Department of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), Science for Life Laboratory, Tomtebodavägen 23, Solna, 17165, Sweden.
Department of Oncology-Pathology, Karolinska Institutet (KI), Science for Life Laboratory, Tomtebodavägen 23, Solna, 17165, Sweden.
Nat Commun. 2018 Jun 20;9(1):2419. doi: 10.1038/s41467-018-04724-5.
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.
肿瘤内异质性是当今癌症治疗的最大挑战之一。在这里，我们使用空间转录组学（ST）技术研究多灶性前列腺癌的全组织基因表达异质性。我们利用一种新的去卷积方法，分析了近 6750 个组织区域的转录组，并为不同的组织成分（如基质、正常和 PIN 腺体、免疫细胞和癌症）提取了不同的表达谱。我们区分健康和患病区域，从而深入了解前列腺癌进展过程中的基因表达变化。与病理学家的注释相比，我们更准确地描绘了癌症病灶的范围，有趣的是，这与组织学变化无关。我们在肿瘤区域附近的基质中发现了基因表达梯度，这使得肿瘤微环境能够重新分层。这些图谱的建立是对前列腺癌进行无偏观察的第一步，也可以作为未来研究的字典。
