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Withdrawal StatementThe authors have withdrawn this manuscript because they have prepared a new manuscript that includes only a portion of the data originally presented here. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.
Oligodendroglioma is a primary central nervous system tumor classified by the presence of isocitrate dehydrogenase (IDH) mutations and codeletion of 1p/19q. Here we describe the generation of an IDH-mutant 1p/19q-codeleted oligodendroglioma mouse model using in utero electroporation. We identified IDH1R132H, PIK3CAE545K, CicKO, Fubp1KO and Cdkn2aKO as the optimal combination (termed OligoCdkn2a) to drive fully penetrant tumors that histologically resemble human grade II/III IDH-mutant, 1p/19q-codeleted oligodendroglioma. Replacing Cdkn2a with Trp53 loss in this mouse model shifted tumor histology towards high grade astrocytoma. OligoCdkn2a tumors displayed metabolic and transcriptional changes associated with IDH and CIC mutations, and single cell sequencing identified a bias towards oligodendrocyte differentiation compared to an IDH wild-type glioblastoma mouse model. OligoCdkn2a tumors represent the first mouse model system to recapitulate the genetic, histological and transcriptional features of human IDH-mutant 1p/19q-codeleted oligodendrogliomas, offering a platform to further dissect tumor biology and test new therapeutic strategies.
Cutaneous squamous cell carcinoma (cSCC) represents a growing public health burden, with incidence projected to increase 23-29% over the coming decade. Topical immunoprevention strategies targeting the PD-L1/PD-1 and TLR4 axes have demonstrated preclinical efficacy, yet optimal intervention timing in humans remains undefined. To address this gap, single-cell RNA sequencing was performed on matched sun-protected (SP), sun-damaged (SD), and actinic keratosis (AK) biopsies from the same individuals, along with independent cSCC cases. Immune checkpoint and innate inflammatory signals were detectable as early as SD skin, prior to histologically confirmed dysplasia. Monotonically increasing expression of CD274 (PD-L1), CTLA4, PDCD1, CD27, and STAT1, alongside progressive TLR4-MYD88 innate immune signaling, was revealed through pseudobulk data analysis, with earliest upregulation at the SD stage. Fuzzy c-means trajectory clustering identified cell-typespecific programs across dendritic cells, macrophages, T cells, fibroblasts, endothelial cells, and keratinocytes. Dendritic cells shifted from early inflammatory antigen-presenting programs toward late PD-L1/IFN-regulatory states; macrophages showed monotonically increasing TLR4-associated myeloid activation; and T cells defined a "hot but exhausted" microenvironment in established cSCC. These findings identify SD and AK as biologically active stages for topical immunoprevention and provide a cellular roadmap for PD-L1/PD-1 and TLR4 blockade strategies.
Protein asparagine (N)-glycosylation, which promotes folding and trafficking of cell surface receptors such as the EGFR, has not been considered a viable target in oncology due to the essential and non-redundant enzymatic activities required for glycan synthesis and transfer. In mammals an exception to this rule is the presence of the oligosaccharyltransferase (OST) catalytic subunit paralogs, STT3A and STT3B. Here we delineate the chemical biology of OST inhibitors and develop an approach for limited inhibition of N-glycosylation optimized for downstream effects on EGFR. Small molecules with enhanced pharmacokinetic properties and preferences for STT3A or STT3B were synthesized, characterized in vitro, and advanced to in vivo testing. The lead from this series, NGI-189, causes tumor regression or growth delay of patient derived and TKI resistant EGFR-mutant lung cancer xenografts without toxicity. Together these results suggest that bioavailable OST inhibitors can be developed as therapeutic agents for oncology. SUMMARYA mechanistic approach for partial inhibition of N-glycosylation delivers small molecules with anti-tumor activity in EGFR mutant NSCLC.
BackgroundFollicular lymphoma (FL) is an incurable B-cell malignancy that constitutes a quarter of all lymphomas. Although RCHOP immuno-chemotherapy induces high rates of complete remission, almost all FL patients experience multiple relapses post-treatment. The limited understanding of treatment response heterogeneity is due to the absence of in vitro or in vivo experimental models, primarily because tumor cells heavily rely on their microenvironment to survive. In this study, we present an innovative xenograft model of primary FL cells in avian embryos, circumventing these limitations. MethodsWe developed the FL-AVI-PDX model by transplanting 20 biopsy FL samples, including good (n=11) and poor clinical responders (POD24, n=9), into chicken embryos. Each set of embryos was treated with RCHOP or vehicle intravenously. We evaluated the effect of immuno-chemotherapy on tumor volume by light sheet microscopy and on tumor biology by transcriptomic analysis at the single-cell level. ResultsWe successfully engrafted all samples in avian embryos. We found that RCHOP treatment in ovo led to tumor volume reduction, which predicted progression-free survival in multivariate analysis, demonstrating the models capacity to capture clinical heterogeneity at the patient level. The FL-AVI-PDX model also provided a unique opportunity to analyze the transcriptomic impact of RCHOP on FL cells using single-cell RNA sequencing. We identified a signature of 21 genes upregulated after RCHOP exposure, displaying significant intra-tumoral heterogeneity. As a proof of concept, we validated the functional involvement of BAX, a gene from the RCHOP-induced signature, as a critical effector of immuno- chemotherapy in vitro and in avian embryos. ConclusionsThe FL-AVI-PDX model is a platform for functional precision oncology in primary FL cells that captures both inter- and intra-patient heterogeneity of clinical response to a complex therapeutic regimen. It offers a unique opportunity to better understand FL biology, opening perspectives for the development of new drugs.
PurposeProton FLASH has been investigated using cyclotron and synchrocyclotron beamlines but not synchrotron beamlines. We evaluated the impact of dose rate (ultra-high [UHDR] vs. conventional [CONV]) and beam configuration (shoot-through [ST] vs. spread-out-Bragg-peak [SOBP]) on acute radiation-induced gastrointestinal toxicity (RIGIT) in mice. We also compared RIGIT between synchrotron-based protons and linac-based electrons with matched mean dose rates. Methods and MaterialsWe administered abdominal irradiation (12-14 Gy single fraction) to female C57BL/6J mice with an 87 MeV synchrotron-based proton beamline (2 cm diameter field size as a lateral beam). Dose rates were 0.2 Gy/s (S-T pCONV), 0.3 Gy/s (SOBP pCONV), 150 Gy/s (S-T pFLASH), and 230 Gy/s (SOBP pFLASH). RIGIT was assessed by the jejunal regenerating crypt assay and survival. We also compared responses to proton [pFLASH and pCONV] with responses to electron CONV (eCONV, 0.4 Gy/s) and electron FLASH (eFLASH, 188-205 Gy/s). ResultsThe number of regenerating jejunal crypts at each matched dose was lowest for pFLASH (similar between S-T and SOBP), greater and similar between pCONV (S-T and SOBP) and eCONV, and greatest for eFLASH. Correspondingly, mice that received pFLASH SOBP had the lowest survival rates (50% at 50 days), followed by pFLASH S-T (80%), and pCONV SOBP (90%), but 100% of mice receiving pCONV S-T survived (log-rank P = 0.047 for the four groups). ConclusionsOur findings are consistent with an increase in RIGIT after synchrotron-based pFLASH versus pCONV. This negative proton-specific FLASH effect versus linac-based electron irradiation underscores the importance of understanding the physical and biological factors that will allow safe and effective clinical translation.
Acute myeloid leukemia (AML) is a multi-clonal disease, existing as a milieu of clones with unique but related genotypes as initiating clones acquire subsequent mutations. However, bulk sequencing cannot fully capture AML clonal architecture or the clonal evolution that occurs as patients undergo therapy. To interrogate clonal evolution, we performed simultaneous single cell molecular profiling and immunophenotyping on 43 samples from 32 NPM1-mutant AML patients at different stages of disease. Here we show that diagnosis and relapsed AML samples display similar clonal architecture patterns, but signaling mutations can drive increased clonal diversity specifically at relapse. We uncovered unique genotype-immunophenotype relationships regardless of disease state, suggesting leukemic lineage trajectories can be hard-wired by the mutations present. Analysis of longitudinal samples from patients on therapy identified dynamic clonal, transcriptomic, and immunophenotypic changes. Our studies provide resolved understanding of leukemic clonal evolution and the relationships between genotype and cell state in leukemia biology.
Atypical chemokine receptor 3 (ACKR3), previously known as C-X-C chemokine receptor type 7 (CXCR7), has emerged as a key player in several biologic processes. Its atypical "intercepting receptor" signaling properties have established ACKR3 as the main regulator in pathophysiological processes in many diseases. However, much less is known the underlying mechanisms of ACKR3 in promoting tumorigenesis. We found, in both human and animal model, that activation of ACKR3 promotes colorectal tumorigenesis through the NOLC1-induced perturbations of rRNA biogenesis. As compared with adjacent non-neoplastic tissue, human colonic cancer tissues demonstrated higher expression of ACKR3, and high ACKR3 expression was associated with increased severity of colonic cancer. Villin-ACKR3 transgenic mice demonstrated the characteristics of ACKR3-induced colorectal cancer, showing the nuclear {beta}-arrestin-1-activated perturbation of rRNA biogenesis. Activation of ACKR3 induced nuclear translocation of {beta}-arrestin-1 ({beta}-arr1), leading to the interaction of {beta}-arr1 with nucleolar and coiled-body phosphoprotein 1 (NOLC1). As the highly phosphorylated protein in the nucleolus, NOLC1 further interacted with Fibrillarin, a highly conserved nucleolar methyltransferase responsible for ribosomal RNA methylation, leading to the increase of methylation in Histone H2A, resulting in the promotion of rRNA transcription of ribosome biogenesis. Conclusion: ACKR3 promotes colorectal tumorigenesis through the perturbation of rRNA biogenesis by nuclear {beta}-arr1-induced interaction of NOLC1 with Fibrillarin. HIGH LIGHTSO_LIACKR3 is an atypical G protein-coupled receptor (GPCR) C_LIO_LIACKR3 promotes colorectal tumorigenesis C_LIO_LIACKR3 induces nuclear translocation of {beta}-arr1 C_LIO_LINuclear {beta}-arr1 interacts with NOLC1 to activate Fibrillarin C_LIO_LIInteraction of NOLC1 to Fibrillarin leads to perturbation of rRNA biogenesis C_LI
An unmet clinical need in solid tumor cancers is the ability to harness the intrinsic spatial information in primary tumors that can be exploited to optimize prognostics, diagnostics and therapeutic strategies for precision medicine. We have developed a transformational spatial analytics (SpAn) computational and systems biology platform that predicts clinical outcomes and captures emergent spatial biology that can potentially inform therapeutic strategies. Here we apply SpAn to primary tumor tissue samples from a cohort of 432 chemo-naive colorectal cancer (CRC) patients iteratively labeled with a highly multiplexed (hyperplexed) panel of fifty-five fluorescently tagged antibodies. SpAn predicted the 5-year risk of CRC recurrence with a mean area under the ROC curve of 88.5% (SE of 0.1%), significantly better than current state-of-the-art methods. SpAn also inferred the emergent network biology of the tumor spatial domains revealing a synergistic role of known features from CRC consensus molecular subtypes that will enhance precision medicine.
Medulloblastoma is currently sub-classified into distinct DNA methylation subgroups/subtypes with particular clinico-molecular features. Using RNA-seq in large well annotated cohorts of medulloblastoma we show that transcriptionally Group3 and Group4 medulloblastomas exist not as discrete types but as intermediates on a bipolar continuum between archetypal Group3 and Group4 entities. Continuum position is prognostic, reflects propensity for specific DNA copy-number changes, key switches in isoform/enhancer usage and RNA-editing. Examining scRNA-seq profiles we show intra-tumoral transcriptional heterogeneity along the continuum is limited in a subtype-dependent manner. By integrating with a human scRNA-seq reference atlas we show this continuum is mirrored by an equivalent continuum of transcriptional cell types in early fetal cerebellar development. We identify unique developmental niches for all four major subgroups and link each to a common developmental antecedent. Our findings show a transcriptional continuum arising from oncogenic disruption of highly specific fetal cerebellar cell types, linked to almost every aspect of Group3/Group4 molecular biology and clinico-pathology.
Current knowledge in three-dimensional (3D) chromatin regulation in normal and disease states was mostly accumulated through Hi-C profiling in in vitro cell culture system. The limitations include failing to recapitulate disease-specific physiological properties and often lacking clinically relevant disease microenvironment. In this study, we conduct tissue-specific Hi-C profiling in a pilot cohort of 12 breast tissues comprising of two normal tissues (NTs) and ten ER+ breast tumor tissues (TTs) including five primary tumors (PTs), and five tamoxifen-treated recurrent tumors (RTs). We find largely preserved compartments, highly heterogeneous topological associated domains (TADs) and intensively variable chromatin loops among breast tumors, demonstrating 3D chromatin-regulated breast tumor heterogeneity. Further cross-examination identifies RT-specific looping-mediated biological pathways and suggests CA2, an enhancer-promoter looping (EPL)-mediated target gene within the bicarbonate transport metabolism pathway, might play a role in driving the tamoxifen resistance. Remarkably, the inhibition of CA2 not only impedes tumor growth both in vitro and in vivo, but also reverses chromatin looping. Our study thus yields significant mechanistic insights into the role and clinical relevance of 3D chromatin architecture in breast cancer endocrine resistance.
Novel preclinical models that better mimic the in vivo tumor microenvironment are needed for advanced understanding of tumor biology and resistance/response to therapy. Herein, we report development of a novel ex vivo patient-derived three-dimensional lung tumor model (3D-LTM), that maintains features of human extracellular matrix, cell-cell interactions, and tissue architecture to evaluate a rapid response to immune checkpoint inhibitors (ICI). Within this model system, we recapitulated the heterogeneity of response to immunotherapy observed in non-small cell lung cancer (NSCLC) patients and defined signatures associated with response for predicting early response of ICI in patients. Spatial transcriptomics of the 3D-LTMs identified positive correlation of CD8+ T cell populations, CD4+ memory T cells, mast cells, NK cells, endothelial cells and non-classical monocytes with response status, whereas macrophages negatively correlated with response status. Pathway analysis of gene expression showed that chemokine signaling related pathways were activated in responder 3D-LTM tissues, whereas suppression of antigen presentation-related pathways and activation of Treg differentiation-related pathways was associated with 3D-LTMs that were not considered responders. This model system has utility for rapid testing of novel immune directed therapy outcomes and for developing biomarkers of ICI response in NSCLC.
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers worldwide and further research on its biology is needed to fully understand the disease. Dysregulation of alternative RNA splicing is a common hallmark in cancer, including PDAC, which provides an emerging source of knowledge and of novel biomarkers and therapeutic tools. Here, we examined the role of EIF4A3, a core component of the Exon Junction Complex intimately linked to RNA splicing, in pancreatic cancer biology. EIF4A3 is overexpressed in PDAC tissue and associated to clinical parameters of malignancy and poorer patient survival. Mechanistically, exploration of PDAC RNA-seq data unveiled the link of EIF4A3 to diverse malignancy processes, in line with its association to key molecular pathways. Accordingly, EIF4A3 targeting in vitro decreased essential functional tumor features such as proliferation, migration, colony formation and sphere formation, while its in vivo targeting reduced tumor growth. EIF4A3 silencing in PDAC cell lines severely altered its transcriptional and spliceosomic landscapes, as shown by RNA-seq analyses, suggesting a role for EIF4A3 in maintaining RNA homeostasis. Our results indicate that EIF4A3 dysregulation in PDAC has a pleiotropic regulatory role on RNA biology, influencing key cellular functions. This paves the way to explore its potential as a novel biomarker and actionable target candidate for this lethal cancer.
Cysteine metabolism occurs across cellular compartments to support diverse biological functions and prevent the induction of ferroptosis. Though the disruption of cytosolic cysteine metabolism is implicated in this form of cell death, it is unknown whether the substantial cysteine metabolism resident within the mitochondria is similarly pertinent to ferroptosis. Here, we show that despite the rapid depletion of intracellular cysteine upon loss of extracellular cystine, cysteine-dependent synthesis of Fe-S clusters persists in the mitochondria of lung cancer cells. This promotes a retention of respiratory function and a maintenance of the mitochondrial redox state. Under these limiting conditions, we find that mitochondrial glutathione sustains the function of the Fe-S proteins critical to oxidative metabolism. This is achieved through CHAC1 catabolism of the cysteine-containing tripeptide within the mitochondrial matrix. We find that disrupting Fe-S cluster synthesis under cysteine restriction protects against the induction of ferroptosis, suggesting that the preservation of mitochondrial function is antagonistic to survival under starved conditions. Overall, our findings implicate mitochondrial cysteine metabolism in the induction of ferroptosis and reveal a novel mechanism of mitochondrial resilience in response to nutrient stress.
Spatial transcriptomics (ST) has revolutionized our understanding of tumor biology but inherently lacks information on the upstream somatic driver mutations. We developed a spatially-aware graph convolutional neural network (MuT-GCNN) that infers TP53 clones directly from ST data. MuT-GCNN was trained on virtual ST slides with clones simulated from a large collection of existing RNA and matched DNA sequencing data. The model is highly performant with precision and recall values exceeding 95% in most analysed cancer types. It is sensitive for single hit mutations and is primarily informed by the expression of p53 signalling genes in cancer cells. After demonstrating the potential of the model on publicly available squamous cell carcinoma (SCC) data, a direct validation was performed using ST and matched DNA sequencing from serial slices obtained from 4 cutaneous SCC samples. With the increasing availability of ST data and upcoming ST atlases, MuT-GCNN can unveil the location of (sub)clonal alterations in TP53, the most frequently mutated gene in human cancer.
Biological effectiveness in ion therapy varies with radiation quality and biological context, yet cancer cell response data acquired under well-characterized physical conditions remain limited. We investigated clonogenic survival and relative biological effectiveness (RBE) in PANC-1 and BxPC-3 pancreatic ductal adenocarcinoma (PDAC) cells irradiated at four positions along pristine 180.1 MeV proton and 352.4 MeV/u carbon ion Bragg curves, with 4 cm spread-out Bragg peak (SOBP) irradiation included as a clinically relevant comparison. Cell plane positioning and dose were verified in a water-tank system using an Advanced Markus ionization chamber, and Monte Carlo simulations using TOPAS provided dose-averaged linear energy transfer (LETD) and microdosimetric quantities. RBE was calculated relative to 200 kVp X-rays using the linear-quadratic survival model. Across the sampled pristine beam positions, spanning LETD values of approximately 1-9 keV/m for protons and 12-163 keV/m for carbon ions, RBE increased with LETD. Proton RBE10 exceeded the conventional clinical value of 1.1 at distal positions, whereas carbon ion RBE10 increased from 2.3 to 5.2 in PANC-1 and from 1.3 to 3.7 in BxPC-3, with larger differences between cell lines observed near the Bragg peak. SOBP measurements showed different biological responses across field conditions despite comparable LETD. These physically characterized survival data provide PDAC-relevant benchmarks for evaluating whether RBE models reproduce biological responses across pristine and SOBP irradiation conditions, supporting the future integration of radiation-quality-dependent effects into ion planning.
Recent advances in deep learning, particularly unsupervised approaches, have shown promise for furthering our biological knowledge through their application to gene expression datasets, though applications to epigenomic data are lacking. Here, we employ an unsupervised deep learning framework with variational autoencoders (VAEs) to learn latent representations of the DNA methylation landscape from three independent breast tumor datasets. Through interrogation of methylation-based learned latent dimension activation values, we demonstrate the feasibility of VAEs to track representative differential methylation patterns among clinical subtypes of tumors. CpGs whose methylation was most correlated VAE latent dimension activation values were significantly enriched for CpG sparse regulatory regions of the genome including enhancer regions. In addition, through comparison with LASSO, we show the utility of the VAE approach for revealing novel information about CpG DNA methylation patterns in breast cancer.
AO_SCPLOWBSTRACTC_SCPLOWRecent multiplexed protein imaging technologies characterize cells, their spatial organization, and interactions within microenvironments at an unprecedented resolution. Although observational data can reveal spatial associations, it does not allow users to infer salient biological relationships and cellular interactions. To address this challenge, we develop a generative model that allows users to test hypotheses about the effect of cell-cell interactions on protein expression through in silico perturbation. Our Cell-Cell Interaction GAN (CCIGAN) model employs a generative adversarial network (GAN) architecture to generate high fidelity synthetic multiplexed images from semantic cell segmentations. Our approach is unique in that it learns relationships between all imaging channels simultaneously and yields biological insights from multiple imaging technologies in silico, capturing known tumor-immune cell interactions missed by other state-of-the-art GAN models.