孙一驰,曾宪琳,张世超
SUN Yichi,ZENG Xianlin,ZHANG Shichao

• 1:贵州医科大学医学影像学院
• 2:贵州省细胞免疫治疗工程研究中心
• 3:贵州省普通高等学校感染免疫与抗体工程特色重点实验室

摘要(Abstract)：

目的 探究糖酵解相关的长链非编码RNA(lncRNA)在头颈鳞状细胞癌（SCCHN）发生、发展中的作用。方法 在TCGA数据库和MSigDB数据库中，获取SCCHN患者的正常组织和癌组织的RNA测序信息和糖酵解基因，通过“limma”包筛选出差异的lncRNA和糖酵解基因，并对差异糖酵解基因进行GO和KEGG功能富集分析；通过Pearson相关分析并筛选出lncRNA后，通过单因素和多因素Cox回归分析构建基于lncRNA表达的风险模型；绘制Kaplan-Meier生存曲线、ROC曲线及决策曲线，通过ESTIMATE估计免疫和基质评分确定SCCHN高/低风险组在信号通路、免疫微环境、免疫检查点、m6A相关基因方面的差异。结果 总共筛选出298个GRLs，通过单因素Cox回归分析确定了60个具有显著预后价值的GRLs，并成功构建了GRLs的风险模型，ROC曲线证明了模型的准确性；相较于高风险组，低风险组免疫细胞浸润增加，并且m6A调节因子和免疫检查点表达均升高。结论 基于GRLs的预后指标是SCCHN患者预后的独立风险因素，是潜在的生物标志物和治疗靶点。
Objective To explore the role of glycolysis-related long non-coding RNAs(GRLs) in the development of squamous cell carcinoma of head and neck( SCCHN).Methods RNA sequencing data and glycolysis-related genes of normal and cancer tissues of SCCHN patients were obtained from TCGA and MSigDB databases. Limma package was used to screen differentially expressed genes and glycolysis-related lncRNA genes. GO annotation and KEGG enrichment analysis were performed on differentially expressed glycolysis-related genes. GRLs were screened out by Pearson correlation analysis. A risk model based on GRL expression was constructed by univariate and multivariate Cox regression analyses. Kaplan-Meier survival curve, ROC curve, and decision curve were drawn. ESTIMATE was performed to estimate immune score and stromal score, which were used to determine the differences in signaling pathways, immune microenvironment, immune checkpoints,and m6A-related genes between SCCHN high-and low-risk groups.Results A total of 298 GRLs were identified. Univariate Cox regression analyses were run on GRLs to obtain 60 GRLs with significant prognostic value. GRL risk model was successfully constructed. The ROC curve results proved the model accuracy. When compared to high risk group, low-risk group had increased immune cell infiltration and elevated expression of both m6A regulators and immune checkpoints.Conclusion GRLs-based prognostic indicators is an independent risk factor for the prognosis of SCCHN patients and a potential biomarker as well as a therapeutic target.

关键词(KeyWords)： 头颈鳞状细胞癌;糖酵解;lncRNA;风险模型;免疫学
squamous cell carcinoma of the head and neck(SCCHN);glycolysis;lncRNA;risk model;immunology

Abstract:

Keywords:

基金项目(Foundation): 贵州省科技计划项目（黔科合支撑[2021]一般431）

作者(Author): 孙一驰,曾宪琳,张世超
SUN Yichi,ZENG Xianlin,ZHANG Shichao

DOI: 10.19367/j.cnki.2096-8388.2022.04.009

参考文献(References)：

• [1] BRAY F, FERLAY J, SOERJOMATARAM I, et al.Global cancer statistics 2018:GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185countries[J]. CA:A Cancer Journal for Clinicians,2018, 68(6):394-424.
• [2] SHIELD K D, FERLAY J, JEMAL A, et al. The global incidence of lip, oral cavity, and pharyngeal cancers by subsite in 2012[J]. CA:A Cancer Journal for Clinicians, 2017, 67(1):51-64.
• [3] KOPPENOL W H, BOUNDDS P L, DANG C V. Otto Warburg's contributions to current concepts of cancer metabolism[J]. Nature Reviews Cancer, 2011, 11(5):325-337.
• [4] BRAGA E A, FRIDMAN M V, MOSCOVTSEV A A, et al. LncRNAs in ovarian cancer progression, metastasis,and main pathways:ceRNA and alternative mechanisms[J]. International Journal of Molecular Sciences, 2020,21(22):1239-1292.
• [5] RAHIMY E, KUO S Z, ONGKEKO W M. Evaluation of non-coding RNAs as potential targets in head and neck squamous cell carcinoma cancer stem cells[J]. Curr Drug Targets, 2014,15(13):1247-1260.
• [6] WANG J Y, LU A Q, CHEN L J. LncRNAs in ovarian cancer[J]. Clinica Chimica Acta; International Journal of Clinical Chemistry, 2019, 490:17-27.
• [7] XU Y, QIU M, SHEN M, et al. The emerging regulatory roles of long non-coding RNAs implicated in cancer metabolism[J]. Molecular Therapy:The Journal of the American Society of Gene Therapy, 2021, 29(7):2209-2218.
• [8] FAN C, TANG Y, WANG J, et al. Role of long non-coding RNAs in glucose metabolism in cancer[J]. Molecular Cancer, 2017, 16(1):130.
• [9] ZHAO L, JI G, LE X, et al. Long noncoding RNA LINC00092 acts in cancer-associated fibroblasts to drive glycolysis and progression of ovarian cancer[J]. Cancer Research, 2017, 77(6):1369-1382.
• [10]LI Z, LI X, WU S, et al. Long non-coding RNA UCA1promotes glycolysis by upregulating hexokinase 2 through the mTOR-STAT3/microRNA143 pathway[J]. Cancer Science, 2014, 105(8):951-955.
• [11]GOLDMAN M J, CRAFT B, HASTIE M, et al. Visualizing and interpreting cancer genomics data via the Xena platform[J]. Nature Biotechnology, 2020, 38(6):675-678.
• [12] HARROW J, FRANKISH A, GONZALEZ J M, et al.GENCODE:the reference human genome annotation for the ENCODE project[J]. Genome Research, 2012, 22(9):1760-1774.
• [13]XU S, TANG L, DAI G, et al. Expression of m6A regulators correlated with immune microenvironment predicts therapeutic efficacy and prognosis in gliomas[J]. Frontiers in Cell and Developmental Biology, 2020, 8:594112.
• [14] ENGEBRETSEN S, BOHLIN J. Statistical predictions with glmnet[J]. Clinical Epigenetics, 2019, 11(1):123.
• [15]SHI J, JIANG D, YANG S, et al. Lpar1, correlated with immune infiltrates, is a potential prognostic biomarker in prostate cancer[J]. Frontiers in Oncology, 2020,10:846
• [16]VANDER HEIDEN M G, DEBERARDINIS R J. Understanding the Intersections between metabolism and cancer biology[J]. Cell, 2017, 168(4):657-669.
• [17]GANAPATHY K S, GESCHWIND J F. Tumor glycolysis as a target for cancer therapy:progress and prospects[J]. Molecular Cancer, 2013, 12:152.
• [18] XING Z, ZHANG Y, LIANG K, et al. Expression of long noncoding RNA YIYA promotes glycolysis in breast cancer[J]. Cancer Research, 2018, 78(16):4524-4532.
• [19]XU S, TANG L, DAI G, et al. Expression of m6A regulators correlated with immune microenvironment predicts therapeutic Efficacy and prognosis in gliomas[J]. Frontiers in Cell and Developmental Biology, 2020,8:594112.
• [20]LI Z, PENG Y, LI J, et al. N(6)-methyladenosine regulates glycolysis of cancer cells through PDK4[J]. Nature Communications, 2020, 11(1):2578.
• [21] YU H, YANG X, TANG J, et al. ALKBH5 inhibited cell proliferation and sensitized bladder cancer cells to cisplatin by m6A-CK2α-mediated glycolysis[J]. Molecular Therapy Nucleic Acids, 2021, 23:27-41.
• [22]LIU J, LIU Z X, WU Q N, et al. Long noncoding RNA AGPG regulates PFKFB3-mediated tumor glycolytic reprogramming[J]. Nature Communications, 2020, 11(1):1507.
• [23]SHEN C, XUAN B, YAN T, et al. m(6)A-dependent glycolysis enhances colorectal cancer progression[J].Molecular Cancer, 2020, 19(1):72.
• [24] CHANG C H, QIU J, O'SULLIVAN D, et al. Metabolic competition in the tumor microenvironment is a driver of cancer progression[J]. Cell, 2015, 162(6):1229-1241.

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