scholarly journals A four-gene signature predicts survival and anti-CTLA4 immunotherapeutic responses based on immune classification of melanoma

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Ying Mei ◽  
Mei-Ju May Chen ◽  
Han Liang ◽  
Li Ma
Keyword(s):  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Gene Set Enrichment ◽  
Malignant Skin ◽  
Cancer Genome Atlas ◽  
Melanoma Patients ◽  
Potential Use

AbstractCutaneous melanoma is the most malignant skin cancer. Biomarkers for stratifying patients at initial diagnosis and informing clinical decisions are highly sought after. Here we classified melanoma patients into three immune subtypes by single-sample gene-set enrichment analysis. We further identified a four-gene tumor immune-relevant (TIR) signature that was significantly associated with the overall survival of melanoma patients in The Cancer Genome Atlas cohort and in an independent validation cohort. Moreover, when applied to melanoma patients treated with the CTLA4 antibody, ipilimumab, the TIR signature could predict the response to ipilimumab and the survival. Notably, the predictive power of the TIR signature was higher than that of other biomarkers. The genes in this signature, SEL1L3, HAPLN3, BST2, and IFITM1, may be functionally involved in melanoma progression and immune response. These findings suggest that this four-gene signature has potential use in prognosis, risk assessment, and prediction of anti-CTLA4 response in melanoma patients.

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 Prognostic Biomarker SYK and its Correlation with Immune Infiltrates in Glioma

2021 ◽  
Author(s):  
Pei Liu ◽  
Jiamin Guo ◽  
Xiaoxiao Xu ◽  
Haixin Sun ◽  
Zheng Gong
Keyword(s):  
Development Process ◽  
Prognostic Biomarker ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Ppi Network ◽  
Glioma Patient ◽  
Gene Set Enrichment ◽  
Protein Protein Interaction ◽  
Cancer Genome Atlas

Abstract Background: Tumor microenvironment (TME) has great effects on the development process of glioma, and we sought to identify effective prognostic factors by analyzing data from patients with glioma. In this paper, CIBERSORT and ESTIMATE calculations were employed to figure up the ratio of tumor-infiltrating immune cells (TICs) and the quantity of immune and stromal components in 698 glioma dates from The Cancer Genome Atlas (TCGA) database. In addition, differentially expressed genes (DEGs) were studied by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and single genes associated with prognosis were identified by PPI network and COX combined analysis. Results: Immune and stromal scores of TME were significantly correlated with glioma patient survival. Through protein–protein interaction (PPI) network and regression analysis of COX, we finally determined that SYK was the best prognostic factor for patients with glioma. Gene Set Enrichment Analysis (GSEA) and CIBERSORT analysis were also employed, with the former showed that high-expression SYK group’s genes are principally enriched immune-related activities and the latter revealed that SYK expression was positively associated with T cells CD4 memory resting and Monocytes. All the above experimental analyses provided the theoretical basis for the biological prediction of SYK.Conclusions: SYK contributes to immune predictors in glioma patients by facilitating the shift of TME from immune dominance to metabolic activity, which provides promising insights into the treatment of glioma.

scholarly journals Comprehensive Analysis of Immune Correlation of KIF20A in Pan-cancer

2020 ◽  
Author(s):  
Xiao-Han Cui ◽  
Qiu-Ju Peng ◽  
Peng Gao ◽  
Xu-Dong Zhang ◽  
Ren-Zhi Li ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Rna Seq ◽  
Gene Set Enrichment ◽  
Related Information ◽  
Common Causes ◽  
Cancer Genome Atlas ◽  
Pan Cancer

Abstract Background: Cancer is one of the most common causes of death, and the morbidity and mortality are gradually increasing in the world. KIF20A plays an important role in tumors, but its immune relevance in pan-cancer needs to be further studied.Methods: KIF20A-related information was download from The Cancer Genome Atlas (TCGA). Collecting RNA-seq data is fragments per kilobase million (FPKM) style data. The ESTIMATE algorithm was used for estimating the stromal and immune scores for 33 tumors. Then, we analyzed the correlation between KIF20A in pan-cancer and immune checkpoints and performed gene set enrichment analysis (GSEA) analysis on the co-expressed genes of KIF20A in pan-cancer.Results: We have confirmed that the expression of KIF20A has a intensive correlation with prognosis in 33 kinds of tumors. Its expression of KIF20A was related to a variety of immune cells and immune checkpoints. Based on the results of GSEA for further analysis, in multiple tumors, KIF20A is related to immune-related pathways.Conclusion: We have demonstrated that KIF20A played an important role in pan-cancer and could affect the occurrence or development of a variety of tumors. Moreover, KIF20A was related to immunity, and KIF20A- related immune research in pan-cancer also needs to be further demonstrate.

scholarly journals Master Regulators, Regulatory Networks, and Pathways of Glioblastoma Subtypes

2014 ◽  
Vol 13s3 ◽  
pp. CIN.S14027 ◽  
Author(s):  
Serdar Bozdag ◽  
Aiguo Li ◽  
Mehmet Baysan ◽  
Howard A. Fine
Keyword(s):  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Gene Set Enrichment ◽  
Master Regulators ◽  
Cancer Genome Atlas ◽  
Gene Regulatory ◽  
Comprehensive Study

Glioblastoma multiforme (GBM) is the most common malignant brain tumor. GBM samples are classified into subtypes based on their transcriptomic and epigenetic profiles. Despite numerous studies to better characterize GBM biology, a comprehensive study to identify GBM subtype-specific master regulators, gene regulatory networks, and pathways is missing. Here, we used FastMEDUSA to compute master regulators and gene regulatory networks for each GBM subtype. We also ran Gene Set Enrichment Analysis and Ingenuity Pathway Analysis on GBM expression dataset from The Cancer Genome Atlas Project to compute GBM- and GBM subtype-specific pathways. Our analysis was able to recover some of the known master regulators and pathways in GBM as well as some putative novel regulators and pathways, which will aide in our understanding of the unique biology of GBM subtypes.

scholarly journals High expression of PIMREG predicts poor survival outcomes and is correlated with immune infiltrates in lung adenocarcinoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11697
Author(s):  
Feng Jiang ◽  
Min Liang ◽  
Xiaolu Huang ◽  
Wenjing Shi ◽  
Yumin Wang
Keyword(s):  
Prognostic Value ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Kaplan Meier ◽  
Cancer Genome Atlas

Background PIMREG is upregulated in multiple cancer types. However, the potential role of PIMREG in lung adenocarcinoma (LUAD) remains unclear. The present study aimed to explore its clinical significance in LUAD. Methods Using the Cancer Genome Atlas (TCGA) databases, we obtained 513 samples of LUAD and 59 normal samples from the Cancer Genome Atlas (TCGA) databases to analyze the relationship between PIMREG and LUAD. We used t and Chi-square tests to evaluate the level of expression of PIMREG and its clinical implication in LUAD. The prognostic value of PIMREG in LUAD was identified through the Kaplan–Meier method, Cox regression analysis, and nomogram. Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were performed to screen biological pathways and analyze the correlation of the immune infiltrating level with the expression of PIMREG in LUAD. Results PIMREG was highly expressed in patients with LUAD. Specifically, the level of PIMREG gradually increased from pathological stage I to IV. Further, we validated the higher expression of PIMREG expressed in LUAD cell lines. Moreover, PIMREG had a high diagnostic value, with an -AUC of 0.955. Kaplan–Meier survival and Cox regression analyses revealed that the high expression of PIMREG was independently associated with poor clinical outcomes. In our prognostic nomogram, the expression of PIMREG implied a significant prognostic value. Gene set enrichment analysis (GSEA) identified that the high expression PIMREG phenotype was involved in the mitotic cell cycle, mRNA splicing, DNA repair, Rho GTPase signaling, TP53 transcriptional regulation, and translation pathways. Next, we also explored the correlation of PIMREG and tumor-immune interactions and found a negative correlation between PIMREG and the immune infiltrating level of T cells, macrophages, B cells, dendritic cells (DCs) , and CD8+ T cells in LUAD. Conclusions High levels of PIMREG correlated with poor prognosis and immune infiltrates in LUAD.

scholarly journals Molecular Features of Glioma Determined and Validated Using Combined TCGA and GTEx Data Analyses

2021 ◽  
Vol 11 ◽  
Author(s):  
Zijiang Yang ◽  
Weiyi Gong ◽  
Ting Zhang ◽  
Heng Gao
Keyword(s):  
Expression Analysis ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Normal Brain ◽  
Gene Set Enrichment ◽  
The Core ◽  
Kaplan Meier ◽  
Cancer Genome Atlas

Gliomas are among the most common intracranial tumors which originated from neuroepithelial cells. Increasing evidence has revealed that long noncoding RNA (lncRNA)-microRNA (miRNA)-mRNA module regulation and tumor-infiltrating immune cells play important regulatory roles in the occurrence and progression of gliomas. However, the precise underlying molecular mechanisms remain largely unknown. Data on gliomas in The Cancer Genome Atlas lack normal control samples; to overcome this limitation, we combined 665 The Cancer Genome Atlas glioma RNA sequence datasets with 188 Genotype-Tissue Expression normal brain RNA sequences to construct an expression matrix profile after normalization. We systematically analyzed the expression of mRNAs, lncRNAs, and miRNAs between gliomas and normal brain tissues. Kaplan–Meier survival analyses were conducted to screen differentially expressed mRNAs, lncRNAs, and miRNAs. A prognostic miRNA-related competitive endogenous RNA network was constructed, and the core subnetworks were filtered using 6 miRNAs, 3 lncRNAs, and 11 mRNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to investigate the biological functions of significantly dysregulated mRNAs. Co-expression network analysis was performed to analyze and screen the core genes. Furthermore, single-sample Gene Set Enrichment Analysis and immune checkpoint gene expression analysis were performed, as co-expression analysis indicated immune gene dysregulation in glioma. Finally, the expression of representative dysregulated genes was validated in U87 cells at the transcriptional level, establishing a foundation for further research. We identified 7017 mRNAs, 437 lncRNAs, and 9 miRNAs that were differentially expressed in gliomas. Kaplan–Meier survival analysis revealed 5684 mRNAs, 61 lncRNAs, and 7 miRNAs with potential as prognostic signatures in patients with glioma. The hub subnetwork of the competing endogenous RNA network between PART1-hsa-mir-25-SLC12A5/TACC2/BSN/TLN2/ZDHHC8 was screened out. Gene co-expression network, single-sample Gene Set Enrichment Analysis, and immune checkpoint expression analysis demonstrated that tumor-infiltrating immune cells are closely related to gliomas. We identified novel potential biomarkers to predict survival and therapeutic targets for patients with gliomas based on a large-scale sample. Importantly, we filtered pivotal genes that provide valuable information for further exploration of the molecular mechanisms underlying glioma tumorigenesis and progression.

scholarly journals Catenin Alpha-2 Mutation Changes the Immune Microenvironment in Lung Adenocarcinoma Patients Receiving Immune Checkpoint Inhibitors

2021 ◽  
Vol 12 ◽  
Author(s):  
Yang Wen ◽  
Anqi Lin ◽  
Weiliang Zhu ◽  
Ting Wei ◽  
Peng Luo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Immune Microenvironment ◽  
Gene Set Enrichment ◽  
Cancer Genome Atlas

Background: Lung cancer has always been the most prevalent cancer. Lung adenocarcinoma (LUAD) is the most common lung cancer subtype and has a high tumor mutation rate. In addition to KRAS, EGFR, ALK, HER2, ROS1, and BRAF, which are known to have high mutation rates, we discovered some new mutated genes, such as catenin alpha-2 (CTNNA2), in LUAD patients treated with immune checkpoint inhibitors (ICIs). These mutant genes are potential therapeutic targets for LUAD.Methods: We analyzed a cohort of LUAD patients with somatic mutation and survival data in the Cancer Genome Atlas (TCGA) database and a cohort of LUAD patients receiving immune checkpoint inhibitors with clinical data and whole-exome sequencing (WES) mutation data to evaluate the role of CTNNA2 gene mutation in LUAD. In addition, CIBERSORT was used to analyze the immune characteristics of CTNNA2 wild-type patients and CTNNA2 mutant-type patients, and gene set enrichment analysis (GSEA) was employed for pathway enrichment analysis. The results were verified by downloading data regarding the drug sensitivity of LUAD cell lines from the Genomics of Drug Sensitivity in Cancer (GDSC) database.Results: We found that CTNNA2 mutation was associated with longer overall survival (OS) in LUAD patients. Analysis of the cohort from the Cancer Genome Atlas showed that patients with CTNNA2 mutation had more tumor neoantigens and a greater tumor mutation burden (TMB). Through further analysis of the tumor immune microenvironment, we found that in LUAD patients with CTNNA2 mutations, the gene expression levels of chemokine C-X-C motif chemokine 9 (CXCL9) and granzyme B (GZMB) were elevated, and the gene expression level of inhibitory receptor killer cell immunoglobulin-like receptor 2DL1 (KIR2DL1) was significantly reduced. These alterations might affect gene expression in macrophages, NK cells, and mast cell markers. In addition, LUAD patients with CTNNA2 mutation had a significantly increased number of mutations in DNA damage response (DDR) genes. The drug susceptibility results and gene set enrichment analysis showed that after CTNNA2 mutation occurred, changes were found in the DNA damage response pathway, the phosphoinositide 3-kinase (PI3K) pathway and others, indicating that CTNNA2 mutation can regulate the activation of PI3K and DDR pathways.Conclusion: Our findings provide novel insights into the underlying pathogenesis of LUAD. CTNNA2 mutation can change the immune microenvironment, thereby improving patient prognosis. The results also suggest that CTNNA2 may become a new biomarker and therapeutic target for LUAD in the future.

scholarly journals CSIG-03. RECONCILING TUMOR HETEROGENEITY IN GLIOBLASTOMA USING A PATHWAY-BASED APPROACH

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii28-ii28
Author(s):  
Alvaro Alvarado ◽  
Kaleab Tessema ◽  
Kunal Patel ◽  
Riki Kawaguchi ◽  
Richard Everson ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Patient Survival ◽  
Molecular Subtype ◽  
Gene List ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Molecular Architecture ◽  
Survival Pathways ◽  
Cancer Genome Atlas

Abstract Despite efforts to gain a deeper understanding of its molecular architecture, glioblastoma (GBM) remains uniformly fatal. While genome-based molecular subtyping has revealed that GBMs may be parsed into several molecularly distinct categories, this insight has yielded little progress towards extending patient survival. In particular, the great phenotypic heterogeneity of GBM – both inter and intratumorally – has hindered therapeutic efforts. To this end, we interrogated tumor samples using a pathway-based approach to resolve tumoral heterogeneity. Gene set enrichment analysis (GSEA) was applied to gene expression data and used to provide an overview of each sample that can be compared to other samples by generating sample clusters based on overall patterns of enrichment. The Cancer Genome Atlas (TCGA) samples were clustered using the canonical and oncogenic signatures and in both cases the clustering was distinct from the molecular subtype previously reported and clusters were informative of patient survival. We also analyzed single cell RNA sequencing datasets and uniformly found two clusters of cells enriched for cell cycle regulation and survival pathways. We have validated our approach by generating gene lists from common elements found in the top contributing genesets for a particular cluster and testing the top targets in appropriate gliomasphere patient-derived lines. Samples enriched for cell cycle related genesets showed a decrease in sphere formation capacity when E2F1, out top target, was silenced and when treated with fulvestrant and calcitriol, which were identified as potential drugs targeting this genelist. Conversely, no changes were observed in samples not enriched for this gene list. Finally, we interrogated spatial heterogeneity and found higher enrichment of the proliferative signature in contrast enhancing compared with non-enhancing regions. Our studies relate inter- and intratumoral heterogeneity to critical cellular pathways dysregulated in GBM, with the ultimate goal of establishing a pipeline for patient- and tumor-specific precision medicine.

scholarly journals Development of a Novel Prognostic Signature Based on Antigen Processing and Presentation in Patients with Breast Cancer

2021 ◽  
Vol 27 ◽  
Author(s):  
Aoshuang Qi ◽  
Mingyi Ju ◽  
Yinfeng Liu ◽  
Jia Bi ◽  
Qian Wei ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Antigen Processing ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
Gene Set ◽  
Antigen Processing And Presentation

Background: Complex antigen processing and presentation processes are involved in the development and progression of breast cancer (BC). A single biomarker is unlikely to adequately reflect the complex interplay between immune cells and cancer; however, there have been few attempts to find a robust antigen processing and presentation-related signature to predict the survival outcome of BC patients with respect to tumor immunology. Therefore, we aimed to develop an accurate gene signature based on immune-related genes for prognosis prediction of BC.Methods: Information on BC patients was obtained from The Cancer Genome Atlas. Gene set enrichment analysis was used to confirm the gene set related to antigen processing and presentation that contributed to BC. Cox proportional regression, multivariate Cox regression, and stratified analysis were used to identify the prognostic power of the gene signature. Differentially expressed mRNAs between high- and low-risk groups were determined by KEGG analysis.Results: A three-gene signature comprising HSPA5 (heat shock protein family A member 5), PSME2 (proteasome activator subunit 2), and HLA-F (major histocompatibility complex, class I, F) was significantly associated with OS. HSPA5 and PSME2 were protective (hazard ratio (HR) < 1), and HLA-F was risky (HR > 1). Risk score, estrogen receptor (ER), progesterone receptor (PR) and PD-L1 were independent prognostic indicators. KIT and ACACB may have important roles in the mechanism by which the gene signature regulates prognosis of BC.Conclusion: The proposed three-gene signature is a promising biomarker for estimating survival outcomes in BC patients.

scholarly journals High RPS27A Expression Predicts Poor Prognosis in Patients With HPV Type 16 Cervical Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Qiming Wang ◽  
Yan Cai ◽  
Xuewen Fu ◽  
Liang Chen
Keyword(s):  
Cervical Cancer ◽  
Poor Prognosis ◽  
Biological Significance ◽  
Enrichment Analysis ◽  
Hpv Infection ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Protein Protein Interaction ◽  
Cervical Cancer Cells ◽  
Cancer Genome Atlas

In recent years, the incidence and the mortality rate of cervical cancer have been gradually increasing, becoming one of the major causes of cancer-related death in women. In particular, patients with advanced and recurrent cervical cancers present a very poor prognosis. In addition, the vast majority of cervical cancer cases are caused by human papillomavirus (HPV) infection, of which HPV16 infection is the main cause and squamous cell carcinoma is the main presenting type. In this study, we performed screening of differentially expressed genes (DEGs) based on The Cancer Genome Atlas (TCGA) database and GSE6791, constructed a protein–protein interaction (PPI) network to screen 34 hub genes, filtered to the remaining 10 genes using the CytoHubba plug-in, and used survival analysis to determine that RPS27A was most associated with the prognosis of cervical cancer patients and has prognostic and predictive value for cervical cancer. The most significant biological functions and pathways of RPS27A enrichment were subsequently investigated with gene set enrichment analysis (GSEA), and integration of TCGA and GTEx database analyses revealed that RPS27A was significantly expressed in most cancer types. In this study, our analysis revealed that RPS27A can be used as a prognostic biomarker for HPV16 cervical cancer and has biological significance for the growth of cervical cancer cells.

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