Ubiquitinated PCNA Drives USP1 Synthetic Lethality in Cancer

An update on small molecule compounds targeting synthetic lethality for cancer therapy

Targeting cancer-specific vulnerabilities through synthetic lethality (SL) is an emerging paradigm in precision oncology. A SL strategy based on PARP inhibitors has demonstrated clinical efficacy. Advances in DNA damage response (DDR) uncover novel SL gene pairs. Beyond BRCA-PARP, emerging SL targets like ATR, ATM, DNA-PK, CHK1, WEE1, CDK12, RAD51, and RAD52 show clinical promise. Selective and bioavailable small molecule inhibitors have been developed to induce SL, but optimization for potency, specificity, and drug-like properties remains challenging. This article illuminated recent progress in the field of medicinal chemistry centered on the rational design of agents capable of eliciting SL specifically in neoplastic cells. It is envisioned that innovative strategies harnessing SL for small molecule design may unlock novel prospects for targeted cancer therapeutics going forward.

Structural and Biochemical Insights into the Mechanism of Action of the Clinical USP1 Inhibitor, KSQ-4279

DNA damage triggers cell signaling cascades that mediate repair. This signaling is frequently dysregulated in cancers. The proteins that mediate this signaling are potential targets for therapeutic intervention. Ubiquitin-specific protease 1 (USP1) is one such target, with small-molecule inhibitors already in clinical trials. Here, we use biochemical assays and cryo-electron microscopy (cryo-EM) to study the clinical USP1 inhibitor, KSQ-4279 (RO7623066), and compare this to the well-established tool compound, ML323. We find that KSQ-4279 binds to the same cryptic site of USP1 as ML323 but disrupts the protein structure in subtly different ways. Inhibitor binding drives a substantial increase in thermal stability of USP1, which may be mediated through the inhibitors filling a hydrophobic tunnel-like pocket in USP1. Our results contribute to the understanding of the mechanism of action of USP1 inhibitors at the molecular level.

New Horizons of Synthetic Lethality in Cancer: Current Development and Future Perspectives

In recent years, synthetic lethality has been recognized as a solid paradigm for anticancer therapies. The discovery of a growing number of synthetic lethal targets has led to a significant expansion in the use of synthetic lethality, far beyond poly(ADP-ribose) polymerase inhibitors used to treat BRCA1/2-defective tumors. In particular, molecular targets within DNA damage response have provided a source of inhibitors that have rapidly reached clinical trials. This Perspective focuses on the most recent progress in synthetic lethal targets and their inhibitors, within and beyond the DNA damage response, describing their design and associated therapeutic strategies. We will conclude by discussing the current challenges and new opportunities for this promising field of research, to stimulate discussion in the medicinal chemistry community, allowing the investigation of synthetic lethality to reach its full potential.

Advances of E3 ligases in lung cancer

Lung cancer is a leading cause of cancer-related death, and the most common type of lung cancer is non-small cell lung cancer, which accounts for approximately 85 % of lung cancer diagnoses. Recent studies have revealed that ubiquitination acts as a crucial part of the development and progression of lung cancer. The E1-E2-E3 three-enzyme cascade has a core function in ubiquitination, so targeted adjustments of E3 ligases could be used in lung cancer treatment. Hence, we elucidate research advances in lung cancer-related E3 ligases by briefly describing the structure and categorization of E3 ligases. Here, we provide a detailed review of the mechanisms by which lung cancer-related E3 ligases modify substrate proteins and regulate signaling pathways to facilitate or suppress cancer progression. We hope to show a new perspective on targeted precision therapy for lung cancer.

Deletion of a core APC/C component reveals APC/C function in regulating neuronal USP1 levels and morphology

Introduction

The Anaphase Promoting Complex (APC/C), an E3 ubiquitin ligase, plays a key role in cell cycle control, but it is also thought to operate in postmitotic neurons. Most studies linking APC/C function to neuron biology employed perturbations of the APC/C activators, cell division cycle protein 20 (Cdc20) and Cdc20 homologue 1 (Cdh1). However, multiple lines of evidence indicate that Cdh1 and Cdc20 can function in APC/C-independent contexts, so that the effects of their perturbation cannot strictly be linked to APC/C function.

Methods

We therefore deleted the gene encoding Anaphase Promoting Complex 4 (APC4), a core APC/C component, in neurons cultured from conditional knockout (cKO) mice.

Results

Our data indicate that several previously published substrates are actually not APC/C substrates, whereas ubiquitin specific peptidase 1 (USP1) protein levels are altered in APC4 knockout (KO) neurons. We propose a model where the APC/C ubiquitylates USP1 early in development, but later ubiquitylates a substrate that directly or indirectly stabilizes USP1. We further discovered a novel role of the APC/C in regulating the number of neurites exiting somata, but we were unable to confirm prior data indicating that the APC/C regulates neurite length, neurite complexity, and synaptogenesis. Finally, we show that APC4 SUMOylation does not impact the ability of the APC/C to control the number of primary neurites or USP1 protein levels.

Discussion

Our data indicate that perturbation studies aimed at dissecting APC/C biology must focus on core APC/C components rather than the APC/C activators, Cdh20 and Cdh1.

DoUBLing up: ubiquitin and ubiquitin-like proteases in genome stability

Maintaining stability of the genome requires dedicated DNA repair and signalling processes that are essential for the faithful duplication and propagation of chromosomes. These DNA damage response (DDR) mechanisms counteract the potentially mutagenic impact of daily genotoxic stresses from both exogenous and endogenous sources. Inherent to these DNA repair pathways is the activity of protein factors that instigate repair processes in response to DNA lesions. The regulation, coordination, and orchestration of these DDR factors is carried out, in a large part, by post-translational modifications, such as phosphorylation, ubiquitylation, and modification with ubiquitin-like proteins (UBLs). The importance of ubiquitylation and UBLylation with SUMO in DNA repair is well established, with the modified targets and downstream signalling consequences relatively well characterised. However, the role of dedicated erasers for ubiquitin and UBLs, known as deubiquitylases (DUBs) and ubiquitin-like proteases (ULPs) respectively, in genome stability is less well established, particularly for emerging UBLs such as ISG15 and UFM1. In this review, we provide an overview of the known regulatory roles and mechanisms of DUBs and ULPs involved in genome stability pathways. Expanding our understanding of the molecular agents and mechanisms underlying the removal of ubiquitin and UBL modifications will be fundamental for progressing our knowledge of the DDR and likely provide new therapeutic avenues for relevant human diseases, such as cancer.

USP1-dependent nucleolytic expansion of PRIMPOL-generated nascent DNA strand discontinuities during replication stress

DNA replication stress-induced fork arrest represents a significant threat to genomic integrity. One major mechanism of replication restart involves repriming downstream of the arrested fork by PRIMPOL, leaving behind a single-stranded DNA (ssDNA) gap. Accumulation of nascent strand ssDNA gaps has emerged as a possible determinant of the cellular hypersensitivity to genotoxic agents in certain genetic backgrounds such as BRCA deficiency, but how gaps are converted into cytotoxic structures is still unclear. Here, we investigate the processing of PRIMPOL-dependent ssDNA gaps upon replication stress induced by hydroxyurea and cisplatin. We show that gaps generated in PRIMPOL-overexpressing cells are expanded in the 3'-5' direction by the MRE11 exonuclease, and in the 5'-3' direction by the EXO1 exonuclease. This bidirectional exonucleolytic gap expansion ultimately promotes their conversion into DSBs. We moreover identify the de-ubiquitinating enzyme USP1 as a critical regulator of PRIMPOL-generated ssDNA gaps. USP1 promotes gap accumulation during S-phase, and their expansion by the MRE11 and EXO1 nucleases. This activity of USP1 is linked to its role in de-ubiquitinating PCNA, suggesting that PCNA ubiquitination prevents gap accumulation during replication. Finally, we show that USP1 depletion suppresses DSB formation in PRIMPOL-overexpressing cells, highlighting an unexpected role for USP1 in promoting genomic instability under these conditions.

Emerging roles of deubiquitinating enzymes in actin cytoskeleton and tumor metastasis

BACKGROUND

Metastasis accounts for the majority of cancer-related deaths. Actin dynamics and actin-based cell migration and invasion are important factors in cancer metastasis. Metastasis is characterized by actin polymerization and depolymerization, which are precisely regulated by molecular changes involving a plethora of actin regulators, including actin-binding proteins (ABPs) and signalling pathways, that enable cancer cell dissemination from the primary tumour. Research on deubiquitinating enzymes (DUBs) has revealed their vital roles in actin dynamics and actin-based migration and invasion during cancer metastasis.

CONCLUSION

Here, we review how DUBs drive tumour metastasis by participating in actin rearrangement and actin-based migration and invasion. We summarize the well-characterized and essential actin cytoskeleton signalling molecules related to DUBs, including Rho GTPases, Src kinases, and ABPs such as cofilin and cortactin. Other DUBs that modulate actin-based migration signalling pathways are also discussed. Finally, we discuss and address therapeutic opportunities and ongoing challenges related to DUBs with respect to actin dynamics.

Optimizer's dilemma: optimization strongly influences model selection in transcriptomic prediction

Motivation

Most models can be fit to data using various optimization approaches. While model choice is frequently reported in machine-learning-based research, optimizers are not often noted. We applied two different implementations of LASSO logistic regression implemented in Python's scikit-learn package, using two different optimization approaches (coordinate descent, implemented in the liblinear library, and stochastic gradient descent, or SGD), to predict mutation status and gene essentiality from gene expression across a variety of pan-cancer driver genes. For varying levels of regularization, we compared performance and model sparsity between optimizers.

Results

After model selection and tuning, we found that liblinear and SGD tended to perform comparably. liblinear models required more extensive tuning of regularization strength, performing best for high model sparsities (more nonzero coefficients), but did not require selection of a learning rate parameter. SGD models required tuning of the learning rate to perform well, but generally performed more robustly across different model sparsities as regularization strength decreased. Given these tradeoffs, we believe that the choice of optimizers should be clearly reported as a part of the model selection and validation process, to allow readers and reviewers to better understand the context in which results have been generated.

Availability and implementation

The code used to carry out the analyses in this study is available at https://github.com/greenelab/pancancer-evaluation/tree/master/01_stratified_classification. Performance/regularization strength curves for all genes in the Vogelstein et al. (2013) dataset are available at https://doi.org/10.6084/m9.figshare.22728644.

Role of Translesion DNA Synthesis in the Metabolism of Replication-associated Nascent Strand Gaps

Translesion DNA synthesis (TLS) is a DNA damage tolerance pathway utilized by cells to overcome lesions encountered throughout DNA replication. During replication stress, cancer cells show increased dependency on TLS proteins for cellular survival and chemoresistance. TLS proteins have been described to be involved in various DNA repair pathways. One of the major emerging roles of TLS is single-stranded DNA (ssDNA) gap-filling, primarily after the repriming activity of PrimPol upon encountering a lesion. Conversely, suppression of ssDNA gap accumulation by TLS is considered to represent a mechanism for cancer cells to evade the toxicity of chemotherapeutic agents, specifically in BRCA-deficient cells. Thus, TLS inhibition is emerging as a potential treatment regimen for DNA repair-deficient tumors.

Targeting the Ubiquitin-Proteasome System and Recent Advances in Cancer Therapy

Ubiquitination is a reversible post-translational modification based on the chemical addition of ubiquitin to proteins with regulatory effects on various signaling pathways. Ubiquitination can alter the molecular functions of tagged substrates with respect to protein turnover, biological activity, subcellular localization or protein-protein interaction. As a result, a wide variety of cellular processes are under ubiquitination-mediated control, contributing to the maintenance of cellular homeostasis. It follows that the dysregulation of ubiquitination reactions plays a relevant role in the pathogenic states of human diseases such as neurodegenerative diseases, immune-related pathologies and cancer. In recent decades, the enzymes of the ubiquitin-proteasome system (UPS), including E3 ubiquitin ligases and deubiquitinases (DUBs), have attracted attention as novel druggable targets for the development of new anticancer therapeutic approaches. This perspective article summarizes the peculiarities shared by the enzymes involved in the ubiquitination reaction which, when deregulated, can lead to tumorigenesis. Accordingly, an overview of the main pharmacological interventions based on targeting the UPS that are in clinical use or still in clinical trials is provided, also highlighting the limitations of the therapeutic efficacy of these approaches. Therefore, various attempts to circumvent drug resistance and side effects as well as UPS-related emerging technologies in anticancer therapeutics are discussed.

Deubiquitinases in cancer

Ubiquitination is an essential regulator of most, if not all, signalling pathways, and defects in cellular signalling are central to cancer initiation, progression and, eventually, metastasis. The attachment of ubiquitin signals by E3 ubiquitin ligases is directly opposed by the action of approximately 100 deubiquitinating enzymes (DUBs) in humans. Together, DUBs and E3 ligases coordinate ubiquitin signalling by providing selectivity for different substrates and/or ubiquitin signals. The balance between ubiquitination and deubiquitination is exquisitely controlled to ensure properly coordinated proteostasis and response to cellular stimuli and stressors. Not surprisingly, then, DUBs have been associated with all hallmarks of cancer. These relationships are often complex and multifaceted, highlighted by the implication of multiple DUBs in certain hallmarks and by the impact of individual DUBs on multiple cancer-associated pathways, sometimes with contrasting cancer-promoting and cancer-inhibiting activities, depending on context and tumour type. Although it is still understudied, the ever-growing knowledge of DUB function in cancer physiology will eventually identify DUBs that warrant specific inhibition or activation, both of which are now feasible. An integrated appreciation of the physiological consequences of DUB modulation in relevant cancer models will eventually lead to the identification of patient populations that will most likely benefit from DUB-targeted therapies.

KR4SL: knowledge graph reasoning for explainable prediction of synthetic lethality

MOTIVATION

Synthetic lethality (SL) is a promising strategy for anticancer therapy, as inhibiting SL partners of genes with cancer-specific mutations can selectively kill the cancer cells without harming the normal cells. Wet-lab techniques for SL screening have issues like high cost and off-target effects. Computational methods can help address these issues. Previous machine learning methods leverage known SL pairs, and the use of knowledge graphs (KGs) can significantly enhance the prediction performance. However, the subgraph structures of KG have not been fully explored. Besides, most machine learning methods lack interpretability, which is an obstacle for wide applications of machine learning to SL identification.

RESULTS

We present a model named KR4SL to predict SL partners for a given primary gene. It captures the structural semantics of a KG by efficiently constructing and learning from relational digraphs in the KG. To encode the semantic information of the relational digraphs, we fuse textual semantics of entities into propagated messages and enhance the sequential semantics of paths using a recurrent neural network. Moreover, we design an attentive aggregator to identify critical subgraph structures that contribute the most to the SL prediction as explanations. Extensive experiments under different settings show that KR4SL significantly outperforms all the baselines. The explanatory subgraphs for the predicted gene pairs can unveil prediction process and mechanisms underlying synthetic lethality. The improved predictive power and interpretability indicate that deep learning is practically useful for SL-based cancer drug target discovery.

AVAILABILITY AND IMPLEMENTATION

The source code is freely available at https://github.com/JieZheng-ShanghaiTech/KR4SL.

Let’s not take DNA breaks for granted. The importance of direct detection of DNA breaks for the successful development of DDR inhibitors

Successful development of a drug candidate requires availability of robust methods that enable precise and quantitative assessment of the biological effects exerted by the molecule of interest. In case of DNA Damage Response inhibitors, the most proximal readout of their efficiency is the level of induced DNA damage, usually - DNA breaks. Here we review the methods that are currently used for the assessment of the level of DNA damage, with special attention to their specificity and sensitivity. We also discuss the most common problems and challenges related to the classic IF or IHC methods that indirectly report on the activation of DNA repair mechanisms as the downstream effects of occurrence of the DNA lesions. Finally, we highlight the advent of new tools, such as STRIDE, which have the potential to transform the landscape of DDR functional biomarkers.