基于肿瘤基因组图谱分析肾透明细胞癌浸润性免疫细胞分布及预后
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摘要
目的了解肾透明细胞癌不同分子亚型中浸润性免疫细胞的分布特点,探讨肾透明细胞癌分子亚型与肿瘤预后的关系。方法采用生物信息学方法,对肿瘤基因组图谱(the cancer genome atlas,TCGA)数据库中肾透明细胞癌样本基因表达定量数据进行分析,对获得的肾透明细胞癌分子亚型,应用CIBERSORT软件计算每个肿瘤样本中22种免疫细胞的分布比例,Cox回归模型评估不同肾透明细胞癌分子亚型与总生存期(OS)的关系。结果验证肾透明细胞癌存在3种亚型。533例肾透明细胞癌肿瘤组织中,M2巨噬细胞(28.33%)、未活化CD4+记忆性T胞(18.05%)、CD8 T细胞(10.05%)、M1巨噬细胞(6.91%)、单核细胞(4.14%)、未活化的肥大细胞(3.86%)、调节性T细胞(3.01%)、滤泡辅助性T细胞(2.83%)及未活化的自然杀伤细胞(2.67%)分布较为丰富。肾透明细胞癌亚型2(4.26%)与亚型3(3.97%)中的调节性T细胞分布比例均显著高于亚型1(1.92%);亚型2(5.79%)与亚型3(5.88%)中的M1巨噬细胞分布比例显著低于亚型1(8.16%);亚型1中的未活化肥大细胞分布比例(5.48%)显著高于亚型2(2.48%)与亚型3(3.45%),以上差异均有统计学意义(均P <0.001)。Kaplan-Meier生存曲线及COX回归分析均发现亚型1组患者总生存期相对较长,且预后相对较好;亚型2组患者总生存期最短,且预后也较差;亚型3组患者总生存期介于亚型1组与亚型2组之间。结论不同肾透明细胞癌分子亚型中,浸润性免疫细胞分布比例差异显著,肾透明细胞癌分子分型与患者预后明显相关。
Objective To investigate the distribution characteristics of infiltrating immune cells in different molecular subtypes of clear cell renal cell carcinoma, and to explore the relationship between molecular subtypes of clear cell renal cell carcinoma and tumor prognosis. Methods Bioinformatics method was used to analyze the quantitative expression data of renal clear cell carcinoma samples in the cancer genome atlas(TCGA) database. For the obtained molecular subsets of clear cell renal cell carcinoma, CIBERSORT software was used to calculate the distribution of 22 immune cells in each tumor sample. Cox regression model was used to assess the relationship between different molecular subtypes of clear cell renal cell carcinoma and overall survival(OS). Results Three subtypes of clear cell renal cell carcinoma were verified. In tissue samples from 533 cases of clear cell renal cell carcinoma, CD8 T cells(10.05%), unactivated CD4+ memory T cells(18.05%), follicular helper T cells(2.83%), regulatory T cells(3.01%), unactivated natural killer cells(2.67%), monocytes(4.14%), M1 macrophages(6.91%), M2 macrophages(28.33%), and unactivated mast cells(3.86%) were more abundantly distributed. The proportion of regulatory T cells in subtype 2(4.26%) and subtype 3(3.97%) was significantly higher than that of subtype 1(1.92%). The proportion of M1 macrophages in subtype 2(5.79%) and subtype 3(5.88%)were significantly lower than those of subtype 1(8.16%). The proportion of unactivated mast cells in subtype 1(5.48%)was significantly higher than that of subtype 2(2.48%) and subtype 3(3.45%). These comparisons were statistically significant(P<0.001). Kaplan-Meier survival curve and COX regression analysis showed that the subtype 1 patients had a relatively longer overall survival and a relatively good prognosis. The subtype 2 patients had the shortest overall survival and poor prognosis, the overall survival of the subtype 3 patients was between subtype 1 and subtype 2. Conclusion The distribution ratios of infiltrating immune cells in different molecular subtypes of clear cell renal cell carcinoma were significantly different, and the molecular classification of clear cell renal cell carcinoma was significantly correlated with the prognosis of patients.
Objective To investigate the distribution characteristics of infiltrating immune cells in different molecular subtypes of clear cell renal cell carcinoma, and to explore the relationship between molecular subtypes of clear cell renal cell carcinoma and tumor prognosis. Methods Bioinformatics method was used to analyze the quantitative expression data of renal clear cell carcinoma samples in the cancer genome atlas(TCGA) database. For the obtained molecular subsets of clear cell renal cell carcinoma, CIBERSORT software was used to calculate the distribution of 22 immune cells in each tumor sample. Cox regression model was used to assess the relationship between different molecular subtypes of clear cell renal cell carcinoma and overall survival(OS). Results Three subtypes of clear cell renal cell carcinoma were verified. In tissue samples from 533 cases of clear cell renal cell carcinoma, CD8 T cells(10.05%), unactivated CD4+ memory T cells(18.05%), follicular helper T cells(2.83%), regulatory T cells(3.01%), unactivated natural killer cells(2.67%), monocytes(4.14%), M1 macrophages(6.91%), M2 macrophages(28.33%), and unactivated mast cells(3.86%) were more abundantly distributed. The proportion of regulatory T cells in subtype 2(4.26%) and subtype 3(3.97%) was significantly higher than that of subtype 1(1.92%). The proportion of M1 macrophages in subtype 2(5.79%) and subtype 3(5.88%)were significantly lower than those of subtype 1(8.16%). The proportion of unactivated mast cells in subtype 1(5.48%)was significantly higher than that of subtype 2(2.48%) and subtype 3(3.45%). These comparisons were statistically significant(P<0.001). Kaplan-Meier survival curve and COX regression analysis showed that the subtype 1 patients had a relatively longer overall survival and a relatively good prognosis. The subtype 2 patients had the shortest overall survival and poor prognosis, the overall survival of the subtype 3 patients was between subtype 1 and subtype 2. Conclusion The distribution ratios of infiltrating immune cells in different molecular subtypes of clear cell renal cell carcinoma were significantly different, and the molecular classification of clear cell renal cell carcinoma was significantly correlated with the prognosis of patients.
引文
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[2]Choueiri TK,Motzer RJ.Systemic therapy for metastatic renalcell carcinoma[J].N Eng J Med,2017,376(4):354-366.
[3]Broad Institute of MIT and Harvard.Broad institute TCGAgenome data analysis center(2016):clustering of m RNAexpression:consensus NMF[EB/OL].[2019-06-03].http://gdac.broadinstitute.org/runs/analyses__2016_01_28/reports/cancer/KIRC-TP/m RNA_Clustering_CNMF/nozzle.html
[4]Zhang S,Zhang E,Long J,et al.Immune infiltration in renal cell carcinoma[J].Cancer Sci,2019,110(5):1564-1572.
[5]高健伟,肖辉,周新,等.免疫检查点抑制剂生物标志物在非小细胞肺癌中的研究进展[J].世界临床药物,2019,40(1):19-23.
[6]张坤,王红.肿瘤基因组图谱泛癌分析计划[J].中国肺癌杂志,2015,18(4):219-223.
[7]Brunet J-P,Tamayo P,Golub TR,et al.Metagenes and molecular pattern discovery using matrix factorization[J].Proc Natl Acad Sci USA,2004,101(12):4164-4169.
[8]Guinney J,Dienstmann R,Wang X,et al.The consensus molecular subtypes of colorectal cancer[J].Nat Med,2015,21(11):1350-1356.
[9]Newman AM,Liu CL,Green MR,et al.Robust enumeration of cell subsets from tissue expression profiles[J].Nat Methods,2015,12(5):453-457.
[10]Ali HR,Chlon L,Pharoah PDP,et al.Patterns of immune infiltration in breast cancer and their clinical implications:a gene-expression-based retrospective study[J].PLo S Med,2016,13(12):e1002194-e1002194.
[11]Rohr-Udilova N,Klinglmüller F,Schulte-Hermann R,et al.Deviations of the immune cell landscape between healthy liver and hepatocellular carcinoma[J].Sci Rep,2018,8(1):6220-6220.
[12]Sadanandam A,Lyssiotis CA,Homicsko K,et al.A colorectal cancer classification system that associates cellular phenotype and responses to therapy[J].Nat Med,2013,19(5):619-625.
[13]Vesely MD,Kershaw MH,Schreiber RD,et al.Natural innate and adaptive immunity to cancer[J].Annu Rev Immunol,2011,29(1):235-271.
[14]Wang Y,Wang Y,Xu L,et al.CD4+T cells promote renal cell carcinoma proliferation via modulating YBX1[J].Exp Cell Res,2018,363(1):95-101.
[15]Yao J,Xi W,Zhu Y,et al.Checkpoint molecule PD-1-assisted CD8+T lymphocyte count in tumor microenvironment predicts overall survival of patients with metastatic renal cell carcinoma treated with tyrosine kinase inhibitors[J].Cancer Manag Res,2018,10:3419-3431.
[16]Kumar P,Bhattacharya P,Prabhakar BS.A comprehensive review on the role of co-signaling receptors and Treg homeostasis in autoimmunity and tumor immunity[J].JAutoimmun,2018,95:77-99.
[17]Santagata S,Napolitano M,D'Alterio C,et al.Targeting CXCR4 reverts the suppressive activity of T-regulatory cells in renal cancer[J].Oncotarget,2017,8(44):77110-77120.
[18]Fu Q,Xu L,Wang Y,et al.Tumor-associated macrophagederived interleukin-23 interlinks kidney cancer glutamine addiction with immune evasion[J].Eur Urol,2019,75(5):752-763.
[19]Gu-Trantien C,Loi S,Garaud S,et al.CD4?follicular helper T cell infiltration predicts breast cancer survival[J].J Clin Invest,2013,123(7):2873-2892.
[20]Shi W,Dong L,Sun Q,et al.Follicular helper T cells promote the effector functions of CD8+T cells via the provision of IL-21,which is downregulated due to PD-1/PD-L1-mediated suppression in colorectal cancer[J].Exp Cell Res,2018,372(1):35-42.