Dataset Information

LAYN Is a Prognostic Biomarker and Correlated With Immune Infiltrates in Gastric and Colon Cancers.

ABSTRACT: Background: Layilin (LAYN) is a critical gene that regulates T cell function. However, the correlations of LAYN to prognosis and tumor-infiltrating lymphocytes in different cancers remain unclear. Methods: LAYN expression was analyzed via the Oncomine database and Tumor Immune Estimation Resource (TIMER) site. We evaluated the influence of LAYN on clinical prognosis using Kaplan-Meier plotter, the PrognoScan database and Gene Expression Profiling Interactive Analysis (GEPIA). The correlations between LAYN and cancer immune infiltrates was investigated via TIMER. In addition, correlations between LAYN expression and gene marker sets of immune infiltrates were analyzed by TIMER and GEPIA. Results: A cohort (GSE17536) of colorectal cancer patients showed that high LAYN expression was associated with poorer overall survival (OS), disease-specific survival (DSS), and disease-free survival (DFS). In addition, high LAYN expression was significantly correlated with poor OS and progression-free survival (PFS) in gastric cancers (OS HR = 1.97, P = 3.6e-10; PFS HR = 2.12, P = 2.3e-10). Moreover, LAYN significantly impacts the prognosis of diverse cancers via The Cancer Genome Atlas (TCGA). Specifically, high LAYN expression was correlated with worse OS and PFS in stage 2 to 4 but not stage 1 and stage N0 gastric cancer patients (P = 0.28, 0.34; P = 0.073, 0.092). LAYN expression was positively correlated with infiltrating levels of CD4+ T and CD8+ T cells, macrophages, neutrophils, and dendritic cells (DCs) in colon adenocarcinoma (COAD) and stomach adenocarcinoma (STAD). LAYN expression showed strong correlations with diverse immune marker sets in COAD and STAD. Conclusions: These findings suggest that LAYN is correlated with prognosis and immune infiltrating levels of, including those of CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and DCs in multiple cancers, especially in colon and gastric cancer patients. In addition, LAYN expression potentially contributes to regulation of tumor-associated macrophages (TAMs), DCs, T cell exhaustion and Tregs in colon and gastric cancer. These findings suggest that LAYN can be used as a prognostic biomarker for determining prognosis and immune infiltration in gastric and colon cancers.

SUBMITTER: Pan JH

PROVIDER: S-EPMC6362421 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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LAYN Is a Prognostic Biomarker and Correlated With Immune Infiltrates in Gastric and Colon Cancers.

Pan Jing-Hua JH Zhou Hong H Cooper Laura L Huang Jin-Lian JL Zhu Sheng-Bin SB Zhao Xiao-Xu XX Ding Hui H Pan Yun-Long YL Rong Lijun L

Frontiers in immunology 20190129

<b>Background:</b> Layilin (LAYN) is a critical gene that regulates T cell function. However, the correlations of LAYN to prognosis and tumor-infiltrating lymphocytes in different cancers remain unclear. <b>Methods:</b> LAYN expression was analyzed via the Oncomine database and Tumor Immune Estimation Resource (TIMER) site. We evaluated the influence of LAYN on clinical prognosis using Kaplan-Meier plotter, the PrognoScan database and Gene Expression Profiling Interactive Analysis (GEPIA). The c ...[more]

PMID: 30761122

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Project description:Colon adenocarcinoma (COAD) is one of the most serious cancers. It is important to accurately predict prognosis and provide individualized treatment. Evidence suggests that clinicopathological features and immune status of the body are related to the occurrence and development of cancer. Expression of long non-coding RNA (LncRNA) ALMS1 intronic transcript 1 (ALMS1-IT1) is observed in some cancer types, and we believe that it may have the potential to serve as a marker of COAD. Therefore, we used the data obtained from the cancer genome atlas (TCGA) database to prove the relationship between ALMS1-IT1 and COAD. Wilcoxon rank sum test, Chi-square test, Fisher exact test and logistic regression were used to evaluate relationships between clinical-pathologic features and ALMS1-IT1 expression. Receiver operating characteristic curves were used to describe binary classifier value of ALMS1-IT1 using area under curve score. Kaplan-Meier method and Cox regression analysis were used to evaluate factors contributing to prognosis. Gene oncology (GO) and (Kyoto Encyclopedia of Genes and Genomes) KEGG enrichment analysis were used to predict the function of differentially expressed genes associated with ALMS1-IT1. Gene set enrichment analysis (GSEA) was used to predict canonical pathways associated with ALMS1-IT1.Immune infiltration analysis was performed to identify the significantly involved functions of ALMS1-IT1. Starbase database was used to predict miRNAs and RNA binding proteins (RBPs) that may interact with ALMS1-IT1. Increased ALMS1-IT1 expression in COAD was associated with N stage (P < .001), M stage (P = .003), Pathologic stage (P = .002), and Primary therapy outcome (P = .009). Receiver operating characteristic curve suggested the significant diagnostic and prognostic ability of ALMS1-IT1 (area under curve = 0.857). High ALMS1-IT1 expression predicted a poorer overall-survival (P = .005) and poorer progression-free interval (PFI) (P = .012), and ALMS1-IT1 expression was independently correlated with PFI in COAD patients (hazard ratio (HR) :1.468; 95% CI: 1.029-2.093; P =.034) (HR: 1.468; 95% CI: 1.029-2.093; P = .034). GO, KEGG, GSEA, and immune infiltration analysis showed that ALMS1-IT1 expression was correlated with regulating the function of DNA and some types of immune infiltrating cells. ALMS1-IT1 expression was significantly correlated with poor survival and immune infiltrations in COAD, and it may be a promising prognostic biomarker in COAD.

Project description:PurposeThe serine protease inhibitor clade E member 1 (SERPINE1) has been studied as a potential biomarker in a variety of cancers, but poorly studied in gastric cancer (GC). The purpose of this study was to explore the prognostic value of SERPINE1 in GC and primarily analyze its functions.MethodsWe analyzed the the prognostic value of SERPINE1 and studied the relationship with clinicopathologic biomarkers in gastric cancer. The expression of SERPINE1 was analyzed by GEO and TCGA databases. Moreover, we validated the results by immunohistochemistry. Next, the correlation analysis between SERPINE1 and the cuproptosis-related genes was analyzed by the "Spearman" method. CIBERSORT and TIMER algorithms were used to analyze the correlation of SERPINE1 with immune infiltration. Furthermore, GO and KEGG gene enrichment analyses were used to study the functions and pathways that SERPINE1 might be involved in. Then, drug sensitivity analysis was performed using CellMiner database. Finally, a cuproptosis-immune-related prognostic model was constructed using genes related to immune and cuproptosis, and verified against external datasets.ResultsSERPINE1 was up-regulated in gastric cancer tissues, which tends toward poor prognosis. Using immunohistochemistry experiment, the expression and prognostic value of SERPINE1 were verified. Then, we found that SERPINE1 was negatively correlated with cuproptosis-related genes FDX1, LIAS, LIPT1, and PDHA1. On the contrary, SERPINE1 was positively correlated with APOE. This indicates the effect of SERPINE1 on the cuproptosis process. Furthermore, by conducting immune-related analyses, it was revealed that SERPINE1 may promote the inhibitory immune microenvironment. The infiltration level of resting NK cells, neutrophils, activated mast cells, and macrophages M2 was positively correlated with SERPINE1. However, B cell memory and plasma cells were negatively correlated with SERPINE1. Functional analysis showed that SERPINE1 was closely related to angiogenesis, apoptosis, and ECM degradation. The KEGG pathway analysis showed that SERPINE1 may be associated with P53, Pi3k/Akt, TGF-β, and other signaling pathways. Drug sensitivity analysis showed that SERPINE1 could be also seen as a potential treatment target. The risk model based on SERPINE1 co-expression genes could better predict the survival of GC patients than SERPINE1 alone. We also verified the prognostic value of the risk score by GEO external datasets.ConclusionSERPINE1 is highly expressed in gastric cancer and related to poor prognosis. SERPINE1 may regulate cuproptosis and the immune microenvironment by a series of pathways. Therefore, SERPINE1 as a prognostic biomarker and potential therapeutic target deserves further study.

Dataset Information

LAYN Is a Prognostic Biomarker and Correlated With Immune Infiltrates in Gastric and Colon Cancers.

Publications

LAYN Is a Prognostic Biomarker and Correlated With Immune Infiltrates in Gastric and Colon Cancers.

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