Current perspectives and trends of CD39-CD73-eAdo/A2aR research in tumor microenvironment: a bibliometric analysis.

Background and objective: Extracellular adenosine (eAdo) bridges tumor metabolism and immune regulation. CD39-CD73-eAdo/A2aR axis regulates tumor microenvironment (TME) and immunotherapy response. In the era of immunotherapy, exploring the impact of the CD39-CD73-eAdo/A2aR axis on TME and developing targeted therapeutic drugs to enhance the efficacy of immunotherapy are the current research hotspots. This study summarizes and explores the research trends and hotspots of the adenosine axis in the field of TME to provide ideas for further in-depth research. Methods: Literature information was obtained from the Web of Science core collection database. The VOS viewer and the bibliometric tool based on R were used to quantify and identify cooperation information and individual influence by analyzing the detailed information of the global annual publication volume, country/region and institution distribution, article authors and co-cited authors, and journal distribution of these articles. At the same time, the distribution of author keywords and the co-occurrence of author keywords, highly cited articles, and highly co-cited references of CD39-CD73-eAdo/A2aR in the field of TME were analyzed to determine research hotspots and trends. Result: 1,721 articles published in the past ten years were included in this study. Through bibliometric analysis, we found that (1) 69 countries and regions explored the effect of the CD39-CD73-eAdo/A2aR on TME, and the research was generally on the rise. Researchers in the United States dominated research in this area, with the highest total citation rate. China had the most significant number of publications. (2) Harvard University has published the most articles in this field. (3) 12,065 authors contributed to the publication of papers in this field, of which 23 published at least eight papers. STAGG J had significant academic influence, with 24 published articles and 2,776 citations. Co-cited authors can be clustered into three categories. Stagg J, Allard B, Ohta A, and Antonioli, L occupied a central position in the network. (4) 579 scholarly journals have published articles in this field. The journal FRONTIERS IN IMMUNOLOGY published the most significant number of papers, with 97 articles and a total of 2,317 citations, and the number of publications increased year by year. (5) "The ectonucleotidases CD39 and CD73: Novel checkpoint inhibitor targets" was the most frequently local cited article (163 times). The "A2A adenosine receptor protects tumors from antitumor T cells" was the most co-cited reference (224 times). (6) Through the analysis of author keywords, we found that the relationship between adenosine and immunotherapy was a core concept for many researchers in this field. Breast cancer, melanoma, colorectal cancer, ovarian cancer, glioblastoma, pancreatic cancer, hepatocellular carcinoma, and lung cancer were the most frequent cancer types in adenosine-related tumor studies. Immunotherapy, immunosuppression, immune checkpoint, and immune checkpoint inhibitors were the hot keywords in the research, reflecting the importance of the adenosine metabolic pathway in tumor immunotherapy. The keywords such as Immunogenic cell death, T cells, Sting, regulatory T cells, innate immunity, and immune infiltration demonstrated the pathways by which adenosine affected the TME. The famous author keywords in recent years have been immunotherapy, immunogenic cell death, inflammation, lung cancer, and gastric cancer. Conclusion: The effect of CD39-CD73-eAdo/A2aR on the infiltration and function of various immune cells in TME, tumor immunotherapy response, and patient prognosis has attracted the attention of researchers from many countries/regions. American scholars still dominate the research in this field, but Chinese scholars produce the most research results. The journal FRONTIERS IN IMMUNOLOGY has published the wealthiest research in the field. Stagg J was a highly influential researcher in this field. Further exploration of targeted inhibition of CD39-CD73-eAdo/A2aR alone or in combination with other immunotherapy, radiotherapy, and chemotherapy in treating various cancer types and developing effective clinical therapeutic drugs are continuous research hotspots in this field.

Corrigendum: Deep learning or radiomics based on CT for predicting the response of gastric cancer to neoadjuvant chemotherapy: a meta-analysis and systematic review.

[This corrects the article DOI: 10.3389/fonc.2024.1363812.].

Deep learning or radiomics based on CT for predicting the response of gastric cancer to neoadjuvant chemotherapy: a meta-analysis and systematic review.

Background: Artificial intelligence (AI) models, clinical models (CM), and the integrated model (IM) are utilized to evaluate the response to neoadjuvant chemotherapy (NACT) in patients diagnosed with gastric cancer. Objective: The objective is to identify the diagnostic test of the AI model and to compare the accuracy of AI, CM, and IM through a comprehensive summary of head-to-head comparative studies. Methods: PubMed, Web of Science, Cochrane Library, and Embase were systematically searched until September 5, 2023, to compile English language studies without regional restrictions. The quality of the included studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) criteria. Forest plots were utilized to illustrate the findings of diagnostic accuracy, while Hierarchical Summary Receiver Operating Characteristic curves were generated to estimate sensitivity (SEN) and specificity (SPE). Meta-regression was applied to analyze heterogeneity across the studies. To assess the presence of publication bias, Deeks' funnel plot and an asymmetry test were employed. Results: A total of 9 studies, comprising 3313 patients, were included for the AI model, with 7 head-to-head comparative studies involving 2699 patients. Across the 9 studies, the pooled SEN for the AI model was 0.75 (95% confidence interval (CI): 0.66, 0.82), and SPE was 0.77 (95% CI: 0.69, 0.84). Meta-regression was conducted, revealing that the cut-off value, approach to predicting response, and gold standard might be sources of heterogeneity. In the head-to-head comparative studies, the pooled SEN for AI was 0.77 (95% CI: 0.69, 0.84) with SPE at 0.79 (95% CI: 0.70, 0.85). For CM, the pooled SEN was 0.67 (95% CI: 0.57, 0.77) with SPE at 0.59 (95% CI: 0.54, 0.64), while for IM, the pooled SEN was 0.83 (95% CI: 0.79, 0.86) with SPE at 0.69 (95% CI: 0.56, 0.79). Notably, there was no statistical difference, except that IM exhibited higher SEN than AI, while maintaining a similar level of SPE in pairwise comparisons. In the Receiver Operating Characteristic analysis subgroup, the CT-based Deep Learning (DL) subgroup, and the National Comprehensive Cancer Network (NCCN) guideline subgroup, the AI model exhibited higher SEN but lower SPE compared to the IM. Conversely, in the training cohort subgroup and the internal validation cohort subgroup, the AI model demonstrated lower SEN but higher SPE than the IM. The subgroup analysis underscored that factors such as the number of cohorts, cohort type, cut-off value, approach to predicting response, and choice of gold standard could impact the reliability and robustness of the results. Conclusion: AI has demonstrated its viability as a tool for predicting the response of GC patients to NACT Furthermore, CT-based DL model in AI was sensitive to extract tumor features and predict the response. The results of subgroup analysis also supported the above conclusions. Large-scale rigorously designed diagnostic accuracy studies and head-to-head comparative studies are anticipated. Systematic review registration: PROSPERO, CRD42022377030.

Prognostic role of preoperative lymphocyte/C-reactive protein associated with upper gastrointestinal cancer: a meta-analysis.

Purpose: The lymphocyte/C-reactive protein (LCR) is a novel immunoinflammatory score and prognostic marker, but the relationship between lymphocyte/C-reactive proteins and clinical outcomes in patients with upper gastrointestinal cancers remains controversial. This study aimed to evaluate the relationship between LCR and the prognosis of upper gastrointestinal cancer by systematic evaluation and meta-analysis. Methods: We systematically searched PubMed, EMBASE, Cochrane, and Web of Science databases to obtain related studies on the relationship between LCR and esophageal cancer (EC), gastric cancer (GC), and esophagogastric junction cancers (EGJ), and used hazard ratio (HR), 95% confidence interval (95%CI) to evaluate the prognostic value of LCR. Outcome measures included overall survival (OS) and disease-free survival (DFS). Results: Eight retrospective cohort studies with 2838 patients were included. Meta-analysis showed that patients with low LCR cancers had poor overall survival OS and disease-free survival DFS (HR=2.18, 95%CI=1.87-2.55; HR=1.88, 95%CI=1.56-2.26). Subgroup analysis based on cancer type, treatment modality, gender, T stage, TNM stage, country, and LCR threshold showed that lower LCR levels were all associated with worse OS and DFS (P<0.05). Conclusion: The LCR can be used as a prognostic marker for patients with upper gastrointestinal cancers, and patients with a lower LCR may have a poor prognosis. Due to the limited number of studies included and mostly retrospective studies, the above findings require validation by more high-quality studies. Systematic Review Registration: https://www.crd.york.ac.uk, identifier CRD42023392433.

Role of 6-phosphogluconate dehydrogenase enzyme 1 in growth and virulence of Toxoplasma gondii and development of attenuated live vaccine.

Toxoplasma gondii is a ubiquitous pathogen that infects all warm-blooded animals, including humans, causing substantial socioeconomic and healthcare burdens. However, there is no ideal vaccine for toxoplasmosis. As metabolism is important in the growth and virulence of Toxoplasma, some key pathways are promising antiparasitic targets. Here, we identified 6-phosphogluconate dehydrogenase 1 (Tg6PGDH1) in the oxidative pentose phosphate pathway as a cytoplasmic protein that is dispensable for tachyzoite growth of T. gondii in vitro but critical for virulence and cyst formation in vivo. The depletion of Tg6PGDH1 causes decreased gene transcription involved in signal transduction, transcriptional regulation and virulence. Furthermore, we analysed the protective effect of the ME49Δ6pgdh1 mutant as an attenuated vaccine and found that ME49Δ6pgdh1 immunization stimulated strong protective immunity against lethal challenges and blocked cyst formation caused by reinfection. Furthermore, we showed that ME49Δ6pgdh1 immunization stimulated increased levels of interferon-gamma, tumour necrosis factor-alpha and Toxoplasma-specific IgG antibodies. These data highlight the role of Tg6PGDH1 in the growth and virulence of T. gondii and its potential as a target for the development of a live-attenuated vaccine.

A novel circRNA, hsa_circ_0069382, regulates gastric cancer progression.

Aberrant expression of circRNAs is closely associated with the progression of gastric cancer; however, the specific mechanisms involved remain unclear. Our aim was to identify new gastric cancer biomarkers and explore the molecular mechanisms of gastric cancer progression. Therefore, we analyzed miRNA and circRNA microarrays of paired early-stage gastric cancer samples. Our study identified a new circRNA called hsa_circ_0069382, that had not been reported before and was expressed at low levels in gastric cancer tissues. Our study also included bioinformatics analyses which determined that the high expression of hsa_circ_0069382 regulated the BTG anti-proliferation factor 2 (BTG2)/ focal adhesion kinase (FAK) axis in gastric cancer lines by sponging for miR-15a-5p. Therefore, proliferation, invasion, and migration of gastric cancer is impacted. miR-15a-5p overexpression partially restored the effects of hsa_circ_0069382. This study provides potential new therapeutic options and a future direction to explore for gastric cancer treatment, and biomarkers.

Small intestinal angiosarcoma on clinical presentation, diagnosis, management and prognosis: A case report and review of the literature.

BACKGROUND: Angiosarcoma is a highly malignant soft-tissue sarcoma derived from vascular endothelial cells that mainly occurs in the skin and subcutaneous tissues. Small-intestinal angiosarcomas are rare, and the prognosis is poor. CASE SUMMARY: We reported a case of primary multifocal ileal angiosarcoma and analyze previously reported cases to improve our understanding of small intestinal angiosarcoma. Small intestinal angiosarcoma is more common in elderly and male patients. Gastrointestinal bleeding, anemia, abdominal pain, weakness, and weight loss were the common symptoms. CD31, CD34, factor VIII-related antigen, ETS-related gene, friend leukemia integration 1, and von Willebrand factor are valuable immunohistochemical markers for the diagnosis of small-intestinal angiosarcoma. Small-intestinal angiosarcoma most commonly occurs in the jejunum, followed by the ileum and duodenum. Radiation and toxicant exposure are risk factors for angiosarcoma. After a definite diagnosis, the mean and median survival time was 8 mo and 3 mo, respectively. Kaplan-Meier survival analysis showed that age, infiltration depth, chemotherapy, and the number of small intestinal segments invaded by tumor lesions were prognostic factors for small intestinal angiosarcoma. Multivariate Cox regression analysis showed that chemotherapy and surgery significantly improved patient prognosis. CONCLUSION: Angiosarcoma should be considered for unexplained melena and abdominal pain, especially in older men and patients with a history of radiation exposure. Prompt treatment, including surgery and adjuvant chemotherapy, is essential to prolonging patient survival.

Development and validation of an ECM-related prognostic signature to predict the immune landscape of human hepatocellular carcinoma.

BACKGROUND: The global burden of hepatocellular carcinoma (HCC) is increasing, negatively impacting social health and economies. The discovery of novel and valuable biomarkers for the early diagnosis and therapeutic guidance of HCC is urgently needed. METHODS: Extracellular matrix (ECM)-related gene sets, transcriptome data and mutation profiles were downloaded from the Matrisome Project and The Cancer Genome Atlas (TCGA)-LIHC datasets. Coexpression analysis was initially performed with the aim of identifying ECM-related lncRNAs (r > 0.4, p < 0.001). The screened lncRNAs were subjected to univariate analysis to obtain a series of prognosis-related lncRNA sets, which were incorporated into least absolute selection and shrinkage operator (LASSO) regression for signature establishment. Following the grouping of LIHC samples according to risk score, the correlations between the signature and clinicopathological, tumour immune infiltration, and mutational characteristics as well as therapeutic response were also analysed. lncRNA expression levels used for modelling were finally examined at the cellular and tissue levels by real-time PCR. All analyses were based on R software. RESULTS: AL031985.3 and MKLN1-AS were ultimately identified as signature-related lncRNAs, and both were significantly upregulated in HCC tissue samples and cell lines. The prognostic value of the signature reflected by the AUC value was superior to that of age, sex, grade and stage. Correlation analysis results demonstrated that high-risk groups exhibited significant enrichment of immune cells (DCs, macrophages and Tregs) and increased expression levels of all immune checkpoint genes. Prominent differences in clinicopathological profiles, immune functions, tumour mutation burden (TMB) and drug sensitivity were noted between the two risk groups. CONCLUSIONS: Our signature represents a valuable predictive tool in the prognostic management of HCC patients. Further validation of the mechanisms involved is needed.

Identification of N7-methylguanosine-related IncRNA signature as a potential predictive biomarker for colon adenocarcinoma.

N7-Methylguanosine (m7G) is an RNA modification serving as a key part of colon cancer development. Thus, a comprehensive analysis was executed to explore prognostic roles and associations with the immune status of the m7G-related lncRNA (m7G-RNAs) in colon adenocarcinoma (COAD). Identification of m7G-RNAs was achieved via Pearson's correlation analysis of lncRNAs in the TCGA-COAD dataset and m7G regulators. A prognostic signature was developed via LASSO analyses. ESTIMATE, CIBERSORT, and ssGSEA algorithms were utilized to assess immune infiltration between different risk groups. Survival analysis suggested the high-risk group possesses poor outcomes compared with the low-risk group. According to the ROC curves, the m7G-RNAs signature exhibited a reliable capability of prediction (AUCs at 1, 3, and 5 years were 0.770, 0.766, and 0.849, respectively). Multivariate hazard analysis proved that the signature was an independent predictive indicator for OS. Moreover, the risk score was related to infiltration levels of naïve B cells, CD4+ memory T cells, and resting NK cells. The result revealed the prognostic value of m7G modification in COAD and provided a novel perspective on personalized immunotherapy strategies.

In silico development and validation of a novel glucose and lipid metabolism-related gene signature in gastric cancer.

Background: Abnormal glucose and lipid metabolism plays a critical role in gastric carcinogenesis and development. Hence, we presented a systematic analysis of glucose and lipid metabolism-related genes to explore their function and prognostic value in gastric cancer (GC). Methods: The consensus clustering algorithm was used to identify the molecular subtypes based on glucose and lipid metabolism-related genes. Subsequently, cox regression analysis and lasso regression analysis were utilized to establish a risk prediction model. A clinical nomogram was constructed to assist prognosis assessment. In addition, ESTIMATE and single-sample gene set enrichment analysis (ssGSEA) algorithms were performed to evaluate the immune infiltration of the metabolic model, and GSEA was used for enrichment analysis of the metabolic signature. Finally, we explored the association between the risk model and anti-cancer therapy for the purpose of clinical application for GC treatment. Results: GC samples were divided into 2 subtypes based on glucose and lipid metabolism-related genes, patients in cluster 2 had a better overall survival (OS) than those in cluster 1. Fifty-two genes were identified by univariable regression analysis. Finally, a 13-gene metabolic signature (CACNA1H, CHST1, IGFBP3, NASP, STC1, VCAN, NUP205, NUP43, PGM2L1, CAV1, ELOVL4, PRKAA2, TNFAIP8L3) was successfully constructed that demonstrated good performance in different datasets, as well as an independent hazardous factor for prognosis. In addition, the nomogram constructed with the clinical variables showed higher predictive efficacy for predicting the 1-, 3-, and 5-year OS. The 13-gene metabolic signature was significantly associated with immune scores and immune cell infiltration in high-risk group. Moreover, GSEA analysis revealed that cancer- and immune-related pathways were enriched in the high-risk group. Finally, our results indicated that there might exist an immunosuppressive status in the high-risk groups. Conclusions: This study demonstrated that glucose and lipid metabolism-related genes were significantly associated with prognosis. Meanwhile, it will provide novel insights into exploring the immunoregulation roles of these genes.

A Novel Matrisomal-Related LncRNA Signature Associated With Survival Outcome and Immune Evasion in Patients With Gastric Cancer.

Background: Different matrisomal patterns are shared across carcinomas. However, little is known about whether there exists a unique tumor matrisome that modulates GC progression and immune regulation. Methods: We conducted a genome-wide analysis based on matrisomal-related lncRNAs (MRLs) in 375 patients with GC from the Cancer Genome Atlas (TCGA) database. Patients were split into the training set and validation set at a ratio of 1:1 using the R package cart. Pearson correlation analysis (PCA) was performed to identify lncRNAs that correlated with matrisome based on differential expression genes. Subsequently, we performed univariate Cox regression analyses and lasso Cox analysis on these lncRNAs to construct a risk model. Considering the primary effect of GRASLND on the GC prognosis, we chose it for further validation in an experimental setting. Results: We identified a 15-MRL signature to predict overall survival and immune cell infiltration of patients with GC. The AUC values to predict 5-year outcome in three sets were 0.89, 0.65, and 0.78, respectively. Further analyses suggested that the high-risk group showed more obvious immune cell infiltration, and demonstrated an immunologically "cold" profile. In vitro, knockdown of GRASLND could inhibit the invasion capability of GC cells, and downregulate the protein expression of crucial matrisomal-related gene MMP9. Conclusions: The 15-MRL gene signature might serve as a relatively good predictive tool to manage patients with GC.

Identification of immunophenotypes in esophageal squamous cell carcinoma based on immune gene sets.

PURPOSE: Esophageal squamous cell carcinoma (ESCC) is a malignant tumor with high heterogeneity. Research on molecular mechanisms involved in the process of tumor origination and progression is extremely limited to investigating mechanisms of molecular typing for ESCC. METHODS: After comprehensively analyzing the gene expression profiles in The Cancer Genome Atlas and Gene Expression Omnibus databases, we identified four immunotypes of ESCC (referred to as C1-C4) based on the gene sets of 28 immune cell subpopulations. The discrepancies in prognostic value, clinical features, drug sensitivity, and tumor components between the immunotypes were individually analyzed. RESULTS: The ranking of immune infiltration is C1 > C4 > C3 > C2. These subtypes are characterized by high and low expression of immune checkpoint proteins, enrichment and insufficiency of immune-related pathways, and differential distribution of immune cell subgroups. Poorer survival was observed in the C1 subtype, which we hypothesized could be caused by an immunosuppressive cell population. Fortunately, C1's susceptibility to anti-PD-1 therapy offers hope for patients with poor prognosis in advanced stages. On the other hand, C4 is sensitive to docetaxel, which may offer novel treatment strategies for ESCC in the future. It is worth noting that immunophenotyping is tightly bound to the abundance of stromal components and stem cells, which could explain the tumor immune escape to some extent. Ultimately, determination of hub genes based on the C1 subtypes provides a reference for the discovery of immunotarget drugs against ESCC. CONCLUSION: The identification of immunophenotypes in our study provides new therapeutic strategies for patients with ESCC.

The Association of Trefoil Factors with Gastric Cancer and Premalignant Lesions: A Cross-Sectional Population-Based Cohort Study.

BACKGROUND: A lack of research on the association of trefoil factors (TFF) with gastric cancer and premalignant lesions (PML) in the general population is an important obstacle to the application of TFFs for gastric cancer screening. We aimed to analyze the association of TFFs with gastric cancer and PMLs in a general population. METHODS: We evaluated 3,986 adults residing in Wuwei, China. We collected baseline characteristics and gastric cancer risk factors, including TFFs, endoscopic diagnosis, and pathologic information. Three logistic regression models were generated to analyze the association between TFFs and gastric cancer, as well as PMLs. Adjusted odds ratio (OR) and 95% confidence intervals (95% CI) were calculated to determine the strength of association. RESULTS: Compared with pepsinogen (PG) and anti-Helicobacter pylori immunoglobulin G antibody (Hp-IgG), TFFs had significant association with gastric cancer and PMLs after adjusting for biomarkers and risk factors (P < 0.05). The ORs (95% CI) for TFF1 (1.67; 1.27-2.20), TFF2 (2.66; 2.01-3.51), and TFF3 (1.32; 1.00-1.74) were larger than the ORs for PGI (0.79; 0.61-1.03), PGI/II (1.00; 0.76-1.31), and Hp-IgG (0.99; 0.73-1.35) in the gastric cancer group. In the intestinal metaplasia (IM) group, not only the TFF3 serum level was the highest, but also the OR (1.92; 1.64-2.25) was the highest. CONCLUSIONS: TFFs were associated with risk of gastric cancer and PMLs. IMPACT: Serum TFFs can improve the screening of high-risk populations for gastric cancer.

Family with sequence similarity 153 member B as a potential prognostic biomarker of gastric cancer.

Gastric cancer (GC) is one of the most common digestive tumors in Northwest China. Previous sequencing analysis revealed that family with sequence similarity 153 member B (FAM153B) might be the primary driver gene of GC. In this study, we aim to explore the potential roles of FAM153B in GC. Microarray data were firstly obtained from public databases with the aim to evaluate the genetic expression of FAM153B between GC and normal tissues. The results were verified in immunohistochemistry (IHC). We also performed the co-expression network analysis and enrichment analysis to identify underlying mechanisms. A correlation analysis of FAM153B expression and immune infiltration was performed then. Furthermore, two GC cell lines were used to evaluate the effect of FAM153B on gastric cell proliferation by employing MTT and Edu assays. Our findings suggest that FAM153B is downregulated in tumoral tissue, and positively associated with unfavorable survival. The enrichment pathways of FAM153B were regulation of signaling receptor activity, DNA replication, cell cycle transition, chromosomal regulation, and so on. Besides, from the perspective of bioinformatics, the protein expression level of FAM153B is related to the degree of immune cell infiltration. In vitro, overexpression of FAM153B inhibit the proliferation of two cell lines. In summary, this study demonstrates that FAM153B might serve as an effective prognostic and therapeutic biomarker in GC.

Risk factors in the development of gastric adenocarcinoma in the general population: A cross-sectional study of the Wuwei Cohort.

Several risk factors have been identified for the development of gastric adenocarcinoma (GAC), where the control group was usually a healthy population. However, it is unclear at what stage known risk factor exert their influence toward the progression to cancer. Based on the Wuwei Cohort, we enrolled 1,739 patients with chronic non-atrophic gastritis (no-CAG), 3,409 patients with chronic atrophic gastritis (CAG), 1,757 patients with intestinal metaplasia (IM), 2,239 patients with low-grade dysplasia (LGD), and 182 patients with high-grade dysplasia (HGD) or GAC to assess the risk factors between each two consecutive stages from no-CAG to GAC/HGD using adjusted logistic regression. We found that different groups of risk factors were associated with different stages. Age, occupation of farmer, low annual family income, Helicobacter pylori (H. pylori) infection, drinking, eating hot food, histories of gastritis and peptic ulcer were associated with the development of CAG. Age, illiteracy, H. pylori infection, smoking, eating hot food, eating quickly, and histories of gastritis and gallbladder diseases were associated with the progression to IM from CAG. Male, occupation of farmer and history of peptic ulcer were associated with the development of LGD from IM. Age, male and polyp history appeared to be risk factors associated with the development of GAC/HGD from LGD. In conclusion, it seems that most risk factors function more as a set of switches that initiated the GAC carcinogenesis. H. Pylori eradication and control of other risk factors should be conducted before IM to decrease the incidence of GAC.

Characterization of lipid droplet metabolism patterns identified prognosis and tumor microenvironment infiltration in gastric cancer.

Background: Gastric cancer is one of the common malignant tumors of the digestive system worldwide, posing a serious threat to human health. A growing number of studies have demonstrated the important role that lipid droplets play in promoting cancer progression. However, few studies have systematically evaluated the role of lipid droplet metabolism-related genes (LDMRGs) in patients with gastric cancer. Methods: We identified two distinct molecular subtypes in the TCGA-STAD cohort based on LDMRGs expression. We then constructed risk prediction scoring models in the TCGA-STAD cohort by lasso regression analysis and validated the model with the GSE15459 and GSE66229 cohorts. Moreover, we constructed a nomogram prediction model by cox regression analysis and evaluated the predictive efficacy of the model by various methods in STAD. Finally, we identified the key gene in LDMRGs, ABCA1, and performed a systematic multi-omics analysis in gastric cancer. Results: Two molecular subtypes were identified based on LDMRGs expression with different survival prognosis and immune infiltration levels. lasso regression models were effective in predicting overall survival (OS) of gastric cancer patients at 1, 3 and 5 years and were validated in the GEO database with consistent results. The nomogram prediction model incorporated additional clinical factors and prognostic molecules to improve the prognostic predictive value of the current TNM staging system. ABCA1 was identified as a key gene in LDMRGs and multi-omics analysis showed a strong correlation between ABCA1 and the prognosis and immune status of patients with gastric cancer. Conclusion: This study reveals the characteristics and possible underlying mechanisms of LDMRGs in gastric cancer, contributing to the identification of new prognostic biomarkers and providing a basis for future research.

Comprehensive analysis to identify DNA damage response-related lncRNA pairs as a prognostic and therapeutic biomarker in gastric cancer.

OBJECTIVE: Gastric cancer (GC) is the fifth most common malignancy and the fourth leading cause of cancer-related mortality worldwide. The identification of valuable predictive signatures to improve the prognosis of patients with GC is becoming a realistic prospect. DNA damage response-related long noncoding ribonucleic acids (drlncRNAs) play an important role in the development of cancers. However, their prognostic and therapeutic values remain sparse in gastric cancer (GC). METHODS: We obtained the transcriptome data and clinical information from The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) cohort. Co-expression network analyses were performed to discover functional modules using the igaph package. Subsequently, lncRNA pairs were identified by bioinformation analysis, and prognostic pairs were determined by univariate analysis, respectively. In addition, we utilized least absolute shrinkage and selection operator (LASSO) cox regression analysis to construct the risk model based on lncRNA pairs. Then, we distinguished between the high- or low- risk groups from patients with GC based on the optimal model. Finally, we reevaluated the association between risk score and overall survival, tumor immune microenvironment, specific tumor-infiltrating immune cells related biomarkers, and the sensitivity of chemotherapeutic agents. RESULTS: 32 drlncRNA pairs were obtained, and a 17-drlncRNA pairs signature was constructed to predict the overall survival of patients with GC. The ROC was 0.797, 0.812 and 0.821 at 1, 2, 3 years, respectively. After reclassifying these patients into different risk-groups, we could differentiate between them based on negative overall survival outcome, specialized tumor immune infiltration status, higher expressed immune cell related biomarkers, and a lower chemotherapeutics sensitivity. Compared with previous models, our model showed better performance with a higher ROC value. CONCLUSION: The prognostic and therapeutic signature established by novel lncRNA pairs could provide promising prediction value, and guide individual treatment strategies in the future.

Comprehensive Analysis to Identify the Epithelial-Mesenchymal Transition-Related Immune Signatures as a Prognostic and Therapeutic Biomarkers in Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is a highly heterogeneous disease with the high rates of the morbidity and mortality due to the lack of the effective prognostic model for prediction. Aim: To construct a risk model composed of the epithelial-mesenchymal transition (EMT)-related immune genes for the assessment of the prognosis, immune infiltration status, and chemosensitivity. Methods: We obtained the transcriptome and clinical data of the HCC samples from The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC) databases. The Pearson correlation analysis was applied to identify the differentially expressed EMT-related immune genes (DE-EMTri-genes). Subsequently, the univariate Cox regression was introduced to screen out the prognostic gene sets and a risk model was constructed based on the least absolute shrinkage and selection operator-penalized Cox regression. Additionally, the receiver operating characteristic (ROC) curves were plotted to compare the prognostic value of the newly established model compared with the previous model. Furthermore, the correlation between the risk model and survival probability, immune characteristic, and efficacy of the chemotherapeutics were analyzed by the bioinformatics methods. Results: Six DE-EMTri-genes were ultimately selected to construct the prognostic model. The area under the curve (AUC) values for 1-, 2-, and 3- year were 0.773, 0.721, and 0.673, respectively. Stratified survival analysis suggested that the prognosis of the low-score group was superior to the high-score group. Moreover, the univariate and multivariate analysis indicated that risk score [hazard ratio (HR) 5.071, 95% CI 3.050, 8.432; HR 4.396, 95% CI 2.624, 7.366; p < 0.001] and stage (HR 2.500, 95% CI 1.721, 3.632; HR 2.111, 95% CI 1.443, 3.089; p < 0.001) served as an independent predictive factors in HCC. In addition, the macrophages, natural killer (NK) cells, and regulatory T (Treg) cells were significantly enriched in the high-risk group. Finally, the patients with the high-risk score might be more sensitive to cisplatin, doxorubicin, etoposide, gemcitabine, and mitomycin C. Conclusion: We established a reliable EMTri-genes-based prognostic signature, which may hold promise for the clinical prediction.

Characterisation and preliminary functional analysis of N-acetyltransferase 13 from Schistosoma japonicum.

BACKGROUND: N-acetyltransferase 13 (NAT13) is a probable catalytic component of the ARD1A-NARG1 complex possessing alpha (N-terminal) acetyltransferase activity. RESULTS: In this study, a full-length complementary DNA (cDNA) encoding Schistosoma japonicum NAT13 (SjNAT13) was isolated from schistosome cDNAs. The 621 bp open reading frame of SjNAT13 encodes a polypeptide of 206 amino acids. Real-time PCR analysis revealed SjNAT13 expression in all tested developmental stages. Transcript levels were highest in cercariae and 21-day-old worms, and higher in male adult worms than female adult worms. The rSjNAT13 protein induced high levels of anti-rSjNAT13 IgG antibodies. In two independent immunoprotection trials, rSjNAT13 induced 24.23% and 24.47% reductions in the numbers of eggs in liver. RNA interference (RNAi) results showed that small interfering RNA (siRNA) Sj-514 significantly reduced SjNAT13 transcript levels in worms and decreased egg production in vitro. CONCLUSIONS: Thus, rSjNAT13 might play an important role in the development and reproduction of schistosomes.

Angiogenesis-Related Immune Signatures Correlate With Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity in Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is one of the highly heterogeneous cancers that lacks an effective risk model for prognosis prediction. Therefore, we searched for angiogenesis-related immune genes that affected the prognosis of HCC to construct a risk model and studied the role of this model in HCC. Methods: In this study, we collected the transcriptome data of HCC from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database. Pearson correlation analysis was performed to identify the association between immune genes and angiogenesis-related genes. Consensus clustering was applied to divide patients into clusters A and B. Subsequently, we studied the differentially expressed angiogenesis-related immune genes (DEari-genes) that affected the prognosis of HCC. The most significant features were identified by least absolute shrinkage and selection operator (LASSO) regression, and a risk model was constructed. The reliability of the risk model was evaluated in the TCGA discovery cohort and the ICGC validation cohort. In addition, we compared the novel risk model to the previous models based on ROC analysis. ssGSEA analysis was used for function evaluation, and pRRophetic was utilized to predict the sensitivity of administering chemotherapeutic agents. Results: Cluster A patients had favorable survival rates. A total of 23 DEari-genes were correlated with the prognosis of HCC. A five-gene (including BIRC5, KITLG, PGF, SPP1, and SHC1) signature-based risk model was constructed. After regrouping the HCC patients by the median score, we could effectively discriminate between them based on the adverse survival outcome, the unique tumor immune microenvironment, and low chemosensitivity. Conclusion: The five-gene signature-based risk score established by ari-genes showed a promising clinical prediction value.