Distinctive Metabolism-Associated Gene Clusters That Are Also Prognostic in Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma

Signature construction and molecular subtype identification based on liver-specific genes for prediction of prognosis, immune activity, and anti-cancer drug sensitivity in hepatocellular carcinoma

BACKGROUND

Liver specific genes (LSGs) are crucial for hepatocyte differentiation and maintaining normal liver function. A deep understanding of LSGs and their heterogeneity in hepatocellular carcinoma (HCC) is necessary to provide clues for HCC diagnosis, prognosis, and treatment.

METHODS

The bulk and single-cell RNA-seq data of HCC were downloaded from TCGA, ICGC, and GEO databases. Through unsupervised cluster analysis, LSGs-based HCC subtypes were identified in TCGA-HCC samples. The prognostic effects of the subtypes were investigated with survival analyses. With GSVA and Wilcoxon test, the LSGs score, stemness score, aging score, immune score and stromal score of the samples were estimated and compared. The HCC subtype-specific genes were identified. The subtypes and their differences were validated in ICGC-HCC samples. LASSO regression analysis was used for key gene selection and risk model construction for HCC overall survival. The model performance was estimated and validated. The key genes were validated for their heterogeneities in HCC cell lines with quantitative real-time PCR and at single-cell level. Their dysregulations were investigated at protein level. Their correlations with HCC response to anti-cancer drugs were estimated in HCC cell lines.

RESULTS

We identified three LSGs-based HCC subtypes with different prognosis, tumor stemness, and aging level. The C1 subtype with low LSGs score and high immune score presented a poor survival, while the C2 subtype with high LSGs score and immune score indicated an enduring survival. Although no significant survival difference between C2 and C3 HCCs was shown, the C2 HCCs presented higher immune score and stroma score. The HCC subtypes and their differences were confirmed in ICGC-HCC dataset. A five-gene prognostic signature for HCC survival was constructed. Its good performance was shown in both the training and validation datasets. The five genes presented significant heterogeneities in different HCC cell lines and hepatocyte subclusters. Their dysregulations were confirmed at protein level. Furthermore, their significant associations with HCC sensitivities to anti-cancer drugs were shown.

CONCLUSIONS

LSGs-based HCC subtype classification and the five-gene risk model might provide useful clues not only for HCC stratification and risk prediction, but also for the development of more personalized therapies for effective HCC treatment.

Disulfidptosis-related signatures for prognostic and immunotherapy reactivity evaluation in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common cancers in the world and a nonnegligible health concern on a worldwide scale. Disulfidptosis is a novel mode of cell death, which is mainly caused by the collapse of the actin skeleton. Although many studies have demonstrated that various types of cell death are associated with cancer treatment, the relationship between disulfidptosis and HCC has not been elucidated.

METHODS

Here, we mainly applied bioinformatics methods to construct a disulfidptosis related risk model in HCC patients. Specifically, transcriptome data and clinical information were downloaded from the Gene Expression Omnibus (GEO), International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) database. A total of 45 co-expressed genes were extracted between the disulfidptosis-related genes (DRGs) and the differential expression genes (DEGs) of liver hepatocellular carcinoma (LIHC) in the TCGA database. The LIHC cohort was divided into two subgroups with different prognosis by k-mean consensus clustering and functional enrichment analysis was performed. Subsequently, three hub genes (CDCA8, SPP2 and RDH16) were screened by Cox regression and LASSO regression analysis. In addition, a risk signature was constructed and the HCC cohort was divided into high risk score and low risk score subgroups to compare the prognosis, clinical features and immune landscape between the two subgroups. Finally, the prognostic model of independent risk factors was constructed and verified.

CONCLUSIONS

High DRGs-related risk score in HCC individuals predict poor prognosis and are associated with poor immunotherapy response, which indicates that risk score assessment model can be utilized to guide clinical treatment strategy.

Retracted: Distinctive Metabolism-Associated Gene Clusters That Are Also Prognostic in Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma

[This retracts the article DOI: 10.1155/2022/6595989.].

The SLIT/ROBO Pathway in Liver Fibrosis and Cancer

Liver fibrosis is a common outcome of most chronic liver insults/injuries that can develop into an irreversible process of cirrhosis and, eventually, liver cancer. In recent years, there has been significant progress in basic and clinical research on liver cancer, leading to the identification of various signaling pathways involved in tumorigenesis and disease progression. Slit glycoprotein (SLIT)1, SLIT2, and SLIT3 are secreted members of a protein family that accelerate positional interactions between cells and their environment during development. These proteins signal through Roundabout receptor (ROBO) receptors (ROBO1, ROBO2, ROBO3, and ROBO4) to achieve their cellular effects. The SLIT and ROBO signaling pathway acts as a neural targeting factor regulating axon guidance, neuronal migration, and axonal remnants in the nervous system. Recent findings suggest that various tumor cells differ in SLIT/ROBO signaling levels and show varying degrees of expression patterns during tumor angiogenesis, cell invasion, metastasis, and infiltration. Emerging roles of the SLIT and ROBO axon-guidance molecules have been discovered in liver fibrosis and cancer development. Herein, we examined the expression patterns of SLIT and ROBO proteins in normal adult livers and two types of liver cancers: hepatocellular carcinoma and cholangiocarcinoma. This review also summarizes the potential therapeutics of this pathway for anti-fibrosis and anti-cancer drug development.

Development and validation of a coagulation-related genes prognostic model for hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) has a high incidence and mortality worldwide, which seriously threatens people's physical and mental health. Coagulation is closely related to the occurrence and development of HCC. Whether coagulation-related genes (CRGs) can be used as prognostic markers for HCC remains to be investigated.

METHODS

Firstly, we identified differentially expressed coagulation-related genes of HCC and control samples in the datasets GSE54236, GSE102079, TCGA-LIHC, and Genecards database. Then, univariate Cox regression analysis, LASSO regression analysis, and multivariate Cox regression analysis were used to determine the key CRGs and establish the coagulation-related risk score (CRRS) prognostic model in the TCGA-LIHC dataset. The predictive capability of the CRRS model was evaluated by Kaplan-Meier survival analysis and ROC analysis. External validation was performed in the ICGC-LIRI-JP dataset. Besides, combining risk score and age, gender, grade, and stage, a nomogram was constructed to quantify the survival probability. We further analyzed the correlation between risk score and functional enrichment, pathway, and tumor immune microenvironment.

RESULTS

We identified 5 key CRGs (FLVCR1, CENPE, LCAT, CYP2C9, and NQO1) and constructed the CRRS prognostic model. The overall survival (OS) of the high-risk group was shorter than that of the low-risk group. The AUC values for 1 -, 3 -, and 5-year OS in the TCGA dataset were 0.769, 0.691, and 0.674, respectively. The Cox analysis showed that CRRS was an independent prognostic factor for HCC. A nomogram established with risk score, age, gender, grade, and stage, has a better prognostic value for HCC patients. In the high-risk group, CD4⁺T cells memory resting, NK cells activated, and B cells naive were significantly lower. The expression levels of immune checkpoint genes in the high-risk group were generally higher than that in the low-risk group.

CONCLUSIONS

The CRRS model has reliable predictive value for the prognosis of HCC patients.

Eicosanoids and other oxylipins in liver injury, inflammation and liver cancer development

Liver cancer is a malignancy developed from underlying liver disease that encompasses liver injury and metabolic disorders. The progression from these underlying liver disease to cancer is accompanied by chronic inflammatory conditions in which liver macrophages play important roles in orchestrating the inflammatory response. During this process, bioactive lipids produced by hepatocytes and macrophages mediate the inflammatory responses by acting as pro-inflammatory factors, as well as, playing roles in the resolution of inflammation conditions. Here, we review the literature discussing the roles of bioactive lipids in acute and chronic hepatic inflammation and progression to cancer.