Development of a Toll-Like Receptor-Based Gene Signature That Can Predict Prognosis, Tumor Microenvironment, and Chemotherapy Response for Hepatocellular Carcinoma

Prediction of the survival status and tumor microenvironment in colorectal cancer through genotyping analysis based on toll-like receptors

BACKGROUND

Colorectal cancer (CRC) ranks third in both the incidence and mortality rates among male and female cancers, and it is the leading digestive system cancer. Due to the inter- and intratumor heterogeneity of cancer, the TNM system is insufficient for predicting prognosis, necessitating the use of molecular biomarkers for prognostic prediction. Toll-like receptors (TLRs) have been associated with CRC survival rates. This study focused on the investigation of the role and potential value of TLRs in CRC genotyping to aid in immunotherapy for CRC patients.

METHODS

Differential gene expression analysis was performed on CRC transcriptomic data from The Cancer Genome Atlas database. TLRs were referred from the literature, and their intersection with differentially expressed genes (DEGs) in CRC yielded TLR-DEGs. The expression patterns of TLR-DEGs were predicted using the STRING website, and copy number variations of TLR-DEGs were analyzed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted on TLR-DEGs. ConsensusClusterPlus R package was used for clustering CRC patients, and ESTIMATE and GSEAbase were employed to analyze immune characteristics of different subtypes. Immune phenotyping scores and tumor immune dysfunction and exclusion scores were evaluated. DEGs of different subtypes were analyzed, followed by GO and KEGG enrichment analyses, the protein-protein interaction (PPI) network analysis, and further selection of hub genes. The sensitivity of drugs was assessed using the identified hub genes.

RESULTS

We identified 37 TLR-DEGs, and the PPI analysis revealed their coexpression, although they were distributed on different chromosomes. Enrichment analyses indicated that the 37 TLR-DEGs were linked to cancer cell immune response. Based on these TLR-DEGs, CRC patients were classified into three subtypes. Cluster2 exhibited lower survival rates and higher immune infiltration levels and predicted poorer response to immune checkpoint inhibitor therapy. The intersection of DEGs from cluster2 and cluster1 with DEGs from cluster2 and cluster3 yielded a set of 426 commonly shared DEGs. Enrichment analyses revealed that these shared DEGs might regulate immune cell viability. Eight common hub genes for different subtypes were further identified to predict drug-related correlations.

CONCLUSION

The developed TLR genotyping was used to predict the survival status and tumor microenvironment of CRC, providing a foundation for understanding the molecular mechanisms of TLR signaling and deepening its clinical significance.

Immune-related gene methylation prognostic instrument for stratification and targeted treatment of ovarian cancer patients toward advanced 3PM approach

Background

DNA methylation is an important mechanism in epigenetics, which can change the transcription ability of genes and is closely related to the pathogenesis of ovarian cancer (OC). We hypothesize that DNA methylation is significantly different in OCs compared to controls. Specific DNA methylation status can be used as a biomarker of OC, and targeted drugs targeting these methylation patterns and DNA methyltransferase may have better therapeutic effects. Studying the key DNA methylation sites of immune-related genes (IRGs) in OC patients and studying the effects of these methylation sites on the immune microenvironment may provide a new method for further exploring the pathogenesis of OC, realizing early detection and effective monitoring of OC, identifying effective biomarkers of DNA methylation subtypes and drug targets, improving the efficacy of targeted drugs or overcoming drug resistance, and better applying it to predictive diagnosis, prevention, and personalized medicine (PPPM; 3PM) of OC.

Method

Hypermethylated subtypes (cluster 1) and hypomethylated subtypes (cluster 2) were established in OCs based on the abundance of different methylation sites in IRGs. The differences in immune score, immune checkpoints, immune cells, and overall survival were analyzed between different methylation subtypes in OC samples. The significant pathways, gene ontology (GO), and protein-protein interaction (PPI) network of the identified methylation sites in IRGs were enriched. In addition, the immune-related methylation signature was constructed with multiple regression analysis. A methylation site model based on IRGs was constructed and verified.

Results

A total of 120 IRGs with 142 differentially methylated sites (DMSs) were identified. The DMSs were clustered into a high-level methylation group (cluster 1) and a low-level methylation group (cluster 2). The significant pathways and GO analysis showed many immune-related and cancer-associated enrichments. A methylation site signature based on IRGs was constructed, including RORC|cg25112191, S100A13|cg14467840, TNF|cg04425624, RLN2|cg03679581, and IL1RL2|cg22797169. The methylation sites of all five genes showed hypomethylation in OC, and there were statistically significant differences among RORC|cg25112191, S100A13|cg14467840, and TNF|cg04425624 (p < 0.05). This prognostic model based on low-level methylation and high-level methylation groups was significantly linked to the immune microenvironment as well as overall survival in OC.

Conclusions

This study provided different methylation subtypes for OC patients according to the methylation sites of IRGs. In addition, it helps establish a relationship between methylation and the immune microenvironment, which showed specific differences in biological signaling pathways, genomic changes, and immune mechanisms within the two subgroups. These data provide ones to deeply understand the mechanism of immune-related methylation genes on the occurrence and development of OC. The methylation-site signature is also to establish new possibilities for OC therapy. These data are a precious resource for stratification and targeted treatment of OC patients toward an advanced 3PM approach.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00359-3.

Hepatocellular Carcinoma: Old and Emerging Therapeutic Targets

Liver cancer, predominantly hepatocellular carcinoma (HCC), globally ranks sixth in incidence and third in cancer-related deaths. HCC risk factors include non-viral hepatitis, alcohol abuse, environmental exposures, and genetic factors. No specific genetic alterations are unequivocally linked to HCC tumorigenesis. Current standard therapies include surgical options, systemic chemotherapy, and kinase inhibitors, like sorafenib and regorafenib. Immunotherapy, targeting immune checkpoints, represents a promising avenue. FDA-approved checkpoint inhibitors, such as atezolizumab and pembrolizumab, show efficacy, and combination therapies enhance clinical responses. Despite this, the treatment of hepatocellular carcinoma (HCC) remains a challenge, as the complex tumor ecosystem and the immunosuppressive microenvironment associated with it hamper the efficacy of the available therapeutic approaches. This review explores current and advanced approaches to treat HCC, considering both known and new potential targets, especially derived from proteomic analysis, which is today considered as the most promising approach. Exploring novel strategies, this review discusses antibody drug conjugates (ADCs), chimeric antigen receptor T-cell therapy (CAR-T), and engineered antibodies. It then reports a systematic analysis of the main ligand/receptor pairs and molecular pathways reported to be overexpressed in tumor cells, highlighting their potential and limitations. Finally, it discusses TGFβ, one of the most promising targets of the HCC microenvironment.

A pyroptosis-related gene expression signature predicts immune microenvironment and prognosis in head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous and aggressive malignancy with a poor prognosis. Pyroptosis triggered by gasdermins family proteins is reported vital for tumor microenvironment and cancer progression. However, pyroptosis-related gene expression and its relationship with immune infiltration and prognosis of HNSCC have not been fully defined.

MATERIAL AND METHODS

RNA-sequencing data of HNSCC patients were acquired from The Cancer Genome Atlas (TCGA) database. A pyroptosis-related gene expression signature and infiltrated immune cells were analyzed. Univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression and nomogram analyses were used to construct a clinical-molecular risk model for survival prognosis.

RESULTS

HNSCC was classified into three different molecular subtypes based on the expression information of pyroptosis-related genes. Immune cell infiltration was demonstrated to be distinct between the three subtypes. The segregation of patients into the high-risk group and low-risk group, were carried out using the signature of differential expression genes (DEGs) signature among the three molecular subtypes. The precision of this signature was corroborated by Receiver operating characteristic curve (ROC) analysis with the 3-year area under time-dependent ROC curve (AUC) reaching 0.711. The risk model was validated in another dataset from the Gene Expression Omnibus (GEO) database. Subsequently we established a clinical-molecular nomogram which combined the risk score with age and stage. The calibration plots for predicting the overall survival rate of 1-, 3-, and 5-years indicated that the nomogram performs well.

CONCLUSION

The expression signature that encompasses pyroptosis-related genes could be used as molecular classification for HNSCC and pyroptosis might be a promising therapeutic target in HNSCC.

Toll-like receptor-guided therapeutic intervention of human cancers: molecular and immunological perspectives

Toll-like receptors (TLRs) serve as the body's first line of defense, recognizing both pathogen-expressed molecules and host-derived molecules released from damaged or dying cells. The wide distribution of different cell types, ranging from epithelial to immune cells, highlights the crucial roles of TLRs in linking innate and adaptive immunity. Upon stimulation, TLRs binding mediates the expression of several adapter proteins and downstream kinases, that lead to the induction of several other signaling molecules such as key pro-inflammatory mediators. Indeed, extraordinary progress in immunobiological research has suggested that TLRs could represent promising targets for the therapeutic intervention of inflammation-associated diseases, autoimmune diseases, microbial infections as well as human cancers. So far, for the prevention and possible treatment of inflammatory diseases, various TLR antagonists/inhibitors have shown to be efficacious at several stages from pre-clinical evaluation to clinical trials. Therefore, the fascinating role of TLRs in modulating the human immune responses at innate as well as adaptive levels directed the scientists to opt for these immune sensor proteins as suitable targets for developing chemotherapeutics and immunotherapeutics against cancer. Hitherto, several TLR-targeting small molecules (e.g., Pam3CSK4, Poly (I:C), Poly (A:U)), chemical compounds, phytocompounds (e.g., Curcumin), peptides, and antibodies have been found to confer protection against several types of cancers. However, administration of inappropriate doses of such TLR-modulating therapeutics or a wrong infusion administration is reported to induce detrimental outcomes. This review summarizes the current findings on the molecular and structural biology of TLRs and gives an overview of the potency and promises of TLR-directed therapeutic strategies against cancers by discussing the findings from established and pipeline discoveries.

Identification of TLRs as potential prognostic biomarkers for lung adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the most common tumors with the highest cancer-related death rate worldwide. Early diagnosis of LUAD can improve survival. Abnormal expression of the Toll-like receptors (TLRs) is related to tumorigenesis and development, inflammation and immune infiltration. However, the role of TLRs as an immunotherapy target and prognostic marker in lung adenocarcinoma is not well understood and needs to be analyzed. Relevant data obtained from databases such as ONCOMINE, UALCAN, GEPIA, and the Kaplan-Meier plotter, GSCALite, GeneMANIA, DAVID 6.8, Metascape, LinkedOmics and TIMER, to compare transcriptional TLRs and survival data of patients with LUAD. The expression levels of TLR1/2/3/4/5/7/8 in LUAD tissues were significantly reduced while the expression levels of TLR6/9/10 were significantly elevated. LUAD patients having low expression of TLR1/2/3/5/8 and high expression of TLR9 had a poor overall survival while patients with low expression of TLR2/3/7 presented with worse first progress. TLR4, TLR7 and TLR8 are the 3 most frequently mutated genes in the TLR family. Correlation suggested a low to moderate correlation among TLR family. TLR family was also involved in the activation or inhibition of the famous cancer related pathways. Analysis of immune infiltrates analysis suggested that TLR1/2/7/8 levels significantly correlated with immune infiltration level. Enrichment analysis revealed that TLRs were involved in TLR signaling pathway, immune response, inflammatory response, primary immunodeficiency, regulation of IL-8 production and PI3K-Akt signaling pathway. Our results provided information on TLRs expression and potential regulatory networks in LUAD. Moreover, our results suggested TLR2/7/8 as a potential prognostic biomarker for lung adenocarcinoma.

Biomarkers for Hepatocellular Carcinoma: From Origin to Clinical Diagnosis

The incidence of hepatocellular carcinoma (HCC) and HCC-related deaths has increased over the last few decades. There are several risk factors of HCC such as viral hepatitis (B, C), cirrhosis, tobacco and alcohol use, aflatoxin-contaminated food, pesticides, diabetes, obesity, nonalcoholic fatty liver disease (NAFLD), and metabolic and genetic diseases. Diagnosis of HCC is based on different methods such as imaging ultrasonography (US), multiphasic enhanced computed tomography (CT), magnetic resonance imaging (MRI), and several diagnostic biomarkers. In this review, we examine the epidemiology of HCC worldwide and in Egypt as well as risk factors associated with the development of HCC and, finally, provide the updated diagnostic biomarkers for the diagnosis of HCC, particularly in the early stages of HCC. Several biomarkers are considered to diagnose HCC, including downregulated or upregulated protein markers secreted during HCC development, circulating nucleic acids or cells, metabolites, and the promising, recently identified biomarkers based on quantitative proteomics through the isobaric tags for relative and absolute quantitation (iTRAQ). In addition, a diagnostic model used to improve the sensitivity of combined biomarkers for the diagnosis of early HCC is discussed.

Toll-Like Receptors and the Response to Radiotherapy in Solid Tumors: Challenges and Opportunities

Toll-like receptors (TLRs) are indispensable for the activation, maintenance and halting of immune responses. TLRs can mediate inflammation by recognizing molecular patterns in microbes (pathogen-associated molecular patterns: PAMPs) and endogenous ligands (danger-associated molecular patterns: DAMPs) released by injured or dead cells. For this reason, TLR ligands have attracted much attention in recent years in many cancer vaccines, alone or in combination with immunotherapy, chemotherapy and radiotherapy (RT). TLRs have been shown to play controversial roles in cancer, depending on various factors that can mediate tumor progression or apoptosis. Several TLR agonists have reached clinical trials and are being evaluated in combination with standard of care therapies, including RT. Despite their prolific and central role in mediating immune responses, the role of TLRs in cancer, particularly in response to radiation, remains poorly understood. Radiation is recognized as either a direct stimulant of TLR pathways, or indirectly through the damage it causes to target cells that subsequently activate TLRs. These effects can mediate pro-tumoral and anti-tumoral effects depending on various factors such as radiation dose and fractionation, as well as host genomic features. In this review, we examine how TLR signaling affects tumor response to RT, and we provide a framework for the design of TLR-based therapies with RT.