Identification of prognostic and immune-related lncRNAs in hepatocellular carcinoma based on the cancer genome atlas data mining

2020 ◽  
Vol 10 (8) ◽  
pp. 1189-1196
Author(s):  
Kaikai Ren ◽  
Jiakang Ma ◽  
Bo Zhou ◽  
Xiaoyan Lin ◽  
Mingyu Hou ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
High Rate ◽  
Prognostic Indicators ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Hepatocellular carcinoma (HCC) is a malignancy originating from hepatocytes with a high rate of distant metastasis and recurrence. HCC prognosis remains poorly understood, although its diagnosis and treatment have improved globally. Therefore, it is necessary to identify reliable predictive and prognostic indicators of HCC. HCC gene expression profiles and corresponding clinical data were downloaded from The Cancer Genome Atlas. Seven lncRNAs (C10orf91, AC011352.3, AC015722.2, AC006372.1, PICSAR, AC110285.3, and AP001972.4) associated with immune and clinicopathological features were identified as biomarker candidates for HCC prognosis based on single-sample gene set enrichment analysis, the ESTIMATE algorithm, and Cox PHR analyses. Altogether, the findings revealed that the seven immune-related lncRNAs may provide a reference for improving HCC prognosis.

Exploring exosome data to identify prognostic gene signatures for lung adenocarcinoma

2021 ◽  
Author(s):  
Jialin Li ◽  
Xinliang Gao ◽  
Suyan Tian ◽  
Mingbo Tang ◽  
Wei Liu
Keyword(s):  
Lung Adenocarcinoma ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Gene Expression Omnibus ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Immune Functions ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background: Exosomes are involved in tumorigenesis, growth and metastasis. However, the prognostic value of exosome-related genes in lung adenocarcinoma (LUAD) remains unclear. Methods: Clinical and transcriptome data from The Cancer Genome Atlas LUAD cohort were used to construct a model based on exosome-related genes, which was validated with LUAD data from the Gene Expression Omnibus (GEO). Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis were used to explore underlying mechanisms; the single-sample gene set enrichment analysis score was used to determine immune functions. Results: A 19-exosome-related gene signature for overall survival in LUAD was predictive in both The Cancer Genome Atlas and GEO LUAD cohorts. Immune-related and extracellular matrix-related pathways were enriched in differentially expressed genes. Immune states differed between high- and low-risk groups. Conclusion: The novel signature can be used to predict outcomes in LUAD.

scholarly journals Screening and Identifying m6A Regulators as an Independent Prognostic Biomarker in Pancreatic Cancer Based on The Cancer Genome Atlas Database

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Bi Lin ◽  
Yangyang Pan ◽  
Dinglai Yu ◽  
Shengjie Dai ◽  
Hongwei Sun ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cox Regression ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Tumor Therapy ◽  
Disease Free Survival ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background. Pancreatic cancer is one of the most malignant tumors of the digestive system, and its treatment has rarely progressed for the last two decades. Studies on m6A regulators for the past few years have seemingly provided a novel approach for malignant tumor therapy. m6A-related factors may be potential biomarkers and therapeutic targets. This research is focused on the gene characteristics and clinical values of m6A regulators in predicting prognosis in pancreatic cancer. Methods. In our study, we obtained gene expression profiles with copy number variation (CNV) data and clinical characteristic data of 186 patients with pancreatic cancer from The Cancer Genome Atlas (TCGA) portal. Then, we determined the alteration of m6a regulators and their correlation with clinicopathological features using the log-rank tests, Cox regression model, and chi-square test. Additionally, we validated the prognostic value of m6A regulators in the International Cancer Genome Consortium (ICGC). Results. The results suggested that pancreatic cancer patients with ALKBH5 CNV were associated with worse overall survival and disease-free survival than those with diploid genes. Additionally, upregulation of the writer gene ALKBH5 had a positive correlation with the activation of AKT pathways in the TCGA database. Conclusion. Our study not only demonstrated genetic characteristic changes of m6A-related genes in pancreatic cancer and found a strong relationship between the changes of ALKBH5 and poor prognosis but also provided a novel therapeutic target for pancreatic cancer therapy.

scholarly journals Identification of the HMMR Gene as a Diagnostic and Prognostic Biomarker in Hepatocellular Carcinoma Based on Integrated Bioinformatics Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Honglan Guo ◽  
Qinqiao Fan
Keyword(s):  
Hepatocellular Carcinoma ◽  
Roc Curve ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Roc Curve Analysis ◽  
Cox Regression Analysis ◽  
Normal Tissues

Background. We aimed to investigate the expression of the hyaluronan-mediated motility receptor (HMMR) gene in hepatocellular carcinoma (HCC) and nonneoplastic tissues and to investigate the diagnostic and prognostic value of HMMR. Method. With the reuse of the publicly available The Cancer Genome Atlas (TCGA) data, 374 HCC patients and 50 nonneoplastic tissues were used to investigate the diagnostic and prognostic values of HMMR genes by receiver operating characteristic (ROC) curve analysis and survival analysis. All patients were divided into low- and high-expression groups based on the median value of HMMR expression level. Univariate and multivariate Cox regression analysis were used to identify prognostic factors. Gene set enrichment analysis (GSEA) was performed to explore the potential mechanism of the HMMR genes involved in HCC. The diagnostic and prognostic values were further validated in an external cohort from the International Cancer Genome Consortium (ICGC). Results. HMMR mRNA expression was significantly elevated in HCC tissues compared with that in normal tissues from both TCGA and the ICGC cohorts (all P values <0.001). Increased HMMR expression was significantly associated with histologic grade, pathological stage, and survival status (all P values <0.05). The area under the ROC curve for HMMR expression in HCC and normal tissues was 0.969 (95% CI: 0.948–0.983) in the TCGA cohort and 0.956 (95% CI: 0.932–0.973) in the ICGC cohort. Patients with high HMMR expression had a poor prognosis than patients with low expression group in both cohorts (all P < 0.001 ). Univariate and multivariate analysis also showed that HMMR is an independent predictor factor associated with overall survival in both cohorts (all P values <0.001). GSEA showed that genes upregulated in the high-HMMR HCC subgroup were mainly significantly enriched in the cell cycle pathway, pathways in cancer, and P53 signaling pathway. Conclusion. HMMR is expressed at high levels in HCC. HMMR overexpression may be an unfavorable prognostic factor for HCC.

scholarly journals CXCL5 Has Potential to Be a Marker for Hepatocellular Carcinoma Prognosis and Was Correlating With Immune Infiltrates

2021 ◽  
Vol 11 ◽  
Author(s):  
Yuan Nie ◽  
Mei-chun Jiang ◽  
Cong Liu ◽  
Qi Liu ◽  
Xuan Zhu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Hospital Data ◽  
Gene Set Enrichment ◽  
Local Hospital ◽  
High Expression Group ◽  
Cancer Genome Atlas

BackgroundsTumor microenvironment (TME) plays a crucial role in the initiation and progression of Hepatocellular Carcinoma (HCC), especially immune infiltrates. However, there is still a challenge in understanding the modulation of the immune and stromal components in TME, especially TME related genes.MethodsThe proportion of tumor-infiltrating immune cells (TICs) and the immune and stromal scores in 374 HCC patients from The Cancer Genome Atlas (TCGA) database were determined using CIBERSORT and ESTIMATE computational methods. The final screened genes were confirmed by the PPI network and univariate Cox regression of the differentially expressed genes based on different immune or stromal scores. The correlation between the expression levels of the final gene interactions and the clinical characteristics was based on TCGA database and local hospital data. Gene set enrichment analysis (GSEA) and the effect of CXCL5 expression on TICs were conducted.ResultsThere were correlations between the expression of CXCL5 and survival of HCC patients and TMN classification both in TCGA database and local hospital data. The immune-related activities were enriched in the high-expression group; however, the metabolic pathways were enriched in the low-expression group. The result of CIBERSORT analyzing had indicated that CXCL5 expression were correlated with the proportion of NK cells activated, macrophages M0, Mast cells resting, Neutrophils.ConclusionsCXCL5 was a potential prognostic marker for HCC and provides clues regarding immune infiltrates, which offers extra insight for therapeutics of HCC, however, more independent cohorts and functional experiments of CXCL5 are warranted.

scholarly journals Profiling pro-neural to mesenchymal transition identifies a lncRNA signature in glioma

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Qingyu Liang ◽  
Gefei Guan ◽  
Xue Li ◽  
Chunmi Wei ◽  
Jianqi Wu ◽  
...  
Keyword(s):  
Cox Regression ◽  
Expression Profiles ◽  
Treatment Strategies ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Risky Behaviors ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Mesenchymal Transition ◽  
Genome Atlas

Abstract Background Molecular classification has laid the framework for exploring glioma biology and treatment strategies. Pro-neural to mesenchymal transition (PMT) of glioma is known to be associated with aggressive phenotypes, unfavorable prognosis, and treatment resistance. Recent studies have highlighted that long non-coding RNAs (lncRNAs) are key mediators in cancer mesenchymal transition. However, the relationship between lncRNAs and PMT in glioma has not been systematically investigated. Methods Gene expression profiles from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), GSE16011, and Rembrandt with available clinical and genomic information were used for analyses. Bioinformatics methods such as weighted gene co-expression network analysis (WGCNA), gene set enrichment analysis (GSEA), Cox analysis, and least absolute shrinkage and selection operator (LASSO) analysis were performed. Results According to PMT scores, we confirmed that PMT status was positively associated with risky behaviors and poor prognosis in glioma. The 149 PMT-related lncRNAs were identified by WGCNA analysis, among which 10 (LINC01057, TP73-AS1, AP000695.4, LINC01503, CRNDE, OSMR-AS1, SNHG18, AC145343.2, RP11-25K21.6, RP11-38L15.2) with significant prognostic value were further screened to construct a PMT-related lncRNA risk signature, which could divide cases into two groups with distinct prognoses. Multivariate Cox regression analyses indicated that the signature was an independent prognostic factor for high-grade glioma. High-risk cases were more likely to be classified as the mesenchymal subtype, which confers enhanced immunosuppressive status by recruiting macrophages, neutrophils, and regulatory T cells. Moreover, six lncRNAs of the signature could act as competing endogenous RNAs to promote PMT in glioblastoma. Conclusions We profiled PMT status in glioma and established a PMT-related 10-lncRNA signature for glioma that could independently predict glioma survival and trigger PMT, which enhanced immunosuppression.

scholarly journals The Cancer Genome Atlas expression profiles of low-grade gliomas

2014 ◽  
Vol 36 (4) ◽  
pp. E23 ◽  
Author(s):  
David D. Gonda ◽  
Vincent J. Cheung ◽  
Karra A. Muller ◽  
Amit Goyal ◽  
Bob S. Carter ◽  
...  
Keyword(s):  
Cpg Island ◽  
Expression Profiles ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Molecular Characteristics ◽  
Low Grade ◽  
Cpg Island Methylator Phenotype ◽  
Low Grade Gliomas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Differentiating between low-grade gliomas (LGGs) of astrocytic and oligodendroglial origin remains a major challenge in neurooncology. Here the authors analyzed The Cancer Genome Atlas (TCGA) profiles of LGGs with the goal of identifying distinct molecular characteristics that would afford accurate and reliable discrimination of astrocytic and oligodendroglial tumors. They found that 1) oligodendrogliomas are more likely to exhibit the glioma-CpG island methylator phenotype (G-CIMP), relative to low-grade astrocytomas; 2) relative to oligodendrogliomas, low-grade astrocytomas exhibit a higher expression of genes related to mitosis, replication, and inflammation; and 3) low-grade astrocytic tumors harbor microRNA profiles similar to those previously described for glioblastoma tumors. Orthogonal intersection of these molecular characteristics with existing molecular markers, such as IDH1 mutation, TP53 mutation, and 1p19q status, should facilitate accurate and reliable pathological diagnosis of LGGs.

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