PO.CL05.05 · 临床研究
三阴性乳腺癌中蒽环类药物诱导的化疗免疫调节的鉴定与表征
Identification and characterization of anthracycline-induced chemoimmunomodulation in triple-negative breast cancer
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
三阴性乳腺癌(TNBC)是最致命的乳腺癌亚型,晚期病例的中位生存期 < 24个月。尽管TNBC的治疗已有进展,化疗仍是根治性治疗的基石。尽管化疗在TNBC治疗中处于核心地位,支撑化疗免疫调节效应(chemoimmunomodulation;CIM)——它使长期疗效及与其他治疗方式的协同成为可能——的分子驱动因素仍研究不足,从而限制了优化化疗方案的努力。本研究旨在鉴定并表征蒽环类药物诱导的CIM状态以应对这一挑战。为此,我们将化疗免疫调节诱导分类器(CIMIC)流程应用于源自TNBC细胞系(N = 6;各3个生物学重复)的差值基因表达值(ΔGE;Δlog2(TPM+1)),这些细胞系在暴露于IC30剂量多柔比星48小时前后通过bulk RNA测序进行了分析。CIMIC是一条迭代式无监督聚类流程,根据样本对横跨19条CIM通路的3,100个基因的诱导情况将样本归入不同的组。使用CIMIC,我们在样本中鉴定出两条离散的CIM轨迹:一条功能性轨迹(Fun-CIM;N = 3个细胞系)和一条功能失调性轨迹(Dys-CIM;N = 3个细胞系),二者高度区分(轮廓系数 = 0.95),并且经标准聚类指标在多次自助重采样中判定为稳定(模糊聚类比例 = 0.00;聚类一致性得分 = 1)。这些CIM状态的特征是抗肿瘤炎症标志物的显著差异性诱导,包括趋化因子(CXCL14)和免疫介质(IFNB1及IL12A/B)(Fun-CIM相对Dys-CIM均为倍数变化(FC)≥ 1.3;p < 0.05;FDR < 0.15),以及促肿瘤标志物,包括肿瘤监视抑制因子(THBS1和TGFB2)、免疫抑制性细胞群体介质(NNMT)和肿瘤内在应激适应信号(EIF2A、YARS1和XPOT)(Dys-CIM相对Fun-CIM均为FC ≥ 1.3;p < 0.05;FDR < 0.15)。对诱导基因的过表达分析发现,Dys-CIM组内富集了蛋白质稳态和线粒体稳态程序,而Fun-CIM组内富集了代谢重编程(FDR < 0.01)。总之,CIMIC使得从配对的治疗前后转录组分析中对不同的CIM诱导状态进行分类成为可能,让人们能够以传统化疗耐药研究单独无法捕捉的方式来审视CIM,剖析CIM异质性,并发现可能是TNBC中功能失调性CIM基础的、以往未受重视的分子程序。据我们所知,CIMIC是首个专为对CIM轨迹进行分类而设计的无监督流程。未来的工作将聚焦于表征可能影响这些CIM诱导状态的基线分子特征,以期为个体化TNBC化疗方案提供依据。
查看英文原文 English abstract
Triple-negative breast cancer (TNBC) is the deadliest breast cancer subtype with a median survival < 24 months in advanced cases. While TNBC treatment has advanced, chemotherapy remains a cornerstone of curative treatment. Despite its central role in TNBC treatment, the molecular drivers underpinning the immunomodulatory effects of chemotherapy (chemoimmunomodulation; CIM), which enable long-term efficacy and synergy with other therapeutic modalities, remain understudied, thereby limiting efforts to optimize chemotherapeutic regimens. This study aims to identify and characterize anthracycline-induced CIM states to address this challenge. To achieve this, we applied our Chemoimmunomodulation Induction Classifier (CIMIC) pipeline to delta gene expression values (ΔGE; Δlog 2 (TPM+1)) derived from TNBC cell lines (N = 6; 3 biological replicates each) profiled by bulk RNA-sequencing pre- and post-48-hour IC 30 doxorubicin exposure. CIMIC is an iterative unsupervised clustering pipeline that classifies samples into distinct groups based on their induction of 3,100 genes spanning 19 CIM pathways. Using CIMIC, we identified two discrete CIM trajectories in our samples, a functional one (Fun-CIM; N = 3 cell lines) and a dysfunctional one (Dys-CIM; N = 3 cell lines) that were highly distinct (silhouette = 0.95) and stable as determined via standard clustering metrics across multiple bootstraps; proportion of ambiguous clustering = 0.00; cluster consensus score = 1). The CIM states were characterized by significantly differential induction of antitumoral inflammatory markers, including chemoattractants ( CXCL14 ) and immune mediators ( IFNB1 and IL12A/B ) (Fun-CIM vs Dys-CIM all fold change (FC) ≥ 1.3; p < 0.05; FDR < 0.15), and protumoral markers, including tumor surveillance inhibitors ( THBS1 and TGFB2 ), immunosuppressive cell population mediators ( NNMT ), and tumor-intrinsic stress adaptation signals ( EIF2A, YARS1, and XPOT ) (Dys-CIM vs Fun-CIM all FC ≥ 1.3; p < 0.05; FDR < 0.15). Overrepresentation analysis of induced genes identified an enrichment of proteostasis and mitochondrial homeostasis programs within the Dys-CIM Group and metabolic rewiring within the Fun-CIM group (FDR < 0.01). Altogether, CIMIC enabled classification of distinct CIM induction states from paired pre- and post-treatment transcriptomic analysis, allowing interrogation of CIM in a manner not captured via traditional chemoresistance studies alone, the dissection of CIM heterogeneity, and the discovery of underappreciated molecular programs that may underlie dysfunctional CIM in TNBC. To our knowledge, CIMIC is the first unsupervised pipeline specifically designed to classify CIM trajectories. Future work will focus on characterizing baseline molecular features that may influence these CIM induction states, toward the goal of informing personalized TNBC chemotherapeutic regimen.
利益披露 Disclosure
K. L. Coleman, None.