Fludarabine, Cytarabine, Granulocyte Colony-Stimulating Factor, and Idarubicin With Gemtuzumab Ozogamicin Improves Event-Free Survival in Younger Patients With Newly Diagnosed AML and Overall Survival in Patients With NPM1 and FLT3 Mutations.

PURPOSE: To determine the optimal induction chemotherapy regimen for younger adults with newly diagnosed AML without known adverse risk cytogenetics. PATIENTS AND METHODS: One thousand thirty-three patients were randomly assigned to intensified (fludarabine, cytarabine, granulocyte colony-stimulating factor, and idarubicin [FLAG-Ida]) or standard (daunorubicin and Ara-C [DA]) induction chemotherapy, with one or two doses of gemtuzumab ozogamicin (GO). The primary end point was overall survival (OS). RESULTS: There was no difference in remission rate after two courses between FLAG-Ida + GO and DA + GO (complete remission [CR] + CR with incomplete hematologic recovery 93% v 91%) or in day 60 mortality (4.3% v 4.6%). There was no difference in OS (66% v 63%; P = .41); however, the risk of relapse was lower with FLAG-Ida + GO (24% v 41%; P < .001) and 3-year event-free survival was higher (57% v 45%; P < .001). In patients with an NPM1 mutation (30%), 3-year OS was significantly higher with FLAG-Ida + GO (82% v 64%; P = .005). NPM1 measurable residual disease (MRD) clearance was also greater, with 88% versus 77% becoming MRD-negative in peripheral blood after cycle 2 (P = .02). Three-year OS was also higher in patients with a FLT3 mutation (64% v 54%; P = .047). Fewer transplants were performed in patients receiving FLAG-Ida + GO (238 v 278; P = .02). There was no difference in outcome according to the number of GO doses, although NPM1 MRD clearance was higher with two doses in the DA arm. Patients with core binding factor AML treated with DA and one dose of GO had a 3-year OS of 96% with no survival benefit from FLAG-Ida + GO. CONCLUSION: Overall, FLAG-Ida + GO significantly reduced relapse without improving OS. However, exploratory analyses show that patients with NPM1 and FLT3 mutations had substantial improvements in OS. By contrast, in patients with core binding factor AML, outcomes were excellent with DA + GO with no FLAG-Ida benefit.

A randomized comparison of CPX-351 and FLAG-Ida in adverse karyotype AML and high-risk MDS: the UK NCRI AML19 trial.

Liposomal daunorubicin and cytarabine (CPX-351) improved overall survival (OS) compared with 7+3 chemotherapy in older patients with secondary acute myeloid leukemia (AML); to date, there have been no randomized studies in younger patients. The high-risk cohort of the UK NCRI AML19 trial (ISRCTN78449203) compared CPX-351 with FLAG-Ida in younger adults with newly diagnosed adverse cytogenetic AML or high-risk myelodysplastic syndromes (MDS). A total of 189 patients were randomized (median age, 56 years). Per clinical criteria, 49% of patients had de novo AML, 20% had secondary AML, and 30% had high-risk MDS. MDS-related cytogenetics were present in 73% of the patients, with a complex karyotype in 49%. TP53 was the most common mutated gene, in 43%. Myelodysplasia-related gene mutations were present in 75 (44%) patients. The overall response rate (CR + CRi) after course 2 was 64% and 76% for CPX-351 and FLAG-Ida, respectively. There was no difference in OS (13.3 months vs 11.4 months) or event-free survival in multivariable analysis. However, relapse-free survival was significantly longer with CPX-351 (median 22.1 vs 8.35 months). There was no difference between the treatment arms in patients with clinically defined secondary AML or those with MDS-related cytogenetic abnormalities; however, an exploratory subgroup of patients with MDS-related gene mutations had significantly longer OS with CPX-351 (median 38.4 vs 16.3 months). In conclusion, the OS of younger patients with adverse risk AML/MDS was not significantly different between CPX-351 and FLAG-Ida.

tDCS induced GABA change is associated with the simulated electric field in M1, an effect mediated by grey matter volume in the MRS voxel.

BACKGROUND AND OBJECTIVE: Transcranial direct current stimulation (tDCS) has wide ranging applications in neuro-behavioural and physiological research, and in neurological rehabilitation. However, it is currently limited by substantial inter-subject variability in responses, which may be explained, at least in part, by anatomical differences that lead to variability in the electric field (E-field) induced in the cortex. Here, we tested whether the variability in the E-field in the stimulated cortex during anodal tDCS, estimated using computational simulations, explains the variability in tDCS induced changes in GABA, a neurophysiological marker of stimulation effect. METHODS: Data from five previously conducted MRS studies were combined. The anode was placed over the left primary motor cortex (M1, 3 studies, N = 24) or right temporal cortex (2 studies, N = 32), with the cathode over the contralateral supraorbital ridge. Single voxel spectroscopy was performed in a 2x2x2cm voxel under the anode in all cases. MRS data were acquired before and either during or after 1 mA tDCS using either a sLASER sequence (7T) or a MEGA-PRESS sequence (3T). sLASER MRS data were analysed using LCModel, and MEGA-PRESS using FID-A and Gannet. E-fields were simulated in a finite element model of the head, based on individual structural MR images, using SimNIBS. Separate linear mixed effects models were run for each E-field variable (mean and 95th percentile; magnitude, and components normal and tangential to grey matter surface, within the MRS voxel). The model included effects of time (pre or post tDCS), E-field, grey matter volume in the MRS voxel, and a 3-way interaction between time, E-field and grey matter volume. Additionally, we ran a permutation analysis using PALM to determine whether E-field anywhere in the brain, not just in the MRS voxel, correlated with GABA change. RESULTS: In M1, higher mean E-field magnitude was associated with greater anodal tDCS-induced decreases in GABA (t(24) = 3.24, p = 0.003). Further, the association between mean E-field magnitude and GABA change was moderated by the grey matter volume in the MRS voxel (t(24) = -3.55, p = 0.002). These relationships were consistent across all E-field variables except the mean of the normal component. No significant relationship was found between tDCS-induced GABA decrease and E-field in the temporal voxel. No significant clusters were found in the whole brain analysis. CONCLUSIONS: Our data suggest that the electric field induced by tDCS within the brain is variable, and is significantly related to anodal tDCS-induced decrease in GABA, a key neurophysiological marker of stimulation. These findings strongly support individualised dosing of tDCS, at least in M1. Further studies examining E-fields in relation to other outcome measures, including behaviour, will help determine the optimal E-fields required for any desired effects.

Learning to optimize perceptual decisions through suppressive interactions in the human brain.

Translating noisy sensory signals to perceptual decisions is critical for successful interactions in complex environments. Learning is known to improve perceptual judgments by filtering external noise and task-irrelevant information. Yet, little is known about the brain mechanisms that mediate learning-dependent suppression. Here, we employ ultra-high field magnetic resonance spectroscopy of GABA to test whether suppressive processing in decision-related and visual areas facilitates perceptual judgments during training. We demonstrate that parietal GABA relates to suppression of task-irrelevant information, while learning-dependent changes in visual GABA relate to enhanced performance in target detection and feature discrimination tasks. Combining GABA measurements with functional brain connectivity demonstrates that training on a target detection task involves local connectivity and disinhibition of visual cortex, while training on a feature discrimination task involves inter-cortical interactions that relate to suppressive visual processing. Our findings provide evidence that learning optimizes perceptual decisions through suppressive interactions in decision-related networks.

The dynamics of cortical GABA in human motor learning.

KEY POINTS: The ability to learn new motor skills is supported by plasticity in the structural and functional organisation of the primary motor cortex in the human brain. Changes inhibitory to signalling by GABA are thought to be crucial in inducing motor cortex plasticity. This study used magnetic resonance spectroscopy (MRS) to quantify the concentration of GABA in human motor cortex during a period of motor learning, as well as during a period of movement and a period at rest. We report evidence for a reduction in the MRS-measured concentration of GABA specific to learning. Further, the GABA concentration early in the learning task was strongly correlated with the magnitude of subsequent learning: higher GABA concentrations were associated with poorer learning. The results provide initial insight into the neurochemical correlates of cortical plasticity associated with motor learning, specifically relevant in therapeutic efforts to induce cortical plasticity during recovery from stroke. ABSTRACT: The ability to learn novel motor skills is a central part of our daily lives and can provide a model for rehabilitation after a stroke. However, there are still fundamental gaps in our understanding of the physiological mechanisms that underpin human motor plasticity. The acquisition of new motor skills is dependent on changes in local circuitry within the primary motor cortex (M1). This reorganisation has been hypothesised to be facilitated by a decrease in local inhibition via modulation of the neurotransmitter GABA, but this link has not been conclusively demonstrated in humans. Here, we used 7 T magnetic resonance spectroscopy to investigate the dynamics of GABA concentrations in human M1 during the learning of an explicit, serial reaction time task. We observed a significant reduction in GABA concentration during motor learning that was not seen in an equivalent motor task lacking a learnable sequence, nor during a passive resting task of the same duration. No change in glutamate was observed in any group. Furthermore, M1 GABA measured early in task performance was strongly correlated with the degree of subsequent learning, such that greater inhibition was associated with poorer subsequent learning. This result suggests that higher levels of cortical inhibition may present a barrier that must be surmounted in order to achieve an increase in M1 excitability, and hence encoding of a new motor skill. These results provide strong support for the mechanistic role of GABAergic inhibition in motor plasticity, raising questions regarding the link between population variability in motor learning and GABA metabolism in the brain.

Neurochemical changes underpinning the development of adjunct therapies in recovery after stroke: A role for GABA?

Stroke is a leading cause of long-term disability, with around three-quarters of stroke survivors experiencing motor problems. Intensive physiotherapy is currently the most effective treatment for post-stroke motor deficits, but much recent research has been targeted at increasing the effects of the intervention by pairing it with a wide variety of adjunct therapies, all of which aim to increase cortical plasticity, and thereby hope to maximize functional outcome. Here, we review the literature describing neurochemical changes underlying plasticity induction following stroke. We discuss methods of assessing neurochemicals in humans, and how these measurements change post-stroke. Motor learning in healthy individuals has been suggested as a model for stroke plasticity, and we discuss the support for this model, and what evidence it provides for neurochemical changes. One converging hypothesis from animal, healthy and stroke studies is the importance of the regulation of the inhibitory neurotransmitter GABA for the induction of cortical plasticity. We discuss the evidence supporting this hypothesis, before finally summarizing the literature surrounding the use of adjunct therapies such as non-invasive brain stimulation and SSRIs in post-stroke motor recovery, both of which have been show to influence the GABAergic system.

A Mechanistic Link from GABA to Cortical Architecture and Perception.

Understanding both the organization of the human cortex and its relation to the performance of distinct functions is fundamental in neuroscience. The primary sensory cortices display topographic organization, whereby receptive fields follow a characteristic pattern, from tonotopy to retinotopy to somatotopy [1]. GABAergic signaling is vital to the maintenance of cortical receptive fields [2]; however, it is unclear how this fine-grain inhibition relates to measurable patterns of perception [3, 4]. Based on perceptual changes following perturbation of the GABAergic system, it is conceivable that the resting level of cortical GABAergic tone directly relates to the spatial specificity of activation in response to a given input [5-7]. The specificity of cortical activation can be considered in terms of cortical tuning: greater cortical tuning yields more localized recruitment of cortical territory in response to a given input. We applied a combination of fMRI, MR spectroscopy, and psychophysics to substantiate the link between the cortical neurochemical milieu, the tuning of cortical activity, and variability in perceptual acuity, using human somatosensory cortex as a model. We provide data that explain human perceptual acuity in terms of both the underlying cellular and metabolic processes. Specifically, higher concentrations of sensorimotor GABA are associated with more selective cortical tuning, which in turn is associated with enhanced perception. These results show anatomical and neurochemical specificity and are replicated in an independent cohort. The mechanistic link from neurochemistry to perception provides a vital step in understanding population variability in sensory behavior, informing metabolic therapeutic interventions to restore perceptual abilities clinically.