Construction and validation of a TP53-associated immune prognostic model for gastric cancer.

Increasing evidence indicates that TP53 mutation impacts the patients' prognosis by regulating the gastric cancer (GC) immunophenotype. An immune prognostic signature (IPS) was constructed based on TP53 status. The effects of the IPS on the immune microenvironment of GC were analyzed. We also constructed a nomogram integrating the IPS and other clinical factors. An IPS was constructed in the TCGA cohort and validated in the meta-GEO cohort. TP53 mutation resulted in the downregulation of the immune response in GC. Concretely, high-risk patients were characterized by increased monocyte, macrophage M0 and T cell follicular helper infiltration; increased stromal score, ESTIMATE score and immune score; higher TIM3 and BTLA expression; and decreased dendritic cell and T cell CD4 memory-activated infiltration and tumor purity. The nomogram also showed good predictive performance. These results suggest that the IPS is an effective prognostic indicator for GC patients, which might provide a theoretical foundation for immunotherapy.

Construction of a 13-microRNA-based signature and prognostic nomogram for predicting overall survival in patients with hepatocellular carcinoma.

AIM: Hepatocellular carcinoma (HCC) is a common malignancy associated with a poor prognosis due to difficulties in reliably estimating overall survival (OS). MicroRNAs (miRNAs) play critical roles in HCC initiation, progression, and metastasis and are highly correlated with patient prognosis. Thus, miRNA-based risk signatures and nomograms are urgently required for predicting OS in patients with HCC. METHODS: We constructed a 13-miRNA-based signature and prognostic nomogram using 408 HCC samples and 58 normal tissues with miRNA sequencing data and clinical data from 323 patients downloaded from The Cancer Genome Atlas. A total of 195 patients were assigned as the internal validation cohort for verification and testing. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis was applied to investigate pathway enrichment for the signature. RESULTS: We identified and validated a 13-miRNA risk signature highly associating with the OS of HCC patients. The signature showed good performances by calculating C-index, area under the curve, and calibration curves. After verification and testing using an internal validation cohort, the results yielded a miRNA-based signature and a prognostic nomogram with reliable predictive accuracy. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis indicated that various genes and multiple pathways were closely related to the mechanisms of HCC proliferation and metastasis. CONCLUSION: We successfully identified a 13-miRNA-based signature and prognostic nomogram that are capable of predicting OS in patients with HCC.

Identification of non-invasive biomarkers for chronic atrophic gastritis from serum exosomal microRNAs.

BACKGROUND: Serum exosomal microRNAs (miRNAs) have been suggested as novel biomarkers for various diseases, especially gastric cancer (GC). But circulating biomarkers for Chronic atrophic gastritis (CAG) which is defined as precancrerous lesions of GC remain largely elusive. To investigate serum exosomal miRNAs that are differently expressed in CAG patients and Chronic nonatrophic gastritis (CNAG) may be helpful for its diagnosis and therapy. METHODS: Patients were recruited according to the diagnosis and exclusioncriteria. RNA was extracted from serum exosomes of 30 CAG and 30 CNAG patients. The miRNA expression profiles were analyzed by next generation sequencing and were validated by qRT-PCR. Receiver operating characteristic (ROC) analysis has been used to evaluate the diagnostic value. RESULTS: 30 CAG patients and 30 CNAG patients were recruited in our study. sRNA-seq results showed that hsa-miR-3591-3p, - 122-3p, and - 122-5p of the top 10 miRNAs (hsa-miR-148a-3p, - 122-3p, - 486-3p, -451a, - 122-5p, - 3591-3p, - 486-5p, -151a-3p, -92a-3p, -320a) were significantly upregulated in exosomes from CAG patients versus those from CNAG patients, but hsa-miR-451a, -151a-3p, and -92a-3p were significantly downregulated. Furthermore, qRT-PCR analysis confirmed that hsa-miR-122-5p and hsa-miR-122-3p were significantly upregulated in CAG samples, but hsa-miR-122-3p hadnot a steable expression. ROC curves showed that the AUC for hsa-miR-122-5p was 0.67 (95% CI 0.52-0.82, SE 62%, SP 86%). A sum of the four miRNAs (panel 1, hsa-miR-122-5p, -451a, -151a-3p, and -92a-3p) did not significantly improve the diagnostic potential (AUC 0.63, 95% CI 0.47 to 0.78). Correlation analysis showed that the expression of hsa-miR-122-5p differed significantly between patients based on atrophic (Moderate atrophic vs. Absent, P value was 0.036.) and IM (compare moderate-severe, absent and mild P values were 0.001 and 0.014, respectively). However, there were no differences between groups based on age, gender, dysplasia, or chronic or active inflammation. CONCLUSION: These results suggested that hsa-miR-122-5p in serum exosomes might serve as a potential biomarker for CAG diagnosis. TRIAL REGISTRATION: Chinese Clinical Trial Registy ( ChiCTR-IOR-16008027 , Date of Registration:2016-03-01).

miR-196a-5p Correlates with Chronic Atrophic Gastritis Progression to Gastric Cancer and Induces Malignant Biological Behaviors of Gastric Cancer Cells by Targeting ACER2.

BACKGROUND: As the prognosis of early gastric cancer (EGC) is significantly better than that of advanced gastric cancer (AGC), the development of biomarkers to monitor the progression of chronic atrophic gastritis (CAG) to gastric cancer (GC) is essential. METHODS: Stomach tissue miRNA and mRNA sequences from patients with chronic non-atrophic gastritis (CNAG), CAG, precancerous lesions of gastric cancer (PLGC), and GC were analyzed. A publicly available GC-related miRNA microarray dataset was obtained from the Gene Expression Omnibus database. Spearman's correlation and differential gene analyses, and clinical validation were used to identify novel miRNAs correlating with CAG progression to GC. miRNA targets were predicted using weighted gene co-expression analysis and databases. A dual-luciferase reporter assay was performed to check for direct interaction between miR-196a-5p and ACER2. The CCK-8 and wound healing assays, and flow cytometry were performed to evaluate cell proliferation, migration, and apoptosis. RESULTS: miR-196a-5p was correlated with CAG progression to GC. Overexpression of miR-196a-5p promoted GC cell proliferation and migration and inhibited apoptosis, whereas suppression of miR-196a-5p exerted the opposite effect. Based on the prediction and luciferase assays, ACER2 was identified as the target of miR-196a-5p. ACER2 was downregulated in GC cell lines. Knockdown of ACER2 increased GC cell proliferation rates and migration ability and inhibited apoptosis, while ACER2 overexpression led to the opposite effect. CONCLUSIONS: miR-196a-5p correlated with CAG progression to GC and induced malignant biological behaviors of GC cells by targeting ACER2, providing a novel monitoring biomarker and target for GC prevention.

Current Evidence and Future Perspective of Accuracy of Artificial Intelligence Application for Early Gastric Cancer Diagnosis With Endoscopy: A Systematic and Meta-Analysis.

Background & Aims: Gastric cancer is the common malignancies from cancer worldwide. Endoscopy is currently the most effective method to detect early gastric cancer (EGC). However, endoscopy is not infallible and EGC can be missed during endoscopy. Artificial intelligence (AI)-assisted endoscopic diagnosis is a recent hot spot of research. We aimed to quantify the diagnostic value of AI-assisted endoscopy in diagnosing EGC. Method: The PubMed, MEDLINE, Embase and the Cochrane Library Databases were searched for articles on AI-assisted endoscopy application in EGC diagnosis. The pooled sensitivity, specificity, and area under the curve (AUC) were calculated, and the endoscopists' diagnostic value was evaluated for comparison. The subgroup was set according to endoscopy modality, and number of training images. A funnel plot was delineated to estimate the publication bias. Result: 16 studies were included in this study. We indicated that the application of AI in endoscopic detection of EGC achieved an AUC of 0.96 (95% CI, 0.94-0.97), a sensitivity of 86% (95% CI, 77-92%), and a specificity of 93% (95% CI, 89-96%). In AI-assisted EGC depth diagnosis, the AUC was 0.82(95% CI, 0.78-0.85), and the pooled sensitivity and specificity was 0.72(95% CI, 0.58-0.82) and 0.79(95% CI, 0.56-0.92). The funnel plot showed no publication bias. Conclusion: The AI applications for EGC diagnosis seemed to be more accurate than the endoscopists. AI assisted EGC diagnosis was more accurate than experts. More prospective studies are needed to make AI-aided EGC diagnosis universal in clinical practice.

Ferroptosis Patterns Correlate with Immune Microenvironment Characterization in Gastric Cancer.

OBJECTIVE: We aimed to build a ferroptosis-based classifier to characterize the molecular features of gastric cancers (GC) and investigate the relationship between different ferroptosis patterns and GC tumor microenvironment (TME). METHODS: Based on the genomic and clinical information from TCGA portal and GEO database, non-negative matrix factorization (NMF) was used to identify ferroptosis subtypes in GC patients. In order to estimate the ferroptosis levels, we established ferroptosis subtype score (FSS) to quantify ferroptosis patterns and ferroptosis potential index (FPI) by principal component analysis (PCA). The correlations of different ferroptosis patterns with TME cell-infiltrating characteristics (including immune cell infiltration, immune checkpoints expression levels, tumor mutational burden (TMB) and immunotherapy response) were systematically analyzed. RESULTS: Two ferroptosis subtypes, C1 (with lower FSS) and C2 (with higher FSS), were determined. C2 displayed a significantly lower FPI than C1. Besides, C2 was associated with diffuse subtype while C1 with intestinal subtype. As for TME characteristics, C2 was in accordance with the immune-excluded phenotype as it showed more active immune and stromal activities but lower TMB, less probability of immunotherapy response and poorer prognosis. C1 was linked to immune-inflamed phenotype as it had lower stromal activities but increased neoantigen load, enhanced response to immunotherapy and relatively better prognosis. CONCLUSION: The systematic assessment of ferroptosis patterns and ferroptosis levels presented in our study implied that ferroptosis serves as an important factor in the formation of TME, which may expand the understanding of TME and provide a novel perspective for the development of targeted immunotherapeutic strategies for GC patients.

Corrigendum: Current Evidence and Future Perspective of Accuracy of Artificial Intelligence Application for Early Gastric Cancer Diagnosis With Endoscopy: A Systematic and Meta-Analysis.

[This corrects the article DOI: 10.3389/fmed.2021.629080.].

CXCR4 is a Novel Biomarker Correlated With Malignant Transformation and Immune Infiltrates in Gastric Precancerous Lesions.

Background: As early gastric cancer (EGC) has a far better prognosis than advanced gastric cancer (GC), early diagnosis and treatment are essential. However, understanding the mechanism of the process from gastric precancerous lesion (GPL) becoming EGC has made little advances. Besides, biomarkers that can monitor the progression of GPL-to-GC are still much insufficient. Methods: Key gene modules associated with GPL progression to EGC were identified by integrating two GPL-related data sets, GSE55696 and GSE130823, using the WGCNA method. Combining with the TCGA-STAD cohort, hub genes were identified. Immunofluorescence was conducted to validate the expression. To explore the implication of hub genes in GPL malignant transformation, a correlation test was conducted to identify their co-expression genes, co-expression cytokines, and co-expression immune cells. Least absolute shrinkage and selection operator (LASSO) Cox regression was applied to shrink CXCR4-related predictors and construct a prognostic model. Functional enrichment was applied for exploring the potential mechanism. Results: The green module in GSE55696 and the yellow module in GSE130823 were regarded as key gene modules associated with GPL progression to EGC, and 219 intersection genes from them were mainly enriched in critical immune biological processes. Combining with the TCGA-STAD cohort, CXCR4 was identified as a novel biomarker correlated with the malignant transformation of GPL, the positive rate of which was increased with GPL progression according to immunofluorescence. CXCR4 co-expression genes were found mainly involved in regulation of actin. CXCR4 co-expression cytokines were enriched in regulation of chemotaxis, cell chemotaxis, mononuclear cell migration, leukocyte chemotaxis, etc. As for co-expression immune cells, the expression level of CXCR4 was positively correlated with the abundance of macrophages but negatively correlated with that of effector memory T cells and NKT cells during GPL malignant transformation. In addition, the CXCR4-related prognostic model was able to predict the prognosis of GC and serve as an independent predictor for overall survival (OS). Conclusions: CXCR4 was a novel biomarker correlated with malignant transformation of GPL and played a vital role in the control of tumor immunity. CXCR4 is possible to serve as a therapeutic target for malignant transformation of GPL.

Construction and Validation of a Ferroptosis-Related Prognostic Model for Gastric Cancer.

BACKGROUND: Gastric cancer (GC), an extremely aggressive tumor with a very different prognosis, is the third leading cause of cancer-related mortality. We aimed to construct a ferroptosis-related prognostic model that can be distinguished prognostically. METHODS: The gene expression and the clinical data of GC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO). The ferroptosis-related genes were obtained from the FerrDb. Using the "limma" R package and univariate Cox analysis, ferroptosis-related genes with differential expression and prognostic value were identified in the TCGA cohort. Last absolute shrinkage and selection operator (LASSO) Cox regression was applied to shrink ferroptosis-related predictors and construct a prognostic model. Functional enrichment, ESTIMATE algorithm, and single-sample gene set enrichment analysis (ssGSEA) were applied for exploring the potential mechanism. GC patients from the GEO cohort were used for validation. RESULTS: An 8-gene prognostic model was constructed and stratified GC patients from TCGA and meta-GEO cohort into high-risk groups or low-risk groups. GC patients in high-risk groups have significantly poorer OS compared with those in low-risk groups. The risk score was identified as an independent predictor for OS. Functional analysis revealed that the risk score was mainly associated with the biological function of extracellular matrix (ECM) organization and tumor immunity. CONCLUSION: In conclusion, the ferroptosis-related model can be utilized for the clinical prognostic prediction in GC.

Evaluation of the protective effects of Chinese herbs against biomolecule damage induced by peroxynitrite.

This work evaluates the protective effects of Chinese herbs against ONOO(-)-induced biomolecule damage. Thirty-two Chinese traditional herbs were preliminarily screened for their ONOO(-)-scavenging activity by the fluorometric method. The potency of scavenging activity was in the following order: Apis cerana Fabricius (Propolis) > Rosmarinus officinalis L (Rosemary) > Pseudolarix amabilis (Nelson) Rehd. (Pine Bark PE) > Echinacea Moenck. (Echinacea); the remaining twenty-eight herbs performed unsatisfactorily for their scavenging activity. The four extracts with high ONOO(-) scavenging activity were selected for further characterization of their inhibiting effects on DNA single breaks, tyrosine nitration and LDL oxidation. A further study of the origin of this scavenging activity on the major active components showed cichoric acid and rosemary acid to both have strong ability to scavenge ONOO(-). These scavengers might be developed as therapeutic drugs for preventing ONOO(-)-involved diseases.

Identification of hub genes correlated with the pathogenesis and prognosis of gastric cancer via bioinformatics methods.

BACKGROUND: Gastric cancer (GC) is the fourth most common cause of cancer-related deaths in the world and 5-year overall survival (OS) rate is less than 10%. So, it is urgent to identified novel diagnostic and prognostic biomarkers. METHODS: Twelve GEO (gene expression omnibus) datasets were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between GC and normal tissues were screened and integrated using limma and RobustRankAggreg (RRA) packages in R software. Protein-protein interaction (PPI) network, GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses for DEGs were conducted via STRING and DAVID, respectively. Moreover, Cox regression model was used to construct a gene prognosis signature. RESULTS: Ten genes (COL1A1, CXCL8, COL3A1, SPP1, COL1A2, TIMP1, CXCL1, BGN, MMP3 and SERPINE1) were identified and might be highly related to GC. Further analysis showed high expression of CXCL8, COL3A1, CXCL1, MMP3 and SERPINE1, were significantly associated with late stage of GC. Lastly, we build a seven-gene prognosis signature (CYP19A1, SERPINE1, CGB5, CALCR, ASGR2, CYTL1 and ABCB5), which can give a good prediction of OS. CONCLUSIONS: Our article screened out key genes highly associating with GC's developments and prognosis, and it is useful for researcher to further understand GC's molecular basis and direct the synthesis medicine of GC.

Identification of a 14-lncRNA Signature and Construction of a Prognostic Nomogram Predicting Overall Survival of Gastric Cancer.

Increasing evidence suggests that aberrant long noncoding (lnc) RNA expression plays a vital role in gastric cancer (GC) initiation and progression. Thus, we aimed to develop a lncRNA-based risk signature and nomogram to predict overall survival (OS) for patients with GC. Our primary cohort was composed of 341 patients with clinical and lncRNA expression data in The Cancer Genome Atlas stomach adenocarcinoma (TCGA STAD), the internal validation cohort was composed of 172 randomly assigned patients, and the external validation cohort was composed of 300 patients from GSE62254 dataset. A risk signature and nomogram were developed for the primary cohort and validated on the validation cohorts. Furthermore, gene set enrichment analysis (GSEA) was used to investigate the pathway enrichment for the risk signature. The expression patterns of several lncRNAs were also investigated in clinical samples from 10 GC patients. We identified and validated a 14-lncRNA signature highly associated with the OS of patients with GC, which performed well on evaluation with C-index, area under the curve, and calibration curves. In addition, univariate and multivariate Cox regression analyses indicated that the lncRNA signature was an independent predictive factor for GC patients. Therefore, a nomogram incorporating lncRNA signature and clinical factors was constructed to predict OS for patients with GC in primary cohort that suggested powerful predictive values for survival in the TCGA cohort and the other two validation cohorts. In addition, GSEA indicated that the identified lncRNAs may regulate the autophagy pathway, affecting tumorigenesis and prognosis of patients with GC. Experimental validation demonstrated that the expression of lncRNAs showed the same trend both in our clinical samples and STAD dataset. These results suggest that both risk signature and nomogram were effective prognostic indicators for patients with GC.

A novel ceRNA axis involves in regulating immune infiltrates and macrophage polarization in gastric cancer.

BACKGROUND: Increasing evidence suggests that the lncRNA-miRNA-mRNA regulatory network is highly correlated with gastric cancer (GC) development. However, a prognosis-associated lncRNA-miRNA-mRNA network remains to be identified in GC. METHODS: Differentially expressed genes (DEGs) were screened by integrating 6 microarray datasets using the RRA method. Hub genes were identified by analysing their degrees in a PPI (protein-protein interaction) network. Upstream miRNAs and lncRNAs of hub genes were predicted by miRTarBase and miRNet, respectively. Key genes, miRNAs and lncRNAs were identified by evaluating their expression and prognosis in GEPIA and Kaplan-Meier plotter, respectively. A key lncRNA-miRNA-mRNA network was constructed in Cytoscape, and the correlations were analysed in the ENCORI database. We also evaluated the mRNA expression of ceRNA axes in the TIMER and Oncomine databases and their correlation with prognosis in GC patients with different clinical features using Kaplan-Meier plotter. In addition, correlations between mRNA and immune infiltrating cells in GC were investigated by the TIMER database. Finally, several experiments were conducted to verify our analyses. RESULTS: Forty-two upregulated and 86 downregulated DEGs were obtained from the "RRA" integrated analysis. Eight of the 20 hub genes were identified as key genes by analysing their expression and prognosis. Seventeen miRNAs were predicted to target key genes, and low expression of 4 miRNAs suggested poor outcome in GC. Furthermore, 155 lncRNAs were predicted to target 4 key miRNAs, and only 5 lncRNAs were highly expressed, suggesting poor outcomes in patients with GC. Then, the H19-miR-29a-3p-COL1A2 axis was constructed by correlation analysis. In addition, COL1A2 was positively correlated with lymphatic metastasis, immune infiltrating cell levels, markers of monocytes, tumour-associated macrophages (TAMs), and M2 macrophages but not M1 macrophages in GC. The experimental results revealed that the H19-miR-29a-3p-COL1A2 axis may promote macrophage polarization from M1 to M2 in GC. CONCLUSIONS: A novel lncRNA-miRNA-mRNA axis was identified and may be involved in regulating immune cell infiltration and macrophage polarization, which may provide new treatment strategies for GC.

Optimal timing of thymectomy in nonthymomatous myasthenia gravis patients in China: A prospective study.

INTRODUCTION: While thymectomy is a recommended therapy for patients with Myasthenia Gravis (MG), there is insufficient evidence of its benefits over other therapies in patients in China, specifically, or of the most optimal timing for the procedure. Thus, there remains a clinical need for the investigation of these questions. Therefore, it is important to compare the clinical efficacy of thymectomy plus oral prednisone, an immunosuppressant protocol with prednisone, or immunosuppressants alone. CONCLUSION: We propose here to prospectively assess 822 cases of MG and 1886 medical records from individuals hospitalized at the First Affiliated Hospital of Guangzhou University of Chinese Medicine and follow them for 3 years. Inclusion criteria will include the following: a Myasthenia Gravis Foundation of America (MGFA) clinical classification between I and IV while on optimal anticholinesterase therapy with or without oral prednisone or immunosuppressive therapy, an MG history of longer than 3 years, being 18 to 60 years of age, and positive testing for serum acetylcholine receptor antibodies (AchR-Ab). Both thymomatous-naïve and non-naïve participants will be included. The primary outcomes will be: mortality, frequency of myasthenic crises, MGFA classification, and changes to the required dose of prednisone and immunosuppressants. Based on these outcomes, we will evaluate the efficacy of thymectomy as well as oral drugs in managing patients with nonthymomatous MG. As of September 2017, this study has been approved by the ethics committee of the First Affiliated Hospital of Guangzhou University of Chinese Medicine and the Registration number is ChiCTR1800017564(Version1.0, September 8,2017).