Biology subjects

Eskandar, E.

Publications and source records attributed to Eskandar, E..

6 recordsLinked to original sources

bioRxiv2025

TIGIT expression dictates the immunosuppressive reprogramming of myeloid cells in glioblastoma

Glioblastoma (GBM) is a deadly brain cancer with near-universal recurrence despite maximal treatment for which new innovations are sorely needed. Immunotherapy has yet to make significant gains in GBM treatment despite revolutionizing other cancer therapies, due in part to GBM-mediated immune suppression. This immune derangement proceeds through several mechanisms, but increasing evidence points to critical roles for tumor-derived extracellular vesicles (EVs) and immunosuppressive myeloid cells as key factors in this process. In the present study, we demonstrate broad expression of TIGIT across myeloid cell populations in the GBM microenvironment, a finding recapitulated by conditioning healthy monocytes with GBM-derived EVs. Further, knockdown of TIGIT expression reduced the immunosuppressive polarization of monocytes, resulting in improvement in T cell function. This finding proceeded in an NLRP3-dependent manner, with substantial co-localization of TIGIT and NLRP3 expression prior to knockdown. These findings point to a novel role for TIGIT expression in diverse myeloid cells in the GBM microenvironment as a marker of immunosuppressive activity and further indicate a hierarchy of immunomodulatory protein activity in these myeloid cells, with TIGIT knockdown unmasking the pro-inflammatory activity of NLRP3. This study bolsters understanding of the immunosuppressive complexities of myeloid cells in the GBM microenvironment, while lending further support to prevention or attenuation of immunosuppressive myeloid cell activity as a means of restoring immune function in GBM. Graphical abstract(Created in BioRender. Asad, M. (2025) https://BioRender.com/euiljoq O_FIG O_LINKSMALLFIG WIDTH=153 HEIGHT=200 SRC="FIGDIR/small/648993v2_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@13dc389org.highwire.dtl.DTLVardef@1f06765org.highwire.dtl.DTLVardef@14200forg.highwire.dtl.DTLVardef@144f245_HPS_FORMAT_FIGEXP M_FIG C_FIG Key PointsO_LITumor-mediated immune suppression is a key barrier to the development of effective immunotherapies for GBM. C_LIO_LITIGIT is broadly expressed in myeloid cells within the GBM microenvironment and can be induced by GBM-derived extracellular vesicles. C_LIO_LIKnockdown of TIGIT reduces immunosuppressive polarization of monocytes and enhances T cell activity via NLRP3 signaling, implicating TIGIT expression as a targetable modifier of immunosuppressive activity in GBM-associated myeloid cells. C_LI Importance of the StudyGlioblastoma (GBM) remains a formidable clinical challenge, with poor prognosis and limited response to current immunotherapies. This study uncovers a novel immunosuppressive axis involving TIGIT expression in myeloid cells, which are key players in the GBM tumor microenvironment. By demonstrating GBM-derived extracellular vesicles induce TIGIT in healthy monocytes and TIGIT knockdown diminishes immunosuppressive polarization in an NLRP3-dependent manner, this study highlights TIGIT as both a marker and modulator of immune dysfunction in GBM. These findings introduce a functional hierarchy of immunoregulatory proteins in tumor-associated myeloid cells, positioning TIGIT as a potential checkpoint target. Restoring immune activity by disrupting this axis could enhance the efficacy of immunotherapy in GBM. Thus, this research not only advances our understanding of tumor-induced immune suppression but also opens a promising therapeutic avenue to reinvigorate anti-tumor immunity in a cancer type historically resistant to immunotherapeutic approaches.

cancer biology↗

bioRxiv2020

The neural computations for stimulus presence and modal identity diverge along a shared circuit

The brain is comprised of neural circuits that are able to flexibly represent the complexity of the external world. In accomplishing this feat, one of the first attributes the brain must code for is whether a stimulus is present and subsequently what sensory information that stimulus contains. One of the core characteristics of that information is which sensory modality(ies) are being represented. How information regarding both the presence and modal identity of a given stimulus is represented and transformed within the brain remains poorly understood. In this study, we investigated how the brain represents the presence and modal identity of a given stimulus while tactile, audio, and audio-tactile stimuli were passively presented to non-human primates. We recorded spiking activity from primary somatosensory (S1) and ventral pre-motor (PMv) cortices, two areas known to be instrumental in transforming sensory information into motor commands for action. Using multivariate analyses to decode stimulus presence and identity, we found that information regarding stimulus presence and modal identity were found in both S1 and PMv and extended beyond the duration of significant evoked spiking activity, and that this information followed different time-courses in these two areas. Further, we combined time-generalization decoding with cross-area decoding to demonstrate that while signaling the presence of a stimulus involves a feedforward-feedback coupling between S1-PMv, the processing of modal identity is largely restricted to S1. Together, these results highlight the differing spatiotemporal dynamics of information flow regarding stimulus presence and modal identity in two nodes of an important cortical sensorimotor circuit. Significance StatementIt is unclear how the structure and function of the brain support differing sensory functions, such as detecting the presence of a stimulus in the environment vs. identifying it. Here, we used multivariate decoding methods on monkey neuronal data to track how information regarding stimulus presence and modal identity flow within a sensorimotor circuit. Results demonstrate that while neural patterns in both primary somatosensory (S1) and ventral pre-motor (PMv) cortices can be used to detect and discriminate between stimuli, they follow different time-courses. Importantly, findings suggest that while information regarding the presence of a stimulus flows reciprocally between S1 and PMv, information regarding stimulus identity is largely contained in S1.

neuroscience↗

bioRxiv2019

Leveraging non-human primate multisensory neurons and circuits in assessing consciousness theory

Both the Global Neuronal Workspace (GNW) and Integrated Information Theory (IIT) posit that highly complex and interconnected networks engender perceptual awareness. GNW specifies that activity recruiting fronto-parietal networks will elicit a subjective experience, while IIT is more concerned with the functional architecture of networks than with activity within it. Here, we argue that according to IIT mathematics, circuits converging on integrative vs. convergent yet non-integrative neurons should support a greater degree of consciousness. We test this hypothesis by analyzing a dataset of neuronal responses collected simultaneously from primary somatosensory cortex (S1) and ventral premotor cortex (vPM) in non-human primates presented with auditory, tactile, and audio-tactile stimuli as they are progressively anesthetized with Propofol. We first describe the multisensory (audio-tactile) characteristics of S1 and vPM neurons (mean and dispersion tendencies, as well as noise-correlations), and functionally label these neurons as convergent or integrative according to their spiking responses. Then, we characterize how these different pools of neurons behave as a function of consciousness. At odds with the IIT mathematics, results suggest that convergent neurons more readily exhibit properties of consciousness (neural complexity and noise correlation) and are more impacted during the loss of consciousness than integrative neurons. Lastly, we provide support for the GNW by showing that neural ignition (i.e., same trial co-activation of S1 and vPM) was more frequent in conscious than unconscious states. Overall, we contrast GNW and IIT within the same single-unit activity dataset, and support the GNW.

neuroscience↗

bioRxiv2019

Intracortical neural activity distal to seizure-onset-areas predicts human focal seizures

The apparent unpredictability of epileptic seizures has a major impact in the quality of life of people with pharmacologically resistant seizures. Here, we present initial results and a proof-of-concept of how focal seizures can be predicted early in advance based on intracortical signals recorded from small neocortical patches away from identified seizure onset areas. We show that machine learning algorithms can discriminate between interictal and preictal periods based on multiunit activity (i.e. thresholded action potential counts) and multi-frequency band local field potentials recorded via 4 X 4 mm2 microelectrode arrays. Microelectrode arrays were implanted in 5 patients undergoing neuromonitoring for resective surgery. Post-implant analysis revealed arrays were outside the seizure onset areas. Preictal periods were defined as the 1-hour period leading to a seizure. A 5-minute gap between the preictal period and the putative seizure onset was enforced to account for potential errors in the determination of actual seizure onset times. We used extreme gradient boosting and long short-term memory networks for prediction. Prediction accuracy based on the area under the receiver operating characteristic curves reached 90% for at least one feature type in each patient. Importantly, successful prediction could be achieved based exclusively on multiunit activity. This result indicates that preictal activity in the recorded neocortical patches involved not only subthreshold postsynaptic potentials, perhaps driven by the distal seizure onset areas, but also neuronal spiking in distal recurrent neocortical networks. Beyond the commonly identified seizure onset areas, our findings point to the engagement of large-scale neuronal networks in the neural dynamics building up toward a seizure. Our initial results obtained on currently available human intracortical recordings warrant new studies on larger datasets, and open new perspectives for seizure prediction and control by emphasizing the contribution of multiscale neural signals in large-scale neuronal networks.

neuroscience↗

bioRxiv2017

The Generation and Propagation of the Human Alpha Rhythm

IntroductionThe alpha rhythm (7-13 Hz) is the longest studied brain oscillation and has been theorized to play a key role in cognition. Still, substantial uncertainty remains over its physiology. In this study, we used micro and macro electrodes in patients undergoing surgery for epilepsy to measure the intracortical and thalamic generators of the human alpha rhythm. We first found that alpha propagates from higher-order anterosuperior cortex towards the lower-order occipital poles, consistent with alpha effecting top-down processing. This cortical alpha drives thalamic alpha, reversing prevailing theories of a thalamic alpha pacemaker. Finally, alpha is dominated by currents and firing in supragranular cortex, contravening the popular conception of alpha as an infragranular rhythm. Together, these results demonstrate that the alpha rhythm reflects short-range supragranular feedback which propagates from higher-order to lower order cortex and cortex to thalamus. These physiological insights explain how alpha could mediate feedback throughout the thalamocortical system.

neuroscience↗

bioRxiv2017

Replay of large-scale spatio-temporal patterns from waking during subsequent slow-wave sleep in human cortex

Animal studies support the hypothesis that in slow-wave sleep, replay of waking neocortical activity under hippocampal guidance leads to memory consolidation. However, no intracranial electrophysiological evidence for replay exists in humans. We identified consistent sequences of population firing peaks across widespread cortical regions during complete waking periods. The occurrence of these Motifs were compared between sleeps preceding the waking period (Sleep-Pre) when the Motifs were identified, and those following (Sleep-Post). In all subjects, the majority of waking Motifs (most of which were novel) had more matches in Sleep-Post than in Sleep-Pre. In rodents, hippocampal replay occurs during local sharp-wave ripples, and the associated neocortical replay tends to occur during local sleep spindles and down-to-up transitions. These waves may facilitate consolidation by sequencing cell-firing and encouraging plasticity. Similarly, we found that Motifs were coupled to neocortical spindles, down-to-up transitions, theta bursts, and hippocampal sharp-wave ripples. While Motifs occurring during cognitive task performance were more likely to have more matches in subsequent sleep, our studies provide no direct demonstration that the replay of Motifs contributes to consolidation. Nonetheless, these results confirm a core prediction of the dominant neurobiological theory of human memory consolidation.

neuroscience↗