scholarly journals Comprehensive Characterization of Transforming Growth Factor Beta Receptor 1 in Stomach Adenocarcinoma Identifies a Prognostic Signature for Predicting Clinical Outcomes and Immune Infiltrates

2021 ◽  
Author(s):  
Yi He ◽  
Haiyang Zhang ◽  
Yan Zhang ◽  
Peiyun Wang ◽  
Kegan Zhu ◽  
...  
Keyword(s):  
Receiver Operating Characteristic ◽  
Signaling Pathway ◽  
Operating Characteristic ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Prognostic Signature ◽  
Pathologic Stage ◽  
Stomach Adenocarcinoma ◽  
Receiver Operating

Abstract Background: Stomach adenocarcinoma (STAD) is the common cancer and ranks third leading cause of cancer death worldwide. TGF‑β receptor 1 (TGFBR1), serving important roles in the TGF‑β family, the mechanisms whereby TGFβ2 governs tumor progression, immune cell infiltration and its correlation with tumor microenvironment (TME) in STAD remains unintelligible. Methods: First, we used the data in the TCGA, GEPIA, and HPA databases to explore the expression level of TGFBR1 in STAD, the correlation between TGFBR1 expression and the clinical features of STAD, its impact on the survival of STAD. Subsequently, a receiver operating characteristic (ROC) curve and nomogram were constructed and LASSO (the Least Absolute Shrinkage and Selection Operator)-selected features were used to build the TGFBR1 prognostic signature. Moreover, GSEA enrichment analysis is used to find the potential molecular mechanism of TGFBR1 to promote the malignant process of STAD. Finally, we further explored the influence of theTGFBR1 expression on the immune microenvironment of STAD patients through the TIMER2.0 and GEPIA database.Results: In our study, TGFBR1 expression was significantly elevated in patients with STAD and positively co-expression with pathologic stage, lymph node metastases (LNM) stage and histopathological grade of STAD. LASSO-selected features were used to build the TGFBR1 prognostic signature. 9 factors with non-zero coefficients were identified. The corresponding risk scores were computed, according to the following formula: Risk score = (-0.2914) *DIXDC1+ (0.1113) *STON1-GTF2A1L+(0.3092) *FERMT2+(-0.0146) *BHMT2+(0.1798) *ABCC9+(0.068) *MSRB3+(-0.1007) *SYNC+(-0.0891) *SORBS1+(0.0828) *TGFBR1.Survival analysis revealed that patients with high TGFBR1 had shorter OS, FP, and PPS. Multivariate Cox analysis revealed TGFBR1 was an independent prognostic factor for OS in STAD. The receiver operating characteristic (ROC) analysis suggested high diagnostic value with the area under curve (AUC) of TGFBR1 was 0.739, and a prognostic nomogram involving age, T, N, M classification, pathologic stage, primary therapy outcome, histologic grade and TGFBR1 to predict the 1, 3, 5-year OS was constructed. GSEA revealed that high TGFBR1 expression was correlated with pathway in cancer, MAPK signaling pathway, NOTCH signaling pathway, focal adhesion and VEGF-C production. ssGSEA showed that TGFBR1 is correlated with NK cells, Tem and Th17 cells. Furthermore, elevated TGFBR1 expression was found to be significantly correlated with several immune checkpoint and immune markers associated with immune cell subsets. Conclusion: In summary, TGFBR1 could be a prognostic biomarker and an important regulator of immune cell infiltration in STAD. The present study revealed the probable underlying molecular mechanisms of TGFBR1 in STAD and provided a potential target for improving the prognosis.

scholarly journals Integrated Transcriptional Profiling Analysis and Immune-Related Risk Model Construction for Intracranial Aneurysm Rupture

2021 ◽  
Vol 15 ◽  
Author(s):  
Dezhi Shan ◽  
Xing Guo ◽  
Guozheng Yang ◽  
Zheng He ◽  
Rongrong Zhao ◽  
...  
Keyword(s):  
Immune Response ◽  
Inflammatory Response ◽  
Signaling Pathway ◽  
Immune Cell ◽  
Risk Model ◽  
Enrichment Analysis ◽  
Cell Infiltration ◽  
Enzyme Linked Immunosorbent Assay ◽  
Immune Cell Infiltration ◽  
Related Risk

Intracranial aneurysms (IAs) may cause lethal subarachnoid hemorrhage upon rupture, but the molecular mechanisms are poorly understood. The aims of this study were to analyze the transcriptional profiles to explore the functions and regulatory networks of differentially expressed genes (DEGs) in IA rupture by bioinformatics methods and to identify the underlying mechanisms. In this study, 1,471 DEGs were obtained, of which 619 were upregulated and 852 were downregulated. Gene enrichment analysis showed that the DEGs were mainly enriched in the inflammatory response, immune response, neutrophil chemotaxis, and macrophage differentiation. Related pathways include the regulation of actin cytoskeleton, leukocyte transendothelial migration, nuclear factor κB signaling pathway, Toll-like receptor signaling pathway, tumor necrosis factor signaling pathway, and chemokine signaling pathway. The enrichment analysis of 20 hub genes, subnetworks, and significant enrichment modules of weighted gene coexpression network analysis showed that the inflammatory response and immune response had a causal relationship with the rupture of unruptured IAs (UIAs). Next, the CIBERSORT method was used to analyze immune cell infiltration into ruptured IAs (RIAs) and UIAs. Macrophage infiltration into RIAs increased significantly compared with that into UIAs. The result of principal component analysis revealed that there was a difference between RIAs and UIAs in immune cell infiltration. A 4-gene immune-related risk model for IA rupture (IRMIR), containing CXCR4, CXCL3, CX3CL1, and CXCL16, was established using the glmnet package in R software. The receiver operating characteristic value revealed that the model represented an excellent clinical situation for potential application. Enzyme-linked immunosorbent assay was performed and showed that the concentrations of CXCR4 and CXCL3 in serum from RIA patients were significantly higher than those in serum from UIA patients. Finally, a competing endogenous RNA network was constructed to provide a potential explanation for the mechanism of immune cell infiltration into IAs. Our findings highlighted the importance of immune cell infiltration into RIAs, providing a direction for further research.

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.

scholarly journals The prognostic value of a tumor microenvironment-based immune cell infiltration score model in colon cancer

2021 ◽  
Author(s):  
Xiaofen Pan ◽  
Xingkui Tang ◽  
Minling Liu ◽  
Xijun Luo ◽  
Mengyuan Zhu ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Signaling Pathway ◽  
Immune Cells ◽  
Evaluation System ◽  
Prognostic Value ◽  
Immune Cell ◽  
Wnt Signaling Pathway ◽  
Mapk Signaling ◽  
Cell Infiltration ◽  
Immune Cell Infiltration

Abstract BackgroundTumor microenvironment consists of tumor cells, immune cells and other matric components. Tumor infiltration immune cells are associated with prognosis. But all the current prognosis evaluation system dose not take tumor immune cells other matrix component into consideration. In the current study, we aimed to construct a prognosis predictive model based on tumor microenvironment.MethodCIBERSORT and ESTIMATE algorithms were used to reveal the immune cell infiltration landscape of colon cancer. Patients were classified into three clusters by ConsensusClusterPlus algorithm. Immune cell infiltration (ICI) scores of each patient were determine by principal-component analysis. Patients were divided to high and low ICI score groups. Survival, gene expression and somatic mutation of the two groups were compared.ResultsPatients with no lymph node invasion, no metastasis, T1-2 disease and stage I-II had higher ICI scores. Calcium signaling pathway, leukocyte transendothelial migration pathway, MAPK signaling pathway, TGF β pathway, and WNT signaling pathway were enriched in high ICI score group. Immune-checkpoint genes and immune-activity associated genes were significantly decreased in high ICI score. Patients in high ICI score group had better survival than low ICI score group. Prognostic value of ICI score was independent of TMB.ConclusionICI score might serve as an independent prognostic biomarker in colon cancer.

scholarly journals Characterization of the immune cell infiltration landscape in head and neck squamous cell carcinoma to aid immunotherapy

2020 ◽  
Author(s):  
Xinhai Zhang ◽  
Tielou Chen ◽  
Boxin Zhang
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Signaling Pathway ◽  
Squamous Cell ◽  
Immune Cell ◽  
Neck Squamous Cell Carcinoma ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Stromal Component

Abstract Background: The tumor microenvironment chiefly consists of tumor cells, and tumor-infiltrating immune cells admixed with the stromal component. The recent clinical trial has shown that the tumor immune cell infiltration is correlated with the sensitivity to immunotherapy and the prognosis of head and neck squamous cell carcinoma (HNSC). However, to date, the immune infiltrative landscape of HNSC has not yet been elucidated. Methods: We proposed two computational algorithms to unravel the immune infiltration landscape of 1029 HNSC patients. The Boruta algorithm and principal component algorithms (PCA) were employed to quantify three immune cell infiltration gene subtypes categorized as per the immune cell infiltrations pattern. Results: The high ICI score subtype was characterized by a higher tumor mutation burden (TMB) and the immune-activated signaling pathway. However, a low ICI score subtype was categorized as per the activation of immunosuppressive signaling pathways such as TGF-BETA, WNT signaling pathway, and lower TMB. Two immunotherapy cohorts confirmed patients with higher ICI score demonstrated significant therapeutic advantages and clinical benefits.Conclusions: This demonstrated that the ICI score could serve as an effective prognostic biomarker and predictive indicator for immunotherapy. A comprehensive understanding of the HNSC immune landscape might help in tailoring immunotherapeutic strategies for different patients.

scholarly journals The Prognostic Value of a Tumor Microenvironment-Based Immune Cell Infiltration Score Model in Colon Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Xingkui Tang ◽  
Minling Liu ◽  
Xijun Luo ◽  
Mengyuan Zhu ◽  
Shan Huang ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Tumor Microenvironment ◽  
Signaling Pathway ◽  
Prognostic Value ◽  
Immune Cell ◽  
Wnt Signaling Pathway ◽  
Mapk Signaling ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Score Model

The current study aimed to construct a prognostic predictive model based on tumor microenvironment. CIBERSORT and ESTIMATE algorithms were used to reveal the immune cell infiltration (ICI) landscape of colon cancer. Patients were classified into three clusters by ConsensusClusterPlus algorithm. ICI scores of each patient were determined by principal component analysis. Patients were divided into high and low ICI score groups. Survival, gene expression, and somatic mutation of the two groups were compared. We found that patients with no lymph node invasion, no metastasis, T1–2 disease, and stage I–II had higher ICI scores. Calcium signaling pathway, leukocyte transendothelial migration pathway, MAPK signaling pathway, TGF β pathway, and Wnt signaling pathway were enriched in the high ICI score group. Immune-checkpoint and immune-activity associated genes were decreased in high ICI score patients. Patients in the high ICI score group had better survival. Prognostic value of ICI score was independent of tumor mutational burden (TMB). The ICI score model constructed in the current study may serve as an independent prognostic biomarker in colon cancer.

Identification of an Immune-Related Prognostic Signature Associated with Immune Infiltration in Melanoma

2020 ◽  
Author(s):  
Nian Liu ◽  
Zijian Liu ◽  
Xinxin Liu ◽  
Xiaoru Duan ◽  
Yuqiong Huang ◽  
...  
Keyword(s):  
Immune Cell ◽  
Underlying Mechanism ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Prognostic Signature ◽  
Immune Infiltration ◽  
Mutation Burden ◽  
Melanoma Prognosis ◽  
Melanoma Patients ◽  
Immune Related Genes

Abstract Background: Melanoma is the leading cause of cancer-related death among skin tumors, with an increasing incidence worldwide. Few studies have effectively investigated the significance of an immune-related genes (IRGs) signature for melanoma prognosis. Methods: Here, we constructed an IRGs prognostic signature using bioinformatics methods and evaluated and validated its predictive capability. Then, immune cell infiltration and tumor mutation burden (TMB) landscapes associated with this signature in melanoma were analyzed comprehensively. Results: With the 10-IRG prognostic signature, melanoma patients in the low-risk group showed better survival with distinct features of high immune cell infiltration and TMB. Importantly, melanoma patients in this subgroup were significantly responsive to MAGE-A3 in the validation cohort. Conclusions: This immune-related prognostic signature is thus a reliable tool to predict melanoma prognosis; as the underlying mechanism of this signature is associated with immune infiltration and mutation burden, it might reflect the benefit of immunotherapy to patients.

scholarly journals Dissecting the Role of N6-Methylandenosine-Related Long Non-coding RNAs Signature in Prognosis and Immune Microenvironment of Breast Cancer

2021 ◽  
Vol 9 ◽  
Author(s):  
Jinguo Zhang ◽  
Benjie Shan ◽  
Lin Lin ◽  
Jie Dong ◽  
Qingqing Sun ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Value ◽  
Immune Cell ◽  
Roc Curves ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Consensus Clustering ◽  
Prognostic Signature ◽  
Non Coding Rnas

Breast cancer (BC) represents a molecularly and clinically heterogeneous disease. Recent progress in immunotherapy has provided a glimmer of hope for several BC subtypes. The relationship between N6-methyladenosine (m6A) modification and long non-coding RNAs (LncRNAs) is still largely unexplored in BC. Here, with the intention to dissect the landscape of m6A-related lncRNAs and explore the immunotherapeutic value of the m6A-related lncRNA signature, we identified m6A-related lncRNAs by co-expression analysis from The Cancer Genome Atlas (TCGA) and stratified BC patients into different subgroups. Furthermore, we generated an m6A-related lncRNA prognostic signature. Four molecular subtypes were identified by consensus clustering. Cluster 3 preferentially had favorable prognosis, upregulated immune checkpoint expression, and high level of immune cell infiltration. Twenty-one m6A-related lncRNAs were applied to construct the m6A-related lncRNA model (m6A-LncRM). Survival analysis and receiver operating characteristic (ROC) curves further confirmed the prognostic value and prediction performance of m6A-LncRM. Finally, high- and low-risk BC subgroups displayed significantly different clinical features and immune cell infiltration status. Overall, our study systematically explored the prognostic value of the m6A-related LncRNAs and identified a high immunogenicity BC subtype. The proposed m6A-related LncRNA model might serve as a robust prognostic signature and attractive immunotherapeutic targets for BC treatment.

scholarly journals Development of an Immune-Related LncRNA Prognostic Signature for Glioma

2021 ◽  
Vol 12 ◽  
Author(s):  
Yudong Cao ◽  
Hecheng Zhu ◽  
Jun Tan ◽  
Wen Yin ◽  
Quanwei Zhou ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Clinical Outcome ◽  
Immune Cell ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Immune Infiltration

IntroductionGlioma is the most common primary cancer of the central nervous system with dismal prognosis. Long noncoding RNAs (lncRNAs) have been discovered to play key roles in tumorigenesis in various cancers, including glioma. Because of the relevance between immune infiltrating and clinical outcome of glioma, identifying immune-related lncRNAs is urgent for better personalized management.Materials and methodsSingle-sample gene set enrichment analysis (ssGSEA) was applied to estimate immune infiltration, and glioma samples were divided into high immune cell infiltration group and low immune cell infiltration group. After screening differentially expressed lncRNAs in two immune groups, least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to construct an immune-related prognostic signature. Additionally, we explored the correlation between immune infiltration and the prognostic signature.ResultsA total of 653 samples were appropriate for further analyses, and 10 lncRNAs were identified as immune-related lncRNAs in glioma. After univariate Cox regression and LASSO Cox regression analysis, six lncRNAs were identified to construct a prognostic signature for glioma, which could be taken as independent prognostic factors in both univariate and multivariate Cox regression analyses. Moreover, risk score was significantly correlated with all the 29 immune-related checkpoint expression (p < 0.05) in ssGSEA except neutrophils (p = 0.43).ConclusionThe study constructed an immune-related prognostic signature for glioma, which contributed to improve clinical outcome prediction and guide immunotherapy.

scholarly journals Ferroptosis Regulators and Tumor Microenvironment Immune Cell Infiltration Characterization in Adrenocortical Carcinoma

2022 ◽  
Author(s):  
Chengquan Shen ◽  
Jing Liu ◽  
Ye Liang ◽  
Zhijuan Liang ◽  
Liping Wang ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Signaling Pathway ◽  
Immune Checkpoint ◽  
Adrenocortical Carcinoma ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Genes Expression ◽  
Receptor Signaling Pathway ◽  
Checkpoint Genes

Abstract Background Adrenocortical carcinoma (ACC) is a rare disease with a poor prognosis and lacking effective systemic treatment options. Recent studies showed that ferroptosis play a prominent role in the initiation and development of cancer. Nonetheless, the potential roles of ferroptosis regulators in the prognosis and tumor microenvironment immunomodulator factors expression remain not fully study. Methods TCGA and GEO ACC datasets were used to investigate the relationship between ferroptosis regulators with prognosis and clinical features. Consensus clustering analysis was performed to divided ACC patients into different ferroptosis subgroups. A ferroptosis scoring system was established for individual ACC using principal component analysis algorithms. The correlation between ferroptosis score and tumor microenvironment immune cell infiltration was analyzed. Results Twenty ferroptosis regulators were differentially expressed in ACC and 17 ferroptosis regulators were closely related to the prognosis of ACC. Three ferroptosis subgroups (Cluster A, B, and C) were determined based on the expression of ferroptosis regulators. Cluster C is preferentially associated with favorable OS, PFS, upregulated antigen-presenting genes expression, and higher immune cell infiltration. GSEA also indicated that Cluster C was prominently related to immune fully activation including chemokine signaling pathway, natural killer cell-mediated cytotoxicity, T cell receptor signaling pathway, and Toll-like receptor signaling pathway. A ferroptosis scoring system was constructed and it could serve as an independent prognostic factor for ACC. The ferroptosis scores were significantly correlated with TMB, immune-checkpoint genes expression, and tumor microenvironment immune cell infiltration in ACC. Further analyses indicated that the ferroptosis score integrated with TMB, immune-checkpoint genes expression, and CD4+ T cell infiltration, could predict the prognosis of ACC. Furthermore, a nomogram was constructed to monitor the prognosis of individual ACC patient. RNA isolation and reverse transcription‑quantitative PCR (RT-qPCR) demonstrated significant differences in the expression levels of ACSL4, FANCD2 and SLC7A1 between ACC and normal tissues. Conclusion Our study demonstrated ferroptosis regulators were significantly associated with the prognosis, clinical characteristics, immune-checkpoint genes expression, and tumor microenvironment immune cell infiltration in ACC. This current study provided comprehensive evidence for further research on ferroptosis regulators in ACC and provides new enlightenment for epigenetic regulation of antitumor immune response.

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