2020
DOI: 10.1016/j.dnarep.2020.102971
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Towards DNA-damage induced autophagy: A Boolean model of p53-induced cell fate mechanisms

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Cited by 41 publications
(37 citation statements)
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“…Our current study demonstrated that inhibiting Wip1 activity led to enhanced apoptosis and autophagy in ovarian granulosa cells. Consistent with previous studies, the p53 pathway activation in granulosa cells induced by WIP inhibition contributed to both cell death phenotypes [60]. The mTOR signal pathway, the negative regulator of autophagy, was significantly inhibited after downregulating WIP1, causing excessive autophagy in granulosa cells.…”
Section: Discussionsupporting
confidence: 90%
See 1 more Smart Citation
“…Our current study demonstrated that inhibiting Wip1 activity led to enhanced apoptosis and autophagy in ovarian granulosa cells. Consistent with previous studies, the p53 pathway activation in granulosa cells induced by WIP inhibition contributed to both cell death phenotypes [60]. The mTOR signal pathway, the negative regulator of autophagy, was significantly inhibited after downregulating WIP1, causing excessive autophagy in granulosa cells.…”
Section: Discussionsupporting
confidence: 90%
“…Bulavin's team demonstrated that Wip1 deficiency or downregulation could activate autophagy through the ATM-mTOR signaling pathway, suggesting modulating WIP1-related autophagy could help preventing atherosclerosis [43,44]. A recent study also demonstrated that Wip1 related p53 pathway controls the cell fate through regulating autophagy and apoptosis [60]. Our current study demonstrated that inhibiting Wip1 activity led to enhanced apoptosis and autophagy in ovarian granulosa cells.…”
Section: Discussionsupporting
confidence: 60%
“…Recently, we published a model about the dynamics of the regulatory cores of SNAIL1 and ZEB1 during TGF-βinduced EMT using a logical computational approach [14] based on the experimental work by Zhang et al [8]. The logical method is recognized as a valuable tool to study biological regulatory processes [15][16][17][18][19][20][21][22][23][24]. Our analysis indicated testable predictions that could help improve strategies for breast cancer treatment.…”
Section: Introductionmentioning
confidence: 79%
“…All these pathways were implicated in cancer cell growth and proliferation [31,32]. SLC17A9 mRNA expression reportedly correlated positively with a TP53 mutation that could modulate DNA damage response, RNA transport, and protein binding [33]. SLC17A9 silencing reportedly inhibited the viability of C2C12, COS1, and HEK293T cells.…”
Section: Discussionmentioning
confidence: 97%