在治疗II期结直肠癌的过程中，选择是否使用辅助化疗仍然具有挑战性。几项研究表明，辅助治疗对患者的生存效益较少，并揭示了过度治疗可能导致的副作用，包括不必要的化疗毒性暴露和生活质量降低。迫切需要预测性生物标志物。因此，我们假设复发和非复发结直肠癌II期患者的空间组织结构揭示了相关的生物标志物。我们使用一种新颖的空间转录组学技术，即原位测序，对结直肠癌II期患者的空间组织结构进行了分析。一个包含176个基因的面板，用于研究特定与癌症相关的进程，如细胞凋亡、增殖、血管生成、干细胞性、氧化应激、缺氧、侵袭和肿瘤微环境组分等，在复发与非复发患者的组织中设计，以检测差异表达的基因。因此，对10例结直肠癌II期患者的FFPE切片进行了原位测序，并进行了计算分析。我们确定了一个肿瘤基因签名，能够根据通过原位测序获得的空间表达模式将组织细分为肿瘤和非肿瘤区域。我们开发了一个名为基因计数（GTC）的计算工具，它可以自动量化原位信号，并将其位置准确地映射到空间组织图中，并自动识别肿瘤和非肿瘤组织区域。使用GTC工具，我们量化了肿瘤组织中与非肿瘤组织相比上调的生物过程的基因表达，以及在复发和非复发结直肠癌II期患者中的表达差异。我们鉴定了三个差异表达基因（FGFR2，MMP11和OTOP2），它们在与非复发患者相比的复发患者的肿瘤组织区域中，预测了结直肠癌II期的复发情况。深入的空间原位测序显示有潜力提供对复发疾病的潜在机制的更深入理解，并揭示了结直肠癌II期患者疾病复发的新潜在预测性生物标志物。我们的开放获取GTC工具使我们能够准确捕捉肿瘤区域，并量化结直肠癌组织的空间基因表达。© 2023 BioMed Central Ltd., Springer Nature的一部分。

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.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.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.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.© 2023. BioMed Central Ltd., part of Springer Nature.