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Biology subjects

Lovrenert, K.

Publications and source records attributed to Lovrenert, K..

2 recordsLinked to original sources

Distinct cell adhesion signature defines glioblastoma myeloid-derived suppressor cell subsets

Increased myeloid-derived suppressor cell (MDSC) frequency is associated with worse outcomes and poor therapeutic response in glioblastoma (GBM). Monocytic (m) MDSCs represent the predominant subset in the GBM microenvironment. However, the molecular basis of mMDSC enrichment in the tumor microenvironment compared to granulocytic (g) MDSCs has yet to be determined. Here, we report that mMDSCs and gMDSCs display differences in their tumoraccelerating ability, with mMDSCs driving tumor growth in GBM models. Epigenetic assessments indicate enhanced gene accessibility for cell adhesion programs in mMDSCs and higher cellsurface integrin expression in mouse and human mMDSCs. Integrin {beta}1 blockage abrogated the tumor-promoting phenotype of mMDSCs and altered the immune profile in the tumor microenvironment. These findings suggest that integrin {beta}1 expression underlies the enrichment of mMDSCs in tumors and represents a putative immunotherapy target to attenuate myeloid cell-driven immune suppression in GBM. SummaryMyeloid-derived suppressor cells (MDSCs) drive glioblastoma growth; however, the function of specific MDSCs subsets is unclear. Bayik et al. demonstrate that adhesion programs are enhanced in monocytic MDSCs and responsible for their GBM-promoting function.

immunology↗

Convergence of case-specific epigenetic alterations identify a confluence of genetic vulnerabilities tied to opioid dependence

Opioid dependence is a highly heterogeneous disease driven by a variety of genetic and environmental risk factors which have yet to be fully elucidated. We interrogated the effects of opioid dependence on the brain using ChIP-seq to quantify patterns of H3K27 acetylation in dorsolateral prefrontal cortical neurons isolated from 51 opioid-overdose cases and 51 accidental death controls. Among opioid cases, we observed global hypoacetylation and identified 388 putative enhancers consistently depleted for H3K27ac. Machine learning on H3K27ac patterns predicts case-control status with high accuracy. We focus on case-specific regulatory alterations, revealing 81,399 hypoacetylation events, uncovering vast inter-patient heterogeneity. We developed a strategy to decode this heterogeneity based on convergence analysis, which leveraged promoter-capture Hi-C to identify five genes over-burdened by alterations in their regulatory network or "plexus": ASTN2, KCNMA1, DUSP4, GABBR2, ENOX1. These convergent loci are enriched for opioid use disorder risk genes and heritability for generalized anxiety, number of sexual partners, and years of education. Overall, our multi-pronged approach uncovers neurobiological aspects of opioid dependence and captures genetic and environmental factors perpetuating the opioid epidemic.

genomics↗