空间肿瘤基因特征可区分结肠癌中的肿瘤和非肿瘤区室：揭示复发的预测生物标志物。

BACKGROUND: Opting for or against the administration of adjuvant chemotherapy in therapeutic management of stage II colon cancer remains challenging. Several studies report few survival benefits for patients treated with adjuvant therapy and additionally revealing potential side effects of overtreatment, including unnecessary exposure to chemotherapy-induced toxicities and reduced quality of life. Predictive biomarkers are urgently needed. We, therefore, hypothesise that the spatial tissue composition of relapsed and non-relapsed colon cancer stage II patients reveals relevant biomarkers. METHODS: The spatial tissue composition of stage II colon cancer patients was examined by a novel spatial transcriptomics technology with sub-cellular resolution, namely in situ sequencing. A panel of 176 genes investigating specific cancer-associated processes such as apoptosis, proliferation, angiogenesis, stemness, oxidative stress, hypoxia, invasion and components of the tumour microenvironment was designed to examine differentially expressed genes in tissue of relapsed versus non-relapsed patients. Therefore, FFPE slides of 10 colon cancer stage II patients either classified as relapsed (5 patients) or non-relapsed (5 patients) were in situ sequenced and computationally analysed. RESULTS: We identified a tumour gene signature that enables the subclassification of tissue into neoplastic and non-neoplastic compartments based on spatial expression patterns obtained through in situ sequencing. We developed a computational tool called Genes-To-Count (GTC), which automates the quantification of in situ signals, accurately mapping their position onto the spatial tissue map and automatically identifies neoplastic and non-neoplastic tissue compartments. The GTC tool was used to quantify gene expression of biological processes upregulated within the neoplastic tissue in comparison to non-neoplastic tissue and within relapsed versus non-relapsed stage II colon patients. Three differentially expressed genes (FGFR2, MMP11 and OTOP2) in the neoplastic tissue compartments of relapsed patients in comparison to non-relapsed patients were identified predicting recurrence in stage II colon cancer. CONCLUSIONS: In depth spatial in situ sequencing showed potential to provide a deeper understanding of the underlying mechanisms involved in the recurrence of disease and revealed novel potential predictive biomarkers for disease relapse in colon cancer stage II patients. Our open-access GTC-tool allowed us to accurately capture the tumour compartment and quantify spatial gene expression in colon cancer tissue.

背景：在 II 期结肠癌的治疗管理中，选择或不选择辅助化疗仍然具有挑战性。一些研究报告称，接受辅助治疗的患者生存获益有限，并且还揭示了过度治疗的潜在副作用，包括不必要地暴露于化疗引起的毒性和降低生活质量。因此迫切需要预测生物标志物。因此，我们假设复发和非复发 II 期结肠癌患者的空间组织组成揭示了相关的生物标志物。

方法：通过一种新的具有亚细胞分辨率的空间转录组学技术——原位测序，检查 II 期结肠癌患者的空间组织组成。设计了一个包含 176 个基因的面板，这些基因调查了特定的与癌症相关的过程，如细胞凋亡、增殖、血管生成、干细胞特性、氧化应激、缺氧、侵袭和肿瘤微环境的成分，以检查复发和非复发患者组织中的差异表达基因。因此，对 10 名 II 期结肠癌患者的 FFPE 切片进行了原位测序和计算分析，这些患者要么被归类为复发（5 名患者），要么被归类为非复发（5 名患者）。

结果：我们确定了一个肿瘤基因特征，该特征能够根据通过原位测序获得的空间表达模式将组织分为肿瘤和非肿瘤区室。我们开发了一种名为 Genes-To-Count (GTC) 的计算工具，该工具可以自动对原位信号进行定量，准确地将其位置映射到空间组织图谱上，并自动识别肿瘤和非肿瘤组织区室。该 GTC 工具用于比较非肿瘤组织和复发与非复发 II 期结肠癌患者的肿瘤组织中上调的生物学过程的基因表达。在与非复发患者相比，在复发患者的肿瘤组织区室中鉴定出三个差异表达基因（FGFR2、MMP11 和 OTOP2），可预测 II 期结肠癌的复发。

结论：深入的空间原位测序显示出提供对疾病复发相关潜在机制的更深入理解的潜力，并揭示了 II 期结肠癌患者疾病复发的新的潜在预测生物标志物。我们的开放访问 GTC 工具允许我们准确捕获肿瘤区室并定量结肠癌组织中的空间基因表达。