Spatiotemporal profiling defines persistence and resistance dynamics during targeted treatment of melanoma.

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.

High-throughput deconvolution of 3D organoid dynamics at cellular resolution for cancer pharmacology with Cellos.

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.

Comprehensive single cell aging atlas of mammary tissues reveals shared epigenomic and transcriptomic signatures of aging and cancer.

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.

Cellos: High-throughput deconvolution of 3D organoid dynamics at cellular resolution for cancer pharmacology.

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.

Challenges and opportunities for modeling aging and cancer.

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.

RNA splicing dysregulation and the hallmarks of cancer.

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.

MYC regulates a pan-cancer network of co-expressed oncogenic splicing factors.

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.

A comprehensive long-read isoform analysis platform and sequencing resource for breast cancer.

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.

Comprehensive Analysis of Alternative Splicing in Gastric Cancer Identifies Epithelial-Mesenchymal Transition Subtypes Associated with Survival.

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.

Breast-Specific Molecular Clocks Comprised of ELF5 Expression and Promoter Methylation Identify Individuals Susceptible to Cancer Initiation.

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.

Poison Exon Splicing Regulates a Coordinated Network of SR Protein Expression during Differentiation and Tumorigenesis.

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.

Differential Functions of Splicing Factors in Mammary Transformation and Breast Cancer Metastasis.

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.

Alternative-splicing defects in cancer: Splicing regulators and their downstream targets, guiding the way to novel cancer therapeutics.

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.

Splicing-factor alterations in cancers.

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.

SRSF1-Regulated Alternative Splicing in Breast Cancer.

Splicing factor SRSF1 is upregulated in human breast tumors, and its overexpression promotes transformation of mammary cells. Using RNA-seq, we identified SRSF1-regulated alternative splicing (AS) targets in organotypic three-dimensional MCF-10A cell cultures that mimic a context relevant to breast cancer. We identified and validated hundreds of endogenous SRSF1-regulated AS events. De novo discovery of the SRSF1 binding motif reconciled discrepancies in previous motif analyses. Using a Bayesian model, we determined positional effects of SRSF1 binding on cassette exons: binding close to the 5' splice site generally promoted exon inclusion, whereas binding near the 3' splice site promoted either exon skipping or inclusion. Finally, we identified SRSF1-regulated AS events deregulated in human tumors; overexpressing one such isoform, exon-9-included CASC4, increased acinar size and proliferation, and decreased apoptosis, partially recapitulating SRSF1's oncogenic effects. Thus, we uncovered SRSF1 positive and negative regulatory mechanisms, and oncogenic AS events that represent potential targets for therapeutics development.

The spliceosome, a potential Achilles heel of MYC-driven tumors.

Alterations in RNA splicing are frequent in human tumors. Two recent studies of lymphoma and breast cancer have identified components of the spliceosome - the core splicing machinery - that are essential for malignant transformation driven by the transcription factor MYC. These findings provide a direct link between MYC and RNA splicing deregulation, and raise the exciting possibility of targeting spliceosome components in MYC-driven tumors.

BRCA2 deep intronic mutation causing activation of a cryptic exon: opening toward a new preventive therapeutic strategy.

PURPOSE: Diagnostic screening of the BRCA1/2 genes in breast cancer families is mostly done on genomic DNA. For families with a very strong family history and no mutation identified in the coding sequences or the exon-intron boundaries, BRCA1/2 transcripts' analysis is an efficient approach to uncover gene inversion and pre-mRNA splicing defaults missed by conventional DNA-based protocols. EXPERIMENTAL DESIGN: We analyzed RNA from patients of negative BRCA families by reverse transcriptase PCR and identified an insertion in one family that we characterized by sequencing and by using a minigene splicing assay. More than 2,000 additional BRCA1/2 negative families were subsequently screened for this mutation using a dedicated PCR approach. RESULTS: Nine families were found to harbor a BRCA2 mutant transcript containing a 95-nucleotide cryptic exon between exons 12 and 13. This cryptic exon results from a new mutation located deep into intron 12, c.6937+594T > G, which reinforces the strength of a preexisting 5' splice site, turning it into a perfect consensus sequence. It is systematically included in transcripts produced by the mutant allele in cells from mutation carriers or produced by a mutant splicing reporter minigene. The inclusion of the cryptic exon was prevented when we cotransfected the minigene with antisense oligonucleotides complementary to the 3' or mutated 5' splice sites. CONCLUSION: This first deep intronic BRCA mutation emphasizes the importance of analyzing RNA to provide comprehensive BRCA1/2 diagnostic tests and opens the possibility of using antisense therapy in the future as an alternative strategy for cancer prevention.

Oncogenic splicing factor SRSF1 is a critical transcriptional target of MYC.

The SR protein splicing factor SRSF1 is a potent proto-oncogene that is frequently upregulated in cancer. Here, we show that SRSF1 is a direct target of the transcription factor oncoprotein MYC. These two oncogenes are significantly coexpressed in lung carcinomas, and MYC knockdown downregulates SRSF1 expression in lung-cancer cell lines. MYC directly activates transcription of SRSF1 through two noncanonical E-boxes in its promoter. The resulting increase in SRSF1 protein is sufficient to modulate alternative splicing of a subset of transcripts. In particular, MYC induction leads to SRSF1-mediated alternative splicing of the signaling kinase MKNK2 and the transcription factor TEAD1. SRSF1 knockdown reduces MYC's oncogenic activity, decreasing proliferation and anchorage-independent growth. These results suggest a mechanism for SRSF1 upregulation in tumors with elevated MYC and identify SRSF1 as a critical MYC target that contributes to its oncogenic potential by enabling MYC to regulate the expression of specific protein isoforms through alternative splicing.

The splicing factor SRSF1 regulates apoptosis and proliferation to promote mammary epithelial cell transformation.

The splicing-factor oncoprotein SRSF1 (also known as SF2/ASF or ASF/SF2) is upregulated in breast cancers. We investigated the ability of SRSF1 to transform human and mouse mammary epithelial cells in vivo and in vitro. SRSF1-overexpressing COMMA-1D cells formed tumors, following orthotopic transplantation to reconstitute the mammary gland. In three-dimensional (3D) culture, SRSF1-overexpressing MCF-10A cells formed larger acini than control cells, reflecting increased proliferation and delayed apoptosis during acinar morphogenesis. These effects required the first RNA-recognition motif and nuclear functions of SRSF1. SRSF1 overexpression promoted alternative splicing of BIM (also known as BCL2L11) and BIN1 to produce isoforms that lack pro-apoptotic functions and contribute to the phenotype. Finally, SRSF1 cooperated specifically with MYC to transform mammary epithelial cells, in part by potentiating eIF4E activation, and these cooperating oncogenes are significantly coexpressed in human breast tumors. Thus, SRSF1 can promote breast cancer, and SRSF1 itself or its downstream effectors may be valuable targets for the development of therapeutics.

Comparison of nonsense-mediated mRNA decay efficiency in various murine tissues.

BACKGROUND: The Nonsense-Mediated mRNA Decay (NMD) pathway detects and degrades mRNAs containing premature termination codons, thereby preventing the accumulation of potentially detrimental truncated proteins. Intertissue variation in the efficiency of this mechanism has been suggested, which could have important implications for the understanding of genotype-phenotype correlations in various genetic disorders. However, compelling evidence in favour of this hypothesis is lacking. Here, we have explored this question by measuring the ratio of mutant versus wild-type Men1 transcripts in thirteen tissues from mice carrying a heterozygous truncating mutation in the ubiquitously expressed Men1 gene. RESULTS: Significant differences were found between two groups of tissues. The first group, which includes testis, ovary, brain and heart, displays a strong decrease of the nonsense transcript (average ratio of 18% of mutant versus wild-type Men1 transcripts, identical to the value measured in murine embryonic fibroblasts). The second group, comprising lung, intestine and thymus, shows much less pronounced NMD (average ratio of 35%). Importantly, the extent of degradation by NMD does not correlate with the expression level of eleven genes encoding proteins involved in NMD or with the expression level of the Men1 gene. CONCLUSION: Mouse models are an attractive option to evaluate the efficiency of NMD in multiple mammalian tissues and organs, given that it is much easier to obtain these from a mouse than from a single individual carrying a germline truncating mutation. In this study, we have uncovered in the thirteen different murine tissues that we examined up to a two-fold difference in NMD efficiency.