5-methylcytosine (m5C) modification is involved in tumor progression. However, the lncRNAs associated with m5C in lung squamous cell carcinoma (LUSC) have not been elucidated. The Cancer Genome Atlas database was used to get the open-accessed transcriptional profiling and clinical information of LUSC patients. All the statistical analyses were performed based on R software v 4.0.0 and SPSS13.0. First, there were 614 m5C-related lncRNAs identified under the criterion of |R|>0.4 and < 0.001 with m5C genes. Next, a prognosis model based on ERICD, AL021068.1, LINC01341, AC254562.3, and AP002360.1 was established, which showed good prediction efficiency in both the training and validation cohorts. Next, a nomogram plot was established by combining the risk score and clinical features for a better application in clinical settings. Pathway enrichment analysis showed that the pathways of angiogenesis, TGF-β signaling, IL6-JAK-STAT3 signaling, protein secretion, androgen response, interferon-α response, and unfolded protein response were significantly enriched in the high-risk patients. Immune infiltration analysis showed that the risk score was positively correlated with neutrophils, resting CD4+ memory T cells, and M2 macrophages, yet negatively correlated with follicular helper T cells, CD8+ T cells, and activated NK cells. Moreover, we found that high-risk patients might be more sensitive to immunotherapy, imatinib, yet resistant to erlotinib, gefitinib, and vinorelbine. In summary, our prognosis model is an effective tool that could robustly predict LUSC patient prognosis, which had the potential for clinical guidance.
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http://dx.doi.org/10.3389/fgene.2022.960229 | DOI Listing |
Skin Res Technol
July 2024
Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China.
Background: As the most important modifications on the RNA level, N6-methyladenosine (m6A-) and 5-methylcytosine (m5C-) modification could have a direct influence on the RNAs. Long non-coding RNAs (lncRNAs) could also be modified by methylcytosine modification. Compared with mRNAs, the function of lncRNAs could be more potent to some extent in biological processes like tumorigenesis.
View Article and Find Full Text PDFSci Rep
April 2024
Department of Radiotherapy, The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, 213003, Jiangsu, China.
N6-methyladenosine (m6A) and 5-methylcytosine (m5C) RNA modifications have garnered significant attention in the field of epigenetic research due to their close association with human cancers. This study we focus on elucidating the expression patterns of m6A/m5C-related long non-coding RNAs (lncRNAs) in esophageal squamous cell carcinoma (ESCC) and assessing their prognostic significance and therapeutic potential. Transcriptomic profiles of ESCC were derived from public resources.
View Article and Find Full Text PDFCancer Cell Int
September 2023
Department of Gastrointestinal Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China.
Background: The prognosis of tumor patients can be assessed by measuring the levels of lncRNAs (long non-coding RNAs), which play a role in controlling the methylation of the RNA. Prognosis in individuals with colorectal adenocarcinoma (CRC) is strongly linked to lncRNA expression, making it imperative to find lncRNAs that are associated with RNA methylation with strong prognostic value.
Methods: In this study, by analyzing TCGA dataset, we were able to develop a risk model for lncRNAs that are associated with m5C with prognostic significance by employing LASSO regression and univariate Cox proportional analysis.
BMC Bioinformatics
July 2023
Department of Neurosurgery, General Hospital of Central Theatre Command of People's Liberation Arm, Wuhan, 430070, China.
Background: N6-methyladenosine (m6A) and 5-methylcytosine (m5C) are the main RNA methylation modifications involved in the oncogenesis of cancer. However, it remains obscure whether m6A/m5C-related long non-coding RNAs (lncRNAs) affect the development and progression of low grade gliomas (LGG).
Methods: We summarized 926 LGG tumor samples with RNA-seq data and clinical information from The Cancer Genome Atlas and Chinese Glioma Genome Atlas.
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