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DeRosa, J.

Publications and source records attributed to DeRosa, J..

2 recordsLinked to original sources

Single-cell Spatial Metabolic and Immune Phenotyping of Head and Neck Cancer Tissues Identifies Tissue Signatures of Response and Resistance to Immunotherapy

Head and neck squamous cell carcinomas (HNSCC) are the seventh most common cancer and represent a global health burden. Immune checkpoint inhibitors (ICIs) have shown promise in treating recurrent/metastatic cases, with durable benefit in [~]30% of patients. Current biomarkers for head and neck tumors are limited in their dynamic ability to capture tumor microenvironment (TME) features, with an increasing need for deeper tissue characterization. Therefore, new biomarkers are needed to accurately stratify patients and predict responses to therapy. Here, we have optimized and applied an ultra-high plex, single-cell spatial protein analysis in HNSCC. Tissues were simultaneously analyzed with a panel of 101 antibodies that targeted biomarkers related to tumor immune, metabolic and stress microenvironments. Our data uncovered a high degree of intra-tumoral heterogeneity intrinsic to head and neck tumors and provided unique insights into the biology of the tumor. In particular, a cellular neighborhood analysis revealed the presence of 6 unique spatial tumor-immune neighborhoods enriched in functionally specialized immune cell subsets across the patient tissue. Additionally, functional phenotyping based on key metabolic and stress markers identified four distinct tumor regions with differential protein signatures. One tumor region was marked by infiltration of CD8+ cytotoxic T cells and overexpression of BAK, a proapoptotic regulator, suggesting strong immune activation and stress. Another adjacent region within the same tumor had high expression of G6PD and MMP9, known drivers of tumor resistance and invasion respectively. This dichotomy of immune activation-induced death and tumor progression in the same sample demonstrates the heterogenous niches and competing microenvironments that underpin clinical responses of therapeutic resistance. Our data integrate single-cell ultra-high plex spatial information with the functional state of the tumor microenvironment to provide insights into a partial response to immune checkpoint inhibitor therapy in HNSCC. We believe that the approach outlined in this study will pave the way towards a new understanding of TME features associated with response and sensitivity to ICI therapies.

cancer biology↗

Neural Systems Underlying the Implementation of Working Memory Removal Operations

Recently multi-voxel pattern analysis has verified the removal of information from working memory (WM) via three distinct operations replacement, suppression, or clearing compared to information being maintained (Kim et al., 2020). Univariate analyses and classifier importance maps indicate that some brain regions commonly contribute to these operations. This study aimed to use multivariate approaches to determine whether, within these commonly activated brain regions, each of these operations is being represented in a similar or distinct manner. To do so, we used Leiden community detection to identify brain networks that are characterized by similar multi-voxel patterns of activity with regard to these WM operations. Four networks were identified. The Visual Network shows similar multi-voxel patterns for maintain and replace, which are highly dissimilar from suppress and clear, suggesting this network differentiates whether an item is held in WM or not. The Somatomotor Network shows distinct multi-voxel patterns for clear relative to the other operations, suggesting that this network diff in clearing information from WM. The Default Mode Network has distinct patterns for suppress and clear, also suggesting that clearing information from WM is distinct from suppressing it. The Frontoparietal Control Network displays distinct multi-voxel patterns for each of the four operations, suggesting that this network has high involvement in regulating the flow of information within WM. These results indicate that how information is removed from WM depends on distinct brain networks that each have a particular manner in which their co-activation patterns represent these operations. SIGNIFICANCE STATEMENTThe ability to actively remove, manipulate and maintain information in working memory (WM) is required for encoding of new information and for controlling thoughts. This study revealed that different brain networks show characteristic multi-voxel activity patterns across four distinct WM operations: maintenance of information, replacement of one item by another, suppression of a specific item, and clearing the mind of all thought. One network, the Frontoparietal Control Network, differentiates all four operations, suggesting it may play a critical role in the controlled removal of information from WM.

neuroscience↗