Intra-tumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology. Utilizing a novel approach for deconvolution, we analyze the transcriptomes of nearly 6750 tissue regions and extract distinct expression profiles for the different tissue components, such as stroma, normal and PIN glands, immune cells and cancer. We distinguish healthy and diseased areas and thereby provide insight into gene expression changes during the progression of prostate cancer. Compared to pathologist annotations, we delineate the extent of cancer foci more accurately, interestingly without link to histological changes. We identify gene expression gradients in stroma adjacent to tumor regions that allow for re-stratification of the tumor microenvironment. The establishment of these profiles is the first step towards an unbiased view of prostate cancer and can serve as a dictionary for future studies.

中文翻译：

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前列腺癌转录组的空间图揭示了未开发的异质性景观。

肿瘤内异质性是当今癌症治疗中最大的挑战之一。在这里，我们使用空间转录组学（ST）技术研究整个多灶性前列腺癌的全组织基因表达异质性。利用一种新的解卷积方法，我们分析了近6750个组织区域的转录组，并提取了不同组织成分（如基质，正常腺和PIN腺，免疫细胞和癌症）的独特表达谱。我们区分健康和患病区域，从而提供对前列腺癌进展过程中基因表达变化的了解。与病理学家的注释相比，我们更准确地描绘了癌灶的范围，有趣的是，与组织学变化无关。我们确定邻近肿瘤区域的基质中的基因表达梯度，以允许肿瘤微环境的重新分层。这些概况的建立是朝着公正理解前列腺癌的第一步，并且可以作为将来研究的词典。