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Seo, K.

Publications and source records attributed to Seo, K..

8 recordsLinked to original sources

IL-6 underlies microenvironment immunosuppression and resistance to therapy in glioblastoma

The glioblastoma tumor immune microenvironment (TIME) is an immunosuppressive barrier to therapy that encumbers glioblastoma responses to immune checkpoint inhibition (ICI). Immunosuppressive cytokines, pro-tumor myeloid cells, and exhausted T-cells are hallmarks of the glioblastoma TIME. Here we integrate spatial and single-cell analyses of patient-matched human glioblastoma samples before and after ICI with genetic, immunologic, single-cell, and pharmacologic studies in preclinical models to reveal that interleukin-6 (IL-6) inhibition reprograms the glioblastoma TIME to sensitize mouse glioblastoma to ICI and radiotherapy. Rare human glioblastoma patients who achieve clinical responses to ICI have lower pre-treatment IL-6 levels compared to glioblastomas who do not respond to ICI. Immune stimulatory gene therapy suppresses IL-6 tumor levels in preclinical murine models of glioblastoma. Furthermore, survival was longer in Il-6 knockout mice with orthotopic SB28 glioblastoma relative to wild-type mice. IL-6 blockade with a neutralizing antibody transiently sensitizes mouse glioblastoma to anti-PD-1 by increasing MHCII+ monocytes, CD103+ migratory dendritic cells (DCs), CD11b+ conventional DCs, and effector CD8+ T cells, and decreasing immunosuppressive Tregs. To translate these findings to a combination treatment strategy for recurrent glioblastoma patients, we show that IL-6 blockade plus ICI durably sensitizes mouse glioblastoma to high-dose radiotherapy.

cancer biology↗

Multiplatform molecular profiling and functional genomic screens identify prognostic signatures and mechanisms underlying MEK inhibitor response in somatic NF1 mutant glioblastoma

NF1 is recurrently mutated in glioblastoma yet the molecular landscape and efficacy of targeted therapies remain unclear. Here, we combine bulk and single cell genomics of human somatic NF1 mutant, IDH-wildtype glioblastomas with functional genomic analysis of cell lines and mouse intracranial tumor models to identify molecular subgroups within NF1 mutant glioblastomas and mechanisms underlying MEK inhibitor response. Targeted DNA sequencing showed homozygous deletion of the cell cycle regulator CDKN2A/B is a poor prognostic marker in somatic NF1 mutant, but not NF1 wildtype, tumors. DNA methylation array profiling revealed three epigenetic groups highlighted by distinct clinical features, co-mutation patterns, and reference methylation classifier identities. Genome-wide CRISPRi screens in glioblastoma cells revealed cell cycle regulators are conserved mediators of cell growth while response to the MEK inhibitor selumetinib converges on Ras/RAF/MEK pathway activation. Repression of the RAF regulator SHOC2 sensitizes glioblastomas to selumetinib in vitro and in vivo in mouse intracranial glioblastoma models. Single cell RNA-sequencing of mouse intracranial glioblastomas treated with the MEK inhibitor selumetinib reveals distinct responses between mesenchymal-like (MES-like) and non MES-like subpopulations suggesting non-MES like cells are intrinsically resistant to MEK inhibition. Finally, single nuclear RNA-sequencing (snRNA-seq) of human NF1 mutant, CDKN2A/B deleted glioblastomas reveals MES-like tumor cells are associated with selumetinib sensitivity signatures while non MES-like cells exhibit increased cell cycle progression and lack selumetinib sensitivity, further supporting the notion that MEK inhibition specifically targets MES-like tumor cell subpopulations. Taken together, our data underscores the heterogeneity between and within somatic NF1 mutant glioblastomas and delineates mechanisms of MEK inhibitor response across distinct tumor subpopulations, guiding the development of future therapeutic strategies that may synergize with MEK inhibition for NF1 mutant tumors. The tumor suppressor NF1 is mutated in 15% of glioblastomas,1-3 the most common malignant brain tumor with poor outcomes and few effective treatments.4 NF1 is a GTPase activating protein (GAP) that negatively regulates Ras, and thus, NF1 loss leads to induction of Ras/RAF/MEK/ERK signaling, driving tumorigenesis and comprising a targetable molecular cascade.5,6 Genomic analysis of glioblastoma demonstrates NF1 mutation is associated with a mesenchymal-like (MES-like) transcriptomic tumor cell subpopulation and altered tumor microenvironment.7,8 More broadly, DNA methylation analysis reveals multiple epigenetic subgroups with overlapping relationships to transcriptomic subtype and DNA alterations, underscoring the complex relationship between genetic drivers and molecular signatures.9 While the updated 2021 Central Nervous System WHO tumor classification incorporates an ever increasing amount of molecular criteria for diffuse astrocytic tumors,10 the existence and clinical significance of molecular subgroups within somatic NF1 mutant, IDH-wildtype glioblastomas based on genetic co-mutations, epigenetic profile, or transcriptomic signatures remain unclear. Preclinical data support the utility of MEK inhibition in NF1 mutant gliomas,11,12 and the MEK inhibitor selumetinib is FDA approved for tumors arising in patients with syndromic neurofibromatosis type 1 (NF-1) harboring a germline NF1 mutation.13,14 In NF-1 associated gliomas, MEK inhibition demonstrates efficacy in a limited case series,15 and combined BRAF/MEK inhibition shows efficacy in BRAF p.V600E mutant gliomas,16 further supporting the translational potential of Ras/Raf/MEK/ERK blockade within genetically defined glioma subtypes. Nevertheless, treatment resistance to molecular monotherapy remains a challenge,17-20 and the mechanisms underlying MEK inhibitor resistance in NF1 mutant glioma are unknown. Here, we integrate targeted DNA sequencing, DNA methylation profiling, and single nuclear RNA-sequencing (snRNA-seq) of human patient somatic NF1 mutant, IDH-wildtype glioblastomas with single cell RNA-sequencing (scRNA-seq), genome-wide clustered regularly interspaced short palindromic repeats interference (CRISPRi) screens, and pharmacologic studies in cell lines and mouse intracranial glioblastoma models to define molecular subgroups and functional mediators of MEK inhibitor response. Targeted DNA sequencing of NF1 mutant, IDH-wildtype glioblastomas (n=186 tumors) revealed CDKN2A/B deletion was associated with poor outcomes in NF1 mutant, but not NF1 wildtype, glioblastomas. DNA methylation profiling (n=129 tumors) demonstrated three epigenetic subgroups with distinct clinical features, co- mutation patterns across cell cycle genes, and reference methylation classifier identities. Genome-wide CRISPRi screens in mouse SB28 and human GBM43 glioblastoma cells identified a conserved cell cycle gene network mediating cell growth, consistent with the clinical importance of additional hits affecting the cell cycle in human somatic NF1 mutant glioblastomas. Moreover, genome-wide mediators of selumetinib response converged upon two Ras pathway effectors mediating selumetinib sensitivity: BRAF and SHOC2. SHOC2 repression in glioblastoma cells significantly improved selumetinib response both in vitro and in intracranial allografts in vivo. Single cell RNA-sequencing (scRNA-seq) of mouse intracranial glioblastomas treated with the MEK inhibitor selumetinib revealed MES-like tumor cells correlated with CDKN2A retention and the CRISPRi screen selumetinib sensitivity signature, with selumetinib resistant cells displaying Ras pathway induction. In contrast, non-MES like tumor cells were CDKN2A deficient and lacked expression of the CRISPRi screen selumetinib sensitivity signature, with selumetinib resistant cells inducing a glial de-differentiation program. Finally, snRNA-seq of NF1 mutant, CDKN2A/B deleted, IDH-wildtype glioblastomas (n=9) showed non MES-like tumor cells exhibit increased cell cycle progression and were not associated with the CRISPRi screen selumetinib sensitivity signature. MES-like tumor cells within newly diagnosed, but not recurrent, tumors retained expression of the CRISPRi screen selumetinib sensitivity signature, suggesting resistance can arise both between and within specific transcriptomic glioblastoma cell tumor cell subpopulations. Taken together, our data identifies clinically important subgroups of NF1 mutant, IDH-wildtype glioblastomas and supports a model in which heterogeneity between tumors and within tumor cell subpopulations underlies MEK inhibitor response, supporting the need for additional synergistic therapeutic approaches beyond maximal Ras pathway blockade for NF1 mutant glioblastomas.

genomics↗

In vivo perturb-seq of cancer and immune cells dissects oncologic drivers and therapy response

Genetic perturbation screens with single cell readouts have enabled rich phenotyping of gene function and regulatory networks. These approaches have been challenging in vivo, especially in adult disease models such as cancer, which include mixtures of malignant and microenvironment cells. Glioblastoma (GBM) is a fatal cancer, and methods of systematically interrogating gene function and therapeutic targets in vivo, especially in combination with standard of care treatment such as radiotherapy, are lacking. Here, we iteratively develop a multiplex in vivo perturb-seq CRISPRi platform for single cell genetic screens in cancer and tumor microenvironment cells that leverages intracranial convection enhanced delivery (CED) of sgRNA libraries into models of GBM. Our platform enables potent silencing of drivers of in vivo growth and tumor maintenance, as well as genes that sensitize GBM to radiotherapy. We find radiotherapy rewires transcriptional responses to genetic perturbations in an in vivo dependent manner, revealing heterogenous patterns of treatment sensitization or resistance in GBM. Furthermore, we demonstrate targeting of genes that function in the tumor microenvironment, enabling alterations of ligand-receptor interactions between immune/stromal cells following in vivo CRISPRi perturbations. In sum, we demonstrate the utility of multiplexed perturb-seq for in vivo single cell dissection of adult cancer and normal tissue biology across multiple cell types in the context of therapeutic intervention, a platform with potential for broad application.

genomics↗

Granulin Loss of Function in Human Mature Brain Organoids Implicates Astrocytes in TDP-43 Pathology

Loss of function (LoF) of Tar-binding protein 43 (TDP-43) and mislocalization, together with TDP-43-positive and hyperphosphorylated inclusions, are found in postmortem tissue of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) patients, including those carrying LoF variants in the progranulin gene (GRN). Modelling TDP-43 pathology has been challenging in vivo and in vitro. We present a 3D-induced pluripotent stem cell (iPSC)-derived paradigm - mature brain organoids (mbOrg) - composed of cortical-like-astrocytes (iA) and neurons (iN). When devoid of GRN, mbOrgs spontaneously recapitulate TDP-43 mislocalization, hyperphosphorylation and LoF phenotypes. Mixing-and-matching genotypes in mbOrgs showed that GRN-/- iA are drivers for TDP-43 pathology. Finally, we rescued TDP-43 LoF by adding exogenous progranulin, demonstrating a link between TDP-43 LoF and progranulin expression. In conclusion, we present an iPSC-derived platform that shows striking features of human TDP-43 proteinopathy and provides a tool for mechanistic modelling of TDP-43 pathology and patient-tailored therapeutic screening for FTD and ALS. HighlightsO_LIGRN-/- iPSC-derived 3D paradigm (mbOrg) composed of mature cortical-like astrocytes and neurons recapitulates features of TDP-43 proteinopathy C_LIO_LIGRN-/- cortical-like astrocytes are necessary and sufficient for the development of the TDP-43 loss of function phenotype in mbOrg. C_LIO_LIA TDP-43 phenotype can be rescued in neurons by treating neuron and astrocyte co-cultures with progranulin full length protein. C_LI eTOC blurbIn this article, de Majo and colleagues present a novel 3D iPSC-derived model to study neurodegenerative disorders such as ALS and FTD. When devoid of GRN expression, these cultures present features of ALS and FTD associated pathology hardly ever observed in vitro. These phenotypes are shown to be primarily driven by diseased astrocytes and can be rescued by progranulin supplementation.

neuroscience↗

Symmetry breaking of hPSCs in micropattern generates a polarized spinal cord-like organoid (pSCO) with dorsoventral organization

Brain organoid research is advancing, but generation of organoids with proper axis formation, which could lead to spatially ordered structures for complex brain structure and function, still remains a challenge. Axis formation and related spatial cell organization in the CNS are initiated by the symmetry breaking during the early embryo development. It has been demonstrated that the geometrically confined culture of human pluripotent stem cells (hPSCs) can be used to induce symmetry breaking and regionalized cell differentiation. In this study, we generated a polarized spinal cord organoid with a self-organized dorsoventral (DV) organization, using 2D cell patterning by geometric confinement. Initially, the application of caudalization signals to hPSCs promoted the regionalized cell differentiation along the radial axis and sprouting-like protrusion morphogenesis in cell colonies confined to ECM protein micropatterns. Detachment of colonies turned them into extended spinal cord-like organoids which maintained center- and edge-derived two poles. Further analyses including single cell RNA sequencing and spatial transcriptome analysis unveiled that these organoids contained rich repertoire of developing spinal cord cells and exhibited the spatially ordered DV domain formation along the long axis without external organizing signals. Modulation of BMP and Shh signaling can control the extent of DV coverage in organoids following the principles of embryo patterning. Our study provides a simple, and precisely controllable method to generate spatially-ordered organoids for understanding of biological principles of cell patterning and axis formation during neural development.

developmental biology↗

Glioblastoma remodeling of neural circuits in the human brain decreases survival

Gliomas synaptically integrate into neural circuits. Prior work has demonstrated bidirectional interactions between neurons and glioma cells, with neuronal activity driving glioma growth and gliomas increasing neuronal excitability. In this study we wanted to know how glioma induced neuronal changes influence neural circuits underlying cognition and whether these interactions influence patient survival. We use intracranial brain recordings during lexical retrieval language tasks in awake humans in addition to site specific tumor tissue biopsies and cell biology experiments. We find that gliomas remodel functional neural circuitry such that task-relevant neural responses activate tumor-infiltrated cortex, beyond cortical excitation normally recruited in the healthy brain. Site-directed biopsies from functionally connected regions within the tumor are enriched for a glioblastoma subpopulation that exhibits a distinct synaptogenic and neuronotrophic phenotype. Tumor cells from functionally connected regions secrete the synaptogenic factor thrombospondin-1, which contributes to the differential neuron-glioma interactions observed in functionally connected tumor regions compared to tumor regions with less functional connectivity. The degree of functional connectivity between glioblastoma and the normal brain negatively impacts both patient survival and language task performance. These data demonstrate that high-grade gliomas functionally remodel neural circuits in the human brain, which both promotes tumor proliferation and impairs cognition.

cancer biology↗

Mono- and bi-allelic protein truncating variants in alpha-actinin 2 cause cardiomyopathy through distinct mechanisms

Alpha-actinin 2 (ACTN2) anchors actin within cardiac sarcomeres. The mechanisms linking ACTN2 mutations to myocardial disease phenotypes are unknown. Here, we characterize patients with novel ACTN2 mutations to reveal insights into the physiological function of ACTN2. Patient-derived iPSC-cardiomyocytes harboring ACTN2 protein-truncating variants were hypertrophic, displayed sarcomeric structural disarray, impaired contractility, and aberrant Ca2+-signaling. In heterozygous indel cells, the truncated protein incorporates into cardiac sarcomeres, leading to aberrant Z-disc structure. In homozygous stop-gain cells, affinity-purification mass spectrometry reveals an intricate ACTN2 interactome with sarcomere and sarcolemma-associated proteins. Loss of the C-terminus of ACTN2 disrupts interaction with ACTN1 and GJA1, two sarcolemma-associated proteins, that may lead to the clinical arrhythmic and relaxation defects. The causality of the stop-gain mutation was verified using CRISPR-Cas9 gene editing. Together, these data advance our understanding of the role of ACTN2 in the human heart and establish recessive inheritance of ACTN2 truncation as causative of disease.

genetics↗

Classifying drugs by their arrhythmogenic risk using machine learning

Abstract.An undesirable side effect of drugs are cardiac arrhythmias, in particular a condition called torsades de pointes. Current paradigms for drug safety evaluation are costly, lengthy, and conservative, and impede efficient drug development. Here we combine multiscale experiment and simulation, high-performance computing, and machine learning to create an easy-to-use risk assessment diagram to quickly and reliable stratify the pro-arrhythmic potential of new and existing drugs. We capitalize on recent developments in machine learning and integrate information across ten orders of magnitude in space and time to provide a holistic picture of the effects of drugs, either individually or in combination with other drugs. We show, both experimentally and computationally, that drug-induced arrhythmias are dominated by the interplay of two currents with opposing effects: the rapid delayed rectifier potassium current and the L-type calcium current. Using Gaussian process classification, we create a classifier that stratifies safe and arrhythmic domains for any combinations of these two currents. We demonstrate that our classifier correctly identifies the risk categories of 23 common drugs, exclusively on the basis of their concentrations at 50% current block. Our new risk assessment diagram explains under which conditions blocking the L-type calcium current can delay or even entirely suppress arrhythmogenic events. Using machine learning in drug safety evaluation can provide a more accurate and comprehensive mechanistic assessment of the pro-arrhythmic potential of new drugs. Our study shapes the way towards establishing science-based criteria to accelerate drug development, design safer drugs, and reduce heart rhythm disorders.

biophysics↗