scholarly journals Analysis of Ferroptosis-Mediated Modification Patterns and Tumor Immune Microenvironment Characterization in Uveal Melanoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Yi Jin ◽  
Zhanwang Wang ◽  
Dong He ◽  
Yuxing Zhu ◽  
Lian Gong ◽  
...  
Keyword(s):  
Uveal Melanoma ◽  
Enrichment Analysis ◽  
Progression Free Survival ◽  
Gene Set Enrichment Analysis ◽  
Consensus Clustering ◽  
Training Set ◽  
Poor Overall Survival ◽  
Competing Endogenous Rna Network ◽  
Underlying Mechanisms ◽  
Cox Analysis

Uveal melanoma (UVM) is an intraocular malignancy in adults in which approximately 50% of patients develop metastatic disease and have a poor prognosis. The need for immunotherapies has rapidly emerged, and recent research has yielded impressive results. Emerging evidence has implicated ferroptosis as a novel type of cell death that may mediate tumor-infiltrating immune cells to influence anticancer immunity. In this study, we first selected 11 ferroptosis regulators in UVM samples from the training set (TCGA and GSE84976 databases) by Cox analysis. We then divided these molecules into modules A and B based on the STRING database and used consensus clustering analysis to classify genes in both modules. According to the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA), the results revealed that the clusters in module A were remarkably related to immune-related pathways. Next, we applied the ESTIMATE and CIBERSORT algorithms and found that these ferroptosis-related patterns may affect a proportion of TME infiltrating cells, thereby mediating the tumor immune environment. Additionally, to further develop the prognostic signatures based on the immune landscape, we established a six-gene-regulator prognostic model in the training set and successfully verified it in the validation set (GSE44295 and GSE27831). Subsequently, we identified the key molecules, including ABCC1, CHAC1, and GSS, which were associated with poor overall survival, progression-free survival, disease-specific survival, and progression-free interval. We constructed a competing endogenous RNA network to further elucidate the mechanisms, which consisted of 29 lncRNAs, 12 miRNAs, and 25 ferroptosis-related mRNAs. Our findings indicate that the ferroptosis-related genes may be suitable potential biomarkers to provide novel insights into UVM prognosis and decipher the underlying mechanisms in tumor microenvironment characterization.

scholarly journals Tumor ferroptosis status demonstrated vulnerability to chemotherapy and reflected immune-activation in colorectal cancer

2020 ◽  
Author(s):  
Yang Lv ◽  
QingYang Feng ◽  
ZhiYuan Zhang ◽  
Peng Zheng ◽  
DeXiang Zhu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
T Cells ◽  
Enrichment Analysis ◽  
Progression Free Survival ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
M1 Macrophage ◽  
Central Molecule ◽  
Ifn Γ ◽  
Cox Analysis

Abstract Background: Existing studies for ferroptosis and prognosis in colorectal cancer (CRC) were limited. In this study, we aim to investigate the prognostic role of ferroptosis markers in patients with CRC and exploration of its micro-environmental distributions. Methods: A total of 911 patients from 2008 to 2013 with CRC were enrolled. Immunohistochemical staining was performed for CRC patients’ tissue microarray. Selection and prognostic validation of markers were based on mRNA data from the cancer genome atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) was performed to indicate relative immune landmarks and hallmarks. Ferroptosis and immune contexture were examined by CIBERSORT. Survival outcomes were analyzed by Kaplan-meier analysis and cox analysis.Results: A panel of 42 genes was selected. Through mRNA expression difference and prognosis analysis, GPX4, NOX1 and ACSL4 were selected as candidate markers. By IHC, increased GPX4, decreased NOX1 and decreased FACL4 indicate poor prognosis and worse clinical characteristics. Ferroptosis score based on GPX4, NOX1 and ACSL4 was constructed and validated with high C-index. Low ferroptosis score can also demonstrate the better progression free survival and better adjuvant chemotherapy (ACT) responsiveness. Moreover, tumor with low ferroptosis score tend to be infiltrated with more CD4+ T cells, CD8+ T cells and less M1 macrophage. Finally, we found that IFN-γ was potentially the central molecule at the crossroad between ferroptosis and onco-immune response. Conclusion: Ferroptosis plays important role on CRC tumor progression, ACT response and prognosis. Ferroptosis contributes to immune-supportive responses and IFN-γ was the central molecule for this process.

A Six-Gene Prognostic Risk Prediction Model In Hepatitis B Virus-Associated Hepatocellular Carcinoma

2021 ◽  
Vol 44 (3) ◽  
pp. E32-44
Author(s):  
Jia Shen ◽  
Ming Shu ◽  
Shujie Xie ◽  
Jia Yan ◽  
Kaile Pan ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Prognostic Model ◽  
Prognostic Score ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Training Set ◽  
Gene Set Enrichment ◽  
B Virus ◽  
Score Model ◽  
Normal Controls

Purpose: This study aimed to screen hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC)-related feature ribonucleic acids (RNAs) and to establish a prognostic model. Methods: The transcriptome expression data of HBV-associated HCC were downloaded from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus database. Differential RNAs between HBV-associated HCC and normal controls were identified by a meta-analysis of TCGA, GSE55092 and GSE121248. Weighted gene co-expression network analysis was performed to identify key RNAs and modules. A prognostic score model was established using TCGA as a training set by Cox regression analysis and was validated in E-TABM-36 dataset. Additionally, independent prognostic clinical factors were screened, and the function of lncRNAs waspredicted through Gene Set Enrichment Analysis. Results: A total of 710 consistent differential RNAs between HBV-associated HCC and normal controls were obtained, including five lncRNAs and 705 mRNAs. An optimized combination of six differential RNAs (DSCR4, DBH, ECM1, GDAP1, MATR3 and RFC4) was selected and a prognostic score model was constructed. Kaplan-Meier analysis demonstrated that the prognosis of the high-risk and low-risk groups separated by this model was significantly different in the training set and the validation set. Gene Set Enrichment Analysis showed that the co-expression genes of DSCR4 were significantly correlated with neuroactive ligand receptor interactionpathway. Conclusion: A prognostic model based on DSCR4, DBH, ECM1, GDAP1, MATR3 and RFC4 was developed that can accurately predict the prognosis of patients with HBV-associated HCC. These genes, as well as histologic grade, may serve as independent prognostic factors in HBV-associated HCC.

Genomic drivers of poor prognosis and enzalutamide resistance in metastatic castration-resistant prostate cancer.

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 146-146
Author(s):  
William S. Chen ◽  
Rahul Raj Aggarwal ◽  
Li Zhang ◽  
Shuang Zhao ◽  
Tomasz M. Beer ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Overall Survival ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Beta Catenin ◽  
Rna Seq ◽  
Castration Resistant Prostate Cancer ◽  
Gene Set Enrichment ◽  
Poor Overall Survival ◽  
Castration Resistant

146 Background: Metastatic castration-resistant prostate cancer (mCRPC) is the lethal form of the disease. Several recent efforts have identified genomic alterations in mCRPC, but the clinical implications of these alterations have not been fully elucidated. We conducted a prospective cohort study (n = 101) using whole genome sequencing (WGS) to analyze the association between key driver gene alterations and overall survival. We also performed whole-transcriptome RNA sequencing (RNA-seq) analyses to identify potential mechanisms of enzalutamide resistance in mCRPC. Methods: Metastasis biopsies were obtained in 101 mCRPC patients as part of the multi-institutional West Coast Prostate Cancer Dream Team project. Samples underwent WGS and RNA-seq. The resulting mutation, copy number, and structural variant calls were integrated to determine functional copy number status of candidate genes for downstream clinical analyses. We performed univariate and multivariable analyses to assess the prognostic significance of candidate genomic events with respect to overall survival. To nominate and investigate genomic pathways associated with enzalutamide resistance, we performed expression-based gene set enrichment analysis followed by cross-sectional enrichment and survival analyses related to the top nominated pathway. Results: RB1 loss was associated with poor overall survival (median 14.1 vs. 42.0 months, p < 0.001). When we compared enzalutamide resistant versus naïve samples using gene set enrichment analysis, we identified the Wnt/beta-catenin pathway as the top differentially expressed pathway in enzalutamide-resistant patients. Furthermore, CTNNB1 (beta-catenin) activating mutations were exclusive to enzalutamide-resistant patients (p = 0.013) and predictive of poor overall survival (median 13.6 vs. 41.7 months, p < 0.001). Conclusions: Impaired survival in mCRPC patients is associated with RB1 loss, identified by integrated genomic analysis of CRPC metastasis biopsies. Among men with mCRPC that was enzalutamide-resistant, the Wnt/beta-catenin pathway is nominated as an important predictive (and potentially therapeutic) pathway.

scholarly journals Identification of an IRGP Signature to Predict Prognosis and Immunotherapeutic Efficiency in Bladder Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Liang-Hao Zhang ◽  
Long-Qing Li ◽  
Yong-Hao Zhan ◽  
Zhao-Wei Zhu ◽  
Xue-Pei Zhang
Keyword(s):  
Bladder Cancer ◽  
Stromal Cells ◽  
Molecular Mechanisms ◽  
Proportional Hazards ◽  
Enrichment Analysis ◽  
Cox Proportional Hazards ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Validation Set

BackgroundIdentify immune-related gene pairs (IRGPs) signature related to the prognosis and immunotherapeutic efficiency for bladder cancer (BLCA) patients.Materials and MethodsOne RNA-seq dataset (The Cancer Genome Atlas Program) and two microarray datasets (GSE13507 and GSE31684) were included in this study. We defined these cohorts as training set to construct IRGPs and one immunotherapy microarray dataset as validation set. Identifying BLCA subclasses based on IRGPs by consensus clustering. The Lasso penalized Cox proportional hazards regression model was used to construct prognostic signature and potential molecular mechanisms were analyzed.ResultsThis signature can accurately predict the overall survival of BLCA patients and was verified in the immunotherapy validation set. IRGP-signatures can be used as independent prognostic risk factor in various clinical subgroups. Use the CIBERSORT algorithm to assess the abundance of infiltrating immune cells in each sample, and combine the results of the gene set enrichment analysis of a single sample to explore the differences in the immune microenvironment between IRPG signature groups. According to the results of GSVA, GSEA, and CIBERSORT algorithm, we found that IRGP is strikingly positive correlated with tumor microenvironment (TME) stromal cells infiltration, indicating that the poor prognosis and immunotherapy might be caused partly by enrichment of stromal cells. Finally, the results from the TIDE analysis revealed that IRGP could efficiently predict the response of immunotherapy in BLCA.ConclusionThe novel IRGP signature has a significant prognostic value for BLCA patients might facilitate personalized for immunotherapy.

scholarly journals High Level of METTL7B Indicates Poor Prognosis of Patients and Is Related to Immunity in Glioma

2021 ◽  
Vol 11 ◽  
Author(s):  
Yujia Xiong ◽  
Mingxuan Li ◽  
Jiwei Bai ◽  
Yutao Sheng ◽  
Yazhuo Zhang
Keyword(s):  
Poor Prognosis ◽  
Immune Cell ◽  
Characteristic Curve ◽  
Glioma Cells ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Immune Checkpoints ◽  
Roc Curve Analysis ◽  
Cox Analysis ◽  
High Level

Glioma is the most common primary intracranial malignant tumor in adults. Although there have been many efforts on potential targeted therapy of glioma, the patient’s prognosis remains dismal. Methyltransferase Like 7B (METTL7B) has been found to affect the development of a variety of tumors. In this study, we collected RNA-seq data of glioma in CGGA and TCGA, analyzed them separately. Then, Kaplan-Meier survival analysis, univariate and multivariate Cox analysis, and receiver operating characteristic curve (ROC curve) analysis were used to evaluate the effect of METTL7B on prognosis. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA) enrichment analyses were used to identify the function or pathway associated with METTL7B. Moreover, the ESTIMATE algorithm, Cibersort algorithm, Spearman correlation analysis, and TIMER database were used to explore the relationship between METTL7B and immunity. Finally, the role of METTL7B was explored in glioma cells. We found that METTL7B is highly expressed in glioma, and high expression of METTL7B in glioma is associated with poor prognosis. In addition, there were significant differences in immune scores and immune cell infiltration between the two groups with different expression levels of METTL7B. Moreover, METTL7B was also correlated with immune checkpoints. Knockdown of METTL7B revealed that METTL7B promoted the progression of glioma cells. The above results indicate that METTL7B affects the prognosis of patients and is related to tumor immunity, speculating that METTL7B may be a new immune-related target for the treatment of glioma.

scholarly journals Construction of a Novel Signature and Prediction of the Immune Landscape in Soft Tissue Sarcomas Based on N6-Methylandenosine-Related LncRNAs

2021 ◽  
Vol 8 ◽  
Author(s):  
Li Zhang ◽  
Xianzhe Tang ◽  
Jia Wan ◽  
Xianghong Zhang ◽  
Tao Zheng ◽  
...  
Keyword(s):  
High Risk ◽  
Soft Tissue ◽  
Cox Regression ◽  
Soft Tissue Sarcomas ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Consensus Clustering ◽  
Immune Microenvironment

Background: N6-methylandenosine-related long non-coding RNAs (m6A-related lncRNAs) are critically involved in cancer development. However, the roles and clinical significance of m6A-related lncRNAs in soft tissue sarcomas (STS) are inconclusive, thereby warranting further investigations.Methods: Transcriptome profiling data were extracted from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx). Consensus clustering was employed to divide patients into clusters and Kaplan–Meier analysis was used to explore the prognostic differences between the subgroups. Gene set enrichment analysis (GSEA) was conducted to identify the biological processes and signaling pathways associated with m6A-Related lncRNAs. Finally, patients were randomly divided into training and validation cohorts, and least absolute shrinkage and selection operator (LASSO) Cox regression was conducted to establish the m6A-related lncRNA-based risk signature.Results: A total of 259 STS patients from TCGA-SARC dataset were enrolled in our study. Thirteen m6A-Related lncRNAs were identified to be closely related to the prognosis of STS patients. Patients were divided into two clusters, and patients in cluster 2 had a better overall survival (OS) than those in cluster 1. Patients in different clusters also showed differences in immune scores, infiltrating immune cells, and immune checkpoint expression. Patients were further classified into high-risk and low-risk subgroups according to risk scores, and high-risk patients were found to have a worse prognosis. The receiver operating characteristic (ROC) curve indicated that the risk signature displayed excellent performance at predicting the prognosis of patients with STS. Further, the risk signature was remarkably connected with the immune microenvironment and chemosensitivity in STS.Conclusion: Our study demonstrated that m6A-related lncRNAs were significantly associated with prognosis and tumor immune microenvironment and could function as independent prognosis-specific predictors in STS, thereby providing novel insights into the roles of m6A-related lncRNAs in STS.

scholarly journals Identification of Potential Diagnostic and Prognostic Biomarkers for Colorectal Cancer Based on GEO and TCGA Databases

2021 ◽  
Vol 11 ◽  
Author(s):  
Zhenjiang Wang ◽  
Mingyi Guo ◽  
Xinbo Ai ◽  
Jianbin Cheng ◽  
Zaiwei Huang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Biomarkers ◽  
High Recurrence Rate ◽  
Mortality And Morbidity ◽  
Invasive Test ◽  
Underlying Mechanisms

Colorectal cancer (CRC) is one of the most common neoplastic diseases worldwide. With a high recurrence rate among all cancers, treatment of CRC only improved a little over the last two decades. The mortality and morbidity rates can be significantly lessened by earlier diagnosis and prompt treatment. Available biomarkers are not sensitive enough for the diagnosis of CRC, whereas the standard diagnostic method, endoscopy, is an invasive test and expensive. Hence, seeking the diagnostic and prognostic biomarkers of CRC is urgent and challenging. With that order, we screened the overlapped differentially expressed genes (DEGs) of GEO (GSE110223, GSE110224, GSE113513) and TCGA datasets. Subsequent protein–protein interaction network analysis recognized the hub genes among these DEGs. Further functional analyses including Gene Ontology and KEGG pathway analysis and gene set enrichment analysis were processed to investigate the role of these genes and potential underlying mechanisms in CRC. Kaplan–Meier analysis and Cox hazard ratio analysis were carried out to clarify the diagnostic and prognostic role of these genes. In conclusion, our present study demonstrated that CCNA2, MAD2L1, DLGAP5, AURKA, and RRM2 are all potential diagnostic biomarkers for CRC and may also be potential treatment targets for clinical implication in the future.

scholarly journals Transcriptional profiling identifies an androgen receptor activity-low, stemness program associated with enzalutamide resistance

2020 ◽  
Vol 117 (22) ◽  
pp. 12315-12323 ◽  
Author(s):  
Joshi J. Alumkal ◽  
Duanchen Sun ◽  
Eric Lu ◽  
Tomasz M. Beer ◽  
George V. Thomas ◽  
...  
Keyword(s):  
Androgen Receptor ◽  
De Novo ◽  
Statistical Significance ◽  
Specific Antigen ◽  
Enrichment Analysis ◽  
Progression Free Survival ◽  
Gene Set Enrichment Analysis ◽  
Specific Gene ◽  
Castration Resistant Prostate Cancer ◽  
Gene Alterations

The androgen receptor (AR) antagonist enzalutamide is one of the principal treatments for men with castration-resistant prostate cancer (CRPC). However, not all patients respond, and resistance mechanisms are largely unknown. We hypothesized that genomic and transcriptional features from metastatic CRPC biopsies prior to treatment would be predictive of de novo treatment resistance. To this end, we conducted a phase II trial of enzalutamide treatment (160 mg/d) in 36 men with metastatic CRPC. Thirty-four patients were evaluable for the primary end point of a prostate-specific antigen (PSA)50 response (PSA decline ≥50% at 12 wk vs. baseline). Nine patients were classified as nonresponders (PSA decline <50%), and 25 patients were classified as responders (PSA decline ≥50%). Failure to achieve a PSA50 was associated with shorter progression-free survival, time on treatment, and overall survival, demonstrating PSA50’s utility. Targeted DNA-sequencing was performed on 26 of 36 biopsies, and RNA-sequencing was performed on 25 of 36 biopsies that contained sufficient material. Using computational methods, we measured AR transcriptional function and performed gene set enrichment analysis (GSEA) to identify pathways whose activity state correlated with de novo resistance.TP53gene alterations were more common in nonresponders, although this did not reach statistical significance (P= 0.055).ARgene alterations and AR expression were similar between groups. Importantly, however, transcriptional measurements demonstrated that specific gene sets—including those linked to low AR transcriptional activity and a stemness program—were activated in nonresponders. Our results suggest that patients whose tumors harbor this program should be considered for clinical trials testing rational agents to overcome de novo enzalutamide resistance.

scholarly journals Screening of independent prognostic long non-coding RNA for gastric cancer in TCGA

2020 ◽  
Author(s):  
Qiang Zhang ◽  
Qiongyun Chen ◽  
Yinyin Lv ◽  
Xuan Dong ◽  
Xiaoqing Huang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Prognostic Factor ◽  
Cox Regression ◽  
Disease Free Survival ◽  
Enrichment Analysis ◽  
R Package ◽  
Gene Set Enrichment Analysis ◽  
Unfavorable Prognostic Factor ◽  
Non Coding Rna ◽  
Cox Analysis

Abstract Background The global incidence of gastric cancer (GC) ranks the fourth among cancers and its 5-year survival is less than 25%. LncRNAs are vital regulators involved in pathological processes of cancer. It is urgent to screen the prognostic lncRNA in GC. Method Expression file and clinical data of GC were downloaded from TCGA. Differentially expressed lncRNAs were calculated by edger R package, followed by the prognosis analysis. COX analysis was conducted to compute the independent factor of GC. Potential signaling pathways that the screened lncRNAs enriched in were evaluated by gene set enrichment analysis (GSEA). At last, Pearson analysis was conducted to predict the possible mechanism of lncRNA in GC process. Result ENSG00000224363 was an unfavorable prognostic factor to OS (overall survival) and DFS (disease-free survival) of GC as COX regression analyzed. GSEA analysis indicated that ENSG00000224363 may regulate cell cycle, apoptosis and autophagy of GC cells. Conclusion LncRNA ENSG00000224363 is overexpressed in GC, serving as an independent unfavorable prognostic factor.

scholarly journals GPR143 is a Prognostic Biomarker Associated with Immune Infiltration in Melanoma

2021 ◽  
Author(s):  
Zixuan Xing ◽  
Shaobo Wu ◽  
Qijuan Zang ◽  
Hao Lei ◽  
Yi Wei ◽  
...  
Keyword(s):  
G Protein ◽  
Prognostic Biomarker ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Congenital Nystagmus ◽  
Immune Infiltration ◽  
Interactive Analysis ◽  
Tcga Dataset ◽  
Cox Analysis ◽  
G Protein Coupled

Abstract Background: Skin cutaneous melanoma (SKCM) is considered one of the most aggressive and lethal cancers of the skin. G-protein coupled receptor 143 (GPR143), which has been reported to cause congenital nystagmus, belongs to the superfamily of G protein-coupled receptors. Methods and Results: We analyzed the expression of GPR143 and survival of SKCM patients in SKCM via Gene Expression Profiling Interactive Analysis (GEPIA). Then, logistic regression and multivariate cox analysis was used to analyze the influence of GPR143 expression on clinicopathological elements and survival. We explored the immune response of 22 TIICs in SKCM via CIBERSORT and used TIMER to assess the correlation of GPR143 expression and immune infiltration level. Finally, we used gene set enrichment analysis (GSEA) to assess the TCGA dataset. The outcomes suggest that GPR143 expression in tumor samples is remarkedly higher than in normal samples and high GPR143 expression is associated with poorer prognosis. The result of multivariate analysis indicated that increased GPR143 expression is an independent prognostic factor for prognosis. We found GPR143 expression level has prominent negative correlations with infiltrating levels of B cell, CD8+ T cells, etc. GSEA indicated that pigment metabolic process, pigment biosynthetic process and other pathways were identified as differentially enriched pathways in Gene Ontology (GO). Oxidative phosphorylation, Parkinson’s disease and other pathways were showed significantly differential enrichment in GPR143 high expression phenotype in Kyoto Encyclopedia of Genes and Genomes (KEGG).Conclusions: In conclusion, GPR143 may be a novel prognostic biomarker and associated with immune infiltrates in SKCM.

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