Back

Investigation of mutated in colorectal cancer evolution history indicate a putative role in Th17/Treg differentiation.

Mickael, M. E.

2022-10-07 evolutionary biology
10.1101/2022.10.06.511065 bioRxiv
Show abstract

The MCC family of genes plays a role in colorectal cancer development through various immunological pathways, including the Th17/Treg axis. We have previously shown that MCC1 and not MCC2 play a role in Treg differentiation. Our understanding of the genetic divergence patterns and evolutionary history of the MCC family in relation to its function, in general, and the Th17/Treg axis, in particular, remains incomplete. In this investigation, we explored 12 species genomes to study the phylogenetic origin, structure, and functional specificity of this family. In vertebrates, both MCC1 and MCC2 homologs have been discovered, while invertebrates have a single MCC homolog. We found MCC homologs as early as Cnidarians and Trichoplax, suggesting that the MCC family first appeared 741 million years ago (Ma), whereas MCC divergence into MCC1 and MCC2 families occurred at 540 Ma. In general, we did not detect significant positive selection regulating MCC evolution. Our investigation, based on MCC1 structural similarity, suggests that they may play a role in the evolutionary changes in Tregs emergence towards complexity, including the ability to utilize calcium for differentiation through the use of the EFH calcium-binding domain. We also found that the motif NPSTGE was highly conserved in MCC1 but not in MCC2. The NPSTGE motif binds KEAP1 with high affinity, suggesting an Nrf2-mediated function for Nrf2. In the case of MCC2, we found that the "Modifier of rudimentary" motif is highly conserved. This motif contributes to the regulation of alternative splicing. Overall, our study sheds light on how the evolution of the MCC family is connected to its function in regulating the Th17/Treg axis.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.