摘要
目的 寻找合适的标志物,联合BRAF突变分析,筛选出适合使用免疫治疗的皮肤黑色素瘤(skin cutaneous melanoma,SKCM)患者,实现精准治疗。方法 从癌症基因组图谱(The Cancer Genome Atlas,TCGA)数据库中获取SKCM患者(n=470)的数据,根据BRAF突变情况,分为非突变组(n=230)和突变组(n=235)。用R软件的Limma包分析上述两组患者各基因的mRNA表达,使用fold-change和校正后P值筛选出差异表达基因(differentially expressed gene,DEG),通过GO(Gene Ontology)数据库对差异基因进行通路富集分析。然后通过String数据库分析趋化因子受体4(chemokine receptor 4,CXCR4)与IL18和TP53分子的作用关系。此外利用Spearman的相关分析统计微卫星不稳定性(microsatellite instability,MSI)与CXCR4表达的相关性,用Pearson系数描述CXCR4与免疫检查点表达的相关性,同时利用Wilcoxon检验分析BRAF突变组与非突变组之间CXCR4的表达差异。最后,我们采用ggplot2和pheatmap分析了SIGLEC15、TIGIT、CD274、HAVCR2、PDCD1、CTLA4、LAG3和PDCD1LG2这8个基因转录本的表达值,并使用肿瘤免疫功能障碍和排斥(tumor immune dysfunction and exclusion,TIDE)算法预测各组免疫检查点阻断(immune checkpoint blockade,ICB)治疗反应性。结果 BRAF基因在SKCM中广泛突变,其突变引起的差异性表达基因主要集中在IL-18和TP53两个通路。CXCR4是与肿瘤关系最为密切的趋化因子,且与IL18和TP53均有密切关系。SKCM癌组织中CXCR4表达显著升高,且在BRAF突变患者中表达水平更高。进一步分析发现,CXCR4与免疫检查点分子HAVCR2,PDCD1,PDCD1LG2,TIGIT在表达上存在正相关性。结合CXCR4表达与BRAF突变情况,将SKCM患者分为4组:BRAF^(WT)-CXCR4高表达(G1组)、BRAF^(WT)-CXCR4低表达(G2组)、BRAF^(MUT)-CXCR4高表达(G3组)、BRAF^(MUT)-CXCR4低表达(G4组),并从免疫检查点表达、ICB预测评分方面评估CXCR4表达联合BRAF突变分析在免疫治疗预测方面的作用,并筛选出更适合免疫治疗的组别。结果表明,CXCR4低表达且BRAF^(WT)的患者MSI高,免疫检查点分子低表达且TIDE评分低即G2组最适合ICB治疗。结论 CXCR4有望成为监测疗效的潜在生物标志物。CXCR4表达水平联合BRAF突变分析,可为筛选出适合ICB治疗的SKCM患者提供理论基础。
Objective To find suitable markers combined with BRAF mutation analysis to screen out skin cutaneous melanoma(SKCM) patients that are suitable for immunotherapy. Methods We acquired the database of SKCM from the The Cancer Genome Atlas(TCGA) and divided the patients(n=470) into wild-type group(n=230) and mutation group(n=235). Limma package of R software was used to study the expression of mRNAs in the two groups.Differentially expressed genes(DEGs) were screened out by fold-change values and adjusted P. We performed enrichment analysis of DEGs via the Gene Ontology(GO) database. String database showed that CXCR4 might interact closely with TP53 and IL18.Pearson correlation analyses were used to describe the correlation between CXCR4 and immune checkpoint. Then we used Spearman’s correlation analysis to describe the correlation between CXCR4expression and microsatellite instability(MSI). Wilcoxon test was applied to analyze the difference in CXCR4 expression between the BRAF mutation group and the non-mutation group. Lastly, the expression levels of SIGLEC15,TIGIT,CD274,HAVCR2,PDCD1,CTLA4,LAG3, and PDCD1LG2 were implemented by packages ggplot2 and pheatmap in R foundation. Moreover,the potential immune checkpoint blockade(ICB) response of each subgroup was predicted with tumor immune dysfunction and exclusion(TIDE) algorithm. Results BRAF gene was widely mutated in SKCM, and DEGs caused by BRAF mutation were mainly concentrated in the IL18 and TP53 pathways. Moreover, CXCR4 was a chemokine closely associated with tumors, and had an expression regulatory network with IL18 and TP53.We found that the expression of CXCR4 remarkably increased in tumor tissues of SKCM, especially in mutation group. We further analyzed the correlation between CXCR4 and immune checkpoints.Interestingly, CXCR4 positively correlated with HAVCR2, PDCD1,PDCD1LG2 and TIGIT. Furtherly, combining BRAF mutation analysis with CXCR4 expression,we divided SKCM patients into 4 subgroups, which were BRAF^(WT)/CXCR4-high(G1),BRAF^(WT)/CXCR4-low(G2), BRAF^(MUT)/CXCR4-high(G3) and BRAF^(MUT)/CXCR4-low(G4). We selected the subgroup which suited for immunotherapy via analyzing the MSI score and expressions of the immune checkpoint, and then predicting immune response.Notably,the subgroup with lower CXCR4 expression was accompanied by higher MSI instability, lower immune checkpoint expression and lower TIDE score. Namely, G2 is the subgroup most suitable for ICB treatment. Conclusion CXCR4 is hopeful to be a potential biomarker for monitoring curative effects.Combining with BRAF detection,it provides a theoretical basis for screening out appropriate SKCM patients to receive ICB treatment.
作者
戴赛林
邵甲云
雪燕
郑洁
DAI Sai-lin;SHAO Jia-yun;XUE Yan;ZHENG Jie(Department of Anesthesiology,Fudan University Shanghai Cancer Center-Department of Oncology,Shanghai Medical College,Fudan University,Shanghai 200032,China;Department of Anesthesiology,Guangdong General Hospital-Guangdong Academy of Medical Sciences,Guangzhou 510080,Guangdong Province,China)
出处
《复旦学报(医学版)》
CAS
CSCD
北大核心
2023年第1期71-79,共9页
Fudan University Journal of Medical Sciences