NEDD8-activating enzyme inhibition induces cell cycle arrest and anaphase catastrophe in malignant T-cells

Advancements in colorectal cancer research: Unveiling the cellular and molecular mechanisms of neddylation (Review)

Neddylation, akin to ubiquitination, represents a post‑translational modification of proteins wherein neural precursor cell‑expressed developmentally downregulated protein 8 (NEDD8) is modified on the substrate protein through a series of reactions. Neddylation plays a pivotal role in the growth and proliferation of animal cells. In colorectal cancer (CRC), it predominantly contributes to the proliferation, metastasis and survival of tumor cells, decreasing overall patient survival. The strategic manipulation of the NEDD8‑mediated neddylation pathway holds immense therapeutic promise in terms of the potential to modulate the growth of tumors by regulating diverse biological responses within cancer cells, such as DNA damage response and apoptosis, among others. MLN4924 is an inhibitor of NEDD8, and its combined use with platinum drugs and irinotecan, as well as cycle inhibitors and NEDD activating enzyme inhibitors screened by drug repurposing, has been found to exert promising antitumor effects. The present review summarizes the recent progress made in the understanding of the role of NEDD8 in the advancement of CRC, suggesting that NEDD8 is a promising anti‑CRC target.

Pharmacologic targeting of Nedd8-activating enzyme reinvigorates T-cell responses in lymphoid neoplasia

Neddylation is a sequential enzyme-based process which regulates the function of E3 Cullin-RING ligase (CRL) and thus degradation of substrate proteins. Here we show that CD8+ T cells are a direct target for therapeutically relevant anti-lymphoma activity of pevonedistat, a Nedd8-activating enzyme (NAE) inhibitor. Pevonedistat-treated patient-derived CD8+ T cells upregulated TNFα and IFNγ and exhibited enhanced cytotoxicity. Pevonedistat induced CD8+ T-cell inflamed microenvironment and delayed tumor progression in A20 syngeneic lymphoma model. This anti-tumor effect lessened when CD8+ T cells lost the ability to engage tumors through MHC class I interactions, achieved either through CD8+ T-cell depletion or genetic knockout of B2M. Meanwhile, loss of UBE2M in tumor did not alter efficacy of pevonedistat. Concurrent blockade of NAE and PD-1 led to enhanced tumor immune infiltration, T-cell activation and chemokine expression and synergistically restricted tumor growth. shRNA-mediated knockdown of HIF-1α, a CRL substrate, abrogated the in vitro effects of pevonedistat, suggesting that NAE inhibition modulates T-cell function in HIF-1α-dependent manner. scRNA-Seq-based clinical analyses in lymphoma patients receiving pevonedistat therapy demonstrated upregulation of interferon response signatures in immune cells. Thus, targeting NAE enhances the inflammatory T-cell state, providing rationale for checkpoint blockade-based combination therapy.

Supervised learning of high-confidence phenotypic subpopulations from single-cell data

Accurately identifying phenotype-relevant cell subsets from heterogeneous cell populations is crucial for delineating the underlying mechanisms driving biological or clinical phenotypes. Here, by deploying a learning with rejection strategy, we developed a novel supervised learning framework called PENCIL to identify subpopulations associated with categorical or continuous phenotypes from single-cell data. By embedding a feature selection function into this flexible framework, for the first time, we were able to select informative features and identify cell subpopulations simultaneously, which enables the accurate identification of phenotypic subpopulations otherwise missed by methods incapable of concurrent gene selection. Furthermore, the regression mode of PENCIL presents a novel ability for supervised phenotypic trajectory learning of subpopulations from single-cell data. We conducted comprehensive simulations to evaluate PENCIĽs versatility in simultaneous gene selection, subpopulation identification and phenotypic trajectory prediction. PENCIL is fast and scalable to analyze 1 million cells within 1 hour. Using the classification mode, PENCIL detected T-cell subpopulations associated with melanoma immunotherapy outcomes. Moreover, when applied to scRNA-seq of a mantle cell lymphoma patient with drug treatment across multiple time points, the regression mode of PENCIL revealed a transcriptional treatment response trajectory. Collectively, our work introduces a scalable and flexible infrastructure to accurately identify phenotype-associated subpopulations from single-cell data.

Inhibition of NEDD8 NEDDylation induced apoptosis in acute myeloid leukemia cells via p53 signaling pathway

MLN4924 is a potent and selective small-molecule inhibitor of NEDD8-activating enzyme, which showed antitumor effect in several types of malignant tumor types. However, the mechanism of action of MLN4924 in acute myeloid leukemia (AML) requires further investigation. Real-time fluorescent quantitative polymerase chain reaction (RT-qPCR) was conducted to detect the mRNA levels of genes. Gene expression was knocked down by short hairpin RNA (shRNA). Moreover, the protein expression was detected by Western blotting (WB) assay. The proliferation and apoptosis of AML cells were measured by Cell Counting Kit-8 (CCK8) assay and flow cytometry (FCM). In the present study, we observed that the mRNA expression levels of NEDD8, UBA3, UBE2M and RBX1 in AML patients were up-regulated compared with healthy controls, which were correlated with worse overall survival (OS) of patients. Besides, knockdown of UBA3, UBE2M and RBX1 inhibited the NEDDylation of CULs and increased the protein expression of p53 and p21 in MOLM-13 cell line. In AML cells, MLN4924 inhibited cell proliferation, promoted cell apoptosis, and induced cell cycle arrest at the G₂/M phase. As revealed by experiments in vivo and in vitro, the NEDDylation of CULs was significantly inhibited and the p53 signaling pathway was activated after MLN4924 treatment. So, we concluded that NEDD8, UBA3, UBE2M and RBX1 may serve as the prognostic biomarkers and novel therapeutic targets for AML. Inhibition of the NEDDylation pathway resulted in an anti-leukemia effect by activating the p53 signaling pathway.