The lack of multi-omics cancer datasets with extensive follow-up information hinders the identification of accurate biomarkers of clinical outcome. In this cohort study, we performed comprehensive genomic analyses on fresh-frozen samples from 348 patients affected by primary colon cancer, encompassing RNA, whole-exome, deep T cell receptor and 16S bacterial rRNA gene sequencing on tumor and matched healthy colon tissue, complemented with tumor whole-genome sequencing for further microbiome characterization. A type 1 helper T cell, cytotoxic, gene expression signature, called Immunologic Constant of Rejection, captured the presence of clonally expanded, tumor-enriched T cell clones and outperformed conventional prognostic molecular biomarkers, such as the consensus molecular subtype and the microsatellite instability classifications. Quantification of genetic immunoediting, defined as a lower number of neoantigens than expected, further refined its prognostic value. We identified a microbiome signature, driven by Ruminococcus bromii, associated with a favorable outcome. By combining microbiome signature and Immunologic Constant of Rejection, we developed and validated a composite score (mICRoScore), which identifies a group of patients with excellent survival probability. The publicly available multi-omics dataset provides a resource for better understanding colon cancer biology that could facilitate the discovery of personalized therapeutic approaches.

缺乏具有广泛随访信息的多组学癌症数据集阻碍了临床结果的准确生物标志物的鉴定。在这项队列研究中，我们对来自 348 名原发性结肠癌患者的新鲜冷冻样本进行了全面的基因组分析，包括对肿瘤和匹配的健康结肠组织进行 RNA、全外显子组、深层 T 细胞受体和 16S 细菌 rRNA 基因测序，补充与肿瘤全基因组测序以进一步表征微生物组。一种 1 型辅助性 T 细胞，细胞毒性，基因表达特征，称为免疫排斥常数，捕获了克隆扩增的肿瘤富集 T 细胞克隆的存在，并且优于传统的预后分子生物标志物，例如共有分子亚型和微卫星不稳定性分类. 基因免疫编辑的量化，定义为新抗原数量低于预期，进一步完善了其预后价值。我们确定了微生物组特征，由溴瘤胃 球菌，与有利的结果相关。通过结合微生物组特征和免疫排斥常数，我们开发并验证了一个综合评分 (mICRoScore)，它确定了一组具有极好的生存概率的患者。公开可用的多组学数据集为更好地了解结肠癌生物学提供了资源，可以促进个性化治疗方法的发现。