key: cord-0056620-px0s10c9
authors: Xu, Wenhua; Yang, Wenna; Wu, Chunfeng; Ma, Xiaocong; Li, Haoyu; Zheng, Jinghui
title: Enolase 1 Correlated With Cancer Progression and Immune-Infiltrating in Multiple Cancer Types: A Pan-Cancer Analysis
date: 2021-02-10
journal: Front Oncol
DOI: 10.3389/fonc.2020.593706
sha: b92b9343f2b0b2107659ab4ba93808d07eb068f7
doc_id: 56620
cord_uid: px0s10c9

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.

Enolase 1 (ENO1) is an oxidative stress protein expressed in endothelial cells. It plays an essential role in the glycolytic pathway by converting 2-phosphoglycerate to phosphoenolpyruvate (1) and functions as a critical contributor to Warburg effect in cancer cells (2) . Recent evidence shows that some enzymes responsible for glycolysis are complicated, multifaceted proteins rather than simple components of the glycolytic pathway (3, 4) . The energy produced by glycolysis is used not only for tumor growth but also for tumor tolerance, such as the discharge of anticancer drugs and their metabolites from cancer cells (5) . ENO1 is involved in a series of physiological processes, such as autoimmunity, hypoxia tolerance, and cell growth (6, 7) . In particular, ENO1 expressed on the cell surface has been shown to promote migration and metastasis of tumor cells by inducing plasminogen activation and extracellular matrix degradation as a plasminogen receptor (8) .

Besides its major role in glycolysis, ENO1 is also considered as a multifunctional protein demonstrating various distinct activities (9) . Previous studies found that the upregulation of ENO1 was positively correlated with progression and poor prognosis in breast cancer, prostate cancer, thyroid carcinoma, hepatocellular carcinoma, cholangiocarcinoma, neuroblastoma, neuroendocrine tumors, lung cancer, and pancreatic cancer (4, (9) (10) (11) (12) (13) . Consistent to previous studies (2, 4, (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) , more details are summarized in Supplementary Table 1 . Additionally, increased ENO1 expression has been observed in different types of drug-resistant cancer cells, suggesting the potential use of ENO1 as a biomarker for drug resistance and as a target for cancer therapy (5) . ENO1 also involves in cell adhesionmediated resistance in non-Hodgkin lymphoma and tamoxifen resistance in breast cancer (24) . ENO1 has been shown to induce autoantibodies in patients with cholangiocarcinoma, breast cancer, head and neck cancer, leukemia, lung cancer, pancreatic cancer and melanoma (25) (26) (27) (28) . The correlation between tumor and autoimmunity may be due to the immunogenicity and proinflammatory stimulation produced by tumor cell death, as well as the activation of inflammatory process in tumor microenvironment, thus increasing the expression of autoantigen to the immune system (29) . ENO1 is a major auto-antigen. ENO1 specific T cells from peripheral blood to tumor are inhibited by a number of immunosuppressive mechanisms (17) . Their presence in the peripheral blood is associated with the prevention of metastasis by excision of cancer circulating cells (30, 31) . One explanation may be that tumor cells physically absorb and neutralize ENO1 antibodies expressed and secreted on the surface to reduce circulating levels.

The recently completed Cancer Genome Atlas (TCGA) project provides matched clinical and molecular data of multiple cancers, which facilitates systematical analysis of the survival impact of single gene expression. The correlation of ENO1 expression with prognosis, tumor stage, and levels of tumor immune infiltrates in different cancers remains unclear.

In this study, we performed a pan-cancer analysis of tumor and normal samples from TCGA dataset to evaluate the impacts of ENO1 on prognosis, staging, and immune infiltrating levels in 23 cancer types, including cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), lung adenocarcinoma (LUAD), and kidney chromophobe (KICH).

The clinical information and expression levels of ENO1 in 33 types of cancers were obtained from UCSC Xena browser (https://xena.ucsc.edu/; accessed by April 20, 2020) (32) and The Cancer Genome Atlas (TCGA, https://portal.gdc.cancer. gov/; accessed by April 20, 2020).

The expression levels of ENO1 in normal tissues were identified in GTEx Portal (https://www.gtexportal.org/home/; accessed by April 20, 2020). The boxplots of ENO1 expression in different types of cancers were constructed by Gene Expression Profiling Interactive Analysis (GEPIA, http://gepia.cancer-pku.cn/index. html; accessed by April 20, 2020) (33).

To evaluate the prognostic potential of ENO1 in cancers, the correlations between ENO1 expression and survival outcomes of cancer patients, including OS and disease-free survival (DFS), were investigated. Patients were divided into high-and low-expression groups using the 50 th percentile of ENO1 expression level as the cutoff value. The association between ENO1 expression and tumor stage was also investigated. The forest plot was generated using the R program (v3.6.1). In the subsequent immune infiltrate analysis and Gene Set Enrichment Analysis (GSEA), cancers were included if (1) tumor samples showed significant changes in ENO1 expression compared to normal tissues, and (2) a significant correlation between ENO1 expression and prognosis was found.

In this study, the cBio Cancer Genomics Portal (http:// cbioportal.org; accessed by April 30, 2020), which is a web tool for mutation analysis and visualization through TCGA cancer genomics profiles (34, 35) , was used for mutation analysis of ENO1. The genetic alteration of ENO1 and impact of alteration situation on prognosis in multiple cancer types were analyzed and visualized via cBio Portal data.

The Tumor Immune Estimation Resource database (TIMER, https://cistrome.shinyapps.io/timer/; accessed by April 20, 2020) includes gene expression profiles of 32 types of cancers from TCGA to estimate the abundance of immune infiltrates (36) . The expressions of ENO1 in these cancers were analyzed. The correlations of ENO1 expression with tumor purity and the abundance of immune infiltrates in CD8 + T cells, CD4 + T cells, B cells, macrophages, neutrophils, and dendritic cells were explored. Lastly, we assessed how ENO1 expression correlated with the expression of particular immune infiltrating cell subset markers.

GSEA GSEA (http://software.broadinstitute.org/gsea/index.jsp; accessed by April 30, 2020) was performed to explore the potential mechanisms involved in the effect of risk score on cancer prognosis (37, 38) . The enrichment analysis was performed using the Molecular Signatures Database (MSigDB) of c2 (c2.cp.kegg.v6.1.symbols.gmt) and c5 (c5.all.v6.1.symbols.gmt). The enriched gene sets in the GSEA that reached a nominal significance level of P < 0.05 were considered significant.

The expression levels of ENO1 in normal tissues were identified in GTEx Portal, and gene expression data from the GEPIA database through TCGA data were analyzed using the P, fold changes (FC) and ranks. Survival curves and violin plots were constructed by GEPIA. The method for ENO1 expression differential analysis between TCGA tumor and normal tissue was one-way ANOVA (|log 2 FC| ≥ 1.00, P < 0.01). P <0.05 was considered as statistically significant in other tests.

The Expression of ENO1 in Different Types of Cancers TCGA contains genomic, epigenomic, transcriptomic, and proteomic data for a total of 33 different cancer types. Cancer datasets with incomplete information on overall survival (OS), tumor stage evaluation, or ENO1 expression, or without control samples were excluded from the analysis. Ten cancer types were excluded from analysis due to incomplete information or lack of control samples. Eventually, the impacts of ENO1 expression on the following 23 cancer types were analyzed: breast invasive carcinoma (BRCA), bladder urothelial carcinoma (BLCA), colon adenocarcinoma (COAD), cholangiocarcinoma (CHOL), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), esophageal carcinoma (ESCA), head and neck squamous cell carcinoma (HNSC), kidney renal papillary cell carcinoma (KIRP), kidney renal clear cell carcinoma (KIRC), kidney chromophobe (KICH), lung squamous cell carcinoma (LUSC), lung adenocarcinoma (LUAD), liver hepatocellular carcinoma (LIHC), prostate adenocarcinoma (PRAD), pheochromocytoma a nd paraganglioma (PCPG), pancreatic adenocarcinoma (PAAD), rectum adenocarcinoma (READ), stomach adenocarcinoma (STAD), skin cutaneous melanoma (SKCM), thymoma (THYM), thyroid carcinoma (THCA), and uterine corpus endometrial carcinoma (UCEC).

The characteristic information is summarized in Table 1 .

The expression levels of ENO1 in normal tissues are shown in Figure 1 . The highest ENO1 expression was found in EBVtransformed lymphocytes, whereas the lowest was observed in the left ventricle of the heart. The boxplots of ENO1 expression in tumor and normal tissues were generated by GEPIA ( Figure  2 ). The expression levels of ENO1 are shown as TPM. The log 2 FC cutoff and P cutoff were set as 1.00 and 0.01, respectively. When compared to the respective normal tissues, ENO1 expression was significantly (P < 0.01) elevated in the tissue samples of CESC, CHOL, ESCA, LUAD, LUSC, and UCEC. However, KICH tumor samples showed a significantly lower level of ENO1 compared to normal tissues (P < 0.01). The expression of ENO1 in the other 16 cancer types was not significantly different from the respective controls (P > 0.01).

To determine the prognostic value of ENO1 in cancer patients, the correlations of ENO1 expression with prognosis and tumor , suggesting that high ENO1 expression might be an independent risk factor for these cancers (all HR > 1.00, P < 0.05). Then the survival curves were constructed to further evaluate the prognostic potential of ENO1 ( Figure 4 ). High ENO1 expression was significantly associated with worse OS in CESC (log-rank P = 0.04), BLCA (log-rank P = 0.03), KICH (log-rank P = 0.01), LIHC (log-rank P = 0.00), and SARC (log-rank P = 0.04), and worse DFS in KICH (log-rank P = 0.03) and SARC (log-rank P = 0.07). Obviously, the expression level of ENO1 was significantly different in the different tumor stages of CESC, LUAD, PICH, PAAD, and LIHC, but not in other types. Correlation of ENO1 expression with prognostic values in all 23 types of cancer is summarized in Supplementary  Table 2 .

The violin plots were generated to demonstrate the impact of ENO1 expression on tumor stage in these cancers. The data of SARC were not plotted due to small sample size ( Figure 5 ). The expression of ENO1 at different pathological stages was significantly different in CESC (F = 2.7, P = 0.0458), LUAD (F = 3.35, P = 0.0189), KICH (F = 4.19, P = 0.00911), PAAD (F = 3.8, P = 0.0113), and LIHC (F = 10.7, P = 1e-06), indicating that ENO1 might play a key role in the progression of these cancers.

Evidently, 195 samples in the altered group and 10,772 samples in the unaltered group were included for ENO1 mutation analysis. The results demonstrated that ENO1 was altered in 1.8% of all the included samples, including inframe mutation, missense mutation, truncating mutation, fusion, amplification, and deep deletion ( Figure 6) . Furthermore, the prognostic FIGURE 2 | ENO1 expression levels in seven types of cancers with significant differential expression of ENO1 between tumor and normal tissues. The expression levels of ENO1 are shown in transcripts per million. The log 2 FC cutoff and P cutoff were set as 1.00 and 0.01, respectively. Pink boxes represent tumor samples and gray boxes represent normal samples. The Y-axes of boxplots represent ENO1 expression in transcripts per million. Plots were generated using GEPIA with data from TCGA. num (T), number of tumor samples; num (N), number of normal samples. significance of ENO1 mutation was estimated via Kaplan-Meier method. The survival curves indicate that no statistical significance was found between the altered group and the unaltered group either in OS (altered group = 188, unaltered group = 10,614, log-rank P = 0.71, Figure 7A ) or DFS (altered group = 98, unaltered group = 5,285, log-rank P = 0.60, Figure 7B ).

The level of tumor-infiltrating lymphocytes is an independent predictor of sentinel lymph node status and survival outcomes in cancers. We further investigated the correlation between ENO1 expression and the abundance of immune infiltrates (Figure 8 ). In CESC, ENO1 expression was negatively and significantly correlated with the infiltrating levels of B cells and macrophages (all P < 0.05). However, no significant correlation was observed between ENO1 expression and tumor purity, as well as the levels of dendritic cells, neutrophils, CD4 + T cells, or CD8 + T cells (all P > 0.05). In KICH, ENO1 expression was positively and significantly correlated to the infiltration of dendritic cells, neutrophils, CD8 + T cells, B cells, and macrophages (all P < 0.05), but no significant correlation was found with tumor purity or the infiltrating level of CD4 + T cells (all P > 0.05). In LUAD, the expression level of ENO1 was negatively correlated to the infiltration of B cells but positively associated with the level of dendritic cells (all P < 0.05). No significant correlation was found between ENO1 expression and the infiltration of other cells (all P > 0.05).

To further explore the potential relationships between ENO1 and infiltrating immune cells, we examined the correlations between ENO1 and several immune cell markers in TIMER and GEPIA. Specifically, we assessed the correlation between ENO1 expression and levels of markers for particular cell subsets including CD8 + T cells, B cells, monocytes and other cells. As shown in Supplementary Table 3 , we adjusted these results based on tumor purity, revealing a significant correlation between ENO1 expression and monocyte markers (CD86, CD115), TAM markers (CCL2, IL10), M1 macrophage markers (INOS, IRF5, COX2), M2 macrophage markers (CD163, VSIG4, MS4A4A), neutrophils markers (CD11b, CD66b), NK cell markers (KIR2DL4), DC markers (BCDA-A, BDCA-4, CD11C), Th1 markers (STAT4), Th2 markers (GATA3, STAT5A), Tfh markers (BCL6), Th17 markers (STAT3) and Treg markers (CCR8, STAT5B, TGFb1).In LIHC, B cells and T cells were two immune cell types most strongly correlated with ENO1 expression. In KICH, tumor purity had no effect on the relationship between ENO1 and tumor markers. At the same time, T cells, B cells, monocytes and dendritic cells also play an important role in immune infiltration markers in LUAD. In TIMER, after adjustments for tumor purity, the ENO1 expression level was significantly correlated with 14 out of 57 immune cell markers in CESC, 30 out of 57 immune cell markers in KICH, and 24 out of 57 immune cell markers in LUAD. Hence, these results confirm our speculation that ENO1 expression in KICH; CESC and LUAD correlate with immune cell infiltration in different manners, which can help explain the differences in patient survival. 

The enrichment score (ES) was calculated using GSEA. The positive ES and negative ES indicated that the gene set was enriched at the top or bottom of the ranked list, respectively. The results revealed that ENO1 was mainly enriched in cell cycle, extracellular matrix (ECM) receptor interaction, DNA replication, apoptosis, and glycolysis process (Figure 9 ).

In the present study, the correlations of ENO1 with prognosis, tumor stage, and immune infiltrating levels in multiple cancers were investigated via analyzing TCGA data. ENO1 is a bifunctional gene that encodes a glycolytic protein and a c-Myc-binding protein (39) . The involvement of ENO1 in a variety of pathways, particularly glycolysis-related pathways, is closely related to tumor formation and progress. Previous studies have reported the effects of ENO1 on tumor development (15, (17) (18) (19) (40) (41) (42) (43) (44) (45) , which support our results showing that ENO1 is significantly correlated with prognosis, tumor stage, and immune infiltrates in cancers.

Tumor-infiltrating immune cells can be effectively targeted by anti-cancer agents and the subtle alterations in their composition and function are correlated with the clinical outcomes of cancer patients (18, 46) . In recent years, there has been growing interest in understanding the role of immune system in the initiation and progression of cancers (47) . Clinical evidence has suggested the effectiveness of immunotherapy for subsets of patients with advanced tumors (48) . Cancer immunotherapy is mostly based on the upregulation of tumor antigens (49) . ENO1 has been found to induce autoantibody production in patients with cholangiocarcinoma, breast tumor, head and neck tumor, leukemia, lung tumor, pancreatic tumor, and melanoma (26, 28, (50) (51) (52) . ENO1-specific T cells can recirculate from the tumor to the periphery despite different functional profiles. The presence of peripheral ENO1-specific T cells is significantly correlated with improved survival, suggesting the prognostic value of these cells in cancers (17) . The correspondence between peripheral and intratumoral ENO1-specific immune responses has been demonstrated, and the circulating ENO1specific T cells exhibited an effective anticancer effect in pancreatic ductal adenocarcinoma (17) . In addition, the enzymatic activity of ENO1 in solid tumors is regulated at posttranslational level as evidenced by the upregulated mRNA and protein expressions of ENO1 in CD8 + tumor-infiltrating lymphocytes (45) . Consistently, our results also showed a significant correlation between ENO1 expression and immune infiltrates. Interestingly, tumor infiltration has no significant effect on the cumulative survival (Supplementary Figure 1) .

The KEGG analysis in this study revealed that ENO1 was mainly enriched in DNA replication, cell cycle, apoptosis, glycolysis process, and ECM receptor interaction. These findings are consistent with a previous study showing that high ENO1 expression is significantly correlated with DNA replication and cell cycle in hepatocellular carcinoma (19) . One of the roles of ENO1 is to act as a plasminogen receptor linked to increased cellular inflammation, migration, and invasion via ECM remodeling (53) , suggesting that the downregulation of ENO1 on cell surface may suppress other tumorigenic processes (41) . ENO1 also shows a regulatory effect on cell cycle. Cancer cells are characterized by aberrant cell cycle activity and unlimited replicative potential. The therapies targeting cellcycle proteins have been used for the treatment of multiple cancers, including prostate cancer, breast cancer, and lung carcinoma (54) . ENO1 is an oncogene that promotes cell cycle progression, proliferation, migration, and invasion. The overexpression of ENO1 increased the levels of oncogenic cell cycle regulators in non-small cell lung cancer (18) . ENO1 also regulated apoptosis and cell cycle in bladder and pancreatic cancer cells (42, 43) . Furthermore, the knockdown of ENO1 has been shown to promote apoptosis and induce the arrest of cell cycle in gastric cancer cells (15) . According to previous findings, circ-ENO1 and its host gene ENO1 were upregulated in LUAD cells (2) . ENO1 might also contribute to the progression of lung cancers by stimulating cell proliferation via accelerating G1/S transition, but not in esophageal cancers (44) . Taken together, the varied expression of ENO1 in different types and stages of cancers implied that the effects of ENO1 may vary in different cancers and at different tumor stages. However, the potential mechanisms involved in the regulation of ENO1 in cancers needs to be further explored. Additionally, mutation of ENO1 was analysis, for it was proved that mutation could affect tumor progression (55, 56) ; however, ENO1 mutation (1.8%) did not impact on prognosis in this study. The Tumor-Node-Metastasis (TNM) classification aims to improve the management of cancers including cancer control, research design, clinical care guidance and decision making (57) . As demonstrated in another study, TNM stage played a critical role in survival in metachronous lung cancer (58) . To build up a comprehensive prognosis predicting and strategies determining system, all relevant factors should be considered, including TNM stage. In this study, differential expression of ENO1 in different stages of CESC, HNSC, BLCA, LUAD, KICH, PAAD, and LIHC was identified, indicating ENO1 could be a marker for tumor staging. In consonance with our results, ENO1 expression was higher in late stages (stages III and IV), particularly that in KICH ( Figure 5E) , meanwhile, high ENO1 expression was significantly associated with worse OS in KICH ( Figure 4I ). Further to our previous statement that ENO1 could promote cancer progression via stimulating cell proliferation, increasing invasion and migration, and other mechanisms, ENO1 may lead to a late stage on the aspect of metastasis. There is still uncertainty, however, whether ENO1 is a determinant of tumor stage.

Our results showed that ENO1 expression was significantly higher in normal tissues as compared to KICH tissues, whereas high expression of ENO1 predicted poor OS in other cancers. Notably, the downregulation of ENO1 has been found in tissue samples from patients with non-small cell lung cancer, and the patients with low ENO1 expression had a worse prognosis (40) . These results indicate a contradictory role of ENO1 in tumor formation. KICH is a rare carcinoma originating from the collecting duct and is typically the least aggressive subtype of renal cell carcinomas with a good prognosis unless characterized by sarcomatous transformation (59, 60) . Although small number of deaths and advanced cases may lead to bias in the analysis of ENO1 expression and survival outcomes, the potential biological function of ENO1 and its correlation to survival are worth further investigation.

There are some limitations in the current study. First, the treatments given to patients might affect the expression of ENO1, leading to a potential bias. Additionally, patients with advanced cancers were underrepresented in TCGA cohort, particularly the ones with KICH, while ENO1 might show different biological activities at different tumor stages. Efforts should be directed towards the preparation of prospective clinical trials to evaluate the prognostic value of ENO1 as a tumor marker in cancers at different stages.

ENO1 significantly regulates macrophage infiltration in CESC and LUAD. In addition, patients with CESC and LUAD had poor clinical outcomes and high macrophage infiltration. Taken together, these analyses reveal the clinical importance of ENO1 as a macrophage infiltration regulator in patients with CESC and LUAD. These results reveal the potential regulatory role of ENO1 in tumor associated macrophage polarization. In summary, this pan-cancer analysis demonstrated that increased ENO1 expression was correlated with poor prognosis and decreased immune infiltration levels in macrophages, CD4 + T cells, CD8 + T cells, and B cells in CESC and LUAD. However, the opposite effect of ENO1 on immune infiltration was observed in KICH. The expression of ENO1 also potentially contributed to the stages of tumor development. Therefore, ENO1 may be used as a potential biomarker for predicting prognosis, tumor stage, and immune infiltration in CESC, LUAD, and KICH patients.

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material. 

Role of enolase-1 in response to hypoxia in breast cancer: exploring the mechanisms of action

CircRNA-ENO1 promoted glycolysis and tumor progression in lung adenocarcinoma through upregulating its host gene ENO1

Multifaceted roles of glycolytic enzymes

ENO1, a potential prognostic head and neck cancer marker, promotes transformation partly via chemokine CCL20 induction

Identification of chemoresistant factors by protein expression analysis with iTRAQ for head and neck carcinoma

a-Enolase expressed on the surfaces of monocytes and macrophages induces robust synovial inflammation in rheumatoid arthritis

ENO1 Acts as a Prognostic Biomarker Candidate and Promotes Tumor Growth and Migration Ability Through the Regulation of Rab1A in Colorectal Cancer

Effects of aenolase (ENO1) over-expression on malignant biological behaviors of AGS cells

Alpha-enolase as a potential cancer prognostic marker promotes cell growth, migration, and invasion in glioma

Vaccination with ENO1 DNA prolongs survival of genetically engineered mice with pancreatic cancer

Estrogen promotes prostate cancer cell migration via paracrine release of ENO1 from stromal cells

Proteomic approach reveals novel targets for retinoic acid-mediated therapy of thyroid carcinoma

Proteomicsbased identification of alpha-enolase as a tumor antigen in non-small lung cancer

Hyperglycemia promotes Snail-induced epithelial-mesenchymal transition of gastric cancer via activating ENO1 expression

Enolase1 overexpression regulates the growth of gastric cancer cells and predicts poor survival

Up-regulated ENO1 promotes the bladder cancer cell growth and proliferation via regulating bcatenin

Peripheral ENO1-specific T cells mirror the intratumoral immune response and their presence is a potential prognostic factor for pancreatic adenocarcinoma

Alpha-enolase promotes cell glycolysis, growth, migration, and invasion in non-small cell lung cancer through FAK-mediated PI3K/AKT pathway

Enolase-1 serves as a biomarker of diagnosis and prognosis in hepatocellular carcinoma patients

ENO1 Overexpression in Pancreatic Cancer Patients and Its Clinical and Diagnostic Significance

A preliminary study of serum marker alpha-enolase in the diagnosis of hepatocellular carcinoma. Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chin

Identification of ENO1 as a potential sputum biomarker for early-stage lung cancer by shotgun proteomics

Alpha-enolase is a potential prognostic marker in clear cell renal cell carcinoma

Increased expression of enolase alpha in human breast cancer confers tamoxifen resistance in human breast cancer cells

Alpha-Enolase (ENO1), a potential target in novel immunotherapies

Proteome analysis of human lung squamous carcinoma

Proteomic analysis of secreted proteins of non-small cell lung cancer

Identification of alpha-enolase as an autoantigen in lung cancer: its overexpression is associated with clinical outcomes

A common repertoire of autoantibodies is shared by cancer and autoimmune disease patients: Inflammation in their induction and impact on tumor growth

Circulating tumor cells in pancreatic cancer patients: methods of detection and clinical implications

Circulating tumor cells in locally advanced pancreatic adenocarcinoma: the ancillary CirCe 07 study to the LAP 07 trial

The UCSC Cancer Genomics Browser: update 2013

GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses

The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data

Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal

TIMER: A Web Server for Comprehensive Analysis of Tumor-Infiltrating Immune Cells

PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes

Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles

c-myc promoter binding protein regulates the cellular response to an altered glucose concentration

Enolase-alpha is frequently down-regulated in non-small cell lung cancer and predicts aggressive biological behavior

Alpha-enolase is upregulated on the cell surface and responds to plasminogen activation in mice expressing a 133p53alpha mimic

Up-regulated ENO1 promotes the bladder cancer cell growth and proliferation via regulating betacatenin

ENO1 silencing impaires hypoxia-induced gemcitabine chemoresistance associated with redox modulation in pancreatic cancer cells

Enolase 1 differentially contributes to cell transformation in lung cancer but not in esophageal cancer

Impaired enolase 1 glycolytic activity restrains effector functions of tumor-infiltrating CD8(+) T cells

Chromophobe renal cell carcinoma and 'capsulomas' with acquired cystic disease of the kidney in a long-term hemodialysis patient

Comprehensive Analysis of the Tumor Microenvironment in Cutaneous Melanoma associated with Immune Infiltration

Pathways-and epigenetic-based assessment of relative immune infiltration in various types of solid tumors

Cancer and the Immune System: Basic Concepts and Targets for Intervention

Identification of melanoma antigens using a Serological Proteome Approach (SERPA)

Plasma autoantibodies against heat shock protein 70, enolase 1 and ribonuclease/angiogenin inhibitor 1 as potential biomarkers for cholangiocarcinoma

Immunoproteomics of HER2-positive and HER2-negative breast cancer patients with positive lymph nodes

Expression of Alpha-Enolase (ENO1), Myc Promoter-Binding Protein-1 (MBP-1) and Matrix Metalloproteinases (MMP-2 and MMP-9) Reflect the Nature and Aggressiveness of Breast Tumors

Cell cycle proteins as promising targets in cancer therapy

The interaction of enolase-1 with caveolae-associated proteins regulates its subcellular localization

Introduction of in vitro transcribed ENO1 mRNA into neuroblastoma cells induces cell death

The TNM classification of malignant tumours-towards common understanding and reasonable expectations

TNM stage is the most important determinant of survival in metachronous lung cancer

Chromophobe Renal Cell Carcinoma is the Most Common Nonclear Renal Cell Carcinoma in Young Women: Results from the SEER Database

Chromophobe Renal Cell Carcinoma Presenting as a Cystic Renal Mass: Case Report and Review of the Literature

The authors would like to thank 51runse, Toweree (Beijing) Education Company, for editing the manuscript.