Identification of m6A-Related Biomarkers Associated with Prognosis of Colorectal Cancer.
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ABSTRACT:
SUBMITTER: Zhang Z
PROVIDER: S-EPMC8364289 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundColorectal cancer is considered as the second most common cancer worldwide. Studies have shown that m6A RNA methylation abnormalities play an important role in the pathogenesis of many human diseases, including cancer. The current study was designed to characterize the mutation of m6A related genes and explore their prognostic role in colorectal cancer.MethodsRNA-seq data and somatic mutation data of TCGA-COAD and TCGA-READ were downloaded from UCSC xena for comprehensive analysis. M6A related genes were selected from previous literatures, including "Writer" protein (METTL3, METTL5, METTL14, METTL16, ZC3H13, RBM15, WTAP, KIAA1429), "Reader" protein YTHDF1, YTHDF2, YTHDF3, YTHDC1, YTHDC2, HNRNPC, IGF2BP1, IGF2BP2, IGF2BP3), and "Eraser" protein (FTO, ALKBH5). Kaplan-Meier diagrams were used to explore the correlation between m6A-related genes and colorectal cancer prognosis. The correlations between m6A-related genes and clinical parameters and immune-related indicators were explored by Spearman correlation analysis. And finally, the expression patterns of five key genes (RBMX, FMR1, IGF2BP1, LRPPRC and YTHDC2) were detected by qPCR in CRC specimens.ResultsIn CRC, the expressions of m6A-related genes were significantly different between CRC and normal control except METTL14, YTHDF2, YTHDF3. Some of CRC patients (178 in 536) have a m6A-related genes mutation. ZC3H13 has highest mutation frequency of all m6A-related genes. M6A-related genes mainly enrich in regulation of mRNA metabolic process pathway. Patients with high expressions of FMR1, LRPPRC, METTL14, RBMX, YTHDC2, YTHDF2, YTHDF3 have poor prognosis in CRC. There was a significant correlation between the FMR1, LRPPRC, RBMX, YTHDC2, IGF2BP1 expression and the clinical characteristics of CRC. In addition, these genes are significantly associated with immune-related indicators. According to the expression patterns of FMR1, LRPPRC, RBMX, YTHDC2, and IGF2BP1, patients with CRC were clustered into two groups, and their survival was significantly different. By evaluating the tumor microenvironment in two clusters using ssGSEA, expressions of immune checkpoints and GSVA enrichment analysis, we observed that the immune and stem cell index of two cluster were much different. The qPCR results showed that RBMX expression was markedly elevated in cancerous tissues than in the normal colonic tissues.ConclusionOur study identified novel prognostic markers associated with immune of CRC cancer patients. Moreover, the potential mechanisms of prognostic markers in regulating the etiology of CRC cancer were investigated. These findings enrich our understanding of the relationships between m6a related genes and CRC, and may provide novel ideas in the therapy of CRC patients.
| S-EPMC10186803 | biostudies-literature
Project description:BackgroundN6-methyladenosine (m6A)-associated single-nucleotide polymorphisms (SNPs) play important roles in cancers, with previous research suggesting potential associations between m6A-SNPs and cancer. However, the relationship between the genetic determinants of m6A modification and colorectal cancer (CRC) remains unclear.MethodsAn integrative method combining raw data and summary statistics of genome-wide association studies with expression quantitative trait loci (eQTL) and differential expression data was applied to screen potential candidate CRC-associated m6A-SNPs.ResultsA total of 402 m6A-SNPs were identified as being associated with CRC (p < 0.001), with 98 showing eQTL signals. In particular, three genes were found to harbor CRC-associated m6A-SNPs: rs178184 in NOVA1, rs35782901 in HTR4, and rs60571683 in SLCO1B3. These genes were differentially expressed in at least one publicly available dataset (p < 0.05), with NOVA1 (p = 3.41×10-11) and HTR4 (p = 5.56×10-7) being significantly downregulated in CRC (dataset: GSE89076), and SLCO1B3 was significantly overexpressed (datasets: GSE32323 [p = 3.27×10-5], GSE21510 [p = 1.09×10-6], and GSE89076 [p = 7.63×10-6]).ConclusionThis study identified three m6A-SNPs (rs178184, rs35782901, and rs60571683) that may be associated with CRC. However, the lack of analysis of primary CRC samples in order to further elucidate the underlying pathogenesis is a major limitation of this study. Future investigations are needed to validate these CRC-associated m6A-SNPs and explore the m6A-mediated pathogenic mechanism in CRC.
| S-EPMC8297552 | biostudies-literature
Project description:BackgroundChronic myeloid leukemia (CML) and acute myeloid leukemia (AML) are two common malignant disorders in leukemia. Although potent drugs are emerging, CML and AML may still relapse after the drug treatment is stopped. N6-methyladenosine (m6A) and lncRNAs play certain roles in the occurrence and development of tumors, but m6A-modified LncRNAs in ML remain to be further investigated.MethodsIn this study, we extracted and analyzed the TCGA gene expression profile of 151 ML patients and the clinical data. On this basis, we then evaluated the immune infiltration capacity of ML and LASSO-penalized Cox analysis was applied to construct the prognostic model based on m6A related lncRNAs to verify the prognostic risk in clinical features of ML. Quantitative reverse transcription PCR was used to detect the expression level of LncRNA in in ML cell lines K562, MOLM13 and acute monocytic leukemia cell line THP-1.ResultsWe found 70 m6A-related lncRNAs that were related to prognosis, and speculated that the content of stromal cells and immune cells would correlate with the survival of patients with ML. Next, Prognostic risk model of m6A-related lncRNAs was validated to have excellent consistency in clinical features of ML. Finally, we verified the expression levels of CRNDE, CHROMR and NARF-IT1 in ML cell lines K562, MOLM13 and acute monocytic leukemia cell line THP-1, which were significant.ConclusionsThe research provides clues for the prognosis prediction of ML patients by using the m6A-related lncRNAs model we have created, and clarifies the accuracy and authenticity of it.
| S-EPMC8739709 | biostudies-literature
Project description:BackgroundColon adenocarcinoma (COAD) is the most common subtype of colon cancer. However, the 5-year survival rate of COAD patients remains unsatisfactory. N6-methyladenosine (m6A) and long noncoding RNAs (lncRNAs) play essential roles in the occurrence and development of COAD. Herein, we are committed to establish and validate a prognostic m6A-related lncRNA signature.MethodsWe obtained m6A-related lncRNAs by coexpression. The m6A-related lncRNA risk signature (m6ALncSig) was developed via univariate, LASSO, and multivariate Cox regression analyses. Kaplan-Meier (KM) survival curves, gene set enrichment analysis (GSEA), and nomogram generation were conducted to assess m6ALncSig. In addition, the potential immunotherapeutic signatures were also discussed. Real-time PCR and CCK8 analysis were performed to evaluate the expression and functions of lncRNA UBA6-AS1, which was selected.ResultsThe risk signature comprising 14 m6A-related lncRNAs (m6ALncSig) was established, which possessed a superior predictive ability of prognosis. Meanwhile, m6ALncSig was linked to immune cell infiltration. The level of UBA6-AS1 expression was validated in 17 pairs of COAD samples. In cell function experiments, UBA6-AS1 knockdown attenuated cell proliferation capacity.ConclusionsCollectively, m6ALncSig could serve as an independent predictive factor for COAD and accurately estimate the outcome for COAD patients. Importantly, UBA6-AS1 was first identified as an oncogene in COAD.
| S-EPMC9472555 | biostudies-literature
Project description:Colorectal cancer (CRC) is one of the most common malignancies and has been a leading cause of cancer-related death worldwide in recent years. N6-methyladenosine (m6A) methylation is the most abundant epigenetic modification of various types of RNAs, and it plays a vital role in promoting cancer development. Here, we obtained SNV and transcriptome data of CRC from The Cancer Genome Atlas (TCGA). We demonstrated that most m6A methylation regulators were aberrantly expressed in individuals with CRC. The abnormal expression of m6A regulators was caused by their different copy number variation (CNV) patterns, and alteration of m6A regulators was significantly correlated with prognosis and tumor stage. By using weighted coexpression network analysis (WGCNA), we identified m6A-related long noncoding RNAs (lncRNAs) and mRNAs; then we used least absolute shrinkage and selection operator (LASSO) Cox regression analysis to construct m6A-related lncRNA and mRNA prognostic signatures in the TCGA dataset. Furthermore, a nomogram with clinicopathological features, lncRNA risk scores, and mRNA risk scores was established, which showed a strong ability to forecast the overall survival of the individuals with CRC in training and testing sets. In conclusion, m6A methylation regulators played a vital role in affecting the prognosis of subjects with CRC, and m6A-related lncRNAs and mRNAs revealed underlying mechanisms in CRC tumorigenesis and progression.
| S-EPMC8753275 | biostudies-literature
Project description:BackgroundColorectal cancer (CRC) is the third most common cancer in the world, and most of them are adenocarcinomas. CRC could be classified as colon adenocarcinoma (COAD) and rectum adenocarcinoma (READ) according to the original tumorigenesis position. Increasing evidences indicated that microRNAs (miRNAs) play an important role in the occurrence of multiple tumors.MethodsIn this study, we firstly downloaded miRNA (COAD, 8 controls vs. 455 tumors; READ, 3 controls vs. 161 tumors) and mRNA (COAD, 41 controls vs. 478 tumors; READ, 10 controls vs. 166 tumors) data from The Cancer Genome Atlas (TCGA) database and then used DESeq2, RegParallel, miRDB, TargetScanHuman 7.2, DAVID 6.8, STRING, and Cytoscape software to identify the potential prognosis biomarkers.ResultsWe identified 175 differential expression miRNAs (DEMs) and 3747 differential expression genes (DEGs) in COAD and 184 DEMs and 3928 DEGs in READ. And then, we obtained 21 (13 in COAD and 8 in READ) DEMs associated with the survival rates, which correlated with 440 (217 in COAD and 223 in READ) overlapping DEGs. Through survival analysis for those overlapping DEGs, we found 11 (8 in COAD and 3 in READ) overlapping DGEs associated with survival rates of patients, which were correlated with 9 (7 in COAD and 2 in READ) DEMs significantly.ConclusionIn this study, we found several candidate prognostic biomarkers which have been identified in various cancers and also found several new prognosis biomarkers of COAD and READ. In conclusion, this analysis based on theoretical knowledge and clinical outcomes we have done needs further confirmation by more researches.
| S-EPMC7501550 | biostudies-literature
Project description:BackgroundLong non-coding RNAs (lncRNAs) play an important role in angiogenesis, immune response, inflammatory response and tumor development and metastasis. m6 A (N6-methyladenosine) is one of the most common RNA modifications in eukaryotes. The aim of our research was to investigate the potential prognostic value of m6A-related lncRNAs in ovarian cancer (OC).MethodsThe data we need for our research was downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Pearson correlation analysis between 21 m6A regulators and lncRNAs was performed to identify m6A-related lncRNAs. Univariate Cox regression analysis was implemented to screen for lncRNAs with prognostic value. A least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox regression analyses was used to further reduct the lncRNAs with prognostic value and construct a m6A-related lncRNAs signature for predicting the prognosis of OC patients.ResultsTwo hundred seventy-five m6A-related lncRNAs were obtained using pearson correlation analysis. 29 m6A-related lncRNAs with prognostic value was selected through univariate Cox regression analysis. Then, a seven m6A-related lncRNAs signature was identified by LASSO Cox regression. Each patient obtained a riskscore through multivariate Cox regression analyses and the patients were classified into high-and low-risk group using the median riskscore as a cutoff. Kaplan-Meier curve revealed that the patients in high-risk group have poor outcome. The receiver operating characteristic curve revealed that the predictive potential of the m6A-related lncRNAs signature for OC was powerful. The predictive potential of the m6A-related lncRNAs signature was successfully validated in the GSE9891, GSE26193 datasets and our clinical specimens. Multivariate analyses suggested that the m6A-related lncRNAs signature was an independent prognostic factor for OC patients. Moreover, a nomogram based on the expression level of the seven m6A-related lncRNAs was established to predict survival rate of patients with OC. Finally, a competing endogenous RNA (ceRNA) network associated with the seven m6A-related lncRNAs was constructed to understand the possible mechanisms of the m6A-related lncRNAs involed in the progression of OC.ConclusionsIn conclusion, our research revealed that the m6A-related lncRNAs may affect the prognosis of OC patients and identified a seven m6A-related lncRNAs signature to predict the prognosis of OC patients.
| S-EPMC9178823 | biostudies-literature
Project description:The metastasis and poor prognosis are still regarded as the main challenge in the clinical treatment of breast cancer (BC). Both N6-methyladenosine (m6A) modification and lncRNAs play vital roles in the carcinogenesis and evolvement of BC. Considering the unknown association of m6A and lncRNAs in BC, this study therefore aims to discern m6A-related lncRNAs and explore their prognostic value in BC patients. Firstly, a total of 6 m6A-related lncRNAs were screened from TCGA database and accordingly constructed a prognostic-predicting model. The BC patients were then divided into high-risk and low-risk groups dependent on the median cutoff of risk score based on this model. Then, the predictive value of this model was validated by the analyses of cox regression, Kaplan-Meier curve, ROC curve, and the biological differences in the two groups were validated by PCA, KEGG, GSEA, immune status as well as in vitro assay. Finally, we accordingly constructed a risk prognostic model based on the 6 identified m6A-related lncRNAs, including Z68871.1, AL122010.1, OTUD6B-AS1, AC090948.3, AL138724.1, EGOT. Interestingly, the BC patients were divided into the low-risk and high-risk groups with different prognoses according to the risk score. Notably, the risk score of the model was an excellent independent prognostic factor. In the clinical sample validation, m6A regulatory proteins were differentially expressed in patients with different risks, and the markers of tumor-associated macrophages and m6A regulators were co-localized in high-risk BC tissues. This well-validated risk assessment tool based on the repertoire of these m6A-related genes and m6A-related lncRNAs, is of highly prognosis-predicting ability, and might provide a supplemental screening method for precisely judging BC prognosis.
| S-EPMC8555664 | biostudies-literature
Project description:Colorectal cancer (CRC) represents one of the most common malignancies with high morbidity worldwide. RNA methylation (m6A) has been considered to tremendously contribute to cancer initiation and progression since its first discovery. In this study, we comprehensively analyzed associations between mRNA expressions of m6A regulators and CRC tumor samples' epidemiologic information from the Cancer Genome Atlas (TCGA). Multivariate Cox proportional hazard model was applied to screening of m6A regulators whose mRNA expressions were significantly associated with CRC tumor samples' overall survival (OS) probability and those significant regulators were used for LASSO regression analysis to construct CRC prognosis prediction signature. As a result, two regulators i.e., YTHDC2 and ALKBH5 were picked out in multivariate analysis. CRC prognosis signature was constructed based on those two regulators through which CRC tumor samples with favorable and inferior prognosis could definitely be distinguished independent of potential confounding factors. This study should be helpful for identifying prognostic different CRC patients and guiding therapeutic method selection.
| S-EPMC7243737 | biostudies-literature
Project description:Osteosarcoma has the worst prognosis among malignant bone tumors, and effective biomarkers are lacking. Our study aims to explore m6A-related and immune-related biomarkers. Gene expression profiles of osteosarcoma and healthy controls were downloaded from multiple public databases, and their m6A-based gene expression was utilized for tumor typing using bioinformatics. Subsequently, a prognostic model for osteosarcoma was constructed using the least absolute shrinkage and selection operator and multivariate Cox regression analysis, and its immune cell composition was calculated using the CIBERSORTx algorithm. We also performed drug sensitivity analysis for these two genes. Finally, analysis was validated using immunohistochemistry. We also examined the RBM15 gene by qRT-PCR in an in vitro experiment. We collected routine blood data from 1738 patients diagnosed with osteosarcoma and 24,344 non-osteosarcoma patients and used two independent sample t tests to verify the accuracy of the CIBERSORTx analysis for immune cell differences. The analysis based on m6A gene expression tumor typing was most reliable using the two typing methods. The prognostic model based on the two genes constituting RNA-binding motif protein 15 (RBM15) and YTDC1 had a much lower survival rate for patients in the high-risk group than those in the low-risk group (P < 0.05). CIBERSORTx immune cell component analysis demonstrated that RBM15 showed a negative and positive correlation with T cells gamma delta and activated natural killer cells, respectively. Drug sensitivity analysis showed that these two genes showed varying degrees of correlation with multiple drugs. The results of immunohistochemistry revealed that the expression of these two genes was significantly higher in osteosarcoma than in paraneoplastic tissues. The results of qRT-PCR experiments showed that the expression of RBM15 was significantly higher in both osteosarcomas than in the control cell lines. Absolute lymphocyte value, lymphocyte percentage, hematocrit and erythrocyte count were lower in osteosarcoma than in the control group (P < 0.001). RBM15 and YTHDC1 can serve as potential prognostic biomarkers associated with m6A in osteosarcoma.
| S-EPMC10066227 | biostudies-literature