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Yoder, S.

Publications and source records attributed to Yoder, S..

4 recordsLinked to original sources

Evaluating the Radiation Sensitivity Index and 12-chemokine gene expression signature for clinical use in a CLIA laboratory

BackgroundThe radiation sensitivity index (RSI) and 12-chemokine gene expression signature (12CK GES) are two gene expression signatures (GES) that were previously developed to predict tumor radiation sensitivity or identify the presence of tertiary lymphoid structures in tumors, respectively. To advance the use of these GES into clinical trial evaluation, their assays must be assessed within the context of the Clinical Laboratory Improvement Amendments (CLIA) process. MethodsUsing HG-U133Plus 2.0 arrays, we first established CLIA laboratory proficiency. Then the accuracy (limit of detection and macrodissection impact), precision (variability by time and operator), sample type (surgery vs. biopsy), and concordance with reference laboratory were evaluated. ResultsRSI and 12CK GES were reproducible (RSI: 0.01 mean difference, 12CK GES 0.17 mean difference) and precise with respect to time and operator. Taken together, the reproducibility analysis of the scores indicated a median RSI difference of 0.06 (6.47% of range) across samples and a median 12CK GES difference of 0.92 (12.29% of range). Experiments indicated that the lower limit of input RNA is 5 ng. Reproducibility with a second CLIA laboratory demonstrated reliability with the median RSI score difference of 0.065 (6% of full range) and 12CK GES difference of 0.93 (12 % of observed range). ConclusionsOverall, under CLIA, RSI and 12CK GES were demonstrated by the Moffitt Cancer Center Advanced Diagnostic Laboratory to be reproducible GES for clinical usage.

genomics↗

Structural Mapping of Polyclonal IgG Responses to HA After Influenza Virus Vaccination or Infection

Cellular and molecular characterization of immune responses elicited by influenza virus infection and seasonal vaccination have informed efforts to improve vaccine efficacy, breadth, and longevity. Here, we use negative stain electron microscopy polyclonal epitope mapping (nsEMPEM) to structurally characterize the humoral IgG antibody responses to hemagglutinin (HA) from human patients vaccinated with a seasonal quadrivalent flu vaccine or infected with influenza A viruses. Our data show that both vaccinated and infected patients had humoral IgGs targeting highly conserved regions on both H1 and H3 subtype HAs, including the stem and anchor, which are targets for universal influenza vaccine design. Responses against H1 predominantly targeted the central stem epitope in infected patients and vaccinated donors, whereas head epitopes were more prominently targeted on H3. Responses against H3 were less abundant, but a greater diversity of H3 epitopes were targeted relative to H1. While our analysis is limited by sample size, on average, vaccinated donors responded to a greater diversity of epitopes on both H1 and H3 than infected patients. These data establish a baseline for assessing polyclonal antibody responses in vaccination and infection, providing context for future vaccine trials and emphasizing the importance of carefully designing vaccines to boost protective responses towards conserved epitopes.

immunology↗

The neuroendocrine transition in prostate cancer is dynamic and dependent on ASCL1

Lineage plasticity is a recognized hallmark of cancer progression that can shape therapy outcomes. The underlying cellular and molecular mechanisms mediating lineage plasticity remain poorly understood. Here, we describe a versatile in vivo platform to identify and interrogate the molecular determinants of neuroendocrine lineage transformation at different stages of prostate cancer progression. Adenocarcinomas reliably develop following orthotopic transplantation of primary mouse prostate organoids acutely engineered with human-relevant driver alterations (e.g., Rb1-/-; Trp53-/-; cMyc+ or Pten-/-; Trp53-/-; cMyc+), but only those with Rb1 deletion progress to ASCL1+ neuroendocrine prostate cancer (NEPC), a highly aggressive, androgen receptor signaling inhibitor (ARSI)-resistant tumor. Importantly, we show this lineage transition requires a native in vivo microenvironment not replicated by conventional organoid culture. By integrating multiplexed immunofluorescence, spatial transcriptomics and PrismSpot to identify cell type-specific spatial gene modules, we reveal that ASCL1+ cells arise from KRT8+ luminal epithelial cells that progressively acquire transcriptional heterogeneity, producing large ASCL1+;KRT8- NEPC clusters. Ascl1 loss in established NEPC results in transient tumor regression followed by recurrence; however, Ascl1 deletion prior to transplantation completely abrogates lineage plasticity, yielding adenocarcinomas with elevated AR expression and marked sensitivity to castration. The dynamic feature of this model reveals the importance of timing of therapies focused on lineage plasticity and offers a platform for identification of additional lineage plasticity drivers.

cell biology↗

Precision Discovery of Novel Inhibitors of Human Cancer Target HsMetAP1 from Vast Unexplored Metagenomic Diversity

Microbial natural products have long been a rich source of human therapeutics. While the chemical diversity encoded in the genomes of microbes is large, this modality has waned as fermentation-based discovery methods have suffered from rediscovery, inefficient scaling, and incompatibility with target-based discovery paradigms. Here, we leverage a metagenomic partitioning strategy to sequence soil microbiomes at unprecedented depth and quality. We then couple these data with target-focused, in silico search strategies and synthetic biology to discover multiple novel natural product inhibitors of human methionine aminopeptidase-1 (HsMetAP1), a validated oncology target. For one of these, metapeptin B, we demonstrate sub-micromolar potency, strong selectivity for HsMetAP1 over HsMetAP2 and elucidate structure-activity relationships. Our approach overcomes challenges of traditional natural product methods, accesses vast, untapped chemical diversity in uncultured microbes, and demonstrates computationally-enabled precision mining of modulators of human proteins.

microbiology↗