The Lautenberg Center for Immunology and Cancer Research, Institute for Medical Research Israel-Canada, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 9112102, Israel.
The Neuroendocrine Tumor Unit, European Neuroendocrine Tumor Society Center of Excellence, Division of Internal Medicine, Hadassah Medical Center, Jerusalem 9112102, Israel.
Proc Natl Acad Sci U S A. 2024 Oct 8;121(41):e2405001121. doi: 10.1073/pnas.2405001121. Epub 2024 Oct 3.
Well-differentiated low-grade lung neuroendocrine tumors (lung carcinoids or LNETs) are histopathologically classified as typical and atypical LNETs, but each subtype is still heterogeneous at both the molecular level and its clinical manifestation. Here, we report genome-wide profiles of primary LNETs' cis-regulatory elements by H3K27ac ChIP-seq with matching RNA-seq profiles. Analysis of these regulatory landscapes revealed three regulatory subtypes, independent of the typical/atypical classification. We identified unique differentiation signals that delineate each subtype. The "proneuronal" subtype emerges under the influence of ASCL1, SOX4, and TCF4 transcription factors, embodying a pronounced proneuronal signature. The "luminal-like" subtype is characterized by gain of acetylation at markers of luminal cells and GATA2 activation and loss of LRP5 and OTP. The "HNF+" subtype is characterized by a robust enhancer landscape driven by HNF1A, HNF4A, and FOXA3, with notable acetylation and expression of FGF signaling genes, especially FGFR3 and FGFR4, pivotal components of the FGF pathway. Our findings not only deepen the understanding of LNETs' regulatory and developmental diversity but also spotlight the HNF+ subtype's reliance on FGFR signaling. We demonstrate that targeting this pathway with FGF inhibitors curtails tumor growth both in vitro and in xenograft models, unveiling a potential vulnerability and paving the way for targeted therapies. Overall, our work provides an important resource for studying LNETs to reveal regulatory networks, differentiation signals, and therapeutically relevant dependencies.
分化良好的低级别肺神经内分泌肿瘤（肺类癌或 LNET）在组织病理学上可分为典型和非典型 LNET，但每种亚型在分子水平及其临床表现上仍然存在异质性。在这里，我们通过 H3K27ac ChIP-seq 与匹配的 RNA-seq 图谱报告了原发性 LNET 顺式调控元件的全基因组图谱。这些调控景观的分析揭示了三种独立于典型/非典型分类的调控亚型。我们确定了独特的分化信号来描绘每个亚型。“倾向神经元”亚型在 ASCL1、SOX4 和 TCF4 转录因子的影响下出现，体现了明显的倾向神经元特征。“管腔样”亚型的特征是在管腔细胞的标记物和 GATA2 激活处获得乙酰化，同时 LRP5 和 OTP 丢失。“HNF+”亚型的特征是由 HNF1A、HNF4A 和 FOXA3 驱动的强大增强子景观，伴随着 FGF 信号基因的显著乙酰化和表达，尤其是 FGF 通路的关键组成部分 FGFR3 和 FGFR4。我们的发现不仅加深了对 LNET 调控和发育多样性的理解，还强调了 HNF+亚型对 FGFR 信号的依赖。我们证明，用 FGF 抑制剂靶向该途径可在体外和异种移植模型中抑制肿瘤生长，揭示了潜在的脆弱性，并为靶向治疗铺平了道路。总的来说，我们的工作为研究 LNET 提供了一个重要的资源，以揭示调控网络、分化信号和治疗相关的依赖性。
