Mechanistic basis for ubiquitin modulation of a protein energy landscape

Ubiquitin is a common posttranslational modification canonically associated with targeting proteins to the 26S proteasome for degradation and also plays a role in numerous other nondegradative cellular processes. Ubiquitination at certain sites destabilizes the substrate protein, with consequences for proteasomal processing, while ubiquitination at other sites has little energetic effect. How this site specificity-and, by extension, the myriad effects of ubiquitination on substrate proteins-arises remains unknown. Here, we systematically characterize the atomic-level effects of ubiquitination at various sites on a model protein, barstar, using a combination of NMR, hydrogen-deuterium exchange mass spectrometry, and molecular dynamics simulation. We find that, regardless of the site of modification, ubiquitination does not induce large structural rearrangements in the substrate. Destabilizing modifications, however, increase fluctuations from the native state resulting in exposure of the substrate's C terminus. Both of the sites occur in regions of barstar with relatively high conformational flexibility. Nevertheless, destabilization appears to occur through different thermodynamic mechanisms, involving a reduction in entropy in one case and a loss in enthalpy in another. By contrast, ubiquitination at a nondestabilizing site protects the substrate C terminus through intermittent formation of a structural motif with the last three residues of ubiquitin. Thus, the biophysical effects of ubiquitination at a given site depend greatly on local context. Taken together, our results reveal how a single posttranslational modification can generate a broad array of distinct effects, providing a framework to guide the design of proteins and therapeutics with desired degradation and quality control properties.

Targeted therapy and drug resistance in triple-negative breast cancer: the EGFR axis

Targeting of estrogen receptor is commonly used as a first-line treatment for hormone-positive breast cancer patients, and is considered as a keystone of systemic cancer therapy. Likewise, HER2-targeted therapy significantly improved the survival of HER2-positive breast cancer patients, indicating that targeted therapy is a powerful therapeutic strategy for breast cancer. However, for triple-negative breast cancer (TNBC), an aggressive breast cancer subtype, there are no clinically approved targeted therapies, and thus, an urgent need to identify potent, highly effective therapeutic targets. In this mini-review, we describe general strategies to inhibit tumor growth by targeted therapies and briefly discuss emerging resistance mechanisms. Particularly, we focus on therapeutic targets for TNBC and discuss combination therapies targeting the epidermal growth factor receptor (EGFR) and associated resistance mechanisms.

Post-translational modifications of protein in response to ionizing radiation

Based on central dogma of genetics, protein is the embodiment and executor of genetic function, post-translational modifications (PTMs) of protein are particularly important and involved in almost all aspects of cell biology and pathogenesis. Studies have shown that ionizing radiation (IR) alters gene expression much more profoundly and a broad variety of cell-process pathways, lots of proteins are modified and activated. Our understanding of the protein in response to ionizing radiation is steadily increasing. Among the various biological processes known to induce radioresistance, PTMs have attracted marked attention in recent years. The present review summarizes the latest knowledge about how PTMs response to ionizing radiation and pathway analysis were conducted. The data provided insights into biological effects of IR and contributing to the development of novel IR-based strategies.

RING Finger Protein 38 Mediates LIM Domain Binding 1 Degradation and Regulates Cell Growth in Colorectal Cancer

Background and Objectives

RING finger protein 38 (RNF38) has been reported to be involved in the tumorigenesis of several tumors, but its role in colorectal cancer (CRC) is still not investigated. In the present study, we aimed to investigate the effect of RNF38 in CRC cells.

Materials and Methods

The public tumor databases GEPIA and Kaplan-Meier Plotter were used to analyze RNF38 expression and patients’ overall survival in CRC. The qRT-PCR was carried out to assess the mRNA levels of RNF38 and LDB1. Western blot and co-immunoprecipitation were used to detect protein expression and ubiquitination. CCK-8 assay was performed to analyze CRC cell growth and viability.

Results

RNF38 was found downregulated in CRC tumor tissues and cell lines, and CRC patients with high RNF38 expression had a longer overall survival than patients with low RNF38 expression. Our further investigations showed that RNF38 interacted with LDB1, and downregulated LDB1 expression by inducing its polyubiquitination. Moreover, overexpression of RNF38 inhibited CRC cell growth but enforced LDB1 could significantly antagonize RNF38-induced cell growth inhibition in CRC cells. Additionally, RNF38/LDB1 axis was involved in the drug sensitivity of 5-FU to CRC cells.

Conclusion

Our studies suggested that RNF38 was functional in CRC cells, and downregulated CRC cell growth by inducing LDB1 polyubiquitination, which indicated that RNF38 could be as a novel target for CRC therapy.

In silico modeling of phosphorylation dependent and independent c-Myc degradation

Background

c-Myc plays an important role in cell proliferation, cell growth and in differentiation, making it a key regulator for carcinogenesis and pluripotency. Tight control of c-myc turnover is required by ubiquitin-mediated degradation. This is achieved in the system by two F-box proteins Skp2 and FBXW7.

Results

Dynamic modelling technique was used to build two exclusive models for phosphorylation dependent degradation of Myc by FBXW7 (Model 1) and phosphorylation independent degradation by Skp2 (Model 2). Sensitivity analysis performed on these two models revealed that these models were corroborating experimental studies. It was also seen that Model 1 was more robust and perhaps more efficient in degrading c-Myc. These results questioned the existence of the two models in the system and to answer the question a combined model was hypothesised which had a decision making switch. The combined model had both Skp2 and FBXW7 mediated degradation where again the latter played a more important role. This model was able to achieve the lowest levels of ubiquitylated Myc and therefore functioned most efficiently in degradation of Myc.

Conclusion

In this report, c-Myc degradation by two F-box proteins was mathematically evaluated based on the importance of c-Myc turnover. The study was performed in a homeostatic system and therefore, prompts the exploration of c-Myc degradation in cancer state and in pluripotent state.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2846-x) contains supplementary material, which is available to authorized users.

Systems modelling of the EGFR-PYK2-c-Met interaction network predicts and prioritizes synergistic drug combinations for triple-negative breast cancer

Prediction of drug combinations that effectively target cancer cells is a critical challenge for cancer therapy, in particular for triple-negative breast cancer (TNBC), a highly aggressive breast cancer subtype with no effective targeted treatment. As signalling pathway networks critically control cancer cell behaviour, analysis of signalling network activity and crosstalk can help predict potent drug combinations and rational stratification of patients, thus bringing therapeutic and prognostic values. We have previously showed that the non-receptor tyrosine kinase PYK2 is a downstream effector of EGFR and c-Met and demonstrated their crosstalk signalling in basal-like TNBC. Here we applied a systems modelling approach and developed a mechanistic model of the integrated EGFR-PYK2-c-Met signalling network to identify and prioritize potent drug combinations for TNBC. Model predictions validated by experimental data revealed that among six potential combinations of drug pairs targeting the central nodes of the network, including EGFR, c-Met, PYK2 and STAT3, co-targeting of EGFR and PYK2 and to a lesser extent of EGFR and c-Met yielded strongest synergistic effect. Importantly, the synergy in co-targeting EGFR and PYK2 was linked to switch-like cell proliferation-associated responses. Moreover, simulations of patient-specific models using public gene expression data of TNBC patients led to predictive stratification of patients into subgroups displaying distinct susceptibility to specific drug combinations. These results suggest that mechanistic systems modelling is a powerful approach for the rational design, prediction and prioritization of potent combination therapies for individual patients, thus providing a concrete step towards personalized treatment for TNBC and other tumour types.

We applied a systems modelling approach combining mechanistic modelling and biological experimentation to identify effective drug combinations for triple-negative breast cancer (TNBC), an aggressive subtype of breast cancer with no approved targeted treatment. The model predicted and prioritized the synergistic combinations as confirmed by experimental data, demonstrating the power of this approach. Moreover, analysis of clinical data of TNBC patients and patient-specific modelling simulation enabled us to stratify the patients into subgroups with distinct susceptibility to specific drug combinations, and thus defined a subset of patient that could benefit from the combined treatments.

Dissecting Cell-Fate Determination Through Integrated Mathematical Modeling of the ERK/MAPK Signaling Pathway

The past three decades have witnessed an enormous progress in the elucidation of the ERK/MAPK signaling pathway and its involvement in various cellular processes. Because of its importance and complex wiring, the ERK pathway has been an intensive subject for mathematical modeling, which facilitates the unraveling of key dynamic properties and behaviors of the pathway. Recently, however, it became evident that the pathway does not act in isolation but closely interacts with many other pathways to coordinate various cellular outcomes under different pathophysiological contexts. This has led to an increasing number of integrated, large-scale models that link the ERK pathway to other functionally important pathways. In this chapter, we first discuss the essential steps in model development and notable models of the ERK pathway. We then use three examples of integrated, multipathway models to investigate how crosstalk of ERK signaling with other pathways regulates cell-fate decision-making in various physiological and disease contexts. Specifically, we focus on ERK interactions with the phosphoinositide-3 kinase (PI3K), c-Jun N-terminal kinase (JNK), and β-adrenergic receptor (β-AR) signaling pathways. We conclude that integrated modeling in combination with wet-lab experimentation have been and will be instrumental in gaining an in-depth understanding of ERK signaling in multiple biological contexts.

USP7 promotes cell proliferation through the stabilization of Ki-67 protein in non-small cell lung cancer cells

The Ki-67 antigen (Ki-67) is the most reliable immunohistochemical marker for evaluation of cell proliferation in non-small cell lung cancer. However, the mechanisms underlying the regulation of protein levels of Ki-67 in non-small cell lung cancer have remained elusive. In this study, we found that Ki-67 and ubiquitin-specific processing protease 7 (USP7) protein were highly expressed in the nucleus of non-small cell lung cancer cells. Furthermore, statistical analysis uncovered the existence of a strong correlation between Ki-67 and USP7 levels. We could also show that the protein levels of Ki-67 in non-small cell lung cancer cells significantly decreased after treatment with P22077, a selective chemical inhibitor of USP7, while the Ki-67 mRNA levels were unperturbed. Similar results were obtained by knocking down USP7 using short hairpin RNA (shRNA) in lung cancer cells. Interestingly, we noticed that ubiquitination levels of Ki-67 increased dramatically in USP7-silenced cells. The tests in vitro and vivo showed a significant delay in tumor cell growth upon knockdown of USP7. Additionally, drug sensitivity tests indicated that USP7-silenced A549 cells had enhanced sensitivity to paclitaxel and docetaxel, while there was no significant change in sensitivity toward carboplatin and cisplatin. Taken together, these data strongly suggest that the overexpression of USP7 might promote cell proliferation by deubiquitinating Ki-67 protein, thereby maintaining its high levels in the non-small cell lung cancer. Our study also hints potential for the development of deubiquitinase-based therapies, especially those targeting USP7 to improve the condition of patients diagnosed with non-small cell lung cancer.