Transcriptome-wide In Vitro Effects of Aspirin on Patient-derived Normal Colon Organoids.

2021 
Mechanisms underlying aspirin chemoprevention of colorectal cancer remain unclear. Prior studies have been limited due to the inability of preclinical models to recapitulate human normal colon epithelium or cellular heterogeneity present in mucosal biopsies. To overcome some of these obstacles we performed in vitro aspirin treatment of colon organoids derived from normal mucosal biopsies to reveal transcriptional networks relevant to aspirin chemoprevention. Colon organoids derived from 38 healthy individuals undergoing endoscopy were treated with 50uM aspirin or vehicle control for 72 hours and subjected to bulk RNA-sequencing. Paired regression analysis using DESeq2 identified differentially expressed genes (DEGs) associated with aspirin treatment. Cellular composition was determined using CIBERSORTx. Aspirin treatment was associated with 1,154 significant (q<0.10) DEGs prior to deconvolution. We provide replication of these findings in an independent population-based RNA-sequencing dataset of mucosal biopsies (BarcUVa-Seq), where a significant enrichment for overlap of DEGs was observed (P<2.2E-16). Single-cell deconvolution revealed changes in cell composition, including a decrease in transit-amplifying cells following aspirin treatment (P=0.01). Following deconvolution, DEGs included novel putative targets for aspirin such as TRABD2A (q=0.055), a negative regulator of Wnt signaling. Weighted gene co-expression network analysis identified 12 significant modules, including two that contained hubs for EGFR and PTGES2, the latter being previously implicated in aspirin chemoprevention. In summary, aspirin treatment of patient-derived colon organoids using physiologically relevant doses resulted in transcriptome-wide changes that reveal altered cell composition and improved understanding of transcriptional pathways, providing novel insight into its chemopreventive properties.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    48
    References
    1
    Citations
    NaN
    KQI
    []