PCR, microarrays, and RNA sequencing, has not only largely contributed to our knowledge about the pathogenesis of recurrent HCC but also led to the development of outcome prediction models based on differentially expressed gene signatures. In recent years, the single-cell RNA sequencing technique has revolutionized our ability to study the complicated crosstalk between cancer cells and the immune environment, which may benefit further investigations on the role of different immune cells in HCC recurrence and the identification of potential therapeutic targets. In the present article, we summarized the major findings yielded with these transcriptome methods within the framework of a causal model consisting of three domains: primary cancer cells; carcinogenic stimuli; and tumor microenvironment. We provided a comprehensive review of the insights that transcriptome analyses have provided into diagnostics, surveillance, and treatment of HCC recurrence.