Non-SMC condensin I complex subunit H mediates mature chromosome condensation and DNA damage in pancreatic cancer cells.
Jae Hyeong KimYuna YounKyung-Tae KimGyubeom JangJin-Hyeok HwangPublished in: Scientific reports (2019)
Non-SMC condensin I complex subunit H (NCAPH) is a vital gene associated with chromosome stability and is required for proper chromosome condensation and segregation. However, the mechanisms through which NCAPH affects pancreatic cancer (PC) and its molecular function remain unclear. In this study, we examined the role of NCAPH in PC cells. Our results showed that NCAPH was overexpressed in clinical PC specimens (GEPIA) and cell lines. In addition, in NCAPH-knockdown cells, colony formation and proliferation were inhibited, and the cell cycle was arrested at the S and G2/M phases owing to failure of mature chromosome condensation (MCC) in poorly condensed chromosomes. Increased cell death in NCAPH-knockdown cells was found to help initiate apoptosis through the activation of caspase-3 and PARP cleavage. Furthermore, NCAPH-knockdown cells showed an increase in chromosomal aberrations and DNA damage via activation of the DNA damage response (Chk1/Chk2) signaling pathways. These data demonstrated that NCAPH played an important role in cell cycle progression and DNA damage by maintaining chromosomal stability through progression of MCC from poorly condensed chromosomes. Ultimately, NCAPH knockdown induced apoptotic cell death, which was partially mediated by caspase-dependent pathways. These findings highlight the potential role of NCAPH as a therapeutic target for PC.
Keyphrases
- cell death
- cell cycle arrest
- dna damage
- cell cycle
- induced apoptosis
- copy number
- oxidative stress
- dna damage response
- signaling pathway
- dna repair
- endoplasmic reticulum stress
- cell proliferation
- pi k akt
- dna methylation
- epithelial mesenchymal transition
- diabetic rats
- gene expression
- deep learning
- electronic health record
- risk assessment
- big data
- single molecule
- ultrasound guided
- machine learning
- high glucose