Both the hypoxia-inducible factor-1 (HIF-1) and tumor suppressor p53 are involved in the cellular response to hypoxia. How the two transcription factors interact to determine cell fates is less well understood. Here, we developed a network model to characterize crosstalk between the HIF-1 and p53 pathways, taking into account that HIF-1α and p53 are targeted for proteasomal degradation by Mdm2 and compete for binding to limiting co-activator p300. We reported the network dynamics under various hypoxic conditions and revealed how the stabilization and transcriptional activities of p53 and HIF-1α are modulated to determine the cell fate. We showed that both the transrepression and transactivation activities of p53 promote apoptosis induction. This work provides new insight into the mechanism for the cellular response to hypoxia.

As a famous tumor suppressor, p53 is also activated under hypoxic conditions. Hypoxia‐induced factor HIF‐1 is involved in the activation of p53 upon hypoxia. However, how p53 is modulated by HIF‐1 pathway to decide cell fate is less understood. In this work, we developed a network model including p53 and HIF‐1 pathways to clarify the mechanism of cell fate decision in response to hypoxia. We found that HIF‐1∝ and p53 are activated under different conditions. Under moderate hypoxia, HIF‐1∝ is activated to induce glycolysis or angiogenesis, and promotes partial accumulation of p53 by inducing PNUTS. Under severe hypoxia, p53 rises to high levels due to ATR‐dependent stabilization and promotes Mdm2‐ dependent HIF‐1∝ degradation. As a result, fully activated p53 triggers apoptosis. Of note, competition for p300 between HIF‐1∝ and p53 plays a key role in regulating their transcriptional activities. This work may advance the understanding of the mechanism for p53 regulation by HIF‐1 in hypoxic response.

Intrinsic tumor-suppressive mechanisms protect normal cells against aberrant proliferation. Although cellular signaling pathways engaged in tumor repression have been largely identified, how they are orchestrated to fulfill their function still remains elusive. Here, we built a tumor-suppressive network model composed of three modules responsible for the regulation of cell proliferation, activation of p53, and induction of apoptosis. Numerical simulations show a rich repertoire of network dynamics when normal cells are subject to serum stimulation and adenovirus E1A overexpression. We showed that oncogenic signaling induces ARF and that ARF further promotes p53 activation to inhibit proliferation. Mitogenic signaling activates E2F activators and promotes Akt activation. p53 and E2F1 cooperate to induce apoptosis, whereas Akt phosphorylates p21 to repress caspase activation. These prosurvival and proapoptotic signals compete to dictate the cell fate of proliferation, cell-cycle arrest, or apoptosis. The cellular outcome is also impacted by the kinetic mode (ultrasensitivity or bistability) of p53. When cells are exposed to serum deprivation and recovery under fixed E1A, the shortest starvation time required for apoptosis induction depends on the terminal serum concentration, which was interpreted in terms of the dynamics of caspase-3 activation and cytochrome c release. We discovered that caspase-3 can be maintained active at high serum concentrations and that E1A overexpression sensitizes serum-starved cells to apoptosis. This work elucidates the roles of tumor repressors and prosurvival factors in tumor repression based on a dynamic network analysis and provides a framework for quantitatively exploring tumor-suppressive mechanisms. Significance Mammalian cells have evolved to develop multiple mechanisms for tumor suppression. It remains challenging to dissect the dynamic mechanism by which signaling proteins are engaged in inhibiting aberrant cell proliferation. Here, we propose a comprehensive network model composed of three signaling pathways and show how this network responds to mitogenic and oncogenic signals. This modeling approach elucidates how a precise temporal control of signaling pathways modulates the cellular response. We reveal the underlying principle for cell-fate decision and identify the roles of the different network components in tumor inhibition. This study sheds light on how the tumor-suppressive function can be modulated by the dynamics of the signaling proteins.

Graded hypoxia is a common microenvironment in malignant solid tumors. As a central regulator in the hypoxic response, hypoxia-inducible factor-1 (HIF-1) can induce multiple cellular processes including glycolysis, angiogenesis, and necroptosis. How cells exploit the HIF-1 pathway to coordinate different processes to survive hypoxia remains unclear. We developed an integrated model of the HIF-1α network to elucidate the mechanism of cellular adaptation to hypoxia. By numerical simulations and bifurcation analysis, we found that HIF-1α is progressively activated with worsening hypoxia due to the sequential deactivation of the hydroxylases prolyl hydroxylase domain enzymes and factor inhibiting HIF (FIH). Bistable switches control the activation and deactivation processes. As a result, glycolysis, immunosuppression, angiogenesis, and necroptosis are orderly elicited in aggravating hypoxia. To avoid the excessive accumulation of lactic acid during glycolysis, HIF-1α induces monocarboxylate transporter and carbonic anhydrase 9 sequentially to export intracellular hydrogen ions, facilitating tumor cell survival. HIF-1α-induced miR-182 facilitates vascular endothelial growth factor production to promote angiogenesis under moderate hypoxia. The imbalance between accumulation and removal of lactic acid in severe hypoxia may result in acidosis and induce cell necroptosis. In addition, the deactivation of FIH results in the destabilization of HIF-1α in anoxia. Collectively, HIF-1α orchestrates the adaptation of tumor cells to hypoxia by selectively inducing its targets according to the severity of hypoxia. Our work may provide clues for tumor therapy by targeting the HIF-1 pathway.

The acetylation of p53 plays an essential role in regulating its transcriptional activity. Nevertheless, how p53 acetylation is modulated in cell fate decision is less understood. We developed a network model to reveal how Tip60‐dependent p53 acetylation is regulated to modulate cellular outcome. We proposed that p53 is progressively activated and exhibits distinct dynamics depending on the severity of DNA damage. For mild damage, p53 is primarily activated to trigger cell cycle arrest by transactivating p21, with its concentration showing pulses. For severe damage, p53 is acetylated at Lysine 120 (K120) by Tip60 to trigger apoptosis by inducing PUMA, and its concentration increases to high levels. Several p53‐centered feedback loops coordinate to regulate its acetylation status, ensuring a robust decision on cell fate.