Rose France, Ibruli Olta, Lichius Luca, Kiljan Martha, Gozum Gokcen, Caiaffa Manoela Iannicelli, Cai Jiali, Niu Li-Na, Herter Jan M, Grüll Holger, Büttner Reinhard, Beleggia Filippo, Bosco Graziella, George Julie, Herter-Sprie Grit S, Reinhardt Hans Christian, Bozek Katarzyna
Center for Molecular Medicine Cologne, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany.
Institute for Biomedical Informatics, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany.
BMC Res Notes. 2025 Sep 8;18(1):385. doi: 10.1186/s13104-025-07460-4.
Small cell lung cancer (SCLC) accounts for approximately 15% of lung tumors and is marked by aggressive growth and early metastatic spread. In this study, we used two SCLC mouse models with differing tumor mutation burdens (TMB). To investigate tumor composition, spatial architecture, and interactions with the surrounding microenvironment, we acquired multiplexed images of mouse lung tumors using imaging mass cytometry (IMC). These data build upon a previously published characterization of the mouse model.
After tumor detection, mice were assigned to one of five treatment groups. Lung tumor tissues were imaged with a 37-marker IMC panel designed to identify major cell types-tumor, immune, and structural-as well as their functional states. When possible, each tumor was sampled both at its center and border regions. Tumor masks in the form of binary images are provided to delineate tumor areas. Additional metadata include tumor onset and endpoint dates to support downstream correlation or predictive analyses based on the image data. This dataset offers a valuable resource for studying the histological and cellular complexity of SCLC in a genetically controlled mouse model across multiple therapeutic conditions.
小细胞肺癌（SCLC）约占肺部肿瘤的15%，其特点是生长迅速且早期发生转移。在本研究中，我们使用了两种具有不同肿瘤突变负荷（TMB）的SCLC小鼠模型。为了研究肿瘤组成、空间结构以及与周围微环境的相互作用，我们使用成像质谱流式细胞术（IMC）获取了小鼠肺部肿瘤的多重图像。这些数据建立在先前发表的小鼠模型特征描述之上。
在检测到肿瘤后，将小鼠分配到五个治疗组之一。用一个旨在识别主要细胞类型（肿瘤、免疫和结构）及其功能状态的37标记IMC面板对肺肿瘤组织进行成像。在可能的情况下，每个肿瘤都在其中心和边缘区域进行采样。以二进制图像形式提供肿瘤掩码以勾勒肿瘤区域。其他元数据包括肿瘤发生和终点日期，以支持基于图像数据的下游相关性或预测性分析。该数据集为研究在多种治疗条件下基因控制的小鼠模型中SCLC的组织学和细胞复杂性提供了宝贵资源。
