Wu Xingwei, Wang Shengnan, Wu Xiaoming, Chen Qianyi, Cheng Jin, Qi Zhilin
Department of Biochemistry and Molecular Biology, Wannan Medical College, Wuhu, Anhui 241002, P.R. China.
Anhui Province Key Laboratory of Active Biological Macro-molecules, Wannan Medical College, Wuhu, Anhui 241002, P.R. China.
J Cancer. 2024 Feb 17;15(7):2045-2065. doi: 10.7150/jca.92128. eCollection 2024.
RNA methylation modifications are important post-translational modifications that are regulated in an epigenetic manner. Recently, N-methyladenosine (mA) RNA modifications have emerged as potential epigenetic markers in tumor biology. Gene expression and clinicopathological data of LIHC were obtained from the cancer genome atlas (TCGA) database. The relationship between long non-coding RNAs (lncRNAs) and mA-related genes was determined by gene expression analysis using Perl and R software. Co-expression network of mA-lncRNA was constructed, and the relevant lncRNAs associated with prognosis were identified using univariate Cox regression analysis. These lncRNAs were then divided into two clusters (cluster 1 and cluster 2) to determine the differences in survival, pathoclinical parameters, and immune cell infiltration between the different lncRNA subtypes. The least absolute shrinkage and selection operator (LASSO) was carried out for regression analysis and prognostic model. The HCC patients were randomly divided into a train group and a test group. According to the median risk score of the model, HCC patients were divided into high-risk and low-risk groups. We built models using the train group and confirmed them through the test group. The mA-lncRNAs derived from the models were analyzed for the tumor mutational burden (TMB), immune evasion and immune function using R software. AL355574.1 was identified as an important mA-associated lncRNA and selected for further investigation. Finally, experiments were conducted to confirm the effect of AL355574.1 on the biological function of HCC and the possible biological mechanisms. Huh7 and HepG2 cells were transfected with AL355574.1 siRNA and cell proliferation ability was measured by CCK-8, EdU and colony formation assays. Wound healing and transwell assays were used to determine the cell migration capacity. The expression levels of MMP-2, MMP-9, E-cadherin, N-cadherin and Akt/mTOR phosphorylation were all determined by Western blotting. The lncRNAs with significant prognostic value were classified into two subtypes by a consistent clustering analysis. We found that the clinical features, immune cell infiltration and tumor microenvironment (TME) were significantly different between the lncRNA subtypes. Our analysis revealed significant correlations between these different lncRNA subtypes and immune infiltrating and stromal cells. We created the final risk profile using LASSO regression, which notably included three lncRNAs (AL355574.1, AL158166.1, TMCC1-AS1). A prognostic signature consisting of the three lncRNAs was constructed, and the model showed excellent prognostic predictive ability. The overall survival (OS) of the low-risk cohort was significantly higher than that of the high-risk cohort in both the train and test group. Both risk score [hazard ratio (HR)=1.062; P<0.001] and stage (HR=1.647; P< 0.001) were considered independent indicators of HCC prognosis by univariate and multivariate Cox regression analysis. In Huh7 and HepG2 cells, AL355574.1 knockdown inhibited cell proliferation and migration, suppressed the protein expression levels of MMP-2, MMP-9, N-cadherin and Akt/mTOR phosphorylation, but promoted the protein expression levels of E-cadherin. This study established a predictive model for the OS of HCC patients, and these OS-related mA-lncRNAs, especially AL355574.1 may play a potential role in the progression of HCC. v experiments also showed that AL355574.1 could enhance the expression of MMPs and EMT through the Akt/mTOR signaling pathway, thereby affected the proliferation and migration of HCC. This provides a new perspective on the anticancer molecular mechanism of AL355574.1 in HCC.
RNA甲基化修饰是重要的翻译后修饰,以表观遗传方式受到调控。最近,N-甲基腺苷(m⁶A)RNA修饰已成为肿瘤生物学中潜在的表观遗传标志物。从癌症基因组图谱(TCGA)数据库中获取了肝癌(LIHC)的基因表达和临床病理数据。使用Perl和R软件通过基因表达分析确定长链非编码RNA(lncRNA)与m⁶A相关基因之间的关系。构建了m⁶A-lncRNA共表达网络,并使用单变量Cox回归分析鉴定与预后相关的lncRNA。然后将这些lncRNA分为两个簇(簇1和簇2),以确定不同lncRNA亚型在生存、病理临床参数和免疫细胞浸润方面的差异。进行最小绝对收缩和选择算子(LASSO)回归分析和预后模型。将肝癌患者随机分为训练组和测试组。根据模型的中位风险评分,将肝癌患者分为高风险组和低风险组。我们使用训练组构建模型,并通过测试组进行验证。使用R软件分析模型中衍生的m⁶A-lncRNA的肿瘤突变负担(TMB)、免疫逃逸和免疫功能。鉴定出AL355574.1是一种重要的m⁶A相关lncRNA并选择进行进一步研究。最后,进行实验以证实AL355574.1对肝癌生物学功能的影响及其可能的生物学机制。用AL355574.1 siRNA转染Huh7和HepG2细胞,并通过CCK-8、EdU和集落形成试验测量细胞增殖能力。使用伤口愈合试验和Transwell试验测定细胞迁移能力。通过蛋白质印迹法测定MMP-2、MMP-9、E-钙黏蛋白、N-钙黏蛋白和Akt/mTOR磷酸化的表达水平。通过一致性聚类分析将具有显著预后价值的lncRNA分为两个亚型。我们发现lncRNA亚型之间的临床特征、免疫细胞浸润和肿瘤微环境(TME)存在显著差异。我们的分析揭示了这些不同lncRNA亚型与免疫浸润细胞和基质细胞之间存在显著相关性。我们使用LASSO回归创建了最终风险模型,其中特别包括三个lncRNA(AL355574.1、AL158166.1、TMCC1-AS1)。构建了由这三个lncRNA组成的预后特征模型,该模型显示出优异的预后预测能力。在训练组和测试组中,低风险队列的总生存期(OS)均显著高于高风险队列。单变量和多变量Cox回归分析均认为风险评分[风险比(HR)=1.062;P<0.001]和分期(HR=1.647;P<0.001)是肝癌预后的独立指标。在Huh7和HepG2细胞中,敲低AL355574.1可抑制细胞增殖和迁移,抑制MMP-2、MMP-9、N-钙黏蛋白和Akt/mTOR磷酸化的蛋白质表达水平,但促进E-钙黏蛋白的蛋白质表达水平。本研究建立了肝癌患者OS的预测模型,这些与OS相关的m⁶A-lncRNA,尤其是AL355574.1可能在肝癌进展中发挥潜在作用。实验还表明,AL355574.1可通过Akt/mTOR信号通路增强MMPs的表达和上皮-间质转化(EMT),从而影响肝癌的增殖和迁移。这为AL355574.1在肝癌中的抗癌分子机制提供了新的视角。