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JGM, Humans, Cohort Studies, Biomarkers, Tumor, Colonic Neoplasms, Transcriptome, Tumor Microenvironment

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Nat Med. 2023;29(5):1273-86.







his work was supported by the Qatar National Research Fund (JSREP07-010-3-005 awarded to W.H. and NPRP11S-0121-180351 awarded to D.B.) and Sidra Medicine Internal funds (SDR100029, D.B. and W.H.). M.C. was also supported by ‘Associazione Italiana per la Ricerca sul Cancro’ under IG 2018, ID 21846 project awarded to M.C. J.D. was supported by a grant from the Qatar Biomedical Research Institute (VR94). We thank P. Blandini (Azienda Sanitaria Locale, ASL3 Genovese) for his expert opinion on machine learning and elastic-net Cox regression model performance. We acknowledge F. Vempalli (Sidra Medicine) for technical assistance in high-performance computing; T. Abu Saqri (Sidra Medicine) and M. Husen Khatib (Sidra Medicine) for their assistance for deploying cBioportal and uploading the AC-ICAM data to dbGAP; and C. Bollensdorff, I. Chepilevskaya and J. Ramm (Sidra Medicine) for their assistance on project management logistics and finance. The work of J.R., J.G., W.H. and D.B. has been supported by QNRF (JSREP07-010-3-005: J.R., W.H.; NPRP11S-0121-180351: J.G. and D.B.). We also thank the reviewers for their constructive feedback that allowed us to increase the quality of our work in its final version.


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.


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