RBFOX2 deregulation promotes pancreatic cancer progression and metastasis through alternative splicing.

RNA splicing is an important biological process associated with cancer initiation and progression. However, the contribution of alternative splicing to pancreatic cancer (PDAC) development is not well understood. Here, we identify an enrichment of RNA binding proteins (RBPs) involved in splicing regulation linked to PDAC progression from a forward genetic screen using Sleeping Beauty insertional mutagenesis in a mouse model of pancreatic cancer. We demonstrate downregulation of RBFOX2, an RBP of the FOX family, promotes pancreatic cancer progression and liver metastasis. Specifically, we show RBFOX2 regulates exon splicing events in transcripts encoding proteins involved in cytoskeletal remodeling programs. These exons are differentially spliced in PDAC patients, with enhanced exon skipping in the classical subtype for several RBFOX2 targets. RBFOX2 mediated splicing of ABI1, encoding the Abelson-interactor 1 adapter protein, controls the abundance and localization of ABI1 protein isoforms in pancreatic cancer cells and promotes the relocalization of ABI1 from the cytoplasm to the periphery of migrating cells. Using splice-switching antisense oligonucleotides (AONs) we demonstrate the ABI1 ∆Ex9 isoform enhances cell migration. Together, our data identify a role for RBFOX2 in promoting PDAC progression through alternative splicing regulation.

Transposon mutagenesis identifies cooperating genetic drivers during keratinocyte transformation and cutaneous squamous cell carcinoma progression.

The systematic identification of genetic events driving cellular transformation and tumor progression in the absence of a highly recurrent oncogenic driver mutation is a challenge in cutaneous oncology. In cutaneous squamous cell carcinoma (cuSCC), the high UV-induced mutational burden poses a hurdle to achieve a complete molecular landscape of this disease. Here, we utilized the Sleeping Beauty transposon mutagenesis system to statistically define drivers of keratinocyte transformation and cuSCC progression in vivo in the absence of UV-IR, and identified both known tumor suppressor genes and novel oncogenic drivers of cuSCC. Functional analysis confirms an oncogenic role for the ZMIZ genes, and tumor suppressive roles for KMT2C, CREBBP and NCOA2, in the initiation or progression of human cuSCC. Taken together, our in vivo screen demonstrates an extremely heterogeneous genetic landscape of cuSCC initiation and progression, which can be harnessed to better understand skin oncogenic etiology and prioritize therapeutic candidates.

HNRNPM controls circRNA biogenesis and splicing fidelity to sustain cancer cell fitness.

High spliceosome activity is a dependency for cancer cells, making them more vulnerable to perturbation of the splicing machinery compared to normal cells. To identify splicing factors important for prostate cancer (PCa) fitness, we performed pooled shRNA screens in vitro and in vivo. Our screens identified heterogeneous nuclear ribonucleoprotein M (HNRNPM) as a regulator of PCa cell growth. RNA- and eCLIP-sequencing identified HNRNPM binding to transcripts of key homeostatic genes. HNRNPM binding to its targets prevents aberrant exon inclusion and backsplicing events. In both linear and circular mis-spliced transcripts, HNRNPM preferentially binds to GU-rich elements in long flanking proximal introns. Mimicry of HNRNPM-dependent linear-splicing events using splice-switching-antisense-oligonucleotides was sufficient to inhibit PCa cell growth. This suggests that PCa dependence on HNRNPM is likely a result of mis-splicing of key homeostatic coding and non-coding genes. Our results have further been confirmed in other solid tumors. Taken together, our data reveal a role for HNRNPM in supporting cancer cell fitness. Inhibition of HNRNPM activity is therefore a potential therapeutic strategy in suppressing growth of PCa and other solid tumors.

Promoterless Transposon Mutagenesis Drives Solid Cancers via Tumor Suppressor Inactivation.

A central challenge in cancer genomics is the systematic identification of single and cooperating tumor suppressor gene mutations driving cellular transformation and tumor progression in the absence of oncogenic driver mutation(s). Multiple in vitro and in vivo gene inactivation screens have enhanced our understanding of the tumor suppressor gene landscape in various cancers. However, these studies are limited to single or combination gene effects, specific organs, or require sensitizing mutations. In this study, we developed and utilized a Sleeping Beauty transposon mutagenesis system that functions only as a gene trap to exclusively inactivate tumor suppressor genes. Using whole body transposon mobilization in wild type mice, we observed that cumulative gene inactivation can drive tumorigenesis of solid cancers. We provide a quantitative landscape of the tumor suppressor genes inactivated in these cancers and show that, despite the absence of oncogenic drivers, these genes converge on key biological pathways and processes associated with cancer hallmarks.

SB Driver Analysis: a Sleeping Beauty cancer driver analysis framework for identifying and prioritizing experimentally actionable oncogenes and tumor suppressors.

Cancer driver prioritization for functional analysis of potential actionable therapeutic targets is a significant challenge. Meta-analyses of mutated genes across different human cancer types for driver prioritization has reaffirmed the role of major players in cancer, including KRAS, TP53 and EGFR, but has had limited success in prioritizing genes with non-recurrent mutations in specific cancer types. Sleeping Beauty (SB) insertional mutagenesis is a powerful experimental gene discovery framework to define driver genes in mouse models of human cancers. Meta-analyses of SB datasets across multiple tumor types is a potentially informative approach to prioritize drivers, and complements efforts in human cancers. Here, we report the development of SB Driver Analysis, an in-silico method for defining cancer driver genes that positively contribute to tumor initiation and progression from population-level SB insertion data sets. We demonstrate that SB Driver Analysis computationally prioritizes drivers and defines distinct driver classes from end-stage tumors that predict their putative functions during tumorigenesis. SB Driver Analysis greatly enhances our ability to analyze, interpret and prioritize drivers from SB cancer datasets and will continue to substantially increase our understanding of the genetic basis of cancer.

SBCDDB: Sleeping Beauty Cancer Driver Database for gene discovery in mouse models of human cancers.

Large-scale oncogenomic studies have identified few frequently mutated cancer drivers and hundreds of infrequently mutated drivers. Defining the biological context for rare driving events is fundamentally important to increasing our understanding of the druggable pathways in cancer. Sleeping Beauty (SB) insertional mutagenesis is a powerful gene discovery tool used to model human cancers in mice. Our lab and others have published a number of studies that identify cancer drivers from these models using various statistical and computational approaches. Here, we have integrated SB data from primary tumor models into an analysis and reporting framework, the Sleeping Beauty Cancer Driver DataBase (SBCDDB, http://sbcddb.moffitt.org), which identifies drivers in individual tumors or tumor populations. Unique to this effort, the SBCDDB utilizes a single, scalable, statistical analysis method that enables data to be grouped by different biological properties. This allows for SB drivers to be evaluated (and re-evaluated) under different contexts. The SBCDDB provides visual representations highlighting the spatial attributes of transposon mutagenesis and couples this functionality with analysis of gene sets, enabling users to interrogate relationships between drivers. The SBCDDB is a powerful resource for comparative oncogenomic analyses with human cancer genomics datasets for driver prioritization.

KRAS-related proteins in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a highly metastatic disease with a high mortality rate. Genetic and biochemical studies have shown that RAS signaling mediated by KRAS plays a pivotal role in disease initiation, progression and drug resistance. RAS signaling affects several cellular processes in PDAC, including cellular proliferation, migration, cellular metabolism and autophagy. 90% of pancreatic cancer patients harbor somatic oncogenic point mutations in KRAS, which lead to constitutive activation of the molecule. Pancreatic cancers lacking KRAS mutations show activation of RAS via upstream signaling through receptor mediated tyrosine kinases, like EGFR, and in a small fraction of patients, oncogenic activation of the downstream B-RAF molecule is detected. RAS-stimulated signaling of RAF/MEK/ERK, PI3K/AKT/mTOR and RalA/B is active in human pancreatic cancers, cancer cell lines and mouse models of PDAC, although activation levels of each signaling arm appear to be variable across different tumors and perhaps within different subclones of single tumors. Recently, several targeted therapies directed towards MEK, ERK, PI3K and mTOR have been assayed in pancreatic cancer cell lines and in mouse models of the disease with promising results for their ability to impede cellular growth or delay tumor formation, and several inhibitors are currently in clinical trials. However, therapy-induced cross activation of RAS effector molecules has elucidated the complexities of targeting RAS signaling. Combinatorial therapies are now being explored as an approach to overcome RAS-induced therapeutic resistance in pancreatic cancer.

Analyzing tumor heterogeneity and driver genes in single myeloid leukemia cells with SBCapSeq.

A central challenge in oncology is how to kill tumors containing heterogeneous cell populations defined by different combinations of mutated genes. Identifying these mutated genes and understanding how they cooperate requires single-cell analysis, but current single-cell analytic methods, such as PCR-based strategies or whole-exome sequencing, are biased, lack sequencing depth or are cost prohibitive. Transposon-based mutagenesis allows the identification of early cancer drivers, but current sequencing methods have limitations that prevent single-cell analysis. We report a liquid-phase, capture-based sequencing and bioinformatics pipeline, Sleeping Beauty (SB) capture hybridization sequencing (SBCapSeq), that facilitates sequencing of transposon insertion sites from single tumor cells in a SB mouse model of myeloid leukemia (ML). SBCapSeq analysis of just 26 cells from one tumor revealed the tumor's major clonal subpopulations, enabled detection of clonal insertion events not detected by other sequencing methods and led to the identification of dominant subclones, each containing a unique pair of interacting gene drivers along with three to six cooperating cancer genes with SB-driven expression changes.

Mutant p53 accumulates in cycling and proliferating cells in the normal tissues of p53 R172H mutant mice.

The tumour suppressor p53 is regulated primarily at the protein level. In normal tissues its levels are maintained at a very low level by the action of specific E3 ligases and the ubiquitin proteosome pathway. The mutant p53 protein contributes to transformation, metastasis and drug resistance. High levels of mutant p53 can be found in tumours and the accumulation of mutant p53 has previously been reported in pathologically normal cells in human skin. We show for the first time that similarly elevated levels of mutant p53 can be detected in apparently normal cells in a mutant p53 knock-in mouse model. In fact, in the small intestine, mutant p53 spontaneously accumulates in a manner dependent on gene dosage and cell type. Mutant p53 protein is regulated similarly to wild type p53, which can accumulate rapidly after induction by ionising radiation or Mdm2 inhibitors, however, the clearance of mutant p53 protein is much slower than wild type p53. The accumulation of the protein in the murine small intestine is limited to the cycling, crypt base columnar cells and proliferative zone and is lost as the cells differentiate and exit the cell cycle. Loss of Mdm2 results in even higher levels of p53 expression but p53 is still restricted to proliferating cells in the small intestine. Therefore, the small intestine of these p53 mutant mice is an experimental system in which we can dissect the molecular pathways leading to p53 accumulation, which has important implications for cancer prevention and therapy.

Sleeping Beauty mutagenesis: exploiting forward genetic screens for cancer gene discovery.

Sleeping Beauty (SB) is a powerful insertional mutagen used in somatic forward genetic screens to identify novel candidate cancer genes. In the past two years, SB has become widely adopted to model human pancreatic, hepatocellular, colorectal and neurological cancers to identify loci that participate in tumor initiation, progression and metastasis. Oncogenomic approaches have directly linked hundreds of genes identified by SB with human cancers, many with prognostic implications. These SB candidate cancer genes are aiding to prioritize punitive human cancer genes for follow-up studies and as possible biomarkers or therapeutic targets. This review highlights recent advances in SB cancer gene discovery, approaches to validate candidate cancer genes, and efforts to integrate SB data across all tumor types to prioritize drug development and tumor specificity.

Transposon insertional mutagenesis models of cancer.

Transposon-based insertional mutagenesis in the mouse provides a powerful approach for identifying new cancer genes. Transposon insertions in cancer genes are selected during tumor development because of their positive effect on tumor growth, and the transposon insertion sites in tumors thus serve as tags for identifying new cancer genes. Direct comparisons of transposon-mutated genes in mouse tumors with mutated genes in human tumors can lend insight into the genes and signaling pathways that drive tumorigenesis. This is critical for prioritizing genes for further study, either for their efficacy as biomarkers or drug targets. In this article, we will introduce DNA transposon-based systems used for gene discovery in mice and discuss their application to identify candidate cancer genes in light of recently published tumor studies.

Sleeping Beauty mutagenesis reveals cooperating mutations and pathways in pancreatic adenocarcinoma.

Pancreatic cancer is one of the most deadly cancers affecting the Western world. Because the disease is highly metastatic and difficult to diagnosis until late stages, the 5-y survival rate is around 5%. The identification of molecular cancer drivers is critical for furthering our understanding of the disease and development of improved diagnostic tools and therapeutics. We have conducted a mutagenic screen using Sleeping Beauty (SB) in mice to identify new candidate cancer genes in pancreatic cancer. By combining SB with an oncogenic Kras allele, we observed highly metastatic pancreatic adenocarcinomas. Using two independent statistical methods to identify loci commonly mutated by SB in these tumors, we identified 681 loci that comprise 543 candidate cancer genes (CCGs); 75 of these CCGs, including Mll3 and Ptk2, have known mutations in human pancreatic cancer. We identified point mutations in human pancreatic patient samples for another 11 CCGs, including Acvr2a and Map2k4. Importantly, 10% of the CCGs are involved in chromatin remodeling, including Arid4b, Kdm6a, and Nsd3, and all SB tumors have at least one mutated gene involved in this process; 20 CCGs, including Ctnnd1, Fbxo11, and Vgll4, are also significantly associated with poor patient survival. SB mutagenesis provides a rich resource of mutations in potential cancer drivers for cross-comparative analyses with ongoing sequencing efforts in human pancreatic adenocarcinoma.

Using targeted transgenic reporter mice to study promoter-specific p53 transcriptional activity.

The p53 transcription factor modulates gene expression programs that induce cell cycle arrest, senescence, or apoptosis, thereby preventing tumorigenesis. However, the mechanisms by which these fates are selected are unclear. Our objective is to understand p53 target gene selection and, thus, enable its optimal manipulation for cancer therapy. We have generated targeted transgenic reporter mice in which EGFP expression is driven by p53 transcriptional activity at a response element from either the p21 or Puma promoter, which induces cell cycle arrest/senescence and apoptosis, respectively. We demonstrate that we could monitor p53 activity in vitro and in vivo and detect variations in p53 activity depending on the response element, tissue type, and stimulus, thereby validating our reporter system and illustrating its utility for preclinical drug studies. Our results also show that the sequence of the p53 response element itself is sufficient to strongly influence p53 target gene selection. Finally, we use our reporter system to provide evidence for p53 transcriptional activity during early embryogenesis, showing that p53 is active as early as embryonic day 3.5 and that p53 activity becomes restricted to embryonic tissue by embryonic day 6.5. The data from this study demonstrate that these reporter mice could serve as powerful tools to answer questions related to basic biology of the p53 pathway, as well as cancer therapy and drug discovery.

Independent effects of APOE on cholesterol metabolism and brain Abeta levels in an Alzheimer disease mouse model.

The APOE epsilon4 allele is the most significant genetic risk factor associated with Alzheimer's disease to date. Epidemiological studies have demonstrated that inheritance of one or more epsilon4 alleles affects both the age of onset and the severity of pathology development. Dosage of APOE epsilon2 and epsilon3 alleles, however, appear to be protective against the effects of epsilon4. Although much of the biology of APOE in peripheral cholesterol metabolism is understood, its role in brain cholesterol metabolism and its impact on AD development is less defined. Several APOE transgenic models have been generated to study the effects of APOE alleles on APP processing and Abeta pathology. However, these models have potential limitations that confound our understanding of the effects of apolipoprotein E (APOE) levels and cholesterol metabolism on disease development. To circumvent these limitations, we have taken a genomic-based approach to better understand the relationship between APOE alleles, cholesterol and Abeta metabolism. We have characterized APOE knock-in mice, which express each human allele under the endogenous regulatory elements, on a defined C57BL6/J background. These mice have significantly different serum cholesterol levels and steady-state brain APOE levels, and yet have equivalent brain cholesterol levels. However, the presence of human APOE significantly increases brain Abeta levels in a genomic-based model of AD, irrespective of genotype. These data indicate an independent role for APOE in cholesterol metabolism in the periphery relative to the CNS, and that the altered levels of cholesterol and APOE in these mice are insufficient to influence Abeta metabolism in a mouse model of Alzheimer's disease.