Explore the active ingredients and potential mechanisms of JianPi QingRe HuaYu Methods in the treatment of gastric inflammation-cancer transformation by network pharmacology and experimental validation.

BACKGROUND: JianPi QingRe HuaYu Methods (JQH) have been long used to treat chronic atrophic gastritis (CAG) and precancerous lesions of gastric cancer (PLGC). However, whether JQH can inhibit the transformation of gastritis to gastric cancer (GC) remains unclear. METHODS: Herein, we first retrieved the active ingredients and targets of JQH from the TCMSP database and the targets related to the gastric inflammation-cancer transformation from public databases. Differentially expressed genes (DEGs) related to gastric inflammation-cancer transformation were identified from the Gene Expression Omnibus (GEO) database. Then, we obtained the potential therapeutic targets of JQH in treating gastric inflammation-cancer transformation by intersecting drugs and disease targets. The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) analyses of the potential therapeutic targets were conducted using R software. Next, we conducted molecular docking and in vitro experiments to validate our results. RESULTS: We obtained 214 potential therapeutic targets of JQH by intersecting drugs and disease targets. We found that the potential mechanisms of JQH in treating gastric inflammation-cancer transformation might be related to JAK-STAT, Wnt, p53 and VEGF signaling pathways. The molecular docking indicated that quercetin, as the main active ingredient of JQH, might inhibit gastric inflammation-cancer transformation by binding with specific receptors. Our experimental results showed that quercetin inhibited cells proliferation (P < 0.001), promoted cell apoptosis (P < 0.001), reduced the secretion of pro-inflammatory cytokines (P < 0.001) and promoted the secretion of anti-inflammatory cytokines (P < 0.001) in MNNG-induced GES-1 cells. Furthermore, quercetin inhibited cells proliferation (P < 0.001) and reduced mRNA and protein level of markers of PLGC (P < 0.001) in CDCA-induced GES-1 cells. CONCLUSION: These results provide the material basis and regulatory mechanisms of JQH in treating gastric inflammation-cancer transformation.

AGAP2-AS1 promotes the assembly of m6A methyltransferases and activation of the IL6/STAT3 pathway by binding with WTAP in the carcinogenesis of gastric cancer.

Owing to the lack of biomarkers for early diagnosis, gastric cancer (GC) is often associated with a poor prognosis. Thus, there is an urgent need to identify early molecular targets in GC. Dysregulated long noncoding RNAs (lncRNAs) have been evaluated by integrated bioinformatics analysis; and we investigate their specific role and potential mechanism via N6-methyladenosine (m6A) methylation modification in the carcinogenesis and progression of GC. In this study, we report upregulation of lncRNA AGAP2-AS1, activated by a gain of H3K4Me3, in GC tissues and cells. AGAP2-AS1 was linked to adverse prognosis in patients with GC. Functionally, AGAP2-AS1 knockdown inhibited cell proliferation and migration of GC cells. Mechanistically, AGAP2-AS1 bound WT1-associated protein (WTAP) to promote the formation of the WTAP/methyltransferase-like 3 (METTL3)/METTL14 m6A methyltransferase complex. AGAP2-AS1 stabilized signal transducer and activator of transcription 3 (STAT3) mRNA in an m6A-dependent manner and, thus, activated the interleukin 6 (IL6)/STAT3 pathway. Importantly, activation of the AGAP2-AS1/WTAP/STAT3 pathways promoted cell proliferation and migration in GC. Collectively, the present findings revealed a novel regulatory relationship between lncRNA and m6A modification. Furthermore, targeting the AGAP2-AS1/WTAP/STAT3 axis may be a promising strategy for the inhibition of inflammation-mediated carcinogenesis and progression in GC.

Mapping the intellectual structure and landscape of nano-drug delivery systems in colorectal cancer.

Background: Colorectal cancer (CRC) is a prevalent malignancy affecting the digestive tract, and its incidence has been steadily rising over the years. Surgery remains the primary treatment modality for advanced colorectal cancer, complemented by chemotherapy. The development of drug resistance to chemotherapy is a significant contributor to treatment failure in colorectal cancer. Nanodrug delivery systems (NDDS) can significantly improve the delivery and efficacy of antitumor drugs in multiple ways. However, there is a lack of visualization of NDDS research structures and research hotspots in the field of colorectal cancer, and the elaboration of potential research areas remains to be discovered. Objective: To comprehensively explore the current research status and development trend of NDDS in CRC research. Methods: Bibliometric analysis of articles and reviews on NDDS for CRC published between 2002 and 2022 using tools including CiteSpace, VOSviewer, R-bibliometrix, and Microsoft Excel was performed. Results: A total of 1866 publications authored by 9,870 individuals affiliated with 6,126 institutions across 293 countries/regions were included in the analysis. These publications appeared in 456 journals. Abnous Khalil has the highest number of publications in this field. The most published journals are the International Journal of Nanomedicine, International Journal of Pharmaceutics, and Biomaterials. Notably, the Journal of Controlled Release has the highest citation count and the third-highest H-index. Thematic analysis identified "inflammatory bowel disease"," "oral drug delivery," and "ulcerative colitis" as areas requiring further development. Keyword analysis revealed that "ulcerative colitis," "exosomes," and "as1411"have emerged as keywords within the last 2 years. These emerging keywords may become the focal points of future research. Conclusion: Our findings reveal the current research landscape and intellectual structure of NDDS in CRC research which helps researchers understand the research trends and hot spots in this field.

Identification of berberine as a potential therapeutic strategy for kidney clear cell carcinoma and COVID-19 based on analysis of large-scale datasets.

Background: Regarding the global coronavirus disease 2019 (COVID)-19 pandemic, kidney clear cell carcinoma (KIRC) has acquired a higher infection probability and may induce fatal complications and death following COVID-19 infection. However, effective treatment strategies remain unavailable. Berberine exhibits significant antiviral and antitumour effects. Thus, this study aimed to provide a promising and reliable therapeutic strategy for clinical decision-making by exploring the therapeutic mechanism of berberine against KIRC/COVID-19. Methods: Based on large-scale data analysis, the target genes, clinical risk, and immune and pharmacological mechanisms of berberine against KIRC/COVID-19 were systematically investigated. Results: In total, 1,038 and 12,992 differentially expressed genes (DEGs) of COVID-19 and KIRC, respectively, were verified from Gene Expression Omnibus and The Cancer Genome Atlas databases, respectively, and 489 berberine target genes were obtained from official websites. After intersecting, 26 genes were considered potential berberine therapeutic targets for KIRC/COVID-19. Berberine mechanism of action against KIRC/COVID-19 was revealed by protein-protein interaction, gene ontology, and Kyoto Encyclopedia of Genes and Genomes with terms including protein interaction, cell proliferation, viral carcinogenesis, and the PI3K/Akt signalling pathway. In COVID-19 patients, ACOX1, LRRK2, MMP8, SLC1A3, CPT1A, H2AC11, H4C8, and SLC1A3 were closely related to disease severity, and the general survival of KIRC patients was closely related to ACOX1, APP, CPT1A, PLK1, and TYMS. Additionally, the risk signature accurately and sensitively depicted the overall survival and patient survival status for KIRC. Numerous neutrophils were enriched in the immune system of COVID-19 patients, and the lives of KIRC patients were endangered due to significant immune cell infiltration. Molecular docking studies indicated that berberine binds strongly to target proteins. Conclusion: This study demonstrated berberine as a potential treatment option in pharmacological, immunological, and clinical practice. Moreover, its therapeutic effects may provide potential and reliable treatment options for patients with KIRC/COVID-19.

Pan-Cancer Analysis of the Characteristics of LY96 in Prognosis and Immunotherapy Across Human Cancer.

Lymphocyte antigen 96 (LY96) is implicated in tumorigenesis by modulating host immunity. However, an integrated pan-cancer analysis of LY96 in prognosis and immunotherapy across human cancers is still lacking. Therefore, we analyzed the LY96 expression and its prognostic role in tumors by multiple databases. We also investigated the correlation between LY96 and copy number, DNA methylation, somatic mutation, microsatellite instability (MSI), tumor mutation burden (TMB), tumor microenvironment (TME), and immune cell infiltration across human cancers. In addition, the biological processes related to LY96 across various tumors and the correlation between LY96 and 50% inhibitive concentration (IC50) of various drugs were investigated. We found that LY96 was differently expressed between tumor and normal tissues and was significantly upregulated in most types of cancers. LY96 was gradually upregulated from stages I to IV in several cancers. Moreover, we found LY96 may play a prognostic role in most cancers, and patients with high or low LY96 expression often show different clinical outcomes. LY96 was also associated with copy number, DNA methylation, somatic mutation, MSI, TMB, TME characteristics, and immune cell infiltration in cancers. LY96 may also regulate classic tumor-associated pathways in several cancers and is related to drug resistance. This article may help to elucidate the role of LY96 in tumorigenesis, which may promote the development of immunotherapy and targeted therapy in cancers.

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.

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.

Development and Validation of a TNF Family-Based Signature for Predicting Prognosis, Tumor Immune Characteristics, and Immunotherapy Response in Colorectal Cancer Patients.

In this study, a comprehensive analysis of TNF family members in colorectal cancer (CRC) was conducted and a TNF family-based signature (TFS) was generated to predict prognosis and immunotherapy response. Using the expression data of 516 CRC patients from The Cancer Genome Atlas (TCGA) database, TNF family members were screened to construct a TFS by using the univariate Cox proportional hazards regression and the least absolute shrinkage and selection operator- (LASSO-) Cox proportional hazards regression method. The TFS was then validated in a meta-Gene Expression Omnibus (GEO) cohort (n = 1162) from the GEO database. Additionally, the tumor immune characteristics and predicted responses to immune checkpoint blockade in TFS-based risk subgroups were analyzed. Eight genes (TNFRSF11A, TNFRSF10C, TNFRSF10B, TNFSF11, TNFRSF25, TNFRSF19, LTBR, and NGFR) were used to construct the TFS. Compared to the high-risk patients, the low-risk patients had better overall survival, which was verified by the GEO data. In addition, a high TFS risk score was associated with high infiltration of regulatory T cells (Tregs), nonactivated macrophages (M0), natural killer cells, immune escape phenotypes, poor immunotherapy response, and tumorigenic and metastasis-related pathways. Conversely, a low TFS risk score was related to high infiltration of resting CD4 memory T cells and resting dendritic cells, few immune escape phenotypes, and high sensitivity to immunotherapy. Thus, the eight gene-based TFS is a promising index to predict the prognosis, immune characteristics, and immunotherapy response in CRC, and our results also provide new understanding of the role of the TNF family members in the prognosis and treatment of CRC.

TBX5-AS1, an enhancer RNA, is a potential novel prognostic biomarker for lung adenocarcinoma.

BACKGROUND: Enhancer RNAs (eRNAs) are demonstrated to be closely associated with tumourigenesis and cancer progression. However, the role of eRNAs in lung adenocarcinoma (LUAD) remains largely unclear. Thus, a comprehensive analysis was constructed to identify the key eRNAs, and to explore the clinical utility of the identified eRNAs in LUAD. METHODS: First, LUAD expression profile data from the Cancer Genome Atlas (TCGA) dataset and eRNA-relevant information were integrated for Kaplan-Meier survival analysis and Spearman's correlation analysis to filtered the key candidate eRNAs that was associated with survival rate and their target genes in LUAD. Then, the key eRNA was selected for subsequent clinical correlation analysis. KEGG pathway enrichment analyses were undertaken to explore the potential signaling pathways of the key eRNA. Data from the human protein atlas (HPA) database were used to validate the outcomes and the quantitative real time-polymerase chain reaction (qRT-PCR) analysis was conducted to measure eRNA expression levels in tumor tissues and paired normal adjacent tissues from LUAD patients. Finally, the eRNAs were validated in pan-cancer. RESULTS: As a result, TBX5-AS1 was identified as the key eRNA, which has T-box transcription factor 5 (TBX5) as its regulatory target. KEGG analysis indicated that TBX5-AS1 may exert a vital role via the PI3K/AKT pathway, Ras signaling pathway, etc. Additionally, the qRT-PCR results and the HPA database indicated that TBX5-AS1 and TBX5 were significantly downregulated in tumour samples compared to matched-adjacent pairs. The pan-cancer validation results showed that TBX5-AS1 was associated with survival in four tumors, namely, adrenocortical carcinoma (ACC), LUAD, lung squamous cell carcinoma (LUSC), and uterine corpus endometrial carcinoma (UCEC). Correlations were found between TBX5-AS1 and its target gene, TBX5, in 26 tumor types. CONCLUSION: Collectively, our results indicated that TBX5-AS1 may be a potential prognostic biomarker for LUAD patients and promote the targeted therapy of LUAD.

High Endothelin Receptor Type A Expression as an Independent Prognostic Biomarker and Correlated with Immune Infiltrates in Stomach Adenocarcinoma.

BACKGROUND: Stomach adenocarcinoma (STAD) is the most common gastrointestinal cancer and is associated with high mortality worldwide. Endothelin receptor type A (EDNRA) is associated with guanine-nucleotide-binding (G) proteins and plays important roles in cellular processes and various diseases. PURPOSE: To investigate the prognosis value of EDNRA expression and its correlation with immune infiltrates in patients with STAD. METHODS: The association between clinical characteristics and EDNRA expression in STAD was analyzed using the Wilcoxon signed-rank test and logistic regression. The Kaplan-Meier plotter analysis and Cox regression were constructed to evaluate the influence of EDNRA on prognosis, and a receiver operating characteristic (ROC) curve and nomogram were constructed. Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were conducted to analyze the correlation between EDNRA and immune infiltrates. In addition, Oncomine, TIMER databases and qRT-PCR of STAD cell lines were used to verify the EDNRA expression in STAD. RESULTS: Our results revealed that EDNRA expression was significantly higher in patients with STAD than normal gastric tissues, and the results have been confirmed by RT-qPCR. KM-plotter analysis revealed that patients with STAD had shorter OS, FP, and PPS (P<0.001). Multivariate Cox analysis further confirmed that high EDNRA expression was an independent risk factor for OS in patients with STAD. Moreover, other clinicopathologic features were related with worse prognosis in STAD, including age, lymph nodes metastases and primary outcome. More importantly, ROC analysis also confirmed the diagnostic value, and a prognostic nomogram involving age, T, M, N classification, pathologic stage, residual tumor and EDNRA was constructed. GSEA revealed that high EDNRA expression was correlated with immunoregulatory interactions between lymphoid and non lymphoid cells pathways, natural killer cell activation involved in immune response, interleukin 1 receptor binding and pathways in cancer, and ssGSEA showed that EDNRA is correlated with macrophages and NK cells. CONCLUSION: Collectively, EDNRA can be an independent prognostic biomarker and correlated with immune infiltration in stomach adenocarcinoma.

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.].

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.

Systematic Pan-Cancer Analysis Identifies TREM2 as an Immunological and Prognostic Biomarker.

Triggering receptor expressed on myeloid cells-2 (TREM2) is a transmembrane receptor of the immunoglobulin superfamily and a crucial signaling hub for multiple pathological pathways that mediate immunity. Although increasing evidence supports a vital role for TREM2 in tumorigenesis of some cancers, no systematic pan-cancer analysis of TREM2 is available. Thus, we aimed to explore the prognostic value, and investigate the potential immunological functions, of TREM2 across 33 cancer types. Based on datasets from The Cancer Genome Atlas, and the Cancer Cell Line Encyclopedia, Genotype Tissue-Expression, cBioPortal, and Human Protein Atlas, we employed an array of bioinformatics methods to explore the potential oncogenic roles of TREM2, including analyzing the relationship between TREM2 and prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), DNA methylation, and immune cell infiltration of different tumors. The results show that TREM2 is highly expressed in most cancers, but present at low levels in lung cancer. Further, TREM2 is positively or negatively associated with prognosis in different cancers. Additionally, TREM2 expression was associated with TMB and MSI in 12 cancer types, while in 20 types of cancer, there was a correlation between TREM2 expression and DNA methylation. Six tumors, including breast invasive carcinoma, cervical squamous cell carcinoma and endocervical adenocarcinoma, kidney renal clear cell carcinoma, lung squamous cell carcinoma, skin cutaneous melanoma, and stomach adenocarcinoma, were screened out for further study, which demonstrated that TREM2 gene expression was negatively correlated with infiltration levels of most immune cells, but positively correlated with infiltration levels of M1 and M2 macrophages. Moreover, correlation with TREM2 expression differed according to T cell subtype. Our study reveals that TREM2 can function as a prognostic marker in various malignant tumors because of its role in tumorigenesis and tumor immunity.

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.

Identification of LINC00665-miR-let-7b-CCNA2 competing endogenous RNA network associated with prognosis of lung adenocarcinoma.

Prognosis of patients with lung cancer remains extremely poor; thus, we sought to unearth novel competing endogenous RNA (ceRNA) networks associated with the prognosis of lung adenocarcinoma (LUAD). Aberrant mRNAs were identified from the intersection of three Gene Expression Omnibus (GEO) datasets. A protein-protein interaction (PPI) network was constructed, and miRNAs and long noncoding RNAs (lncRNAs) upstream of mRNAs were predicted. In the present study, 402 upregulated and 638 downregulated genes in lung cancer tissues were identified. Functional analysis showed significant enrichment of cancer pathways. In these top hub genes, 10 upregulated and 7 downregulated genes had substantial prognostic values in LUAD. Thirty-seven miRNAs were predicted to target 17 key genes, and only five miRNAs exhibited prognostic correlation. Through stepwise reverse prediction and validation from miRNA to lncRNA, four key lncRNAs were identified using expression and survival analysis. Ultimately, the co-expression analysis identified LINC00665-miR-let-7b-CCNA2 as the key ceRNA network associated with the prognosis of LUAD. We successfully constructed a novel ceRNA network wherein each component was significantly associated with the prognosis of LUAD. Hence, we propose that this network may provide key biomarkers or potential therapeutic targets for LUAD prognosis.

Molecular subtypes based on DNA methylation predict prognosis in lung squamous cell carcinoma.

BACKGROUND: Due to tumor heterogeneity, the diagnosis, treatment, and prognosis of patients with lung squamous cell carcinoma (LUSC) are difficult. DNA methylation is an important regulator of gene expression, which may help the diagnosis and therapy of patients with LUSC. METHODS: In this study, we collected the clinical information of LUSC patients in the Cancer Genome Atlas (TCGA) database and the relevant methylated sequences of the University of California Santa Cruz (UCSC) database to construct methylated subtypes and performed prognostic analysis. RESULTS: Nine hundred sixty-five potential independent prognosis methylation sites were finally identified and the genes were identified. Based on consensus clustering analysis, seven subtypes were identified by using 965 CpG sites and corresponding survival curves were plotted. The prognostic analysis model was constructed according to the methylation sites' information of the subtype with the best prognosis. Internal and external verifications were used to evaluate the prediction model. CONCLUSIONS: Models based on differences in DNA methylation levels may help to classify the molecular subtypes of LUSC patients, and provide more individualized treatment recommendations and prognostic assessments for different clinical subtypes. GNAS, FZD2, FZD10 are the core three genes that may be related to the prognosis of LUSC patients.

Identification of potential crucial genes associated with the pathogenesis and prognosis of liver hepatocellular carcinoma.

AIMS: Liver hepatocellular carcinoma (LIHC) is the main manifestation of primary liver cancer, with low survival rate and poor prognosis. Medical decision-making process of LIHC is so complex that new biomarkers for diagnosis and prognosis have yet to be explored, this study aimed to identify the genes involved in the pathophysiology of LIHC and biomarkers that can be used to predict the prognosis of LIHC. METHODS: Six Gene Expression Omnibus (GEO) datasets selected from GEO were screened and integrated to find out the differential expression genes (DEGs) obtained from LIHC and normal hepatic tissues. The Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analysis of DEGs was implemented by DAVID. The Protein-protein interaction network was performed via STRING. In addition, Cox regression model was used to construct a gene prognostic signature. RESULTS: We ascertained 10 hub genes, nine of them (CDK1, CDC20, CCNB1, Thymidylate synthetase, Nuclear division cycle80, NUF2, MAD2L1, CCNA2 and BIRC5) as biomarkers of progression in LIHC patients. We also build a six gene prognosis signature (SOCS2, GAS2L3, NLRP5, TAF3, UTP11 and GAGE2A), which can be implemented to predict over survival effectively. CONCLUSIONS: We revealed promising genes that may participate in the pathophysiology of LIHC, and found available biomarkers for LIHC prognosis prediction, which were significant for researchers to further understand the molecular basis of LIHC and direct the synthesis medicine of LIHC.

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.

Identification of potential crucial genes associated with the pathogenesis and prognosis of pancreatic adenocarcinoma.

Pancreatic adenocarcinoma (PAAD) is a type of malignant tumor with the highest mortality rate among all neoplasms worldwide, and its exact pathogenesis is still poorly understood. Timely diagnosis and treatment are of great importance in order to decrease the mortality rate of PAAD. Therefore, identifying new biomarkers for diagnosis and prognosis is essential to enable early detection of PAAD and to improve the overall survival (OS) rate. In order to screen and integrate differentially expressed genes (DEGs) between PAAD and normal tissues, a total of seven datasets were downloaded from the Gene Expression Omnibus database and the 'limma' and 'robustrankggreg' packages in R software were used. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis of the DEGs was performed using the Database for Annotation, Visualization and Integrated Discovery website, and the protein-protein interaction network analysis was performed using the Search Tool for the Retrieval of Interacting Genes/Proteins database. A gene prognostic signature was constructed using the Cox regression model. A total of 10 genes (CDK1, CCNB1, CDC20, ASPM, UBE2C, TPX2, TOP2A, NUSAP1, KIF20A and DLGAP5) that may be associated with pancreatic adenocarcinoma were identified. According to the differentially expressed genes in The Cancer Genome Atlas, the present study set up four prognostic signatures (matrix metalloproteinase 12, sodium voltage-gated channel α subunit 11, tetraspanin 1 and SH3 domain and tetratricopeptide repeats-containing 2), which effectively predicted OS. The hub genes that were highly associated with the occurrence, development and prognosis of PAAD were identified, which may be helpful to further understand the molecular basis of pancreatic cancer and guide the synthesis of drugs for PPAD.

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.