Biology subjects

Rathmell, J. C.

Publications and source records attributed to Rathmell, J. C..

25 records · Page 2Linked to original sources

bioRxiv2021

Single-Cell Profiling of the Antigen-Specific Response to BNT162b2 SARS-CoV-2 RNA Vaccine

RNA-based vaccines against SARS-CoV-2 are critical to limiting COVID-19 severity and spread. Cellular mechanisms driving antigen-specific responses to these vaccines, however, remain uncertain. We used single-cell technologies to identify and characterized antigen-specific cells and antibody responses to the RNA vaccine BNT162b2 in longitudinal samples from a cohort of healthy donors. Mass cytometry and machine learning pinpointed a novel expanding, population of antigen-specific non-canonical memory CD4+ and CD8+ T cells. B cell sequencing suggested progression from IgM, with apparent cross-reactivity to endemic coronaviruses, to SARS-CoV-2-specific IgA and IgG memory B cells and plasmablasts. Responding lymphocyte populations correlated with eventual SARS-CoV-2 IgG and a donor lacking these cell populations failed to sustain SARS-CoV-2-specific antibodies and experienced breakthrough infection. These integrated proteomic and genomic platforms reveal an antigen-specific cellular basis of RNA vaccine-based immunity. ONE SENTENCE SUMMARYSingle-cell profiling reveals the cellular basis of the antigen-specific response to the BNT162b2 SARS-CoV-2 RNA vaccine.

immunology↗

bioRxiv2021

Multiplatform Computational Analysis of Mast Cells in Adrenocortical Carcinoma Tumor Microenvironment

IntroductionImmunotherapeutic response failure of adrenocortical carcinomas (ACC) highlights a need for novel strategies targeting immune cell populations in the tumor microenvironment (TME) to overcome tumor resistance and enhance therapeutic response. A recent study explored a new link between tumor mast cell (MC) infiltration and improved outcomes in patients with ACC. We further dissect the role of MC in TME of ACC by examining the tumor MC expression signatures and MC activity within TME to provide additional insight into potential novel immunotherapeutic targets. MethodsUsing CIBERSORTx computational immunogenomic deconvolution algorithm to analyze ACC tumor gene mRNA expression data (TCGA, N=79), we estimated the abundance of tumor immune infiltrating MC, and assessed prognostic potential of MC signaling genes as pro- or anti- tumor signatures, as well as the impact on overall (OS) and disease-free (DFS) survival. ResultsWe stratified MC signaling genes with survival prognostic values (OS, DFS, p<0.05) into anti-tumor (ALOX5, CCL2, CCL5, CXCL10, HDC, IL16, TNF, TPSAB1, VEGFD) and pro-tumor (CXCL1, CXCL3, CXCL8, IL4, IL13, PTGS3, TNSF4, VEGFD) groups. Anti-tumor MC signature, as the predominant phenotype, was associated with improved OS and DFS. ConclusionThe deconvolution analysis of TCGA data identified MC infiltration in ACC microenvironment as predominantly associated with anti-tumor activity. Future studies stemming from our findings may help define the role of MC in TME and the impact on patient survival in patients with ACC. Modulation of tumor MC infiltration may serve as a potential target for novel synergistic immunotherapies for the treatment and improved survival of patients with ACC.

cancer biology↗

bioRxiv2021

Multiplatform Integrative Analyses of Immunosuppressive Signatures in Cortisol-secreting Adrenocortical Carcinoma

Adrenocortical carcinoma (ACC) is a rare but highly aggressive malignancy and nearly half of ACC tumors have been shown to overproduce and secrete adrenal steroids. Excess cortisol secretion, in particular, has been associated with poor prognosis among ACC patients. Furthermore, recent immunotherapy clinical trials demonstrated significant immunoresistance among cortisol-secreting ACC (CS-ACC) patients when compared to their non-Cortisol-secreting (nonCS-ACC) counterparts. The immunosuppressive role of excess glucocorticoid therapies and secretion is well established, however, the impact of the cortisol hypersecretion on ACC tumor microenvironment (TME), immune expression profiles, and immune cell responses remain largely undefined. In this study, we characterized the TME of ACC patients and compared the immunogenomic profiles of nonCS-ACC and CS-ACC tumors to assess the impact of differentially expressed genes (DEGs) related to immune processes on patient prognosis. Comprehensive multiplatform immunogenomic computational analyses of ACC tumors deciphered an immunosuppressive expression profile with a direct impact on patient survival. We identified several primary immunogenomic prognostic indicators and potential targets within the tumor immune landscape of CS-ACC that define a distinct TME and provide additional insight into the understanding of potential contributory mechanisms underlying failure of initial immunotherapeutic trials and poor prognosis of patients with CS-ACC.

cancer biology↗

bioRxiv2020

Cell Programmed Nutrient Partitioning in the Tumor Microenvironment

The tumor microenvironment (TME) includes transformed cancer and infiltrating immune cells1,2. Cancer cells can consume large quantities of glucose through Warburg metabolism3,4 that can be visualized with positron emission tomography (PET). While infiltrating immune cells also rely on glucose, disruptions to metabolism can contribute to tumor immunological evasion5-9. How immune cell metabolism is programmed or restrained by competition with cancer cells for nutrients, remains uncertain. Here we used PET tracers to measure the accessibility of glucose and glutamine to cell subsets in the TME. Surprisingly, myeloid cells including macrophages were the greatest consumers of intra-tumoral glucose, followed by T cells and cancer cells. Cancer cells, in contrast, had the highest glutamine uptake. This distinct nutrient partitioning was programmed through selective mTORC1 signaling and glucose or glutamine-related gene expression. Inhibition of glutamine uptake enhanced glucose uptake across tumor resident cell types and shifted macrophage phenotype, demonstrating glucose is not limiting in the TME. Thus, cancer cells are not the only cells in tumors which exhibit high glucose uptake in vivo and instead preferentially utilize glutamine over other cell types. We observe that intrinsic cellular programs can play a major role in the use of some nutrients. Together, these data argue cell selective partitioning of glucose and glutamine can be exploited to develop therapies and imaging strategies to alter the metabolic programs of specific cell populations in the TME.

cancer biology↗

bioRxiv2020

Macrophages Promote Aortic Valve Cell Calcification Through STAT3 Splicing

ObjectiveMacrophages have been described in calcific aortic valve disease, but it is unclear if they promote or counteract calcification. We aimed to determine how macrophages are involved in calcification using the Notch1+/- model of calcific aortic valve disease. Approach and ResultsMacrophages in wild-type and Notch1+/- murine aortic valves were characterized by flow cytometry. Macrophages in Notch1+/- aortic valves had increased expression of MHCII. We then used bone marrow transplants to test if differences in Notch1+/- macrophages drive disease. Notch1+/- mice had increased valve thickness, macrophage infiltration, and M1-like macrophage polarization regardless of transplanted bone marrow genotype. In vitro approaches confirm that Notch1+/- aortic valve cells promote macrophage invasion as quantified by migration index and M1-like polarization quantified by Ly6C and CCR2 positivity regardless of macrophage genotype. Finally, we found that macrophage interaction with aortic valve cells promotes osteogenic, but not dystrophic, calcification by decreasing abundance of the STAT3{beta} isoform. ConclusionsThis study reveals that Notch1+/- aortic valve disease involves increased macrophage recruitment and polarization driven by altered aortic valve cell secretion, and that increased macrophage recruitment promotes osteogenic calcification through STAT3 splicing changes. Further investigation of STAT3 and macrophage-driven inflammation as therapeutic targets in calcific aortic valve disease is warranted. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/919001v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@3ee95org.highwire.dtl.DTLVardef@24ae93org.highwire.dtl.DTLVardef@41497corg.highwire.dtl.DTLVardef@3f6c05_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2020

Single-cell metabolic analysis by mass cytometry reveals distinct transitional states of CD8 T cell differentiation

Memory T cells conventionally rely on oxidative phosphorylation and short-lived effector T cells on glycolysis. Here, we investigate how T cells arrive at these states during an immune response. In order to understand the metabolic state of rare, early activated T cells, we adapted mass cytometry to quantify metabolic regulators at single-cell resolution in parallel with cell signaling, proliferation, and effector function. We interrogated CD8 T cell activation in vitro as well as the trajectory of CD8 T cells responding to Listeria monocytogenes infection, a well-characterized in vivo model for studies of T cell differentiation. This approach revealed a unique metabolic state in early activated T cells characterized by maximal expression of glycolytic and oxidative metabolic proteins. Peak utilization of both pathways was confirmed by extracellular flux analysis. Cells in this transient state were most abundant five days post-infection before rapidly downregulating metabolic protein expression. This approach should be useful for mechanistic investigations of metabolic regulation of immune responses.

immunology↗

bioRxiv2018

Antigen receptor control of methionine metabolism in T cells

Immune activated T lymphocytes modulate the activity of key metabolic pathways to support the transcriptional reprograming and reshaping of cell proteomes that permits effector T cell differentiation. The present study uses high resolution mass spectrometry and metabolic labelling to explore how T cells control the methionine cycle to produce methyl donors for protein and nucleotide methylations. We show that antigen receptor engagement controls flux through the methionine cycle and also controls RNA and histone methylations. We establish that the main rate limiting step for the methionine cycle is control of methionine transporter expression by antigen receptors. Only T cells that respond to antigen to upregulate and sustain methionine transport are supplied with the methyl donors that permit the dynamic nucleotide methylations and epigenetic reprogramming that drives T cell differentiation.

immunology↗