scholarly journals INHBA is a Prognostic Biomarker and Correlated With Immune Cell Infiltration in Cervical Cancer

2022 ◽  
Vol 12 ◽  
Author(s):  
Kaidi Zhao ◽  
Yuexiong Yi ◽  
Zhou Ma ◽  
Wei Zhang
Keyword(s):  
Cervical Cancer ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
R Package ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Cancer Data ◽  
Pan Cancer ◽  
Geo Database

Background: Inhibin A (INHBA), a member of the TGF-β superfamily, has been shown to be differentially expressed in various cancer types and is associated with prognosis. However, its role in cervical cancer remains unclear.Methods: We aimed to demonstrate the relationship between INHBA expression and pan-cancer using The Cancer Genome Atlas (TCGA) database. Next, we validated INHBA expression in cervical cancer using the Gene Expression Omnibus (GEO) database, including GSE7803, GSE63514, and GSE9750 datasets. Enrichment analysis of INHBA was performed using the R package “clusterProfiler.” We analyzed the association between immune infiltration level and INHBA expression in cervical cancer using the single-sample gene set enrichment analysis (ssGSEA) method by the R package GSVA. We explored the association between INHBA expression and prognosis using the R package “survival”.Results: Pan-cancer data analysis showed that INHBA expression was elevated in 19 tumor types, including cervical cancer. We further confirmed that INHBA expression was higher in cervical cancer samples from GEO database and cervical cancer cell lines than in normal cervical cells. Survival prognosis analysis indicated that higher INHBA expression was significantly associated with reduced Overall Survival (p = 0.001), disease Specific Survival (p = 0.006), and Progression Free Interval (p = 0.001) in cervical cancer and poorer prognosis in other tumors. GSEA and infiltration analysis showed that INHBA expression was significantly associated with tumor progression and some types of immune infiltrating cells.Conclusion:INHBA was highly expressed in cervical cancer and was significantly associated with poor prognosis. Meanwhile, it was correlated with immune cell infiltration and could be used as a promising prognostic target for cervical cancer.

scholarly journals Comprehensive Analysis to Identify SPP1 as a Prognostic Biomarker in Cervical Cancer

2022 ◽  
Vol 12 ◽  
Author(s):  
Kaidi Zhao ◽  
Zhou Ma ◽  
Wei Zhang
Keyword(s):  
Cervical Cancer ◽  
Roc Curve ◽  
Immune Cell ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
R Package ◽  
Cancer Data ◽  
Immune Infiltration ◽  
Pan Cancer ◽  
Geo Database

Background:SPP1, secreted phosphoprotein 1, is a member of the small integrin-binding ligand N-linked glycoprotein (SIBLING) family. Previous studies have proven SPP1 overexpressed in a variety of cancers and can be identified as a prognostic factor, while no study has explored the function and carcinogenic mechanism of SPP1 in cervical cancer.Methods: We aimed to demonstrate the relationship between SPP1 expression and pan-cancer using The Cancer Genome Atlas (TCGA) database. Next, we validated SPP1 expression of cervical cancer in the Gene Expression Omnibus (GEO) database, including GSE7803, GSE63514, and GSE9750. The receiver operating characteristic (ROC) curve was used to evaluate the feasibility of SPP1 as a differentiating factor by the area under curve (AUC) score. Cox regression and logistic regression were performed to evaluate factors associated with prognosis. The SPP1-binding protein network was built by the STRING tool. Enrichment analysis by the R package clusterProfiler was used to explore potential function of SPP1. The single-sample GSEA (ssGSEA) method from the R package GSVA and TIMER database were used to investigate the association between the immune infiltration level and SPP1 expression in cervical cancer.Results: Pan-cancer data analysis showed that SPP1 expression was higher in most cancer types, including cervical cancer, and we got the same result in the GEO database. The ROC curve suggested that SPP1 could be a potential diagnostic biomarker (AUC = 0.877). High SPP1 expression was associated with poorer overall survival (OS) (P = 0.032). Further enrichment and immune infiltration analysis revealed that high SPP1 expression was correlated with regulating the infiltration level of neutrophil cells and some immune cell types, including macrophage and DC.Conclusion:SPP1 expression was higher in cervical cancer tissues than in normal cervical epithelial tissues. It was significantly associated with poor prognosis and immune cell infiltration. Thus, SPP1 may become a promising prognostic biomarker for cervical cancer patients.

scholarly journals HILPDA Is a Prognostic Biomarker and Correlates With Macrophage Infiltration in Pan-Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Chengdong Liu ◽  
Xiaohan Zhou ◽  
Hanyi Zeng ◽  
Dehua Wu ◽  
Li Liu
Keyword(s):  
Survival Data ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Clinical Prognosis ◽  
Cancer Data ◽  
Tumor Types ◽  
Pan Cancer

Background: The protein hypoxia-inducible lipid droplet-associated (HILPDA) is differentially expressed in various tumors. However, its role and correlation with immune cell infiltration in most tumors remain unclear.Methods: HILPDA expression was analyzed in pan-cancer data from The Cancer Genome Atlas (TCGA) database. The influence of HILPDA in clinical prognosis was evaluated using clinical survival data from TCGA. Enrichment analysis of HILPDA was conducted using the R package “clusterProfiler.” We downloaded the immune cell infiltration score of TCGA samples from published articles and analyzed the correlation between the magnitude of immune cell infiltration and HILPDA expression.Results: HILPDA was highly expressed and associated with worse overall survival, disease-specific survival, and progression-free interval in most tumor types. In addition, HILPDA expression was significantly associated with the glycolysis pathway and infiltration of immune cells. Tumor-associated macrophage (TAM) infiltration increased in tissues with high HILPDA expression in most tumor types. Immunosuppressive genes, such as PD-L1, PD-1, TGFB1, and TGFBR1 were positively correlated with HILPDA.Conclusions: Our study suggests that HILPDA is a marker of poor prognosis. High HILPDA may contribute to TAM infiltration and be associated with tumor immunosuppression status.

scholarly journals Pan-Cancer Analyses Reveal Oncogenic and Immunological Role of Dickkopf-1 (DKK1)

2021 ◽  
Vol 12 ◽  
Author(s):  
Shuang Gao ◽  
Ye Jin ◽  
Hongmei Zhang
Keyword(s):  
Wnt Signaling ◽  
Signaling Pathway ◽  
Immune Cell ◽  
Wnt Signaling Pathway ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Dickkopf 1 ◽  
Pan Cancer

WNT signaling pathway inhibitor Dickkopf-1 (DKK1) is related to cancer progression; however, its diagnostic and prognostic potential have not been investigated in a pan-cancer perspective. In this study, multiple bioinformatic analyses were conducted to evaluate therapeutic value of DKK1 in human cancers. The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) project served as data resources. The Wilcoxon rank test was performed to evaluate the expression difference of DKK1 between cancer tissues and normal tissues. A Kaplan-Meier curve and Cox regression were used for prognosis evaluation. Single-sample gene set enrichment analysis (ssGSEA) was used to evaluate the association of DKK1 expression with the immune cell infiltration. The potential function of DKK1 was explored by STRING and clusterProfiler. We found that the expression level of DKK1 is significantly different in different cancer types. Importantly, we demonstrated that DKK1 is an independent risk factor in ESCA, LUAD, MESO, and STAD. Further analysis revealed that DKK1 had a large effect on the immune cell infiltration and markers of certain immune cells, such as Th1 and Th2 cells. PPI network analysis and further pathway enrichment analysis indicated that DKK1 was mainly involved in the WNT signaling pathway. Our findings suggested that DKK1 might serve as a marker of prognosis for certain cancers by affecting the WNT signaling pathway and tumor immune microenvironment.

scholarly journals AHSA1 is a Prognostic Biomarker that Correlates with Macrophage Infiltration in Pan-Cancer

2021 ◽  
Author(s):  
Fulei Li ◽  
Chengdong Liu ◽  
Yanling Chen ◽  
Shasha Li ◽  
Lu Bai
Keyword(s):  
T Cells ◽  
Cd8 T Cells ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Cancer Data ◽  
Pan Cancer

Abstract Background: Activator of heat shock 90 kDa protein ATPase homolog 1 (AHSA1) is differentially expressed in several tumor types. However, its association with immune cell infiltration remains elusive. Methods: AHSA1 expression was analyzed using The Cancer Genome Atlas (TCGA) pan-cancer data and normal tissue expression data from Genotype-Tissue Expression (GTEx). The clinical prognostic role of AHSA1 in pan-cancer was investigated, and an enrichment analysis of AHSA1 was performed using the R package “clusterProfiler.” We downloaded data regarding the immune cell infiltration level of TCGA pan-cancer tissues and analyzed the association between immune cell infiltration and AHSA1 expression. Results: The results of TCGA pan-cancer data analysis revealed that AHSA1 was overexpressed and associated with poor survival in patients with cancer. Furthermore, the infiltration levels of tumor-associated macrophages (TAMs) were higher, while those of CD8+ T cells were lower, in the high AHSA1 expression group. Conclusions: Our study suggests that AHSA1 is an oncogene and a risk factor for patient survival in cancer. AHSA1 may contribute to high infiltration levels of TAMs and low infiltration levels of CD8+ T cells, thus indicating that high AHSA1 expression may be associated with the tumor immunosuppressive microenvironment.

scholarly journals ARID1A Is a Prognostic Biomarker and Associated with Immune Infiltrates in Hepatocellular Carcinoma

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
Yuanyuan Feng ◽  
Xinfang Tang ◽  
Changcheng Li ◽  
Ying Su ◽  
Xiaoyu Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Migration And Invasion ◽  
Risk Indicator ◽  
Immune Cell Infiltration

Objective. ARID1A has been discovered as a potential cancer biomarker. But its role in hepatocellular carcinoma (HCC) is subject to considerable dispute. Methods. The relationship between ARID1A and clinical factors was investigated. Clinicopathological variables related to overall survival in HCC subjects were identified using Cox and Kaplan–Meier studies. The connection between immune infiltrating cells and ARID1A expression was investigated using the tumor Genome Atlas (TCGA) dataset for gene set enrichment analysis (GSEA). Finally, a cell experiment was used to confirm it. Results. The gender and cancer topography (T) categorization of HCC were linked to increased ARID1A expression. Participants with advanced levels of ARID1A expression had a worse prognosis than someone with lower levels. ARID1A was shown to be a risk indicator of overall survival on its own. ARID1A expression is inversely proportional to immune cell infiltration. In vitro, decreasing ARID1A expression substantially slowed the cell cycle and decreased HCC cell proliferation, migration, and invasion. Conclusion. The expression of ARID1A could be used to predict the outcome of HCC. It is closely related to tumor immune cell infiltration.

scholarly journals RNA N6-Methyladenosine Regulator-Mediated Methylation Modifications Pattern and Immune Infiltration Features in Glioblastoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Yimin Pan ◽  
Kai Xiao ◽  
Yue Li ◽  
Yuzhe Li ◽  
Qing Liu
Keyword(s):  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Lasso Regression ◽  
Gene Set Enrichment ◽  
Clinical Prognosis ◽  
Prognostic Assessment ◽  
The Relationship

Glioblastoma (GBM) is a group of intracranial neoplasms with intra-tumoral heterogeneity. RNA N6-methyladenosine (m6A) methylation modification reportedly plays roles in immune response. The relationship between the m6A modification pattern and immune cell infiltration in GBM remains unknown. Utilizing expression data of GBM patients, we thoroughly explored the potential m6A modification pattern and m6A-related signatures based on 21 regulators. Thereafter, the m6A methylation modification-based prognostic assessment pipeline (MPAP) was constructed to quantitatively assess GBM patients’ clinical prognosis combining the Robustness and LASSO regression. Single-sample gene-set enrichment analysis (ssGSEA) was used to estimate the specific immune cell infiltration level. We identified two diverse clusters with diverse m6A modification characteristics. Based on differentially expressed genes (DEGs) within two clusters, m6A-related signatures were identified to establish the MPAP, which can be used to quantitatively forecast the prognosis of GBM patients. In addition, the relationship between 21 m6A regulators and specific immune cell infiltration was demonstrated in our study and the m6A regulator ELAVL1 was determined to play an important role in the anticancer response to PD-L1 therapy. Our findings indicated the relationship between m6A methylation modification patterns and tumor microenvironment immune cell infiltration, through which we could comprehensively understand resistance to multiple therapies in GBM, as well as accomplish precise risk stratification according to m6A-related signatures.

scholarly journals Cancer Stemness Associated With Prognosis and the Efficacy of Immunotherapy in Adrenocortical Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Xiaoxi Shi ◽  
Yuanlin Liu ◽  
Shuai Cheng ◽  
Haidi Hu ◽  
Jian Zhang ◽  
...  
Keyword(s):  
Adrenocortical Carcinoma ◽  
Immune Cell ◽  
Checkpoint Inhibitors ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Potential Biomarker ◽  
Lower Expression

BackgroundCancer stem cells (CSCs) have been proven to influence drug resistance, recurrence, and metastasis in tumors. Our study aimed to identify stemness-related prognostic biomarkers for new therapeutic strategies in adrenocortical carcinoma.MethodsRNA-seq data and clinical characteristics were downloaded from The Cancer Genome Atlas (TCGA). The stemness indexes, mDNAsi and mRNAsi, were calculated to classify all samples into low-score and high-score groups. Two algorithms, based on the R language, ESTIMATE and single-sample Gene Set Enrichment Analysis (ssGSEA) were used to assess the immune cell infiltration states of adrenocortical carcinoma patients. Weighted Gene Co-expression Network Analysis (WGCNA) was used to find genes that were related to the stemness of cancer. By bioinformatics methods, the correlations between biomarkers capable of predicting immune checkpoint inhibitors (ICIs) responses and stemness of cancer were explored.ResultsHigh-mRNAsi predicted shorter overall survival (OS) and a higher metastatic trend in adrenocortical carcinoma (ACC) patients. Compared with the low-mRNAsi group, the high-mRNAsi group had a lower ImmuneScore and StromalScroe. Twenty-two stemness-related prognostic genes were obtained by WGCNA, which focused on the function of the cell cycle and cell mitosis. Immune cell infiltration, especially CD8+T cell, increased in the low-mRNAsi group compared with the high-mRNAsi group. Lower expression of PD-L1, CTLA-4, and TIGHT was evaluated in the high-mRNAsi group.ConclusionsACC patients with high-mRNAsi have poor prognosis and less immune cell infiltration. Combined with the finding of lower expression of CTLA-4, TIGHT, and PD-L1 in the high-mRNAsi group, we came to the conclusion that stemness index is a potential biomarker to predict the effectiveness of ICIs.

scholarly journals Glycolysis-associated lncRNAs identify a subgroup of cancer patients with poor prognoses and a high-infiltration immune microenvironment

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Kuo-Hao Ho ◽  
Tzu-Wen Huang ◽  
Chwen-Ming Shih ◽  
Yi-Ting Lee ◽  
Ann-Jeng Liu ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Immune Cell ◽  
Molecular Subtypes ◽  
Differentially Expressed Gene ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Low Grade ◽  
Immune Cell Infiltration ◽  
Mesenchymal Transition ◽  
Cancer Data

Abstract Background Long noncoding (lnc)RNAs and glycolysis are both recognized as key regulators of cancers. Some lncRNAs are also reportedly involved in regulating glycolysis metabolism. However, glycolysis-associated lncRNA signatures and their clinical relevance in cancers remain unclear. We investigated the roles of glycolysis-associated lncRNAs in cancers. Methods Glycolysis scores and glycolysis-associated lncRNA signatures were established using a single-sample gene set enrichment analysis (GSEA) of The Cancer Genome Atlas pan-cancer data. Consensus clustering assays and genomic classifiers were used to stratify patient subtypes and for validation. Fisher’s exact test was performed to investigate genomic mutations and molecular subtypes. A differentially expressed gene analysis, with GSEA, transcription factor (TF) activity scoring, cellular distributions, and immune cell infiltration, was conducted to explore the functions of glycolysis-associated lncRNAs. Results Glycolysis-associated lncRNA signatures across 33 cancer types were generated and used to stratify patients into distinct clusters. Patients in cluster 3 had high glycolysis scores and poor survival, especially in bladder carcinoma, low-grade gliomas, mesotheliomas, pancreatic adenocarcinomas, and uveal melanomas. The clinical significance of lncRNA-defined groups was validated using external datasets and genomic classifiers. Gene mutations, molecular subtypes associated with poor prognoses, TFs, oncogenic signaling such as the epithelial-to-mesenchymal transition (EMT), and high immune cell infiltration demonstrated significant associations with cluster 3 patients. Furthermore, five lncRNAs, namely MIR4435-2HG, AC078846.1, AL157392.3, AP001273.1, and RAD51-AS1, exhibited significant correlations with glycolysis across the five cancers. Except MIR4435-2HG, the lncRNAs were distributed in nuclei. MIR4435-2HG was connected to glycolysis, EMT, and immune infiltrations in cancers. Conclusions We identified a subgroup of cancer patients stratified by glycolysis-associated lncRNAs with poor prognoses, high immune infiltration, and EMT activation, thus providing new directions for cancer therapy.

scholarly journals P4HA1, a Prognostic Biomarker that Correlates With Immune Infiltrates in Lung Adenocarcinoma and Pan-Cancer

2021 ◽  
Vol 9 ◽  
Author(s):  
Qi Zhao ◽  
Junfeng Liu
Keyword(s):  
Prognostic Value ◽  
Immune Cell ◽  
Prognostic Biomarker ◽  
Enrichment Analysis ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Pathway Enrichment Analysis ◽  
Immune Cell Infiltration ◽  
Pan Cancer

Objective: Prolyl 4-hydroxylase, alpha polypeptide I (P4HA1), a key enzyme in collagen synthesis, comprises two identical alpha subunits and two beta subunits. However, the immunomodulatory role of P4HA1 in tumor immune microenvironment (TIME) remains unclear. This study aimed to evaluate the prognostic value of P4HA1 in pan-cancer and explore the relationship between P4HA1 expression and TIME.Methods: P4HA1 expression, clinical features, mutations, DNA methylation, copy number alteration, and prognostic value in pan-cancer were investigated using the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression data. Pathway enrichment analysis of P4HA1 was performed using R package “clusterProfiler.” The correlation between immune cell infiltration level and P4HA1 expression was analyzed using three sources of immune cell infiltration data, including ImmuCellAI database, TIMER2 database, and a published work.Results: P4HA1 was substantially overexpressed in most cancer types. P4HA1 overexpression was associated with poor survival in patients. Additionally, we discovered that P4HA1 expression was positively associated with infiltration levels of immunosuppressive cells, such as tumor-associated macrophages, cancer-associated fibroblasts, nTregs, and iTregs, and negatively correlated with CD8+ T and NK cells in pan-cancer.Conclusions: Our results highlighted that P4HA1 might serve as a potential prognostic biomarker in pan-cancer. P4HA1 overexpression is indicative of an immunosuppressive microenvironment. P4HA1 may be a potential target of immunotherapy.

scholarly journals Comprehensive Analysis of the Immune and Prognostic Implication of COL6A6 in Lung Adenocarcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Yi Ma ◽  
Mantang Qiu ◽  
Haifa Guo ◽  
Haiming Chen ◽  
Jiawei Li ◽  
...  
Keyword(s):  
T Cell ◽  
Lung Adenocarcinoma ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Gene Copy ◽  
Immune Cell Infiltration ◽  
Term Survival

Collagen type VI alpha 6 chain (COL6A6), a novel collagen, has been considered as a tumor suppressor and therapeutic target in several tumors. However, the functional role of COL6A6 in immune cell infiltration and prognostic value in lung adenocarcinoma (LUAD) remains unknown. Here, we evaluated COL6A6 expression and its impact on survival among LUAD patients from The Cancer Genome Atlas (TCGA) and several other databases. COL6A6 was downregulated in LUAD tissues compared to normal tissues at both mRNA and protein levels. COL6A6 expression was negatively associated with pathological stage, tumor stage, and lymph node metastasis. High COL6A6 expression was a favorable prognostic factor in LUAD. Next, we explored the associations between COL6A6 expression and immune cell infiltration. COL6A6 expression was positively associated with the infiltration of B cells, T cells, neutrophils and dendritic cells. Additionally, the immune cell infiltration levels were associated with COL6A6 gene copy number in LUAD. Consistently, gene set enrichment analysis showed that various immune pathways were enriched in the LUAD samples with high COL6A6 expression, including pathways related to T cell activation and T cell receptor signaling. The impacts of COL6A6 on immune activity were further assessed by enrichment analysis of 50 COL6A6-associated immunomodulators. Thereafter, using Cox regression, we identified a seven-gene risk prediction signature based on the COL6A6-associated immunomodulators. The resulting risk score was an independent prognostic predictor in LUAD. Receiver operating characteristic curve analysis confirmed that the seven-gene signature had good prognostic accuracy in the TCGA-LUAD cohort and a Gene Expression Omnibus dataset. Finally, we constructed a clinical nomogram to predict long-term survival probabilities, and calibration curves verified its accuracy. Our findings highlight that COL6A6 is involved in tumor immunity, suggesting COL6A6 may be a potential immunotherapeutic target in LUAD. The proposed seven-gene signature is a promising prognostic biomarker in LUAD.

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