FKBP5 as a Selection Biomarker for Gemcitabine and Akt Inhibitors in Treatment of Pancreatic Cancer

We have recently shown that the immunophilin FKBP5 (also known as FKBP51) is a scaffolding protein that can enhance PHLPP-AKT interaction and facilitate PHLPP-mediated dephosphorylation of Akt Ser473, negatively regulating Akt activation in vitro. Therefore, FKBP5 might function as a tumor suppressor, and levels of FKBP5 would affect cell response to chemotherapy. In the current study, we have taken a step forward by using a pancreatic cancer xenograft mice model to show that down regulation of FKBP5 in shFKBP5 xenograft mice promotes tumor growth and resistance to gemcitabine, a phenomenon consistent with our previous findings in pancreatic cell lines. In addition, we also found that inhibitors targeting the Akt pathway, including PI3K inhibitor, Akt inhibitor and mTOR inhibitor had a different effect on sensitization to gemcitabine and other chemotherapeutic agents in cell lines, with a specific Akt inhibitor, triciribine, having the greatest sensitization effect. We then tested the hypothesis that addition of triciribine can sensitize gemcitabine treatment, especially in shFKBP5 pancreatic cancer xenograft mice. We found that combination treatment with gemcitabine and triciribine has a better effect on tumor inhibition than either drug alone (p<0.005) and that the inhibition effect is more significant in shFKBP5 xenograft mice than wt mice (p<0.05). These effects were correlated with level of Akt 473 phosphorylation as well as proliferation rate, as indicated by Ki67 staining in xenograft tumor tissues. These results provide evidence in support of future clinical trials designed to tailor therapy based on our observations

Minimum-time control for structurally persistent continuous Petri nets and the application in distributed Control

In this report, we first address the minimum-time control problem of structurally persistent timed continuous Petri Net systems (ContPN). In particular, an ON-OFF controller is proposed to drive the system from a given initial marking to the final marking in minimum-time. The controller is developed first for the discrete-time system ensuring that all transitions are fired as fast as possible in each sampling period until the required total firing counts are reached. After that, they are stopped suddenly. By taking the limit of the sampling period, the controller for continuous-time systems is obtained. Simplicity and the fact that it ensures minimum-time are the main advantages of the controller. A manufacturing system is taken as case study to illustrate the control strategy. In a distributed controlled system, normally a complex dynamic system, the controllers are not centralized in one location, but are distributed in subsystems. We try to apply the ON-OFF controller into the distributed control of large scale systems modeled with timed continuous Petri net. The original net system is first structurally decompose into smaller subnets through sets of places. Then the ON-OFF controller is applied in controlling each subsystem. Algorithms are proposed to compute admissible control laws for the local subsystems in a distributed way. It is proved that with that control laws, the final state can be reached in minimum time

On Minimum-time Control of Continuous Petri nets: Centralized and Decentralized Perspectives

Muchos sistemas artificiales, como los sistemas de manufactura, de logística, de telecomunicaciones o de tráfico, pueden ser vistos "de manera natural" como Sistemas Dinámicos de Eventos Discretos (DEDS). Desafortunadamente, cuando tienen grandes poblaciones, estos sistemas pueden sufrir del clásico problema de la explosión de estados. Con la intención de evitar este problema, se pueden aplicar técnicas de fluidificación, obteniendo una relajación fluida del modelo original discreto. Las redes de Petri continuas (CPNs) son una aproximación fluida de las redes de Petri discretas, un conocido formalismo para los DEDS. Una ventaja clave del empleo de las CPNs es que, a menudo, llevan a una substancial reducción del coste computacional. Esta tesis se centra en el control de Redes de Petri continuas temporizadas (TCPNs), donde las transiciones tienen una interpretación temporal asociada. Se asume que los sistemas siguen una semántica de servidores infinitos (velocidad variable) y que las acciones de control aplicables son la disminución de la velocidad del disparo de las transiciones. Se consideran dos interesantes problemas de control en esta tesis: 1) control del marcado objetivo, donde el objetivo es conducir el sistema (tan rápido como sea posible) desde un estado inicial a un estado final deseado, y es similar al problema de control set-point para cualquier sistema de estado continuo; 2) control del flujo óptimo, donde el objetivo es conducir el sistema a un flujo óptimo sin conocimiento a priori del estado final. En particular, estamos interesados en alcanzar el flujo máximo tan rápido como sea posible, lo cual suele ser deseable en la mayoría de sistemas prácticos. El problema de control del marcado objetivo se considera desde las perspectivas centralizada y descentralizada. Proponemos varios controladores centralizados en tiempo mínimo, y todos ellos están basados en una estrategia ON/OFF. Para algunas subclases, como las redes Choice-Free (CF), se garantiza la evolución en tiempo mínimo; mientras que para redes generales, los controladores propuestos son heurísticos. Respecto del problema de control descentralizado, proponemos en primer lugar un controlador descentralizado en tiempo mínimo para redes CF. Para redes generales, proponemos una aproximación distribuida del método Model Predictive Control (MPC); sin embargo en este método no se considera evolución en tiempo mínimo. El problema de control de flujo óptimo (en nuestro caso, flujo máximo) en tiempo mínimo se considera para redes CF. Proponemos un algoritmo heurístico en el que calculamos los "mejores" firing count vectors que llevan al sistema al flujo máximo, y aplicamos una estrategia de disparo ON/OFF. También demostramos que, debido a que las redes CF son persistentes, podemos reducir el tiempo que tarda en alcanzar el flujo máximo con algunos disparos adicionales. Los métodos de control propuestos se han implementado e integrado en una herramienta para Redes de Petri híbridas basada en Matlab, llamada SimHPN

Control of continuous Petri nets using ON/OFF based method

Abstract: Continuous Petri Nets (CPN) can be used to approximate classical discrete Petri nets which suffer from the state explosion problem. In this paper we focus on the control of timed CPN (TCPN), aiming to drive the system from an initial state to a desired final one. This problem is similar to the set-point control problem in a general continuous-state system. In a previous work, a simple and efficient ON/OFF controller was proposed for structurally persistent nets, and it is proved to be minimum-time. In this work the ON/OFF controller is extended to general TCPN, but in this case, the minimum-time evolution is not guaranteed. Three extensions are proposed, all of them are based on the ON/OFF strategy. Some comparisons of those controllers are given in terms of their applications to an assembly system

Integrative Gene Set Analysis: Application to Platinum Pharmacogenomics

Integrative genomics has the potential to uncover relevant loci, as clinical outcome and response to chemotherapies are most likely not due to a single gene (or data type) but rather a complex relationship involving genetic variation, mRNA, DNA methylation, and copy number variation. In addition to this complexity, many complex phenotypes are thought to be controlled by the interplay of multiple genes within the same molecular pathway or gene set (GS). To address these two challenges, we propose an integrative gene set analysis approach and apply this strategy to a cisplatin (CDDP) pharmacogenomics study involving lymphoblastoid cell lines for which genome-wide SNP and mRNA expression data was collected. Application of the integrative GS analysis implicated the role of the RNA binding and cytoskeletal part GSs. The genes LMNB1 and CENPF, within the cytoskeletal part GS, were functionally validated with siRNA knockdown experiments, where the knockdown of LMNB1 and CENPF resulted in CDDP resistance in multiple cancer cell lines. This study demonstrates the utility of an integrative GS analysis strategy for detecting novel genes associated with response to cancer therapies, moving closer to tailored therapy decisions for cancer patients.National Institutes of Health (U.S.) (NIH/NCI GM61388)National Institutes of Health (U.S.) (NIH/NCI CA140879)National Institutes of Health (U.S.) (NIH/NCI GM86689)National Institutes of Health (U.S.) (NIH/NCI CA130828)National Institutes of Health (U.S.) (NIH/NCI CA138461)National Institutes of Health (U.S.) (NIH/NCI CA102701)Mayo Foundation for Medical Education and Researc

CDC25B partners with PP2A to induce AMPK activation and tumor suppression in triple negative breast cancer

Cell division cycle 25 (CDC25) dual specificity phosphatases positively regulate the cell cycle by activating cyclin-dependent kinase/cyclin complexes. Here, we demonstrate that in addition to its role in cell cycle regulation, CDC25B functions as a regulator of protein phosphatase 2A (PP2A), a major cellular Ser/Thr phosphatase, through its direct interaction with PP2A catalytic subunit. Importantly, CDC25B alters the regulation of AMP-activated protein kinase signaling (AMPK) by PP2A, increasing AMPK activity by inhibiting PP2A to dephosphorylate AMPK. CDC25B depletion leads to metformin resistance by inhibiting metformin-induced AMPK activation. Furthermore, dual inhibition of CDC25B and PP2A further inhibits growth of 3D organoids isolated from patient derived xenograft model of breast cancer compared to CDC25B inhibition alone. Our study identifies CDC25B as a regulator of PP2A, and uncovers a mechanism of controlling the activity of a key energy metabolism marker, AMPK

Aromatase inhibitors, estrogens and musculoskeletal pain: estrogen-dependent T-cell leukemia 1A (TCL1A) gene-mediated regulation of cytokine expression

Introduction: Arthralgias and myalgias are major side effects associated with aromatase inhibitor (AI) therapy of breast cancer. In a recent genome-wide association study, we identified SNPs - including one that created an estrogen response element near the 3' end of the T-cell leukemia 1A (TCL1A) gene - that were associated with musculoskeletal pain in women on adjuvant AI therapy for breast cancer. We also showed estrogen-dependent, SNP-modulated variation in TCL1A expression and, in preliminary experiments, showed that TCL1A could induce IL-17RA expression. In the present study, we set out to determine whether these SNPs might influence cytokine expression and effect more widely, and, if so, to explore the mechanism of TCL1A-related AI-induced side effects. Methods: The functional genomic experiments performed included determinations of TCL1A, cytokine and cytokine receptor expression in response to estrogen treatment of U2OS cells and lymphoblastoid cell lines that had been stably transfected with estrogen receptor alpha. Changes in mRNA and protein expression after gene knockdown and overexpression were also determined, as was NF-κB transcriptional activity. Results: Estradiol (E2) increased TCL1A expression and, in a TCL1A SNP-dependent fashion, also altered the expression of IL-17, IL-17RA, IL-12, IL-12RB2 and IL-1R2. TCL1A expression was higher in E2-treated lymphoblastoid cell lines with variant SNP genotypes, and induction of the expression of cytokine and cytokine receptor genes was mediated by TCL1A. Finally, estrogen receptor alpha blockade with ICI-182,780 in the presence of E2 resulted in greatly increased NF-κB transcriptional activity, but only in cells that carried variant SNP genotypes. These results linked variant TCL1A SNP sequences that are associated with AI-dependent musculoskeletal pain with increased E2-dependent TCL1A expression and with downstream alterations in cytokine and cytokine receptor expression as well as NF-κB transcriptional activity. Conclusions: SNPs near the 3' terminus of TCL1A were associated with AI-dependent musculoskeletal pain. E2 induced SNP-dependent TCL1A expression, which in turn altered IL-17, IL-17RA, IL-12, IL-12RB2, and IL-1R2 expression as well as NF-κB transcriptional activity. These results provide a pharmacogenomic explanation for a clinically important adverse drug reaction as well as insights into a novel estrogen-dependent mechanism for the modulation of cytokine and cytokine receptor expression