Identification and Validation of Hub Genes Associated With Hepatocellular Carcinoma Via Integrated Bioinformatics Analysis

RACGAP1 and MKI67 are potential prognostic biomarker in hepatocellular carcinoma caused by HBV/HCV via lactylation

Introduction

Hepatocellular carcinoma (HCC) is recognized as the prime and lethal form of liver cancer caused by the hepatitis B virus (HBV) and hepatitis C virus (HCV) globally. Lactate is an end product of glycolysis that influences epigenetic expression through histone lactylation. While MKI67 and RACGAP1 play crucial roles in HBV- and HCV-related HCC. However, the role of lactylation-related genes (LRGs) effects in this context remains unclear. This study innovatively explored the role of LRGs in HBV/HCV-associated HCC, identifying novel biomarkers for diagnosis and prognosis.

Methods

The present study used various online databases for analysis, and the findings were validated via immunohistochemical (IHC) analysis of HCC patient samples (n=60).

Results

We identified six signature LRGs (ALB, G6PD, HMGA1, MKI67, RACGAP1, and RFC4) possess prognostic potential, correlation with immune infiltration, and lactylation-related pathways, providing novel insights into tumor microenvironment (TME) of HCC. Moreover, MKI67 and RACGAP1 were significantly associated with HBV- and HCV-related HCC. IHC confirmed these findings, with high expression of MKI67 and RACGAP1 was significantly linked with HBV/HCV-associated HCC compared to non-viral HCC. The expression is also significantly associated with key clinical variables.

Conclusion

Our results suggest that MKI67 and RACGAP1 could serve as promising biomarkers for detecting and predicting HCC caused by HBV/HCV via lactylation, opening a new direction for immune-targeted therapies.

Identification of key exosomes-related genes in hepatitis B virus-related hepatocellular carcinoma

One of the primary risk factors for hepatocellular carcinoma (HCC) is the hepatitis B virus (HBV). Exosomes have a significant impact on the dissemination of HBV-infected HCC. This study aimed to screen HBV exosome-related hub genes in HCC for a better understanding of the HCC pathogenic mechanism. First, multiple HBV-induced HCC datasets were collected from the Gene Expression Omnibus (GEO) database, and the exosome-related gene set was obtained from relevant literature. Nine HBV-related HCC exosome hub genes (HP, C9, APOA1, PON1, TTR, LPA, FCN2, FCN3, and MBL2) were selected through differential analysis and network analysis. An analysis of the receiver operation characteristic (ROC) revealed that these genes had good diagnostic value. These hub genes were primarily enriched in biological processes such as the citrate cycle tca cycle, phenylalanine metabolism, and fatty acid metabolism, according to gene set enrichment analysis (GSEA). Furthermore, this study predicted the miRNA (hsa-miR-590-5p) targeting LPA, as well as 12 lncRNAs (AL121655, SAP30-DT, LINC00472, etc.) targeting hsa-miR-590-5p. Finally, nelarabine, methylprednisolone, and methylprednisolone were predicted to be possible medications that target the hub gene based on the CellMiner database. To sum up, this work was crucial for discovering new biomarkers and comprehending the function of exosome-related genes in the growth of HBV-infected HCC.

Comparative transcriptomic analysis uncovers molecular heterogeneity in hepatobiliary cancers

Hepatobiliary cancers (HBCs) pose a major global health challenge, with a lack of effective targeted biomarkers. Due to their complex anatomical locations, shared risk factors, and the limitations of targeted therapies, generalized treatment strategies are often used for gallbladder cancer (GBC), hepatocellular carcinoma (HCC), and intrahepatic cholangiocarcinoma (ICC). This study aimed to identify specific transcriptomic signatures in GBC, HCC, and ICC. The transcriptomic data analysis revealed distinct expression profiles, highlighting complex molecular heterogeneity within these cancers, even within the same organ system. Functional annotation revealed distinct biological pathways associated with each type of HBCs. GBC was linked to cell cycle regulation, HCC was associated with immune system modulation, and ICC was involved in metabolic dysregulation, particularly lipid metabolism. Gene co-expression network (GCN) and protein-protein interaction (PPI) network analyses identified potential key genes, such as MAPK3 and ERBB2 in GBC, AC069287.1 and ACTN2 in HCC, and TRPC1 and BACE1 in ICC. The FOX family of transcription factors (TFs) was conserved across all three cancer types. To further explore the relationship between Epithelial-Mesenchymal Transition (EMT) and the identified hub genes and TFs, an EMT score analysis was conducted. This analysis revealed distinct phenotypic characteristics in each cancer type, with TFs identified in GBC and ICC showing a stronger correlation with EMT compared to those in HCC. External validation using The Cancer Genome Atlas (TCGA) databases confirmed the expression of candidate genes, underscoring their potential as therapeutic targets. These findings provide valuable insights into the molecular heterogeneity and complexity of HBCs, opening new avenues for personalized therapeutic interventions.

Identifying new molecular signatures and potential therapeutics for idiopathic pulmonary fibrosis: a network medicine approach

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease characterized by excessive collagen deposition and fibrosis of the lung parenchyma, leading to respiratory failure. The molecular mechanisms underlying IPF pathogenesis remain incompletely understood, hindering the development of effective therapeutic strategies. We have used a network medicine approach to comprehensively analyze molecular interactions and identify novel molecular signatures and potential therapeutics associated with IPF progression. Our integrative analysis revealed dysregulated molecular networks that are central to IPF pathophysiology. We have highlighted key molecular players and signaling pathways that are implicated in aberrant fibrotic processes. This systems-level understanding enables the identification of new biomarkers and therapeutic targets for IPF, providing potential avenues for precision medicine. Drug repurposing analysis revealed several drug candidates with anti-fibrotic, anti-inflammatory, and anti-cancer activities that could potentially slow fibrotic progression and improve patient outcomes. This study offers new insights into the molecular underpinnings of IPF and highlights network medicine approaches in uncovering complex disease mechanisms. The molecular signatures and therapeutic targets identified hold promise for developing precision therapies tailored to individual patients, ultimately advancing the management of this debilitating lung disease.

Exploring gene regulatory interaction networks and predicting therapeutic molecules for hypopharyngeal cancer and EGFR-mutated lung adenocarcinoma

Hypopharyngeal cancer is a disease that is associated with EGFR-mutated lung adenocarcinoma. Here we utilized a bioinformatics approach to identify genetic commonalities between these two diseases. To this end, we examined microarray datasets from GEO (Gene Expression Omnibus) to identify differentially expressed genes, common genes, and hub genes between the selected two diseases. Our analyses identified potential therapeutic molecules for the selected diseases based on 10 hub genes with the highest interactions according to the degree topology method and the maximum clique centrality (MCC). These therapeutic molecules may have the potential for simultaneous treatment of these diseases.

Comprehensive Profiling and Therapeutic Insights into Differentially Expressed Genes in Hepatocellular Carcinoma

Background: Drug repurposing is a strategy that complements the conventional approach of developing new drugs. Hepatocellular carcinoma (HCC) is a highly prevalent type of liver cancer, necessitating an in-depth understanding of the underlying molecular alterations for improved treatment. Methods: We searched for a vast array of microarray experiments in addition to RNA-seq data. Through rigorous filtering processes, we have identified highly representative differentially expressed genes (DEGs) between tumor and non-tumor liver tissues and identified a distinct class of possible new candidate drugs. Results: Functional enrichment analysis revealed distinct biological processes associated with metal ions, including zinc, cadmium, and copper, potentially implicating chronic metal ion exposure in tumorigenesis. Conversely, up-regulated genes are associated with mitotic events and kinase activities, aligning with the relevance of kinases in HCC. To unravel the regulatory networks governing these DEGs, we employed topological analysis methods, identifying 25 hub genes and their regulatory transcription factors. In the pursuit of potential therapeutic options, we explored drug repurposing strategies based on computational approaches, analyzing their potential to reverse the expression patterns of key genes, including AURKA, CCNB1, CDK1, RRM2, and TOP2A. Potential therapeutic chemicals are alvocidib, AT-7519, kenpaullone, PHA-793887, JNJ-7706621, danusertibe, doxorubicin and analogues, mitoxantrone, podofilox, teniposide, and amonafide. Conclusion: This multi-omic study offers a comprehensive view of DEGs in HCC, shedding light on potential therapeutic targets and drug repurposing opportunities.

The Hepatic Antioxidant System Damage Induced with the Cafeteria (CAF) Diet Is Largely Counteracted Using SCD Probiotics during Development of Male Wistar Rats

The cafeteria (CAF) diet, reflective of predominant Western dietary behaviors, is implicated in hastening weight gain, subsequently resulting in health complications such as obesity, diabetes, and cancer. To this end, it is vital to notice the deleterious consequences of the CAF regimen prior to the onset of complications, which is fundamental for early intervention in the context of numerous diseases. Probiotic-derived postbiotic metabolites have gained attention for their antioxidative properties, offering a potential countermeasure against oxidative stress. This research sought to discern the protective efficacy of SCD Probiotics against liver glutathione system damage arising from the CAF diet during developmental phases. Male Wistar rats, from weaning on day 21 to day 56, were categorized into four groups: a control on a conventional diet; a group on a standard diet enriched with SCD Probiotics; a mixed-diet group comprising both CAF and standard feed; and a combination diet group supplemented with SCD Probiotics. Through the application of real-time PCR, enzyme activity assessments, and quantitative metabolite analyses, our findings highlight the CAF diet's adverse influence on the liver's antioxidant defenses via shifts in gene expression. Yet, the inclusion of SCD Probiotics mostly ameliorated these harmful effects. Remarkably, the positive regulatory influence of SCD Probiotics on the liver's antioxidant system was consistently observed, independent of the CAF diet's presence.

Loss of ficolin-3 expression is associated with poor prognosis in patients with hepatocellular carcinoma

Background: Ficolin-3 (FCN3) is a well-known circulating pattern recognition molecule which plays a role in host immune responses to cancer via activation of the lectin complement pathway. Nevertheless, the clinical significance of FCN3 in patients with hepatocellular carcinoma (HCC) is unclear. Methods: Eighty-seven HCC patients who received hepatectomy at our hospital were included. Immunohistochemical staining was used to assess the FCN3 expression in both tumorous and non-tumorous tissues from the patients, who were classified into high and low expression groups. Differences in clinicopathological characteristics between the two groups were then analyzed. Results: Survival was significantly associated with FCN3 immunohistochemical score (p for trend = 0.048). Kaplan-Meier analysis revealed a higher overall survival rate in the patients with a high FCN3 expression than in those with a low FCN3 expression (p=0.031). A high FCN3 expression in tumor tissue was independently associated with better overall survival (p=0.042). However, multivariate analysis showed that FCN3 expression was not an independent risk factor for overall survival. Conclusion: Our findings suggest that FCN3 is significantly related to the prognosis of HCC. FCN3 may be a prognostic marker in patients with HCC.

Ficolin-2: A potential immune-related therapeutic target with low expression in liver cancer

Objective

This study aimed to investigate the role of ficolin-2 (FCN2) in the development and course of hepatocellular carcinoma (HCC) and to contribute to the evolution of innovative HCC therapeutics.

Methods

Oncomine, GEPIA (Gene Expression Profiling Interactive Analysis), TISIDB (Tumor Immune System Interactions and Drug Bank database), UALCAN (University of Alabama at Birmingham Cancer data analysis portal), UCSC (University of California, Santa Cruz), R package, the Kaplan–Meier technique, Cox regression analysis, LinkedOmics, Pearson’s correlation, and a nomogram were used to investigate the prognostic value of FCN2 in HCC. Co-expressed genes were screened. A protein–protein interaction network was created using the STRING database. Finally, immunohistochemistry was performed to establish the expression of FCN2 in HCC tissues. A pan-cancer study centered on HCC-related molecular analysis was also conducted to look for a link between FCN2 and immune infiltration, immune modulators, and chemokine receptors.

Results

In HCC tissues, the expression of FCN2 was observed to be lower than that in normal tissues. This was connected to the HCC marker alpha-fetoprotein, showing that FCN2 is involved in the development and progression of cancer. FCN2 may act through Staphylococcus aureus infection, lectins, and other pathways. Furthermore, at the immune level, the expression of FCN2 in HCC was associated with some immune cell infiltration, immunomodulators, and chemokine receptors.

Conclusion

FCN2 may be an immune checkpoint inhibitor for HCC, creating a breakthrough in the treatment of HCC.

Pathway analysis of sepsis-induced changes gene expression

Background

Sepsis reaction is a response to an infection composed of genetic elements. This research aims to better understand how sepsis affects the molecular pathways in whole blood samples.

Methods

Whole blood samples from healthy controls (n = 18), sepsis nonsurvivors (n = 9), and sepsis survivors (n = 26) were retrieved from the gene expression omnibus (GEO) collection of the national center for biotechnology information (NCBI) (accession number GSE54514). The NCBI's GEO2R program was used to determine differential expression, and the ingenuity pathway analysis (IPA) software was utilized to do a pathway analysis.

Results

In sepsis patients, 2672 genes were substantially differently expressed (p value 0.05). One thousand three hundred four genes were overexpressed, and one thousand three hundred sixty-eight were under-expressed. The inhibition of ARE-mediated mRNA degradation pathway and the Pl3K/AKT signaling spliceosomal cycle were the most significant canonical pathways identified by ingenuity pathway analysis (IPA). The IPA upstream analysis predicted the ESR1, SIRT1, and PTPRR proteins, and the drugs filgrastim and fluticasone were top transcriptional regulators.

Conclusions

The inhibition of ARE-mediated mRNA degradation pathway and the Pl3K/AKT signaling spliceosomal cycle were highlighted as essential pathways of inflammation by IPA, indicating widespread cancer owing to sepsis. Our data imply that sepsis considerably influences gene pathways in whole blood samples, pointing to possible targets for sepsis treatment.

Identification of Metabolic Pathways Differentially Regulated in Somatic and Zygotic Embryos of Maritime Pine

Embryogenesis is a complex phase of conifer development involving hundreds of genes, and a proper understanding of this process is critical not only to produce embryos with different applied purposes but also for comparative studies with angiosperms. A global view of transcriptome dynamics during pine somatic and zygotic embryogenesis is currently missing. Here, we present a genome-wide transcriptome analysis of somatic and zygotic embryos at three developmental stages to identify conserved biological processes and gene functions during late embryogenesis. Most of the differences became more significant as the developmental process progressed from early to cotyledonary stages, and a higher number of genes were differentially expressed in somatic than in zygotic embryos. Metabolic pathways substantially affected included those involved in amino acid biosynthesis and utilization, and this difference was already observable at early developmental stages. Overall, this effect was found to be independent of the line (genotype) used to produce the somatic embryos. Additionally, transcription factors differentially expressed in somatic versus zygotic embryos were analyzed. Some potential hub regulatory genes were identified that can provide clues as to what transcription factors are controlling the process and to how the observed differences between somatic and zygotic embryogenesis in conifers could be regulated.

A Novel Gene Signature Based on CDC20 and FCN3 for Prediction of Prognosis and Immune Features in Patients with Hepatocellular Carcinoma

Long-term survivals of patients with hepatocellular carcinoma (HCC) remain unfavorable, which is largely attributed to active carcinogenesis. Growing studies have suggested that the reliable gene signature could act as an independent prognosis factor for HCC patients. We tried to screen the survival-related genes and develop a prognostic prediction model for HCC patients based on the expression profiles of the critical survival-related genes. In this study, we analyzed TCGA datasets and identified 280 genes with differential expressions (125 increased genes and 155 reduced genes). We analyzed the prognosis value of the top 10 dysregulated genes in HCC patients and identified three critical genes, including FCN3, CDC20, and E2F1, which were confirmed to be associated with long-term survival in both TCGA and ICGC datasets. The results of the LASSO model screened CDC20 and FCN3 for the development of the prognostic model. The CDC20 expression was distinctly increased in HCC specimens, while the FCN3 expression was distinctly decreased in HCC. At a suitable cutoff, patients were divided into low-risk and high-risk groups. Survival assays revealed that patients in high-risk groups exhibited a shorter overall survival than those in low-risk groups. Finally, we examine the relationships between risk score and immune infiltration abundance in HCC and observed that risk score was positively correlated with infiltration degree of B cells, T cell CD4+ cells, neutrophil, macrophage, and myeloid dendritic cells. Overall, we identified three critical survival-related genes and used CDC20 and FCN3 to develop a novel model for predicting outcomes and immune landscapes for patients with HCC. The above three genes also have a high potential for targeted cancer therapy of patients with HCC.

An Integrated Fibrosis Signature for Predicting Survival and Immunotherapy Efficacy of Patients With Hepatocellular Carcinoma

Introduction: Fibrosis, a primary cause of hepatocellular carcinoma (HCC), is intimately associated with inflammation, the tumor microenvironment (TME), and multiple carcinogenic pathways. Currently, due to widespread inter- and intra-tumoral heterogeneity of HCC, the efficacy of immunotherapy is limited. Seeking a stable and novel tool to predict prognosis and immunotherapy response is imperative. Methods: Using stepwise Cox regression, least absolute shrinkage and selection operator (LASSO), and random survival forest algorithms, the fibrosis-associated signature (FAIS) was developed and further validated. Subsequently, comprehensive exploration was conducted to identify distinct genomic alterations, clinical features, biological functions, and immune landscapes of HCC patients. Results: The FAIS was an independent prognostic predictor of overall survival and recurrence-free survival in HCC. In parallel, the FAIS exhibited stable and accurate performance at predicting prognosis based on the evaluation of Kaplan-Meier survival curves, receiver operator characteristic curves, decision curve analysis, and Harrell's C-index. Further investigation elucidated that the high-risk group presented an inferior prognosis with advanced clinical traits and a high mutation frequency of TP53, whereas the low-risk group was characterized by superior CD8⁺ T cell infiltration, a higher TIS score, and a lower TIDE score. Additionally, patients in the low-risk group might yield more benefits from immunotherapy. Conclusion: The FAIS was an excellent scoring system that could stratify HCC patients and might serve as a promising tool to guide surveillance, improve prognosis, and facilitate clinical management.

Single-Cell Transcriptomics Reveals the Expression of Aging- and Senescence-Associated Genes in Distinct Cancer Cell Populations

The human aging process is associated with molecular changes and cellular degeneration, resulting in a significant increase in cancer incidence with age. Despite their potential correlation, the relationship between cancer- and ageing-related transcriptional changes is largely unknown. In this study, we aimed to analyze aging-associated transcriptional patterns in publicly available bulk mRNA-seq and single-cell RNA-seq (scRNA-seq) datasets for chronic myelogenous leukemia (CML), colorectal cancer (CRC), hepatocellular carcinoma (HCC), lung cancer (LC), and pancreatic ductal adenocarcinoma (PDAC). Indeed, we detected that various aging/senescence-induced genes (ASIGs) were upregulated in malignant diseases compared to healthy control samples. To elucidate the importance of ASIGs during cell development, pseudotime analyses were performed, which revealed a late enrichment of distinct cancer-specific ASIG signatures. Notably, we were able to demonstrate that all cancer entities analyzed in this study comprised cell populations expressing ASIGs. While only minor correlations were detected between ASIGs and transcriptome-wide changes in PDAC, a high proportion of ASIGs was induced in CML, CRC, HCC, and LC samples. These unique cellular subpopulations could serve as a basis for future studies on the role of aging and senescence in human malignancies.