Enolase 1 Correlated With Cancer Progression and Immune-Infiltrating in Multiple Cancer Types: A Pan-Cancer Analysis

Enolase 1 (ENO1) is an oxidative stress protein expressed in endothelial cells. This study aimed to investigate the correlation of ENO1 with prognosis, tumor stage, and levels of tumor-infiltrating immune cells in multiple cancers. ENO1 expression and its influence on tumor stage and clinical prognosis were analyzed by UCSC Xena browser, Gene Expression Profiling Interactive Analysis (GEPIA), The Cancer Genome Atlas (TCGA), and GTEx Portal. The ENO1 mutation analysis was performed by cBio Portal, and demonstrated ENO1 mutation (1.8%) did not impact on tumor prognosis. The relationship between ENO1 expression and tumor immunity was analyzed by Tumor Immune Estimation Resource (TIMER) and GEPIA. The potential functions of ENO1 in pathways were investigated by Gene Set Enrichment Analysis. ENO1 expression was significantly different in tumor and corresponding normal tissues. ENO1 expression in multiple tumor tissues correlated with prognosis and stage. ENO1 showed correlation with immune infiltrates including B cells, CD8+ and CD4+ T cells, macrophages, neutrophils, and dendritic cells, and tumor purity. ENO1 was proved to be involved in DNA replication, cell cycle, apoptosis, glycolysis process, and other processes. These findings indicate that ENO1 is a potential prognostic biomarker that correlates with cancer progression immune infiltration.

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A Pan-Cancer Study: The Immunological and Prognostic Significance of Aberrant SPP1 Expression on Tumors

10.21203/rs.3.rs-855946/v1 ◽

2021 ◽

Author(s):

Tian peng Huang ◽

Wei Ye ◽

Xue jiao Lin

Keyword(s):

Tumor Immunity ◽

Cancer Progression ◽

Immune Cell ◽

Prognostic Significance ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Multiple Cancer ◽

Multiple Tumor ◽

Cancer Types

Abstract Background Secretory phosphoprotein 1 (SPP1) is a glyco-phosphoprotein that is widely expressed in a variety of cancer cells. Current studies have identified that SPP1 is differentially expressed in a variety of cancer cell species. However, there are few studies on the level of SPP1 expression in different types of cancer and its clinical significance. Methods In this study, we analyzed SPP1 levels and its significance in 33 different cancer types by using The Cancer Genome Atlas (TCGA) database. The study analyzed the correlation between SPP1 expression and tumor immunity. Results The results showed that SPP1 transcript levels were aberrantly expressed in most tumors. Univariate Cox analysis showed that SPP1 was strongly associated with Overall survival in multiple tumor types. We also found that SPP1 was significantly correlated with tumor immune microenvironment, tumor immune cells, and tumor infiltrating lymphocyte markers. The correlation of SPP1 with Tumor mutational load (TMB) and Microsatellite instability (MSI) also predicts its role in assessing the efficacy of immunotherapy. Gene set enrichment analysis of 33 cancer types provided further evidence for the relationship between SPP1 levels and cancer progression and immune cell infiltration. Conclusion our study concludes that SPP1 plays an important role in tumorigenesis and tumor immunity and can be used as a marker for the assessment of clinical indicators in multiple cancer types.

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Multiomic analysis of the function of SPOCK1 across cancers: an integrated bioinformatics approach

Journal of International Medical Research ◽

10.1177/0300060520962659 ◽

2021 ◽

Vol 49 (6) ◽

pp. 030006052096265

Author(s):

Jie Han ◽

Yihui Rong ◽

Xudong Gao

Keyword(s):

Gene Expression ◽

Cancer Progression ◽

Immune Cells ◽

Immune Cell ◽

Cancer Cell Line ◽

Enrichment Analysis ◽

Tissue Expression ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Normal Tissues

Objective To investigate SPARC (osteonectin), cwcv and kazal like domains proteoglycan 1 ( SPOCK1) gene expression across The Cancer Genome Atlas (TCGA) cancers, both in cancer versus normal tissues and in different stages across the cancer types. Methods This integrated bioinformatics study used data from several bioinformatics databases (Cancer Cell Line Encyclopedia, Genotype-Tissue Expression, TCGA, Tumor Immune Estimation Resource [TIMER]) to define the expression pattern of the SPOCK1 gene. A survival analysis was undertaken across the cancers. The search tool for retrieval of interacting genes (STRING) database was used to identify proteins that interacted with SPOCK1. Gene Set Enrichment Analysis was conducted to determine pathway enrichment. The TIMER database was used to explore the correlation between SPOCK1 and immune cell infiltration. Results This multiomic analysis showed that the SPOCK1 gene was expressed differently between normal tissues and tumours in several cancers and that it was involved in cancer progression. The overexpression of the SPOCK1 gene was associated with poor clinical outcomes. Analysis of gene expression and tumour-infiltrating immune cells showed that SPOCK1 correlated with several immune cells across cancers. Conclusions This research showed that SPOCK1 might serve as a new target for several cancer therapies in the future.

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Zic Family Member 2 (ZIC2): a Potential Diagnostic and Prognostic Biomarker for Pan-Cancer

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.631067 ◽

2021 ◽

Vol 8 ◽

Author(s):

Zhengtong Lv ◽

Lin Qi ◽

Xiheng Hu ◽

Miao Mo ◽

Huichuan Jiang ◽

...

Keyword(s):

Tumor Microenvironment ◽

Zinc Finger Protein ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Multiple Cancer ◽

Survival Prognosis ◽

Multiple Tumor ◽

Immune Related Genes ◽

Pan Cancer

Background: As a transcription factor, Zinc finger protein ZIC2 can interact with various DNAs and proteins. Current studies have shown that ZIC2 plays an oncogene role in various cancers. In this study, we systematically characterize the prevalence and predictive value of ZIC2 expression across multiple cancer types.Methods: We mined several public databases, including Oncomine, the Cancer Genome Atlas (TCGA), cBioPortal, Kaplan-Meier Plotter and PrognoScan to evaluated the differentially expressed ZIC2 between tumor samples and normal control samples in pan-cancner, and then explored the association between ZIC2 expression and patient survival, prognosis and clinicopathologic stage. We also analyzed the relationship between tumor mutation burden (TMB), microsatellite instability (MSI), tumor microenvironment, tumor- and immune-related genes and ZIC2 expression. Finally, we explored the potential signaling pathway mechanism through gene set enrichment analysis (GSEA).Results: ZIC2 expression was higher in most cancer tissues compared with adjacent normal tissues. High ZIC2 expression was associated with worse prognosis and a higher clinicopathologic stage. ZIC2 expression was strongly associated with the TMB, MSI, tumor microenvironment and tumor- and immune-related genes. The GSEA revealed that multiple tumor- and immune-related pathways were differentially enriched in ZIC2 high or low expression phenotype.Conclusion: ZIC2 expression may be a potential prognostic molecular biomarker of poor survival in pan-cancer and may act as an oncogene with a strong effect in the processes of tumorigenesis and progression.

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Comprehensive Analysis of ESRRA in Endometrial Cancer

Technology in Cancer Research & Treatment ◽

10.1177/1533033821992083 ◽

2021 ◽

Vol 20 ◽

pp. 153303382199208

Author(s):

Shufang Wang ◽

Xinlong Huo

Keyword(s):

Endometrial Cancer ◽

Protein Expression ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Expression Level ◽

Operating Characteristics ◽

Protein Expression Level ◽

Normal Tissues

Background: Estrogen-related receptor alpha (ESRRA) was reported to play an important role in multiple biological processes of neoplastic diseases. The roles of ESRRA in endometrial cancer have not been fully investigated yet. Methods: Expression data and clinicopathological data of patients with uteri corpus endometrial carcinoma (UCEC) were obtained from The Cancer Genome Atlas (TCGA). Comprehensive bioinformatics analysis was performed, including receiver operating characteristics (ROC) curve analysis, Kaplan-Meier survival analysis, gene ontology (GO) enrichment analysis, and Gene Set Enrichment Analysis (GSEA). Immunohistochemistry was used to detect the protein expression level of ESRRA and CCK-8 assay was performed to evaluate the effect of ESRRA on the proliferation ability. Results: A total of 552 UCEC tissues and 35 normal tissues were obtained from the TCGA database. The mRNA and protein expression level of ESRRA was highly elevated in UCEC compared with normal tissues, and was closely associated with poor prognosis. ROC analysis indicated a very high diagnostic value of ESRRA for patients with UCEC. GO and GSEA functional analysis showed that ESRRA might be mainly involved in cellular metabolism processes, in turn, tumorigenesis and progression of UCEC. Knockdown of ESRRA inhibited the proliferation of UCEC cells in vitro. Further immune cell infiltration demonstrated that ESRRA enhanced the infiltration level of neutrophil cell and reduced that of T cell (CD4+ naïve), NK cell, and cancer associated fibroblast (CAF). The alteration of immune microenvironment will greatly help in developing immune checkpoint therapy for UCEC. Conclusions: Our study comprehensively analyzed the expression level, clinical value, and possible mechanisms of action of ESRRA in UCEC. These findings showed that ESRRA might be a potential diagnostic and therapeutic target.

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Identification of the HMMR Gene as a Diagnostic and Prognostic Biomarker in Hepatocellular Carcinoma Based on Integrated Bioinformatics Analysis

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/5970085 ◽

2021 ◽

Vol 2021 ◽

pp. 1-8

Author(s):

Honglan Guo ◽

Qinqiao Fan

Keyword(s):

Hepatocellular Carcinoma ◽

Roc Curve ◽

Cox Regression ◽

Enrichment Analysis ◽

Cancer Genome ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Roc Curve Analysis ◽

Cox Regression Analysis ◽

Normal Tissues

Background. We aimed to investigate the expression of the hyaluronan-mediated motility receptor (HMMR) gene in hepatocellular carcinoma (HCC) and nonneoplastic tissues and to investigate the diagnostic and prognostic value of HMMR. Method. With the reuse of the publicly available The Cancer Genome Atlas (TCGA) data, 374 HCC patients and 50 nonneoplastic tissues were used to investigate the diagnostic and prognostic values of HMMR genes by receiver operating characteristic (ROC) curve analysis and survival analysis. All patients were divided into low- and high-expression groups based on the median value of HMMR expression level. Univariate and multivariate Cox regression analysis were used to identify prognostic factors. Gene set enrichment analysis (GSEA) was performed to explore the potential mechanism of the HMMR genes involved in HCC. The diagnostic and prognostic values were further validated in an external cohort from the International Cancer Genome Consortium (ICGC). Results. HMMR mRNA expression was significantly elevated in HCC tissues compared with that in normal tissues from both TCGA and the ICGC cohorts (all P values <0.001). Increased HMMR expression was significantly associated with histologic grade, pathological stage, and survival status (all P values <0.05). The area under the ROC curve for HMMR expression in HCC and normal tissues was 0.969 (95% CI: 0.948–0.983) in the TCGA cohort and 0.956 (95% CI: 0.932–0.973) in the ICGC cohort. Patients with high HMMR expression had a poor prognosis than patients with low expression group in both cohorts (all P < 0.001 ). Univariate and multivariate analysis also showed that HMMR is an independent predictor factor associated with overall survival in both cohorts (all P values <0.001). GSEA showed that genes upregulated in the high-HMMR HCC subgroup were mainly significantly enriched in the cell cycle pathway, pathways in cancer, and P53 signaling pathway. Conclusion. HMMR is expressed at high levels in HCC. HMMR overexpression may be an unfavorable prognostic factor for HCC.

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Clinical significance and biological mechanisms of glutathione S-transferase mu gene family in colon adenocarcinoma

BMC Medical Genetics ◽

10.1186/s12881-020-01066-2 ◽

2020 ◽

Vol 21 (1) ◽

Author(s):

Erna Guo ◽

Haotang Wei ◽

Xiwen Liao ◽

Liuyu Wu ◽

Xiaoyun Zeng

Keyword(s):

Gene Family ◽

Colon Adenocarcinoma ◽

Enrichment Analysis ◽

Clinical Information ◽

Underlying Mechanism ◽

Tumor Stage ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Glutathione S Transferase ◽

Low Expression

Abstract Background Colon adenocarcinoma (COAD) is the most common form of colon cancer. The glutathione S-transferase Mu (GSTM) gene belongs to the GST gene family, which functions in cell metabolism and detoxification. The relationship between GSTM and COAD and the underlying mechanism remain unknown. Methods Data extracted from The Cancer Genome Atlas included mRNA expression and clinical information such as gender, age, and tumor stage. Prognostic values of GSTM genes were identified by survival analysis. Function and mechanism of prognostic GSTM genes were identified by gene set enrichment analysis. A nomogram was used to predict the contribution of risk factors to the outcome of COAD patients. Results Low expression of GSTM1 and GSTM2 was related to favorable OS (adjusted P = 0.006, adjusted HR = 0.559, 95% CI = 0.367–0.849 and adjusted P = 0.002, adjusted HR = 0.519, 95% CI = 0.342–0.790, respectively) after adjusting for tumor stage. Enrichment analysis also showed that genes involved were related to cell cycle, metabolism, and detoxification processes, as well as the Wnt signaling and NF-κB pathways. Conclusions In conclusion, low expression of GSTM1 and GSTM2 were significantly associated with favorable prognosis in COAD. These two genes may serve as potential biomarkers of COAD prognosis.

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Down-regulation of DLG2 predicts an unfavorable prognosis and promotes the proliferation and migration of Hepatocellular Carcinoma.

10.21203/rs.3.rs-22758/v1 ◽

2020 ◽

Author(s):

Jiawei Gu ◽

Runqi Hong ◽

Gengming Niu ◽

Zhiqing Hu ◽

Tao Song ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Enrichment Analysis ◽

Underlying Mechanism ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Down Regulation ◽

Normal Tissues ◽

And Migration ◽

Proliferation And Migration

Abstract Background Discs large MAGUK scaffold protein 2 (DLG2), a member of the MAGUK family, has been associated with certain tumor suppressing processes. In this study, we aim to identify the prognosis value and specific function of DLG2 in hepatocellular carcinomas (HCCs). Methods Expression of DLG2 in HCCs and adjacent normal tissues (NTs) was analyzed with transcriptomic datasets from the Integrative Molecular Database of Hepatocellular Carcinoma (HCCDB) and immunohistochemical (IHC) staining of a tissue microarray (TMA). Prognostic roles of DLG2 in HCCs were investigated in the TMA cohort and validated in two cohorts from HCCDB. The in vitro activities of DLG2 were investigated in cultured HCC cells with lentiviruses. The underlying mechanism was explored using Gene Set Enrichment Analysis (GSEA) and gene-gene correlation analyses with The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset. Results The expression of DLG2 was significantly decreased in HCCs compared to that in NTs. Down-regulation of DLG2 in HCCs was associated with unfavorable prognosis. Overexpression of DLG2 inhibited, while knockdown of DLG2 prompted proliferation and migration of cultured HCCs. Mechanistically, DLG2 may inhibited cell growth of HCCs by interacting with key molecules that regulate cell cycles. Conclusion DLG2 inhibited HCC progression and may be a novel prognosis biomarker and therapeutic target for HCC.

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Immunoglobulin superfamily member 10 is a novel prognostic biomarker for breast cancer

PeerJ ◽

10.7717/peerj.10128 ◽

2020 ◽

Vol 8 ◽

pp. e10128

Author(s):

Mengxue Wang ◽

Meng Dai ◽

Yu-shen Wu ◽

Ziying Yi ◽

Yunhai Li ◽

...

Keyword(s):

Breast Cancer ◽

Quantitative Polymerase Chain Reaction ◽

Enrichment Analysis ◽

Clinical Information ◽

Tumor Stage ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Immunoglobulin Superfamily ◽

Qrt Pcr ◽

Mtorc1 Signaling

Background Immunoglobulin superfamily member 10 (IGSF10) is a member of the immunoglobulin superfamily that is expressed at high levels in both the gallbladder and ovary. Currently, the role and possible mechanism of IGSF10 in breast cancer remain unclear. Method By applying real-time quantitative polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC), the expression of IGSF10 in breast cancer cells and tissues was detected. We collected the clinical information from 700 patients with breast cancer in The Cancer Genome Atlas (TCGA), and analyzed the relationship between IGSF10 expression and the clinicopathological features and survival outcomes of these patients. The potential mechanisms and pathways associated with IGSF10 in breast cancer were explored by performing a gene set enrichment analysis (GSEA). Results According to TCGA data, qRT-PCR and IHC experiments, levels of the IGSF10 mRNA and protein were significantly decreased in breast cancer tissues. IGSF10 expression was significantly correlated with age, tumor size, and tumor stage. Moreover, shorter overall survival (OS) and relapse-free survival (RFS) correlated with lower IGSF10 expression, according to the survival analysis. The multivariate analysis identified that IGSF10 as an independent prognostic factor for the OS (hazard ratio (HR) = 1.793, 95% confidence interval (CI) [1.141–2.815], P = 0.011) and RFS (HR = 2.298, 95% CI [1.317–4.010], P = 0.003) of patients with breast cancer. Based on the GSEA, IGSF10 was involved in DNA repair, cell cycle, and glycolysis. IGSF10 was also associated with the PI3K/Akt/mTOR and mTORC1 signaling pathways. Conclusions This study revealed a clear relationship between IGSF10 expression and the tumorigenesis of breast cancer for the first time. Therefore, further studies are needed to understand the mechanism of IGSF10 in breast cancer.

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m6A RNA Methylation Regulator YTHDF1 Correlated With Immune Microenvironment Predicts Clinical Outcomes and Therapeutic Efficacy in Breast Cancer

Frontiers in Medicine ◽

10.3389/fmed.2021.667543 ◽

2021 ◽

Vol 8 ◽

Author(s):

Ying Hu ◽

Qinwen Pan ◽

Minghao Wang ◽

Xiang Ai ◽

Yuzhao Yan ◽

...

Keyword(s):

Breast Cancer ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Mrna Levels ◽

Somatic Variation ◽

Immune Microenvironment ◽

Normal Tissues ◽

Monocytes And Macrophages ◽

M6a Rna Methylation

Objective: Increasing evidence highlights the roles of N6-methyladenosine (m6A) and its regulators in oncogenesis. Herein, this study observed the associations of m6A regulators with breast cancer.Methods: RNA-seq profiles of breast cancer were retrieved from the Cancer Genome Atlas (TCGA) database. The expression of m6A regulators was analyzed in tumor and normal tissues. Their expression correlations were analyzed by Spearson test. Overall survival (OS) analysis of these regulators was then presented. Gene set enrichment analysis (GSEA) was performed in high and low YTHDF1 expression groups. The correlations of YTHDF1 expression with immune cells and tumor mutation burden (TMB) were calculated in breast cancer samples. Somatic variation was assessed in high and low YTHDF1 expression groups.Results: Most of m6A regulators were abnormally expressed in breast cancer compared to normal tissues. At the mRNA levels, there were closely relationships between them. Among them, YTHDF1 up-regulation was significantly related to undesirable prognosis (p = 0.025). GSEA results showed that high YTHDF1 expression was associated with cancer-related pathways. Furthermore, YTHDF1 expression was significantly correlated with T cells CD4 memory activated, NK cells activated, monocytes, and macrophages. There were higher TMB scores in YTHDF1 up-regulation group than its down-regulation group. Missense mutation and non-sense mutation were the most frequent mutation types.Conclusion: Our findings suggested that dysregulated m6A regulator YTHDF1 was predictive of survival outcomes as well as response to immunotherapy of breast cancer, and were closely related to immune microenvironment.

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Uncovering of the Association Between m5C Regulator-Mediated Methylation Modification Patterns and Tumor Microenvironment Infiltration Characteristics in Hepatocellular Carcinoma

10.21203/rs.3.rs-580707/v1 ◽

2021 ◽

Author(s):

Xinyu Gu ◽

Haibo Zhou ◽

Qingfei Chu ◽

Qiuxian Zheng ◽

Jing Wang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cells ◽

Immune Cell ◽

Enrichment Analysis ◽

Tumour Microenvironment ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cell Infiltration ◽

Gene Set ◽

Normal Tissues

Abstract Background: 5-Methylcytosine (m5C) plays essential roles in hepatocellular carcinoma (HCC), but the association between m5C regulation and immune cell infiltration in HCC has not yet been clarified.Methods: In this study, we analysed 371 patients with HCC from The Cancer Genome Atlas (TCGA) database, and the expression of 13 m5C regulators was investigated. Additionally, gene set variation analysis (GSVA), unsupervised clustering analysis, single-sample gene set enrichment analysis (ssGSEA), correlation analysis, and immunohistochemical (IHC) staining were performed.Results: Among the 371 patients, 41 had mutations in m5C regulators, the frequency of which was 11.26%. Then, we identified three m5C modification patterns that had obvious tumour microenvironment (TME) cell infiltration characteristics. Cluster-1 had an immune rejection phenotype; Cluster-2 had an immunoinflammatory phenotype; and Cluster-3 had an immune desert phenotype. In addition, we found that DNMT1 was highly expressed in tumour tissues compared with normal tissues in a tissue microarray (TMA) and that it was positively correlated with many TME-infiltrating immune cells. High expression of the m5C regulator DNMT1 was related to a poor prognosis in patients with HCC. Furthermore, we developed three Immu-clusters that were consistent with the immune characteristics of the m5C methylation modification patterns. We also discovered differences in the levels of immune cells and expression of chemokines and cytokines among the three Immu-clusters.Conclusions: Our work revealed the association between m5C modification and immune regulators in the TME. These findings also suggest that DNMT1 has great potential as a prognostic biomarker and therapeutic target for HCC.

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