Glioblastomas are malignant tumors of the central nervous system hallmarked by subclonal diversity and dynamic adaptation amid developmental hierarchies. The source of dynamic reorganization within the spatial context of these tumors remains elusive. Here, we characterized glioblastomas by spatially resolved transcriptomics, metabolomics, and proteomics. By deciphering regionally shared transcriptional programs across patients, we infer that glioblastoma is organized by spatial segregation of lineage states and adapts to inflammatory and/or metabolic stimuli, reminiscent of the reactive transformation in mature astrocytes. Integration of metabolic imaging and imaging mass cytometry uncovered locoregional tumor-host interdependence, resulting in spatially exclusive adaptive transcriptional programs. Inferring copy-number alterations emphasizes a spatially cohesive organization of subclones associated with reactive transcriptional programs, confirming that environmental stress gives rise to selection pressure. A model of glioblastoma stem cells implanted into human and rodent neocortical tissue mimicking various environments confirmed that transcriptional states originate from dynamic adaptation to various environments.

Sporadic Alzheimer's disease (AD) exclusively affects elderly people. Using direct conversion of AD patient fibroblasts into induced neurons (iNs), we generated an age-equivalent neuronal model. AD patient-derived iNs exhibit strong neuronal transcriptome signatures characterized by downregulation of mature neuronal properties and upregulation of immature and progenitor-like signaling pathways. Mapping iNs to longitudinal neuronal differentiation trajectory data demonstrated that AD iNs reflect a hypo-mature neuronal identity characterized by markers of stress, cell cycle, and de-differentiation. Epigenetic landscape profiling revealed an underlying aberrant neuronal state that shares similarities with malignant transformation and age-dependent epigenetic erosion. To probe for the involvement of aging, we generated rejuvenated iPSC-derived neurons that showed no significant disease-related transcriptome signatures, a feature that is consistent with epigenetic clock and brain ontogenesis mapping, which indicate that fibroblast-derived iNs more closely reflect old adult brain stages. Our findings identify AD-related neuronal changes as age-dependent cellular programs that impair neuronal identity.

Immune checkpoint inhibitor (ICI) therapy has shown a significant benefit in the treatment of a variety of cancer entities. However, immune-related adverse events (irAEs) occur frequently and can lead to ICI treatment termination. MicroRNA-146a (miR-146a) has regulatory functions in immune cells. We observed that mice lacking miR-146a developed markedly more severe irAEs compared with WT mice in several irAE target organs in 2 different murine models. miR-146a ^–/– mice exhibited increased T cell activation and effector function upon ICI treatment. Moreover, neutrophil numbers in the spleen and the inflamed intestine were highly increased in ICI-treated miR-146a ^–/– mice. Therapeutic administration of a miR-146a mimic reduced irAE severity. To validate our preclinical findings in patients, we analyzed the effect of a SNP in the MIR146A gene on irAE severity in 167 patients treated with ICIs. We found that the SNP rs2910164 leading to reduced miR-146a expression was associated with an increased risk of developing severe irAEs, reduced progression-free survival, and increased neutrophil counts both at baseline and during ICI therapy. In conclusion, we characterized miR-146a as a molecular target for preventing ICI-mediated autoimmune dysregulation. Furthermore, we identified the MIR146A SNP rs2910164 as a biomarker to predict severe irAE development in ICI-treated patients.

Direct conversion of human somatic fibroblasts into induced neurons (iNs) allows for the generation of functional neurons while bypassing any stem cell intermediary stages. Although iN technology has an enormous potential for modeling age-related diseases, as well as therapeutic approaches, the technology faces limitations due to variable conversion efficiencies and a lack of thorough understanding of the signaling pathways directing iN conversion. Here, we introduce a new all-in-one inducible lentiviral system that simplifies fibroblast transgenesis for the two pioneer transcription factors, Ngn2 and Ascl1, and markedly improves iN yields. Further, our timeline RNA-Seq data across the course of conversion has identified signaling pathways that become transcriptionally enriched during iN conversion. Small molecular modulators were identified for four signaling pathways that reliably increase the yield of iNs. Taken together, these advances provide an improved toolkit for iN technology and new insight into the mechanisms influencing direct iN conversion.