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Xiaotao Jiang,1,2 Fan Liu,2,3 Peng Liu,1,2 Yanhua Yan,1,2 Shaoyang Lan,1 Kunhai Zhuang,1,4 Yufeng Liu,5 Kailin Jiang,1,2 Yuancheng Huang,1,2 Kechao Nie,1,2 Zhihua Zheng,1,2 Jinglin Pan,6 Junhui Zheng,1,2 Fengbin Liu,1,4 Shijie Xu,5 Peiwu Li,1 Yi Wen1 1Department of Gastroenterology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, People’s Republic of China; 2First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, People’s Republic of China; 3Zhaoqing Hospital of Chinese Medicine Affiliated to Southern Medical University, Zhaoqing, Guangdong, People’s Republic of China; 4Baiyun Hospital of the First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, People’s Republic of China; 5Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, People’s Republic of China; 6Department of Gastroenterology, Hainan Provincial Hospital of Traditional Chinese Medicine, Haikou, Hainan, People’s Republic of ChinaCorrespondence: Peiwu Li; Yi Wen Email doctorlipw2@163.com; 421491922@qq.comObjective: 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.Keywords: ferroptosis, gastric cancer, immune cell infiltration, tumor microenvironment, immunotherapy

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.

Objectives: The purpose of this study was to investigate the role of 13 m5C-related regulators in colon adenocarcinoma (COAD) and determine their prognostic value.Main Methods: Gene expression and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) datasets. The expression of m5C-related regulators were analyzed with clinicopathological characteristics and alterations within m5C-related regulators. Subsequently, different subtypes of patients with COAD were identified. Then, the prognostic value of m5C-related regulators in COAD were confirmed via univariate Cox regression and least absolute shrinkage and selection operator (LASSO) Cox regression analyses. The prognostic value of risk scores was evaluated using the Kaplan-Meier method, receiver operating characteristic (ROC) curves, and univariate and multivariate regression analyses. Additionally, Gene Set Enrichment Analysisc (GSEA), Kyoto Encyclopedia of Genes and Genomes c (KEGG) pathways, and Gene Ontologyc (GO) analysis were performed for biological functional analysis.Results: m5C-related regulators were found to be differentially expressed in COAD with different clinicopathological features. We observed a high alteration frequency in these genes, which were significantly correlated with their mRNA expression levels. Two clusters with different prognostic features were identified. Based on two independent prognostic m5C-related regulators (NSUN6 and ALYREF), a risk signature with good predictive significance was constructed. Univariate and multivariate Cox regression analyses suggested that the risk score was an independent prognostic factor. Biological processes and pathways associated with cancer, immune response, and RNA processing were identified.Conclusion: We revealed the genetic signatures and prognostic values of m5C-related regulators in COAD. Together, this has improved our understanding of m5C RNA modification and provided novel insights to identify predictive biomarkers and develop molecular targeted therapy for COAD.

ObjectivesThe purpose of this study was to investigate the role of m6A-related lncRNAs in gastric adenocarcinoma (STAD) and to determine their prognostic value.MethodsGene expression and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) database. Correlation analysis and univariate Cox regression analysis were conducted to identify m6A-related prognostic lncRNAs. Subsequently, different clusters of patients with STAD were identified via consensus clustering analysis, and a prognostic signature was established by least absolute shrinkage and selection operator (LASSO) Cox regression analyses. The clinicopathological characteristics, tumor microenvironment (TME), immune checkpoint genes (ICGs) expression, and the response to immune checkpoint inhibitors (ICIs) in different clusters and subgroups were explored. The prognostic value of the prognostic signature was evaluated using the Kaplan-Meier method, receiver operating characteristic curves, and univariate and multivariate regression analyses. Additionally, Gene Set Enrichment Analysis (GSEA), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and Gene Ontology (GO) analysis were performed for biological functional analysis.ResultsTwo clusters based on 19 m6A-related lncRNAs were identified, and a prognostic signature comprising 14 m6A-related lncRNAs was constructed, which had significant value in predicting the OS of patients with STAD, clinicopathological characteristics, TME, ICGs expression, and the response to ICIs. Biological processes and pathways associated with cancer and immune response were identified.ConclusionsWe revealed the role and prognostic value of m6A-related lncRNAs in STAD. Together, our finding refreshed the understanding of m6A-related lncRNAs and provided novel insights to identify predictive biomarkers and immunotherapy targets for STAD.

Purpose: The purpose of this study was to investigate the role of m6A-related lncRNAs in colon adenocarcinoma (COAD) and determine their prognostic value.Material and methods: Gene expression and clinicopathological data were obtained from The Cancer Genome Atlas database. Correlation and univariate Cox regression analysis were conducted to identify m6A-related prognostic lncRNAs. A prognostic signature was established via least absolute shrinkage and selection operator (LASSO) Cox regression analyses. The prognostic value of risk scores was evaluated using the Kaplan-Meier method, receiver operating characteristic curves, and univariate and multivariate regression analyses. Whether the prognostic model could serve as a prognostic indicator for overall survival (OS) in subgroups of patients with different clinical characteristics were explored. Next, We established a competing endogenous RNA network. Gene Set Enrichment Analysis, Kyoto Encyclopedia of Genes and Genomes pathway, and Gene Ontology analysis were performed for biological functional analysis.Results: 36 lncRNAs that were highly correlated with OS of patients were identified. A prognostic signature comprising 11 m6A-related lncRNAs was constructed, which had significant value in predicting the OS of patients . Univariate and Multivariate Cox regression analyses suggested that the risk score was an independent prognostic factor. This m6A-related lncRNA prognostic model could serve as a prognostic indicator for OS in subgroups of patients with different clinical characteristics. Biological processes and pathways associated with cancer were identified.Conclusion: We revealed the role and prognostic value of m6A-related lncRNAs in COAD. Our finding refreshed the understanding of m6A-related lncRNAs and provided novel insights to identify predictive biomarkers and develop targeted therapy for COAD.

Background: With the coming of immunotherapy era, immunotherapy is gradually playing a vital role in the treatment of gastric cancer (GC). However, immune microenvironment in gastric precancerous lesions (GPL) and early gastric cancer (EGC) still remain largely unknown. Methods: From the Gene Expression Omnibus (GEO), data of three GPL-related gene expression profiles (GSE55696, GSE87666 and GSE130823) and three GC data sets with clinical information (GSE66229, GSE15459 and GSE34942) were downloaded. Three GC data were consolidated as a GC meta-GEO cohort. RNA sequencing data of 375 stomach adenocarcinoma (STAD) samples with clinical information from The Cancer Genome Atlas (TCGA) and 175 stomach normal controls (NC) from Genotype-Tissue Expression (GTEx) datasets were obtained from the UCSC Xena browser, which were merged as a STAD TCGA-GTEx cohort. The abundance of immune cells in above datasets were estimated using Immune Cell Abundance Identifier (ImmuCellAI) algorithm. Firstly, key immune cells associated with GPL progression to EGC were identified using one‐way analysis of variance (ANOVA) test as well as Spearman’s correlation test in two GPL and EGC related datasets (GSE55696 and GSE87666). Then, weighted gene co-expression analysis (WGCNA) and pathway enrichment were adopted to identify hub gene co-expression network. Candidate hub genes were identified based on network parameters. Combining expression comparison and prognosis analysis in STAD TCGA-GTEx and GC meta-GEO cohort, Genes with significant difference between GC and NC and prognostic significance were identified as real hub genes. Correlation between real hub genes and key immune cells was evaluated using Pearson’s correlation test. The pattern of key immune cells infiltration and hub genes expression as well as their correlation during GPL progression to EGC were validated in an independent cohort GSE130823. The correlation was also verified in the GC datasets (STAD TCGA-GTEx and GC meta-GEO cohort).Results: Combining with GSE55696 and GSE87666 cohorts, NKT cell was found gradually decreased with GPL progression and negatively correlated with tumorigenesis significantly. It was identified as the key immune cell associated with GPL progression to EGC based on one-way ANOVA test and Spearman’s correlation test. Further verification indicated that it was significantly downregulated in GC in meta-GEO cohort and STAD TCGA-GTEx cohort. According to the results of WGCNA and KEGG pathway enrichment, green modules in GSE55696 and GSE87666 cohorts were considered as hub modules as they were negatively associated with NKT cell infiltration at a significant level and their overlapping genes were significantly enriched in immune-related pathways. In further screening, CXCR4 was found to be significantly upregulated in GC and had a poor prognosis, which was determined as the real hub gene. CXCR4 expression was found increased with GPL progression, positively correlated with tumorigenesis and negatively correlated with NKT cell infiltration significantly. The pattern of NKT cell infiltration and CXCR4 expression as well as their relationship stay consistent in the independent GPL cohort GSE130823. The negative correlation of CXCR4 with NKT cell infiltration was also confirmed in GC datasets (GC meta-GEO cohort and STAD TCGA-GTEx cohort).Conclusion: CXCR4 and NKT cell are possible to serve as biomarkers in monitoring GPL progression to EGC. Besides, CXCR4 may be involved in regulating NKT cell infiltration during GPL progression to EGC, which may provide a new immunotherapeutic target.

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.

Background: The transformation of chronic inflammation into adenocarcinoma in stomach lacks specific molecular markers to monitor early cancer development and effective drugs for early intervention. In this study, we identified two key genes, LYZ (encoding lysozyme) and SST (encoding somatostatin). Methods: LYZ and SST was identified by integrating high-throughput sequencing data derived from patients related to gastritis-cancer and microarray data of The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Their expression was verified in human specimens and rat model of gastritis-cancer. The clinicopathological significance study for predicting the progression of chronic gastritis to cancer transition and cancer prognosis was using ROC curve, survival and correlation analysis. Their expression difference was tested in patients those received effective interventions, based on a multicenter randomized control clinical trial for precancerous disease in stomach. Findings: LYZ and SST were consistently downregulated in the process of chronic inflammation into adenocarcinoma in stomach. The ROC curves of these genes had a great value in predicting precancerous disease and gastric cancer independently and in combination. Their expression levels were correlated with gastritis and intestinal metaplasia staging, and would increase after effective intervention in precancerous patients. Interpretation: We identified LYZ and SST as key “hub” genes for chronic gastritis to cancer transition, promising biomarkers of significant clinical predictive value, and potential targets for inhibiting gastric cancer development. Trial Registration: ChiCTR-IOR-16008027 Funding Statement: National Natural Science Foundation of China (No.81703931, 81973819) Natural science foundation of Guangdong province in 2017 (2017A030310121) Natural science foundation of Guangdong province in 2019 (2019A1515011145) Breakthrough Project of TCM Dominant Diseases with Special Funds for Strengthening Traditional Chinese Medicine in 2015 (No.19), Guangdong Administration of Traditional Chinese Medicine. Major Projects of First-Class Disciplines in Guangzhou University of TCM in 2018 (A1-AFD018181A27). Major Research Projects of Guangzhou University in TCM in 2019 (A1-2606-19-110-007). Innovative Research Team Project of Innovation Hospital in the First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine in 2017 (2017TD05). Youth Scientific Research Talents Training Program of Innovation Hospital in the First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine in 2015 (2015QN09). The Second Batch of Clinical Research Program of Innovation Hospital Phase II project in the First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine in 2019 (2019IIT19). Declaration of Interests: The authors declare no conflicts. Ethics Approval Statement: The ethics committee of the first affiliated hospital of Guangzhou University of Traditional Chinese Medicine approved this study (approval number ZYYECK [2015]024-ND-01, ZYYECK [2017]023-XZ-01, ZYYECK [2019]015). The ethics committee of the first affiliated hospital of Guangzhou University of Traditional Chinese Medicine approved this study (approval number ZYYECK [2015]024-ND-01). The rat study design and protocol were approved by the animal ethics committee of Beijing University of Chinese Medicine, China (No. BUCM-4-2018060403-2007).

Background Ankylosing spondylitis (AS) is a chronic inflammatory rheumatic disease. The dysregulated immune system plays an important role in the pathogenesis of AS. Myeloid-derived suppressor cells (MDSCs) play a key immunoregulatory role in autoimmune arthritis. The aim of this study was to clarify the underlying immunoregulatory mechanism of MDSCs in patients with AS. Methods Flow cytometry was used to analyze the phenotype of MDSCs among peripheral blood mononuclear cells (PBMCs) from 46 patients with AS and 46 healthy control subjects. The correlation between MDSC frequency and the disease index of patients with AS was evaluated. A T cell proliferation experiment was used to evaluate the immunosuppressive function of MDSCs. Results Polymorphonuclear (PMN) and monocytic (M)-MDSCs were significantly elevated in the PBMCs of patients with AS, when compared with levels in healthy controls. Additionally, M-MDSC levels correlated positively with the clinical index of AS, including the Bath ankylosing spondylitis disease activity index (BASDAI) score, erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) levels. M-MDSCs derived from patients with AS suppressed T cell responses, and this effect was dependent on the induction of arginase-I. Furthermore, AS-derived M-MDSCs showed high levels of phosphorylated STAT3. Stattic, a STAT3-specific inhibitor, and STAT3-targeted siRNA abrogated the immunosuppressive function of M-MDSCs. Inhibition of STAT3 signaling also resulted in decreased arginase-I activity. Conclusions STAT3/arginase-I signaling plays an important role in both the expansion and activation of M-MDSCs in patients with AS. This information may be beneficial in developing novel therapeutic strategies for preventing AS. Electronic supplementary material The online version of this article (10.1186/s13075-018-1654-4) contains supplementary material, which is available to authorized users.