Differential Expression of the TLR4 Gene in Pan-Cancer and Its Related Mechanism

An Ultrasound Image-Based Deep Learning Radiomics Nomogram for Differentiating Between Benign and Malignant Indeterminate Cytology (Bethesda III) Thyroid Nodules: A Retrospective Study

RATIONALE AND OBJECTIVES

Our objective is to develop and validate a deep learning radiomics nomogram (DLRN) based on preoperative ultrasound images and clinical features, for predicting the malignancy of thyroid nodules with indeterminate cytology (Bethesda III).

MATERIALS AND METHODS

Between June 2017 and June 2022, we conducted a retrospective study on 194 patients with surgically confirmed indeterminate cytology (Bethesda III) in our hospital. The training and internal validation cohorts were comprised of 155 and 39 patients, in a 7:3 ratio. To facilitate external validation, we selected an additional 80 patients from each of the remaining two medical centers. Utilizing preoperative ultrasound data, we obtained imaging markers that encompass both deep learning and manually radiomic features. After feature selection, we developed a comprehensive diagnostic model to evaluate the predictive value for Bethesda III benign and malignant cases. The model's diagnostic accuracy, calibration, and clinical applicability were systematically assessed.

RESULTS

The results showed that the prediction model, which integrated 512 DTL features extracted from the pre-trained Resnet34 network, ultrasound radiomics, and clinical features, exhibited superior stability in distinguishing between benign and malignant indeterminate thyroid nodules (Bethesda Class III). In the validation set, the AUC was 0.92 (95% CI: 0.831-1.000), and the accuracy, sensitivity, specificity, precision, and recall were 0.897, 0.882, 0.909, 0.882, and 0.882, respectively.

CONCLUSION

The comprehensive multidimensional data model based on deep transfer learning, ultrasound radiomics features, and clinical characteristics can effectively distinguish the benign and malignant indeterminate thyroid nodules (Bethesda Class III), providing valuable guidance for treatment selection in patients with indeterminate thyroid nodules (Bethesda Class III).

Toll-like receptor 4 - a multifunctional virus recognition receptor

Since the initial description of Toll receptors in Drosophila and their mammalian counterparts Toll-like receptors (TLRs), numerous fundamental and applied studies have explored their crucial role as sensors of pathogen-associated molecular patterns (PAMPs). Among the ten human TLRs, TLR4 is particularly well known for its ability to detect lipopolysaccharides (LPS), a component of the Gram-negative bacterial cell wall. In addition to its archetypal functions, TLR4 is also a versatile virus sensor. This review provides a background on the discovery of TLR4 and how this knowledge laid a foundation for characterization of its diverse roles in antiviral responses, examined through genetic, biochemical, structural, and immunological approaches. These advances have led to a deeper understanding of the molecular functions that enable TLR4 to orchestrate multi-nodal control by professional antigen-presenting cells (APCs) to initiate appropriate and regulated antiviral immune responses.

A vision transformer-based deep transfer learning nomogram for predicting lymph node metastasis in lung adenocarcinoma

BACKGROUND

Lymph node metastasis (LNM) plays a crucial role in the management of lung cancer; however, the ability of chest computed tomography (CT) imaging to detect LNM status is limited.

PURPOSE

This study aimed to develop and validate a vision transformer-based deep transfer learning nomogram for predicting LNM in lung adenocarcinoma patients using preoperative unenhanced chest CT imaging.

METHODS

This study included 528 patients with lung adenocarcinoma who were randomly divided into training and validation cohorts at a 7:3 ratio. The pretrained vision transformer (ViT) was utilized to extract deep transfer learning (DTL) feature, and logistic regression was employed to construct a ViT-based DTL model. Subsequently, the model was compared with six classical convolutional neural network (CNN) models. Finally, the ViT-based DTL signature was combined with independent clinical predictors to construct a ViT-based deep transfer learning nomogram (DTLN).

RESULTS

The ViT-based DTL model showed good performance, with an area under the curve (AUC) of 0.821 (95% CI, 0.775-0.867) in the training cohort and 0.825 (95% CI, 0.758-0.891) in the validation cohort. The ViT-based DTL model demonstrated comparable performance to classical CNN models in predicting LNM, and the ViT-based DTL signature was then used to construct ViT-based DTLN with independent clinical predictors such as tumor maximum diameter, location, and density. The DTLN achieved the best predictive performance, with AUCs of 0.865 (95% CI, 0.827-0.903) and 0.894 (95% CI, 0845-0942), respectively, surpassing both the clinical factor model and the ViT-based DTL model (p < 0.001).

CONCLUSION

This study developed a new DTL model based on ViT to predict LNM status in lung adenocarcinoma patients and revealed that the performance of the ViT-based DTL model was comparable to that of classical CNN models, confirming that ViT was viable for deep learning tasks involving medical images. The ViT-based DTLN performed exceptionally well and can assist clinicians and radiologists in making accurate judgments and formulating appropriate treatment plans.

Identification of common core genes and pathways in childhood sepsis and cancer by bioinformatics analysis

INTRODUCTION

Sepsis and cancer are both leading causes of death worldwide, and they share several pathophysiological characteristics. Some studies have suggested a possible association between sepsis and cancer; however, few have investigated the core genes involved in both diseases.

METHODS

Core genes common to both sepsis and cancer were identified using pediatric sepsis datasets (GEO: GSE26378, GSE4607, GSE8121 and GSE13904) and cancer databases (TCGA: BRCA, COADREAD, ESCA, KIRC, LIHC, LUAD, STAD). Gene Ontology (GO) and Reactome enrichment analyses, along with a protein-protein interaction (PPI) network analysis, were performed. Pharmacophore screening was applied to predict the targets of oxymatrine and ulinastatin, and potential target genes shared by both cancer and sepsis were identified. Survival analysis was performed. The association between the target genes and tumor size and number of positive lymph nodes was investigated by Pearson correlation analysis. The association between the target genes and tumor stage was investigated by Fisher's exact test. Molecular docking analysis was performed to evaluate the affinity of the candidate drugs for their targets.

RESULTS

A total of 641 common genes were identified. GO enrichment analysis showed that common genes were enriched in neutrophil degranulation, inflammatory response and innate immune response. Reactome enrichment analysis showed that common genes were enriched in neutrophil degranulation, interleukin-4 and interleukin-13 signaling, transcriptional regulation of granulopoiesis and interleukin-10 signaling. The PPI network showed that the top 10 core genes were TLR4, IL1B, IL10, ITGAM, TLR2, PTPRC, CDK1, FOS, MMP9 and ITGB2. The survival analysis showed that the high expression of BCAT1, CSAD, G6PD, GM2A, MMP9, PYGL and TOP2A was associated with poorer prognosis in several cancers. Molecular docking showed that oxymatrine and ulinastatin can bind to protein targets with highly stable binding.

CONCLUSIONS

We identified genes with common effects on both childhood sepsis and cancer, which provides new insights into the association between sepsis and cancer. In addition, two drugs with potential clinical application value were identified. Further studies are required to validate the role of these common core genes in sepsis and cancer and to evaluate the potential utility of these drugs.

Disrupting CENP-N mediated SEPT9 methylation as a strategy to inhibit aerobic glycolysis and liver metastasis in colorectal cancer

Colorectal cancer (CRC) is a prevalent malignancy with a high mortality rate, primarily due to liver metastasis. This study explores the role of centromere protein N (CENP-N) in mediating the methylation of septin 9 (SEPT9) and its subsequent effects on aerobic glycolysis and liver metastasis in CRC. We employed in vitro and in vivo experiments, including single-cell RNA sequencing, methylation-specific PCR (MSP), ChIP assays, and various functional assays to assess the impact of CENP-N and SEPT9 on CRC cell proliferation, migration, invasion, and metabolic reprogramming. Our data reveal that CENP-N directly interacts with SEPT9, enhancing its methylation at specific lysine residues. This modification significantly upregulates key glycolytic enzymes, thereby promoting aerobic glycolysis, CRC cell proliferation, and migration. In vivo studies further demonstrate that the CENP-N/SEPT9 axis facilitates liver metastasis of CRC, as confirmed by fluorescence imaging and histological analysis. This study identifies a novel pathway where CENP-N-mediated methylation of SEPT9 drives metabolic reprogramming and metastasis in CRC. These findings suggest potential therapeutic targets for inhibiting CRC progression and liver metastasis, offering new insights into CRC pathogenesis.

Cytotoxic Effect of Trypanosoma cruzi Calcineurin B Against Melanoma and Adenocarcinoma Cells In Vitro

Chagas disease caused by the obligate intracellular flagellate protozoan Trypanozoma cruzi infects about 6 million people. From the 1930s to the present, the antitumor capacity of T. cruzi has been studied; however, the identification of the responsible molecules for this effect remains undiscovered. Calcineurin, a calcium/calmodulin-dependent serine/threonine phosphatase, is a heterodimer consisting of a catalytic subunit (CaNA) and a regulatory subunit (CaNB). It has been described that T. cruzi CaN is involved in the cell invasion and proliferation of the parasite. Recently, extracellular human CaNB has been demonstrated to be capable of inhibiting tumor growth cells, conferring an antitumor effect; however, the extracellular role of T. cruzi CaNB (TcCaNB) is still unknown. The objective of this work was to investigate the antitumor potential of TcCaNB by interacting with membrane proteins and evaluating its effects on the viability, proliferation, and morphology of tumor cells in vitro. Additionally, the possible mechanism of action of TcCaNB was explored. Murine melanoma (B16-F10), human cervical adenocarcinoma (HeLa), and African green monkey kidney epithelial (Vero) cell lines were employed for in vitro assays. Far Western blot and immunofluorescence were performed to assess the interaction of TcCaNB with membrane proteins, and the effect of TcCaNB on cell viability and proliferation was evaluated using the MTS assay and the CyQUANT NF assay, respectively. The effect of the caspase inhibitor Z-VAD-FMK on TcCaNB-stimulated tumor cells was investigated to determine if TcCaNB-induced cell death was associated with apoptosis. To assess cell cycle progression, TcCaNB-treated cells were analyzed by flow cytometry. In this study, the results showed an interaction of TcCaNB with cell membrane proteins in B16-F10 and HeLa tumor lines, indicating that TcCaNB is capable of decreasing viability and proliferation of B16-F10 and HeLa cells, with no significant effect observed in Vero cells. Furthermore, morphological changes were observed in tumor cells treated with TcCaNB. DNA fragmentations and inhibition of caspases with Z-VAD-FMK partially counteracted the cytotoxic effects of TcCaNB on tumor cells, suggesting that TcCaNB-induced cell death might be associated with apoptosis. Additionally, TcCaNB caused S phase cell cycle arrest in HeLa cells, with an increase in the sub-G1 population indicative of apoptosis, while no significant effects were observed in Vero cells.

Comprehensive pan-cancer analysis of FUTs family as prognostic and immunity markers based on multi-omics data

BACKGROUND

The dysregulation of fucosyltransferases (FUTs) contributes to alterations in fucosylated epitope expression, which serve as distinctive features of cancer cells. Nonetheless, a comprehensive elucidation of the prognostic biological marker and therapeutic target of the FUTs family in pan-cancer remains elusive.

METHODS

Over 10,000 individuals' profiling information was examined, including information on 750 small molecule drugs, 33 types of cancer, and 24 types of immune cells. We focused on POFUT2's function and applied GSVA (Gene Set Variation Analysis) to calculate the FUT score. Survival and cancer pathways were found to be correlated with this score. After deriving a signature via univariate Cox and LASSO regression, we generated and analyzed the ROC curve and developed a nomogram.

RESULTS

Our comprehensive analysis revealed epigenetic, genomic, and immunogenomic changes in FUTs, particularly POFUT2, resulting in aberrant expression. Elevated frequencies of CNV (Copy number variation), SNV (Single Nucleotide Variant), and hypermethylation were observed in FUTs. Additionally, the survival of patients with various types of cancers may be predicted by FUT expression. Immune response and prognosis in numerous types of cancer were found to be strongly linked to aberrant POFUT2 expression. Pathway analysis unveiled the role of FUTs in apoptosis, epithelial-to-mesenchymal transition (EMT), cell cycle, DNA damage response, RAS/MAPK, TSC/mTOR, PI3K/AKT, AR, ER, and RTK. A prognostic index for patients diagnosed with adrenocortical carcinoma (ACC) was established by applying a risk model incorporating nine FUTs and based on the findings of the GSVA.

CONCLUSIONS

FUTs, particularly POFUT2, emerge as candidate targets for improving the outcomes of immune therapy. The significance of aberrant MUC12 expression, cancer immune therapy, and patient survival in the context of diverse malignancies is enhanced by the strong correlation observed among these factors. Our five-gene risk signature provides patients with ACC with an independent prognostic indicator, emphasizing the critical function of these genes in inhibiting the immune system's response in ACC.

Insights into the prognostic value and immunological role of CD74 in pan-cancer

BACKGROUND

CD74 is a non-polymorphic type II transmembrane glycoprotein. It is involved in the regulation of T and B cell development, and dendritic cell (DC) motility. Numerous studies have found that CD74 exerts an essential role in tumor immunity, but the expression profile of CD74 is still not systematically reported, and its value in human pan-cancer analysis is unknown. In this study, we analyzed the expression pattern of CD74 in 33 cancers, and evaluated the significance of CD74 in prognosis prediction and cancer immunity.

METHODS

Pan-cancer dataset from UCSC Xena.We used the Sangerbox website combined with R software' Timer, CIBERSORT method and IOBR package to analyze and plot the data. Survival was assessed using the Kaplan-Meier method and log-rank test for 33 cancer types (p < 0.05). In addition, to explore the relationship between CD74 expression and immune checkpoints, immune cell infiltration, tumor mutational burden (TMB) and microsatellite instability (MSI), Spearman correlation analysis was performed.

RESULTS

This study comprehensively analyzed CD74 expression in 33 different tumor types, revealing that CD74 play an crucial role in cancer formation and development.

CONCLUSIONS

CD74 gene expression in different cancers is associated with immune cell infiltration and immunomodulators and may provide a promising target for survival and immunotherapy. Our study shows that CD74 has an essential role as a biomarker of prognosis during tumor development, which highlights the possibility of new targeted therapies.

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.

A network pharmacology method explores the molecular mechanism of Coptis chinensis for the treatment of Alzheimer's disease

To predict the molecular mechanisms of action of Coptis chinensis in the treatment of Alzheimer's disease using network pharmacology. The active ingredients and targets of Coptis chinensis were obtained from the Traditional Chinese Medicine System Pharmacology Database. Target information for Alzheimer's disease was screened using the GeneCard and OMIM databases. The Venn diagram tool was used to identify the intersecting targets of Coptis chinensis and Alzheimer's disease. The obtained target information was entered into the STRING database to construct a protein-protein interaction network. The R language was used to perform Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses of significant targets. Auto Dock Vina software was used for molecular docking. Fourteen effective active ingredients and 158 key targets associated with Coptis chinensis were identified. There were 1113 targets related to Alzheimer's disease genes. A drug-component-disease-target network was constructed and 84 key targets were identified for the treatment of Alzheimer's disease by Coptis chinensis. The main signaling pathways were the PI3K-Akt, AGE-RAGE, MAPK, HIF-1, TNF, and relaxin signaling pathways. The molecular docking results showed that berberine has a high affinity for Alzheimer's Disease. Coptis chinensis could play a multi-target and multi-pathway role against Alzheimer's disease, which has guiding significance for clinical research.

Profiling targets and potential target pairs of CAR-T cell therapy in clinical trials

Since the approval of the first chimeric antigen receptor (CAR)-T product in 2017, the number of new CAR-T clinical trials worldwide exceeds 100 per year. 1649 clinical studies have been conducted to explore possible future clinical applications of targets or target pairs through different biotechnologies. In this study, we aim to take a data-driven analytical approach to explore potential dual-target pairs based on clinical trial information. We screened 1283 non-withdrawal interventional CAR-T clinical trials spanning 96 different targets and 74 target pairs from clinicaltrials.gov. Through the Circos plot and temporal network plots, the information between targets and indications was visualized. Based on the assumption that two targets of a target pair must target the same indication, five new target pairs were inferred, including CD19/CD7, CD19/CD5, CD19/CD37, and CD19/BAFFR and validated by expression pattern, literature and patent information. This study provides novel support for target profiling of CAR-T from the perspective of clinical trials and also provides a reference for researchers and developers to select new targets or target pairs of CAR-T cell therapy.

Identification of a bile acid and bile salt metabolism-related lncRNA signature for predicting prognosis and treatment response in hepatocellular carcinoma

Bile acids and salts have been shown to play a role in liver carcinogenesis through DNA damage, inflammation, and tumor proliferation. However, the correlation between bile acid metabolism and hepatocellular carcinoma (HCC) prognosis remains unclear. This study aimed to identify a predictive signature of bile acid and bile salt metabolism-related long non-coding RNAs (lncRNAs) for HCC prognosis and treatment response. The study used HCC RNA-sequencing data and corresponding clinical and prognostic data from The Cancer Genome Atlas. A prognostic model consisting of five bile acid and bile salt metabolism-related lncRNAs was developed and evaluated in a training set, a validation set and an external set. The model demonstrated good performance in predicting HCC prognosis and was shown to be an independent biomarker for prognosis. Additionally, our study revealed a significant association between the signature and immune cell infiltration, as well as its predictive value for therapeutic responses to both immunotherapy and chemotherapy. Furthermore, three LncRNAs (LUCAT1, AL031985.3 and AC015908.3) expression levels in our signature were validated through qRT-PCR in a cohort of 50 pairs of HCC patient tumor samples and corresponding adjacent non-tumor samples, along with 10 samples of normal liver tissue adjacent to benign lesions. These findings suggest that this novel bile acid and bile salt metabolism-related lncRNA signature can independently predict the prognosis of patients with HCC and may be utilized as a potential predictor of response to treatment in this setting.

DNMT1-mediated DNA methylation in toll-like receptor 4 (TLR4) inactivates NF-κB signal pathway-triggered pyroptotic cell death and cellular inflammation to ameliorate lipopolysaccharides (LPS)-induced osteomyelitis

Toll-like receptor 4 (TLR4) plays a critical role in various human diseases, and was associated with pyroptotic cell death and inflammatory responses. DNA methylation, which has stable and reversible properties, has been reported to alter the expression of target genes, including TLR4. However, the role of methylated TLR4 in osteomyelitis (OM) and the underlying molecular mechanisms remain unclear. RNA sequencing was used to identify differentially expressed genes and associated signaling pathways. RT-qPCR, Western blot, emzyme-linked immunosorbent assay (ELISA), cell counting kit-8 (CCK-8) and LDH assay kit were used to detect mRNA and protein expression of relevant genes, cell viability and the LDH activity, respectively. TLR4 methylation was detected by methylation-specific PCR (MSP) and verified by Chromatin immunoprecipitation (ChIP). Here, we found that DNA methyltransferase-1 (DNMT1)-mediated TLR4 demethylation significantly suppressed lipopolysaccharides (LPS)-induced pyroptosis and inflammatory response by inhibiting the TLR4/nuclear transcription factor-kappa B (NF-κB) axis. First, we confirmed TLR4 as the study target by mRNA transcriptome sequencing analysis, and TLR4 was observably high-expressed in both OM patients and LPS-treated osteoblastic MC3T3-E1. Then, we found that downregulation of DNMT1 blocked TLR4 promoter methylation modification, resulting in upregulation of TLR4. Simultaneously, functional experiments indicated that suppression of TLR4 or overexpression of DNMT1 promoted cell proliferation and inhibited cell pyroptosis and inflammation in LPS-induced MC3T3-E1, while upregulation of TLR4 restored the effects of DNMT1 silencing on OM progression. In addition, TLR4 elevated phosphorylation of IκB-α and NF-κB p65 in the NF-κB signal pathway, and inhibition of TLR4 or the NF-κB inhibitor PDTC reversed the influence of inhibition of DNMT1. In conclusion, our study demonstrated that DNMT1-mediated TLR4 DNA methylation alleviated LPS-induced OM by inhibiting the NF-κB signaling pathway.

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.

Immunomodulatory Gene-Splicing Dysregulation in Tumorigenesis: Unmasking the Complexity

Cancer is a global health concern with rising incidence, morbidity, and mortality. The interaction between the tumor and immune cells within the tumor microenvironment is facilitated by signaling pathways driven by immunomodulatory proteins. Alternative splicing regulates the production of multiple immunomodulatory proteins with diverse functionality from a single mRNA transcript. Splicing factors are pivotal in modulating alternative splicing processes but are also subject to regulation. The dysregulation of alternative splicing may result from splicing factor (SF) abnormal expression levels and mutations in the cis and trans-acting elements and small nuclear RNA (snRNA) molecules. Aberrant splicing may generate abnormal mRNA transcripts encoding isoforms with altered functions that contribute to tumorigenesis or cancer progression. This review uncovers the complexity of immunomodulatory genes splicing dysregulation in oncogenesis. Identifying specific immunomodulatory splicing isoforms that contribute to cancer could be utilized to improve current immunotherapeutic drugs or develop novel therapeutic interventions for cancer.

ANXA2 is a potential biomarker for cancer prognosis and immune infiltration: A systematic pan-cancer analysis

Background: Annexin A2 (ANXA2) belongs to the Annexin A family and plays a role in epithelial-mesenchymal transition, fibrinolysis, and other physiological processes. Annexin A2 has been extensively implicated in tumorigenesis and development in previous studies, but its precise role in pan-cancer remains largely unknown. Methods: We adopted bioinformatics methods to explore the oncogenic role of Annexin A2 using different databases, including the Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) biobank, the Human Protein Atlas (HPA), the Gene Expression Profiling Interaction Analysis (GEPIA) and cBioPortal. We analyzed the differential expression of Annexin A2 in different tumors and its relationship with cancer prognosis, immune cell infiltration, DNA methylation, tumor mutation burden (TMB), microsatellite instability (MSI) and mismatch repair (MMR). Furtherly, we conducted a Gene Set Enrichment Analysis (GSEA) to identify the Annexin A2-related pathways. Results: Annexin A2 expression was upregulated in most cancers, except in kidney chromophobe (KICH) and prostate adenocarcinoma (PRAD). Annexin A2 showed a good diagnostic efficacy in twelve types of cancer. The high expression of Annexin A2 was significantly associated with a reduced overall survival, disease-specific survival and progression-free interval in seven cancers. The Annexin A2 expression was variably associated with infiltration of 24 types of immune cells in 32 tumor microenvironments. In addition, Annexin A2 expression was differently associated with 47 immune checkpoints, immunoregulators, DNA methylation, tumor mutation burden, microsatellite instability and mismatch repair in pan-cancer. Gene Set Enrichment Analysis revealed that Annexin A2 was significantly correlated with immune-related pathways in fifteen cancers. Conclusion: Annexin A2 widely correlates with immune infiltration and may function as a promising prognostic biomarker in many tumors, showing its potential as a target for immunotherapy in pan-cancer.

Pattern-recognition receptors in endometriosis: A narrative review

Endometriosis is closely associated with ectopic focal inflammation and immunosuppressive microenvironment. Multiple types of pattern recognition receptors (PRRs) are present in the innate immune system, which are able to detect pathogen-associated molecular patterns (PAMPs) and danger-associated molecular patterns (DAMPs) in both intracellular and external environments. However, the exact role of PRRs in endometriosis and the underlying molecular mechanism are unclear. PRRs are necessary for the innate immune system to identify and destroy invasive foreign infectious agents. Mammals mainly have two types of microbial recognition systems. The first one consists of the membrane-bound receptors, such as toll-like receptors (TLRs), which recognize extracellular microorganisms and activate intracellular signals to stimulate immune responses. The second one consists of the intracellular PRRs, including nod-like receptors (NLRs) and antiviral proteins retinoic acid-inducible gene I (RIG-I) and melanoma differentiation-associated gene 5 (MDA-5) with helix enzyme domain. In this review, we mainly focus on the key role of PRRs in the pathological processes associated with endometriosis. PRRs recognize PAMPs and can distinguish pathogenic microorganisms from self, triggering receptor ligand reaction followed by the stimulation of host immune response. Activated immune response promotes the transmission of microbial infection signals to the cells. As endometriosis is characterized by dysregulated inflammation and immune response, PRRs may potentially be involved in the activation of endometriosis-associated inflammation and immune disorders. Toll-like receptor 2 (TLR2), toll-like receptor 3 (TLR3), toll-like receptor 4 (TLR4), nod-like receptor family caspase activation and recruitment domain (CARD) domain containing 5 (NLRC5), nod-like receptor family pyrin domain containing 3 (NLRP3), and c-type lectin receptors (CLRs) play essential roles in endometriosis development by regulating immune and inflammatory responses. Absent in melanoma 2 (AIM2)-like receptors (ALRs) and retinoic acid-inducible gene I-like receptors (RLRs) may be involved in the activation of endometriosis-associated immune and inflammation disorders. PRRs, especially TLRs, may serve as potential therapeutic targets for alleviating pain in endometriosis patients. PRRs and their ligands interact with the innate immune system to enhance inflammation in the stromal cells during endometriosis. Thus, targeting PRRs and their new synthetic ligands may provide new therapeutic options for treating endometriosis.

Effects of Methadone on the Toll-like Receptor 4 Expression in Human Non-Small Cell Lung Carcinoma A549 Cell Line Using In-silico and In vitro Techniques

Background

In this study, the effects of methadone and naloxone on the expression of toll-like receptor 4 (TLR4) gene have been evaluated in human non-small cell lung carcinoma A549 cell line migration using in-silico and in vitro techniques.

Materials and Methods

Lung cancer A549 cell cultures were stimulated for 24 h with methadone (5, 10, and 20 μM) and naloxone (20 and 40 μM) concentrations. The level of TLR4 expression was determined by the quantitative real-time polymerase chain reaction. Migration of the A549 cells was investigated after a 4-h incubation period with methadone using the Boyden Chamber assay.

Results

Migration rate of the A549 cells treated with 5 (P < 0.05) and 20 (P < 0.01) μM methadone was, respectively, increased and decreased with 20 μM naloxone (P < 0.05). Furthermore, the TLR4 expression was enhanced with 5 (P < 0.05) and 20 (P < 0.01) μM methadone and decreased with 20 (P < 0.05) and 40 μM naloxone (P < 0.01). In addition, in silico docking analysis revealed docking of methadone to MD-2 and TLR4.

Conclusion

According to the present DATA, methadone affects the TLR4 expression. It may however cause adverse consequences by increasing the TLR4 expression. Therefore, the useful analgesic properties of methadone should be separated from the unwanted TLR4-mediated side effects.

DHRS7 is an immune-related prognostic biomarker of KIRC and pan-cancer

Renal clear cell carcinoma (KIRC) is one malignancy whose development and prognosis have been associated with aberrant DHRS7 expression. However, the catalytic activity and pathophysiology of KIRC are poorly understood, and no sensitive tumor biomarkers have yet been discovered. In our study, we examined the significant influence of DHRS7 on the tumor microenvironment (TME) and tumor progression using an overall predictable and prognostic evaluation approach. We found novel cancer staging, particularly in KIRC, as well as potential therapeutic drugs out of 27 drug sensitivity tests. Using Perl scripts, it was possible to determine the number of somatic mutations present in 33 tumors, as well as the relative scores of 22 immune cells using CIBERSORT, the relationship between immune infiltration and differential expression using TCGA data, and the immune microenvironment score using the estimate technique. Our results show that DHRS7 is abnormally expressed in pan-cancer patients, which influences their survival. Low DHRS7 expression was associated with late clinical stages and a low survival rate in KIRC patients, suggesting a poor prognosis and course of treatment, in HNSG, MESO, and KIRC patients. We also found that DHRS7 was associated with TMB and MSI in certain tumors. Using KIRC as an example, we discovered a negative correlation between DHRS7 expression and immunological assessments, suggesting that this substance might be used as a tumor biomarker.

Development and validation of a predictive model combining clinical, radiomics, and deep transfer learning features for lymph node metastasis in early gastric cancer

Background

This study aims to develop and validate a predictive model combining deep transfer learning, radiomics, and clinical features for lymph node metastasis (LNM) in early gastric cancer (EGC).

Materials and methods

This study retrospectively collected 555 patients with EGC, and randomly divided them into two cohorts with a ratio of 7:3 (training cohort, n = 388; internal validation cohort, n = 167). A total of 79 patients with EGC collected from the Second Affiliated Hospital of Soochow University were used as external validation cohort. Pre-trained deep learning networks were used to extract deep transfer learning (DTL) features, and radiomics features were extracted based on hand-crafted features. We employed the Spearman rank correlation test and least absolute shrinkage and selection operator regression for feature selection from the combined features of clinical, radiomics, and DTL features, and then, machine learning classification models including support vector machine, K-nearest neighbor, random decision forests (RF), and XGBoost were trained, and their performance by determining the area under the curve (AUC) were compared.

Results

We constructed eight pre-trained transfer learning networks and extracted DTL features, respectively. The results showed that 1,048 DTL features extracted based on the pre-trained Resnet152 network combined in the predictive model had the best performance in discriminating the LNM status of EGC, with an AUC of 0.901 (95% CI: 0.847-0.956) and 0.915 (95% CI: 0.850-0.981) in the internal validation and external validation cohorts, respectively.

Conclusion

We first utilized comprehensive multidimensional data based on deep transfer learning, radiomics, and clinical features with a good predictive ability for discriminating the LNM status in EGC, which could provide favorable information when choosing therapy options for individuals with EGC.

Polymorphisms in toll-like receptor 3 and 4 genes as prognostic and outcome biomarkers in melanoma patients

Melanoma is one of the most aggressive tumors, and in the setting of rising incidence and mortality, there is an urgent need to identify new prognostic markers. Toll-like receptors (TLRs), are aberrantly expressed in numerous cancers, including melanoma. TLR signaling provides a microenvironment that is involved in antitumor immune response, chronic inflammation, cancer cell proliferation and evasion of immune destruction. In the present study, we investigated whether single nucleotide polymorphisms (SNPs) in TLR3 and TLR4 genes are associated with clinicopathologic features, progression and survival of melanoma patients. The study was conducted on 120 melanoma patients. DNA extracted from peripheral blood was genotyped for TLR3 polymorphisms rs5743312 and rs3775291 (L412F) and TLR4 polymorphisms rs4986790 (D299G) and rs4986791 (T399I), by TaqMan Real-Time PCR Assays. Kaplan-Meier survival curves were compared by the log-rank test. TLR3 polymorphism L412F was associated with a higher mitotic index (P = 0.035). TLR4 D299G and T399I polymorphisms were associated with indicators of melanoma severity, nodal metastases (P = 0.005 and P = 0.007, respectively) and advanced stage III (P = 0.005 and P = 0.004, respectively). Cox regression analysis showed that the presence of tumor-infiltrating lymphocytes (TILs) predicted better overall survival (HR = 0.318; P = 0.004). TLR4 T399I polymorphism was significantly associated with worse survival, P = 0.025. The overall survival rates were significantly lower for patients carrying variant allele T of TLR4 T399I SNP (TC and TT genotypes combined) (P = 0.008, log-rank test), compared to wild-type genotype CC. Our findings indicate that TLR4 polymorphisms T399I (rs4986791) and D299G (rs4986790) could be potential prognostic and survival markers for melanoma patients.

TMED2/9/10 Serve as Biomarkers for Poor Prognosis in Head and Neck Squamous Carcinoma

Background: Head and neck squamous carcinoma (HNSC) is one of the most common malignant tumors with high incidence and poor prognosis. Transmembrane emp24 structural domain (TMED) proteins are involved in protein transport and vesicle budding processes, which have implicated various malignancies’ progression. However, the roles of TMEDs in HNSC, especially in terms of development and prognosis, have not been fully elucidated.

Methods: We applied TIMER 2.0, UALCAN, GEPIA 2, Kaplan-Meier plotter, GEO, The Human Protein Atlas (HPA), cBioPortal, Linkedomics, Metascape, GRNdb, STRING, and Cytoscape to investigate the roles of TMED family members in HNSC.

Results: Compared with normal tissues, the mRNA expression levels of TMED1/2/4/5/7/8/9/10 were significantly increased in the TCGA HNSC dataset. And we combined GEPIA 2 and Kaplan-Meier Plotter to select TMED2/9/10 with prognostic value. Then we detected the levels of mRNA in the GEO HNSC database and the protein expression in HPA. It was found that the mRNA and protein expression levels of TMED2/9/10 were increased in HNSC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that TMED2/9/10 and their co-expressed genes promoted the malignant behavior of tumors by participating in biological processes such as intracellular transferase complex, protein transport, focal adhesion, intracellular protein processing. Single-cell analysis and immune infiltration analysis suggested that immune responses of cancer-associated fibroblasts and endothelial cells might be associated with prognosis. Finally, the transcription factors-genes network and protein-protein functional interaction network pointed to genes such as X-box binding protein 1 (XBP1) and TMED7, which might cooperate with TMED2/9/10 to change the progression of HNSC.

Conclusions: Our study implied that TMED2/9/10 and related genes mightjointly affect the prognosis of HNSC, providing specific clues for further experimental research, personalized diagnosis strategies, and targeted clinical therapy for HNSC.

TRDMT1 exhibited protective effects against LPS-induced inflammation in rats through TLR4-NF-κB/MAPK-TNF-α pathway

Background

Inflammation is a complex physiological and pathological process. Although many types of inflammation are well characterized, their physiological functions are largely unknown. tRNA aspartic acid methyltransferase 1 (TRDMT1) has been implicated as a stress‐related protein, but its intrinsic biological role is unclear.

Methods

We constructed a Trdmt1 knockout rat and adopted the LPS‐induced sepsis model. Survival curve, histopathological examination, expression of inflammatory factors, and protein level of TLR4 pathway were analyzed.

Results

Trdmt1 deletion had no obvious impact on development and growth. Trdmt1 deletion slightly increased the mortality during aging. Our data showed that Trdmt1 strongly responded in LPS‐treated rats, and Trdmt1 knockout rats were vulnerable to LPS treatment with declined survival rate. We also observed more aggravated tissue damage and more cumulative functional cell degeneration in LPS‐treated knockout rats compared with control rats. Further studies showed upregulated TNF‐α level in liver, spleen, lung, and serum tissues, which may be explained by enhanced p65 and p38 phosphorylation.

Conclusions

Our data demonstrated that Trdmt1 plays a protective role in inflammation by regulating the TLR4‐NF‐κB/MAPK‐TNF‐α pathway. This work provides useful information to understand the TRDMT1 function in inflammation.

A Novel Pyroptotic and Inflammatory Gene Signature Predicts the Prognosis of Cutaneous Melanoma and the Effect of Anticancer Therapies

Purpose

The purpose of this study was to construct a gene signature comprising genes related to both inflammation and pyroptosis (GRIPs) to predict the prognosis of patients with cutaneous melanoma patients and the efficacy of immunotherapy, chemotherapy, and targeted therapy in these patients.

Methods

Gene expression profiles were collected from The Cancer Genome Atlas. Weighted gene co-expression network analysis was performed to identify GRIPs. Univariable Cox regression and Lasso regression further selected key prognostic genes. Multivariable Cox regression was used to construct a risk score, which stratified patients into high- and low-risk groups. Areas under the ROC curves (AUCs) were calculated, and Kaplan-Meier analyses were performed for the two groups, following validation in an external cohort from Gene Expression Omnibus (GEO). A nomogram including the GRIP signature and clinicopathological characteristics was developed for clinical use. Gene set enrichment analysis illustrated differentially enriched pathways. Differences in the tumor microenvironment (TME) between the two groups were assessed. The efficacies of immune checkpoint inhibitors (ICIs), chemotherapeutic agents, and targeted agents were predicted for both groups. Immunohistochemical analyses of the GRIPs between the normal and CM tissues were performed using the Human Protein Atlas data. The qRT-PCR experiments validated the expression of genes in CM cell lines, Hacat, and PIG1 cell lines.

Results

A total of 185 GRIPs were identified. A novel gene signature comprising eight GRIPs (TLR1, CCL8, EMP3, IFNGR2, CCL25, IL15, RTP4, and NLRP6) was constructed. The signature had AUCs of 0.714 and 0.659 for predicting 3-year overall survival (OS) in the TCGA entire and GEO validation cohorts, respectively. Kaplan-Meier analyses revealed that the high-risk group had a poorer prognosis. Multivariable Cox regression showed that the GRIP signature was an independent predictor of OS with higher accuracy than traditional clinicopathological features. The nomogram showed good accuracy and reliability in predicting 3-year OS (AUC = 0.810). GSEA and TME analyses showed that the high-risk group had lower levels of pyroptosis, inflammation, and immune response, such as lower levels of CD8+ T-cell infiltration, CD4+ memory-activated T-cell infiltration, and ICI. In addition, low-risk patients whose disease expressed PD-1 or CTLA-4 were likely to respond better to ICIs, and several chemotherapeutic and targeted agents. Immunohistochemical analysis confirmed the distinct expression of five out of the eight GRIPs between normal and CM tissues.

Conclusion

Our novel 8-GRIP signature can accurately predict the prognosis of patients with CM and the efficacies of multiple anticancer therapies. These GRIPs might be potential prognostic biomarkers and therapeutic targets for CM.

Prognostic and Immunological Roles of MMP-9 in Pan-Cancer

BACKGROUND

Matrix metalloproteinase-9 (MMP-9) can degrade the extracellular matrix and participate in tumor progression. The relationship between MMP-9 and immune cells has been reported in various malignant tumors. However, there is a lack of comprehensive pan-cancer studies on the relationship between MMP-9 and cancer prognosis and immune infiltration.

METHOD

We used data from TCGA and GTEx databases to comprehensively analyze the differential expression of MMP-9 in normal and cancerous tissues. Survival analysis was performed to understand the prognostic role of MMP-9 in different tumors. We then analyzed the expression of MMP-9 across different tumors and at different clinical stages. Based on the results, we assessed the correlation between MMP-9 expression and immune-associated genes and immunocytes. Finally, we calculated the tumor mutation burden (TMB) of 33 cancer types and analyzed the correlation between MMP-9 and TMB, DNA microsatellite instability, and DNA repair genes.

RESULTS

MMP-9 significantly affected the prognosis and metastasis of various cancers. It was associated based on overall survival, disease-specific survival in five tumors, progression-free interval in seven tumors, and clinical stage in eight tumors, as well as with prognosis and metastasis in adrenocortical carcinoma and kidney renal clear cell carcinoma. It was also coexpressed with immune-related genes and DNA repair genes. The expression of MMP-9 was positively correlated with the markers of T cells, tumor-associated macrophages, Th1 cells, and T cell exhaustion. Furthermore, MMP-9 expression was highly correlated with macrophage M0 in 28 tumors. In addition, its expression was associated with TMB in eight cancer types and DNA microsatellite instability in six cancer types.

CONCLUSION

MMP-9 is related to immune infiltration in pan-cancer and can be used as a biomarker related to cancer prognosis and metastasis. Our findings provide prognostic molecular markers and new ideas for immunotherapy.