scholarly journals Glucose-6-Phosphate Dehydrogenase is a Prognostic Biomarker and Correlated with Immune Infiltrates in Hepatocellular Carcinoma

2022 ◽  
Author(s):  
Yang Bu ◽  
Kejun Liu ◽  
Yiming Niu ◽  
Ji Hao ◽  
Lei Cui ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Microenvironment ◽  
Liver Cancer ◽  
Immune Cell ◽  
Cox Regression ◽  
Functional Enrichment ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Potential Biomarker ◽  
Glucose 6 Phosphate Dehydrogenase

Abstract Background: Glucose-6-phosphate dehydrogenase (G6PD) plays an important role in the metabolic and immunological aspects of tumors. In hepatocellular carcinoma (HCC), the alteration of tumor microenvironment influences recurrence and metastasis. We extracted G6PD-related data from public databases of HCC tissues and used a bioinformatics approach to explore the correlation between G6PD expression and clinicopathological features and prognosis of immune cell infiltration in HCC.Methods: We extract G6PD expression information from TCGA and GEO databases in liver cancer tissues and normal tissues, validated by immunohistochemistry, and the correlation between G6PD expression and clinical features is analyzed, and the clinical significance of G6PD in liver cancer is assessed by Kaplan-Meier, Cox regression and prognostic line graph models. Functional enrichment analysis is performed by protein-protein interaction (PPI) network, GO/KEGG, GSEA and G6PD-associated differentially expressed genes (DEGs). TIMER and ssGSEA packages are used to assess the correlation between expression and the level of immune cell infiltration.Results: Our results show that G6PD expression is significantly upregulated in hepatocellular carcinoma tissues (P < 0.001). G6PD expression is associated with histological grade, pathological stage, T-stage, vascular infiltration and AFP level (P < 0.05); HCC patients in the low G6PD expression group had longer overall survival and better prognosis compared with the high G6PD expression group (P < 0.05). The level of G6PD expression also affects the levels of macrophages, unactivated dendritic cells, B cells, and follicular helper T cells in the tumor microenvironment.Conclusion: High expression of G6PD is a potential biomarker for poor prognosis of hepatocellular carcinoma, and G6PD may be a target for immunotherapy of HCC.

scholarly journals Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Shixin Xiang ◽  
Jing Li ◽  
Jing Shen ◽  
Yueshui Zhao ◽  
Xu Wu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Tumor Microenvironment ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Tumor Purity

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. The efficacy of immunotherapy usually depends on the interaction of immunomodulation in the tumor microenvironment (TME). This study aimed to explore the potential stromal-immune score-based prognostic genes related to immunotherapy in HCC through bioinformatics analysis.Methods: ESTIMATE algorithm was applied to calculate the immune/stromal/Estimate scores and tumor purity of HCC using the Cancer Genome Atlas (TCGA) transcriptome data. Functional enrichment analysis of differentially expressed genes (DEGs) was analyzed by the Database for Annotation, Visualization, and Integrated Discovery database (DAVID). Univariate and multivariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were performed for prognostic gene screening. The expression and prognostic value of these genes were further verified by KM-plotter database and the Human Protein Atlas (HPA) database. The correlation of the selected genes and the immune cell infiltration were analyzed by single sample gene set enrichment analysis (ssGSEA) algorithm and Tumor Immune Estimation Resource (TIMER).Results: Data analysis revealed that higher immune/stromal/Estimate scores were significantly associated with better survival benefits in HCC within 7 years, while the tumor purity showed a reverse trend. DEGs based on both immune and stromal scores primarily affected the cytokine–cytokine receptor interaction signaling pathway. Among the DEGs, three genes (CASKIN1, EMR3, and GBP5) were found most significantly associated with survival. Moreover, the expression levels of CASKIN1, EMR3, and GBP5 genes were significantly correlated with immune/stromal/Estimate scores or tumor purity and multiple immune cell infiltration. Among them, GBP5 genes were highly related to immune infiltration.Conclusion: This study identified three key genes which were related to the TME and had prognostic significance in HCC, which may be promising markers for predicting immunotherapy outcomes.

scholarly journals Hypoxic Characteristic in the Immunosuppressive Microenvironment of Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhuomao Mo ◽  
Daiyuan Liu ◽  
Dade Rong ◽  
Shijun Zhang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Cell ◽  
Cox Regression ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Checkpoints ◽  
Immune Cell Infiltration ◽  
Immunosuppressive Microenvironment

Background: Generally, hepatocellular carcinoma (HCC) exists in an immunosuppressive microenvironment that promotes tumor evasion. Hypoxia can impact intercellular crosstalk in the tumor microenvironment. This study aimed to explore and elucidate the underlying relationship between hypoxia and immunotherapy in patients with HCC.Methods: HCC genomic and clinicopathological datasets were obtained from The Cancer Genome Atlas (TCGA-LIHC), Gene Expression Omnibus databases (GSE14520) and International Cancer Genome Consortium (ICGC-LIRI). The TCGA-LIHC cases were divided into clusters based on single sample gene set enrichment analysis and hierarchical clustering. After identifying patients with immunosuppressive microenvironment with different hypoxic conditions, correlations between immunological characteristics and hypoxia clusters were investigated. Subsequently, a hypoxia-associated score was established by differential expression, univariable Cox regression, and lasso regression analyses. The score was verified by survival and receiver operating characteristic curve analyses. The GSE14520 cohort was used to validate the findings of immune cell infiltration and immune checkpoints expression, while the ICGC-LIRI cohort was employed to verify the hypoxia-associated score.Results: We identified hypoxic patients with immunosuppressive HCC. This cluster exhibited higher immune cell infiltration and immune checkpoint expression in the TCGA cohort, while similar significant differences were observed in the GEO cohort. The hypoxia-associated score was composed of five genes (ephrin A3, dihydropyrimidinase like 4, solute carrier family 2 member 5, stanniocalcin 2, and lysyl oxidase). In both two cohorts, survival analysis revealed significant differences between the high-risk and low-risk groups. In addition, compared to other clinical parameters, the established score had the highest predictive performance at both 3 and 5 years in two cohorts.Conclusion: This study provides further evidence of the link between hypoxic signals in patients and immunosuppression in HCC. Defining hypoxia-associated HCC subtypes may help reveal potential regulatory mechanisms between hypoxia and the immunosuppressive microenvironment, and our hypoxia-associated score could exhibit potential implications for future predictive models.

scholarly journals Prediction of Hepatocellular Carcinoma Prognosis and Immune Cell Infiltration Using Gene Signature Associated with Inflammatory Response

2022 ◽  
Vol 2022 ◽  
pp. 1-24
Author(s):  
Bin-Bin Da ◽  
Shuai Luo ◽  
Ming Huang ◽  
Fei Song ◽  
Rong Ding ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Inflammatory Response ◽  
Immune Cell ◽  
Cox Regression ◽  
Inflammatory Responses ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Differential Analysis

It has been demonstrated that the inflammatory response influences cancer development and can be used as a prognostic biomarker in various tumors. However, the relevance of genes associated with inflammatory responses in hepatocellular carcinoma (HCC) remains unknown. The Cancer Genome Atlas (TCGA) database was analyzed using weighted gene coexpression network analysis (WGCNA) and differential analysis to discover essential inflammatory response-related genes (IFRGs). Cox regression studies, both univariate and multivariate, were employed to develop a prognostic IFRGs signature. Additionally, Gene Set Enrichment Analysis (GSEA) was used to deduce the biological function of the IFRGs signature. Finally, we estimated immune cell infiltration using a single sample GSEA (ssGSEA) and x-cell. Our results revealed that, among the major HCC IFRGs, two (DNASE1L3 and KLKB1) were employed to create a predictive IFRG signature. The IFRG signature could correctly predict overall survival (O.S) as per Kaplan-Meier time-dependent roc curves analysis. It was also linked to pathological tumor stage and T stage and might be used as a prognostic predictor in HCC. GSEA analysis concluded that the IFRG signature might influence the immune response in HCC. Immunological cell infiltration and immune checkpoint molecule expression differed in the high-risk and low-risk groups. As a result of our findings, DNASILE may play a role in the tumor microenvironment. However, more research is necessary to confirm the role of DNASE1L3 and KLKB1.

scholarly journals A Critical Role of Peptidylprolyl Isomerase A Pseudogene 22/microRNA-197-3p/Peptidylprolyl Isomerase A Axis in Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuwei Gu ◽  
Chao Wang ◽  
Shengsen Chen ◽  
Jia Tang ◽  
Xiaoxiao Guo ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Cell ◽  
Critical Role ◽  
Enrichment Analysis ◽  
Vital Role ◽  
Functional Enrichment ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Chemokine Ligand ◽  
Peptidylprolyl Isomerase

The burden of hepatocellular carcinoma (HCC) worldwide is increasing over time, while the underlying molecular mechanism of HCC development is still under exploration. Pseudogenes are classified as a special type of long non-coding RNAs (lncRNAs), and they played a vital role in regulating tumor-associated gene expression. Here, we report that a pseudogene peptidylprolyl isomerase A pseudogene 22 (PPIAP22) and its parental gene peptidylprolyl isomerase A (PPIA) were upregulated in HCC and were associated with the clinical outcomes of HCC. Further investigation revealed that PPIAP22 might upregulate the expression of PPIA through sponging microRNA (miR)-197-3p, behaving as competing endogenous RNA (ceRNA). PPIA could participate in the development of HCC by regulating mRNA metabolic process and tumor immunity based on the functional enrichment analysis. We also found a strong correlation between the expression levels of PPIA and the immune cell infiltration or the expression of chemokines, especially macrophage, C-C motif chemokine ligand 15 (CCL15), and C-X-C motif chemokine ligand 12 (CXCL12). Our findings demonstrate that the PPIAP22/miR-197-3p/PPIA axis plays a vital role in the progression of HCC by increasing the malignancy of tumor cells and regulating the immune cell infiltration, especially macrophage, through CCL15-CCR1 or CXCL12-CXCR4/CXCR7 pathways.

scholarly journals Construction of a Six Immune-Related lncRNAs Signature to Predict Outcome, Immune Cell Infiltration and Immunotherapy Response in Patients with Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Pengcheng Zhou ◽  
Jiang Wei ◽  
Lu Yuhua ◽  
Wang Lei ◽  
Zhang Yewei
Keyword(s):  
Hepatocellular Carcinoma ◽  
High Risk ◽  
Tumor Microenvironment ◽  
Immune Cells ◽  
Immune Cell ◽  
Cox Regression ◽  
Risk Group ◽  
Immune Cell Infiltration ◽  
Biological Processes ◽  
Qrt Pcr

Abstract Background: Hepatocellular carcinoma (HCC) is one of the most lethal malignant tumors worldwide with poor prognosis. Growing evidence has demonstrated that immune-related long non-coding RNAs (lncRNAs) are relevant to tumor microenvironment (TME) and can help to assess the effects of immunotherapy and evaluate prognosis. This study aimed to identify an immune-related lncRNA signature for the prospective assessment of immunotherapy and prognosis in HCC. Methods: HCC RNA-seq data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) project database. Firstly, we used ESTIMATE to evaluate the tumor microenvironment (TME). Then, cox regression analysis was used to construct a prognostic signature and the risk score. Univariate Cox regression, multivariate Cox regression, principal components analysis (PCA), the receiver operating characteristic (ROC) curve and stratification analyses were applied to confirm. Gene set enrichment analysis (GSEA) analysis was employed to explore the biological processes and pathways. Besides, CIBERSORT was used to estimate the abundance of tumor-infiltrating immune cells (TIICs). Furthermore, the relationship between the immune-related lncRNA signature and immune checkpoint genes was investigated. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) assays were used to demonstrated the expression of the six lncRNAs. Results:.We identified a six immune-related lncRNAs (MSC-AS1, AC145207.5, SNHG3, AL365203.2, AL031985.3, NRAV) with the ability to stratify patients into high-risk and low-risk groups with significantly different survival. Univariate Cox regression, multivariate Cox regression, ROC and stratification analyses confirmed that the six immune-related lncRNA signature was a novel independent prognostic factor in HCC patients. The high-risk group and low-risk group illustrated different distributions in PCA. GSEA suggested that the six immune-related lncRNA signature is involved in the immune-related biological processes and pathways. Besides, the six immune-related lncRNA signature was associated with the infiltration of immune cells. Furthermore, the six immune-related lncRNA signature was associated with the expression of critical immune genes and could predict the clinical response of immunotherapy. Finally, qRT-PCR demonstrated that the six lncRNAs were significantly differentially expressed in HCC cell lines and normal hepatic cell line. Conclusions: In summary, we identified a six immune-related lncRNA signature with the ability to predict outcome, immune cell infiltration and immunotherapy response in patients with hepatocellular carcinoma.

scholarly journals Deciphering the Pyroptosis-Related Prognostic Signature and Immune Cell Infiltration Characteristics of Colon Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Ran Wei ◽  
Shuofeng Li ◽  
Guanhua Yu ◽  
Xu Guan ◽  
Hengchang Liu ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Tumor Microenvironment ◽  
Immune Cell ◽  
Cox Regression ◽  
Tumor Development ◽  
Assessment Model ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Immune Microenvironment ◽  
Molecular Patterns

Background: Colon cancer (CC) remains one of the most common malignancies with a poor prognosis. Pyroptosis, referred to as cellular inflammatory necrosis, is thought to influence tumor development. However, the potential effects of pyroptosis-related regulators (PRRs) on the CC immune microenvironment remain unknown.Methods: In this study, 27 PRRs reported in the previous study were used to cluster the 1,334 CC samples into three pyroptosis-related molecular patterns. Through subtype pattern differential analysis and structure network mining using Weighted Gene Co-expression Network Analysis (WGCNA), 854 signature genes associated with the PRRs were discovered. Further LASSO-penalized Cox regression of these genes established an eight-gene assessment model for predicting prognosis.Results: The CC patients were subtyped based on three distinct pyroptosis-related molecular patterns. These pyroptosis-related patterns were correlated with different clinical outcomes and immune cell infiltration characteristics in the tumor microenvironment. The pyroptosis-related eight-signature model was established and used to assess the prognosis of CC patients with medium-to-high accuracy by employing the risk scores, which was named “PRM-scores.” Greater inflammatory cell infiltration was observed in tumors with low PRM-scores, indicating a potential benefit of immunotherapy in these patients.Conclusions: This study suggests that PRRs have a significant effect on the tumor immune microenvironment and tumor development. Evaluating the pyroptosis-related patterns and related models will promote our understanding of immune cell infiltration characteristics in the tumor microenvironment and provide a theoretical basis for future research targeting pyroptosis in cancer.

scholarly journals Comprehensive analysis of immune-related prognostic genes in the tumour microenvironment of hepatocellular carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Weike Gao ◽  
Luan Li ◽  
Xinyin Han ◽  
Siyao Liu ◽  
Chengzhen Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Proportional Hazards ◽  
Immune Cell ◽  
Prognostic Index ◽  
Tumour Microenvironment ◽  
Cox Proportional Hazards ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Potential Biomarker

Abstract Background The mortality rate of hepatocellular carcinoma (HCC) remains high worldwide despite surgery and chemotherapy. Immunotherapy is a promising treatment for the rapidly expanding HCC spectrum. Therefore, it is necessary to further explore the immune-related characteristics of the tumour microenvironment (TME), which plays a vital role in tumour initiation and progression. Methods In this research, 866 immune-related differentially expressed genes (DEGs) were identified by integrating the DEGs of samples from The Cancer Genome Atlas (TCGA)-HCC dataset and the immune-related genes from databases (InnateDB; ImmPort). Afterwards, 144 candidate prognostic genes were defined through weighted gene co-expression network analysis (WGCNA). Results Seven immune-related prognostic DEGs were identified using the L1-penalized least absolute shrinkage and selection operator (LASSO) Cox proportional hazards (PH) model, and the ImmuneRiskScore model was constructed on this basis. The prognostic index of the ImmuneRiskScore model was then validated in the relevant dataset. Patients were divided into high- and low-risk groups according to the ImmuneRiskScore. Differences in the immune cell infiltration of patients with different ImmuneRiskScore values were clarified, and the correlation of immune cell infiltration with immunotherapy biomarkers was further explored. Conclusion The ImmuneRiskScore of HCC could be a prognostic marker and can reflect the immune characteristics of the TME. Furthermore, it provides a potential biomarker for predicting the response to immunotherapy in HCC patients.

scholarly journals SFTPA1 is a potential prognostic biomarker correlated with immune cell infiltration and response to immunotherapy in lung adenocarcinoma

2021 ◽  
Author(s):  
Lu Yuan ◽  
Xixi Wu ◽  
Longshan Zhang ◽  
Mi Yang ◽  
Xiaoqing Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
T Cells ◽  
Lung Adenocarcinoma ◽  
Expression Profile ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Regulatory Pathways ◽  
Chronic Lung Diseases ◽  
Potential Biomarker

AbstractPulmonary surfactant protein A1 (SFTPA1) is a member of the C-type lectin subfamily that plays a critical role in maintaining lung tissue homeostasis and the innate immune response. SFTPA1 disruption can cause several acute or chronic lung diseases, including lung cancer. However, little research has been performed to associate SFTPA1 with immune cell infiltration and the response to immunotherapy in lung cancer. The findings of our study describe the SFTPA1 expression profile in multiple databases and was validated in BALB/c mice, human tumor tissues, and paired normal tissues using an immunohistochemistry assay. High SFTPA1 mRNA expression was associated with a favorable prognosis through a survival analysis in lung adenocarcinoma (LUAD) samples from TCGA. Further GeneOntology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses showed that SFTPA1 was involved in the toll-like receptor signaling pathway. An immune infiltration analysis clarified that high SFTPA1 expression was associated with an increased number of M1 macrophages, CD8+ T cells, memory activated CD4+ T cells, regulatory T cells, as well as a reduced number of M2 macrophages. Our clinical data suggest that SFTPA1 may serve as a biomarker for predicting a favorable response to immunotherapy for patients with LUAD. Collectively, our study extends the expression profile and potential regulatory pathways of SFTPA1 and may provide a potential biomarker for establishing novel preventive and therapeutic strategies for lung adenocarcinoma.

scholarly journals Identification of immune-based prostate cancer subtypes using mRNA expression

2020 ◽  
Author(s):  
Jukun Song ◽  
Song He ◽  
Wei Wang ◽  
Jiaming Su ◽  
Dongbo Yuan ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Immune Response ◽  
Immune Cells ◽  
Immune Cell ◽  
Molecular Classification ◽  
Cell Types ◽  
Functional Enrichment ◽  
Cell Infiltration ◽  
Cell Subpopulation ◽  
Immune Cell Infiltration

Abstract Background Immune infiltration of Prostate cancer (PCa) was highly related to clinical outcomes. However, previous works failed to elucidate the diversity of different immune cell types that make up the function of the immune response system. The aim of the study was to uncover the composition of TIICs in PCa utilizing the CIBERSORT algorithm and further reveal the molecular characteristics of PCa subtypes. Method In the present work, we employed the CIBERSORT method to evaluate the relative proportions of immune cell profiling in PCa and adjacent samples, normal samples. We analyzed the correlation between immune cell infiltration and clinical information. The tumor-infiltrating immune cells of the TCGA PCa cohort were analyzed for the first time. The fractions of 22 immune cell types were imputed to determine the correlation between each immune cell subpopulation and clinical feature. Three types of molecular classification were identified via R-package of “CancerSubtypes”. The functional enrichment was analyzed in each subtype. The submap and TIDE algorithm were used to predict the clinical response to immune checkpoint blockade, and GDSC was employed to screen chemotherapeutic targets for the potential treatment of PCa. Results In current work, we utilized the CIBERSORT algorithm to assess the relative proportions of immune cell profiling in PCa and adjacent samples, normal samples. We investigated the correlation between immune cell infiltration and clinical data. The tumor-infiltrating immune cells in the TCGA PCa cohort were analyzed. The 22 immune cells were also calculated to determine the correlation between each immune cell subpopulation and survival and response to chemotherapy. Three types of molecular classification were identified. Each subtype has specific molecular and clinical characteristics. Meanwhile, Cluster I is defined as advanced PCa, and is more likely to respond to immunotherapy. Conclusions Our results demonstrated that differences in immune response may be important drivers of PCa progression and response to treatment. The deconvolution algorithm of gene expression microarray data by CIBERSOFT provides useful information about the immune cell composition of PCa patients. In addition, we have found a subtype of immunopositive PCa subtype and will help to explore the reasons for the poor effect of PCa on immunotherapy, and it is expected that immunotherapy will be used to guide the individualized management and treatment of PCa patients.

scholarly journals Identification and validation of tumor microenvironment-related lncRNA prognostic signature for uveal melanoma

2021 ◽  
Vol 14 (8) ◽  
pp. 1151-1159
Author(s):  
Chen-Lu Liao ◽  
◽  
Xing-Yu Sun ◽  
Qi Zhou ◽  
Min Tian ◽  
...  
Keyword(s):  
Prognostic Value ◽  
Prognostic Markers ◽  
Immune Cell ◽  
Cox Regression ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Prognostic Signature ◽  
Profile Data ◽  
Small Molecule Drugs

AIM: To investigate the role of tumor microenvironment (TME)-related long non-coding RNA (lncRNA) in uveal melanoma (UM), probable prognostic signature and potential small molecule drugs using bioinformatics analysis. METHODS: UM expression profile data were downloaded from the Cancer Genome Atlas (TCGA) and bioinformatics methods were used to find prognostic lncRNAs related to UM immune cell infiltration. The gene expression profile data of 80 TCGA specimens were analyzed using the single sample Gene Set Enrichment Analysis (ssGSEA) method, and the immune cell infiltration of a single specimen was evaluated. Finally, the specimens were divided into high and low infiltration groups. The differential expression between the two groups was analyzed using the R package ‘edgeR’. Univariate, multivariate and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analyses were performed to explore the prognostic value of TME-related lncRNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional analyses were also performed. The Connectivity Map (CMap) data set was used to screen molecular drugs that may treat UM. RESULTS: A total of 2393 differentially expressed genes were identified and met the criteria for the low and high immune cell infiltration groups. Univariate Cox analysis of lncRNA genes with differential expression identified 186 genes associated with prognosis. Eight prognostic markers of TME-included lncRNA genes were established as potentially independent prognostic elements. Among 269 differentially expressed lncRNAs, 69 were up-regulated and 200 were down-regulated. Univariate Cox regression analysis of the risk indicators and clinical characteristics of the 8 lncRNA gene constructs showed that age, TNM stage, tumor base diameter, and low and high risk indices had significant prognostic value. We screened the potential small-molecule drugs for UM, including W-13, AH-6809 and Imatinib. CONCLUSION: The prognostic markers identified in this study are reliable biomarkers of UM. This study expands our current understanding of the role of TME-related lncRNAs in UM genesis, which may lay the foundations for future treatment of this disease.

Sign in / Sign up

Export Citation Format

Share Document