Selenium Induces Pancreatic Cancer Cell Death Alone and in Combination with Gemcitabine

Survival rate for pancreatic cancer remains poor and newer treatments are urgently required. Selenium, an essential trace element, offers protection against several cancer types and has not been explored much against pancreatic cancer specifically in combination with known chemotherapeutic agents. The present study was designed to investigate selenium and Gemcitabine at varying doses alone and in combination in established pancreatic cancer cell lines growing in 2D as well as 3D platforms. Comparison of multi-dimensional synergy of combinations’ (MuSyc) model and highest single agent (HSA) model provided quantitative insights into how much better the combination performed than either compound tested alone in a 2D versus 3D growth of pancreatic cancer cell lines. The outcomes of the study further showed promise in combining selenium and Gemcitabine when evaluated for apoptosis, proliferation, and ENT1 protein expression, specifically in BxPC-3 pancreatic cancer cells in vitro.

MuSyC is a consensus framework that unifies multi-drug synergy metrics for combinatorial drug discovery

Drug combination discovery depends on reliable synergy metrics but no consensus exists on the correct synergy criterion to characterize combined interactions. The fragmented state of the field confounds analysis, impedes reproducibility, and delays clinical translation of potential combination treatments. Here we present a mass-action based formalism to quantify synergy. With this formalism, we clarify the relationship between the dominant drug synergy principles, and present a mapping of commonly used frameworks onto a unified synergy landscape. From this, we show how biases emerge due to intrinsic assumptions which hinder their broad applicability and impact the interpretation of synergy in discovery efforts. Specifically, we describe how traditional metrics mask consequential synergistic interactions, and contain biases dependent on the Hill-slope and maximal effect of single-drugs. We show how these biases systematically impact synergy classification in large combination screens, potentially misleading discovery efforts. Thus the proposed formalism can provide a consistent, unbiased interpretation of drug synergy, and accelerate the translatability of synergy studies.

The lack of a unifying metric characterizing combinatorial drug interactions has impeded the development of combinatorial therapies. Here, the authors present MuSyC, a consensus synergy metric that overcomes several caveats associated with other, popular metrics.

synergy: a Python library for calculating, analyzing and visualizing drug combination synergy

SUMMARY

Combinations of multiple pharmacological agents can achieve a substantial benefit over treatment with single agents alone. Combinations that achieve 'more than the sum of their parts' are called synergistic. There have been many proposed frameworks to understand and quantify drug combination synergy with different assumptions and domains of applicability. We introduce here synergy, a Python library that (i) implements a broad array of popular synergy models, (ii) provides tools for evaluating confidence intervals and conducting power analysis and (iii) provides standardized tools to analyze and visualize drug combinations and their synergies and antagonisms.

AVAILABILITY AND IMPLEMENTATION

synergy is available on all operating systems for Python >=3.5. It is freely available from https://pypi.org/project/synergy, and its source code is available at https://github.com/djwooten/synergy. This software is released under the GNU General Public License, version 3.0 or later.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Mathematical modeling of the Candida albicans yeast to hyphal transition reveals novel control strategies

Candida albicans, an opportunistic fungal pathogen, is a significant cause of human infections, particularly in immunocompromised individuals. Phenotypic plasticity between two morphological phenotypes, yeast and hyphae, is a key mechanism by which C. albicans can thrive in many microenvironments and cause disease in the host. Understanding the decision points and key driver genes controlling this important transition and how these genes respond to different environmental signals is critical to understanding how C. albicans causes infections in the host. Here we build and analyze a Boolean dynamical model of the C. albicans yeast to hyphal transition, integrating multiple environmental factors and regulatory mechanisms. We validate the model by a systematic comparison to prior experiments, which led to agreement in 17 out of 22 cases. The discrepancies motivate alternative hypotheses that are testable by follow-up experiments. Analysis of this model revealed two time-constrained windows of opportunity that must be met for the complete transition from the yeast to hyphal phenotype, as well as control strategies that can robustly prevent this transition. We experimentally validate two of these control predictions in C. albicans strains lacking the transcription factor UME6 and the histone deacetylase HDA1, respectively. This model will serve as a strong base from which to develop a systems biology understanding of C. albicans morphogenesis.

Data-Driven Math Model of FLT3-ITD Acute Myeloid Leukemia Reveals Potential Therapeutic Targets

FLT3-mutant acute myeloid leukemia (AML) is an aggressive form of leukemia with poor prognosis. Treatment with FLT3 inhibitors frequently produces a clinical response, but the disease nevertheless often recurs. Recent studies have revealed system-wide gene expression changes in FLT3-mutant AML cell lines in response to drug treatment. Here we sought a systems-level understanding of how these cells mediate these drug-induced changes. Using RNAseq data from AML cells with an internal tandem duplication FLT3 mutation (FLT3-ITD) under six drug treatment conditions including quizartinib and dexamethasone, we identified seven distinct gene programs representing diverse biological processes involved in AML drug-induced changes. Based on the literature knowledge about genes from these modules, along with public gene regulatory network databases, we constructed a network of FLT3-ITD AML. Applying the BooleaBayes algorithm to this network and the RNAseq data, we created a probabilistic, data-driven dynamical model of acquired resistance to these drugs. Analysis of this model reveals several interventions that may disrupt targeted parts of the system-wide drug response. We anticipate co-targeting these points may result in synergistic treatments that can overcome resistance and prevent eventual recurrence.

Charting the Fragmented Landscape of Drug Synergy

Even as the clinical impact of drug combinations continues to accelerate, no consensus on how to quantify drug synergy has emerged. Rather, surveying the landscape of drug synergy reveals the persistence of historical fissures regarding the appropriate domains of conflicting synergy models - fissures impacting all aspects of combination therapy discovery and deployment. Herein we chronicle the impact of these divisions on: (i) the design, interpretation, and reproducibility of high-throughput combination screens; (ii) the performance of algorithms to predict synergistic mixtures; and (iii) the search for higher-order synergistic interactions. Further progress in each of these subfields hinges on reaching a consensus regarding the long-standing rifts in the field.

Systems-level network modeling of Small Cell Lung Cancer subtypes identifies master regulators and destabilizers

Adopting a systems approach, we devise a general workflow to define actionable subtypes in human cancers. Applied to small cell lung cancer (SCLC), the workflow identifies four subtypes based on global gene expression patterns and ontologies. Three correspond to known subtypes (SCLC-A, SCLC-N, and SCLC-Y), while the fourth is a previously undescribed ASCL1+ neuroendocrine variant (NEv2, or SCLC-A2). Tumor deconvolution with subtype gene signatures shows that all of the subtypes are detectable in varying proportions in human and mouse tumors. To understand how multiple stable subtypes can arise within a tumor, we infer a network of transcription factors and develop BooleaBayes, a minimally-constrained Boolean rule-fitting approach. In silico perturbations of the network identify master regulators and destabilizers of its attractors. Specific to NEv2, BooleaBayes predicts ELF3 and NR0B1 as master regulators of the subtype, and TCF3 as a master destabilizer. Since the four subtypes exhibit differential drug sensitivity, with NEv2 consistently least sensitive, these findings may lead to actionable therapeutic strategies that consider SCLC intratumoral heterogeneity. Our systems-level approach should generalize to other cancer types.

Quantifying Drug Combination Synergy along Potency and Efficacy Axes

Two goals motivate treating diseases with drug combinations: reduce off-target toxicity by minimizing doses (synergistic potency) and improve outcomes by escalating effect (synergistic efficacy). Established drug synergy frameworks obscure such distinction, failing to harness the potential of modern chemical libraries. We therefore developed multi-dimensional synergy of combinations (MuSyC), a formalism based on a generalized, multi-dimensional Hill equation, which decouples synergistic potency and efficacy. In mutant-EGFR-driven lung cancer, MuSyC reveals that combining a mutant-EGFR inhibitor with inhibitors of other kinases may result only in synergistic potency, whereas synergistic efficacy can be achieved by co-targeting mutant-EGFR and epigenetic regulation or microtubule polymerization. In mutant-BRAF melanoma, MuSyC determines whether a molecular correlate of BRAFi insensitivity alters a BRAF inhibitor's potency, efficacy, or both. These findings showcase MuSyC's potential to transform the enterprise of drug-combination screens by precisely guiding translation of combinations toward dose reduction, improved efficacy, or both.

Mathematical models of cell phenotype regulation and reprogramming: Make cancer cells sensitive again!

A cell's phenotype is the observable actualization of complex interactions between its genome, epigenome, and local environment. While traditional views in cancer have held that cellular and tumor phenotypes are largely functions of genomic instability, increasing attention has recently been given to epigenetic and microenvironmental influences. Such non-genetic factors allow cancer cells to experience intrinsic diversity and plasticity, and at the tumor level can result in phenotypic heterogeneity and treatment evasion. In 2006, Takahashi and Yamanaka exploited the epigenome's plasticity by "reprogramming" differentiated cells into a pluripotent state by inducing expression of a cocktail of four transcription factors. Recent advances in cancer biology have shown not only that cellular reprogramming is possible for malignant cells, but it may provide a foundation for future therapies. Nevertheless, cell reprogramming experiments are frequently plagued by low efficiency, activation of aberrant transcriptional programs, instability, and often rely on expertise gathered from systems which may not translate directly to cancer. Here, we review a theoretical framework tracing back to Waddington's epigenetic landscape which may be used to derive quantitative and qualitative understanding of cellular reprogramming. Implications for tumor heterogeneity, evolution and adaptation are discussed in the context of designing new treatments to re-sensitize recalcitrant tumors. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.

Novel Hybrid Phenotype Revealed in Small Cell Lung Cancer by a Transcription Factor Network Model That Can Explain Tumor Heterogeneity

Small cell lung cancer (SCLC) is a devastating disease due to its propensity for early invasion and refractory relapse after initial treatment response. Although these aggressive traits have been associated with phenotypic heterogeneity, our understanding of this association remains incomplete. To fill this knowledge gap, we inferred a set of 33 transcription factors (TF) associated with gene signatures of the known neuroendocrine/epithelial (NE) and non-neuroendocrine/mesenchymal-like (ML) SCLC phenotypes. The topology of this SCLC TF network was derived from prior knowledge and was simulated using Boolean modeling. These simulations predicted that the network settles into attractors, or TF expression patterns, that correlate with NE or ML phenotypes, suggesting that TF network dynamics underlie the emergence of heterogeneous SCLC phenotypes. However, several cell lines and patient tumor specimens failed to correlate with either the NE or ML attractors. By flow cytometry, single cells within these cell lines simultaneously expressed surface markers of both NE and ML differentiation, confirming the existence of a "hybrid" phenotype. Upon exposure to standard-of-care cytotoxic drugs or epigenetic modifiers, NE and ML cell populations converged toward the hybrid state, suggesting possible escape from treatment. Our findings indicate that SCLC phenotypic heterogeneity can be specified dynamically by attractor states of a master regulatory TF network. Thus, SCLC heterogeneity may be best understood as states within an epigenetic landscape. Understanding phenotypic transitions within this landscape may provide insights to clinical applications. Cancer Res; 77(5); 1063-74. ©2016 AACR.

Abstract 3761: Distinct transcriptional programs drive phenotypic heterogeneity in small cell lung cancer

Small-cell lung cancer (SCLC), a lethal neuroendocrine cancer, lacks targetable oncogenes and is monolithically treated with standard combination chemotherapy. Interestingly, distinct subpopulations of neuroendocrine and non-neuroendocrine cells have been identified in mouse models of SCLC, but their existence in human SCLC remains unknown. Phenotypic heterogeneity, an important phenomenon in cellular reprogramming and therapeutic resistance, can arise from cell state transitions (i.e. network-level changes dynamically controlled by transcriptional regulators). The motivation for this study is to determine whether phenotypically distinct cell states exist in human SCLC, and investigate transcription factor (TF) dynamics that maintain these states.

We implemented a mixed bioinformatics and experimental approach that defines inter-tumor heterogeneity in SCLC patients and cell lines as a spectrum of neuroendocrine (NE) and mesenchymal (MC) differentiation delineated by two anti-correlated gene co-expression networks. Features such as adhesion, surface markers and kinases effectively summarize heterogeneity in SCLC cell lines and patients as three distinct phenotypic states: NE, MC and intermediate.

To characterize the transcriptional influence that governs these distinct phenotypic states, we constructed a TF regulatory network using the mutual information based method ARACNE. Boolean network model dynamics of the top 19 predicted TFs of the NE and MC networks gives rise to 3 distinct clusters of stable phenotypic states or ‘attractors’, each given by a unique TF network configuration. These TF network states were validated at both gene and protein level in SCLC cell lines and patients, identifying specific network states governing NE, MC and intermediate attractors. In silico TF perturbation experiments (single or combination TF activation/knockdown) performed to explore the possibility of state transitions, indicated that the NE state is more easily reprogrammable via single TF manipulations than the MC state, which required a combination of 3-4 simultaneous TF manipulations. SOX2, FOXA2 and OVOL2 were identified as master regulators of MC → NE state transitions while NOTCH1, MYC, SMAD3, and NFKB1 were master regulators of the NE → MC state transitions. Experimentally, phenotypic state transitions such as NE → Intermediate and MC → Intermediate were successfully induced using HDAC inhibitors, but not with demethylating agents or cisplatin. Etoposide treatment could also induce NE → Intermediate state transitions in NE cell lines but MC cell lines were resistant. Drug rebound experiments reveal that the transitioned cells fall back into NE/MC differentiated states upon removal of the drug.

Thus, classification of human SCLC into 3 distinct phenotypic states - NE, MC and intermediate serves as a useful mapping tool for defining heterogeneity that could lead into personalized treatment strategies.

Citation Format: Akshata R. Udyavar, Megan Hoeksema, David J. Wooten, Mukesh Bansal, Andrea Califano, Lourdes Estrada, Jonathan Irish, Pierre Massion, Vito Quaranta. Distinct transcriptional programs drive phenotypic heterogeneity in small cell lung cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3761. doi:10.1158/1538-7445.AM2015-3761

The Electronic Structure and Secondary Pyroelectric Properties of Lithium Tetraborate

We review the pyroelectric properties and electronic structure of Li₂B₄O₇(110) and Li₂B₄O₇(100) surfaces. There is evidence for a pyroelectric current along the [110] direction of stoichiometric Li₂B₄O₇ so that the pyroelectric coefficient is nonzero but roughly 10³ smaller than along the [001] direction of spontaneous polarization. Abrupt decreases in the pyroelectric coefficient along the [110] direction can be correlated with anomalies in the elastic stiffness contributing to the concept that the pyroelectric coefficient is not simply a vector but has qualities of a tensor, as expected. The time dependent surface photovoltaic charging suggests that surface charging is dependent on crystal orientation and doping, as well as temperature.

Blood lead levels in children in south central Los Angeles

We retrospectively reviewed 3 679 pediatric records from King/Drew Medical Center, south central Los Angeles, between 1991 and 1994. Blood lead levels of children were followed to age 18 y. Patients were not referred specifically for lead poisoning. The sample was primarily Latino. Geometric mean blood lead peaked at 6.7 micrograms/dl (0.32 mumol/l) between 2 and 3 y of age. There was a downward secular trend and a seasonal trend. Males had higher lead levels than females. Children who lived in several zipcode areas, in which the lowest family incomes were reported, had higher lead levels. More Latino children had higher lead levels than African American children. Latino children (i.e., 20.2%) who were 1-5 y of age had blood lead levels that were > or = 10 micrograms/dl. Young Latino children in this zone of Los Angeles may be at increased risk for lead exposure.

Effects of drug dose, volume, and concentration on spinal anesthesia with isobaric tetracaine

BACKGROUND AND OBJECTIVES

Factors governing the spread of local anesthetic in the subarachnoid space have been controversial because of failure to consider the drug related and physical factors. Most studies of isobaric spinal anesthesia in the literature were made using plain bupivacaine which is slightly hypobaric. In this study the effects of drug dose, volume, and concentration were investigated employing isobaric tetracaine (IT).

METHODS

One hundred twenty patients were randomly allocated to four groups to receive IT diluted to appropriate concentrations with cerebrospinal fluid. Drugs were administered in lateral position at L3-4 level, with the patient remaining horizontal (supine) during the study. Neural block was assessed by pinprick and the Bromage scale. Except for the factor under investigation, identical techniques were used.

RESULTS

Data indicated that volume was the immediate major factor affecting the extent of spread reflected by the significant difference in peak levels between group 1 and group 2 patients. When volume remained constant, increasing dose (mass) concomitantly increased concentration resulting in a faster onset, longer block, and a higher peak level. However, this effect was not prominent and often limited as increasing the dose from 15 mg to 20 mg had no significant effect on the peak levels in group 3 and group 4 patients.

CONCLUSIONS

In IT spinal anesthesia, the role of baricity/posture interaction no longer exists, the volume appears the most significant factor by simple bulk displacement or area of contact. Next in significance is the dosage. Increased dose in the same volume implies an increase in concentration that results in faster onset and longer duration and, to a less extent, the peak level.

Translaryngeal guided intubation in an uncooperative patient with maxillofacial injury: case report

Maxillofacial injuries can produce a wide variety of airway problems. We report the case of a difficult airway situation in an intoxicated and combative patient with maxillofacial injury, for which we resorted to awake translaryngeal guided intubation (TLI).

Adequacy of general anesthesia for cesarean section

To assess the adequacy of the general anesthesia commonly employed for Cesarean section, we used isolated forearm technique to study 30 parturients (physical status ASA I/II, aged 17-35 yr) scheduled for nonemergent abdominal delivery. Anesthesia was induced with intravenous thiopental (3 mg/kg, 250 mg maximum) and succinylcholine (1.5 mg/kg), and then proceeded with a mixture of 50% N2O, 50% O2, and 0.5% halothane at a flow of 5 L/min and end-tidal CO2 at 40 mm Hg. Paralysis was maintained with a 0.1% succinylcholine infusion. When eyelash reflex disappeared, patients received taped instruction via headphones at 1-min intervals for 10 min. The tapes instructed patients to flex fingers if they were able to hear, to make a fist or squeeze the investigator's hand if they felt pain, to remember six target words, and to respond with specific physical signals during later interviews. Three sets of tapes assigned at random were used in the study. For signs of inadequate anesthesia, other variables such as eye centering, pupil size, sweating, and lacrimation were concomitantly monitored at the time of induction, laryngoscopy/intubation, and skin incision, and then at 1-min intervals for 10 min. Brain activity was also monitored by means of computerized aperiodic analysis of electroencephalogram Lifescan). Patients were interviewed in the postanesthesia recovery room and again 24 h later. At the time of skin incision, 96.7% of patients (29/30) signaled awareness by flexing fingers, 86.7% (26/30) exhibited lacrimation, and 80% (24/30) made a fist or squeezed the investigator's hand, indicating pain perception.(ABSTRACT TRUNCATED AT 250 WORDS)

Prolongation of epidural bupivacaine analgesia with glycerin

Glycerin has been used as a drug carrier/depot, but never with local anaesthetics. This study was an attempt to use the slow drug release mechanism to prolong the anaesthetic effects of bupivacaine in epidural block. Twenty-seven adults with cancer pain were prospectively selected according to their primary lesions and problems, but their allocation to study groups was randomized. Group I (n = 13), received 5 ml bupivacaine, 0.125% in normal saline via a previous implanted epidural catheter. When the pain returned to its original intensity, the same amount of the same strength anaesthetic dissolved in 50% glycerin was given via the same catheter. Group II (n = 14) received the same solutions, but in the reverse order. Also five patients in each group received plain 50% glycerin prior to administration of the anaesthetic solutions to serve as controls. The pharmacological effects were assessed by the blinded observers. Analgesia produced with glycerin solution was prolonged compared with the saline solution (12.2 vs 7.2 and 11.6 vs 7.4 hr, P < 0.01). The order of giving the solution did not produce any differences. Plan 50% glycerin did not produce analgesic effects. Neither motor blockade nor other adverse effects or complications were observed in either group. It was concluded that 0.125% bupivacaine in 50% glycerin administered epidurally is not neurotoxic. The prolongation of analgesia observed is attributed to the slow release of bupivacaine from the glycerin base which functions as drug depot. In addition to relief of chronic pain, this novel approach may have other clinical applications such as the relief of labour or postoperative pain.

Translaryngeal guided intubation solved a critical airway problem

Airway obstruction during the induction of general anesthesia remains a persistent problem in modern anesthesia practice, particularly in obstetric patients. Generally, a careful preoperative airway evaluation uncovers most abnormalities that might make intubation difficult. The planning and preparation for additional intubation equipment facilitate an anticipated difficult intubation. However, situations may arise in which unanticipated airway obstruction occurs requiring prompt management. Although every anesthesia provider is trained to manage such acute airway problems, the provision of a patent airway is not always possible, particularly when repeated attempts at endoscopic or blind intubation have failed, leaving a bloody field that prevents optimal visualization, or when time does not allow to wake up the patient. In this article a difficult airway problem is reported in which translaryngeal guided intubation was lifesaving.

Translaryngeal guided intubation for difficult intubation

Airway obstruction remains a constant problem in acute care. This is particularly true when there are anatomical or pathological abnormalities, trauma, or when repeated failed attempts at endoscopic or blind intubations have left a bloody field, preventing clear visualization of the vocal cords. Our refinement of translaryngeal guided intubation (TLI) uses a spring guidewire accompanied by a plastic sheath protector. The wire is introduced percutaneously via a cricothyroid puncture and passed cephalad into the oropharynx or nasopharynx and out through the mouth or one of the nostrils. The plastic sheath is slid over the wire into the trachea. A well-lubricated endotracheal tube is then inserted to the desired position using the plastic sheath as a stylet. This technique works very well, and we are convinced that TLI is one of the most effective emergency techniques to secure an airway. It can be performed quickly with inexpensive equipment and is a promising addition to the currently recommended alternatives.