Cell State Changes Research Articles

Capture at the ER-mitochondrial contacts licenses IP3 receptors to stimulate local Ca2+ transfer and oxidative metabolism

Endoplasmic reticulum-mitochondria contacts (ERMCs) are restructured in response to changes in cell state. While this restructuring has been implicated as a cause or consequence of pathology in numerous systems, the underlying molecular dynamics are poorly understood. Here, we show means to visualize the capture of motile IP3 receptors (IP3Rs) at ERMCs and document the immediate consequences for calcium signaling and metabolism. IP3Rs are of particular interest because their presence provides a scaffold for ERMCs that mediate local calcium signaling, and their function outside of ERMCs depends on their motility. Unexpectedly, in a cell model with little ERMC Ca2+ coupling, IP3Rs captured at mitochondria promptly mediate Ca2+ transfer, stimulating mitochondrial oxidative metabolism. The Ca2+ transfer does not require linkage with a pore-forming protein in the outer mitochondrial membrane. Thus, motile IP3Rs can traffic in and out of ERMCs, and, when ‘parked’, mediate calcium signal propagation to the mitochondria, creating a dynamic arrangement that supports local communication.

OS08.2.A Three layers of neuronal-like mechanisms driving brain tumor invasion

Abstract Background Glioblastoma are characterized by their infiltration into the whole brain. Membrane protrusions of glioma cells called tumor microtubes are subcellular structures contributing to glioma cell invasion. They are the anatomical building block to build a functional and therapy-resistant tumor cell network interconnected by tumor microtubes (TMs) that characterizes a glioblastoma cell subpopulation, while other subpopulations appear unconnected to other glioma cells. The biological role of glioblastoma cells lacking connections with each other remains unclear. Furthermore, how neurogliomal synapses influence this subpopulation is unclear. Material and Methods Time-lapse in vivo two-photon microscopy and single-cell RNA-sequencing are combined to characterize functional different subpopulations of glioblastoma cells. Intravital, augmented microscopy, three-dimensional calcium imaging, electrophysiology and volume electron microscopy are used to investigate the role of neuronal invasion mechanisms and the role of neurogliomal synapses for tumor microtube generation and dynamics. Results In-vivo imaging revealed that glioblastoma cells lacking connections to other tumor cells and astrocytes were the main subpopulation driving glioblastoma invasion invasion. These glioblastoma cells were characterised with single-cell RNA-sequencing. This revealed that this subpopulation is enriched for neuronal, neural progenitor-like, and non-mesenchymal-like cell states as previously described. Sparse regions enriched with such tumor-cell and astrocyte-unconnected, invasive glioblastoma cells evolve over time into regions with tumor-cell and astrocyte-connected, glioblastoma cell networks reflected by molecular cell state changes that are reflected in cell state changes in different regions of human glioblastoma. In addition, mechanisms of glioblastoma cell invasion resembled neuronal and neural progenitor patterns during brain development. Lastly, neuronal activity stimulated neurogliomal synapses and subsequently increased glioblastoma cell invasivieness by stimulating generation of new tumor microtubes and enhanced tumor microtube dynamics. Conclusion This study uncovers three novel layers of neuronal features driving glioblastoma cell invasion. We are able to connect molecular, cellular heterogeneity and functional glioblastoma cell states interlinking heterogeneity and dissemination of glioblastoma, two important hallmarks of this disease. Lastly, this study delineates a potential roadmap to clinical translation with the multidimensional characterisation of human glioblastoma.

Integrating temporal single-cell gene expression modalities for trajectory inference and disease prediction

BackgroundCurrent methods for analyzing single-cell datasets have relied primarily on static gene expression measurements to characterize the molecular state of individual cells. However, capturing temporal changes in cell state is crucial for the interpretation of dynamic phenotypes such as the cell cycle, development, or disease progression. RNA velocity infers the direction and speed of transcriptional changes in individual cells, yet it is unclear how these temporal gene expression modalities may be leveraged for predictive modeling of cellular dynamics.ResultsHere, we present the first task-oriented benchmarking study that investigates integration of temporal sequencing modalities for dynamic cell state prediction. We benchmark ten integration approaches on ten datasets spanning different biological contexts, sequencing technologies, and species. We find that integrated data more accurately infers biological trajectories and achieves increased performance on classifying cells according to perturbation and disease states. Furthermore, we show that simple concatenation of spliced and unspliced molecules performs consistently well on classification tasks and can be used over more memory intensive and computationally expensive methods.ConclusionsThis work illustrates how integrated temporal gene expression modalities may be leveraged for predicting cellular trajectories and sample-associated perturbation and disease phenotypes. Additionally, this study provides users with practical recommendations for task-specific integration of single-cell gene expression modalities.

Contrastive latent variable modeling with application to case-control sequencing experiments

High-throughput RNA-sequencing (RNA-seq) technologies are powerful tools for understanding cellular state. Often, it is of interest to quantify and to summarize changes in cell state that occur between experimental or biological conditions. Differential expression is typically assessed using univariate tests to measure genewise shifts in expression. However, these methods largely ignore changes in transcriptional correlation. Furthermore, there is a need to identify the low-dimensional structure of the gene expression shift to identify collections of genes that change between conditions. Here, we propose contrastive latent variable models designed for count data to create a richer portrait of differential expression in sequencing data. These models disentangle the sources of transcriptional variation in different conditions in the context of an explicit model of variation at baseline. Moreover, we develop a model-based hypothesis testing framework that can test for global and gene subset-specific changes in expression. We evaluate our model through extensive simulations and analyses with count-based gene expression data from perturbation and observational sequencing experiments. We find that our methods effectively summarize and quantify complex transcriptional changes in case-control experimental sequencing data.

Impact of Growth Conditions on Pseudomonas fluorescens Morphology Characterized by Atomic Force Microscopy.

This work is dedicated to the characterization by Atomic Force Microscopy (AFM) of Pseudomonas fluorescens, bacteria having high potential in biotechnology. They were first studied first in optimal conditions in terms of culture medium and temperature. AFM revealed a more-or-less elongated morphology with typical dimensions in the micrometer range, and an organization of the outer membrane characterized by the presence of long and randomly distributed ripples, which are likely related to the organization of lipopolysaccharides (LPS). The outer membrane also presents invaginations, some of them showing a reorganization of ripples, which could be the first sign of a bacterial stress response. In a second step, bacteria grown under unfavorable conditions were characterized. The choice of the medium appeared to be more critical in the case of the second generation of cells, the less adapted medium inducing not only changes in the membrane organization but also larger damages in bacteria. An increased growth temperature affected both the usual “swollen” morphology and the organization of the outer membrane. Here also, LPS likely contribute to membrane remodelling, which makes them potential markers to track cell state changes.

Cellular mechanisms of oligoclonal vascular smooth muscle cell expansion in cardiovascular disease.

Quiescent, differentiated adult vascular smooth muscle cells (VSMCs) can be induced to proliferate and switch phenotype. Such plasticity underlies blood vessel homeostasis and contributes to vascular disease development. Oligoclonal VSMC contribution is a hallmark of end-stage vascular disease. Here, we aim to understand cellular mechanisms underpinning generation of this VSMC oligoclonality. We investigate the dynamics of VSMC clone formation using confocal microscopy and single-cell transcriptomics in VSMC-lineage-traced animal models. We find that activation of medial VSMC proliferation occurs at low frequency after vascular injury and that only a subset of expanding clones migrate, which together drives formation of oligoclonal neointimal lesions. VSMC contribution in small atherosclerotic lesions is typically from one or two clones, similar to observations in mature lesions. Low frequency (<0.1%) of clonal VSMC proliferation is also observed in vitro. Single-cell RNA-sequencing revealed progressive cell state changes across a contiguous VSMC population at onset of injury-induced proliferation. Proliferating VSMCs mapped selectively to one of two distinct trajectories and were associated with cells showing extensive phenotypic switching. A proliferation-associated transitory state shared pronounced similarities with atypical SCA1+ VSMCs from uninjured mouse arteries and VSMCs in healthy human aorta. We show functionally that clonal expansion of SCA1+ VSMCs from healthy arteries occurs at higher rate and frequency compared with SCA1- cells. Our data suggest that activation of proliferation at low frequency is a general, cell-intrinsic feature of VSMCs. We show that rare VSMCs in healthy arteries display VSMC phenotypic switching akin to that observed in pathological vessel remodelling and that this is a conserved feature of mouse and human healthy arteries. The increased proliferation of modulated VSMCs from healthy arteries suggests that these cells respond more readily to disease-inducing cues and could drive oligoclonal VSMC expansion.

Lineage plasticity in prostate cancer depends on JAK/STAT inflammatory signaling.

Drug resistance in cancer is often linked to changes in tumor cell state or lineage, but the molecular mechanisms driving this plasticity remain unclear. Using murine organoid and genetically engineered mouse models, we investigated the causes of lineage plasticity in prostate cancer and its relationship to antiandrogen resistance. We found that plasticity initiates in an epithelial population defined by mixed luminal-basal phenotype and that it depends on increased Janus kinase (JAK) and fibroblast growth factor receptor (FGFR) activity. Organoid cultures from patients with castration-resistant disease harboring mixed-lineage cells reproduce the dependency observed in mice by up-regulating luminal gene expression upon JAK and FGFR inhibitor treatment. Single-cell analysis confirms the presence of mixed-lineage cells with increased JAK/STAT (signal transducer and activator of transcription) and FGFR signaling in a subset of patients with metastatic disease, with implications for stratifying patients for clinical trials.

Highlights from Recent Cancer Literature

Breaking Insights| August 03 2022 Highlights from Recent Cancer Literature Author & Article Information Online ISSN: 1538-7445 Print ISSN: 0008-5472 ©2022 American Association for Cancer Research2022American Association for Cancer Research Cancer Res (2022) 82 (15): 2659–2660. https://doi.org/10.1158/0008-5472.CAN-82-15-BI Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Cite Icon Cite Search Site Article Versions Icon Versions Version of Record August 3 2022 Citation Highlights from Recent Cancer Literature. Cancer Res 1 August 2022; 82 (15): 2659–2660. https://doi.org/10.1158/0008-5472.CAN-82-15-BI Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest Search Advanced Search As part of the Glioma Longitudinal Analysis (GLASS) Consortium aimed at understanding glioma evolution and therapeutic vulnerabilities, Varn and colleagues analyzed over 300 glioma patients wild-type or mutant for isocitrate dehydrogenase (IDH-wt and IDH-mut, respectively), with RNA and DNA sequencing data available at multiple time points. Longitudinally, the authors discovered that the IDH-wt gliomas switched from the classical subtype to the mesenchymal subtype, whereas IDH-mut gliomas remained proneural. Moreover, IDH-wt gliomas showed increases in oligodendrocytes, neural signaling pathways, and invasion. Whereas IDH-wt glioma typically present with CDKN2A deletions, IDH-mut tumors tended to acquire deletions in CDKN2A or amplifications of CCND2 at recurrence. Myeloid cells were also implicated in driving the mesenchymal subtype of glioma at recurrence, potentially through myeloid-tumor interactions such as those mediated by oncostatin M and its receptor. Expert Commentary: Diffuse gliomas undergo several changes in cell state and molecular... You do not currently have access to this content.

Non-synergy of PD-1 blockade with T-cell therapy in solid tumors

BackgroundCell therapy has shown promise in the treatment of certain solid tumors, but its efficacy may be limited by inhibition of therapeutic T cells by the programmed cell death protein-1...

Mapping Phenotypic Plasticity upon the Cancer Cell State Landscape Using Manifold Learning.

Phenotypic plasticity describes the ability of cancer cells to undergo dynamic, nongenetic cell state changes that amplify cancer heterogeneity to promote metastasis and therapy evasion. Thus, cancer cells occupy a continuous spectrum of phenotypic states connected by trajectories defining dynamic transitions upon a cancer cell state landscape. With technologies proliferating to systematically record molecular mechanisms at single-cell resolution, we illuminate manifold learning techniques as emerging computational tools to effectively model cell state dynamics in a way that mimics our understanding of the cell state landscape. We anticipate that "state-gating" therapies targeting phenotypic plasticity will limit cancer heterogeneity, metastasis, and therapy resistance. Nongenetic mechanisms underlying phenotypic plasticity have emerged as significant drivers of tumor heterogeneity, metastasis, and therapy resistance. Herein, we discuss new experimental and computational techniques to define phenotypic plasticity as a scaffold to guide accelerated progress in uncovering new vulnerabilities for therapeutic exploitation.

Emergence of Resistance to MTI-101 Selects for a MET Genotype and Phenotype in EGFR Driven PC-9 and PTEN Deleted H446 Lung Cancer Cell Lines.

Simple SummaryMTI-101 is a first-in-class novel cyclic peptide shown to have anti-tumor activity in both multiple myeloma and castrate-resistant prostate in vivo cancer models. These data suggest the potential for a broad spectrum of anti-cancer activity for this class of compounds. To further delineate determinants of sensitivity and resistance that were not dependent on oncogenic drivers, two isogenic drug-resistant cell lines were generated with chronic exposure to MTI-101 in a non-small cell lung cancer (NSCLC) PC-9 (EGFR driven) and a small cell lung cancer (SCLC) H446 (PTEN deleted and c-MYC amplified). Our data indicate that the chronic exposure of MTI-101 selects for a stable mesenchymal-to-epithelial (MET) genotype and phenotype in both PC-9 and H446 lung cancer cell lines.MTI-101 is a first-in-class cyclic peptide that kills cells via calcium overload in a caspase-independent manner. Understanding biomarkers of response is critical for positioning a novel therapeutic toward clinical development. Isogenic MTI-101-acquired drug-resistant lung cancer cell line systems (PC-9 and H446) coupled with differential RNA-SEQ analysis indicated that downregulated genes were enriched in the hallmark gene set for epithelial-to-mesenchymal transition (EMT) in both MTI-101-acquired resistant cell lines. The RNA-SEQ results were consistent with changes in the phenotype, including a decreased invasion in Matrigel and expression changes in EMT markers (E-cadherin, vimentin and Twist) at the protein level. Furthermore, in the EGFR-driven PC-9 cell line, selection for resistance towards MTI-101 resulted in collateral sensitivity toward EGFR inhibitors. MTI-101 treatment showed synergistic activity with the standard of care agents erlotinib, osimertinib and cisplatin when used in combination in PC-9 and H446 cells, respectively. Finally, in vivo data indicate that MTI-101 treatment selects for increased E-cadherin and decreased vimentin in H446, along with a decreased incident of bone metastasis in the PC-9 in vivo model. Together, these data indicate that chronic MTI-101 treatment can lead to a change in cell state that could potentially be leveraged therapeutically to reduce metastatic disease.

Single-cell analyses define a continuum of cell state and composition changes in the malignant transformation of polyps to colorectal cancer

To chart cell composition and cell state changes that occur during the transformation of healthy colon to precancerous adenomas to colorectal cancer (CRC), we generated single-cell chromatin accessibility profiles and single-cell transcriptomes from 1,000 to 10,000 cells per sample for 48 polyps, 27 normal tissues and 6 CRCs collected from patients with or without germline APC mutations. A large fraction of polyp and CRC cells exhibit a stem-like phenotype, and we define a continuum of epigenetic and transcriptional changes occurring in these stem-like cells as they progress from homeostasis to CRC. Advanced polyps contain increasing numbers of stem-like cells, regulatory T cells and a subtype of pre-cancer-associated fibroblasts. In the cancerous state, we observe T cell exhaustion, RUNX1-regulated cancer-associated fibroblasts and increasing accessibility associated with HNF4A motifs in epithelia. DNA methylation changes in sporadic CRC are strongly anti-correlated with accessibility changes along this continuum, further identifying regulatory markers for molecular staging of polyps.

Abstract 1600: Dose-dependent effects of interferon-gamma treatment on pancreatic ductal adenocarcinoma cell states

Abstract Interferon-gamma (IFNγ) is a canonical proinflammatory cytokine that has well-studied antitumor functions such as the upregulation of MHC Class I (MHC-I), increased Th1 development, macrophage activity, innate immune cell recruitment, and in tumor cells increased apoptosis, decreased angiogenesis and proliferation. However, IFNγ is also important in limiting tissue destruction due to inflammation, taking on an immunotolerant role and allowing cancer cells to evade immune surveillance. We previously identified an interferon response cell state across diverse cancer types, as defined by the relative expression of IFIT1, HLA-A, HLA-DRA, STAT1, and IRF1. The interferon response cell state is heterogeneously expressed in cancer cells and appears to function both by cancer cell extrinsic and intrinsic mechanisms. Several clinical trials have tested the efficacy of IFNγ as a therapeutic for immune system stimulation in patients with melanoma. However, these have failed to detect effective outcomes, and have even noted some pro-growth actions, perhaps consistent with IFNγ’s immunotolerant role in maintaining tissue homeostasis. We are interested in identifying cell populations that are vulnerable to the antitumor functions of IFNγ, as well as cell populations that may be susceptible to IFNγ’s pro-tumor actions. To test this, we treated a pancreatic ductal adenocarcinoma cell line with three doses of IFNγ in vitro every day for five days and analyzed expression of proteins associated with IFNγ signaling by flow cytometry each day. Distinct doses of IFNγ have been shown to affect varying degrees of antitumor and pro-tumor responses. For example, growth inhibition has been seen upon treatment with high dose IFNγ, while treatment with low dose IFNγ is consistent with increased metastatic capability such as increased resistance to cytotoxic lymphocytes and natural killer cells despite the upregulation of MHC-I. We thus treated cells with three doses of IFNγ: low, normal, and high. Preliminary results have shown a dose dependent effect of IFNγ including the upregulation of MHC-I and PDL1. Ongoing work includes identifying changes in cell states using single-cell RNA-sequencing to uncover how cancer cells respond to varying intensities of IFNγ exposure. Additionally, we are analyzing how release of IFNγ from cancer cells changes following treatment of IFNγ at different doses. This work will provide insight into the mechanisms by which cancer cells evade immune surveillance and how cell states can describe a tumor’s vulnerability to IFNγ’s antitumor and pro-tumor effects. Citation Format: Deborah A. Liberman, Dalia Barkley, Itai Yanai. Dose-dependent effects of interferon-gamma treatment on pancreatic ductal adenocarcinoma cell states [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1600.

Abstract 2146: A quantitative in vivo pharmacogenomics platform uncovers biomarkers of therapy response

Abstract Cancer is characterized by heterogeneous genetic alterations that drive changes in cell state that often impact responses to therapy. Recent successes in the development of therapies targeting oncogenes has dramatically improved cancer care for subsets of patients and generated a wave of interest in precision cancer medicines. However, efforts to broadly discover effective targeted therapies have been stymied by a limited understanding of how response to drugs is modulated by tumor genotype. Here, we describe an in vivo functional cancer pharmacogenomics (PGx) platform optimized for the discovery of genetic drivers of response to therapies. By ​​coupling somatic genome editing, DNA barcoding, next generation sequencing, and robust statistical methods with genetically engineered mouse models of human lung cancer, the effects of different candidate therapies can be precisely quantified across thousands of tumors of diverse tumor suppressor genotypes. These tumors are initiated de novo in the native microenvironmental context in mice with an intact adaptive immune system. To illustrate the translational value of our platform, we tested a standard-of-care chemotherapy combination of carboplatin and pemetrexed (carbo/pem) in mice with oncogenic KrasG12D-driven lung tumors with inactivation of 22 putative tumor suppressors. Treatment after 12 weeks of tumor growth for 3 weeks led to greater than 75% reduction in tumor sizes relative to vehicle controls. Surprisingly, although chemotherapy affects cell proliferation pathways rather than a defined genetic component, we identified a diverse spectrum of genotype-specific sensitivity and resistance to carbo/pem treatment in our model. We next determined the extent to which our empirical PGx data could predict human clinical outcomes by analyzing clinicogenomic data from &amp;gt;200 patients with KRAS mutant lung cancer who received combination chemotherapy treatment. Training a multivariate Cox proportional hazards (PH) model on overall survival from treatment initiation using our 22 cancer-associated genes as binary features in combination with baseline clinical data revealed a remarkable agreement between the Cox-PH coefficients and our empirical PGx data. Further analysis of the human survival data using multiple machine learning (ML) methods identified Random Survival Forests (RSF) as the top performing model. Importantly, using mouse empirical PGx data to rank genes for feature selection significantly improved the predictive power of the ML model. Together, these results demonstrate how leveraging our PGx platform together with human data within a machine learning framework may improve the prediction of patient clinical outcomes, and thus profoundly impact our ability to realize the promise of precision medicine. Citation Format: Michael Rosen, David Amar, Ian Winters, Hira Rizvi, Wensheng Nie, Gregory Wall, Dmitri Petrov, Monte Winslow, Charles Rudin, Joseph Juan. A quantitative in vivo pharmacogenomics platform uncovers biomarkers of therapy response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2146.

Abstract 3169: Inducible lineage tracing system for the identification of tumor-initiating cells

Abstract Purpose of study: We have developed a Tamoxifen (TAM)-inducible, Cre recombinase-dependent, STAT3 signaling-specific lentiviral lineage-tracing (LT) system to identify tumor-initiating cells (TICs), to probe their behaviors, and to identify candidate genetic vulnerabilities. Background: Metastasis and therapeutic resistance are a major clinical challenge, responsible for the vast majority of cancer deaths. A subpopulation of tumor cells known to have intrinsic resistance to standard therapies and contribute to metastasis function as “cancer stem”, or tumor-initiating, cells (TICs). Enriched populations of TICs are typically identified by markers such as aldehyde dehydrogenase activity, the cell surface marker combination of CD44+/CD24-, or fluorescent reporters for signaling pathways that regulate TIC function such as STAT3. Despite their utility, TIC markers and reporters have limitations. Marker expression can be unstable and there is no established method to lineage trace long-lived TICs or to follow them as they undergo cell state changes. Methods: To augment existing TIC reporters, we developed a two component TAM-inducible, Cre recombinase-dependent, STAT3 signaling-specific lentiviral LT system. The first component is a vector that labels cells with active STAT3 signaling (EGFP+), followed by a self-cleaving peptide and TAM-inducible Cre-recombinase (4M67-EGFP-P2A-CreERT2). The second component is a constitutively expressed dual-color switching Cre-dependent reporter vector (EFS-loxPdsRedloxP-mNeptune2). Addition of TAM drives color switching from dsRed to mNeptune2 via CreERT2 recombination in STAT3 signaling cells. Both lentiviral vectors were constructed using Gateway® Cloning. Sum159 cells were transduced with the LT system and reporter activity was validated both in vitro and in vivo using confocal microscopy and flow cytometry. Four LT cell populations (EGFP+/mNeptune2+, EGFP+/dsRed+, EGFP-/mNeptune2+, and EGFP-/dsRed+) were enriched using fluorescence activated cell sorting, then analyzed by single cell RNA sequencing (scRNA seq). Results: Our results confirm the STAT3 LT reporter identifies STAT3 signaling cells (EGFP+), which can be labelled (mNeptune2+) upon addition of TAM. We conducted a TAM dose response curve to identify the optimal TAM dose for complete and partial labeling of STAT3 signaling cells. scRNA seq uncovered gene expression patterns within the TIC compartment and revealed similarities and differences in gene expression between the TIC compartment and the remaining LT reporter populations. Conclusions: These data demonstrate our LT system is a powerful tool that can be applied to uncover the role of TICs in metastasis and therapeutic resistance, as well as identify genetic vulnerabilities to specifically target TICs. Citation Format: Eric P. Souto, Michael T. Lewis. Inducible lineage tracing system for the identification of tumor-initiating cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3169.

Abstract 6215: The immune cell atlas of human neuroblastoma

Abstract Our current knowledge of the different immune cells in neuroblastoma is based on in vitro and in vivo studies mainly focusing on a single cell type. Different studies have conveyed conflicting results and despite the use of anti-GD2 immunotherapy in the clinic, a comprehensive immune cell overview at the single-cell level is still missing and understanding the complete composition of immune cells neuroblastoma will be crucial for the development of novel immunotherapeutics against the disease. In this study, we performed single-cell RNA-sequencing on human neuroblastoma coupled with multiplex immunohistochemistry and survival analysis to provide a complete cellular and molecular immune cell landscape of human neuroblastoma. Further, we contrasted the neuroblastoma data with single-cell RNA-sequencing data from normal fetal adrenal gland to characterize cell-state changes from normal tissue to neuroblastoma. Our analysis revealed 27 immune cell subtypes including distinct subpopulations of myeloid, NK, B and T cells that were associated with a survival benefit. Multiple subtypes of B and NK cells, not seen in neuroblastoma before, were identified. We propose the presence of tertiary lymphoid structures and showed that Active NK cells correlated with improved survival. In contrast to adult cancers, we detected no difference in cytotoxicity and exhaustion score for cytotoxic T cells, nor Treg activity. However, we demonstrated an increase in inflammatory monocyte signature score from normal to tumor derived myeloid cells. Finally, we performed receptor-ligand interaction analysis between tumor, stroma and immune cells, where we highlight several interactions that we suggest for future studies of how to exploit immune cells as a therapeutic option in neuroblastoma. Our findings significantly broaden the understanding of the immune composition in neuroblastoma and provides a resource for the development of novel immunotherapeutics. Citation Format: Bronte Manouk Verhoeven, Shenglin Mei, Thale K. Olsen, Karin K. Gustafsson, Anders Valind, Axel Lindström, David G. Nord, Shahrzad S. Fard, Catharina Hagerling, Peter V. Kharchenko, Per Kogner, John I. Johnsen, Ninib Baryawno. The immune cell atlas of human neuroblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6215.

Abstract 6053: Characterizing plasticity of chemotherapy-tolerant persister cells in rhabdomyosarcoma

Abstract Rhabdomyosarcoma (RMS) is a rare pediatric soft tissue sarcoma (250-300 cases a year in the US). The prognosis for patients with relapsed and metastatic disease remains poor with less than 30% overall survival rate. Current treatment regimens are ineffective against relapsed disease of RMS. There remains the urgent to need to identify more effective therapy options. While some studies have demonstrated up-regulation of multi-drug resistance genes and abnormal activity of selected signaling pathways in chemotherapy-resistant RMS tumors, the cellular and molecular mechanisms underlying adaptive cell changes leading to persistent survival of treatment-resistant RMS cells remain poorly understood. The stem cell-like tumor propagating cells (TPCs) have the capacity for self-renewal and are thought to be responsible for initiating treatment-resistant relapse and metastasis of some cancer types. The drug-tolerant persister (DTP) cell population with stem-cell like features has been shown in some cancer types to exhibit plasticity in cell state and dynamic changes in chromatin and transcriptional activity. A better understanding of how the cellular plasticity of the DTPs is regulated is critical for developing therapies to overcome treatment resistance in RMS. We have shown that initial treatment of RMS cells with standard-of-care cytotoxic agent, vincristine, selects for a DTP that is enriched with CD133+ stem-like cells. By gene expression studies, MYC and YBX1 driven-gene networks are upregulated in CD133+ cells. Targeted disruption of MYC and YBX1 by CRISPR/Cas9 reduces self-renewal capacity of RMS cells, and overexpression of MYC and YBX1 confers tolerance on RMS cells to vincristine. RMS cells treated in long-term culture with incremental increase in vincristine dose gives rise to late DTP with a distinct transcriptional profile including up-regulation of many genes regulated by the myogenic regulatory factor, MYOD1. MYC binds to the promoters of YBX1 and MYOD1. The findings suggest dynamic transcriptional changes and cell state plasticity of the DTPs in RMS. Our ongoing work includes characterizing the mechanisms by which MYC and MYOD1 regulate cell state plasticity and transcriptional adaptation of the DTP, assess inter- and intra-tumoral transcriptional heterogeneity of treatment-refractory RMS tumors and determine prognostic significance of functional network modules of MYC, MYOD and their downstream genes. Our ultimate goal is to translate our findings into more effective therapies for treatment-refractory RMS patients. Citation Format: Weiliang Tang, Madeline Fritzke, Spencer Stinson, Eleanor Chen. Characterizing plasticity of chemotherapy-tolerant persister cells in rhabdomyosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6053.

EZH2 endorses cell plasticity to non-small cell lung cancer cells facilitating mesenchymal to epithelial transition and tumour colonization.

Reversible transition between the epithelial and mesenchymal states are key aspects of carcinoma cell dissemination and the metastatic disease, and thus, characterizing the molecular basis of the epithelial to mesenchymal transition (EMT) is crucial to find druggable targets and more effective therapeutic approaches in cancer. Emerging studies suggest that epigenetic regulators might endorse cancer cells with the cell plasticity required to conduct dynamic changes in cell state during EMT. However, epigenetic mechanisms involved remain mostly unknown. Polycomb Repressive Complexes (PRCs) proteins are well-established epigenetic regulators of development and stem cell differentiation, but their role in different cancer systems is inconsistent and sometimes paradoxical. In this study, we have analysed the role of the PRC2 protein EZH2 in lung carcinoma cells. We found that besides its described role in CDKN2A-dependent cell proliferation, EZH2 upholds the epithelial state of cancer cells by repressing the transcription of hundreds of mesenchymal genes. Chemical inhibition or genetic removal of EZH2 promotes the residence of cancer cells in the mesenchymal state during reversible epithelial-mesenchymal transition. In fitting, analysis of human patient samples and tumour xenograft models indicate that EZH2 is required to efficiently repress mesenchymal genes and facilitate tumour colonization in vivo. Overall, this study discloses a novel role of PRC2 as a master regulator of EMT in carcinoma cells. This finding has important implications for the design of therapies based on EZH2 inhibitors in human cancer patients.

MEDB-73. Lipid metabolism as a therapeutic vulnerability in BET inhibitor-resistant medulloblastoma

MYC-driven medulloblastomas are a particularly devastating group of pediatric brain tumors that exhibit resistance and continued progression despite standard of care treatments. Our preclinical work identified BET-bromodomain inhibitors as a potentially promising new class of drugs for children with medulloblastoma and other MYC-driven cancers, providing rationale to evaluate these agents in clinical trials. However, treatment with BET inhibitor (BETi) alone is unlikely to be sufficient to cure, with most tumors evolving to acquire resistance to single-agent targeted therapies. We applied an integrative genomics approach to identify genes and pathways mediating BETi response in medulloblastoma. These studies revealed that MYC-driven medulloblastoma cells with acquired resistance to BETi reinstate transcription of essential genes suppressed by drug and exhibit changes in cell state and new vulnerabilities not present in drug-sensitive cells. We now have a growing body of evidence showing that BET inhibition downregulates the expression of key lipid metabolism genes and metabolism-related signaling pathways, and that medulloblastoma cells with adaptive resistance to drug differentially express and exhibit preferential dependency on specific lipid metabolic genes and transcriptional regulators. Our studies explore the possibility of exploiting these metabolic vulnerabilities to overcome BETi resistance and provide a more efficacious upfront therapy.

DIPG-54. p53 pathway reactivation as a therapeutic strategy in diffuse intrinsic pontine glioma

TP53 is the most frequently mutated tumor suppressor with somatic alterations found in approximately 50% of all human cancers. In the remaining TP53 wild-type (WT) tumors, functional inactivation of the p53 pathway may be achieved through a variety of other mechanisms, including gene deletion, epigenetic silencing, and/or alterations in prominent negative regulators, including MDM2/MDM4 and PPM1D. These alterations block p53 activity and lead to uncontrolled cell proliferation and oncogenesis in a majority of cancers, including the highly aggressive, universally fatal glial cell tumors of childhood, known as Diffuse Intrinsic Pontine Gliomas (DIPGs). DIPGs are inoperable due to their location within the brainstem. Available treatment options, including radiotherapy, have had a palliative effect at best, with almost all children succumbing to the disease within 18 months of diagnosis. Recent advances have led to an improved understanding of the biological underpinnings of this disease and identification of recurrent genetic alterations that represent potential therapeutic targets for these patients. Prominent among these targets in DIPGs with WT p53 status (50%) are MDM2/4 and PPM1D, whose suppression lead to p53 reactivation specifically in the WT p53 context. We have undertaken a combination of approaches to better understand the therapeutic potential of MDM2 and PPM1D inhibition in DIPG, characterizing the genomic, transcriptomic, and cell-state changes that drive resistance, and identifying novel vulnerabilities that can be exploited with combination therapies towards a cure.