CA9 transcriptional expression determines prognosis and tumour grade in tongue squamous cell carcinoma patients

The Importance of HHLA2 in Solid Tumors-A Review of the Literature

Cancer immunotherapy is a rapidly developing field of medicine that aims to use the host's immune mechanisms to inhibit and eliminate cancer cells. Antibodies targeting CTLA-4, PD-1, and its ligand PD-L1 are used in various cancer therapies. However, the most thoroughly researched pathway targeting PD-1/PD-L1 has many limitations, and multiple malignancies resist its effects. Human endogenous retrovirus-H Long repeat-associating 2 (HHLA2, known as B7H5/B7H7/B7y) is the youngest known molecule from the B7 family. HHLA2/TMIGD2/KIRD3DL3 is one of the critical pathways in modulating the immune response. Recent studies have demonstrated that HHLA2 has a double effect in modulating the immune system. The connection of HHLA2 with TMIGD2 induces T cell growth and cytokine production via an AKT-dependent signaling cascade. On the other hand, the binding of HHLA2 and KIR3DL3 leads to the inhibition of T cells and mediates tumor resistance against NK cells. This review aimed to summarize novel information about HHLA2, focusing on immunological mechanisms and clinical features of the HHLA2/KIR3DL3/TMIGD2 pathway in the context of potential strategies for malignancy treatment.

Construction and validation of a prognostic model for tongue cancer based on three genes signature

Tongue squamous cell carcinoma (TSCC) has a poor prognosis and destructive characteristics. Reliable biomarkers are urgently required to predict disease outcomes and to guide TSCC treatment. This study aimed to develop a multigene signature and prognostic nomogram that can accurately predict the prognosis of patients with TSCC. We screened differentially expressed genes associated with TSCC using The Cancer Genome Atlas dataset. Based on this, we developed a new multi-mRNA gene signature using univariate Cox regression, Least Absolute Shrinkage and Selection Operator regression, and multivariate Cox regression. We used the concordance index to evaluate the accuracy of this new multigene model. Moreover, we performed receiver operating characteristic and Kaplan-Meier survival analyses to assess the predictive ability of the new multigene model. In addition, we created a prognostic nomogram incorporating clinical and pathological characteristics, with the aim of enhancing the adaptability of this model in practical clinical settings. We successfully developed a new prognostic model based on the expression levels of these 3 mRNAs that can be used to predict the prognosis of patients with TSCC. This prediction model includes 3 genes: KRT33B, CDKN2A, and CA9. In the validation set, the concordance index of this model was 0.851, and the area under the curve was 0.778 and 0.821 in the training and validation sets, respectively. Kaplan-Meier survival analysis showed that regardless of whether it was in the training or validation set, the prognosis of high-risk patients was significantly worse than that of low-risk patients (P < .001). Multivariate Cox regression analysis revealed that this model was an independent prognostic factor for patients with TSCC (P < .001). Our study suggests that this 3-gene signature model has a high level of accuracy and predictive ability, is closely related to the overall survival rate of patients with TSCC, and can independently predict the prognosis of TSCC patients with high accuracy and predictive ability.

Para-toluenesulfonamide, a novel potent carbonic anhydrase inhibitor, improves hypoxia-induced metastatic breast cancer cell viability and prevents resistance to αPD-1 therapy in triple-negative breast cancer

Overexpression of the hypoxia-induced transmembrane enzyme carbonic anhydrase IX (CA9) has been associated with poor prognosis and chemoresistance in aggressive breast cancer. This study aimed to investigate the involvement of CA9 in the anti-tumor activity of para-toluenesulfonamide (PTS) and elucidate its mechanism of action against breast cancer both in vitro and in vivo. MCF-7 and MDA-MB-231 breast cancer cells were treated with PTS or subjected to hypoxic conditions using cobalt chloride (CoCl2), with acetazolamide serving as a positive control. Additionally, 4T1 breast cancer cell allograft mice were co-treated with PTS and α-programmed cell death 1 (αPD-1) monoclonal antibody for one month. The results demonstrated that PTS effectively reduced cell viability and reversed migration ability in MCF-7 and MDA-MB-231 cells under CoCl2-induced hypoxia. Furthermore, PTS upregulated the expression of apoptosis-related proteins and downregulated CA9, hypoxia-inducible factor-1α (HIF-1α), and vascular endothelial growth factor (VEGF) proteins, possibly through modulation of p38 MAPK and ERK1/2 phosphorylated proteins. In the animal model, PTS100 inhibited tumor growth and lung metastasis in mammary tumor allograft mice, exhibiting synergistic effects when combined with αPD-1 therapy. Collectively, our findings suggest that PTS inhibits breast cancer growth and metastasis through the p38 MAPK/ERK1/2 pathway. Moreover, PTS may have the potential to prevent the development of resistance to αPD-1 therapy in breast cancer.

Downregulation of HHLA2 inhibits ovarian cancer progression via the NF-κB signaling pathway and suppresses the expression of CA9

HHLA2 has been recently demonstrated to play multifaceted roles in several types of cancers. However, its underlying mechanism in the progression of human ovarian cancer (OC) remains largely unexplored. In the present study, we aimed to determine whether downregulation of HHLA2 inhibited malignant phenotypes of human OC cells and explore its specific mechanism. Our results revealed that downregulation of HHLA2 by transfection with a lentiviral vector significantly suppressed the viability, invasion, and migration of OC cells. Interaction study showed that downregulation of HHLA2 in OC cells reduced the expression of CA9 and increased the expressions of p-IKKβ and p-RelA. Conversely, the viability, invasion, and migration of HHLA2-depleted OC cells were increased when CA9 was upregulated. In vivo, we found that downregulation of HHLA2 significantly inhibited tumor growth, which was reversed by CA9 overexpression. In addition, downregulation of HHLA2 inhibited the OC progression via activating the NF-κB signaling pathway and decreasing the expression of CA9. Collectively, our data suggested a link between HHLA2 and NF-κB axis in the pathogenesis of OC, and these findings might provide valuable insights into the development of novel potential therapeutic targets for OC.

Adjuvant activity of tubeimosides by mediating the local immune microenvironment

Rhizoma Bolbostemmatis, the dry tuber of Bolbostemma paniculatum, has being used for the treatment of acute mastitis and tumors in traditional Chinese medicine. In this study, tubeimoside (TBM) I, II, and III from this drug were investigated for the adjuvant activities, structure-activity relationships (SAR), and mechanisms of action. Three TBMs significantly boosted the antigen-specific humoral and cellular immune responses and elicited both Th1/Th2 and Tc1/Tc2 responses towards ovalbumin (OVA) in mice. TBM I also remarkably facilitated mRNA and protein expression of various chemokines and cytokines in the local muscle tissues. Flow cytometry revealed that TBM I promoted the recruitment and antigen uptake of immune cells in the injected muscles, and augmented the migration and antigen transport of immune cells to the draining lymph nodes. Gene expression microarray analysis manifested that TBM I modulated immune, chemotaxis, and inflammation-related genes. The integrated analysis of network pharmacology, transcriptomics, and molecular docking predicted that TBM I exerted adjuvant activity by interaction with SYK and LYN. Further investigation verified that SYK-STAT3 signaling axis was involved in the TBM I-induced inflammatory response in the C2C12 cells. Our results for the first time demonstrated that TBMs might be promising vaccine adjuvant candidates and exert the adjuvant activity through mediating the local immune microenvironment. SAR information contributes to developing the semisynthetic saponin derivatives with adjuvant activities.

Comparisons of Forecasting for Survival Outcome for Head and Neck Squamous Cell Carcinoma by using Machine Learning Models based on Multi-omics

Background: Machine learning methods showed excellent predictive ability in a wide range of fields. For the survival of head and neck squamous cell carcinoma (HNSC), its multi-omics influence is crucial. This study attempts to establish a variety of machine learning multi-omics models to predict the survival of HNSC and find the most suitable machine learning prediction method. Methods: The HNSC clinical data and multi-omics data were downloaded from the TCGA database. The important variables were screened by the LASSO algorithm. We used a total of 12 supervised machine learning models to predict the outcome of HNSC survival and compared the results. In vitro qPCR was performed to verify core genes predicted by the random forest algorithm. Results: For omics of HNSC, the results of the twelve models showed that the performance of multi-omics was better than each single-omic alone. Results were presented, which showed that the Bayesian network(BN) model (area under the curve [AUC] 0.8250, F1 score=0.7917) and random forest(RF) model (area under the curve [AUC] 0.8002,F1 score=0.7839) played good prediction performance in HNSC multi-omics data. The results of in vitro qPCR were consistent with the RF algorithm. Conclusion: Machine learning methods could better forecast the survival outcome of HNSC. Meanwhile, this study found that the BN model and the RF model were the most superior. Moreover, the forecast result of multi-omics was better than single-omic alone in HNSC.

The Immunological Contribution of a Novel Metabolism-Related Signature to the Prognosis and Anti-Tumor Immunity in Cervical Cancer

Cervical cancer is the most frequently diagnosed malignancy in the female reproductive system. Conventional stratification of patients based on clinicopathological characters has gradually been outpaced by a molecular profiling strategy. Our study aimed to identify a reliable metabolism-related predictive signature for the prognosis and anti-tumor immunity in cervical cancer. In this study, we extracted five metabolism-related hub genes, including ALOX12B, CA9, FAR2, F5 and TDO2, for the establishment of the risk score model. The Kaplan-Meier curve suggested that patients with a high-risk score apparently had a worse prognosis in the cervical cancer training cohort (TCGA, n = 304, p < 0.0001), validation cohort (GSE44001, n = 300, p = 0.0059) and pan-cancer cohorts (including nine TCGA tumors). Using a gene set enrichment analysis (GSEA), we observed that the model was correlated with various immune-regulation-related pathways. Furthermore, pan-cancer cohorts and immunohistochemical analysis showed that the infiltration of tumor infiltrating lymphocytes (TILs) was lower in the high-score group. Additionally, the model could also predict the prognosis of patients with cervical cancer based on the expression of immune checkpoints (ICPs) in both the discovery and validation cohorts. Our study established and validated a metabolism-related prognostic model, which might improve the accuracy of predicting the clinical outcome of patients with cervical cancer and provide guidance for personalized treatment.

LncRNA GACAT1 induces tongue squamous cell carcinoma migration and proliferation via miR-149

Recent studies have observed that lncRNAs (long non‐coding RNAs) are involved in the progression of various tumours including tongue squamous cell carcinoma (TSCC). Recently, a new lnRNA, GACAT1, has been firstly identified in gastric cancer. However, its potential role in TSCC remains unknown. In this reference, we observed that GACAT1 was overexpressed in TSCC samples and cell lines. Of 25 TSCC specimens, GACAT1 expression was overexpressed in 18 patients (18/25, 72%) compared to non‐tumour specimens. Ectopic expression of GACAT1 induced cell growth and migration and promoted epithelial to mesenchymal transition in TSCC. In addition, ectopic expression of GACAT1 decreased miR‐149 expression in SCC1 cell. We observed that miR‐149 expression was down‐regulated in TSCC cell lines. Moreover, we observed that GACAT1 expression was negatively correlated with miR‐149 expression. GACAT1 overexpression induced TSCC cell growth and migration via regulating miR‐149 expression. These data provided that GACAT1 played an oncogenic role in the progression of TSCC partly through modulating miR‐149 expression.

Identification of MEDAG as a Hub Candidate Gene in the Onset and Progression of Type 2 Diabetes Mellitus by Comprehensive Bioinformatics Analysis

Objectives

We conducted the present study to identify novel hub candidate genes in the pathogenesis of type 2 diabetes mellitus (T2DM) and provide potential biomarkers or therapeutic targets for dealing with the disease.

Methods

We conducted weighted gene coexpression network analysis on a series of the expression profiles of the pancreas islet of T2DM patients obtained from the Gene Expression Omnibus database to construct a weighted coexpression network. After dividing genes into separated coexpression modules, we identified a T2DM-related module using Pearson's correlation analysis. Then, hub genes were identified from the T2DM-related module using the Maximal Clique Centrality method and validated by correlation analysis with clinical traits, differentially expressed gene analysis, validation in other datasets, and single-gene gene set enrichment analysis (GSEA).

Results

Genes were divided into 16 coexpression modules, and one module was identified as a T2DM-related module. Four hub candidate genes were identified, and MEDAG was a novel hub candidate gene. The expression level of MEDAG was positively correlated with hemoglobin A1c (HbA1c) and was evidently overexpressed in the pancreas islet tissue of T2DM patients compared with normal control. Analyses on two other datasets supported the results. GSEA verified that MEDAG plays essential roles in T2DM.

Conclusions

MEDAG is a novel hub candidate of T2DM, and its irregular expression in the pancreas islet plays vital roles in the pathogenesis of T2DM. MEDAG is a potential target of intervention in the future for the treatment of T2DM.

Identification of a Transcriptional Prognostic Signature From Five Metabolic Pathways in Oral Squamous Cell Carcinoma

Dysregulated metabolic pathways have been appreciated to be intimately associated with tumorigenesis and patient prognosis. Here, we sought to develop a novel prognostic signature based on metabolic pathways in patients with primary oral squamous cell carcinoma (OSCC). The original RNA-seq data of OSCC from The Cancer Genome Atlas (TCGA) project and Gene Expression Omnibus (GEO) database were transformed into a metabolic pathway enrichment score matrix by single-sample gene set enrichment analysis (ssGSEA). A novel prognostic signature based on metabolic pathways was constructed by LASSO and stepwise Cox regression analysis in the training cohort and validated in both testing and validation cohorts. The optimal cut-off value was obtained using the Youden index by receiver operating characteristic (ROC) curve. The overall survival curves were plotted by the Kaplan-Meier method. A time-dependent ROC curve analysis with 1, 3, 5 years as the defining point was performed to evaluate the predictive value of this prognostic signature. A 5-metabolic pathways prognostic signature (5MPS) for OSCC was constructed which stratified patients into subgroups with favorable or inferior survival. It served as an independent prognostic factor for patient survival and had a satisfactory predictive performance for OSCC. Our results developed a novel prognostic signature based on dysregulated metabolic pathways in OSCC and provided support for aberrant metabolism underlying OSCC tumorigenesis.

CA9 transcriptional expression determines prognosis and tumour grade in tongue squamous cell carcinoma patients

CA9 is a member of the carbonic anhydrases’ family, that is often expressed in cancer cells under hypoxic condition. However, the role of CA9 in the molecular mechanisms of tongue squamous cell carcinoma (TSCC) pathogenesis remains unclear. CA9 expression was analysed using the TCGA database, and its influence on survival was performed using Kaplan‐Meier, LASSO and COX regression analyses. The correlation between CA9 and immune infiltration was investigated by CIBERSORT and ESTIMATE. Moreover, the relationship between CA9 expression and downstream molecular regulation pathways was analysed by GSEA, GO and WGCNA. CA9 expression correlated with clinical prognosis and tumour grade in TSCC. Moreover, CA9 expression potentially contributes to the regulation of cancer cell differentiation and mediates tumour‐associated genes and signalling pathways, including apoptosis, hypoxia, G2M checkpoint, PI3K/AKR/mTOR signalling and TGF‐beta signalling pathways. However, the follicular helper T cells, regulatory T cells, immune and stromal scores showed no significance between high and low CA9 expression groups. These findings suggested that CA9 plays a critical role of TSCC prognosis and tumour grade. CA9 expression significantly correlated with the regulation of cell differentiation, various oncogenes and cancer‐associated pathways.