PO.MCB06.04 · 分子与细胞生物学
定义肺癌中的神经分子特征及其功能意义
Defining neural molecular features and their functional significance in lung cancer
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
背景:肺癌仍然是癌症相关死亡的主要原因,在美国每年造成超过150,000例死亡。尽管基因组表征和免疫治疗已显著重塑了治疗格局,但总体5年生存率仍然较低,约为29.7%,部分原因在于组织学亚型之间和内部的异质性。具有神经内分泌(NE)特征的肺癌表现出特别具有侵袭性的临床行为,包括高脑转移率和对免疫治疗的不良反应。新出现的证据表明,一部分肺腺癌(LUAD)获得了独立于NE身份的神经特性。也有报道称,NE-SCLC中内在神经元样电活动的获得驱动了致瘤能力和转移潜能。这些神经特征可能代表了一个与谱系可塑性、转移和免疫逃逸相关的、尚未被认识的生物学轴。
依据与假设:我们先前的表观基因组研究在肺鳞状细胞癌(LUSC)中识别出神经样谱系亚类(nLUSC),其以SOX2/BRN2环路为标志,与以SOX2/TP63环路为标志的经典亚群形成对比。神经因子在肺癌中被意外地征用(co-opted),以建立与神经发育通路一致的增强子图景。我们假设,被征用的神经环路在肺癌中建立了神经样表观基因组程序,赋予其增强的神经亲和力和内在的免疫豁免,从而促进转移和对免疫治疗的耐药。
实验步骤:首先,我们培养了有或无异位dNp63表达(其抑制神经程序)的nLUSC细胞系,并在transwell中量化其向分化的人谷氨酸能神经元的迁移,同时对与神经元相互作用时的转录组和表观基因组重塑进行图谱分析。其次,我们用IFN-γ刺激一组经典和神经型LUSC细胞以测量抗原呈递活性。我们将T细胞与LUSC细胞系共培养,并测量细胞内和释放的颗粒酶B(Granzyme B)和穿孔素水平,以量化T细胞介导的细胞毒性,同时对转录组和增强子图景进行图谱分析以识别神经特征的富集。
结果:与其经典对应物相比,nLUSC表现出功能上不同的行为。nLUSC细胞表现出向神经元增强的迁移能力。经典细胞在基线时通过MHC-I和MHC-II标志物均维持更强的抗原呈递潜能,并主要上调抗原呈递机制(APM)并增强其免疫原性,而nLUSC细胞则表现出更具免疫抑制性的反应;例如,在IFN-γ刺激下上调PD-L1、CD95和HLA-E。
结论:本研究揭示,神经型和经典型肺癌亚型不仅在转录上存在差异,而且在与神经亲和力和免疫逃逸相关的行为上也存在功能差异。
查看英文原文 English abstract
Background: Lung cancer remains the leading cause of cancer-related mortality, accounting for over 150,000 deaths annually in the US. Although genomic characterization and immunotherapy have significantly reshaped the treatment landscape, overall 5-year survival remains low at ~29.7%, partially due to the heterogeneity across and within histologic subtypes. Lung cancers with neuroendocrine (NE) features exhibit particularly aggressive clinical behavior, including high rates of brain metastasis and poor responsiveness to immunotherapy. Emerging evidence suggests that a subset of LUAD acquires neural traits independent of NE identity. Acquisition of intrinsic neuron-like electrical activity in NE-SCLC drives tumorigenic capability and metastatic potential has been also reported. These neural features may represent an unrecognized biological axis associated with lineage plasticity, metastasis, and immune escape.
Rationale and hypothesis: Our previous epigenomic studies identified neural-like lineage subclasses within LUSC (nLUSC) signified by SOX2/BRN2 circuitry in contrast to classical subset signified by SOX2/TP63 circuitry. Neural factors were unexpectedly co-opted in lung cancer to establish enhancer landscapes consistent with neural developmental pathways. We hypothesize that co-opted neural circuitries establish neural-like epigenomic programs in lung cancers, conferring enhanced neural affinity and intrinsic immune privilege that facilitate metastasis and resistance to immunotherapy.
Experimental procedures: First, we cultured nLUSC cell lines with or without ectopic dNp63 expression that suppresses neural program and quantified migration toward differentiated human glutamatergic neurons in transwell, along with profiling transcriptomic and epigenomic remodeling upon interaction with neurons. Second, we stimulated a panel of classical and neural LUSC cells with IFN-gamma to measure the antigen presentation activity. We co-cultured T cells with LUSC lines and measured intracellular and released Granzyme B and perforin levels to quantify T cell-mediated cytotoxicity, along with profiling transcriptomes and enhancer landscapes to identify enrichment of neural signatures.
Results: nLUSC exhibits functionally distinct behaviors compared to their classical counterparts. nLUSC cells demonstrated enhanced migratory capacity towards neurons. Classical cells maintained stronger antigen-presenting potential by both MHC-I and MHC-II markers at baseline and predominantly upregulated APM and enhanced their immunogenicity, whereas nLUSC cells exhibited a more immunosuppressive response; e.g., upregulation of PD-L1 , CD95 and HLA-E upon IFNgamma stimulation.
Conclusions: The study reveals that neural and classical lung cancer subtypes are not only transcriptionally divergent but also functionally distinct in behaviors relevant to neural affinity and immune escape.
利益披露 Disclosure
R. Bhattacharya, None..
D. V. Rinsum, None..
A. Dykhno, None..
H. Watanabe, None.