Identification of an eight-m6A RNA methylation regulator prognostic signature of uterine corpus endometrial carcinoma based on bioinformatics analysis

Background: As the fourth most common malignant tumors in women, uterine corpus endometrial carcinoma (UCEC) requires novel and reliable biomarkers for prognosis prediction to improve the overall survival. Oxidative phosphorylation (OXPHOS) is found to be strongly correlated with the progression of tumor. Here, we aimed to construct an OXPHOS-related and immune microenvironment prognostic signature to stratify UCEC patients for optimization of treatment strategies.Method: Prognosis-associated OXPHOS-related differentially expressed genes were identified by multivariable Cox regression from TCGA–UCEC cohort. Based on the candidate genes, an OXPHOS-related prognostic signature was constructed by the train set data and verified by the entire set. When integrated with relevant clinical characteristics, a nomogram was also created for clinical application. Through comparison of tumor microenvironment between different risk groups, the underlying mechanism of the model and the inner correlation between immune microenvironment and energy metabolism were further investigated.Results: An OXPHOS-related signature containing ATP5IF1, COX6B1, FOXP3, and NDUFB11 was constructed and had better predictive ability compared with other recently published signatures in UCEC. Patients with lower risk score showed higher immune cell infiltration, higher ESTIMATE score (p = 2.808E−18), lower tumor purity (p = 2.808E−18), higher immunophenoscores (IPSs) (p < 0.05), lower expression of mismatch repair (MMR) proteins (p < 0.05), higher microsatellite instability (MSI), lower expression of markers of N6-methyladenosine (m6A) mRNA methylation regulators, higher tumor mutation burden (TMB) (p = 1.278E−9), and more sensitivity to immune checkpoint blockade (ICB) (p < 0.001) and chemotherapy drugs, thus, possessing improved prognosis.Conclusion: An OXPHOS-related and immune microenvironment prognostic signature classifying EC patients into different risk subsets was constructed in our study, which could be used to predict the prognosis of patients and help to select a specific subset of patients who might benefit from immunotherapy and chemotherapy, thus, improving the overall survival rate of UCEC. These findings may contribute to the discovery of novel and robust biomarkers or target therapy in UCEC and give new insights into the molecular mechanism of tumorigenesis and progression of UCEC.

Download Full-text

Comprehensive Analysis of PD-L1 Expression, Immune Infiltrates, and m6A RNA Methylation Regulators in Esophageal Squamous Cell Carcinoma

Frontiers in Immunology ◽

10.3389/fimmu.2021.669750 ◽

2021 ◽

Vol 12 ◽

Author(s):

Wei Guo ◽

Fengwei Tan ◽

Qilin Huai ◽

Zhen Wang ◽

Fei Shao ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

T Cells ◽

Esophageal Squamous Cell Carcinoma ◽

Immune Cell ◽

Immune Cell Infiltration ◽

Consensus Clustering ◽

Prognostic Signature ◽

Rna Methylation ◽

M6a Rna Methylation ◽

Immune Score

BackgroundEsophageal squamous cell carcinoma (ESCC) is one of the most common cancer types and represents a threat to global public health. N6-Methyladenosine (m6A) methylation plays a key role in the occurrence and development of many tumors, but there are still few studies investigating ESCC. This study attempts to construct a prognostic signature of ESCC based on m6A RNA methylation regulators and to explore the potential association of these regulators with the tumor immune microenvironment (TIME).MethodsThe transcriptome sequencing data and clinical information of 20 m6A RNA methylation regulators in 453 patients with ESCC (The Cancer Genome Atlas [TCGA] cohort, n = 95; Gene Expression Omnibus [GEO] cohort, n = 358) were obtained. The differing expression levels of m6A regulators between ESCC and normal tissue were evaluated. Based on the expression of these regulators, consensus clustering was performed to investigate different ESCC clusters. PD-L1 expression, immune score, immune cell infiltration and potential mechanisms among different clusters were examined. LASSO Cox regression analysis was utilized to obtain a prognostic signature based on m6A RNA methylation modulators. The relationship between the risk score based on the prognostic signature and the TIME of ESCC patients was studied in detail.ResultsSix m6A regulators (METTL3, WTAP, IGF2BP3, YTHDF1, HNRNPA2B1 and HNRNPC) were observed to be significantly highly expressed in ESCC tissues. Two molecular subtypes (clusters 1/2) were determined by consensus clustering of 20 m6A modulators. The expression level of PD-L1 in ESCC tissues increased significantly and was significantly negatively correlated with the expression levels of YTHDF2, METL14 and KIAA1429. The immune score, CD8 T cells, resting mast cells, and regulatory T cells (Tregs) in cluster 2 were significantly increased. Gene set enrichment analysis (GSEA) shows that this cluster involves multiple hallmark pathways. We constructed a five-gene prognostic signature based on m6A RNA methylation, and the risk score based on the prognostic signature was determined to be an independent prognostic indicator of ESCC. More importantly, the prognostic value of the prognostic signature was verified using another independent cohort. m6A regulators are related to TIME, and their copy-number alterations will dynamically affect the number of tumor-infiltrating immune cells.ConclusionOur study established a strong prognostic signature based on m6A RNA methylation regulators; this signature was able to accurately predict the prognosis of ESCC patients. The m6A methylation regulator may be a key mediator of PD-L1 expression and immune cell infiltration and may strongly affect the TIME of ESCC.

Download Full-text

Identification of an immune gene signature for predicting the prognosis of patients with uterine corpus endometrial carcinoma

Cancer Cell International ◽

10.1186/s12935-020-01560-w ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Cankun Zhou ◽

Chaomei Li ◽

Fangli Yan ◽

Yuhua Zheng

Keyword(s):

Endometrial Carcinoma ◽

Immune Cell ◽

Cox Regression ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Immune Gene ◽

Prognostic Signature ◽

Cox Regression Analysis ◽

Uterine Corpus ◽

Immune Genes

Abstract Background Uterine corpus endometrial carcinoma (UCEC) is a frequent gynecological malignancy with a poor prognosis particularly at an advanced stage. Herein, this study aims to construct prognostic markers of UCEC based on immune-related genes to predict the prognosis of UCEC. Methods We analyzed expression data of 575 UCEC patients from The Cancer Genome Atlas database and immune genes from the ImmPort database, which were used for generation and validation of the signature. We constructed a transcription factor regulatory network based on Cistrome databases, and also performed functional enrichment and pathway analyses for the differentially expressed immune genes. Moreover, the prognostic value of 410 immune genes was determined using the Cox regression analysis. We then constructed and verified a prognostic signature. Finally, we performed immune infiltration analysis using TIMER-generating immune cell content. Results The immune cell microenvironment as well as the PI3K-Akt, and MARK signaling pathways were involved in UCEC development. The established prognostic signature revealed a ten-gene prognostic signature, comprising of PDIA3, LTA, PSMC4, TNF, SBDS, HDGF, HTR3E, NR3C1, PGR, and CBLC. This signature showed a strong prognostic ability in both the training and testing sets and thus can be used as an independent tool to predict the prognosis of UCEC. In addition, levels of B cells and neutrophils were significantly correlated with the patient’s risk score, while the expression of ten genes was associated with immune cell infiltrates. Conclusions In summary, the ten-gene prognostic signature may guide the selection of the immunotherapy for UCEC.

Download Full-text

M 6A-related genes characterization in hepatocellular cancer identifies prognostic relevant gene signatures

10.21203/rs.2.22602/v1 ◽

2020 ◽

Author(s):

peng zhu ◽

Qianqian Ren ◽

Nan He ◽

Cheng Zhou ◽

Zhao Gong ◽

...

Keyword(s):

Clinical Outcomes ◽

Cox Regression ◽

Hepatocellular Cancer ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Consensus Clustering ◽

Prognostic Signature ◽

High Group ◽

Rna Methylation ◽

M6a Rna Methylation

Abstract Background Hepatocellular carcinoma (HCC) is among the most common types of cancers that threat the public health worldwide. N6-methyladenosine (m6A) RNA methylation, associated with cancer initiation and progression, is dynamically regulated by m6A RNA methylation associated genes. However, little is known about the expression status and the prognostic value of m6A associated genes in HCC. This study aimed to identify the expression profiling pattern and clinical significance of m6A-related genes in HCC. Methods The Cancer Genome Atlas (TCGA-LIHC), the Gene Expression Omnibus (GSE14520) and the Human Protein Atlas (HPA) databases were gathered for this study. Consensus clustering analysis was performed to identify the clusters of HCC with different clinical outcome. A prognostic signature built by the least absolute shrinkage and selection operator (LASSO) Cox regression model was utilized to discover subtypes correlated with different clinical outcomes of HCC patients and the differences between subgroups were characterized in terms of epigenetic dysregulation and somatic mutation frequencies. Results Most of the m6A-related genes were upregulated and involved with the prognosis and malignancy of HCC. A four-gene prognostic signature revealed two HCC subtypes (namely, risk-high group and risk-low group) that correlated with different clinical outcomes. Patients in risk-high group were accompanied with much more epigenetic silencing and significant mutation at TP53 and FLG, while ALB were mutated frequently for risk-low group. Conclusion Our characterization tightly links the expression of m6A genes with clinical outcomes of HCC, providing valuable molecular-level information that points to decoding heterogeneity, guiding personalized management and treatment of HCC patients.

Download Full-text

Prognostic Value of an m6A RNA Methylation Regulator-Based Signature in Patients with Hepatocellular Carcinoma

BioMed Research International ◽

10.1155/2020/2053902 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Xiaomin Wu ◽

Xiaojing Zhang ◽

Leilei Tao ◽

Xichao Dai ◽

Ping Chen

Keyword(s):

Hepatocellular Carcinoma ◽

Regression Analysis ◽

Cox Regression ◽

Malignant Tumors ◽

The Cancer Genome Atlas ◽

Prognostic Signature ◽

Cox Regression Analysis ◽

Rna Methylation ◽

M6a Rna Methylation ◽

Cluster 2

Purposes. Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. Recent researches have demonstrated that m6A methylation regulators play a key role in various cancers, such as gastric cancer and colon adenocarcinoma. Several m6A methylation regulators are reported to predict the prognosis of HCC. Therefore, there is a need to further identify the predictive value of m6A methylation regulators in HCC. Methods. We utilized The Cancer Genome Atlas (TCGA) database to obtain the gene expression profile of m6A RNA methylation regulators and clinical information for patients with HCC. Besides, we identified two clusters of HCC with various clinical factors by consensus clustering analysis. Then the least absolute shrinkage and selection operator (LASSO) and the Cox regression analysis were applied to construct a prognostic signature. Results. Except for ZC3H13 and METTL14, a majority of the thirteen m6A RNA methylation regulators were significantly overexpressed in HCC specimens. HCC patients were classified into two groups (cluster 1 and cluster 2). The cluster 1 was with a significantly worse prognosis than cluster 2, and most of the 13 known m6A RNA methylation regulators were upregulated in cluster 1. Besides, we developed a prognostic signature consisting of YTHDF2, YTHDF1, METTL3, KIAA1429, and ZC3H13, which could successfully differentiate high-risk patients. More importantly, univariate and multivariate Cox regression analysis indicated that the signature-based risk score was an independent prognostic factor for patients with HCC. Conclusions. Our study showed these five m6A RNA methylation regulators can be used as practical and reliable prognostic tools of HCC, which might have potential value for therapeutic strategies.

Download Full-text

Pan-cancer analysis of two types of uterine cancer uncovered the clinical and prognostic associations with m6A RNA methylation regulators

Molecular Omics ◽

10.1039/d0mo00113a ◽

2021 ◽

Author(s):

Zhilin Zou ◽

Shuguang Zhou ◽

Guosheng Liang ◽

Zhenye Tang ◽

Kai Li ◽

...

Keyword(s):

Uterine Cancer ◽

Rna Methylation ◽

Uterine Corpus ◽

M6a Rna Methylation ◽

The Relationship ◽

Pan Cancer

The role of m6A RNA methylation modification in uterine cancer has not been clearly studied. We explored the relationship between m6A regulators and the clinical and prognosis in uterine corpus...

Download Full-text

Development and Clinical Validation of Novel 8-Gene Prognostic Signature Associated With the Proportion of Regulatory T Cells by Weighted Gene Co-Expression Network Analysis in Uterine Corpus Endometrial Carcinoma

Frontiers in Immunology ◽

10.3389/fimmu.2021.788431 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jinhui Liu ◽

Rui Geng ◽

Sheng Yang ◽

Fang Shao ◽

Zihang Zhong ◽

...

Keyword(s):

Overall Survival ◽

High Risk ◽

Network Analysis ◽

Endometrial Carcinoma ◽

Risk Score ◽

Immune Status ◽

Low Risk ◽

Prognostic Signature ◽

Uterine Corpus ◽

Risk Patients

BackgroundUterine corpus endometrial carcinoma (UCEC) is a gynecological malignant tumor with low survival rate and poor prognosis. The traditional clinicopathological staging is insufficient to estimate the prognosis of UCEC. It is necessary to select a more effective prognostic signature of UCEC to predict the prognosis and immunotherapy effect of UCEC.MethodsCIBERSORT and weighted correlation network analysis (WGCNA) algorithms were combined to screen modules related to regulatory T (Treg) cells. Subsequently, univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were used to identify the genes in key modules. The difference in overall survival (OS) between high- and low-risk patients was analyzed by Kaplan–Meier analysis. The Tregs-related risk signature (TRRS) was screened by uni- and multivariate Cox analyses. Afterward, we analyzed the expression difference of TRRS and verified its ability to predict the prognosis of UCEC and the effect of immunotherapy.ResultsRed module has the highest correlation with Tregs among all clustered modules. Pathways enrichment indicated that the related processes of UCEC were primarily associated to the immune system. Eight genes (ZSWIM1, NPRL3, GOLGA7, ST6GALNAC4, CDC16, ITPK1, PCSK4, and CORO1B) were selected to construct TRRS. We found that this TRRS is a significantly independent prognostic factor of UCEC. Low-risk patients have higher overall survival than high-risk patients. The immune status of different groups was different, and tumor-related pathways were enriched in patients with higher risk score. Low-risk patients are more likely take higher tumor mutation burden (TMB). Meanwhile, they are more sensitive to chemotherapy than patients with high-risk score, which indicated a superior prognosis. Immune checkpoints such as PD-1, CTLA4, PD-L1, and PD-L2 all had a higher expression level in low-risk group. TRRS expression really has a relevance with the sensitivity of UCEC patients to chemotherapeutic drugs.ConclusionWe developed and validated a TRRS to estimate the prognosis and reflect the immune status of UCEC, which could accurately assess the prognosis of patients with UCEC and supply personalized treatments for them.

Download Full-text