Triple-negative breast cancer, the poorest-prognosis breast cancer subtype, lacks clinically approved biomarkers for patient risk stratification and treatment management. Prior literature has shown that interrogation of the tumor-immune microenvironment may be a promising approach for the discovery of methods to fill these gaps. Recently developed high-dimensional tissue imaging technology, such as multiplexed ion beam imaging, provide spatial context to protein expression in the microenvironment, allowing in-depth characterization of cellular processes. We demonstrate that profiling the functional proteins involved in cell-to-cell interactions in the microenvironment can predict recurrence and overall survival. We highlight the immunological relevance of the immunoregulatory proteins PD-1, PD-L1, IDO, and Lag3 by tying interactions involving them to recurrence and survival. Multivariate analysis reveals that our methods provide additional prognostic information compared to clinical variables. In this work, we present a computational pipeline for the examination of the tumor-immune microenvironment using multiplexed ion-beam imaging that produces interpretable results, and is generalizable to other cancer types.

中文翻译：

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肿瘤免疫微环境的多重成像分析揭示了三阴性乳腺癌结果的预测因子。

三阴性乳腺癌是预后最差的乳腺癌亚型，缺乏临床批准的用于患者风险分层和治疗管理的生物标志物。先前的文献表明，对免疫免疫的微环境进行讯问可能是发现填补这些空白的方法的一种有前途的方法。最近开发的高维组织成像技术（例如多路离子束成像）为微环境中的蛋白质表达提供了空间背景，从而可以深入表征细胞过程。我们证明，在微环境中分析参与细胞间相互作用的功能蛋白可以预测复发和整体生存。我们强调了免疫调节蛋白PD-1，PD-L1，IDO，和Lag3通过将涉及它们的相互作用与复发和生存联系起来。多变量分析表明，与临床变量相比，我们的方法可提供更多的预后信息。在这项工作中，我们提出了使用多重离子束成像技术检查肿瘤免疫微环境的计算流程，该方法可产生可解释的结果，并且可推广到其他类型的癌症。