bioRxivImmunologyPreprint
Loss of C3aR induces immune infiltration and inflammatory microbiota in a novel spontaneous model of colon cancer
C. Krieg, L. M. Weber, B. Fosso, G. Hardiman, E. Mileti, S. El Aidy, M. Marzano, M. D. Robinson, S. Guglietta
Abstract
Several lines of evidence suggest that inflammation plays a pivotal role in the development and progression of colorectal cancer (CRC) and can be unleashed by the loss of innate immunosurveillance. The complement system is a well characterized first line of defense against pathogens and a central component of the immune response. Emerging evidence suggests that complement anaphylatoxin C3a produced upon complement activation and acting via its receptor (C3aR) may play a role in intestinal homeostasis. However, to date, it is unknown whether and how the C3a/C3aR axis can affect CRC. By mining publicly available datasets, we found that CpG island methylation of c3ar1 occurs in CRC patients and is associated with significant downregulation of C3aR. By reverse-translating this finding we were able to shift in APCMin/+ mice the tumorigenesis from the small intestine to the colon therefore generating a novel mouse model, which more closely mirrors the CRC in humans. Transcriptomic analysis on colorectal polyps from our newly developed genetic mouse model revealed a significant increase in innate and adaptive immune signatures in absence of C3aR. Furthermore, loss of C3aR significantly impacted the fecal and tumor-associated microbiota and supported the blooming of pro-inflammatory bacterial species as confirmed by experiments of fecal microbiota transplantation. Future studies will elucidate whether loss of C3aR can be exploited as a biomarker for sub-groups of CRC and whether the C3a/C3aR axis may be exploited for the generation of more effective therapeutic interventions.
- organism: mouse
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: cell-cell communication
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: experimental assay
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