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Policy testing is an important means for quality assurance of access control policies. Experimental studies on the testing methods of XACML policies have shown their varying levels of effectiveness. However, there is a lack of explanation for why they are unable to detect certain types of faults. It is unclear what is essential to the fault detection capability. To address this issue, we propose a theory on policy testing by formalizing the fault detection conditions with respect to a comprehensive fault model of XACML policies. The detection condition of a policy fault, composed of the reachability, necessity, and propagation constraints, is sufficient and necessary for revealing the fault. The formalized fault detection conditions can qualify the inherent strengths and limitations of testing methods. We have applied the formalization to the qualitative evaluations of five testing methods for the current version of the XACML standard. The results show that, for each method, there are certain types of faults that can always or never be revealed, while the detection of other faults may depend on the particular policy structure. 

Hyperactive sphingosine 1-phosphate (S1P) signaling is associated with a poor prognosis of triple-negative breast cancer (TNBC). Despite recent evidence that links the S1P receptor 1 (S1P1) to TNBC cell survival, its role in TNBC invasion and the underlying mechanisms remain elusive. Combining analyses of human TNBC cells with zebrafish xenografts, we found that phosphorylation of S1P receptor 1 (S1P1) at threonine 236 (T236) is critical for TNBC dissemination. Compared to luminal breast cancer cells, TNBC cells exhibit a significant increase of phospho-S1P1 T236 but not the total S1P1 levels. Misexpression of phosphorylation-defective S1P1 T236A (alanine) decreases TNBC cell migration in vitro and disease invasion in zebrafish xenografts. Pharmacologic disruption of S1P1 T236 phosphorylation, using either a pan-AKT inhibitor (MK2206) or an S1P1 functional antagonist (FTY720, an FDA-approved drug for treating multiple sclerosis), suppresses TNBC cell migration in vitro and tumor invasion in vivo. Finally, we show that human TNBC cells with AKT activation and elevated phospho-S1P1 T236 are sensitive to FTY720-induced cytotoxic effects. These findings indicate that the AKT-enhanced phosphorylation of S1P1 T236 mediates much of the TNBC invasiveness, providing a potential biomarker to select TNBC patients for the clinical application of FTY720. 

Despite the development of metabolism-based therapy for a variety of malignancies, resistance to single-agent treatment is common due to the metabolic plasticity of cancer cells. Improved understanding of how malignant cells rewire metabolic pathways can guide the rational selection of combination therapy to circumvent drug resistance. Here, we show that human T-ALL cells shift their metabolism from oxidative decarboxylation to reductive carboxylation when the TCA cycle is disrupted. The α-ketoglutarate dehydrogenase complex (KGDHC) in the TCA cycle regulates oxidative decarboxylation by converting α-ketoglutarate (α-KG) to succinyl-CoA, while isocitrate dehydrogenase (IDH) 1 and 2 govern reductive carboxylation. Metabolomics flux analysis of T-ALL reveals enhanced reductive carboxylation upon genetic depletion of the E2 subunit of KGDHC, dihydrolipoamide-succinyl transferase (DLST), mimicking pharmacological inhibition of the complex. Mechanistically, KGDHC dysfunction causes increased demethylation of nuclear DNA by α-KG-dependent dioxygenases (e.g., TET demethylases), leading to increased production of both IDH1 and 2. Consequently, dual pharmacologic inhibition of the TCA cycle and TET demethylases demonstrates additive efficacy in reducing the tumor burden in zebrafish xenografts. These findings provide mechanistic insights into how T-ALL develops resistance to drugs targeting the TCA cycle and therapeutic strategies to overcome this resistance. 

Mitochondria are energetic and dynamic organelles with a crucial role in bioenergetics, metabolism, and signaling. Mitochondrial proteins, encoded by both nuclear and mitochondrial DNA, must be properly regulated to ensure proteostasis. Mitochondrial protein quality control (MPQC) serves as a critical surveillance system, employing different pathways and regulators as cellular guardians to ensure mitochondrial protein quality and quantity. In this review, we describe key pathways and players in MPQC, such as mitochondrial protein translocation-associated degradation, mitochondrial stress responses, chaperones, and proteases, and how they work together to safeguard mitochondrial health and integrity. Deregulated MPQC leads to proteotoxicity and dysfunctional mitochondria, which contributes to numerous human diseases, including cancer. We discuss how alterations in MPQC components are linked to tumorigenesis, whether they act as drivers, suppressors, or both. Finally, we summarize recent advances that seek to target these alterations for the development of anti-cancer drugs. 

Abstract Triple-negative breast cancer (TNBC) is traditionally considered a glycolytic tumor with a poor prognosis while lacking targeted therapies. Here we show that high expression of dihydrolipoamide S-succinyltransferase (DLST), a tricarboxylic acid (TCA) cycle enzyme, predicts poor overall and recurrence-free survival among TNBC patients. DLST depletion suppresses growth and induces death in subsets of human TNBC cell lines, which are capable of utilizing glutamine anaplerosis. Metabolomics profiling reveals significant changes in the TCA cycle and reactive oxygen species (ROS) related pathways for sensitive but not resistant TNBC cells. Consequently, DLST depletion in sensitive TNBC cells increases ROS levels while N-acetyl-L-cysteine partially rescues cell growth. Importantly, suppression of the TCA cycle through DLST depletion or CPI-613, a drug currently in clinical trials for treating other cancers, decreases the burden and invasion of these TNBC. Together, our data demonstrate differential TCA-cycle usage in TNBC and provide therapeutic implications for the DLST-dependent subsets. 

While the existing methods for testing XACML policies have varying levels of effectiveness, none of them can reveal the majority of policy faults. The undisclosed faults may lead to unauthorized access and denial of service. This paper presents an approach to strong mutation testing of XACML policies that automatically generates tests from the mutants of a given policy. Such mutants represent the targeted faults that may appear in the policy. In this approach, we first compose the strong mutation constraints that capture the semantic difference between each mutant and its original policy. Then, we use a constraint solver to derive an access request (i.e., test). The test suite generated from all the mutants of a policy can achieve a perfect mutation score, thus uncover all hypothesized faults or demonstrate their absence. Based on the mutation-based approach, this paper further explores optimal test suite that achieves a perfect mutation score without duplicate tests. To evaluate the proposed approach, our experiments have included all the subject policies in the relevant literature and used a number of new policies. The results demonstrate that: (1) it is scalable to generate a mutation-based test suite to achieve a perfect mutation score, (2) it can be impractical to generate the optimal test suite due to the expensive removal of duplicate tests, (3) different from the results of the existing study, the modified-condition/decision coverage-based method, currently the most effective one, has low mutation scores for several policies. 

We designed a few polymyxin derivatives which exhibit broad-spectrum antimicrobial activity. Lead compound P1 could disrupt bacterial membranes rapidly without developing resistance, inhibit biofilms formed by E. coli , and exhibit excellent in vivo activity in an MRSA-infected thigh burden mouse model. 

While the standard language XACML is very expressive for specifying fine-grained access control policies, defects can get into XACML policies for various reasons, such as misunderstanding of access control requirements, omissions, and coding errors. These defects may result in unauthorized accesses, escalation of privileges, and denial of service. Therefore, quality assurance of XACML policies for real-world information systems has become an important issue. To address this issue, this paper presents a family of coverage criteria for XACML policies, such as rule coverage, rule pair coverage, decision coverage, and Modified Condition/Decision Coverage (MC/DC). To demonstrate the assurance levels of these coverage criteria, we have developed methods for automatically generating tests, i.e., access requests, to satisfy the coverage criteria using a constraint solver. We have evaluated these methods through mutation analysis of various policies with different levels of complexity. The experiment results have shown that the rule coverage is far from adequate for revealing the majority of defects in XACML policies, and that both MC/DC and decision coverage tests have outperformed the existing methods for testing XACML policies. In particular, MC/DC tests achieve a very high level of quality assurance of XACML policies.