PO.TB10.06 · 肿瘤生物学
通过新型 SignalStar® 多重免疫组织化学检测法对 DLBCL 肿瘤微环境进行空间分析
Spatial analysis of the DLBCL tumor microenvironment via the novel SignalStar® multiplex immunohistochemistry assay
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摘要 Abstract
中文摘要
弥漫大 B 细胞淋巴瘤(DLBCL)肿瘤中免疫景观的复杂性凸显了理解肿瘤微环境(TME)内 T 细胞活化与免疫抑制之间相互作用的必要性。鉴于这些肿瘤的异质性以及 TME 内细胞相互作用的重要性,迫切需要能够同时可视化多种生物标志物和细胞表型的先进技术。多重免疫组织化学(mIHC)为这种精细的空间分析提供了有效的解决方案。
在此,我们开发了一个 20 重 SignalStar 多重免疫组织化学(mIHC)板块,旨在描绘 T 细胞活化与抑制状态,并在空间上表征 TME 内的肿瘤细胞、髓系细胞和血管细胞。所得图像使用 Elucidate Bio 空间分析流程进行处理。图像基于 DAPI 染色进行共配准和分割,并采用标志物特异性分类器将细胞标记为各自染色的阳性或阴性。随后对表达强度进行归一化处理,并使用 Leiden 算法进行聚类以分配主导谱系表型。通过基于图的社群检测,识别出更高阶的细胞邻域。我们还将 SignalStar 空间蛋白质组学数据与正交的单细胞 RNA 测序数据进行了关联。我们的分析揭示了六个具有独特空间组织和细胞组成的不同细胞邻域,分别由富含 CD4+ T 细胞、CD8+ T 细胞、M2 样巨噬细胞、树突状细胞、有免疫细胞浸润的肿瘤细胞或无免疫细胞浸润的肿瘤细胞的邻域构成。就存在的细胞表型和细胞邻域而言,在肿瘤间和肿瘤内均观察到显著的异质性。虽然存在的各类细胞邻域数量在统计学上无显著差异,但完全缓解者与进展者相比,M1 样巨噬细胞的总数被发现显著更高。DLBCL 肿瘤由充满各种类型多样细胞的微环境组成,这些细胞全部排列成不同的邻域。我们的研究结果表明,SignalStar mIHC 检测法与 Elucidate Bio 空间分析流程相结合,是探索这一复杂肿瘤微环境的精细组成和空间布局的有效手段。
查看英文原文 English abstract
The complexity of the immune landscape in Diffuse Large B Cell Lymphoma (DLBCL) tumors underscores the necessity of understanding the interplay between T cell activation and immunosuppression within the tumor microenvironment (TME). Given the heterogeneity of these tumors and the importance of cellular interactions within the TME, there is a pressing need for advanced technologies capable of visualizing multiple biomarkers and cell phenotypes simultaneously. Multiplex immunohistochemistry (mIHC) offers an effective solution for this detailed spatial analysis.
Here, we developed a 20-plex SignalStar multiplex immunohistochemistry (mIHC) panel aimed at profiling T cell activation and suppression states, as well as spatially characterizing tumor, myeloid, and vascular cells within the TME. The resulting images underwent processing using the Elucidate Bio Spatial Analysis pipeline. The images were co-registered and segmented based on DAPI staining and marker-specific classifiers were employed to label cells as either positive or negative for each respective stain. Expression intensities were subsequently normalized and clustered using the Leiden algorithm to assign predominant lineage phenotypes. Through graph-based community detection, higher-order cellular neighborhoods were identified. We also correlate the Signalstar spatial proteomics data to an orthogonal single cell RNA sequencing data. Our analysis revealed six distinct cell neighborhoods with unique spatial organization and cellular composition, consisting of those that were rich in either CD4+ T cells, CD8+ T cells, M2-like macrophages, dendritic cells, tumor cells with immune cell infiltration or tumor cells without immune cell infiltration. Substantial heterogeneity was observed with respect to the cell phenotypes and cell neighborhoods that were present, both inter- and intra- tumorally. While there were no statistically significant differences in the numbers of the various cell neighborhoods that were present, the overall number of M1-like macrophages was found to be significantly higher in complete responders vs. progressors. DLBCL tumors are composed of microenvironments filled with diverse cells of various types, all arranged into distinct neighborhoods. Our findings indicate that the SignalStar mIHC assay, when paired with the Elucidate Bio Spatial Analysis pipeline, serves as an effective means to explore the intricate composition and spatial layout of this complex tumor microenvironment.
利益披露 Disclosure
J. Ziello, None.