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BACKGROUND: Advances in our understanding of the molecular biology of meningiomas have led to significant gains in the ability to predict patient prognosis and tumor recurrence and to identify novel targets for therapeutic design. Specifically, classification of meningiomas based on DNA methylation has greatly improved our ability to risk stratify patients, however new questions have arisen in terms of the underlying impact these DNA methylation signatures have on meningioma biology. METHODS: This study utilizes RNA-seq data from 486 meningioma samples corresponding to three meningioma DNA methylation groups (Merlin-intact, Immune-enriched, and Hypermitotic), followed by in vitro experiments utilizing human meningioma cell lines. RESULTS: We identify alterations in RNA splicing between meningioma DNA methylation groups including individual splicing events that correlate with Hypermitotic meningiomas and predict tumor recurrence and overall patient prognosis and compile a set of splicing events that can accurately predict DNA methylation classification based on RNA-seq data. Furthermore, we validate these events using RT-PCR in patient samples and meningioma cell lines. Additionally, we identify alterations in RNA binding proteins and splicing factors that lie upstream of RNA splicing events, including upregulation of SRSF1 in Hypermitotic meningiomas which we show drives alternative RNA splicing changes. Finally, we design splice switching antisense oligonucleotides to target RNA splicing changes in NASP and MFF observed in Hypermitotic meningiomas, providing a rationale for RNA-based therapeutic design. CONCLUSIONS: RNA splicing is an important driver of meningioma phenotypes that can be useful in prognosticating patients and as a potential exploit for therapeutic vulnerabilities.
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Proteína Forkhead Box M1 , Neoplasias Meníngeas , Meningioma , RNA Mensageiro , Proteínas de Ligação a RNA , Humanos , Proteínas de Ligação a RNA/genética , Proteínas de Ligação a RNA/metabolismo , RNA Mensageiro/metabolismo , RNA Mensageiro/genética , Proteína Forkhead Box M1/genética , Proteína Forkhead Box M1/metabolismo , Neoplasias Meníngeas/genética , Neoplasias Meníngeas/patologia , Neoplasias Meníngeas/metabolismo , Meningioma/genética , Meningioma/metabolismo , Meningioma/patologia , Estabilidade de RNA/genética , Regulação Neoplásica da Expressão GênicaRESUMO
Resistance of BRAF-mutant melanomas to targeted therapy arises from the ability of cells to enter a persister state, evade treatment with relative dormancy, and repopulate the tumor when reactivated. Using spatial transcriptomics in patient derived xenograft models, we capture clonal lineage evolution during treatment, finding the persister state to show increased oxidative phosphorylation, decreased proliferation, and increased invasive capacity, with central-to-peripheral gradients. Phylogenetic tracing identifies intrinsic- and acquired-resistance mechanisms (e.g. dual specific phosphatases, Reticulon-4, CDK2) and suggests specific temporal windows of potential therapeutic efficacy. Using deep learning to analyze histopathological slides, we find morphological features of specific cell states, demonstrating that juxtaposition of transcriptomics and histology data enables identification of phenotypically-distinct populations using imaging data alone. In summary, we define state change and lineage selection during melanoma treatment with spatiotemporal resolution, elucidating how choice and timing of therapeutic agents will impact the ability to eradicate resistant clones. Statement of Significance: Tumor evolution is accelerated by application of anti-cancer therapy, resulting in clonal expansions leading to dormancy and subsequently resistance, but the dynamics of this process are incompletely understood. Tracking clonal progression during treatment, we identify conserved, global transcriptional changes and local clone-clone and spatial patterns underlying the emergence of resistance.
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Three-dimensional (3D) organoid cultures are flexible systems to interrogate cellular growth, morphology, multicellular spatial architecture, and cellular interactions in response to treatment. However, computational methods for analysis of 3D organoids with sufficiently high-throughput and cellular resolution are needed. Here we report Cellos, an accurate, high-throughput pipeline for 3D organoid segmentation using classical algorithms and nuclear segmentation using a trained Stardist-3D convolutional neural network. To evaluate Cellos, we analyze ~100,000 organoids with ~2.35 million cells from multiple treatment experiments. Cellos segments dye-stained or fluorescently-labeled nuclei and accurately distinguishes distinct labeled cell populations within organoids. Cellos can recapitulate traditional luminescence-based drug response of cells with complex drug sensitivities, while also quantifying changes in organoid and nuclear morphologies caused by treatment as well as cell-cell spatial relationships that reflect ecological affinity. Cellos provides powerful tools to perform high-throughput analysis for pharmacological testing and biological investigation of organoids based on 3D imaging.
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Neoplasias , Humanos , Organoides , Proliferação de Células , Redes Neurais de ComputaçãoRESUMO
Aging is the greatest risk factor for breast cancer; however, how age-related cellular and molecular events impact cancer initiation is unknown. We investigate how aging rewires transcriptomic and epigenomic programs of mouse mammary glands at single cell resolution, yielding a comprehensive resource for aging and cancer biology. Aged epithelial cells exhibit epigenetic and transcriptional changes in metabolic, pro-inflammatory, or cancer-associated genes. Aged stromal cells downregulate fibroblast marker genes and upregulate markers of senescence and cancer-associated fibroblasts. Among immune cells, distinct T cell subsets (Gzmk+, memory CD4+, γδ) and M2-like macrophages expand with age. Spatial transcriptomics reveal co-localization of aged immune and epithelial cells in situ. Lastly, transcriptional signatures of aging mammary cells are found in human breast tumors, suggesting mechanistic links between aging and cancer. Together, these data uncover that epithelial, immune, and stromal cells shift in proportions and cell identity, potentially impacting cell plasticity, aged microenvironment, and neoplasia risk.
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Numerous factors regulate alternative splicing of human genes at a co-transcriptional level. However, how alternative splicing depends on the regulation of gene expression is poorly understood. We leveraged data from the Genotype-Tissue Expression (GTEx) project to show a significant association of gene expression and splicing for 6874 (4.9%) of 141,043 exons in 1106 (13.3%) of 8314 genes with substantially variable expression in ten GTEx tissues. About half of these exons demonstrate higher inclusion with higher gene expression, and half demonstrate higher exclusion, with the observed direction of coupling being highly consistent across different tissues and in external datasets. The exons differ with respect to sequence characteristics, enriched sequence motifs, RNA polymerase II binding, and inferred transcription rate of downstream introns. The exons were enriched for hundreds of isoform-specific Gene Ontology annotations, suggesting that the coupling of expression and alternative splicing described here may provide an important gene regulatory mechanism that might be used in a variety of biological contexts. In particular, higher inclusion exons could play an important role during cell division.
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Three-dimensional (3D) culture models, such as organoids, are flexible systems to interrogate cellular growth and morphology, multicellular spatial architecture, and cell interactions in response to drug treatment. However, new computational methods to segment and analyze 3D models at cellular resolution with sufficiently high throughput are needed to realize these possibilities. Here we report Cellos (Cell and Organoid Segmentation), an accurate, high throughput image analysis pipeline for 3D organoid and nuclear segmentation analysis. Cellos segments organoids in 3D using classical algorithms and segments nuclei using a Stardist-3D convolutional neural network which we trained on a manually annotated dataset of 3,862 cells from 36 organoids confocally imaged at 5 µm z-resolution. To evaluate the capabilities of Cellos we then analyzed 74,450 organoids with 1.65 million cells, from multiple experiments on triple negative breast cancer organoids containing clonal mixtures with complex cisplatin sensitivities. Cellos was able to accurately distinguish ratios of distinct fluorescently labelled cell populations in organoids, with ≤3% deviation from the seeding ratios in each well and was effective for both fluorescently labelled nuclei and independent DAPI stained datasets. Cellos was able to recapitulate traditional luminescence-based drug response quantifications by analyzing 3D images, including parallel analysis of multiple cancer clones in the same well. Moreover, Cellos was able to identify organoid and nuclear morphology feature changes associated with treatment. Finally, Cellos enables 3D analysis of cell spatial relationships, which we used to detect ecological affinity between cancer cells beyond what arises from local cell division or organoid composition. Cellos provides powerful tools to perform high throughput analysis for pharmacological testing and biological investigation of organoids based on 3D imaging.
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Age is among the main risk factors for cancer, and any cancer study in adults is faced with an aging tissue and organism. Yet, pre-clinical studies are carried out using young mice and are not able to address the impact of aging and associated comorbidities on disease biology and treatment outcomes. Here, we discuss the limitations of current mouse cancer models and suggest strategies for developing novel models to address these major gaps in knowledge and experimental approaches.
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Envelhecimento , Neoplasias , Animais , Camundongos , Neoplasias/genética , Modelos Animais de Doenças , Fatores de RiscoRESUMO
Dysregulated RNA splicing is a molecular feature that characterizes almost all tumour types. Cancer-associated splicing alterations arise from both recurrent mutations and altered expression of trans-acting factors governing splicing catalysis and regulation. Cancer-associated splicing dysregulation can promote tumorigenesis via diverse mechanisms, contributing to increased cell proliferation, decreased apoptosis, enhanced migration and metastatic potential, resistance to chemotherapy and evasion of immune surveillance. Recent studies have identified specific cancer-associated isoforms that play critical roles in cancer cell transformation and growth and demonstrated the therapeutic benefits of correcting or otherwise antagonizing such cancer-associated mRNA isoforms. Clinical-grade small molecules that modulate or inhibit RNA splicing have similarly been developed as promising anticancer therapeutics. Here, we review splicing alterations characteristic of cancer cell transcriptomes, dysregulated splicing's contributions to tumour initiation and progression, and existing and emerging approaches for targeting splicing for cancer therapy. Finally, we discuss the outstanding questions and challenges that must be addressed to translate these findings into the clinic.
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Processamento Alternativo , Neoplasias , Humanos , Splicing de RNA/genética , Neoplasias/tratamento farmacológico , Neoplasias/genética , Neoplasias/metabolismo , Isoformas de Proteínas/genética , Carcinogênese , Transformação Celular NeoplásicaRESUMO
MYC is dysregulated in >50% of cancers, but direct targeting of MYC has been clinically unsuccessful. Targeting downstream MYC effector pathways represents an attractive alternative. MYC regulates alternative mRNA splicing, but the mechanistic links between MYC and the splicing machinery in cancer remain underexplored. Here, we identify a network of co-expressed splicing factors (SF-modules) in MYC-active breast tumors. Of these, one is a pan-cancer SF-module correlating with MYC activity across 33 tumor types. In mammary cell models, MYC activation leads to co-upregulation of pan-cancer module SFs and to changes in >4,000 splicing events. In breast cancer organoids, co-overexpression of the pan-cancer SF-module induces MYC-regulated splicing events and increases organoid size and invasiveness, while knockdown decreases organoid size. Finally, we uncover a MYC-activity pan-cancer splicing signature correlating with survival across tumor types. Our findings provide insight into the mechanisms of MYC-regulated splicing and for the development of therapeutics for MYC-driven tumors.
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Neoplasias da Mama , Oncogenes , Feminino , Humanos , Neoplasias da Mama/genética , Neoplasias da Mama/patologia , Carcinogênese/genética , Proteínas Proto-Oncogênicas c-myc/genética , Splicing de RNA/genética , Fatores de Processamento de RNA/genéticaRESUMO
Tumors display widespread transcriptome alterations, but the full repertoire of isoform-level alternative splicing in cancer is unknown. We developed a long-read (LR) RNA sequencing and analytical platform that identifies and annotates full-length isoforms and infers tumor-specific splicing events. Application of this platform to breast cancer samples identifies thousands of previously unannotated isoforms; ~30% affect protein coding exons and are predicted to alter protein localization and function. We performed extensive cross-validation with -omics datasets to support transcription and translation of novel isoforms. We identified 3059 breast tumorspecific splicing events, including 35 that are significantly associated with patient survival. Of these, 21 are absent from GENCODE and 10 are enriched in specific breast cancer subtypes. Together, our results demonstrate the complexity, cancer subtype specificity, and clinical relevance of previously unidentified isoforms and splicing events in breast cancer that are only annotatable by LR-seq and provide a rich resource of immuno-oncology therapeutic targets.
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Neoplasias da Mama , Processamento Alternativo , Neoplasias da Mama/genética , Feminino , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Humanos , Isoformas de Proteínas/genética , Isoformas de Proteínas/metabolismo , Análise de Sequência de RNA/métodos , TranscriptomaRESUMO
Alternatively spliced RNA isoforms are a hallmark of tumors, but their nature, prevalence, and clinical implications in gastric cancer have not been comprehensively characterized. We systematically profiled the splicing landscape of 83 gastric tumors and matched normal mucosa, identifying and experimentally validating eight splicing events that can classify all gastric cancers into three subtypes: epithelial-splicing (EpiS), mesenchymal-splicing (MesS), and hybrid-splicing. These subtypes were associated with distinct molecular signatures and epithelial-mesenchymal transition markers. Subtype-specific splicing events were enriched in motifs for splicing factors RBM24 and ESRP1, which were upregulated in MesS and EpiS tumors, respectively. A simple classifier based only on RNA levels of RBM24 and ESRP1, which can be readily implemented in the clinic, was sufficient to distinguish gastric cancer subtypes and predict patient survival in multiple independent patient cohorts. Overall, this study provides insights into alternative splicing in gastric cancer and the potential clinical utility of splicing-based patient classification. SIGNIFICANCE: This study presents a comprehensive analysis of alternative splicing in the context of patient classification, molecular mechanisms, and prognosis in gastric cancer.
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Processamento Alternativo , Transição Epitelial-Mesenquimal/genética , Perfilação da Expressão Gênica/métodos , Regulação Neoplásica da Expressão Gênica , Neoplasias Gástricas/genética , Adulto , Idoso , Idoso de 80 Anos ou mais , Linhagem Celular Tumoral , Análise por Conglomerados , Feminino , Humanos , Estimativa de Kaplan-Meier , Masculino , Pessoa de Meia-Idade , Fatores de Processamento de RNA/genética , Proteínas de Ligação a RNA/genética , RNA-Seq/métodos , Reação em Cadeia da Polimerase Via Transcriptase Reversa , Neoplasias Gástricas/classificaçãoRESUMO
A robust breast cancer prevention strategy requires risk assessment biomarkers for early detection. We show that expression of ELF5, a transcription factor critical for normal mammary development, is downregulated in mammary luminal epithelia with age. DNA methylation of the ELF5 promoter is negatively correlated with expression in an age-dependent manner. Both ELF5 methylation and gene expression were used to build biological clocks to estimate chronological ages of mammary epithelia. ELF5 clock-based estimates of biological age in luminal epithelia from average-risk women were within three years of chronological age. Biological ages of breast epithelia from BRCA1 or BRCA2 mutation carriers, who were high risk for developing breast cancer, suggested they were accelerated by two decades relative to chronological age. The ELF5 DNA methylation clock had better performance at predicting biological age in luminal epithelial cells as compared with two other epigenetic clocks based on whole tissues. We propose that the changes in ELF5 expression or ELF5-proximal DNA methylation in luminal epithelia are emergent properties of at-risk breast tissue and constitute breast-specific biological clocks. PREVENTION RELEVANCE: ELF5 expression or DNA methylation level at the ELF5 promoter region can be used as breast-specific biological clocks to identify women at higher than average risk of breast cancer.
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Neoplasias da Mama/diagnóstico , Neoplasias da Mama/genética , Mama/metabolismo , Relógios Circadianos/genética , Proteínas de Ligação a DNA/genética , Fatores de Transcrição/genética , Adulto , Biomarcadores Tumorais/genética , Mama/patologia , Neoplasias da Mama/patologia , Transformação Celular Neoplásica , Células Cultivadas , Metilação de DNA , Proteínas de Ligação a DNA/metabolismo , Detecção Precoce de Câncer/métodos , Feminino , Regulação Neoplásica da Expressão Gênica , Predisposição Genética para Doença/genética , Testes Genéticos/métodos , Humanos , Pessoa de Meia-Idade , Especificidade de Órgãos/genética , Regiões Promotoras Genéticas , Fatores de Transcrição/metabolismoRESUMO
Alternative RNA splicing is a key step in gene expression that allows generation of numerous messenger RNA transcripts encoding proteins of varied functions from the same gene. It is thus a rich source of proteomic and functional diversity. Alterations in alternative RNA splicing are observed both during healthy aging and in a number of human diseases, several of which display premature aging phenotypes or increased incidence with age. Age-associated splicing alterations include differential splicing of genes associated with hallmarks of aging, as well as changes in the levels of core spliceosomal genes and regulatory splicing factors. Here, we review the current known links between alternative RNA splicing, its regulators, healthy biological aging, and diseases associated with aging or aging-like phenotypes. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA Processing > Splicing Regulation/Alternative Splicing.
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Envelhecimento Saudável , Processamento Alternativo , Humanos , Proteômica , Splicing de RNA , Spliceossomos/metabolismoRESUMO
The RNA isoform repertoire is regulated by splicing factor (SF) expression, and alterations in SF levels are associated with disease. SFs contain ultraconserved poison exon (PE) sequences that exhibit greater identity across species than nearby coding exons, but their physiological role and molecular regulation is incompletely understood. We show that PEs in serine-arginine-rich (SR) proteins, a family of 14 essential SFs, are differentially spliced during induced pluripotent stem cell (iPSC) differentiation and in tumors versus normal tissues. We uncover an extensive cross-regulatory network of SR proteins controlling their expression via alternative splicing coupled to nonsense-mediated decay. We define sequences that regulate PE inclusion and protein expression of the oncogenic SF TRA2ß using an RNA-targeting CRISPR screen. We demonstrate location dependency of RS domain activity on regulation of TRA2ß-PE using CRISPR artificial SFs. Finally, we develop splice-switching antisense oligonucleotides to reverse the increased skipping of TRA2ß-PE detected in breast tumors, altering breast cancer cell viability, proliferation, and migration.
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Neoplasias da Mama/patologia , Diferenciação Celular , Éxons , Síndromes Mielodisplásicas/patologia , Proteínas do Tecido Nervoso/metabolismo , Splicing de RNA , Fatores de Processamento de Serina-Arginina/metabolismo , Neoplasias da Mama/genética , Neoplasias da Mama/metabolismo , Feminino , Humanos , Síndromes Mielodisplásicas/genética , Síndromes Mielodisplásicas/metabolismo , Proteínas do Tecido Nervoso/genética , Isoformas de Proteínas , Fatores de Processamento de Serina-Arginina/genética , Células Tumorais CultivadasRESUMO
We present Hierarchical Bayesian Analysis of Differential Expression and ALternative Splicing (HBA-DEALS), which simultaneously characterizes differential expression and splicing in cohorts. HBA-DEALS attains state of the art or better performance for both expression and splicing and allows genes to be characterized as having differential gene expression, differential alternative splicing, both, or neither. HBA-DEALS analysis of GTEx data demonstrated sets of genes that show predominant DGE or DAST across multiple tissue types. These sets have pervasive differences with respect to gene structure, function, membership in protein complexes, and promoter architecture.
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Processamento Alternativo , Expressão Gênica , Modelos Biológicos , Análise de Sequência de RNA , Software , Teorema de BayesRESUMO
Misregulation of alternative splicing is a hallmark of human tumors, yet to what extent and how it contributes to malignancy are only beginning to be unraveled. Here, we define which members of the splicing factor SR and SR-like families contribute to breast cancer and uncover differences and redundancies in their targets and biological functions. We identify splicing factors frequently altered in human breast tumors and assay their oncogenic functions using breast organoid models. We demonstrate that not all splicing factors affect mammary tumorigenesis in MCF-10A cells. Specifically, the upregulation of SRSF4, SRSF6, or TRA2ß disrupts acinar morphogenesis and promotes cell proliferation and invasion in MCF-10A cells. By characterizing the targets of these oncogenic splicing factors, we identify shared spliced isoforms associated with well-established cancer hallmarks. Finally, we demonstrate that TRA2ß is regulated by the MYC oncogene, plays a role in metastasis maintenance in vivo, and its levels correlate with breast cancer patient survival.
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Neoplasias da Mama/genética , Fatores de Processamento de RNA/metabolismo , Splicing de RNA/genética , Neoplasias da Mama/patologia , Humanos , Metástase NeoplásicaRESUMO
Defects in alternative splicing are frequently found in human tumors and result either from mutations in splicing-regulatory elements of specific cancer genes or from changes in the regulatory splicing machinery. RNA splicing regulators have emerged as a new class of oncoproteins and tumor suppressors, and contribute to disease progression by modulating RNA isoforms involved in the hallmark cancer pathways. Thus, dysregulation of alternative RNA splicing is fundamental to cancer and provides a potentially rich source of novel therapeutic targets. Here, we review the alterations in splicing regulatory factors detected in human tumors, as well as the resulting alternatively spliced isoforms that impact cancer hallmarks, and discuss how they contribute to disease pathogenesis. RNA splicing is a highly regulated process and, as such, the regulators are themselves tightly regulated. Differential transcriptional and posttranscriptional regulation of splicing factors modulates their levels and activities in tumor cells. Furthermore, the composition of the tumor microenvironment can also influence which isoforms are expressed in a given cell type and impact drug responses. Finally, we summarize current efforts in targeting alternative splicing, including global splicing inhibition using small molecules blocking the spliceosome or splicing-factor-modifying enzymes, as well as splice-switching RNA-based therapeutics to modulate cancer-specific splicing isoforms. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA Processing > Splicing Regulation/Alternative Splicing.
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Processamento Alternativo/efeitos dos fármacos , Processamento Alternativo/genética , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Regulação Neoplásica da Expressão Gênica/genética , Neoplasias/tratamento farmacológico , Neoplasias/genética , Bibliotecas de Moléculas Pequenas/farmacologia , Humanos , Neoplasias/metabolismo , Bibliotecas de Moléculas Pequenas/química , Spliceossomos/efeitos dos fármacos , Spliceossomos/genética , Spliceossomos/metabolismoRESUMO
Tumor-associated alterations in RNA splicing result either from mutations in splicing-regulatory elements or changes in components of the splicing machinery. This review summarizes our current understanding of the role of splicing-factor alterations in human cancers. We describe splicing-factor alterations detected in human tumors and the resulting changes in splicing, highlighting cell-type-specific similarities and differences. We review the mechanisms of splicing-factor regulation in normal and cancer cells. Finally, we summarize recent efforts to develop novel cancer therapies, based on targeting either the oncogenic splicing events or their upstream splicing regulators.