[1]巴 颖,张核子,余晨笛,等.基于TCGA数据库构建和评估口腔癌的免疫相关预后模型[J].医学信息,2022,35(06):14-20.[doi:10.3969/j.issn.1006-1959.2022.06.004]
　BA Ying,ZHANG He-zi,YU Chen-di,et al.Construction and Evaluation of Immune Related Prognosis Model of Oral Cancer Based on TCGA Database[J].Medical Information,2022,35(06):14-20.[doi:10.3969/j.issn.1006-1959.2022.06.004]
点击复制

基于TCGA数据库构建和评估口腔癌的免疫相关预后模型()
分享到：

医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
35卷
期数:
2022年06期
页码:
14-20
栏目:
出版日期:
2022-03-15

文章信息/Info

Title:
Construction and Evaluation of Immune Related Prognosis Model of Oral Cancer Based on TCGA Database
文章编号:
1006-1959（2022）06-0014-07
作者:
巴 颖; 张核子; 余晨笛; 等
（深圳市核子基因科技有限公司，广东 深圳 518071）
Author(s):
BA Ying; ZHANG He-zi; YU Chen-di; et al.
(Shenzhen Nucleus Gene Technology Co., Ltd.,Shenzhen 518071,Guangdong,China)
关键词:
口腔癌; 预后模型; 肿瘤微环境; TCGA数据库; 免疫治疗
Keywords:
Oral cancer; Prognostic model; Tumor microenvironment; TCGA database; Immunotherapy
分类号:
R446
DOI:
10.3969/j.issn.1006-1959.2022.06.004
文献标志码:
A
摘要:
目的 构建和评估口腔癌免疫相关的预后模型，探索口腔癌肿瘤免疫微环境的分子特性。方法 基于TCGA数据库中HNSC队列的mRNA表达数据、临床信息和ImmPort数据库中的免疫相关基因列表，利用R包limma分析得到免疫相关的差异表达基因列表，通过单因子回归和多因子回归分析构建口腔癌的免疫相关预后模型，并进一步结合临床特征构建列线图模型，综合评估预后模型的性能。结果 共得到1533个差异表达基因，其中73个基因与免疫相关，通过单因子回归和多因子回归分析得到6个免疫相关的差异基因与预后相关；构建的预后模型ROC曲线下的面积在3年时为0.678，4年时为0.671，5年时为0.683；构建的列线图模型的C-index从0.63增加至0.67，基于建立的预后风险模型，高风险评分组的预后差于低风险评分组，差异有统计学意义（P＜0.05）；预后风险评分与N分期相关（P＜0.05），与病理分期和T分期无关（P＞0.05）；高风险评分组的基因MUC16突变率偏高，而NOTCH1则相反（P＜0.05），且高风险评分组的免疫治疗相关靶基因的表达水平偏低（P＜0.05）；较高的TMB与较差的预后相关（P＜0.05）。结论 本次构建的预后模型和对肿瘤免疫微环境的分子特性的探索可能有助于口腔癌患者的预后风险预测和免疫治疗。
Abstract:
Objective To construct and evaluate an immune-related prognostic model for oral cancer and explore the molecular characteristics of tumor immune microenvironment.Methods Based on the mRNA expression data and clinical information of HNSC cohort in TCGA database and the list of immune-related genes in ImmPort database, the list of immune-related differentially expressed genes was obtained by R-packet limma analysis. The immune-related prognosis model of oral cancer was constructed by single factor regression and multi-factor regression analysis, and the line graph model was further constructed by combining the clinical characteristics to comprehensively evaluate the performance of the prognosis model.Results A total of 1533 DEGs were obtained, of which 73 genes were immune related. Six immune-related DEGs were significantly correlated with prognosis by univariable Cox regression and multivariate Cox regression analysis (P<0.05). The area under the ROC curve of the constructed prognostic model was 0.678 at 3 years, 0.671 at 4 years and 0.683 at 5 years. The C-index of the constructed nomogram model increased from 0.63 to 0.67. Based on the established prognostic risk model, the prognosis of the high-risk score group was worse than that of the low-risk score group (P<0.05). The prognostic risk score was significantly correlated with N stage (P<0.05), but not correlated with pathological stage and T stage (P>0.05). In addition, the mutation rate of gene MUC16 in the high-risk score group was significantly higher, while NOTCH1 was the opposite (P<0.05), and the expression level of immunotherapy related target genes in the high-risk score group was significantly lower (P<0.05), and higher TMB was significantly associated with poor prognosis (P<0.05).Conclusion The constructed prognostic model and the exploration of the molecular characteristics of tumor immune microenvironment will help to predict the prognostic risk and immunotherapy of oral cancer patients.

参考文献/References:

[1]Wong T,Wiesenfeld D.Oral Cancer[J].Aust Dent J,2018,63(Suppl1):S91-S99.[2]Bawaskar HS,Bawaskar PH.Oral diseases: a global public health challenge[J].Lancet,2020,395(10219):185-186.[3]Khurshid Z,Zafar MS,Khan RS,et al.Role of Salivary Biomarkers in Oral Cancer Detection[J].Adv Clin Chem,2018(86):23-70.[4]Lei X,Lei Y,Li JK,et al.Immune cells within the tumor microenvironment: Biological functions and roles in cancer immunotherapy[J].Cancer Lett,2020(470):126-133.[5]Kondoh N,Mizuno-Kamiya M,Umemura N,et al.Immunomodulatory aspects in the progression and treatment of oral malignancy[J].Jpn Dent Sci Rev,2019,55(1):113-120.[6]Dorta-Estremera S,Hegde VL,Slay RB,et al.Targeting interferon signaling and CTLA-4 enhance the therapeutic efficacy of anti-PD-1 immunotherapy in preclinical model of HPV+ oral cancer[J].J Immunother Cancer,2019,7(1):252.[7]Huang GZ,Wu QQ,Zheng ZN,et al.Identification of Candidate Biomarkers and Analysis of Prognostic Values in Oral Squamous Cell Carcinoma[J].Front Oncol,2019(9):1054.[8]Zhao XT,Zhu Y,Zhou JF,et al.Development of a novel 7 immune-related genes prognostic model for oral cancer: A study based on TCGA database[J].Oral Oncol,2021(112):105088.[9]Sasahira T,Kirita T.Hallmarks of Cancer-Related Newly Prognostic Factors of Oral Squamous Cell Carcinoma[J].Int J Mol Sci,2018,19(8):2413.[10]Wang J,Wang Y,Kong F,et al.Identification of a six-gene prognostic signature for oral squamous cell carcinoma[J].J Cell Physiol,2020,235(3):3056-3068.[11]Chen B,Khodadoust MS,Liu CL,et al.Profiling Tumor Infiltrating Immune Cells with CIBERSORT[J].Methods Mol Biol,2018(1711):243-259.[12]Mayakonda A,Lin DC,Assenov Y,et al.Maftools:efficient and comprehensive analysis of somatic variants in cancer[J].Genome Res,2018,28(11):1747-1756.[13]Bagchi S,Yuan R,Engleman EG.Immune Checkpoint Inhibitors for the Treatment of Cancer: Clinical Impact and Mechanisms of Response and Resistance[J].Annu Rev Pathol,2021(16):223-249.[14]Doumas S,Foukas PG,Economopoulou P,et al.Atypical patterns of responses in the era of immune checkpoint inhibitors in head and neck cancer[J].Oral Oncol,2020(100):104477.[15]Yao Y,Yan Z,Lian S,et al.Prognostic value of novel immune-related genomic biomarkers identified in head and neck squamous cell carcinoma[J].J Immunother Cancer,2020,8(2):e000444.[16]Hadler-Olsen E,Wirsing AM.Tissue-infiltrating immune cells as prognostic markers in oral squamous cell carcinoma: a systematic review and meta-analysis[J].Br J Cancer,2019,120(7):714-727.[17]Rah YC,Ahn JC,Jeon EH,et al.Low expression of CD40L in tumor-free lymph node of oral cavity cancer related with poor prognosis[J].Int J Clin Oncol,2018,23(5):851-859.[18]Azad AK,Bairati I,Qiu X,et al.A genome-wide association study of non-HPV-related head and neck squamous cell carcinoma identifies prognostic genetic sequence variants in the MAP-kinase and hormone pathways[J].Cancer Epidemiol,2016(42):173-180.[19]Wang R,Sun Y,Yu W,et al.Downregulation of miRNA-214 in cancer-associated fibroblasts contributes to migration and invasion of gastric cancer cells through targeting FGF9 and inducing EMT[J].J Exp Clin Cancer Res,2019,38(1):20.[20]Peng Z,Guan Q,Luo J,et al.Sophoridine exerts tumor-suppressive activities via promoting ESRRG-mediated β-catenin degradation in gastric cancer[J].BMC Cancer,2020,20(1):582. [21]Chung SJ,Nagaraju GP,Nagalingam A,et al.ADIPOQ/adiponectin induces cytotoxic autophagy in breast cancer cells through STK11/LKB1-mediated activation of the AMPK-ULK1 axis[J].Autophagy,2017,13(8):1386-1403.

相似文献/References:

[1]宁尚波,杨东红,付 爽.选择性动脉灌注化疗在口腔癌治疗中的进展[J].医学信息,2018,31(03):28.[doi:10.3969/j.issn.1006-1959.2018.03.009]
　NING Shang-bo,YANG Dong-hong,FU Shuang.Progress of Selective Arterial infusion Chemotherapy in the Treatment of Oral Cancer[J].Medical Information,2018,31(06):28.[doi:10.3969/j.issn.1006-1959.2018.03.009]
[2]刘 亭,鞠 进.氨磷汀联合精准护理治疗口腔癌放疗的临床效果[J].医学信息,2019,32(17):182.[doi:10.3969/j.issn.1006-1959.2019.17.063]
　LIU Ting,JU Jin.Clinical Effect of Amifostine Combined with Precision Nursing in the Treatment of Oral Cancer Radiotherapy[J].Medical Information,2019,32(06):182.[doi:10.3969/j.issn.1006-1959.2019.17.063]
[3]张祥鑫,董星星,耿 涛,等.基于与铁死亡相关基因的肺腺癌的新型预后模型构建[J].医学信息,2021,34(15):96.[doi:10.3969/j.issn.1006-1959.2021.15.025]
　ZHANG Xiang-xin,DONG Xing-xing,GENG Tao,et al.Construction of A Novel Prognostic Model of Lung Adenocarcinoma Based on Genes Related to Iron Death[J].Medical Information,2021,34(06):96.[doi:10.3969/j.issn.1006-1959.2021.15.025]
[4]操利超,巴 颖,卢晓萍,等.基于TCGA和GEO数据库构建结肠癌预后模型[J].医学信息,2021,34(24):27.[doi:10.3969/j.issn.1006-1959.2021.24.006]
　CAO Li-chao,BA Ying,LU Xiao-ping,et al.Prognostic Model of Colon Cancer Based on TCGA and GEO Database[J].Medical Information,2021,34(06):27.[doi:10.3969/j.issn.1006-1959.2021.24.006]
[5]李一鸣,陈文翔,王 禹,等.肝癌预后模型的构建及其在免疫治疗中的作用研究[J].医学信息,2022,35(04):68.[doi:10.3969/j.issn.1006-1959.2022.04.018]
　LI Yi-ming,CHEN Wen-xiang,WANG Yu,et al.The Construction of a Prognostic Model for Hepatocellular Carcinomaand its Role in Immunotherapy[J].Medical Information,2022,35(06):68.[doi:10.3969/j.issn.1006-1959.2022.04.018]
[6]毛 伟,张 琳,刘清钊.肾透明细胞癌细胞焦亡相关基因预后模型的建立与应用[J].医学信息,2022,35(14):1.[doi:10.3969/j.issn.1006-1959.2022.14.001]
　MAO Wei,ZHANG Lin,LIU Qing-zhao.Constructionand Application of Pyroptosis-related Genes Prognosis Model in Clear Cell Renal Cell Carcinoma[J].Medical Information,2022,35(06):1.[doi:10.3969/j.issn.1006-1959.2022.14.001]
[7]朱思哲,叶成林.基于生物信息学分析构建免疫相关基因脓毒症预后模型[J].医学信息,2022,35(15):1.[doi:10.3969/j.issn.1006-1959.2022.15.001]
　ZHU Si-zhe,YE Cheng-lin.Identification of Immune-related Gene Prognostic Model for Sepsis Based on Bioinformatics Analysis[J].Medical Information,2022,35(06):1.[doi:10.3969/j.issn.1006-1959.2022.15.001]
[8]谢明杰,陈穗保.基于PI3K/AKT信号通路探讨表儿茶素对口腔癌细胞的作用[J].医学信息,2022,35(15):46.[doi:10.3969/j.issn.1006-1959.2022.15.009]
　XIE Ming-jie,CHEN Sui-bao.Effect of Epicatechin on Oral Cancer Cells Based on PI3K/AKT Signaling Pathway[J].Medical Information,2022,35(06):46.[doi:10.3969/j.issn.1006-1959.2022.15.009]
[9]李 敖,王玉然,王文浩.基于公共数据库分析自噬相关基因在肺腺癌患者中的预后意义[J].医学信息,2022,35(22):17.[doi:10.3969/j.issn.1006-1959.2022.22.003]
　LI Ao,WANG Yu-ran,WANG Wen-hao.Prognostic Significance of Autophagy-related Genes in Patients with Lung Adenocarcinoma Based on Public Database Analysis[J].Medical Information,2022,35(06):17.[doi:10.3969/j.issn.1006-1959.2022.22.003]
[10]章海斌,王 练.基于糖酵解相关基因GFUS对三阴性乳腺癌疗效预测模型构建与验证[J].医学信息,2024,37(01):22.[doi:10.3969/j.issn.1006-1959.2024.01.004]
　ZHANG Hai-bin,WANG Lian.Construction and Validation of a Prediction Model for the Efficacy of Triple-negative Breast Cancer Based on the Glycolysis-related Gene GFUS[J].Medical Information,2024,37(06):22.[doi:10.3969/j.issn.1006-1959.2024.01.004]

更新日期/Last Update: 1900-01-01