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Abstract：
Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intratumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the cell-extrinsic 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 TME exhibit substantial variability, closely mirroring the tumor phenotype, suggesting TME-driven reprogramming of NE cell states. We identify cancer-associated fibroblasts (CAFs) as a crucial element of SCLC TME heterogeneity, contributing to immune exclusion, and predicting exceptionally poor prognosis. Our work provides a comprehensive map of SCLC tumor and TME ecosystems, emphasizing their pivotal role in SCLC\'s adaptable nature, opening possibilities for reprogramming the TME-tumor communications that shape SCLC tumor states.
摘要：
小细胞肺癌（SCLC）是最致命的肺癌形式。肿瘤内异质性，以神经内分泌（NE）和非神经内分泌（非NE）细胞状态为标志，定义SCLC，但对SCLC可塑性的细胞外在驱动因素知之甚少。要绘制SCLC肿瘤微环境（TME）的景观，我们将空间分辨转录组学和基于定量质谱的蛋白质组学应用于通过快速尸检获得的转移性SCLC肿瘤.TME中非恶性细胞的表型和总体组成表现出实质性的变异性。密切反映肿瘤表型，表明TME驱动的NE细胞状态的重编程。我们确定癌症相关成纤维细胞（CAFs）是SCLCTME异质性的关键因素，有助于免疫排斥，并预测异常不良的预后。我们的工作提供了SCLC肿瘤和TME生态系统的全面地图，强调它们在SCLC适应性中的关键作用，为重新编程塑造SCLC肿瘤状态的TME-肿瘤通信开辟了可能性。
