Genetic expression and mutational profile analysis in different pathologic stages of hepatocellular carcinoma patients

PNMA1 is a novel immune modulator and therapeutic target in hepatocellular carcinoma linked to bile acid metabolism

Hepatocellular carcinoma (HCC) necessitates innovative prognostic biomarkers and therapeutic targets. By investigating PNMA1 in HCC via the TCGA and GEO databases and our clinical data, we found that its overexpression is associated with worse survival. The relevance of PNMA1 extends to immune factors such as M1 macrophages, CD8+ T cells, and immune checkpoints. Mechanistically, PNMA1 shapes a suppressive tumor microenvironment strongly linked to bile acid metabolism. It promotes tumor progression via immune inhibition and PI3K-AKT pathway activation. Notably, PNMA1 has emerged as a promising therapeutic target for tyrosine kinase inhibitors, as confirmed by reduced IC50 values and molecular docking. Experimental knockdown of PNMA1 hindered HepG2 cell proliferation and migration. Furthermore, PNMA1 is a pivotal HCC biomarker and therapeutic target with a focus on cancer progression, immune modulation, and bile acid metabolism.

Tissue inhibitor of metalloproteinase-3 expression affects clinicopathological features and prognosis of aflatoxin B1-related hepatocellular carcinoma

BACKGROUND

The dysregulation of tissue inhibitor of metalloproteinase-3 (TIMP3) was positively correlated with the progression of hepatocellular carcinoma (HCC). However, it is not clear whether TIMP3 expression is associated with the clinicopathological features and prognosis of aflatoxin B1 (AFB1)-related HCC (AHCC).

AIM

To assess the effects of TIMP3 expression on the clinicopathological features and prognosis of AHCC.

METHODS

A retrospective study, including 182 patients with AHCC, was conducted to explore the link between TIMP3 expression in cancerous tissues and the clinicopathological characteristics and prognosis of AHCC. TIMP3 expression was detected by immunohistochemistry and its effects on the clinicopathological features and prognosis of AHCC were evaluated by Kaplan-Meier survival analysis and Cox regression survival analysis. Odds ratio, hazard ratio (HR), median overall survival time (MST), median tumor recurrence-free survival time (MRT), and corresponding 95% confidential interval (CI) was calculated to evaluate the potential of TIMP3 expression in predicting AHCC prognosis.

RESULTS

Kaplan-Meier survival analysis showed that compared with high TIMP3 expression, low TIMP3 expression in tumor tissues significantly decreased the MST (36.00 mo vs 18.00 mo) and MRT (32.00 mo vs 16 mo) of patients with AHCC. Multivariate Cox regression survival analysis further proved that decreased expression of TIMP3 increased the risk of death (HR = 2.85, 95%CI: 2.04-4.00) and tumor recurrence (HR = 2.26, 95%CI: 1.57-3.26). Furthermore, decreased expression of TIMP3 protein in tissues with AHCC was significantly correlated with tumor clinicopathological features, such as tumor size, tumor grade and stage, tumor microvessel density, and tumor blood invasion. Additionally, TIMP3 protein expression was also negatively associated with amount of AFB1-DNA adducts in tumor tissues.

CONCLUSION

These findings indicate that the dysregulation of TIMP3 expression is related to AHCC biological behaviors and affects tumor outcome, suggesting that TIMP3 may act as a prognostic biomarker for AHCC.

Development and Validation of a Novel Nomogram Integrated with Hypoxic and Lactate Metabolic Characteristics for Prognosis Prediction in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. Accumulating evidence indicates that hypoxia and lactate metabolism play critical roles in tumor progression and therapeutic efficacy. This study aimed to construct a hypoxia- and lactate metabolism-related prognostic model (HLPM) to evaluate survival and treatment responses for HCC patients and develop a nomogram integrated with HLPM and clinical characteristics for prognosis prediction in HCC.

Methods

Expression profile and clinical data of HCC were obtained from TCGA and ICGC databases. The univariate, LASSO and stepwise multivariate Cox analyses were used to identify the hypoxia- and lactate metabolism-related biomarkers, whose expression levels were then validated in 14 pairs tissue samples and single-cell RNA sequencing dataset. Kaplan-Meier survival curves were utilized to assess the prognostic values of biomarkers or models. Analyses of ImmuCellAI, TIDE and drug sensitivity were conducted to evaluate the therapeutic responses of patients. Furthermore, the nomogram integrated with hypoxic and lactate metabolic characteristics was established through univariate and multivariate Cox analyses. ROC curves, C-index, and calibration curves were depicted to evaluate the performance of the nomogram.

Results

Five hypoxia- and lactate metabolism-related biomarkers (KIF20A, IRAK1, ADM, PPARGC1A and EPO) were used to construct HLPM. The expression of five prognostic biomarkers was validated in 14 pairs tissue samples and single-cell RNA sequencing dataset. Analyses of ImmuCellAI, TIDE and drug sensitivity implied that patients with low-risk score were more sensitive to immunotherapy and major chemotherapeutic agents. The nomogram that contained age, histological grade and risk score of HLPM was developed and exhibited a better capacity in prognosis prediction than HLPM only.

Conclusion

A novel nomogram integrated with hypoxic and lactate metabolic characteristics was developed and validated for prognosis prediction in HCC, providing insight into personalized decision-making in clinical management.

Analysis of Somatic Mutations in the TCGA-LIHC Whole Exome Sequence to Identify the Neoantigen for Immunotherapy in Hepatocellular Carcinoma

There are numerous clinically proven methods for treating cancer worldwide. Immunotherapy has been used to treat cancer with significant success in the current studies. The purpose of this work is to identify somatically altered target gene neoantigens and investigate liver cancer-related immune cell interaction and functional changes for potential immunotherapy in future clinical trials. Clinical patient data from the Cancer Genome Atlas (TCGA) database were used in this investigation. The R maf utility package was used to perform somatic analysis. The 17-mer peptide neoantigens were extracted using an in-house Python software called Peptide.py. Additionally, the epitope analysis was conducted using NetMHCpan4.1 program. Neopeptide immunogenicity was assessed using DeepCNN-Ineo, and tumor immune interaction, association with immune cells, correlation, and survival analysis were assessed using the TIMER web server. Based on somatic mutation analysis, we have identified the top 10 driver genes (TP53, TNN, CTNNB1, MUC16, ALB, PCLO, MUC4, ABCA13, APOB, and RYR2). From the superfamily of 20 HLA (Human leukocyte antigens) allele epitopes, we discovered 5653 neopeptides. Based on T cell receptor face hydrophobic analysis, these neopeptides were subjected to immunogenicity investigation. A mutation linked to tumor growth may have an impact on immune cells. According to this study's correlation and survival analysis, all driver genes may function as immune targets for liver cancer. These genes are recognized to be immune targets. In the future, immune checkpoint inhibitors may be developed to prolong patient survival times and prevent hepatocellular carcinoma (HCC) through immunotherapy.

Identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma

Background

This study aimed to examine glycolysis/gluconeogenesis-related genes in hepatocellular carcinoma (HCC) and evaluate their potential roles in HCC progression and immunotherapy response.

Methods

Data analyzed in this study were collected from GSE14520, GSE76427, GSE174570, The Cancer Genome Atlas (TCGA), PXD006512, and GSE149614 datasets, metabolic pathways were collected from MSigDB database. Differentially expressed genes (DEGs) were identified between HCC and controls. Differentially expressed glycolysis/gluconeogenesis-related genes (candidate genes) were obtained and consensus clustering was performed based on the expression of candidate genes. Bioinformatics analysis was used to evaluate candidate genes and screen prognostic genes. Finally, the key results were tested in HCC patients.

Results

Thirteen differentially expressed glycolysis/gluconeogenesis-related genes were validated in additional datasets. Consensus clustering analysis identified two distinct patient clusters (C1 and C2) with different prognoses and immune microenvironments. Immune score and tumor purity were significantly higher in C1 than in C2, and CD4+ memory activated T cell, Tfh, Tregs, and macrophage M0 were higher infiltrated in HCC and C1 group. The study also identified five intersecting DEGs from candidate genes in TCGA, GSE14520, and GSE141198 as prognostic genes, which had a protective role in HCC patient prognosis. Compared with the control group, the prognostic genes all showed decreased expression in HCC patients in RT-qPCR and Western blot analyses. Flow cytometry verified the abnormal infiltration level of immune cells in HCC patients.

Conclusion

Results showed that glycolysis/gluconeogenesis-related genes were associated with patient prognosis, immune microenvironment, and response to immunotherapy in HCC. It suggests that the model based on five prognostic genes may valuable for predicting the prognosis and immunotherapy response of HCC patients.

Cuproptosis-related lncRNAs predict the prognosis and immune response in hepatocellular carcinoma

Cuproptosis has been recently used to indicate unique biological processes triggered by Cu action as a new term. This study aimed to explore the relationship between cuproptosis-related lncRNA and hepatocellular carcinoma (HCC) with regard to immunity and prognosis. RNA sequencing and the clinical data were downloaded from the TCGA database. The cuproptosis-related genes were sorted out through literature study. The cuproptosis-related IncRNA signature was identified by Cox regression analysis and the least absolute shrinkage and selection operator analysis. The K-M survival analysis, receiver operating characteristic analysis, and C-index analysis were adopted to evaluate the prognostic prediction performance of the signature. The functional enrichment, immune infiltration and tumor mutation analysis were further analyzed. Subsequently, we predicted the differences in chemosensitivity from tumor gene expression levels for some chemotherapy drugs. The prognostic signature consisting of 5 overall survival-related CUPlncRNAs. It showed an extraordinary ability to predict the prognoses of patients with HCC. The signature can predict the abundance of immune cell infiltration, immune functions, expression of immune checkpoint inhibitors, m6A genes, which was supported by the GO biological process and KEGG analysis. And it may also have a guiding effect in the sensitivity of different chemotherapeutic drugs and tumor mutation burden. We constructed a new cuproptosis-related lncRNA signature for HCC patients. The model can be used for prognostic prediction and immune evaluation, providing a reference for immunotherapies and targeted therapies.

Advances in SEMA3F regulation of clinically high-incidence cancers

Cancer has become a leading cause of morbidity and mortality in recent years. Its high prevalence has had a severe impact on society. Researchers have achieved fruitful results in the causative factors, pathogenesis, treatment strategies, and cancer prevention. Semaphorin 3F (SEMA3F), a member of the signaling family, was initially reported in the literature to inhibit the growth, invasion, and metastasis of cancer cells in lung cancer. Later studies showed it has cancer-inhibiting effects in malignant tumors such as breast, colorectal, ovarian, oral squamous cell carcinoma, melanoma, and head and neck squamous carcinoma. In contrast, recent studies have reported that SEMA3F is expressed more in hepatocellular carcinoma than in normal tissue and promotes metastasis of hepatocellular carcinoma. We chose lung, breast, colorectal, and hepatocellular carcinomas with high clinical prevalence to review the roles and molecular mechanisms of SEMA3F in these four carcinomas. We concluded with an outlook on clinical interventions for patients targeting SEMA3F.

NUDT1 Could Be a Prognostic Biomarker and Correlated with Immune Infiltration in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is a malignant tumor with high morbidity and mortality. As a member of the Nudix hydrolase superfamily, Nudix (nucleoside diphosphate-linked moiety X)-type motif 1 (NUDT1) is closely related to the occurrence and development of cancer. Our study aims to explore the role of NUDT1 in ccRCC and its relationship with immune infiltration.

Methods

The NUDT1 expression matrix and corresponding clinical information were obtained from The Cancer Genome Atlas (TCGA) database. The expression difference of NUDT1 in ccRCC and its relationship with the clinical characteristics were investigated using R software. Kaplan-Meier (K-M) analysis, univariate Cox regression, multivariate Cox regression, receiver operating characteristic (ROC) curve, and nomogram were utilized to evaluate the survival and prognosis of patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to explore the function of differential genes in low- or high-expression group of NUDT1. TCGA dataset and Tumor IMmune Estimation Resource (TIMER) database were utilized to explore the relationship between NUDT1 and immune infiltration. Finally, TCGA dataset was utilized for gene set enrichment analysis (GSEA).

Results

NUDT1 was not only overexpressed in ccRCC but also significantly correlated with clinicopathological features (P < 0.05). K-M survival analysis showed that upregulated NUDT1 was closely related to the decrease of overall survival (OS) and progression-free survival (PFS) in ccRCC patients. Multivariate Cox regression revealed that NUDT1 was a independent prognostic indicator (HR = 1.437, 95% CI: 1.065-1.939, P=0.018). The ROC curve showed that NUDT1 had a certain accuracy in predicting the outcome of ccRCC patiens. Furthermore, a total of 150 coexpressed genes and 1,886 differentially expressed genes (DEGs) were identified. GO/KEGG and GSEA results suggested that NUDT1 and its DEGs were involved in the immune-related pathways. NUDT1 expression was positively correlated with infiltrating levels of regulatory T cells (Tregs), CD8⁺ T cells, follicular helper T cells, and M0 macrophages. In addition, NUDT1 was positively related to immune checkpoints, such as PD-1, LAG3, CTLA4, and CD70, in ccRCC.

Conclusion

NUDT1 plays a key role in the prognosis and immune cell infiltration of ccRCC patients, indicating its potential use as a prognostic biomarker and therapeutic target.

Expression profile and prognostic values of LSM family in skin cutaneous melanoma

Background

The like-Smith (LSM) family is a group of RNA-binding proteins involved in RNA metabolism. However, their involvement in tumors, particularly skin cutaneous melanoma (SKCM), is not fully understood. In this study, we focused on the expression profiles and prognostic values of the LSM family in SKCM.

Methods

Raw data were downloaded from The Cancer Genome Atlas. The expression profile and prognostic value of LSM genes in SKCM were explored using the GEPIA, cBioPortal, and HPA databases. Protein–protein and gene–gene interaction analyses were performed using STRING and GeneMANIA. Enrichment and Cox regression analysis were conducted using R software. The TISIDB database was used to explore the relationship between LSMs and immunomodulators. Receiver operating characteristic curves and nomogram models were constructed to validate prognostic values.

Results

mRNA and protein expression levels of LSM2, LSM4, and LSM12 were significantly elevated in SKCM. The upregulated mRNA expression of LSM2 (p = 0.0013) and LSM4 (p = 0.0043) was significantly correlated with poor overall survival in patients with SKCM, whereas only LSM2 (p = 0.049) overexpression was markedly associated with worse disease-free survival. LSM2 overexpression was an independent risk factor (p = 0.013) and was confirmed to have a high prognostic value in SKCM using the receiver operating characteristic curve (AUC = 0.942) and nomogram models. All LSM genes were identified as genomic mutations, whereas alteration of LSM2 (p = 0.0153) significantly affected the overall survival in patients with SKCM. Significant correlations were observed between LSM family expression, immune cell infiltration, and immunomodulator. Furthermore, function and pathway enrichment analysis showed that the LSM family was mainly RNA binding proteins and involved in RNA splicing and degradation.

Conclusion

Expression profiles and prognostic values of LSM in SKCM were inconsistent. Among the LSM family, only LSM2 may serve as a potential poor prognosticator and immunotherapeutic target of SKCM.

SNRPD2 Is a Novel Substrate for the Ubiquitin Ligase Activity of the Salmonella Type III Secretion Effector SlrP

Simple Summary

Salmonella is a genus of bacterial pathogens that can cause several diseases in humans and other animals. These bacteria can inject proteins known as effectors into animal cells through a secretion system. One of these effectors, SlrP, promotes the covalent addition of ubiquitin, a small eukaryotic protein, to specific host proteins, leading to an alteration of their stability or function. Here, we have performed a genetic screen to find new human targets of SlrP. In this way, we have identified SNRPD2, a core component of the spliceosome, the ribonucleoprotein complex that removes introns from eukaryotic pre-mRNA. SNRPD2 physically interacts with SlrP and is also a substrate of its ubiquitination activity. Lysines at positions 85 and 92 in SNRPD2 are among the residues that were ubiquitinated in the presence of SlrP. The identification of new host targets of Salmonella effectors contributes to a better understanding of the biological processes that are highjacked by these pathogens during infection, and can help in the design of future therapeutic strategies.

Abstract

SlrP is a protein with E3 ubiquitin ligase activity that is translocated by Salmonella enterica serovar Typhimurium into eukaryotic host cells through a type III secretion system. A yeast two-hybrid screen was performed to find new human partners for this protein. Among the interacting proteins identified by this screen was SNRPD2, a core component of the spliceosome. In vitro ubiquitination assays demonstrated that SNRPD2 is a substrate for the catalytic activity of SlrP, but not for other members of the NEL family of E3 ubiquitin ligases, SspH1 and SspH2. The lysine residues modified by this activity were identified by mass spectrometry. The identification of a new ubiquitination target for SlrP is a relevant contribution to the understanding of the role of this Salmonella effector.

Network analysis of hepatocellular carcinoma liquid biopsies augmented by single-cell sequencing data

Liquid biopsy, the analysis of body fluids, represents a promising approach for disease diagnosis and prognosis with minimal intervention. Sequencing cell-free RNA derived from liquid biopsies has been very promising for the diagnosis of several diseases. Cancer research, in particular, has emerged as a prominent candidate since early diagnosis has been shown to be a critical determinant of disease prognosis. Although high-throughput analysis of liquid biopsies has uncovered many differentially expressed genes in the context of cancer, the functional connection between these genes is not investigated in depth. An important approach to remedy this issue is the construction of gene networks which describes the correlation patterns between different genes, thereby allowing to infer their functional organization. In this study, we aimed at characterizing extracellular transcriptome gene networks of hepatocellular carcinoma patients compared to healthy controls. Our analysis revealed a number of genes previously associated with hepatocellular carcinoma and uncovered their association network in the blood. Our study thus demonstrates the feasibility of performing gene co-expression network analysis from cell-free RNA data and its utility in studying hepatocellular carcinoma. Furthermore, we augmented cell-free RNA network analysis with single-cell RNA sequencing data which enables the contextualization of the identified network modules with cell-type specific transcriptomes from the liver.

Impact of hepatocyte-specific deletion of staphylococcal nuclease and tudor domain containing 1 (SND1) on liver insulin resistance and acute liver failure of mice

Although our previous research shows an ameliorated high-fat diet (HFD)-induced hepatic steatosis and insulin resistance in global SND1 transgenic mice, the involvement of SND1 loss-of-function in hepatic metabolism remains elusive. Herein, we aim to explore the potential impact of hepatocyte-specific SND1 deletion on insulin-resistant mice. As SND1 is reported to be linked to inflammatory response, the pathobiological feature of acute liver failure (ALF) is also investigated. Hence, we construct the conditional liver knockout (LKO) mice of SND1 for the first time. Under the condition of HFD, the absence of hepatic SND1 affects the weight of white adipose tissue, but not the gross morphology, body weight, cholesterol level, liver weight, and hepatic steatosis of mice. Furthermore, we fail to observe significant differences in either HFD-induced insulin resistance or lipopolysaccharide/D-galactosamine-induced (LPS/D-GaIN) ALF between LKO and wild type (WT) mice in terms of inflammation and tissue damage. Compared with negative controls, there is no differential SND1 expression in various species of sample with insulin resistance or ALF, based on several gene expression omnibus datasets, including GSE23343, GSE160646, GSE120243, GSE48794, GSE13271, GSE151268, GSE62026, GSE120652, and GSE38941. Enrichment result of SND1-binding partners or related genes indicates a sequence of issues related to RNA or lipid metabolism, but not glucose homeostasis or hepatic failure. Overall, hepatic SND1 is insufficient to alter the phenotypes of hepatic insulin resistance and acute liver failure in mice. The SND1 in various organs is likely to cooperate in regulating glucose homeostasis by affecting the expression of lipid metabolism-related RNA transcripts during stress.

USP7 inhibition induces apoptosis in glioblastoma by enhancing ubiquitination of ARF4

Background

Glioblastomas (GBMs) are grade IV central nervous system tumors characterized by a poor prognosis and a short median overall survival. Effective induction of GBM cell death is difficult because the GBM cell population is genetically unstable, resistant to chemotherapy and highly angiogenic. In recent studies, ubiquitin-specific protease 7 (USP7) is shown to scavenge ubiquitin from oncogenic protein substrates, so effective inhibition of USP7 may be a potential key treatment for GBM.

Methods

Immunohistochemistry and western blotting were used to detect the expression of USP7 in GBM tissues. In vitro apoptosis assay of USP7 inhibition was performed by western blotting, immunofluorescence, and flow cytometry. Anti-apoptotic substrates of USP7 were defined by Co-IP and TMT proteomics. Western blotting and IP were used to verify the relationship between USP7 and its substrate. In an in vivo experiment using an intracranial xenograft model in nude mice was constructed to assess the therapeutic effect of target USP7.

Results

Immunohistochemistry and western blotting confirmed that USP7 was significantly upregulated in glioblastoma samples. In in vitro experiments, inhibition of USP7 in GBM induced significant apoptosis. Co-IP and TMT proteomics identified a key anti-apoptotic substrate of USP7, ADP-ribosylation factor 4 (ARF4). Western blotting and IP confirmed that USP7 interacted directly with ARF4 and catalyzed the removal of the K48-linked polyubiquitinated chain that binded to ARF4. In addition, in vivo experiments revealed that USP7 inhibition significantly suppressed tumor growth and promoted the expression of apoptotic genes.

Conclusions

Targeted inhibition of USP7 enhances the ubiquitination of ARF4 and ultimately mediates the apoptosis of GBM cells. In a clinical sense, P5091 as a novel specific inhibitor of USP7 may be an effective approach for the treatment of GBM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02208-z.