MMP-9-dependent proteolysis of the histone H3 N-terminal tail: a critical epigenetic step in driving oncogenic transcription and colon tumorigenesis.
Yonghwan ShinSungmin KimGangning LiangWoojin AnPublished in: Molecular oncology (2024)
Matrix metalloproteinase 9 (MMP-9) is a member of the MMP family and has been recently identified as a nuclear protease capable of clipping histone H3 N-terminal tails (H3NT). This MMP-9-dependent H3NT proteolysis is critical for establishing an active state of gene transcription during osteoclast differentiation and melanoma development. However, whether H3NT cleavage by MMP-9 plays a similar role in other cellular events has not been explored. Here, we dissect the functional contribution of MMP-9-dependent H3NT clipping to colonic tumorigenesis by using a combination of genome-wide transcriptome data, ChIP/ChIPac-qPCR, CRISPR/dCas9 gene-targeting system, and in vivo xenograft models. We show that MMP-9 is overexpressed in colon cancer cells and catalyzes H3NT proteolysis to drive transcriptional activation of growth stimulatory genes. Our studies using knockdown and inhibition approaches clearly indicate that MMP-9 mediates transcriptional activation and promotes colonic tumorigenesis in a manner dependent on its protease activity toward H3NT. Remarkably, artificial H3NT proteolysis at target gene promoters with dCAS9-MMP-9 is sufficient for establishing their transcriptional competence in colon cancer cells, underscoring the importance of MMP-9-dependent H3NT proteolysis per se in the transactivation process. Our data establish new functions and mechanisms for MMP-9 in driving the oncogenic transcription program in colon cancer through H3NT proteolysis, and demonstrate how this epigenetic pathway can be exploited as a potential therapeutic target for cancer treatment.
Keyphrases
- genome wide
- cell migration
- transcription factor
- dna methylation
- gene expression
- copy number
- crispr cas
- machine learning
- risk assessment
- circulating tumor cells
- high throughput
- deep learning
- quality improvement
- cancer therapy
- single cell
- genome editing
- case control
- artificial intelligence
- rna seq
- bone loss
- heat shock protein