mRNA vaccine development and applications: A special focus on tumors (Review).

Cancer is characterized by unlimited proliferation and metastasis, and traditional therapeutic strategies usually result in the acquisition of drug resistance, thus highlighting the need for more personalized treatment. mRNA vaccines transfer the gene sequences of exogenous target antigens into human cells through transcription and translation to stimulate the body to produce specific immune responses against the encoded proteins, so as to enable the body to obtain immune protection against said antigens; this approach may be adopted for personalized cancer therapy. Since the recent coronavirus pandemic, the development of mRNA vaccines has seen substantial progress and widespread adoption. In the present review, the development of mRNA vaccines, their mechanisms of action, factors influencing their function and the current clinical applications of the vaccine are discussed. A focus is placed on the application of mRNA vaccines in cancer, with the aim of highlighting unique advances and the remaining challenges of this novel and promising therapeutic approach.

Comprehensive analysis of the dynamic changes of volatile and non-volatile metabolites in boletus edulis during processing by HS-SPME-GC-MS and UPLC-MS/MS analysis.

In order to investigate the dynamic changes of flavor compounds, Ultra Performance Liquid Chromatography Tandem Mass Spectrometry (UPLC-MS/MS) combined with Headspace Solid Phase Microextraction Gas Chromatography Mass Spectrometry (HS-SPME-GC-MS) was used to detect the metabolites in different drying processes. A total of 80 volatile compounds and 1319 non-volatile compounds were identified. The trend in the changes of C-8 compounds and sulfur-containing compounds were generally consistent with the trend of key enzyme activities. 479 differential metabolites were identified and revealed that metabolic profiles of compounds in Boletus edulis were altered with increased organic acids and derivatives and lipids and lipid-like molecules. Fatty acids and amino acids were transformed into volatile compounds under the action of enzymes, which played a significant role in the formation of the distinctive flavor of Boletus edulis. Our study provided a theoretical support for fully comprehending the formation mechanism of flavor from Boletus edulis during drying processes.

A prognostic model for Schistosoma japonicum infection-associated liver hepatocellular carcinoma: strengthening the connection through initial biological experiments.

BACKGROUND: Numerous studies have shown that Schistosoma japonicum infection correlates with an increased risk of liver hepatocellular carcinoma (LIHC). However, data regarding the role of this infection in LIHC oncogenesis are scarce. This study aimed to investigate the potential mechanisms of hepatocarcinogenesis associated with Schistosoma japonicum infection. METHODS: By examining chronic liver disease as a mediator, we identified the genes contributing to Schistosoma japonicum infection and LIHC. We selected 15 key differentially expressed genes (DEGs) using weighted gene co-expression network analysis (WGCNA) and random survival forest models. Consensus clustering revealed two subgroups with distinct prognoses. Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression identified six prognostic DEGs, forming an Schistosoma japonicum infection-associated signature for strong prognosis prediction. This signature, which is an independent LIHC risk factor, was significantly correlated with clinical variables. Four DEGs, including BMI1, were selected based on their protein expression levels in cancerous and normal tissues. We confirmed BMI1's role in LIHC using Schistosoma japonicum-infected mouse models and molecular experiments. RESULTS: We identified a series of DEGs that mediate schistosomiasis, the parasitic disease caused by Schistosoma japonicum infection, and hepatocarcinogenesis, and constructed a suitable prognostic model. We analyzed the mechanisms by which these DEGs regulate disease and present the differences in prognosis between the different genotypes. Finally, we verified our findings using molecular biology experiments. CONCLUSION: Bioinformatics and molecular biology analyses confirmed a relationship between schistosomiasis and liver hepatocellular cancer. Furthermore, we validated the role of a potential oncoprotein factor that may be associated with infection and carcinogenesis. These findings enhance our understanding of Schistosoma japonicum infection's role in LIHC carcinogenesis.

An angiogenesis-associated gene-based signature predicting prognosis and immunotherapy efficacy of head and neck squamous cell carcinoma patients.

OBJECTIVES: To develop a model that can assist in the diagnosis and prediction of prognosis for head and neck squamous cell carcinoma (HNSCC). MATERIALS AND METHODS: Data from TCGA and GEO databases were used to generate normalized gene expression data. Consensus Cluster Plus was used for cluster analysis and the relationship between angiogenesis-associated gene (AAG) expression patterns, clinical characteristics and survival was examined. Support vector machine (SVM) and least absolute shrinkage and selection operator (LASSO) analyzes and multiple logistic regression analyzes were performed to determine the diagnostic model, and a prognostic nomogram was constructed using univariate and multivariate Cox regression analyses. ESTIMATE, XCELL, TIMER, QUANTISEQ, MCPCOUNTER, EPIC, CIBERSORT-ABS, CIBERSORT algorithms were used to assess the immune microenvironment of HNSCC patients. In addition, gene set enrichment analysis, treatment sensitivity analysis, and AAGs mutation studies were performed. Finally, we also performed immunohistochemistry (IHC) staining in the tissue samples. RESULTS: We classified HNSCC patients into subtypes based on differences in AAG expression from TCGA and GEO databases. There are differences in clinical features, TME, and immune-related gene expression between two subgroups. We constructed a HNSCC diagnostic model based on nine AAGs, which has good sensitivity and specificity. After further screening, we constructed a prognostic risk signature for HNSCC based on six AAGs. The constructed risk score had a good independent prognostic significance, and it was further constructed into a prognostic nomogram together with age and stage. Different prognostic risk groups have differences in immune microenvironment, drug sensitivity, gene enrichment and gene mutation. CONCLUSION: We have constructed a diagnostic and prognostic model for HNSCC based on AAG, which has good performance. The constructed prognostic risk score is closely related to tumor immune microenvironment and immunotherapy response.

A pan-cancer analysis uncovering the function of CRHBP in tumor immunity, prognosis and drug response: especially its function in LIHC.

Corticotropin-releasing hormone-binding protein (CRHBP) is involved in many physiological processes. However, it is still unclear what role CRHBP has in tumor immunity and prognosis prediction. Using databases such as the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Tumor Protein Database, Timer Database, and Gene Expression Profiling Interactive Analysis (GEPIA), we evaluated the potential role of CRHBP in diverse cancers. Further research looked into the relationships between CRHBP and tumor survival prognosis, immune infiltration, immune checkpoint (ICP) indicators, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), DNA methylation, tumor microenvironment (TME), and drug responsiveness. The anticancer effect of CRHBP in liver hepatocellular carcinoma (LIHC) was shown by Western blotting, EdU staining, JC-1 staining, transwell test, and wound healing assays. CRHBP expression is significantly low in the majority of tumor types and is associated with survival prognosis, ICP markers, TMB, and microsatellite instability (MSI). The expression of CRHBP was found to be substantially related to the quantity of six immune cell types, as well as the interstitial and immunological scores, showing that CRHBP has a substantial impact in the TME. We also noticed a link between the IC50 of a number of anticancer medicines and the degree of CRHBP expression. CRHBP-related signaling pathways were discovered using functional enrichment. Cox regression analysis showed that CRHBP expression was an independent prognostic factor for LIHC. CRHBP has a tumor suppressor function in LIHC, according to cell and molecular biology trials. CRHBP has a significant impact on tumor immunity, treatment, and prognosis, and has the potential as a cancer treatment target and prognostic indicator.

Function of microRNA­124 in the pathogenesis of cancer (Review).

Non­coding RNAs with a length of 22­24 nt are known as microRNAs (miRNAs or miRs), which are critical regulators of protein translation. Over the past 10 years, the roles of miRNAs have been extensively investigated in several human cancer types. There is evidence to indicate that miRNAs regulate gene expression by concentrating on a number of substances that have an impact on the physiology and development of cancer cells. Thus, miRNAs as regarded as effective targets for further studies on the design of novel therapeutic strategies. Hepatocellular carcinoma, breast, prostate, and ovarian cancer are only a few of the cancers that miR­124 suppresses. Furthermore, it has been shown that miR­124 is linked to the development and aggressive spread of malignancies. The aim of the present review was to clarify and highlight the role of miR­124 in the development and progression of cancer, emphasizing recent research illustrating how miR­124 has been used as a therapeutic agent against cancer, as well as the diagnostic potential, regulatory mechanisms and clinical application of miR­124.

Clinical analysis of prolonged viral clearance time in patients with lymphoma combined with novel coronavirus infection.

Objective: To compare the period of viral clearance and its influencing factors after severe acute respiratory syndrome coronavirus (SARS-CoV-2) infection between patients with lymphoma and lung cancer. Methods: We retrospectively collected the clinical data of patients with lymphoma and lung cancer (118 cases) diagnosed with SARS-CoV-2 infection and hospitalized in the First Affiliated Hospital of Anhui Medical University between 1 December 2022, and 15 March 2023. Finally, 87 patients with prolonged virus clearance times were included and divided into lymphoma (40 cases) and lung cancer (47 cases) groups. We used the Kaplan-Meier method to draw a negative turn curve. We performed a univariate analysis of the prolongation of virus clearance time and a Cox regression model for multivariate analysis. Results: The median times for viral clearance in the lung cancer and lymphoma groups were 18 (95% confidence interval [CI] 15.112-20.888) and 32 (95%CI 27.429-36.571) days, respectively. Log-rank analysis showed a statistically significant difference (p = 0.048), and the lymphocyte count in the lymphoma group was lower than that in the lung cancer group (p = 0.044). We used the Cox regression model to conduct a multivariate analysis, which revealed that in lymphoma patients, the interval between the time of diagnosis and the time of SARS-CoV-2 infection <24 months (hazard ratio [HR]: 0.182, 95%CI: 0.062-0.535, p = 0.02), an interval between the last anti-CD20 monoclonal antibody treatment and the time of SARS-CoV-2 infection of <2 months (HR: 0.101, 95%CI: 0.029-0.358, p < 0.001), and a decrease in peripheral blood lymphocyte levels (HR: 0.380, 95%CI: 0.179-0.808, p = 0.012) were independent risk factors for prolonged viral clearance time. Conclusion: Patients with lymphoma combined with SARS-CoV-2 infection had a longer virus clearance time than did patients with lung cancer. Moreover, the lymphocyte count in the lymphoma group was lower than that in the lung cancer group; therefore, the immune status of patients with lymphoma is lower than that of patients with lung cancer. An interval between lymphoma diagnosis and SARS-CoV-2 infection of <2 years, anti-CD20 monoclonal antibody treatment within the past 2 months, and a decrease in lymphocyte levels in the peripheral blood prolonged the virus clearance time in the patients in this study.

A predictive model of immune infiltration and prognosis of head and neck squamous cell carcinoma based on cell adhesion-related genes: including molecular biological validation.

Background: Focal adhesion serves as a bridge between tumour cells and the extracellular matrix (ECM) and has multiple roles in tumour invasion, migration, and therapeutic resistance. However, studies on focal adhesion-related genes (FARGs) in head and neck squamous cell carcinoma (HNSCC) are limited. Methods: Data on HNSCC samples were obtained from The Cancer Genome Atlas and GSE41613 datasets, and 199 FARGs were obtained from the Molecular Signatures database. The integrated datasets' dimensions were reduced by the use of cluster analysis, which was also used to classify patients with HNSCC into subclusters. A FARG signature model was developed and utilized to calculate each patient's risk score using least extreme shrinkage and selection operator regression analysis. The risk score was done to quantify the subgroups of all patients. We evaluated the model's value for prognostic prediction, immune infiltration status, and therapeutic response in HNSCC. Preliminary molecular and biological experiments were performed to verify these results. Results: Two different HNSCC molecular subtypes were identified according to FARGs, and patients with C2 had a shorter overall survival (OS) than those with C1. We constructed an FARG signature comprising nine genes. We constructed a FARG signature consisting of nine genes. Patients with higher risk scores calculated from the FARG signature had a lower OS, and the FARG signature was considered an independent prognostic factor for HNSCC in univariate and multivariate analyses. FARGs are associated with immune cell invasion, gene mutation status, and chemosensitivity. Finally, we observed an abnormal overexpression of MAPK9 in HNSCC tissues, and MAPK9 knockdown greatly impeded the proliferation, migration, and invasion of HNSCC cells. Conclusion: The FARG signature can provide reliable prognostic prediction for patients with HNSCC. Apart from that, the genes in this model were related to immune invasion, gene mutation status, and chemosensitivity, which may provide new ideas for targeted therapies for HNSCC.

A machine learning model for distinguishing Kawasaki disease from sepsis.

KD is an acute systemic vasculitis that most commonly affects children under 5 years old. Sepsis is a systemic inflammatory response syndrome caused by infection. The main clinical manifestations of both are fever, and laboratory tests include elevated WBC count, C-reactive protein, and procalcitonin. However, the two treatments are very different. Therefore, it is necessary to establish a dynamic nomogram based on clinical data to help clinicians make timely diagnoses and decision-making. In this study, we analyzed 299 KD patients and 309 sepsis patients. We collected patients' age, sex, height, weight, BMI, and 33 biological parameters of a routine blood test. After dividing the patients into a training set and validation set, the least absolute shrinkage and selection operator method, support vector machine and receiver operating characteristic curve were used to select significant factors and construct the nomogram. The performance of the nomogram was evaluated by discrimination and calibration. The decision curve analysis was used to assess the clinical usefulness of the nomogram. This nomogram shows that height, WBC, monocyte, eosinophil, lymphocyte to monocyte count ratio (LMR), PA, GGT and platelet are independent predictors of the KD diagnostic model. The c-index of the nomogram in the training set and validation is 0.926 and 0.878, which describes good discrimination. The nomogram is well calibrated. The decision curve analysis showed that the nomogram has better clinical application value and decision-making assistance ability. The nomogram has good performance of distinguishing KD from sepsis and is helpful for clinical pediatricians to make early clinical decisions.

Effectiveness of the recurrent laryngeal nerve monitoring during endoscopic thyroid surgery: systematic review and meta-analysis.

BACKGROUND: Thyroid disease is a common endocrine disorder, and thyroid surgeries and postoperative complications have increased recently. This study aimed to explore the effectiveness of intraoperative nerve monitoring (IONM) in endoscopic thyroid surgery using subgroup analysis and determine confounding factors. MATERIALS AND METHODS: Two researchers individually searched for relevant studies published till November 2022 in the PubMed, Embase, Web of Science and Cochrane Library databases. Eventually, eight studies met the inclusion criteria. Heterogeneity was assessed using the Cochran's Q test, and a funnel plot was implemented to evaluate publication bias. The odds ratio or risk difference were calculated using fixed-effects models. The weighted mean difference of continuous variables was calculated. Subgroup analysis was performed according to the disease type. RESULTS: Eight eligible papers included 915 patients and 1242 exposed nerves. The frequencies of transient, permanent and total recurrent laryngeal nerve (RLN) palsy were 2.64, 0.19 and 2.83%, respectively, in the IONM group and 6.15, 0.75 and 6.90%, respectively, in the conventional exposure group. In addition, analysis of the secondary outcome indicators for the average total length of surgery, localisation time of the RLN, recognition rate of the superior laryngeal nerve and length of incision revealed that IONM reduced the localisation time of the RLN and increased the identification rate of the superior laryngeal nerve. Subgroup analysis showed that IONM significantly reduced the incidence of RLN palsy in patients with malignancies. CONCLUSIONS: The use of IONM significantly reduced the incidence of transient RLN palsy during endoscopic thyroid surgery, but it did not significantly reduce the incidence of permanent RLN palsy. However, the reduction in the total RLN palsy was statistically significant. In addition, IONM can effectively reduce the location time of the RLN and increase the recognition rate of the superior laryngeal nerve. Therefore, the application of IONM for malignant tumours is recommended.

Non-thermal plasma-treated melatonin inhibits the biological activity of HCC cells by increasing intracellular ROS levels and reducing RRM2 expression.

Non-thermal plasma (NTP) is thought to have a cytotoxic effect on tumor cells. Although its application in cancer therapy has shown considerable promise, the current understanding of its mechanism of action and cellular responses remains incomplete. Furthermore, the use of melatonin (MEL) as an adjuvant anticancer drug remains unexplored. In this study, we found that NTP assists MEL in promoting apoptosis, delaying cell cycle progression, and inhibiting cell invasion and migration in hepatocellular carcinoma (HCC) cells. This mechanism may be associated with the regulation of intracellular reactive oxygen species levels and ribonucleotide reductase regulatory subunit M2 expression. Our findings confirm the pharmacological role of MEL and the adjuvant value of NTP, emphasizing their potential in combination therapy for HCC. Our study may have important implications for the development of new approaches for HCC treatment.

Identifying Macrophage-Related Genes in Ulcerative Colitis Using Weighted Coexpression Network Analysis and Machine Learning.

Ulcerative colitis (UC) is an inflammatory bowel disease of unknown cause that typically affects the colon and rectum. Innate intestinal immunity, including macrophages, plays a significant role in the pathological development of UC. Using the CIBERSORT algorithm, we observed elevated levels of 22 types of immune cell infiltrates, as well as increased M1 and decreased M2 macrophages in UC compared to normal colonic mucosa. Weighted gene coexpression network analysis (WGCNA) was used to identify modules associated with macrophages and UC, resulting in the identification of 52 macrophage-related genes (MRGs) that were enriched in macrophages at single-cell resolution. Consensus clustering based on these 52 MRGs divided the integrated UC cohorts into three subtypes. Machine learning algorithms were used to identify ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1), sodium- and chloride-dependent neutral and basic amino acid transporter B(0+) (SLC6A14), and 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2) in the training set, and their diagnostic value was validated in independent validation sets. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) revealed the main biological effects, and that interleukin-17 was one of several signaling pathways enriched by the three genes. We also constructed a competitive endogenous RNA (CeRNA) network reflecting a potential posttranscriptional regulatory mechanism. Expression of diagnostic markers was validated in vivo and in biospecimens, and our immunohistochemistry (IHC) results confirmed that HMGCS2 gradually decreased during the transformation of UC to colorectal cancer. In conclusion, ENPP1, SLC6A14, and HMGCS2 are associated with macrophages and the progression of UC pathogenesis and have good diagnostic value for patients with UC.

Development and validation of an online nomogram for predicting the outcome of open tracheotomy decannulation: a two-center retrospective analysis.

BACKGROUND: Tracheotomy decannulation is critical for patients in the intensive care unit (ICU) to recover. In this study, we developed and validated an intuitive nomogram to predict the success rate of tracheotomy decannulation. METHODS: We collected the data of 627 ICU patients before open tracheotomy decannulation from two medical institutions, including 466 patients (135 success and 331 failure) from the First Affiliated Hospital of Anhui Medical University as a training cohort, and 161 patients (57 success and 104 failure) from the Second Affiliated Hospital of Anhui Medical University as an external validation cohort. A least absolute shrinkage and multivariate logistic regression analysis were performed to determine the independent risk factors and construct the nomogram. The area under the receiver operating characteristic curve (AUC) was used to assess discrimination and the calibration plots were used to assess consistency. The clinical application was assessed using decision curve analysis and the clinical impact curve. RESULTS: 7 independent risk factors were eventually included in the prediction model. The AUC of the training cohort, internal validation and external validation were 0.932, 0.926, and 0.915, showing good discrimination. The model performed well in terms of calibration, decision curve analysis, and clinical impact curves. The superior performance of the model was also confirmed by external validation. CONCLUSION: This nomogram can help ICU physicians identify high-risk patients for decannulation and plan their pre-decannulation treatment accordingly.

The role of IL-6 in coronavirus, especially in COVID-19.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infects both people and animals and may cause significant respiratory problems, including lung illness: Corona Virus Disease 2019 (COVID-19). Swabs taken from the throat and nose of people who have the illness or are suspected of having it have shown this pathogenic virus. When SARS-CoV-2 infects the upper and lower respiratory tracts, it may induce moderate to severe respiratory symptoms, as well as the release of pro-inflammatory cytokines including interleukin 6 (IL-6). COVID-19-induced reduction of IL-6 in an inflammatory state may have a hitherto undiscovered therapeutic impact. Many inflammatory disorders, including viral infections, has been found to be regulated by IL-6. In individuals with COVID-19, one of the primary inflammatory agents that causes inflammatory storm is IL-6. It promotes the inflammatory response of virus infection, including the virus infection caused by SARS-CoV-2, and provides a new diagnostic and therapeutic strategy. In this review article, we highlighted the functions of IL-6 in the coronavirus, especially in COVID-19, showing that IL-6 activation plays an important function in the progression of coronavirus and is a rational therapeutic goal for inflammation aimed at coronavirus.

An ion-channel-gene-based prediction model for head and neck squamous cell carcinoma: Prognostic assessment and treatment guidance.

Purpose: Head and neck squamous cell carcinoma (HNSCC) is a very diverse malignancy with a poor prognosis. The purpose of this study was to develop a new signature based on 12 ion channel genes to predict the outcome and immune status of HNSCC patients. Methods: Clinicopathological information and gene sequencing data of HNSCC patients were generated from the Cancer Genome Atlas and Gene Expression Omnibus databases. A set of 323 ion channel genes was obtained from the HUGO Gene Nomenclature Committee database and literature review. Using univariate Cox regression analysis, the ion channel genes related to HNSCC prognosis were identified. A prognostic signature and nomogram were then created using machine learning methods. Kaplan-Meier analysis was used to explore the relevance of the risk scores and overall survival (OS). We also investigated the association between risk scores, tumor immune infiltration, and gene mutational status. Finally, we detected the expression levels of the signature genes by quantitative real-time polymerase chain reaction, western blotting, and immunohistochemistry. Results: We separated the patients into high- and low-risk groups according to the risk scores computed based on these 12 ion channel genes, and the OS of the low-risk group was significantly longer (p<0.001). The area under the curve for predicting 3-year survival was 0.729. Univariate and multivariate analyses showed that the 12-ion-channel-gene risk model was an independent prognostic factor. We also developed a nomogram model based on risk scores and clinicopathological variables to forecast outcomes. Furthermore, immune cell infiltration, gene mutation status, immunotherapy response, and chemotherapeutic treatment sensitivity were all linked to risk scores. Moreover, high expression levels of ANO1, AQP9, and BEST2 were detected in HNSCC tissues, whereas AQP5, SCNN1G, and SCN4A expression was low in HNSCC tissues, as determined by experiments. Conclusion: The 12-ion-channel-gene prognostic signatures have been demonstrated to be highly efficient in predicting the prognosis, immune microenvironment, gene mutation status, immunotherapy response, and chemotherapeutic sensitivity of HNSCC patients.

The role of resveratrol on rheumatoid arthritis: From bench to bedside.

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by symmetrical polyarthritis as its main clinical manifestation. Uncontrolled RA eventually leads to joint deformities and loss of function. Currently, the pathogenesis of RA remains under discussion, and RA treatment is still at the bottleneck stage. Resveratrol has long been regarded as a potential antioxidant drug for RA treatment. Currently, resveratrol is considered to exert therapeutic effects on RA by activating silent information regulator 1 (SIRT1) and its downstream pathways. There is notable crosstalk between the SIRT1 and NF-κB pathways, and these pathways, which play an essential role in the development of RA, are unexpectedly linked to the influence of resveratrol. Based on recent studies of almost all the pathways that resveratrol can affect, this review summarizes a regulatory chain of core components that cover multiple tracks. We also list the effects of resveratrol on immune cells and other subtle controls, which can help clinicians understand the known mechanism of resveratrol and better treat patients with RA.

Interleukin 22 and its association with neurodegenerative disease activity.

It is worth noting that neuroinflammation is well recognized as a symptom of neurodegenerative diseases (NDs). The regulation of neuroinflammation becomes an attractive focus for innovative ND treatment technologies. There is evidence that IL-22 is associated with the development and progression of a wide assortment of NDs. For example, IL-22 can activate glial cells, causing them to generate pro-inflammatory cytokines and encourage lymphocyte infiltration in the brain. IL-22 mRNA is highly expressed in Alzheimer's disease (AD) patients, and a high expression of IL-22 has also been detected in the brains of patients with other NDs. We examine the role of IL-22 in the development and treatment of NDs in this review, and we believe that IL-22 has therapeutic potential in these diseases.

Emerging role of different DNA methyltransferases in the pathogenesis of cancer.

DNA methylation is one of the most essential epigenetic mechanisms to regulate gene expression. DNA methyltransferases (DNMTs) play a vital role in DNA methylation in the genome. In mammals, DNMTs act with some elements to regulate the dynamic DNA methylation patterns of embryonic and adult cells. Conversely, the aberrant function of DNMTs is frequently the hallmark in judging cancer, including total hypomethylation and partial hypermethylation of tumor suppressor genes (TSGs), which improve the malignancy of tumors, aggravate the ailment for patients, and significantly exacerbate the difficulty of cancer therapy. Since DNA methylation is reversible, currently, DNMTs are viewed as an important epigenetic target for drug development. However, the impression of DNMTs on cancers is still controversial, and therapeutic methods targeting DNMTs remain under exploration. This review mainly summarizes the relationship between the main DNMTs and cancers as well as regulatory mechanisms and clinical applications of DNMTs in cancer and highlights several forthcoming strategies for targeting DNMTs.

A Signature Based on Costimulatory Molecules for the Assessment of Prognosis and Immune Characteristics in Patients With Stomach Adenocarcinoma.

Although costimulatory molecules have been shown to boost antitumor immune responses, their significance in stomach adenocarcinoma (STAD) remains unknown. The purpose of this study was to examine the gene expression patterns of costimulatory molecule genes in patients with STAD and develop a predictive signature to aid in therapy selection and outcome prediction. We used 60 costimulatory family genes from prior research to conduct the first complete costimulatory molecular analysis in patients with STAD. In the two study groups, consensus clustering analysis based on these 60 genes indicated unique distribution patterns and prognostic differences. Using the least absolute shrinkage and selection operator and Cox regression analysis, we identified nine costimulatory molecular gene pairs (CMGPs) with prognostic value. With these nine CMGPs, we were able to develop a costimulatory molecule-related prognostic signature that performed well in an external dataset. For the patients with STAD, the signature was proven to be a risk factor independent of the clinical characteristics, indicating that this signature may be employed in conjunction with clinical considerations. A further connection between the signature and immunotherapy response was discovered. The patients with high mutation rates, an abundance of infiltrating immune cells, and an immunosuppressive milieu were classified as high-risk patients. It is possible that these high-risk patients have a better prognosis for immunotherapy since they have higher cytolytic activity scores and immunophenoscores of CTLA4 and PD-L1/PD-L2 blockers. Therefore, our signature may help clinicians in assessing patient prognosis and developing treatment plans.

Myeloid cells in alcoholic liver diseases: Mechanism and prospect.

Alcoholic liver disease (ALD) is a leading chronic liver disease in which immune cells play a vital role. Myeloid cells have been extensively studied in ALD, including granulocytes, macrophages, monocytes, and dendritic cells, which are involved in the occurrence and progression of steatosis, inflammation, fibrosis, and eventual cirrhosis. These cells can be popularly targeted and regulated by factors from different sources, including cytokines secreted by other cells, extracellular vesicles, and substances in serum-for example, infiltration of monocytes or neutrophils, activation of Kupffer cells, and polarization of macrophages. These processes can affect and change the function and phenotype of myeloid cells. Here we mainly review the key mediators that affect the infiltration and function of mainly myeloid cells in ALD as well as their regulatory mechanisms on target cells, which may provide novel immunotherapeutic approaches. The single-cell multimodal omics of myeloid cells is also discussed to help transform them into basic research or therapeutic strategy of ALD clinically.