No abstract

The cullin-based CRL4-CDT2 ubiquitin ligase is emerging as a master regulator of cell proliferation. CRL4-CDT2 prevents re-initiation of DNA replication during the same cell cycle “rereplication” through targeted degradation of CDT1, SET8 and p21 during S-phase of the cell cycle. We show that CDT2 is overexpressed in cutaneous melanoma and predicts poor overall and disease-free survival. CDT2 ablation inhibited a panel of melanoma cell lines through the induction of SET8- and p21-dependent DNA rereplication and senescence. Pevonedistat (MLN4924), a specific inhibitor of the NEDD8 activating enzyme (NAE), inhibits the activity of cullin E3 ligases, thereby stabilizing a vast number of cullin substrates and resulting in cancer cell inhibition in vitro and tumor suppression in nude mice. We demonstrate that pevonedistat is effective at inhibiting the proliferation of melanoma cell lines in vitro through the induction of rereplication-dependent permanent growth arrest as well as through a transient, non-rereplication-dependent mechanism. CRISPR/Cas9-mediated heterozygous deletion of CDKN1A (encoding p21) or SET8 in melanoma cells demonstrated that the rereplication-mediated cytotoxicity of pevonedistat is mediated through preventing the degradation of p21 and SET8 and is essential for melanoma suppression in nude mice. By contrast, pevonedistat-induced transient growth suppression was independent of p21 or SET8, and insufficient to inhibit tumor growth in vivo. Pevonedistat additionally synergized with the BRAF kinase inhibitor PLX4720 to inhibit BRAF melanoma, and suppressed PLX4720-resistant melanoma cells. These findings demonstrate that the CRL4-CDT2-SET8/p21 degradation axis is the primary target of inhibition by pevonedistat in melanoma and suggest that a broad patient population may benefit from pevonedistat therapy.Research in ContextThe identification of new molecular targets and effective inhibitors is of utmost significance for the clinical management of melanoma. This study identifies CDT2, a substrate receptor for the CRL4 ubiquitin ligase, as a prognostic marker and therapeutic target in melanoma. CDT2 is required for melanoma cell proliferation and inhibition of CRL4CDT2 by pevonedistat suppresses melanoma in vitro and in vivo through the induction of DNA rereplication and senescence through the stabilization of the CRL4CDT2 substrates p21 and SET8. Pevonedistat also synergizes with vemurafenib in vivo and suppresses vemurafenib-resistant melanoma cells. These findings show a significant promise for targeting CRL4CDT2 therapeutically.

What is already known about this topic? The highly transmissible SARS-CoV-2 Delta variant has begun to cause increases in cases, hospitalizations, and deaths in parts of the United States. With slowed vaccination uptake, this novel variant is expected to increase the risk of pandemic resurgence in the US in July-December 2021. What is added by this report? Data from nine mechanistic models project substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant. These resurgences, which have now been observed in most states, were projected to occur across most of the US, coinciding with school and business reopening. Reaching higher vaccine coverage in July-December 2021 reduces the size and duration of the projected resurgence substantially. The expected impact of the outbreak is largely concentrated in a subset of states with lower vaccination coverage. What are the implications for public health practice? Renewed efforts to increase vaccination uptake are critical to limiting transmission and disease, particularly in states with lower current vaccination coverage. Reaching higher vaccination goals in the coming months can potentially avert 1.5 million cases and 21,000 deaths and improve the ability to safely resume social contacts, and educational and business activities. Continued or renewed non-pharmaceutical interventions, including masking, can also help limit transmission, particularly as schools and businesses reopen.

When pressed for time, outbreak investigators often use homogeneous mixing models to model infectious diseases in data-poor regions. But recent outbreaks such as the 2014 Ebola outbreak in West Africa have shown the limitations of this approach in an era of increasing urbanization and connectivity. Both outbreak detection and predictive modeling depend on realistic estimates of human and disease mobility, but these data are difficult to acquire in a timely manner. This is especially true when dealing with an emerging outbreak in an under-resourced nation. Weighted travel networks with realistic estimates for population flows are often proprietary, expensive, or nonexistent. Here we propose a method for rapidly generating a mobility model from open-source data. As an example, we use road and river network data, along with population estimates, to construct a realistic model of human movement between health zones in the Democratic Republic of the Congo (DRC). Using these mobility data, we then fit an epidemic model to real-world surveillance data from the recent Ebola outbreak in the Nord Kivu region of the DRC to illustrate a potential use of the generated mobility estimation. In addition to providing a way for rapid risk estimation, this approach brings together novel techniques to merge diverse GIS datasets that can then be used to address issues that pertain to public health and global health security.