Microenvironment Shapes Small Cell Lung Cancer Neuroendocrine States and Presents Therapeutic Opportunities [DMS273 SCLC cell lines]

Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intra-tumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the drivers of SCLC plasticity are poorly understood. To map the landscape of SCLC tumor microenvironment (TME), we apply spatially resolved transcriptomics and quantitative mass spectrometry-based proteomics to metastatic SCLC tumors obtained via rapid autopsy. The phenotype and overall composition of non-malignant cells in the tumor microenvironment (TME) exhibits substantial variability, closely mirroring the tumor phenotype, suggesting TME-driven reprogramming of NE cell states. We identify cancer-associated fibroblasts (CAF) as a crucial element of SCLC TME heterogeneity, contributing to immune exclusion, and predicting exceptionally poor prognosis. Together, our work provides a comprehensive map of SCLC tumor and TME ecosystems, emphasizing their pivotal role in SCLCs adaptable nature, opening possibilities for re-programming the intercellular communications that shape SCLC tumor states. Overall design: DMS273 SCLC cell lines treated with Vehicle (control) and Erdafitinib (Pan-FGFR inhibitor) at 33.33 micromolar concentration for 5 days followed by RNA-seq analysis

小细胞肺癌（Small-cell lung cancer, SCLC）是致死性最高的肺癌类型。小细胞肺癌的核心特征为肿瘤内异质性（Intra-tumoral heterogeneity），以神经内分泌（neuroendocrine, NE）与非神经内分泌（non-neuroendocrine, non-NE）细胞状态为典型标志，但目前对小细胞肺癌可塑性的驱动机制尚不清楚。为刻画小细胞肺癌肿瘤微环境（tumor microenvironment, TME）的全貌，本研究对通过快速尸检获取的转移性小细胞肺癌肿瘤，采用空间转录组学（spatially resolved transcriptomics）与基于定量质谱的蛋白质组学（quantitative mass spectrometry-based proteomics）技术进行分析。肿瘤微环境中非恶性细胞的表型与整体组成存在显著异质性，且与肿瘤表型高度匹配，提示肿瘤微环境可介导神经内分泌细胞状态的重编程。本研究鉴定出癌相关成纤维细胞（cancer-associated fibroblasts, CAF）是小细胞肺癌肿瘤微环境异质性的关键组分，其可介导免疫排斥，并可显著预测不良预后。综上，本研究构建了小细胞肺癌肿瘤与肿瘤微环境生态系统的全景图谱，强调了二者在小细胞肺癌可塑性特征中的核心作用，为重塑调控小细胞肺癌肿瘤状态的细胞间通讯提供了新的研究方向。整体实验设计：将DMS273小细胞肺癌细胞系分别经溶剂对照与33.33微摩尔浓度的厄达替尼（Erdafitinib，泛FGFR抑制剂）处理5天后，进行RNA测序（RNA-seq）分析