M6A-related bioinformatics analysis reveals that HNRNPC facilitates progression of OSCC via EMT.

Aging
Guang-Zhao HuangXiao-Zhi Lv

Abstract

Increasing evidence suggests that N6-methyladenosine(m6A) has a vital role in cancer progression. Therefore, we aimed to explore the prognostic relevance of m6A-related genes in oral squamous cell carcinoma (OSCC). First, Expression profiles were downloaded from The Cancer Genome Atlas (TCGA) and m6A-related genes were extracted afterwards. Then, cluster analysis and principal component analysis (PCA) were used to analyze m6A-related genes. And differentially-expressed analysis was performed in R software. Furthermore, a risk model was constructed, and crucial m6A genes were selected to explore its biological effects in OSCC cells. Total of 13 m6A-related genes were extracted and 8 differentially-expressed genes were identified. Subsequently, m6A-based clustering showed 2 subtypes with different clinical outcome. In addition, a risk model was successfully established. Of 13 m6A-related genes, only heterogeneous nuclear ribonucleoprotein C (HNRNPC) might be an independent biomarker and mean unfavorable overall survival in OSCC by univariate and multivariate cox regression analysis. Functional studies revealed that overexpression of HNRNPC promoted carcinogenesis of OSCC via epithelial- mesenchymal transition (EMT). In total, a r...Continue Reading

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Citations

Sep 9, 2020·Open Biology·Wenxiu RuHong Chen
Sep 23, 2020·International Journal of Molecular Sciences·Jonas WeißeTony Gutschner
Feb 16, 2021·Frontiers in Oncology·Lin YangWei-Min Tong
Mar 20, 2021·Molecular Therapy. Nucleic Acids·Hui LiDa Pang
Mar 23, 2021·Frontiers in Cell and Developmental Biology·Huaying ZhaoFeng Wang
May 7, 2021·Journal of Orthopaedic Surgery and Research·Hua LiuZhigang Cai
Jul 24, 2021·The Journal of Experimental Medicine·Anna-Maria HerznerMatthew L Albert
Oct 1, 2021·Oncology Letters·Yang ZhouWeigan Shen

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Methods Mentioned

BETA
transfection
PCA

Software Mentioned

GDC
R
R package glmnet
ggplots
SPSS23
SSPS
LASSO

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