Biology subjects

Mayer, A. T.

Publications and source records attributed to Mayer, A. T..

4 recordsLinked to original sources

bioRxiv2022

7-UP: generating in silico CODEX from a small set of immunofluorescence markers

Multiplex immunofluorescence (mIF) assays multiple protein biomarkers on a single tissue section. Recently, high-plex CODEX (co-detection by indexing) systems enable simultaneous imaging of 40+ protein biomarkers, unlocking more detailed molecular phenotyping, leading to richer insights into cellular interactions and disease. However, high-plex imaging can be slower and more costly to collect, limiting its applications, especially in clinical settings. We propose a machine learning framework, 7-UP, that can computationally generate in silico 40-plex CODEX at single-cell resolution from a standard 7-plex mIF panel by leveraging cellular morphology. We demonstrate the usefulness of the imputed biomarkers in accurately classifying cell types and predicting patient survival outcomes. Furthermore, 7-UPs imputations generalize well across samples from different clinical sites and cancer types. 7-UP opens the possibility of in silico CODEX, making insights from high-plex mIF more widely available.

bioinformatics↗

bioRxiv2022

SPACE-GM: geometric deep learning of disease-associated microenvironments from multiplex spatial protein profiles.

Multiplexed immunofluorescence imaging enables high-dimensional molecular profiling at subcellular resolution. However, learning disease-relevant cellular environments from these rich imaging data is an open challenge. We developed SPAtial CEllular Graphical Modeling (SPACE-GM), a geometric deep learning framework that flexibly models tumor microenvironments (TMEs) as cellular graphs. We applied SPACE-GM to 658 head-and-neck and colorectal human cancer samples assayed with 40-plex immunofluorescence imaging to identify spatial motifs associated with cancer recurrence and patient survival after immunotherapy. SPACE-GM is substantially more accurate in predicting patient outcomes than previous approaches for modeling spatial data using neighborhood cell-type compositions. Computational interpretation of the disease-relevant microenvironments identified by SPACE-GM generates insights into the effect of spatial dispersion of tumor cells and granulocytes on patient prognosis.

bioinformatics↗

bioRxiv2021

Injectable Nanoparticle-Based Hydrogels Enable the Safe and Effective Deployment of Immunostimulatory CD40 Agonist Antibodies

When properly deployed, the immune system can eliminate deadly pathogens, eradicate metastatic cancers, and provide long-lasting protection from diverse diseases. Unfortunately, realizing these remarkable capabilities is inherently risky as disruption to immune homeostasis can elicit dangerous complications or autoimmune disorders. While current research is continuously expanding the arsenal of potent immunotherapeutics, there is a technological gap when it comes to controlling when, where, and how long these drugs act on the body. Here, we explore the ability of a slow-releasing injectable hydrogel depot to reduce the problematic dose-limiting toxicities of immunostimulatory CD40 agonist (CD40a) while maintaining their potent anti-cancer efficacy. We leverage a previously described polymer-nanoparticle (PNP) hydrogel system that exhibits shear-thinning and yield-stress properties that we hypothesized would improve locoregional delivery of the CD40a immunotherapy. Using PET imaging, we demonstrate that prolonged hydrogel-based delivery redistributes CD40a exposure to the tumor and the tumor draining lymph node (TdLN), thereby reducing weight loss, hepatotoxicity, and cytokine storm associated with standard treatment. Moreover, CD40a-loaded hydrogels mediate improved local cytokine induction in the TdLN and improve treatment efficacy in the B16F10 melanoma model. PNP hydrogels, therefore, represent a facile, drug-agnostic method to ameliorate immune-related adverse effects and explore locoregional delivery of immunostimulatory drugs.

bioengineering↗

bioRxiv2020

Activating Immune Recognition in Pancreatic Ductal Adenocarcinoma Using Autophagy Inhibition, MEK blockade and CD40 Agonism

Pancreatic ductal adenocarcinoma (PDA) patients have not yet benefitted from the revolution in cancer immunotherapy due in large part to the dominantly immunosuppressive tumor microenvironment (TME). MEK inhibition combined with autophagy inhibition leads to transient tumor responses in some PDA patients. We find that co-inhibition of MEK (using cobimetinib, COBI) and autophagy (using mefloquine, MFQ), but not either treatment alone, activates the Type I Interferon/STING pathway in tumor cells which in turn reprogram tumor associated macrophages (TAMs) in paracrine to foster an immunogenic switch. This effect is augmented by a CD40 agonist (aCD40). Triple therapy (COBI+MFQ+aCD40) achieved cytotoxic T cell activation in an immunologically "cold" mouse PDA model, leading to enhanced anti-tumor immunity. Collectively, MEK and autophagy co-inhibition coupled with CD40 agonism invokes immuno-reprograming and is an attractive therapeutic approach for PDA immunotherapy development.

cancer biology↗