遗传 ›› 2025, Vol. 47 ›› Issue (7): 768-785.doi: 10.16288/j.yczz.25-007
程芙蓉1,2(), 宋文煜2, 曹鹏博2, 周钢桥1,2(
)
收稿日期:
2025-01-06
修回日期:
2025-03-17
出版日期:
2025-03-26
发布日期:
2025-03-26
通讯作者:
周钢桥,博士,研究员,研究方向:医学遗传与基因组学。E-mail: zhougq114@126.com作者简介:
程芙蓉,硕士研究生,专业方向:生物学。E-mail: 1578877852@qq.com
基金资助:
Furong Cheng1,2(), Wenyu Song2, Pengbo Cao2, Gangqiao Zhou1,2(
)
Received:
2025-01-06
Revised:
2025-03-17
Published:
2025-03-26
Online:
2025-03-26
Supported by:
摘要:
抵抗失巢凋亡(anoikis)进而促进癌细胞存活是许多癌症发生、发展的关键特征。肝细胞癌(hepatocellular carcinoma,HCC)是一种复发率高、转移性强的恶性肿瘤,但其失巢凋亡相关研究仍然较少。因此,基于失巢凋亡相关基因(anoikis-related gene,ARG)预测HCC的预后及免疫微环境变化,可为基于失巢凋亡的治疗策略提供新的理论依据。本文基于癌症基因组图谱(The Cancer Genome Atlas,TCGA)HCC转录组数据,鉴定出74个在肝癌中显著差异表达的ARG。通过LASSO-Cox回归模型建立了包含其中9个特征基因的HCC预后风险评分模型。多因素Cox比例风险回归分析表明,该模型能准确预测患者总体生存率,是HCC新的独立预后指标。基于ARG建立的不同风险组在通路活性、免疫细胞浸润和HCC患者生存状态等多方面存在显著差异。与低风险组相比,高风险组中细胞增殖相关通路显著活化,免疫抑制性细胞的浸润比例显著增加,且与肝癌患者对PD-L1单抗治疗耐药相关。上述结果表明,本研究建立的ARG风险评分模型作为一种新的指标可以预测HCC患者的预后,并初步揭示了ARG在肝癌进展中的重要作用。
程芙蓉, 宋文煜, 曹鹏博, 周钢桥. 失巢凋亡相关转录特征预测肝癌预后和免疫微环境的潜在价值[J]. 遗传, 2025, 47(7): 768-785.
Furong Cheng, Wenyu Song, Pengbo Cao, Gangqiao Zhou. Potential value of anoikis transcriptional signatures in predicting prognosis and immune microenvironment in hepatocellular carcinoma[J]. Hereditas(Beijing), 2025, 47(7): 768-785.
图2
肝癌相关ARG预后风险模型的构建及验证 A:通过10倍交叉验证确定LASSO回归模型最佳惩罚因子;B:33个ARG的LASSO回归系数曲线。不同的颜色代表不同的基因;C:森林图显示单因素Cox回归分析显示9个最佳预后ARG的HR和95% CI;D:热图展示了9个最佳预后ARG在TCGA肝癌患者(346例)中的表达水平;E:根据风险评分对肝癌患者进行排序;F:散点图展示了HCC患者生存时间与预后风险评分的相关性。使用χ2检验计算P值;G:三维散点PCA图展示了高风险和低风险评分的肝癌患者;H:根据ARG预后风险模型,分析TCGA肝癌队列中高风险组和低风险组的肝癌患者的Kaplan-Meier生存曲线;I:根据ARG预后风险模型,验证GSE144269队列中具有高风险和低风险评分的肝癌患者的Kaplan-Meier生存曲线。Cox回归分析计算风险比(HR)和95%置信区间(CI),log-rank检验计算P值。HR:风险比;CI:置信区间;PCA:主成分分析;TCGA:癌症基因组图谱。"
图6
失巢凋亡相关基因对免疫细胞浸润的影响 A:根据风险评分,通过CIBERSORT预测TCGA-LIHC肿瘤中22种免疫细胞比例的热图;B:免疫细胞比例和风险评分之间相关性的热图。运用Spearman相关性分析计算相关系数(Rho);C:高风险组和低风险组免疫细胞浸润情况。采用Kruskal-Wallis检验计算显著差异;D:高风险和低风险组中13种免疫功能特征打分情况;E:风险评分和免疫检查点表达水平的相关性热图。运用Spearman相关性分析计算相关系数(Rho);F:高风险和低风险组中免疫检查点的表达水平分析。采用Kruskal-Wallis检验计算显著差异。GSEA:基因集富集分析;TPM:转录本每百万读数;APC:抗原呈递细胞;CCR:C-C趋化因子受体;HLA:人类白细胞抗原;MHC:主要组织相容性复合体;IFN:干扰素。*:P<0.05,**:P< 0.01,***:P<0.001,****:P< 0.0001,ns表示不显著(non-significant)。"
图7
ARG风险评分在肝癌微环境中各细胞类型中的分布及其与肝癌患者免疫治疗响应之间的关系 A:UMAP图展示了肝癌肿瘤微环境中主要细胞类型的分布情况。肝癌单细胞转录组数据来源于GSE149614(包括10例肝癌患者肿瘤样本的40,373个单细胞);B:ARG风险评分在肝癌微环境的各细胞类型中的活性;C:高风险组和低风险组中免疫细胞富集情况。采用Ro/e指数进行组间差异比较;D:高风险组和低风险组免疫细胞浸润比例变化;E:ARG风险评分在肝癌PD-L1单抗治疗队列中响应和未响应患者中的分布差异。此队列基因表达谱数据集来源于GSE279750(包括10例肝癌患者),采用秩和检验计算P值。NR:无响应患者;R:响应患者;Ro/e:观察到的细胞数与预期细胞数的比值;Tcm:中央记忆T细胞;Th1:辅助I型T细胞;Treg:调节T细胞;Te:效应T细胞;Tex:耗竭T细胞;Tm:记忆T细胞;Tpro:增殖T细胞;DC:树突状细胞;Mac:巨噬细胞;NK:自然杀伤性细胞;NKT:自然杀伤性T细胞;Fib:成纤维细胞;Endo:内皮细胞;Epi:上皮细胞。"
图8
BSG在多种肿瘤中表达显著上调,且与肝癌的不良预后显著相关 A:BSG在肝癌与非肿瘤组织中的表达水平。运用秩和检验计算P值;B:BSG在肝癌中的表达与生存率之间的相关性分析。运用Kaplan-Meier生存分析绘制不同组别的生存曲线,Cox回归分析计算风险比(HR)和95%置信区间(CI),log-rank检验计算P值;C:BSG在13种肿瘤中的表达水平。HR:风险比;CI:置信区间;TCGA:癌症基因组图谱;TPM:转录本每百万读数;BLAC:膀胱尿路上皮癌;BRCA:乳腺浸润性癌;CHOL:胆管癌;ESCA:食管癌;HNSC:头颈部鳞状细胞癌;KICH:肾嫌色细胞癌;KIRC:肾透明细胞癌;LUAD:肺腺癌;LUSC:肺鳞状细胞癌;PRAD:前列腺腺癌;STAD:胃腺癌;THCA:甲状腺癌;UCEC:子宫内膜癌;T:肿瘤样本;N:非肿瘤样本。*:P<0.05,**:P< 0.01,***:P<0.001,ns表示不显著(non-significant)。"
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