Colitis-associated cancer (CAC) arises from a complex interplay between host and environmental factors. In this report, we investigated the role of the gut microbiome using Winnie mice, a UC-like model with a missense mutation in the Muc2 gene. Upon rederivation from a conventional (CONV) to a specific-pathogen-free (SPF) facility, Winnie mice developed severe colitis and, notably, spontaneous CAC that progressively worsened over time. In contrast, CONV Winnie showed only mild colitis but no tumorigenesis. By comparison, when rederived into germ-free (GF) conditions, SPF Winnie mice were protected from colitis and colon tumors, indicating an essential role for the gut microbiome in the development of CAC in these mice. Using shotgun metagenomics, metabolomics, and lipidomics, we identified a distinct pro-inflammatory microbial and metabolic signature that potentially drives the transition from colitis to CAC. Fecal microbiota transplantation (FMT), using either SPF Winnie or WT (Bl/6) donors into GF Winnie recipients, demonstrated that while colitis developed regardless of the donor, only FMT from SPF Winnie donors resulted in CAC. Our studies present a relevant model of CAC, providing strong evidence that the microbiome plays a key role in its pathogenesis, thereby challenging the concept of colon cancer as a strictly non-transmissible disease.
Giulio Verna, Stefania De Santis, Bianca N. Islam, Eduardo M. Sommella, Danilo Licastro, Liangliang Zhang, Fabiano De Almelda Celio, Emily N. Miller, Fabrizio Merciai, Vicky Caponigro, Wei Xin, Pietro Campiglia, Theresa T. Pizarro, Marcello Chieppa, Fabio Cominelli
Usage data is cumulative from November 2025 through November 2025.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 176 | 0 |
| 88 | 0 | |
| Supplemental data | 33 | 0 |
| Citation downloads | 4 | 0 |
| Totals | 301 | 0 |
| Total Views | 301 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.