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Biology subjects

McKinnon, K.

Publications and source records attributed to McKinnon, K..

4 recordsLinked to original sources

Discovery of frameshift-associated TCRs following personalized neoantigen vaccination in a patient with osteosarcoma

Personalized antigen-directed immunotherapies, including personalized cancer vaccines, are emerging as promising therapeutic modalities for a range of cancer types. Immune monitoring can be used to evaluate the efficacy of a vaccine in stimulating the immune response pre- and post-vaccination; however, such approaches typically stop short of identifying which T cell receptors (TCRs) are functionally driving therapeutic responses. Here, we present a case report of immune monitoring and subsequent TCR discovery experiments following administration of personalized cancer vaccines in a patient with locally recurrent osteosarcoma. Whole PBMCs were stimulated with vaccine peptides (>16 AA) in vitro for 11 days, after which IFN{gamma} ELISPOT identified total T cell responses for 12 of 15 tested peptides post-vaccination. In vitro expanded samples were submitted for 10x single-cell TCR sequencing, from which 26 TCRs were chosen for generation of TCR-T cells based on clonal expansion and culture specificity. Of the generated TCR-T cells, 25 produced functional TCRs, 4 of which were specific to vaccine peptides. However, downstream testing revealed each was MHC class-II restricted. To address this, we repeated the in vitro stimulations with co-cultures of isolated CD8+ T cells with autologous dendritic cells, and cultures of whole PBMCs with anti-MHC class-II blocking antibody. These cultures yielded 10 additional TCRs, 2 of which were responsive to a vaccine peptide containing a MAP2 frameshift mutation. These findings demonstrate an effective approach for leveraging post-vaccination expanded antigen-specific T cell populations for discovery of novel T cell receptors for downstream cellular therapies.

immunology↗

Oncogenic and immunomodulatory functions of SUV420H1 in HPV-negative head and neck squamous cell carcinoma.

Despite the advent of immunotherapy, human-papilloma-virus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) carries a high morbidity and mortality rate, thus novel therapies are urgently needed. Suppressor Of Variegation 4-20 Homolog 1 (SUV420H1) is a protein lysine methyltransferase that writes H4K20me3. Approximately 35% of HPV-negative HNSCC tumors carry gains/amplifications of SUV420H1. Gene Set Enrichment Analysis (GSEA) showed enrichment of proliferation-, epithelial-mesenchymal transition (EMT)- and immune-response pathways in SUV420H1-overexpressing HPV-negative HNSCC tumors. Depletion of SUV420H1 led to decreased proliferation, cell cycling and invasion in human HPV-negative HNSCC cell lines, while enzymatic inhibition decreased the invasive capacity but not the proliferation and cell cycling of HPV-negative HNSCC cell lines, supporting the presence of catalytically-independent and -dependent functions of SUV420H1. In a syngeneic mouse model of mouse oral carcinoma 1 tumors (MOC1), Suv420h1 knockout (KO) in MOC1 cancer cells halted tumor growth and synergized with anti-PD-1 therapy. In the tumor immune microenvironment (TIME) of Suv420h1 KO MOC1 tumors, a significant increase in the macrophage compartment with a concurrent decrease in the protumorigenic granulocytic myeloid derived suppressor cells (gMDSCs) was observed. Genome-wide mapping of SUV420H1-mediated H4K20me3 revealed enrichment of EMT-, IFN-response, and myeloid-attracting chemokines. This work provides rationale for the depletion/degradation of SUV420H1 as a novel therapeutic strategy to hinder proliferation and invasion, and to impart sensitization to anti-PD-1 immunotherapy for patients with HPV-negative HNSCC tumors with SUV420H1 gain/amplification.

cancer biology↗

Predictive Prioritization of Enhancers Associated with Pancreas Disease Risk

Genetic and epigenetic variations in regulatory enhancer elements increase susceptibility to a range of pathologies. Despite recent advances, linking enhancer elements to target genes and predicting transcriptional outcomes of enhancer dysfunction remain significant challenges. Using 3D chromatin conformation assays, we generated an extensive enhancer interaction dataset for the human pancreas, encompassing more than 20 donors and five major cell types, including both exocrine and endocrine compartments. We employed a network approach to parse chromatin interactions into enhancer-promoter tree models, facilitating a quantitative, genome-wide analysis of enhancer connectivity. With these tree models, we developed a machine learning algorithm to estimate the impact of enhancer perturbations on cell type-specific gene expression in the human pancreas. Orthogonal to our computational approach, we perturbed enhancer function in primary human pancreas cells using CRISPR interference and quantified the effects at the single-cell level through RNA FISH coupled with high-throughput imaging. Our enhancer tree models enabled the annotation of common germline risk variants associated with pancreas diseases, linking them to putative target genes in specific cell types. For pancreatic ductal adenocarcinoma, we found a stronger enrichment of disease susceptibility variants within acinar cell regulatory elements, despite ductal cells historically being assumed as the primary cell-of-origin. Our integrative approach--combining cell type-specific enhancer-promoter interaction mapping, computational models, and single-cell enhancer perturbation assays--produced a robust resource for studying the genetic basis of pancreas disorders.

genomics↗

A simple, high-throughput method of protein and label removal from extracellular vesicle samples

Evidence continues to increase of the clinical utility extracellular vesicles (EVs) can provide as translational biomarkers. While a wide variety of EV isolation and purification methods have been implemented, few techniques are high-throughput and scalable for removing excess fluorescent reagents (e.g. dyes, antibodies). EVs are too small to be recovered from routine cell-processing procedures, such as filtration or centrifugation. The lack of suitable methods for removing unbound labels, especially in optical assays, is a major roadblock to accurate EV phenotyping and utilization of EV assays in a translational or clinical setting. Therefore, we developed a method for using a multi-modal resin, referred to as EV-Clean, to remove unbound labels from EV samples, and we demonstrate improvement in flow cytometric EV analysis with the use of this EV-Clean method.

biochemistry↗