Systematic Construction and Validation of a Prognostic Model for Hepatocellular Carcinoma Based on Immune-Related Genes

Matrix metalloproteinase 1 is a poor prognostic biomarker for patients with hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains an incurable malignancy despite the treatment methods being continually updated. Matrix metalloproteinases (MMPs) promote the progression of HCC; however, no consensus exists on which MMP plays the predominant role in HCCs. In the present study, we analyzed differentially expressed genes in HCCs, especially MMPs, compared with adjacent tissues using the Cancer Genome Atlas database. The KEGG enrichment pathway using differentially expressed genes included extracellular matrix-receptor interaction, which was correlated with MMPs. We found that among the MMP family, only MMP1, MMP3, MMP8, MMP9, MMP11, MMP12, MMP14, MMP15, MMP20, MMP21, and MMP24 significantly increased in HCCs compared with adjacent tissues. Crucially, survival and univariate analyses indicated that only MMPs 1, 9, 12, and 14 predict poor overall survival; however, multivariate Cox analysis and a nomogram demonstrated that only MMP1 is a poor prognostic biomarker for HCCs. In addition, we observed significant enrichment of uncharacterized cells but decreased macrophages in HCC tissues. Consistent with decreased macrophages in HCCs, MMP1 was negatively associated with macrophages but positively correlated with uncharacterized cells, indicating that the main producer of MMP1 is uncharacterized cells. Furthermore, MMP1 expression was negatively correlated with immune responses of HCCs. Taken together, our findings indicated that MMP1 is a poor and predominant prognostic biomarker for patients with HCC and that anti-MMP1 may be a novel therapy that is worth studying in depth.

Integrating Network Pharmacology and Bioinformatics to Explore the Effects of Dangshen (Codonopsis pilosula) Against Hepatocellular Carcinoma: Validation Based on the Active Compound Luteolin

Purpose

This study aimed to explore the pharmacological mechanism of Dangshen (Codonopsis pilosula) against hepatocellular carcinoma (HCC) based on network pharmacology and bioinformatics, and to verify the anticancer effect of luteolin, the active ingredient of Codonopsis pilosula, on HCC cells.

Methods

The effective compounds and potential targets of Codonopsis pilosula were established using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database. The genes related to HCC were obtained through the GeneCards database. The interactive genes were imported into the Visualization and Integrated Discovery database for Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal enrichment, and the hub genes were screened out. The Cancer Genome Atlas database was used to construct a prognosis model, and the prognosis and clinicopathological correlation were analyzed. In in vitro experiments, we verified the effects of luteolin, an active compound of Codonopsis pilosula, on the proliferation, cell cycle, apoptosis and migration of HCC cells.

Results

A total of 21 effective compounds of Codonopsis pilosula and 98 potential downstream target genes were screened through the TCMSP database, and 1406 HCC target genes were obtained through the GeneCards database. Finally, 53 interacting genes between the two databases were obtained, among which, the 10 key node genes were CASP3, TP53, MDM2, AKT1, ESR1, BCL2L1, MCL1, HSP90AA1, CASP9, and CCND1, involving 77 typical GO terms and 72 KEGG signals. The Kaplan-Meier survival curve of the model group showed that the overall survival of the low-risk group was significantly higher than that of the high-risk group. Luteolin significantly inhibited the proliferation and migration of HCC cells, induced apoptosis, and increased the G2/M phase ratio. Mechanistically, luteolin significantly inhibited the phosphorylation of MAPK-JNK and Akt (Thr308) and subsequently led to upregulation of ESR1. Pharmacological inhibition of ESR1 with fulvestrant enhanced cell viability and migration and attenuated apoptosis.

Conclusion

Codonopsis pilosula has potential for clinical development due to its anti-HCC properties. Luteolin, the effective component of Codonopsis pilosula, plays anti-HCC role through AKT- or MAPK-JNK signaling mediated ESR1.

N6-methylandenosine-related immune genes correlate with prognosis and immune landscapes in gastric cancer

OBJECTIVES

This study aimed to probe into the significance of N6-methyladenosine (m6A)-related immune genes (m6AIGs) in predicting prognoses and immune landscapes of patients with gastric cancer (GC).

METHODS

The clinical data and transcriptomic matrix of GC patients were acquired from The Cancer Genome Atlas database. The clinically meaningful m6AIGs were acquired by univariate Cox regression analysis. GC patients were stratified into different clusters via consensus clustering analysis and different risk subgroups via m6AIGs prognostic signature. The clinicopathological features and tumor microenvironment (TME) in the different clusters and different risk subgroups were explored. The predictive performance was evaluated using the KM method, ROC curves, and univariate and multivariate regression analyses. Moreover, we fabricated a nomogram based on risk scores and clinical risk characteristics. Biological functional analysis was performed based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways. The connectivity map was used to screen out potential small molecule drugs for GC patients.

RESULTS

A total of 14 prognostic m6AIGs and two clusters based on 14 prognostic m6AIGs were identified. A prognostic signature based on 4 m6AIGs and a nomogram based on independent prognostic factors was constructed and validated. Different clusters and different risk subgroups were significantly correlated with TME scores, the distribution of immune cells, and the expression of immune checkpoint genes. Some malignant and immune biological processes and pathways were correlated with the patients with poor prognosis. Ten small molecular drugs with potential therapeutic effect were screened out.

CONCLUSIONS

This study revealed the prognostic role and significant values of m6AIGs in GC, which enhanced the understanding of m6AIGs and paved the way for developing predictive biomarkers and therapeutic targets for GC.

Comprehensive analysis of ESR1-related ceRNA axis as a novel prognostic biomarker in hepatocellular carcinoma

Aims: To further understand, detect and treat hepatocellular carcinoma (HCC), it is urgent to conduct more in-depth research on the mechanism of sex-associated differences. Materials & methods: We established a ceRNA triple regulatory axis associated with ESR1 in HCC and performed expression, survival and nuclear-cytoplasmic localization analyses. In addition to this, we performed methylation analysis and immune infiltration analysis of the ceRNA axis. Results: We constructed the LINC01018/hsa-miR-197-3p/GNA14 (lncRNA/miRNA/mRNA) ceRNA axis to further explain the mechanism of sex-related prognosis in the development of HCC and to provide new insights into candidate biomarkers for targeted therapies. Conclusion: Our study is an innovative attempt at demonstrating the mechanism underlying the prognosis associated with sex differences in HCC by constructing a ceRNA axis (LINC01018/hsa-miR-197-3p/GNA14).

Comprehensive Analysis of the Correlation Between Pyroptosis-Related LncRNAs and Tumor Microenvironment, Prognosis, and Immune Infiltration in Hepatocellular Carcinoma

Background: Accumulating evidence shows that pyroptosis plays a crucial role in hepatocellular carcinoma (HCC). However, the relationship between pyroptosis-related long non-coding RNAs (lncRNAs) and HCC tumor characteristics remains enigmatic. We aimed to explore the predictive effect of pyroptosis-related lncRNAs (PRLs) in the prognosis of HCC.

Methods: We comprehensively analyzed the role of the PRLs in the tumor microenvironment and HCC prognosis by integrating genomic data from patients of HCC. Consensus clustering analysis of PRLs was applied to identify HCC subtypes. A prognostic model was then established with a training cohort from The Cancer Genome Atlas (TCGA) using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Further, we evaluated the accuracy of this predictive model using a validation set. We predicted IC50s of commonly used chemotherapeutic and targeted drugs through the R package pRRophetic.

Results: Based on pyroptosis-related lncRNAs, a prognostic risk signature composed of seven PRLs (MKLN1AS, AL031985.3, SNHG4, GHRLOS, AC005479.2, AC099850.4, and AC026412.3) was established. For long-term prognosis of HCC patients, our model shows excellent accuracy to forecast overall survival of HCC individuals both in training set and testing set. We found a significant correlation between clinical features and the risk score. Patients in the high-risk group had tumor characteristics associated with progression such as aggressive pathological grade and stage. Besides that, gene set enrichment analysis (GSEA) showed that cell cycle and focal adhesion were significantly enriched in the high-risk group.

Conclusion: The association of the risk model constituted by these seven pyroptosis-related lncRNAs with clinical prognosis, tumor microenvironment, chemotherapy and small molecule drugs was evaluated. Our study provides strong evidence for individualized prediction of prognosis, shedding light on immunotherapy in HCC patients.