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

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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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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Development of a Novel Prognostic Signature Based on Antigen Processing and Presentation in Patients with Breast Cancer

Pathology & Oncology Research ◽

10.3389/pore.2021.600727 ◽

2021 ◽

Vol 27 ◽

Author(s):

Aoshuang Qi ◽

Mingyi Ju ◽

Yinfeng Liu ◽

Jia Bi ◽

Qian Wei ◽

...

Keyword(s):

Breast Cancer ◽

Antigen Processing ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Signature ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Prognostic Indicators ◽

Gene Set ◽

Antigen Processing And Presentation

Background: Complex antigen processing and presentation processes are involved in the development and progression of breast cancer (BC). A single biomarker is unlikely to adequately reflect the complex interplay between immune cells and cancer; however, there have been few attempts to find a robust antigen processing and presentation-related signature to predict the survival outcome of BC patients with respect to tumor immunology. Therefore, we aimed to develop an accurate gene signature based on immune-related genes for prognosis prediction of BC.Methods: Information on BC patients was obtained from The Cancer Genome Atlas. Gene set enrichment analysis was used to confirm the gene set related to antigen processing and presentation that contributed to BC. Cox proportional regression, multivariate Cox regression, and stratified analysis were used to identify the prognostic power of the gene signature. Differentially expressed mRNAs between high- and low-risk groups were determined by KEGG analysis.Results: A three-gene signature comprising HSPA5 (heat shock protein family A member 5), PSME2 (proteasome activator subunit 2), and HLA-F (major histocompatibility complex, class I, F) was significantly associated with OS. HSPA5 and PSME2 were protective (hazard ratio (HR) < 1), and HLA-F was risky (HR > 1). Risk score, estrogen receptor (ER), progesterone receptor (PR) and PD-L1 were independent prognostic indicators. KIT and ACACB may have important roles in the mechanism by which the gene signature regulates prognosis of BC.Conclusion: The proposed three-gene signature is a promising biomarker for estimating survival outcomes in BC patients.

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RNA N6-Methyladenosine Regulators Contribute to Tumor Immune Microenvironment and Have Clinical Prognostic Impact in Breast Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.650499 ◽

2022 ◽

Vol 12 ◽

Author(s):

Lan-Xin Mu ◽

You-Cheng Shao ◽

Lei Wei ◽

Fang-Fang Chen ◽

Jing-Wei Zhang

Keyword(s):

Breast Cancer ◽

Immune Cell ◽

Risk Model ◽

Cox Regression ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Prognostic Impact ◽

Immune Microenvironment ◽

Model Based ◽

Tumor Immune Microenvironment

Purpose: This study aims to reveal the relationship between RNA N6-methyladenosine (m6A) regulators and tumor immune microenvironment (TME) in breast cancer, and to establish a risk model for predicting the occurrence and development of tumors.Patients and methods: In the present study, we respectively downloaded the transcriptome dataset of breast cancer from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database to analyze the mutation characteristics of m6A regulators and their expression profile in different clinicopathological groups. Then we used the weighted correlation network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO), and cox regression to construct a risk prediction model based on m6A-associated hub genes. In addition, Immune infiltration analysis and gene set enrichment analysis (GSEA) was used to evaluate the immune cell context and the enriched gene sets among the subgroups.Results: Compared with adjacent normal tissue, differentially expressed 24 m6A regulators were identified in breast cancer. According to the expression features of m6A regulators above, we established two subgroups of breast cancer, which were also surprisingly distinguished by the feature of the immune microenvironment. The Model based on modification patterns of m6A regulators could predict the patient’s T stage and evaluate their prognosis. Besides, the low m6aRiskscore group presents an immune-activated phenotype as well as a lower tumor mutation load, and its 5-years survival rate was 90.5%, while that of the high m6ariskscore group was only 74.1%. Finally, the cohort confirmed that age (p < 0.001) and m6aRiskscore (p < 0.001) are both risk factors for breast cancer in the multivariate regression.Conclusion: The m6A regulators play an important role in the regulation of breast tumor immune microenvironment and is helpful to provide guidance for clinical immunotherapy.

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

Frontiers in Oncology ◽

10.3389/fonc.2020.593706 ◽

2021 ◽

Vol 10 ◽

Author(s):

Wenhua Xu ◽

Wenna Yang ◽

Chunfeng Wu ◽

Xiaocong Ma ◽

Haoyu Li ◽

...

Keyword(s):

Cancer Progression ◽

Stress Protein ◽

Enrichment Analysis ◽

Tumor Stage ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Multiple Cancer ◽

Clinical Prognosis ◽

Multiple Tumor ◽

Normal Tissues

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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Mind Bomb 1 Promotes Pancreatic Cancer Proliferation by Activating β-Catenin Signaling

Journal of Nanoscience and Nanotechnology ◽

10.1166/jnn.2020.18755 ◽

2020 ◽

Vol 20 (12) ◽

pp. 7276-7282

Author(s):

Xiao Fu ◽

Neng Tang ◽

Weiqi Xie ◽

Liang Mao ◽

Yudong Qiu

Keyword(s):

Pancreatic Cancer ◽

Cancer Metastasis ◽

Mrna Level ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Pancreatic Tumors ◽

Mrna Levels ◽

Cancer Proliferation

Mind bomb 1 (MIB1), an E3 ligase, plays a vital role in chemo-resistance and cancer metastasis. According to The Cancer Genome Atlas (TCGA), MIB1 gene is preferentially amplified in pancreatic cancer. Copy number alterations in MIB1 gene are associated with worse survival. Gene Expression Omnibus (GEO) also showed that pancreatic cancer with high mRNA level of MIB1 tend to be more resistant to gemcitabine and higher mRNA levels of MIB1 are found in pancreatic tumors compared with adjacent normal tissues. MIB1 knockdown (KD) in Panc-1 and HPAF2 cell lines significantly inhibit proliferation and colony formation of pancreatic cancer. The gene set enrichment analysis (GSEA) has also showed that β-catenin is the downstream of MIB1. Western blot analysis showed that total and active β-catenin levels are decreased in MIB1 KD cells. β-catenin inhibitor also inhibits proliferation of Panc-1 and HPAF2 cells. We in this study implanted HPAF2 scramble and MIB1 KD cells orthotopically in athymic nude mice. Gemcitabine was used to treat the mice. Results revealed that after MIB1 KD HPAF2 cells were more sensitive to gemcitabine. In conclusion, we demonstrated that MIB1 promotes pancreatic cancer proliferation through activating β-catenin signaling. MIB1 may thus be a therapeutic target in pancreatic cancer therapy.

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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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Construction of a Novel Signature and Prediction of the Immune Landscape in Soft Tissue Sarcomas Based on N6-Methylandenosine-Related LncRNAs

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.715764 ◽

2021 ◽

Vol 8 ◽

Author(s):

Li Zhang ◽

Xianzhe Tang ◽

Jia Wan ◽

Xianghong Zhang ◽

Tao Zheng ◽

...

Keyword(s):

High Risk ◽

Soft Tissue ◽

Cox Regression ◽

Soft Tissue Sarcomas ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Risk Scores ◽

Consensus Clustering ◽

Immune Microenvironment

Background: N6-methylandenosine-related long non-coding RNAs (m6A-related lncRNAs) are critically involved in cancer development. However, the roles and clinical significance of m6A-related lncRNAs in soft tissue sarcomas (STS) are inconclusive, thereby warranting further investigations.Methods: Transcriptome profiling data were extracted from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx). Consensus clustering was employed to divide patients into clusters and Kaplan–Meier analysis was used to explore the prognostic differences between the subgroups. Gene set enrichment analysis (GSEA) was conducted to identify the biological processes and signaling pathways associated with m6A-Related lncRNAs. Finally, patients were randomly divided into training and validation cohorts, and least absolute shrinkage and selection operator (LASSO) Cox regression was conducted to establish the m6A-related lncRNA-based risk signature.Results: A total of 259 STS patients from TCGA-SARC dataset were enrolled in our study. Thirteen m6A-Related lncRNAs were identified to be closely related to the prognosis of STS patients. Patients were divided into two clusters, and patients in cluster 2 had a better overall survival (OS) than those in cluster 1. Patients in different clusters also showed differences in immune scores, infiltrating immune cells, and immune checkpoint expression. Patients were further classified into high-risk and low-risk subgroups according to risk scores, and high-risk patients were found to have a worse prognosis. The receiver operating characteristic (ROC) curve indicated that the risk signature displayed excellent performance at predicting the prognosis of patients with STS. Further, the risk signature was remarkably connected with the immune microenvironment and chemosensitivity in STS.Conclusion: Our study demonstrated that m6A-related lncRNAs were significantly associated with prognosis and tumor immune microenvironment and could function as independent prognosis-specific predictors in STS, thereby providing novel insights into the roles of m6A-related lncRNAs in STS.

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Association of Th2 high tumors with aggressive features of breast cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.e12584 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. e12584-e12584

Author(s):

Yoshihisa Tokumaru ◽

Lan Le ◽

Masanori Oshi ◽

Eriko Katsuta ◽

Nobuhisa Matsuhashi ◽

...

Keyword(s):

Breast Cancer ◽

T Cells ◽

Cancer Progression ◽

Immune Cells ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Th2 Cells ◽

Immune Microenvironment ◽

Adaptive Immune Cells ◽

Tumor Immune Microenvironment

e12584 Background: Recent studies have shown that infiltrating T-lymphocytes have been implicated in the promotion of breast cancer progression. Upon activation, these antigen-presenting cells then recruit adaptive immune cells. It has been proposed that polarization of CD4+ effector T-cells towards the immunosuppressive Th2 cells induce cytokine release and T-cell anergy, which lead to polarization of M2 tumor-associated macrophages (TAM’s), providing a protumorigenic microenvironment. We hypothesized that there is a correlation between high levels of Th2 cells and aggressive features of breast cancer and unfavorable tumor immune environment. Methods: Clinicopathological data and overall survival information was obtained on 1069 breast cancer patients from The Cancer Genome Atlas (TCGA) database. We defined Th2 high and low levels with the median cutoff. Results: Analysis of cell composition of the immune cells within tumor immune microenvironment demonstrated that Th2 high tumors did not consistently associated with unfavorable tumor immune microenvironment. Pro-cancer immune cells, such as macrophage M2 cells were increased with Th2 high tumors whereas, regulatory T cells were decreased with Th2 high tumors (p < 0.01 and p < 0.001 respectively). On the contrary, infiltration of anti-cancer cells, such as macrophage M1 was increased whereas CD8 T cells were decreased with Th2 high tumors (p < 0.05 and p < 0.001 respectively). Th2 was not shown to have correlation with IL-4, IL-6, IL-10 and IL-13, all of which has been reported to associate with Th2 cells. Th2 levels were associated with advanced grades. Also, correlation analysis demonstrated that there was a strong correlation between Th2 levels and Ki-67. These results were further validated with gene set enrichment analysis (GSEA). GSEA revealed that in Th2 high tumors enriched the gene sets associated with cell proliferation and cell cycle. Conclusions: High expression of immunosuppressive Th2 cells was associated with highly proliferative features of breast cancer, but not with unfavorable tumor immune microenvironment.

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Identification of FPR3 as a unique biomarker for targeted therapy in the immune microenvironment of breast cancer

10.21203/rs.3.rs-63478/v1 ◽

2020 ◽

Author(s):

Jian Qi ◽

Yu Liu ◽

Jiliang Hu ◽

Li Lu ◽

Zhen Dou ◽

...

Keyword(s):

Breast Cancer ◽

Network Analysis ◽

Poor Prognosis ◽

Functional Module ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Ppi Network ◽

Immune Microenvironment ◽

Tumor Stages ◽

Immune Score

Abstract Background Immunotherapy is in the ascendant, but its use in the treatment of breast cancer remains limited. Thus, identification and evaluation of prognostic biomarkers of tissue microenvironment will reveal new immune-based therapeutic strategies for breast cancer. Methods Using in silico bioinformatic approach, we investigated the tumor microenvironmental and genetic factors related to breast cancer. We calculated the Immune score, Stromal score, Estimate score, Tumor purity, Tumor mutation burden (TMB), Mutant-allele tumor heterogeneity (MATH) of breast cancer patients from the Cancer Genome Atlas (TCGA) using the ESTIMATE algorithm and Maftools. Weighted correlation network analysis (WGCNA) was used to identify gene patterns association with the Immune score. Then we use the MCODE plugin of Cytoscape to analyze the protein-protein interaction (PPI) network for mining the functional gene modules. Survival and Cox analysis was further performed to identify the key prognostic targets in immune microenvironment. Gene set enrichment analysis (GSEA) was utilized to explore the carcinogenic pathways associated with the target genes. Results Significant correlations between Immune/Stromal scores with breast cancer subtypes and tumor stages were established. Importantly, we found that the Immune score, but not the Stromal score, was significantly related to the patient's prognosis. WGCNA identified a pattern of gene function associated with Immune score, and that almost all of these genes (388 genes) are significantly upregulated in the higher Immune score group. PPI network analysis revealed the enrichment of immune checkpoint genes in the functional module but predicting a good prognosis by survival analysis. Among all the upregulated genes, FPR3, a G protein-coupled receptor essential for neutrophil activation, is the sole factor that predicts poor prognosis. GSEA analysis showed FRP3 upregulation synergizes with the activation of many pathways involved in carcinogenesis. Conclusions This study identified FPR3 as a key immune-related biomarker predicting a poor prognosis for breast cancer, revealing it as a promising targetable gene for immunotherapy.

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A Novel Prognostic Biomarker of Luminal Breast Cancer: High CD39 Expression Is Related to Poor Survival

Frontiers in Genetics ◽

10.3389/fgene.2021.682503 ◽

2021 ◽

Vol 12 ◽

Author(s):

Xiaojian Ni ◽

Wenze Wan ◽

Jingjing Ma ◽

Xinyou Liu ◽

Bohao Zheng ◽

...

Keyword(s):

Breast Cancer ◽

Immune Cell ◽

Statistical Tests ◽

Characteristic Curve ◽

Multivariable Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Luminal Breast Cancer ◽

Functional Surface

BackgroundCD39 is one of the functional surface markers for T regulatory cells, the prognostic role and immune-related effects of CD39 in luminal breast cancer (BC) patients has not been evaluated yet. The aim of the current study was to explore the association between CD39 expression and clinic pathological characteristics and the prognosis in luminal BC patients.MethodsClinical information and RNA-sequencing (RNA-Seq) expression data were extracted from The Cancer Genome Atlas (TCGA). Patients were divided into a high or low CD39 expression group by the optimal cutoff value (4.18) identified from the receiver operating characteristic curve analysis. The relationships between CD39 expression and clinic pathological features were evaluated by the corresponding statistical tests. Survival analyses were applied to evaluate the overall survival between the high and low CD39 expression groups in luminal BC. Furthermore, Gene Expression Omnibus datasets were used for external data validation. Gene set enrichment analysis (GSEA) was also performed, and CIBERSORT was used to analyze the immune cell populations.ResultsAnalysis of 439 cases of tumor data showed that CD39 was overexpressed in luminal BC. The multivariable analysis suggested that CD39 expression was an independent prognostic factor for luminal BC patients. GSEA suggested that CD39 might play an important role in luminal BC progression through immune regulation. Analysis of immune cell patterns revealed high CD39 expression correlated to a higher proportion of CD8+ T cells and M2 macrophages.ConclusionThis study demonstrates that CD39 expression correlates with the prognosis of luminal BC through TCGA database mining. Further studies are warranted further to elucidate this potential novel therapeutic strategy for BC.

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