美国圣路易斯华盛顿大学Li Ding，Feng Chen，Ryan C. Fields，William E. Gillanders和美国普林斯顿大学Benjamin J. Raphael共同合作，近期取得重要工作进展。他们研究提出，二维和三维空间中的肿瘤演变和微环境相互作用。相关研究成果2024年10月30日在线发表于《自然》杂志上。

为研究癌细胞与非癌细胞之间的空间相互作用，研究人员对来自6种癌症类型的78例病例的131个肿瘤切片，进行了Visium空间转录组学（ST）分析。此外，结合了48个匹配的单核RNA测序样本和22个匹配的联合检测索引（CODEX）样本。为描述肿瘤结构和生态位，研究人员将“肿瘤微区域”定义为，由基质成分分隔的空间上独立的癌细胞簇。这些微区域在不同癌症类型中的大小和密度有所不同，且在转移性样本中观察到最大的微区域。

研究人员进一步将具有共享遗传改变的微区域分组为“空间亚克隆”。其中35个肿瘤切片展示了亚克隆结构。具有不同拷贝数变异和突变的空间亚克隆表现出差异性致癌活性。研究人员发现，微区域中心的代谢活性增加，而在前沿区域则显示出增强的抗原呈递活性。研究人员还观察到微区域内T细胞的浸润存在差异，而巨噬细胞主要位于肿瘤边界。通过共同配准来自16个样本的48个连续ST切片，研究人员重建了3D肿瘤结构，这提供了肿瘤空间组织和异质性的见解。

此外，使用无监督深度学习算法并整合ST和CODEX数据，研究人员识别出免疫活跃和冷淡的区域，并在3D亚克隆周围发现了增强的免疫耗竭标记。这些发现有助于通过与局部微环境的相互作用，来理解2D和3D空间中的肿瘤空间演化，为肿瘤生物学提供了重要的见解。

附：英文原文

Title: Tumour evolution and microenvironment interactions in 2D and 3D space

Author: Mo, Chia-Kuei, Liu, Jingxian, Chen, Siqi, Storrs, Erik, Targino da Costa, Andre Luiz N., Houston, Andrew, Wendl, Michael C., Jayasinghe, Reyka G., Iglesia, Michael D., Ma, Cong, Herndon, John M., Southard-Smith, Austin N., Liu, Xinhao, Mudd, Jacqueline, Karpova, Alla, Shinkle, Andrew, Goedegebuure, S. Peter, Abdelzaher, Abdurrahman Taha Mousa Ali, Bo, Peng, Fulghum, Lauren, Livingston, Samantha, Balaban, Metin, Hill, Angela, Ippolito, Joseph E., Thorsson, Vesteinn, Held, Jason M., Hagemann, Ian S., Kim, Eric H., Bayguinov, Peter O., Kim, Albert H., Mullen, Mary M., Shoghi, Kooresh I., Ju, Tao, Reimers, Melissa A., Weimholt, Cody, Kang, Liang-I, Puram, Sidharth V., Veis, Deborah J., Pachynski, Russell, Fuh, Katherine C., Chheda, Milan G., Gillanders, William E., Fields, Ryan C., Raphael, Benjamin J., Chen, Feng, Ding, Li

Issue&Volume: 2024-10-30

Abstract: To study the spatial interactions among cancer and non-cancer cells1, we here examined a cohort of 131 tumour sections from 78 cases across 6 cancer types by Visium spatial transcriptomics (ST). This was combined with 48 matched single-nucleus RNA sequencing samples and 22 matched co-detection by indexing (CODEX) samples. To describe tumour structures and habitats, we defined ‘tumour microregions’ as spatially distinct cancer cell clusters separated by stromal components. They varied in size and density among cancer types, with the largest microregions observed in metastatic samples. We further grouped microregions with shared genetic alterations into ‘spatial subclones’. Thirty five tumour sections exhibited subclonal structures. Spatial subclones with distinct copy number variations and mutations displayed differential oncogenic activities. We identified increased metabolic activity at the centre and increased antigen presentation along the leading edges of microregions. We also observed variable Tcell infiltrations within microregions and macrophages predominantly residing at tumour boundaries. We reconstructed 3D tumour structures by co-registering 48 serial ST sections from 16 samples, which provided insights into the spatial organization and heterogeneity of tumours. Additionally, using an unsupervised deep-learning algorithm and integrating ST and CODEX data, we identified both immune hot and cold neighbourhoods and enhanced immune exhaustion markers surrounding the 3D subclones. These findings contribute to the understanding of spatial tumour evolution through interactions with the local microenvironment in 2D and 3D space, providing valuable insights into tumour biology.

DOI: 10.1038/s41586-024-08087-4

Source: https://www.nature.com/articles/s41586-024-08087-4