scholarly journals Identification and development of a novel invasion-related gene signature for prognosis prediction in colon adenocarcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jiahua Liu ◽  
Chunhui Jiang ◽  
Chunjie Xu ◽  
Dongyang Wang ◽  
Yuguang Shen ◽  
...  
Keyword(s):  
T Cells ◽  
External Validation ◽  
Colon Adenocarcinoma ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Immune Infiltration ◽  
Prognosis Prediction ◽  
Protein Levels ◽  
Limma Package ◽  
Cox Analysis

AbstractThe overall survival of metastatic colon adenocarcinoma (COAD) remains poor, so it is important to explore the mechanisms of metastasis and invasion. This study aimed to identify invasion-related genetic markers for prognosis prediction in patients with COAD. Three molecular subtypes (C1, C2, and C3) were obtained based on 97 metastasis-related genes in 365 COAD samples from The Cancer Genome Atlas (TCGA). A total of 983 differentially expressed genes (DEGs) were identified among the different subtypes by using the limma package. A 6-gene signature (ITLN1, HOXD9, TSPAN11, GPRC5B, TIMP1, and CXCL13) was constructed via Lasso-Cox analysis. The signature showed strong robustness and could be used in the training, testing, and external validation (GSE17537) cohorts with stable predictive efficiency. Compared with other published signatures, our model showed better performance in predicting outcomes. Pan-cancer expression analysis results showed that ITLN1, TSPAN11, CXCL13, and GPRC5B were downregulated and TIMP1 was upregulated in most tumor samples, including COAD, which was consistent with the results of the TCGA and GEO cohorts. Western blot analysis and immunohistochemistry were performed to validate protein expression. Tumor immune infiltration analysis results showed that TSPAN11, GPRC5B, TIMP1, and CXCL13 protein levels were significantly positively correlated with CD4+ T cells, macrophages, neutrophils, and dendritic cells. Further, the TIMP1 and CXCL13 proteins were significantly related to the tumor immune infiltration of CD8+ T cells. We recommend using our signature as a molecular prognostic classifier to assess the prognostic risk of patients with COAD.

scholarly journals Density of immunogenic antigens does not explain the presence or absence of the T-cell–inflamed tumor microenvironment in melanoma

2016 ◽  
Vol 113 (48) ◽  
pp. E7759-E7768 ◽  
Author(s):  
Stefani Spranger ◽  
Jason J. Luke ◽  
Riyue Bao ◽  
Yuanyuan Zha ◽  
Kyle M. Hernandez ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
T Cell ◽  
Tumor Microenvironment ◽  
Solid Tumors ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Immune Infiltration ◽  
Cancer Testis

Melanoma metastases can be categorized by gene expression for the presence of a T-cell–inflamed tumor microenvironment, which correlates with clinical efficacy of immunotherapies. T cells frequently recognize mutational antigens corresponding to nonsynonymous somatic mutations (NSSMs), and in some cases shared differentiation or cancer–testis antigens. Therapies are being pursued to trigger immune infiltration into non–T-cell–inflamed tumors in the hope of rendering them immunotherapy responsive. However, whether those tumors express antigens capable of T-cell recognition has not been explored. To address this question, 266 melanomas from The Cancer Genome Atlas (TCGA) were categorized by the presence or absence of a T-cell–inflamed gene signature. These two subsets were interrogated for cancer–testis, differentiation, and somatic mutational antigens. No statistically significant differences were observed, including density of NSSMs. Focusing on hypothetical HLA-A2+binding scores, 707 peptides were synthesized, corresponding to all identified candidate neoepitopes. No differences were observed in measured HLA-A2 binding between inflamed and noninflamed cohorts. Twenty peptides were randomly selected from each cohort to evaluate priming and recognition by human CD8+T cells in vitro with 25% of peptides confirmed to be immunogenic in both. A similar gene expression profile applied to all solid tumors of TCGA revealed no association between T-cell signature and NSSMs. Our results indicate that lack of spontaneous immune infiltration in solid tumors is unlikely due to lack of antigens. Strategies that improve T-cell infiltration into tumors may therefore be able to facilitate clinical response to immunotherapy once antigens become recognized.

scholarly journals Novel Epigenetic Eight-Gene Signature Predictive of Poor Prognosis and MSI-Like Phenotype in Human Metastatic Colorectal Carcinomas

Cancers ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 158
Author(s):  
Valentina Condelli ◽  
Giovanni Calice ◽  
Alessandra Cassano ◽  
Michele Basso ◽  
Maria Grazia Rodriquenz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Poor Prognosis ◽  
Cpg Island ◽  
Colon Adenocarcinoma ◽  
Gene Signature ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Cpg Island Methylator Phenotype ◽  
Prognostic Information ◽  
Global Methylation

Epigenetics is involved in tumor progression and drug resistance in human colorectal carcinoma (CRC). This study addressed the hypothesis that the DNA methylation profiling may predict the clinical behavior of metastatic CRCs (mCRCs). The global methylation profile of two human mCRC subgroups with significantly different outcome was analyzed and compared with gene expression and methylation data from The Cancer Genome Atlas COlon ADenocarcinoma (TCGA COAD) and the NCBI GENE expression Omnibus repository (GEO) GSE48684 mCRCs datasets to identify a prognostic signature of functionally methylated genes. A novel epigenetic signature of eight hypermethylated genes was characterized that was able to identify mCRCs with poor prognosis, which had a CpG-island methylator phenotype (CIMP)-high and microsatellite instability (MSI)-like phenotype. Interestingly, methylation events were enriched in genes located on the q-arm of chromosomes 13 and 20, two chromosomal regions with gain/loss alterations associated with adenoma-to-carcinoma progression. Finally, the expression of the eight-genes signature and MSI-enriching genes was confirmed in oxaliplatin- and irinotecan-resistant CRC cell lines. These data reveal that the hypermethylation of specific genes may provide prognostic information that is able to identify a subgroup of mCRCs with poor prognosis.

scholarly journals Transcriptome of Tumor-Infiltrating T Cells in Colorectal Cancer Patients Uncovered a Unique Gene Signature in CD4+ T Cells Associated with Poor Disease-Specific Survival

Vaccines ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 334
Author(s):  
Salman M. Toor ◽  
Varun Sasidharan Nair ◽  
Reem Saleh ◽  
Rowaida Z. Taha ◽  
Khaled Murshed ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
T Cells ◽  
T Cell Activation ◽  
Cd4 T Cells ◽  
Poor Prognosis ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Disease Specific Survival ◽  
Unique Gene ◽  
Disease Specific

Colorectal cancer (CRC) is influenced by infiltration of immune cell populations in the tumor microenvironment. While elevated levels of cytotoxic T cells are associated with improved prognosis, limited studies have reported associations between CD4+ T cells and disease outcomes. We recently performed transcriptomic profiling and comparative analyses of sorted CD4+ and CD8+ tumor-infiltrating lymphocytes (TILs) from bulk tumors of CRC patients with varying disease stages. In this study, we compared the transcriptomes of CD4+ with CD8+ TILs. Functional annotation pathway analyses revealed the downregulation of inflammatory response-related genes, while T cell activation and angiogenesis-related genes were upregulated in CD4+ TILs. The top 200 deregulated genes in CD4+ TILs were aligned with the cancer genome atlas (TCGA) CRC dataset to identify a unique gene signature associated with poor prognosis. Moreover, 69 upregulated and 20 downregulated genes showed similar trends of up/downregulation in the TCGA dataset and were used to calculate “poor prognosis score” (ppScore), which was significantly associated with disease-specific survival. High ppScore patients showed lower expression of Treg-, Th1-, and Th17-related genes, and higher expression of Th2-related genes. Our data highlight the significance of T cells within the TME and identify a unique candidate prognostic gene signature for CD4+ TILs in CRC patients.

Immune and clinical features of CD96 expression in glioma by large-scale analysis

2020 ◽  
Author(s):  
Qiang Zhang ◽  
Hua Zhong ◽  
Yinchun Fan ◽  
Qian Liu ◽  
Jiancheng Song ◽  
...  
Keyword(s):  
Immune Response ◽  
T Cells ◽  
Large Scale ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Immune Functions ◽  
Clinical Prognosis ◽  
Regulatory Pathways ◽  
Cox Analysis ◽  
Genome Atlas

Abstract Background: Immune checkpoints target regulatory pathways in T cells which enhance antitumor immune responses and elicit durable clinical responses . As a novel immune checkpoint, CD96 is an attractive key target for cancer immunotherapy. However, there is no integrative investigation of CD96 in glioma. Our study explored the relationship between CD96 expression and clinical prognosis in glioma. Methods: A total of 1,024 RNA and clinical data were enrolled in this study, including 325 samples from the Chinese Glioma Genome Atlas (CGGA) database and 699 samples from The Cancer Genome Atlas (TCGA) dataset. R language was used to perform statistical analysis and draw figures. Results: CD96 had a consistently positive relationship with glioblastoma and highly enriched in IDH-wildtype and mesenchymal subtype glioma. GO enrichment and GSVA analyses suggested that CD96 was more involved in immune functions, especially related to T cell-mediated immune response in glioma. Subsequent immune infiltration analysis manifes ted that CD96 was positively correlated with infiltrating levels of CD4+ T and CD8+ T cells, macrophages , neutrophils, and DCs in GBM and LGG. Additionally, CD96 was tightly associated with other immune checkpoints including PD-1 , CTLA-4 , TIGIT , and TIM-3 . Univariate and multivariate Cox analysis demonstrated that CD96 acts as an independent indicator of poor prognosis in glioma. Conclusion: CD96 expression was increased in malignant phenotype and negatively associated with overall survival (OS) in glioma. CD96 also showed a positive correlation with other immune checkpoints, immune response, and inflammatory activity. Our findings indicate that CD96 is a promising clinical target for further immunotherapeutic in glioma patients.

scholarly journals Evidence of Omics, Immune Infiltration, and Pharmacogenomic for SENP1 in the Pan-Cancer Cohort

2021 ◽  
Vol 12 ◽  
Author(s):  
Somayye Taghvaei ◽  
Farzaneh Sabouni ◽  
Zarrin Minuchehr
Keyword(s):  
Cell Cycle ◽  
T Cells ◽  
Cellular Response ◽  
Clinical Stage ◽  
Critical Role ◽  
Drug Analysis ◽  
The Cancer Genome Atlas ◽  
Immune Infiltration ◽  
Specific Protease ◽  
Approved Drugs

Sentrin specific-protease 1 (SENP1) is a protein involved in deSUMOylation that is almost overexpressed in cancer. SENP1 has a determinative role in the activation of transcription programs in the innate immune responses and the development B of and C lymphocytes. We found, SENP1 possibly plays a critical role in immune infiltration and acts as an expression marker in PAAD, ESCA, and THYM. CD4+ T cells, CD8+ T cells, and macrophages were more key-related immune cells, indicating that SENP1 might be introduced as a potential target for cancer immunotherapy. We further showed that dysregulation of SENP1 is powerfully associated with decreased patient survival and clinical stage. Total SENP1 protein also increases in cancer. SENP1 is also controlled by transcription factors (TFs) CREB1, KDM5A, REST, and YY1 that regulates apoptosis, cell cycle, cell proliferation, invasion, tumorigenesis, and metastasis. These TFs were in a positive correlation with SENP1. MiR-138–5p, miR-129-1-3p, and miR-129-2-3p also inhibit tumorigenesis through targeting of SENP1. The SENP1 expression level positively correlated with the expression levels of UBN1, SP3, SAP130, NUP98, NUP153 in 32 tumor types. SENP1 and correlated and binding genes: SAP130, NUP98, and NUP153 activated cell cycle. Consistent with this finding, drug analysis was indicated SENP1 is sensitive to cell cycle, apoptosis, and RTK signaling regulators. In the end, SENP1 and its expression-correlated and functional binding genes were enriched in cell cycle, apoptosis, cellular response to DNA damage stimulus. We found that the cell cycle is the main way for tumorigenesis by SENP1. SENP1 attenuates the effect of inhibitory drugs on the cell cycle. We also introduced effective FDA-Approved drugs that can inhibit SENP1. Therefore in the treatments in which these drugs are used, SENP1 inhibition is a suitable approach. This study supplies a wide analysis of the SENP1 across The Cancer Genome Atlas (CGA) cancer types. These results suggest the potential roles of SENP1 as a biomarker for cancer. Since these drugs and the drugs that cause to resistance are applied to cancer treatment, then these two class drugs can use to inhibition of SENP1.

scholarly journals Novel Hypoxia-Related Gene Signature for Risk Stratification and Prognosis in Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Quanxiao Li ◽  
Limin Jin ◽  
Meng Jin
Keyword(s):  
Hepatocellular Carcinoma ◽  
Risk Stratification ◽  
Risk Group ◽  
External Validation ◽  
Gene Signature ◽  
Cancer Genome ◽  
Low Risk ◽  
The Cancer Genome Atlas ◽  
Individual Risk ◽  
Tumor Node Metastasis Stage

Hepatocellular carcinoma (HCC) is the most common form of liver cancer with limited therapeutic options and low survival rate. The hypoxic microenvironment plays a vital role in progression, metabolism, and prognosis of malignancies. Therefore, this study aims to develop and validate a hypoxia gene signature for risk stratification and prognosis prediction of HCC patients. The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases were used as a training cohort, and one Gene Expression Omnibus database (GSE14520) was served as an external validation cohort. Our results showed that eight hypoxia-related genes (HRGs) were identified by the least absolute shrinkage and selection operator analysis to develop the hypoxia gene signature and demarcated HCC patients into the high- and low-risk groups. In TCGA, ICGC, and GSE14520 datasets, patients in the high-risk group had worse overall survival outcomes than those in the low-risk group (all log-rank P < 0.001). Besides, the risk score derived from the hypoxia gene signature could serve as an independent prognostic factor for HCC patients in the three independent datasets. Finally, a nomogram including the gene signature and tumor-node-metastasis stage was constructed to serve clinical practice. In the present study, a novel hypoxia signature risk model could reflect individual risk classification and provide therapeutic targets for patients with HCC. The prognostic nomogram may help predict individualized survival.

scholarly journals Identification of hepatocellular carcinoma prognostic markers based on 10-immune gene signature

2020 ◽  
Vol 40 (8) ◽  
Author(s):  
Kaifei Zhao ◽  
Lin Xu ◽  
Feng Li ◽  
Jin Ao ◽  
Guojun Jiang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Risk Prediction ◽  
Clinical Features ◽  
Risk Model ◽  
Risk Group ◽  
External Validation ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Immune Gene ◽  
Test Set

Abstract Background: Due to the heterogeneity of hepatocellular carcinoma (HCC), hepatocelluarin-associated differentially expressed genes were analyzed by bioinformatics methods to screen the molecular markers for HCC prognosis and potential molecular targets for immunotherapy. Methods: RNA-seq data and clinical follow-up data of HCC were downloaded from The Cancer Genome Atlas (TCGA) database. Multivariate Cox analysis and Lasso regression were used to identify robust immunity-related genes. Finally, a risk prognosis model of immune gene pairs was established and verified by clinical features, test set and Gene Expression Omnibus (GEO) external validation set. Results: A total of 536 immune-related gene (IRGs) were significantly associated with the prognosis of patients with HCC. Ten robust IRGs were finally obtained and a prognostic risk prediction model was constructed by feature selection of Lasso. The risk score of each sample is calculated based on the risk model and is divided into high risk group (Risk-H) and low risk group (Risk-L). Risk models enable risk stratification of samples in training sets, test sets, external validation sets, staging and subtypes. The area under the curve (AUC) in the training set and the test set were all >0.67, and there were significant overall suvival (OS) differences between the Risk-H and Risk-L samples. Compared with the published four models, the traditional clinical features of Grade, Stage and Gender, the model performed better on the risk prediction of HCC prognosis. Conclusion: The present study constructed 10-gene signature as a novel prognostic marker for predicting survival in patients with HCC.

scholarly journals A Novel Lactate Metabolism-Related Gene Signature for Predicting Clinical Outcome and Tumor Microenvironment in Hepatocellular Carcinoma

2022 ◽  
Vol 9 ◽  
Author(s):  
Yue Li ◽  
Huanye Mo ◽  
Shengli Wu ◽  
Xin Liu ◽  
Kangsheng Tu
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
Tumor Microenvironment ◽  
External Validation ◽  
Gene Signature ◽  
Metabolic Reprogramming ◽  
Lactate Metabolism ◽  
Related Gene ◽  
High Group ◽  
Cox Regression Analysis

Hepatocellular carcinoma (HCC) is the main subtype of primary liver cancer with high malignancy and poor prognosis. Metabolic reprogramming is a hallmark of cancer and has great importance on the tumor microenvironment (TME). As an abundant metabolite, lactate plays a crucial role in cancer progression and the immunosuppressive TME. Nonetheless, the potential roles of lactate in HCC remain unclear. In this study, we downloaded transcriptomic data of HCC patients with corresponding clinical information from the TCGA and ICGC portals. The TCGA-HCC dataset used as the training cohort, while the ICGC-LIRI-JP dataset was served as an external validation cohort. Cox regression analysis and the LASSO regression model were combined to construct the lactate metabolism-related gene signature (LMRGS). Then, we assessed the clinical significance of LMRGS in HCC. Besides, enriched molecular functions, tumor mutation burden (TMB), infiltrating immune cells, and immune checkpoint were comprehensively analyzed in different LMRGS subgroups. In total, 66 differentially expressed lactate metabolism-related genes (LMRGs) were screened. The functions of LMRGs were mainly enriched in mitochondrial activity and metabolic processes. The LMRGS comprised of six key LMRGs (FKTN, PDSS1, PET117, PUS1, RARS1, and RNASEH1) had significant clinical value for independently predicting the prognosis of HCC patients. The overall survival and median survival of patients in the LMRGS-high group were significantly shorter than in the LMRGS-low group. In addition, there were differences in TMB between the two LMRGS subgroups. The probability of genetic mutations was higher in the LMRGS-high group. Most importantly, the LMRGS reflected the TME characteristics. In the LMRGS-high group, the immune microenvironment presented a suppressed state, accompanied by more inhibitory immune cell infiltration, including follicular helper T cells and regulatory T cells. Additionally, the expression of inhibitory checkpoint molecules was much higher in the LMRGS-high group. Our study suggested that the LMRGS was a robust biomarker to predict the clinical outcomes and evaluate the TME of patients with HCC.

scholarly journals EVI2B Is a New Prognostic Biomarker in Metastatic Melanoma with IFNgamma Associated Immune Infiltration

Cancers ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 4110
Author(s):  
Satoru Yonekura ◽  
Kosuke Ueda
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Metastatic Melanoma ◽  
Prognostic Biomarker ◽  
Integration Site ◽  
Tumor Infiltrating Lymphocytes ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Immune Infiltration ◽  
Ifn Γ

Background: To assess the prognostic role and the antitumor immunological relevance of ecotropic viral integration site 2B (EVI2B) in metastatic melanoma. Methods: In this study, we integrated clinical data, mRNA expression data, and the distribution and fraction of tumor infiltrating lymphocytes (TILs) using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets (GSE65904 and GSE19234). Results: The univariate and multivariate analyses showed that higher gene expression of EVI2B was significantly associated with longer prognoses. The EVI2B-high melanoma tissue had favorable histological parameters such as a brisk global distribution pattern and clustering structure of TILs (i.e., Banfield and Raftery index) with enriched CD8+ T cells over regulatory T cells and increased cytotoxicity scores. In addition, EVI2B expression positively correlated with IFN-γ signature genes (CXCL10, CXCL9, HLA-DRA, IDO1, IFNG, and STAT1) and other various immunomodulatory genes. Conclusion: EVI2B is a novel prognostic biomarker with IFN-γ associated immune infiltration in metastatic melanoma.

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