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Leuthardt, E. C.

Publications and source records attributed to Leuthardt, E. C..

2 recordsLinked to original sources

The conventional dendritic cell 1 subset primes CD8+ T cells and traffics tumor antigen to drive anti-tumor immunity in the brain

The central nervous system (CNS) antigen presenting cell (APC) which primes anti-tumor CD8+ T cell responses remains undefined. Elsewhere, the conventional dendritic cell 1 (cDC1) performs this role. However, steady-state brain cDC1 are rare; cDC localize to choroid plexus and dura. Using preclinical glioblastoma models and cDC1-deficient mice, we explored the role of cDC1 in CNS anti-tumor immunity. We determined that cDC1 mediate checkpoint blockade-induced survival benefit and prime neoantigen-specific CD8+ T cells against brain tumors. We observed that cDC, including cDC1, isolated from the tumor, the dura, and the CNS-draining cervical lymph nodes harbored a traceable fluorescent tumor-antigen. In patient samples, we observed several APC subsets (including the CD141+ cDC1-equivalent) infiltrating glioblastomas, meningiomas, and dura. In these same subsets, we identified a tumor-specific fluorescent metabolite of 5- aminolevulinic acid, which labels tumor cells during fluorescence-guided glioblastoma resection. Together, these data elucidate the specialized behavior of cDC1 and suggest cDC1 play a significant role in CNS anti-tumor immunity. One Sentence SummaryCNS cDC1 engage in previously undefined behavior to establish immune responses against brain tumors.

immunology

Individualized precision targeting of dorsal attention and default mode networks with rTMS in traumatic brain injury-associated depression

BackgroundAt the group level, antidepressant efficacy of rTMS targets is inversely related to their normative connectivity with subgenual anterior cingulate cortex (sgACC). Individualized connectivity may yield better targets, particularly in patients with neuropsychiatric disorders who may have aberrant connectivity. However, sgACC connectivity shows poor test-retest reliability at the individual level. Individualized resting-state network mapping (RSNM) can reliably map inter-individual variability in brain network organization. ObjectiveTo identify individualized RSNM-based rTMS targets that reliably target the sgACC connectivity profile. MethodsWe used RSNM to identify network-based rTMS targets in 10 healthy controls and 13 individuals with traumatic brain injury-associated depression (TBI-D). These "RSNM targets" were compared with consensus structural targets and targets based on individualized anti-correlation with a group-mean-derived sgACC region ("anti-group-mean sgACC targets"). The TBI-D cohort was randomized to receive active (n=9) or sham (n=4) rTMS to RSNM targets. ResultsThe group-mean sgACC connectivity profile was reliably estimated by individualized correlation with default mode network (DMN) and anti-correlation with dorsal attention network (DAN). Individualized RSNM targets were then identified based on DAN anti-correlation and DMN correlation. Counterintuitively, anti-correlation with the group-mean sgACC connectivity profile was stronger and more reliable for RSNM-derived targets than for "anti-group-mean sgACC targets". Improvement in depression after RSNM-targeted rTMS was predicted by target anti-correlation with the portions of sgACC. Active treatment led to increased connectivity within and between several relevant regions. ConclusionsRSNM may enable reliable individualized rTMS targeting, although further research is needed to determine whether this personalized approach can improve clinical outcomes.

neuroscience