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Legumain Induces Oral Cancer Pain by Biased Agonism of Protease-Activated Receptor-2

Tu, Nguyen Huu; Jensen, Dane D; Anderson, Bethany M; Chen, Elyssa; Jimenez-Vargas, Nestor N; Scheff, Nicole N; Inoue, Kenji; Tran, Hung D; Dolan, John C; Meek, Tamaryn A; Hollenberg, Morley D; Liu, Cheng Z; Vanner, Stephen J; Janal, Malvin N; Bunnett, Nigel W; Edgington-Mitchell, Laura E; Schmidt, Brian L
Oral squamous cell carcinoma (OSCC) is one of the most painful cancers, which interferes with orofacial function including talking and eating. We report that legumain (Lgmn) cleaves protease-activated receptor-2 (PAR2) in the acidic OSCC microenvironment to cause pain. Lgmn is a cysteine protease of late endosomes and lysosomes that can be secreted; it exhibits maximal activity in acidic environments. The role of Lgmn in PAR2-dependent cancer pain is unknown. We studied Lgmn activation in human oral cancers and oral cancer mouse models. Lgmn was activated in OSCC patient tumors, compared to matched normal oral tissue. After intraplantar, facial or lingual injection, Lgmn evoked nociception in wild-type (WT) female mice but not in female mice lacking PAR2 in NaV1.8-positive neurons (Par2Nav1.8), nor in female mice treated with a Lgmn inhibitor, LI-1. Inoculation of an OSCC cell line caused mechanical and thermal hyperalgesia that was reversed by LI-1. Par2Nav1.8 and Lgmn deletion attenuated mechanical allodynia in female mice with carcinogen-induced OSCC. Lgmn caused PAR2-dependent hyperexcitability of trigeminal neurons from WT female mice. Par2 deletion, LI-1 and inhibitors of adenylyl cyclase or protein kinase A prevented the effects of Lgmn. Under acidified conditions, Lgmn cleaved within the extracellular N-terminus of PAR2 at Asn30↓Arg31, proximal to the canonical trypsin activation site. Lgmn activated PAR2 by biased mechanisms in HEK293 cells to induce Ca2+ mobilization, cAMP formation and protein kinase A/D activation, but not β-arrestin recruitment or PAR2 endocytosis. Thus, in the acidified OSCC microenvironment Lgmn activates PAR2 by biased mechanisms that evoke cancer pain.SIGNIFICANCE STATEMENTOral squamous cell carcinoma (OSCC) is one of the most painful cancers. We report that legumain (Lgmn), which exhibits maximal activity in acidic environments, cleaves protease-activated receptor-2 (PAR2) on neurons to produce OSCC pain. Active Lgmn was elevated in OSCC patient tumors, compared to matched normal oral tissue. Lgmn evokes pain-like behavior through PAR2 Exposure of pain-sensing neurons to Lgmn decreased the current required to generate an action potential through PAR2 Inhibitors of adenylyl cyclase and protein kinase A prevented the effects of Lgmn. Lgmn activated PAR2 to induce calcium mobilization, cAMP formation and activation of protein kinase D and A, but not β-arrestin recruitment or PAR2 endocytosis. Thus, Lgmn is a biased agonist of PAR2 that evokes cancer pain.
PMID: 33172978
ISSN: 1529-2401
CID: 4665122

A Gradient of Sharpening Effects by Perceptual Prior across the Human Cortical Hierarchy

González-García, Carlos; He, Biyu Jade
Prior knowledge profoundly influences perceptual processing. Previous studies have revealed consistent suppression of predicted stimulus information in sensory areas, but how prior knowledge modulates processing higher up in the cortical hierarchy remains poorly understood. In addition, the mechanism leading to suppression of predicted sensory information remains unclear, and studies thus far have revealed a mixed pattern of results in support of either the 'sharpening' or 'dampening' model. Here, using 7T fMRI in humans (both sexes), we observed that prior knowledge acquired from fast, one-shot perceptual learning sharpens neural representation throughout the ventral visual stream, generating suppressed sensory responses. In contrast, the frontoparietal (FPN) and default-mode (DMN) networks exhibit similar sharpening of content-specific neural representation but in the context of unchanged and enhanced activity magnitudes, respectively-a pattern we refer to as 'selective enhancement'. Together, these results reveal a heretofore unknown macroscopic gradient of prior knowledge's sharpening effect on neural representations across the cortical hierarchy.SIGNIFICANCE STATEMENT:A fundamental question in neuroscience is how prior knowledge shapes perceptual processing. Perception is constantly informed by internal priors in the brain acquired from past experiences, but the neural mechanisms underlying this process are poorly understood. To date, research on this question has focused on early visual regions, reporting a consistent downregulation when predicted stimuli are encountered. Here, using a dramatic one-shot perceptual learning paradigm, we observed that prior knowledge results in sharper neural representations across the cortical hierarchy of the human brain through a gradient of mechanisms. In visual regions, neural responses tuned away from internal predictions are suppressed. In frontoparietal regions, neural activity consistent with priors is selectively enhanced. These results deepen our understanding of how prior knowledge informs perception.
PMID: 33208472
ISSN: 1529-2401
CID: 4673592

Photoswitchable Lipids

Morstein, Johannes; Impastato, Anna C; Trauner, Dirk
Photoswitchable lipids are emerging tools for the precise manipulation and study of lipid function. They can modulate many aspects of membrane biophysics, including permeability, fluidity, lipid mobility and domain formation. They are also very useful in lipid physiology and enable optical control of a wide array of lipid receptors, such as ion channels, G protein-coupled receptors, nuclear hormone receptors, and enzymes that translocate to membranes. Enzymes involved in lipid metabolism often process them in a light-dependent fashion. Photoswitchable lipids complement other functionalized lipids widely used in lipid chemical biology, including isotope-labeled lipids (lipidomics), fluorescent lipids (imaging), bifunctional lipids (lipid-protein crosslinking), photocaged lipids (photopharmacology), and other labeled variants.
PMID: 32790211
ISSN: 1439-7633
CID: 4722352

Assessing temporal responsiveness of primary stimulated neurons in auditory brainstem and cochlear implant users

Azadpour, Mahan; Shapiro, William H; Roland, J Thomas; Svirsky, Mario A
The reasons why clinical outcomes with auditory brainstem implants (ABIs) are generally poorer than with cochlear implants (CIs) are still somewhat elusive. Prior work has focused on differences in processing of spectral information due to possibly poorer tonotopic representation and higher channel interaction with ABIs than with CIs. In contrast, this study examines the hypothesis that a potential contributing reason for poor speech perception in ABI users may be the relative lack of temporal responsiveness of the primary neurons that are stimulated by the ABI. The cochlear nucleus, the site of ABI stimulation, consists of different neuron types, most of which have much more complex responses than the auditory nerve neurons stimulated by a CI. Temporal responsiveness of primary stimulated neurons was assessed in a group of ABI and CI users by measuring recovery of electrically evoked compound action potentials (ECAPs) from single-pulse forward masking. Slower ECAP recovery tended to be associated with poorer hearing outcomes in both groups. ABI subjects with the longest recovery time had no speech understanding or even no hearing sensation with their ABI device; speech perception for the one CI outlier with long ECAP recovery time was well below average. To the extent that ECAP recovery measures reveal temporal properties of the primary neurons that receive direct stimulation form neural prosthesis devices, they may provide a physiological underpinning for clinical outcomes of auditory implants. ECAP recovery measures may be used to determine which portions of the cochlear nucleus to stimulate, and possibly allow us to enhance the stimulation paradigms.
PMID: 33434815
ISSN: 1878-5891
CID: 4746742

A Normative and Biologically Plausible Algorithm for Independent Component Analysis

Chapter by: Bahroun, Yanis; Chklovskii, Dmitri B.; Sengupta, Anirvan M.
in: Advances in Neural Information Processing Systems by
[S.l.] : Neural information processing systems foundation, 2021
pp. 7368-7384
ISBN: 9781713845393
CID: 5314952

The normalization of consumer valuations: Context-dependent preferences from neurobiological constraints

Webb, Ryan; Glimcher, Paul W.; Louie, Kenway
Consumer valuations are shaped by choice sets, exemplified by patterns of substitution between alternatives as choice sets are varied. Building on recent neuroeconomic evidence that valuations are transformed during the choice process, we incorporate the canonical divisive normalization computation into a discrete choice model and characterize how choice behaviour depends on both size and composition of the choice set. We then examine evidence for such behaviour from two choice experiments that vary the size and composition of the choice set. We find that divisive normalization more accurately captures observed behaviour than alternative models, including an example range normalization model. These results are robust across experimental paradigms. Finally, we demonstrate that Divisive Normalization implements an efficient means for the brain to represent valuations given neurobiological constraints, yielding the fewest choice errors possible given those constraints.
SCOPUS:85099481857
ISSN: 0025-1909
CID: 4769932

Nutritional prevention and treatment of urinary tract stones

Chapter by: Dahl, Neera K.; Goldfarb, David S.
in: Nutritional Management of Renal Disease, Fourth Edition by
[S.l.] : Elsevier, 2021
pp. 685-697
ISBN: 9780128185414
CID: 5369612

Across-animal odor decoding by probabilistic manifold alignment

Chapter by: Herrero-Vidal, Pedro; Rinberg, Dmitry; Savin, Cristina
in: Advances in Neural Information Processing Systems by
[S.l.] : Neural information processing systems foundation, 2021
pp. 20360-20372
ISBN: 9781713845393
CID: 5315252

Optoacoustic visualization of GCaMP6f labeled deep brain activity in a murine intracardiac perfusion model

Chapter by: Degtyaruk, Oleksiy; Larney, Benedict Mc; Deán-Ben, Xosé Luis; Shoham, Shy; Razansky, Daniel
in: Progress in Biomedical Optics and Imaging - Proceedings of SPIE by
[S.l.] : SPIE, 2021
pp. ?-?
ISBN: 9781510640931
CID: 4962652

Neural optimal feedback control with local learning rules

Chapter by: Friedrich, Johannes; Golkar, Siavash; Farashahi, Shiva; Genkin, Alexander; Sengupta, Anirvan M.; Chklovskii, Dmitri B.
in: Advances in Neural Information Processing Systems by
[S.l.] : Neural information processing systems foundation, 2021
pp. 16358-16370
ISBN: 9781713845393
CID: 5314862