Identification of a three-m6A related gene risk score model as a potential prognostic biomarker in clear cell renal cell carcinoma

N6-methyladenosine (m 6 A) modification is the most abundant modification on eukaryotic RNA. In recent years, lots of studies have reported that m 6 A modification and m 6 A RNA methylation regulators were involved in cancer progression. However, the m 6 A level and its regulators in esophageal cancer (ESCA) remain poorly understood. In this study, we analyzed the expression of m 6 A regulators using The Cancer Genome Atlas data and found 14 of 19 m 6 A regulators are significantly increased in ESCA samples. Then we performed a univariate Cox regression analysis and LASSO (least absolute shrinkage and selection operator) Cox regression model to investigate the prognostic role of m 6 A regulators in ESCA, and the results indicated that a two-gene prognostic signature including ALKBH5 and HNRNPA2B1 could predict overall survival of ESCA patients. Moreover, HNRNPA2B1 is higher expressed in high-risk scores subtype of ESCA, indicating that HNRNPA2B1 may be involved in ESCA development. Subsequently, we confirmed that the level of m 6 A and HNRNPA2B1 was significantly increased in ESCA. We also found that HNRNPA2B1 expression positively correlated with tumor diameter and lymphatic metastasis of ESCA. Moreover, functional study showed that knockdown of HNRNPA2B1 inhibited the proliferation, migration, and invasion of ESCA. Mechanistically, we found that knockdown of HNRNPA2B1 inhibited the expression of de novo fatty acid synthetic enzymes, ACLY and ACC1, and subsequently suppressed cellular lipid accumulation. In conclusion, our study provides critical clues to understand the role of m 6 A and its regulators in ESCA. Moreover, HNRNPA2B1 functions as an oncogenic factor in promoting ESCA progression via up-regulation of fatty acid synthesis enzymes ACLY and ACC1, and it may be a promising prognostic biomarker and therapeutic target for human ESCA.

Section: Methodsmentioning

confidence: 99%

m6A Reader HNRNPA2B1 Promotes Esophageal Cancer Progression via Up-Regulation of ACLY and ACC1

Guo

Wang

et al. 2020

“…Chen et al systematically analyzed the global m6A modification pattern in KIRC and correlated it with cancerrelated gene expressions (39). Zhou (44). However, all of them have not correlated m6A regulators with TME.…”

Section: Discussionmentioning

confidence: 99%

RNA Modification of N6-Methyladenosine Predicts Immune Phenotypes and Therapeutic Opportunities in Kidney Renal Clear Cell Carcinoma

et al. 2021

RNA modification of N6-methyladenosine (m6A) plays critical roles in various biological processes, such as cancer development, inflammation, and the anticancer immune response. However, the role played by a comprehensive m6A modification pattern in regulating anticancer immunity in kidney renal clear cell carcinoma (KIRC) has not been fully elucidated. In this study, we identified two independent m6A modification patterns with distinct biological functions, immunological characteristics, and prognoses in KIRC. Next, we developed an m6A score algorithm to quantify an individual's m6A modification pattern, which was independently validated in external cohorts. The m6A cluster 1 and low m6A score groups were characterized by a hot tumor microenvironment with an increased infiltration level of cytotoxic immune cells, higher tumor mutation burden, higher immune checkpoint expression, and decreased stroma-associated signature enrichment. In general, the m6A cluster 1 and low m6A score groups reflected an inflammatory phenotype, which may be more sensitive to anticancer immunotherapy. The m6A cluster 2 and high m6A score groups indicated a non-inflammatory phenotype, which may not be sensitive to immunotherapy but rather to targeted therapy. In this study, we first identified m6A clusters and m6A scores to elucidate immune phenotypes and to predict the prognosis and immunotherapy response in KIRC, which can guide urologists for making more precise clinical decisions.

“…The prognostic value of these regulators have also been analyzed in multiple malignant tumors, including liver cancer ( 45 ), gastric cancer ( 46 ), clear cell renal cell carcinoma (ccRCC) ( 47 , 48 ), colorectal cancer ( 32 ). The prognostic signature obtained using two m 6 A RNA methylation regulators (METTL14 and METTL3) had significant value in ccRCC, the AUC value for their risk prediction is 0.706 ( 47 , 48 ). The expression of METTL14 and ALKBH5 were reported to be independent prognostic factors in CRC ( 32 ).…”

Section: Discussionmentioning

confidence: 99%

A Ten-N6-Methyladenosine (m6A)-Modified Gene Signature Based on a Risk Score System Predicts Patient Prognosis in Rectum Adenocarcinoma

Huang

Wang

et al. 2021

ObjectivesThe study aims to analyze the expression of N6-methyladenosine (m6A)-modified genes in rectum adenocarcinoma (READ) and identify reliable prognostic biomarkers to predict the prognosis of READ.Materials and MethodsRNA sequence data of READ and corresponding clinical survival data were obtained from The Cancer Genome Atlas (TCGA) database. N6-methyladenosine (m6A)-modified genes in READ were downloaded from the “m6Avar” database. Differentially expressed m6A-modified genes in READ stratified by different clinicopathological characteristics were identified using the “limma” package in R. Protein-protein interaction (PPI) network and co-expression analysis of differentially expressed genes (DEGs) were performed using “STRING” and Cytoscape, respectively. Principal component analysis (PCA) was done using R. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were used to functionally annotate the differentially expressed genes in different subgroups. Univariate Cox regression analyses were conducted to identify the powerful independent prognostic factors in READ associated with overall survival (OS). A robust likelihood-based survival model was built using the “rbsurv” package to screen for survival-associated signature genes. The Support Vector Machine (SVM) was used to predict the prognosis of READ through the risk score of survival-associated signature genes. Correlation analysis were carried out using GraphPad prism 8.ResultsWe screened 974 differentially expressed m6A-modified genes among four types of READ samples. Two READ subgroups (group 1 and group 2) were identified by K means clustering according to the expression of DEGs. The two subgroups were significantly different in overall survival and pathological stages. Next, 118 differentially expressed genes between the two subgroups were screened and the expression of 112 genes was found to be related to the prognosis of READ. Next, a panel of 10 survival-associated signature genes including adamtsl1, csmd2, fam13c, fam184a, klhl4, olfml2b, pdzd4, sec14l5, setbp1, tmem132b was constructed. The signature performed very well for prognosis prediction, time-dependent receiver-operating characteristic (ROC) analysis displaying an area under the curve (AUC) of 0.863, 0.8721, and 0.8752 for 3-year survival rate, prognostic status, and pathological stage prediction, respectively. Correlation analysis showed that the expression levels of the 10 m6A-modified genes were positively correlated with that of m6A demethylase FTO and ALKBH5.ConclusionThis study identified potential m6A-modified genes that may be involved in the pathophysiology of READ and constructed a novel gene expression panel for READ risk stratification and prognosis prediction.