Microbiome-based Diagnostic Tool for the Screening of Colorectal Cancer (GUILTI)

Colorectal cancer (CRC) is one of the most common cancer and cause of cancer death worldwide. Population-based screening programs for average risk populations have proven effective in reducing both incidence and mortality of CRC through early detection of cancer. The fecal immunochemical testing (FIT), has still a suboptimal diagnostic yield, with both missed adenomas and, mainly, unnecessary colonoscopies.The identification of novel, non-invasive biomarkers is currently one of the research areas driving most expenditure forces in the field of CRC.A large body of evidence shows that alterations of the gut microbiome and the enrichment of specific taxa(e.g. Fusobacterium nucleatum, Parvimonas micra, and others) are involved in the pathogenesis of CRC. Moreover, recent studies, have discovered common microbial signatures able to reproducibly discriminate between patients with CRC and healthy controls.The goal of this observational study to develop a gut microbiome based diagnostic tool for the identification of CRC and advanced colorectal adenomas in patients enrolled in the national colorectal cancer (CRC) screening program (50-74 year-old) and among who refer to all centers involved in this study for screening colonoscopy with positivity of FIT, of both sex. The primary endpoint of the study is to develop a gut microbiome-based diagnostic tool for the identification of CRC and advanced colorectal adenomas in patients involved in the national CRC screening program, using both statistical and machine learning approaches. The secondary endpoints are: * The association of clinical and colonoscopy outcomes with FIT results; * The characterization of gut microbiome from an ecological, taxonomic, phylogenetic and functional point of view; * The association between microbiome signatures with clinical and colonoscopy outcomes, through statistical and machine-learning algorithms. At baseline, enrolled patients will provide a fecal sample within 2 weeks from enrollment and demographic, clinical characteristics and laboratory data will be recorded. Enrolled patients will be scheduled for colonoscopy, as for clinical practice, within 4 weeks from the positive FIT and histology of resected lesions will be assessed by experienced pathologists according to the WHO classification and the Vienna criteria. Clinical, endoscopic and microbial data will be combined through statistical and machine learning algorithms to identify specific microbial biomarkers associated with CRC and develop a new diagnostic tool, based on a scoring system. This tool will be validated, and its diagnostic performances will be compared with traditional screening methods.

Sex

All

Minimum age

50 Years

Maximum age

74 Years

Inclusion Criteria:

* Patients participating in the national CRC screening program (50-74 years old)
* Positivity to the FIT;
* Ability to provide written informed consent and to be compliant with the study procedures.

Exclusion Criteria:

* Patients unfit for colonoscopy;
* Other oncological conditions;
* Concomitant severe comorbidities or gastrointestinal (GI) organic diseases (e.g. diverticular disease, inflammatory bowel disease);
* Antibiotics, proton pump inhibitors or probiotics within 4 weeks prior to enrollment.

• BACKGROUNDPasolli E, Asnicar F, Manara S, Zolfo M, Karcher N, Armanini F, Beghini F, Manghi P, Tett A, Ghensi P, Collado MC, Rice BL, DuLong C, Morgan XC, Golden CD, Quince C, Huttenhower C, Segata N. Extensive Unexplored Human Microbiome Diversity Revealed by Over 150,000 Genomes from Metagenomes Spanning Age, Geography, and Lifestyle. Cell. 2019 Jan 24;176(3):649-662.e20. doi: 10.1016/j.cell.2019.01.001. Epub 2019 Jan 17. PMID 30661755
• BACKGROUNDBlanco-Miguez A, Beghini F, Cumbo F, McIver LJ, Thompson KN, Zolfo M, Manghi P, Dubois L, Huang KD, Thomas AM, Nickols WA, Piccinno G, Piperni E, Puncochar M, Valles-Colomer M, Tett A, Giordano F, Davies R, Wolf J, Berry SE, Spector TD, Franzosa EA, Pasolli E, Asnicar F, Huttenhower C, Segata N. Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4. Nat Biotechnol. 2023 Nov;41(11):1633-1644. doi: 10.1038/s41587-023-01688-w. Epub 2023 Feb 23. PMID 36823356
• BACKGROUNDBeghini F, McIver LJ, Blanco-Miguez A, Dubois L, Asnicar F, Maharjan S, Mailyan A, Manghi P, Scholz M, Thomas AM, Valles-Colomer M, Weingart G, Zhang Y, Zolfo M, Huttenhower C, Franzosa EA, Segata N. Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3. Elife. 2021 May 4;10:e65088. doi: 10.7554/eLife.65088. PMID 33944776
• BACKGROUNDSchlemper RJ, Riddell RH, Kato Y, Borchard F, Cooper HS, Dawsey SM, Dixon MF, Fenoglio-Preiser CM, Flejou JF, Geboes K, Hattori T, Hirota T, Itabashi M, Iwafuchi M, Iwashita A, Kim YI, Kirchner T, Klimpfinger M, Koike M, Lauwers GY, Lewin KJ, Oberhuber G, Offner F, Price AB, Rubio CA, Shimizu M, Shimoda T, Sipponen P, Solcia E, Stolte M, Watanabe H, Yamabe H. The Vienna classification of gastrointestinal epithelial neoplasia. Gut. 2000 Aug;47(2):251-5. doi: 10.1136/gut.47.2.251. PMID 10896917
• BACKGROUNDKaminski MF, Thomas-Gibson S, Bugajski M, Bretthauer M, Rees CJ, Dekker E, Hoff G, Jover R, Suchanek S, Ferlitsch M, Anderson J, Roesch T, Hultcranz R, Racz I, Kuipers EJ, Garborg K, East JE, Rupinski M, Seip B, Bennett C, Senore C, Minozzi S, Bisschops R, Domagk D, Valori R, Spada C, Hassan C, Dinis-Ribeiro M, Rutter MD. Performance measures for lower gastrointestinal endoscopy: a European Society of Gastrointestinal Endoscopy (ESGE) Quality Improvement Initiative. Endoscopy. 2017 Apr;49(4):378-397. doi: 10.1055/s-0043-103411. Epub 2017 Mar 7.