Personalizing HER2-targeted therapy in metastatic breast cancer beyond HER2 status: what we have learned from clinical specimens.

HER2 is over-expressed in approximately 25% to 30% of human metastatic breast cancers, primarily due to gene amplification. There are currently two HER2-targeted therapies approved for clinical use, the monoclonal HER2 antibody trastuzumab and the EGFR/HER2 dual tyrosine kinase inhibitor lapatinib. Although both agents show clinical benefit in a subset of patients with metastatic breast cancer, many patients with HER2-over-expressing metastatic breast tumors do not respond to these agents. Furthermore, those who do show an initial response generally demonstrate disease progression, on average in less than one year. It has become clear that HER2 expression status alone does not adequately predict response to HER2-targeted therapy. Identification and clinical validation of molecular predictors of response to trastuzumab and lapatinib is critical for further personalizing treatment and improving clinical benefit for patients whose tumors over-express HER2. In this review, we discuss published data describing potential predictors of response or resistance to trastuzumab and lapatinib. While a discussion of the preclinical work is provided, the emphasis is placed on potential predictors that have been studied in clinical specimens such as tumor tissue or serum obtained from patients treated with HER2-targeted therapy. The present analysis and synthesis of the available literature therefore contribute towards an emerging knowledgebase to personalize breast cancer treatment taking into factors including but beyond HER2 expression.

Multiscale brain modelling.

A central difficulty of brain modelling is to span the range of spatio-temporal scales from synapses to the whole brain. This paper overviews results from a recent model of the generation of brain electrical activity that incorporates both basic microscopic neurophysiology and large-scale brain anatomy to predict brain electrical activity at scales from a few tenths of a millimetre to the whole brain. This model incorporates synaptic and dendritic dynamics, nonlinearity of the firing response, axonal propagation and corticocortical and corticothalamic pathways. Its relatively few parameters measure quantities such as synaptic strengths, corticothalamic delays, synaptic and dendritic time constants, and axonal ranges, and are all constrained by independent physiological measurements. It reproduces quantitative forms of electroencephalograms seen in various states of arousal, evoked response potentials, coherence functions, seizure dynamics and other phenomena. Fitting model predictions to experimental data enables underlying physiological parameters to be inferred, giving a new non-invasive window into brain function that complements slower, but finer-resolution, techniques such as fMRI. Because the parameters measure physiological quantities relating to multiple scales, and probe deep structures such as the thalamus, this will permit the testing of a range of hypotheses about vigilance, cognition, drug action and brain function. In addition, referencing to a standardized database of subjects adds strength and specificity to characterizations obtained.

Biophysical modeling of tonic cortical electrical activity in attention deficit hyperactivity disorder.

Psychophysiological theories characterize Attention Deficit Hyperactivity Disorder (ADHD) in terms of cortical hypoarousal and a lack of inhibition of irrelevant sensory input, drawing on evidence of abnormal electroencephalographic (EEG) delta-theta activity. To investigate the mechanisms underlying this disorder a biophysical model of the cortex was used to fit and replicate the EEGs from 54 ADHD adolescents and their control subjects. The EEG abnormalities in ADHD were accounted for by the model's neurophysiological parameters as follows: (i) dendritic response times were increased, (ii) intrathalamic activity involving the thalamic reticular nucleus (TRN) was increased, consistent with enhanced delta-theta activity, and (iii) intracortical activity was increased, consistent with slow wave (<1 Hz) abnormalities. The longer dendritic response time is consistent with the increase in the activity of inhibitory cells types, particularly in the TRN, and therefore reduced arousal. The increase in intracortical activity may also reflect an increase in background activity or cortical noise within neocortical circuits. In terms of neurochemistry, these findings may be accounted for by disturbances in the cholinergic and/or noradrenergic systems. To the knowledge of the authors, this is the first study to use a detailed biophysical model of the brain to elucidate the neurophysiological mechanisms underlying tonic abnormalities in ADHD.

Stimulant drug action in attention deficit hyperactivity disorder (ADHD): inference of neurophysiological mechanisms via quantitative modelling.

OBJECTIVE: To infer the neural mechanisms underlying tonic transitions in the electroencephalogram (EEG) in 11 adolescents diagnosed with attention deficit hyperactivity disorder (ADHD) before and after treatment with stimulant medication. METHODS: A biophysical model was used to analyse electroencephalographic (EEG) measures of tonic brain activity at multiple scalp sites before and after treatment with medication. RESULTS: It was observed that stimulants had the affect of significantly reducing the parameter controlling activation in the intrathalamic pathway involving the thalamic reticular nucleus (TRN) and the parameter controlling excitatory cortical activity. The effect of stimulant medication was also found to be preferentially localized within subcortical nuclei projecting towards frontal and central scalp sites. CONCLUSIONS: It is suggested that the action of stimulant medication occurs via suppression of the locus coeruleus, which in turn reduces stimulation of the TRN, and improves cortical arousal. The effects localized to frontal and central sites are consistent with the occurrence of frontal delta-theta EEG abnormalities in ADHD, and existing theories of hypoarousal. SIGNIFICANCE: To our knowledge, this is the first study where a detailed biophysical model of the brain has been used to estimate changes in neurophysiological parameters underlying the effects of stimulant medication in ADHD.

Estimation of multiscale neurophysiologic parameters by electroencephalographic means.

It is shown that new model-based electroencephalographic (EEG) methods can quantify neurophysiologic parameters that underlie EEG generation in ways that are complementary to and consistent with standard physiologic techniques. This is done by isolating parameter ranges that give good matches between model predictions and a variety of experimental EEG-related phenomena simultaneously. Resulting constraints range from the submicrometer synaptic level to length scales of tens of centimeters, and from timescales of around 1 ms to 1 s or more, and are found to be consistent with independent physiologic and anatomic measures. In the process, a new method of obtaining model parameters from the data is developed, including a Monte Carlo implementation for use when not all input data are available. Overall, the approaches used are complementary to other methods, constraining allowable parameter ranges in different ways and leading to much tighter constraints overall. EEG methods often provide the most restrictive individual constraints. This approach opens a new, noninvasive window on quantitative brain analysis, with the ability to monitor temporal changes, and the potential to map spatial variations. Unlike traditional phenomenologic quantitative EEG measures, the methods proposed here are based explicitly on physiology and anatomy.

Neurophysical modeling of brain dynamics.

A recent neurophysical model of brain electrical activity is outlined and applied to EEG phenomena. It incorporates single-neuron physiology and the large-scale anatomy of corticocortical and corticothalamic pathways, including synaptic strengths, dendritic propagation, nonlinear firing responses, and axonal conduction. Small perturbations from steady states account for observed EEGs as functions of arousal. Evoked response potentials (ERPs), correlation, and coherence functions are also reproduced. Feedback via thalamic nuclei is critical in determining the forms of these quantities, the transition between sleep and waking, and stability against seizures. Many disorders correspond to significant changes in EEGs, which can potentially be quantified in terms of the underlying physiology using this theory. In the nonlinear regime, limit cycles are often seen, including a regime in which they have the characteristic petit mal 3 Hz spike-and-wave form.

Simulated electrocortical activity at microscopic, mesoscopic, and global scales.

Simulation of electrocortical activity requires (a) determination of the most crucial features to be modelled, (b) specification of state equations with parameters that can be determined against independent measurements, and (c) explanation of electrical events in the brain at several scales. We report our attempts to address these problems, and show that mutually consistent explanations, and simulation of experimental data can be achieved for cortical gamma activity, synchronous oscillation, and the main features of the EEG power spectrum including the cerebral rhythms and evoked potentials. These simulations include consideration of dendritic and synaptic dynamics, AMPA, NMDA, and GABA receptors, and intracortical and cortical/subcortical interactions. We speculate on the way in which Hebbian learning and intrinsic reinforcement processes might complement the brain dynamics thus explained, to produce elementary cognitive operations.

Dynamics of large-scale brain activity in normal arousal states and epileptic seizures.

Links between electroencephalograms (EEGs) and underlying aspects of neurophysiology and anatomy are poorly understood. Here a nonlinear continuum model of large-scale brain electrical activity is used to analyze arousal states and their stability and nonlinear dynamics for physiologically realistic parameters. A simple ordered arousal sequence in a reduced parameter space is inferred and found to be consistent with experimentally determined parameters of waking states. Instabilities arise at spectral peaks of the major clinically observed EEG rhythms-mainly slow wave, delta, theta, alpha, and sleep spindle-with each instability zone lying near its most common experimental precursor arousal states in the reduced space. Theta, alpha, and spindle instabilities evolve toward low-dimensional nonlinear limit cycles that correspond closely to EEGs of petit mal seizures for theta instability, and grand mal seizures for the other types. Nonlinear stimulus-induced entrainment and seizures are also seen, EEG spectra and potentials evoked by stimuli are reproduced, and numerous other points of experimental agreement are found. Inverse modeling enables physiological parameters underlying observed EEGs to be determined by a new, noninvasive route. This model thus provides a single, powerful framework for quantitative understanding of a wide variety of brain phenomena.

The effect of nanometer dimension topographical features on the hygienic status of stainless steel.

Wear of food contact surfaces through abrasion may increase the surface roughness and introduce different topographical features. Both of these properties may enhance retention of soil and microorganisms and affect the surface cleanability. To test this hypothesis, stainless steel surfaces with topographical features and surface roughness (Ra) values simulating those of worn in-use surfaces were prepared. Surfaces were imaged and Ra values determined using atomic force microscopy (AFM). These ranged from 23 to 900 nm. Surfaces were sprayed with standardized cell suspensions of Pseudomonas aeruginosa or Staphylococcus aureus and allowed to air dry and were then cleaned using a nonionic detergent delivered via a manual linear cleaning device. There was a 2-log reduction in numbers attached after cleaning, but there was no significant difference (P > 0.05) between the cleanability of the surfaces in terms of the numbers of cells per unit area remaining after cleaning, although cells appeared to be retained within topographical features. Thus, the simulated effect of wear of a hygienic food contact surface did not affect its cleanability after a one-off microbiological soiling event. AFM provided hitherto unavailable information on the topography of worn stainless steel surfaces. In future work, the surfaces will be repeatedly challenged with an organic soil-microorganism mixture after cleaning events, to provide a more rigorous, realistic test.

Prediction of electroencephalographic spectra from neurophysiology.

A recent neurophysical model of propagation of electrical waves in the cortex is extended to include a physiologically motivated subcortical feedback loop via the thalamus. The electroencephalographic spectrum when the system is driven by white noise is then calculated analytically in terms of physiological parameters, including the effects of filtering of signals by the cerebrospinal fluid, skull, and scalp. The spectral power at low frequencies is found to vary as f(-1) when awake and f(-3) when asleep, with a breakpoint to a steeper power-law tail at frequencies above about 20 Hz in both cases; the f(-1) range concurs with recent magnetoencephalographic observations of such a regime. Parameter sensitivities are explored, enabling a model with fewer free parameters to be proposed, and showing that spectra predicted for physiologically reasonable parameter values strongly resemble those observed in the laboratory. Alpha and beta peaks seen near 10 Hz and twice that frequency, respectively, in the relaxed wakeful state are generated via subcortical feedback in this model, thereby leading to predictions of their frequencies in terms of physiological parameters, and of correlations in their occurrence. Subcortical feedback is also predicted to be responsible for production of anticorrelated peaks in deep sleep states that correspond to the occurrence of theta rhythm at around half the alpha frequency and sleep spindles at 3/2 times the alpha frequency. An additional positively correlated waking peak near three times the alpha frequency is also predicted and tentatively observed, as are two new types of sleep spindle near 5/2 and 7/2 times the alpha frequency, and anticorrelated with alpha. These results provide a theoretical basis for the conventional division of EEG spectra into frequency bands, but imply that the exact bounds of these bands depend on the individual. Three types of potential instability are found: one at zero frequency, another in the theta band at around half the alpha frequency, and a third at the alpha frequency itself.

Activity of the plasma membrane H(+)-ATPase is a key physiological determinant of thermotolerance in Saccharomyces cerevisiae.

The role of membrane integrity and the membrane ATPase in the mechanism of thermotolerance in Saccharomyces cerevisiae was investigated. The resistance to lethal heat of a mutant strain with reduced expression of the membrane ATPase was significantly less than that of the wild-type parent. However, prior exposure to sub-lethal temperatures resulted in the induction of similar levels of thermotolerance in the mutant compared to the parent strain, suggesting that the mechanism of sub-lethal heat-induced thermotolerance is independent of ATPase activity. Supporting this, exposure to sub-lethal heat stress did not result in increased levels of glucose-induced acid efflux at lethal temperatures and there was little correlation between levels of acid efflux and levels of heat resistance. ATPase activity in crude membrane preparations from sub-lethally heat-stressed cells was similar to that in preparations from unstressed cells. Study of net acid flux during heating revealed that pre-stressed cells were able to protect the proton gradient for longer. This may confer an 'advantage' to these cells that results in increased thermotolerance. This was supported by the observation that prior exposure to sub-lethal heat resulted in a transient protection against the large increase in membrane permeability that occurs at lethal temperatures. However, no protection against the large drop in intracellular pH was detected. Sub-lethal heat-induced protection of membrane integrity also occurred to the same extent in the reduced-expression membrane ATPase mutant, further implying that the mechanism of induced thermotolerance is independent of ATPase activity. To conclude, although the membrane ATPase is essential for basal heat resistance, thermotolerance induced by prior exposure to stress is largely conferred by a mechanism that is independent of the enzyme.