Paralkar, M. P. | bioRxiv Science

bioRxiv2020

Systemic Bone Loss Following Myocardial Infarction in Mice is Mitigated by Treatment with a β3 Adrenergic Receptor Antagonist

Myocardial infarction (MI) and osteoporotic fracture (Fx) are leading causes of morbidity and mortality worldwide, and there is epidemiological evidence linking their incidence, suggesting possible crosstalk. MI can exacerbate underlying atherosclerosis through sympathetic nervous system activation and {beta}3 adrenoreceptor-mediated release of hematopoietic stem cells (HSCs), leading to monocytosis. We hypothesized that this same pathway may initiate systemic bone loss following MI, since osteoclasts differentiate from monocytes. In this study, MI was performed in 12-week-old male mice (n=24), and mice were randomized to treatment with a {beta}3-adrenergic receptor antagonist (SR 59230A) or no treatment for 10 days post-operatively; additional mice (n=21, treated and untreated) served as un-operated controls. Bone mineral density (BMD), bone mineral content (BMC), and body composition were quantified at baseline and 10 days post-MI using DXA; at 10 days post-MI circulating monocyte and neutrophil levels were quantified, and the L5 vertebral body and femur were analyzed with micro-computed tomography. We found that MI led to increases in circulating monocyte and neutrophil levels, but contrary to our initial hypothesis, {beta}3-antagonist treatment further increased circulating monocytes compared to untreated mice. BMD and BMC of MI mice decreased at the femur and lumbar spine (-6.9% femur BMD, -3.5% lumbar BMD); {beta}3-antagonist treatment diminished this bone loss response (-5.3% femur BMD, -1.2% lumbar BMD). Similarly, trabecular bone volume was decreased in MI mice compared to control mice, and this bone loss was partially attenuated by {beta}3-antagonist treatment. These results suggest that MI leads to bone loss at both the axial and appendicular skeleton, and that the sympathetic nervous system may be a modulator of this response. This study is the first to mechanistically show bone loss following an ischemic injury; these findings suggest that bone loss and increased fracture risk may be important clinical co-morbidities following MI or other ischemic injuries.

physiology↗

bioRxiv2017

Population-level distribution and putative immunogenicity of cancer neoepitopes

BackgroundTumor neoantigens are a driver of cancer immunotherapy response; however, current neoantigen prediction tools produce many candidates that require further prioritization for research/clinical applications. Additional filtration criteria and population-level understanding may help to produce refined lists of putative neoantigens. Herein, we show neoepitope immunogenicity is likely related to measures of peptide novelty and report population-level behavior of these and other metrics.\n\nMethodsWe propose four peptide novelty metrics to refine predicted neoantigenicity: tumor vs. paired normal peptide binding affinity difference, tumor vs. paired normal peptide sequence similarity, tumor vs. closest human peptide sequence similarity, and tumor vs. closest microbial peptide sequence similarity. We apply these metrics to tumor neoepitopes predicted from somatic missense mutations in The Cancer Genome Atlas (TCGA) and a cohort of melanoma patients, as well as to a group of peptides with neoepitope-specific immune response data using an extension of pVAC-Seq [1].\n\nResultsWe show neoepitope burden varies across TCGA disease sites and HLA alleles, with surprisingly low repetition of neoepitope sequences across patients or neoepitope preferences among sets of HLA alleles. Only 20.3% of predicted neoepitopes across TCGA patients displayed novel binding change based on our binding affinity difference criteria. Similarity of amino acid sequence was typically high between paired tumor-normal epitopes, but in 24.6% of cases, neoepitopes were more similar to other human peptides, or even to bacterial (56.8% of cases) or viral peptides (15.5% of cases), than their paired normal counterparts. Applied to peptides with neoepitope-specific immune response, a linear model incorporating neoepitope binding affinity, protein sequence similarity between neoepitopes and their closest viral peptides, and paired binding affinity difference was able to predict immunogenicity with an AUROC of 0.66.\n\nConclusionsOur proposed neoepitope prioritization criteria emphasize neoepitope novelty and refine patient neoepitope predictions for focus on biologically meaningful candidate neoantigens. We have demonstrated that neoepitopes should be considered not only with respect to their paired normal epitope, but with respect to the entire human proteome, as well as bacterial and viral peptides, with potential implications for neoepitope immunogenicity and personalized vaccines for cancer treatment. We conclude that putative neoantigens are highly variable across individuals as a function of both cancer genetics and personalized HLA repertoire, while the overall behavior of filtration criteria reflects predictable patterns.

cancer biology↗