Glioblastoma multiforme(GBM),the most common and aggressive primary brain tumor in adults,is the most malignant and still has no cure.However,the novel role of long non-coding RNAs(lncRNAs)in the pathogenesis of gliob...Glioblastoma multiforme(GBM),the most common and aggressive primary brain tumor in adults,is the most malignant and still has no cure.However,the novel role of long non-coding RNAs(lncRNAs)in the pathogenesis of glioblastoma is attracting extensive attention.LncRNAs are transcribed RNA molecules over 200 nucleotides long that do not encode proteins.Unlike small non-coding RNAs,such as microRNAs(miRNAs),lncRNAs have more complex secondary and tertiary structures that enable them to interact with DNA,RNA,and proteins and perform multiple regulatory functions.LncRNAs act as molecular sponges,absorbing and sequestering other biomolecules,particularly miRNAs,thereby preventing these molecules from performing their normal functions.LncRNAs influence glioblastoma through gene expression regulation,molecular sponge capacity,epigenetic modulation,and signaling pathway interactions.In glioblastoma,a large number of lncRNAs have been found to be abnormally expressed,affecting tumor growth,invasion and resistance to treatment.Due to its regulatory role and disease-specific expression patterns,lncRNA has become a potential biomarker for glioblastoma and a promising new therapeutic target.This paper discusses the spongy role of lncRNAs in glioblastoma and its potential therapeutic applications,which will lay a foundation for our understanding of glioblastoma biology and the development of new diagnostic and therapeutic strategies in the future.展开更多
Aging is highly associated with tumor formation and progression.However,little research has explored the association of aging-related lncRNAs(ARLs)with the prognosis and tumor immune microenvironment(TIME)of head and ...Aging is highly associated with tumor formation and progression.However,little research has explored the association of aging-related lncRNAs(ARLs)with the prognosis and tumor immune microenvironment(TIME)of head and neck squamous cell carcinoma(HNSCC).RNA sequences and clinicopathological data of HNSCC patients and normal subjects were downloaded from The Cancer Genome Atlas.In the training group,we used Pearson correlation,univariate Cox regression,least absolute shrinkage/selection operator regression analyses,and multivariate Cox regression to build a prognostic model.In the test group,we evaluated the model.Multivariate Cox regression was done to screen out independent prognostic factors,with which we constructed a nomogram.Afterward,we demonstrated the predictive value of the risk scores based on the model and the nomogram using time-dependent receiver operating characteristics.Gene set enrichment analysis,immune correlation analysis,and half-maximal inhibitory concentration were also performed to reveal the different landscapes of TIME between risk groups and to predict immuno-and chemo-therapeutic responses.The most important LINC00861 in the model was examined in HNE1,CNE1,and CNE2 nasopharyngeal carcinoma cell lines and transfected into the cell lines CNE1 and CNE2 using the LINC00861-pcDNA3.1 construct plasmid.In addition,CCK-8,Edu,and SA-β-gal staining assays were conducted to test the biofunction of LINC00861 in the CNE1 and CNE2 cells.The signature based on nine ARLs has a good predictive value in survival time,immune infiltration,immune checkpoint expression,and sensitivity to multiple drugs.LINC00861 expression in CNE2 was significantly lower than in the HNE1 and CNE1 cells,and LINC00861 overexpression significantly inhibited the proliferation and increased the senescence of nasopharyngeal carcinoma cell lines.This work built and verified a new prognostic model for HNSCC based on ARLs and mapped the immune landscape in HNSCC.LINC00861 is a protective factor for the development of HNSCC.展开更多
目的:胶质母细胞瘤(glioblastoma,GBM)是最常见的原发性中枢神经系统恶性肿瘤,预后差。双硫死亡是一种新发现的调节性细胞死亡形式,其失调与癌症进展及治疗相关。目前,关于双硫死亡相关的长链非编码RNAs(disulfidptosis-related long no...目的:胶质母细胞瘤(glioblastoma,GBM)是最常见的原发性中枢神经系统恶性肿瘤,预后差。双硫死亡是一种新发现的调节性细胞死亡形式,其失调与癌症进展及治疗相关。目前,关于双硫死亡相关的长链非编码RNAs(disulfidptosis-related long non-coding RNAs,DRLs)在GBM中的研究还很有限。本研究旨在探讨DRLs与GBM患者预后的关系,构建并验证预后模型。方法:从癌症基因组图谱网站下载153例GBM患者样本的RNA测序数据和相应的临床特征,并从既往研究中获得10个双硫死亡相关的基因。将153例GBM患者样本按照1?1的比例随机分为训练集和验证集,前者用于筛选与GBM患者预后相关的DRLs和构建预后模型,后者和全部数据集的数据用于检验预后模型的准确性。根据单因素Cox回归分析、LASSO回归分析和多因素Cox回归分析,筛选出与GBM预后相关的DRLs并构建最佳预后模型。采用Kaplan-Meier生存分析、受试者操作特征(receiver operator characteristic,ROC)曲线分析和C指数分析评估该模型的预测性能。根据风险评分中位数分别将训练集、验证集和全部数据集的GBM患者分为高、低风险组,进一步对每个数据集中不同风险组之间的基因进行基因集变异分析、基因集富集分析、免疫微环境特征和免疫检查点基因分析、抗肿瘤药物敏感性预测分析。结果:构建并验证了一个包含9个DRLs的预后模型。训练集、验证集和全部数据集中风险评分与患者预后生存状态的关系散点图显示风险评分越高,病死患者越多,符合模型的预测;Kaplan-Meier生存分析结果表明3个数据集中高风险组GBM患者的总生存期均低于低风险组;ROC曲线分析结果表明训练集1、2和3年的曲线下面积(area under the curve,AUC)均保持在0.75以上,而验证集和全部数据集1、2和3年的AUC均分别保持在0.60和0.70以上,表明该模型预测性能良好;与年龄和性别相比,该风险模型更能预测GBM患者生存时间。基因分析结果表明预后较差的高风险组富集了免疫相关的通路,具有较高的免疫得分、免疫相关功能激活、免疫细胞浸润和较高的免疫检查点基因表达,且表现出对多种抗肿瘤药物敏感。结论:基于9个DRLs构建的预后模型对GBM患者的预后评估具有潜在的临床应用价值,有助于评估不同风险组GBM患者的基因差异、免疫浸润情况和抗肿瘤药物敏感性,为实现GBM的个性化治疗提供依据。展开更多
基金The study is funded by Binzhou Medical University Research Fund Project(Grant Number BY2021KYQD02).
文摘Glioblastoma multiforme(GBM),the most common and aggressive primary brain tumor in adults,is the most malignant and still has no cure.However,the novel role of long non-coding RNAs(lncRNAs)in the pathogenesis of glioblastoma is attracting extensive attention.LncRNAs are transcribed RNA molecules over 200 nucleotides long that do not encode proteins.Unlike small non-coding RNAs,such as microRNAs(miRNAs),lncRNAs have more complex secondary and tertiary structures that enable them to interact with DNA,RNA,and proteins and perform multiple regulatory functions.LncRNAs act as molecular sponges,absorbing and sequestering other biomolecules,particularly miRNAs,thereby preventing these molecules from performing their normal functions.LncRNAs influence glioblastoma through gene expression regulation,molecular sponge capacity,epigenetic modulation,and signaling pathway interactions.In glioblastoma,a large number of lncRNAs have been found to be abnormally expressed,affecting tumor growth,invasion and resistance to treatment.Due to its regulatory role and disease-specific expression patterns,lncRNA has become a potential biomarker for glioblastoma and a promising new therapeutic target.This paper discusses the spongy role of lncRNAs in glioblastoma and its potential therapeutic applications,which will lay a foundation for our understanding of glioblastoma biology and the development of new diagnostic and therapeutic strategies in the future.
基金supported by the National Natural Science Foundation of China(82003228)the Natural Science Foundation of Jiangsu Province(BK20201080)the Research Project of Clinical Medical Science and Technology Development Fund of Jiangsu University(JLY2021097).
文摘Aging is highly associated with tumor formation and progression.However,little research has explored the association of aging-related lncRNAs(ARLs)with the prognosis and tumor immune microenvironment(TIME)of head and neck squamous cell carcinoma(HNSCC).RNA sequences and clinicopathological data of HNSCC patients and normal subjects were downloaded from The Cancer Genome Atlas.In the training group,we used Pearson correlation,univariate Cox regression,least absolute shrinkage/selection operator regression analyses,and multivariate Cox regression to build a prognostic model.In the test group,we evaluated the model.Multivariate Cox regression was done to screen out independent prognostic factors,with which we constructed a nomogram.Afterward,we demonstrated the predictive value of the risk scores based on the model and the nomogram using time-dependent receiver operating characteristics.Gene set enrichment analysis,immune correlation analysis,and half-maximal inhibitory concentration were also performed to reveal the different landscapes of TIME between risk groups and to predict immuno-and chemo-therapeutic responses.The most important LINC00861 in the model was examined in HNE1,CNE1,and CNE2 nasopharyngeal carcinoma cell lines and transfected into the cell lines CNE1 and CNE2 using the LINC00861-pcDNA3.1 construct plasmid.In addition,CCK-8,Edu,and SA-β-gal staining assays were conducted to test the biofunction of LINC00861 in the CNE1 and CNE2 cells.The signature based on nine ARLs has a good predictive value in survival time,immune infiltration,immune checkpoint expression,and sensitivity to multiple drugs.LINC00861 expression in CNE2 was significantly lower than in the HNE1 and CNE1 cells,and LINC00861 overexpression significantly inhibited the proliferation and increased the senescence of nasopharyngeal carcinoma cell lines.This work built and verified a new prognostic model for HNSCC based on ARLs and mapped the immune landscape in HNSCC.LINC00861 is a protective factor for the development of HNSCC.
文摘目的:胶质母细胞瘤(glioblastoma,GBM)是最常见的原发性中枢神经系统恶性肿瘤,预后差。双硫死亡是一种新发现的调节性细胞死亡形式,其失调与癌症进展及治疗相关。目前,关于双硫死亡相关的长链非编码RNAs(disulfidptosis-related long non-coding RNAs,DRLs)在GBM中的研究还很有限。本研究旨在探讨DRLs与GBM患者预后的关系,构建并验证预后模型。方法:从癌症基因组图谱网站下载153例GBM患者样本的RNA测序数据和相应的临床特征,并从既往研究中获得10个双硫死亡相关的基因。将153例GBM患者样本按照1?1的比例随机分为训练集和验证集,前者用于筛选与GBM患者预后相关的DRLs和构建预后模型,后者和全部数据集的数据用于检验预后模型的准确性。根据单因素Cox回归分析、LASSO回归分析和多因素Cox回归分析,筛选出与GBM预后相关的DRLs并构建最佳预后模型。采用Kaplan-Meier生存分析、受试者操作特征(receiver operator characteristic,ROC)曲线分析和C指数分析评估该模型的预测性能。根据风险评分中位数分别将训练集、验证集和全部数据集的GBM患者分为高、低风险组,进一步对每个数据集中不同风险组之间的基因进行基因集变异分析、基因集富集分析、免疫微环境特征和免疫检查点基因分析、抗肿瘤药物敏感性预测分析。结果:构建并验证了一个包含9个DRLs的预后模型。训练集、验证集和全部数据集中风险评分与患者预后生存状态的关系散点图显示风险评分越高,病死患者越多,符合模型的预测;Kaplan-Meier生存分析结果表明3个数据集中高风险组GBM患者的总生存期均低于低风险组;ROC曲线分析结果表明训练集1、2和3年的曲线下面积(area under the curve,AUC)均保持在0.75以上,而验证集和全部数据集1、2和3年的AUC均分别保持在0.60和0.70以上,表明该模型预测性能良好;与年龄和性别相比,该风险模型更能预测GBM患者生存时间。基因分析结果表明预后较差的高风险组富集了免疫相关的通路,具有较高的免疫得分、免疫相关功能激活、免疫细胞浸润和较高的免疫检查点基因表达,且表现出对多种抗肿瘤药物敏感。结论:基于9个DRLs构建的预后模型对GBM患者的预后评估具有潜在的临床应用价值,有助于评估不同风险组GBM患者的基因差异、免疫浸润情况和抗肿瘤药物敏感性,为实现GBM的个性化治疗提供依据。
