Malignant peripheral nerve sheath tumors (MPNSTs) are sarcomas of Schwann cell lineage origin that occur sporadically or in association with the inherited syndrome neurofibromatosis type 1. To identify genetic drivers of MPNST development, we used the Sleeping Beauty (SB) transposon-based somatic mutagenesis system in mice with somatic loss of transformation-related protein p53 (Trp53) function and/or overexpression of human epidermal growth factor receptor (EGFR). Common insertion site (CIS) analysis of 269 neurofibromas and 106 MPNSTs identified 695 and 87 sites with a statistically significant number of recurrent transposon insertions, respectively. Comparison to human data sets identified new and known driver genes for MPNST formation at these sites. Pairwise co-occurrence analysis of CIS-associated genes identified many cooperating mutations that are enriched in Wnt/β-catenin, PI3K-AKT-mTOR and growth factor receptor signaling pathways. Lastly, we identified several new proto-oncogenes, including Foxr2 (encoding forkhead box R2), which we functionally validated as a proto-oncogene involved in MPNST maintenance.

Medulloblastoma and central nervous system primitive neuroectodermal tumors (CNS-PNET) are aggressive, poorly differentiated brain tumors with limited effective therapies. Using Sleeping Beauty (SB) transposon mutagenesis, we identified novel genetic drivers of medulloblastoma and CNS-PNET. Cross-species gene expression analyses classified SB-driven tumors into distinct medulloblastoma and CNS-PNET subgroups, indicating they resemble human Sonic hedgehog and group 3 and 4 medulloblastoma and CNS neuroblastoma with FOXR2 activation. This represents the first genetically induced mouse model of CNS-PNET and a rare model of group 3 and 4 medulloblastoma. We identified several putative proto-oncogenes including Arhgap36, Megf10, and Foxr2. Genetic manipulation of these genes demonstrated a robust impact on tumorigenesis in vitro and in vivo. We also determined that FOXR2 interacts with N-MYC, increases C-MYC protein stability, and activates FAK/SRC signaling. Altogether, our study identified several promising therapeutic targets in medulloblastoma and CNS-PNET. Significance: A transposon-induced mouse model identifies several novel genetic drivers and potential therapeutic targets in medulloblastoma and CNS-PNET.

Follicular lymphoma and diffuse large B-cell lymphoma (DLBCL) are the most common non-Hodgkin lymphomas distinguishable by unique mutations, chromosomal rearrangements, and gene expression patterns. Here, it is demonstrated that early B-cell progenitors express 2′,3′-cyclic-nucleotide 3′ phosphodiesterase (CNP) and that when targeted with Sleeping Beauty (SB) mutagenesis, Trp53R270H mutation or Pten loss gave rise to highly penetrant lymphoid diseases, predominantly follicular lymphoma and DLBCL. In efforts to identify the genetic drivers and signaling pathways that are functionally important in lymphomagenesis, SB transposon insertions were analyzed from splenomegaly specimens of SB-mutagenized mice (n = 23) and SB-mutagenized mice on a Trp53R270H background (n = 7) and identified 48 and 12 sites with statistically recurrent transposon insertion events, respectively. Comparison with human data sets revealed novel and known driver genes for B-cell development, disease, and signaling pathways: PI3K–AKT–mTOR, MAPK, NFκB, and B-cell receptor (BCR). Finally, functional data indicate that modulating Ras-responsive element-binding protein 1 (RREB1) expression in human DLBCL cell lines in vitro alters KRAS expression, signaling, and proliferation; thus, suggesting that this proto-oncogene is a common mechanism of RAS/MAPK hyperactivation in human DLBCL. Implications: A forward genetic screen identified new genetic drivers of human B-cell lymphoma and uncovered a RAS/MAPK–activating mechanism not previously appreciated in human lymphoid disease. Overall, these data support targeting the RAS/MAPK pathway as a viable therapeutic target in a subset of human patients with DLBCL.

We previously identified ZNF217 as an oncogenic driver of a subset of osteosarcomas using the Sleeping Beauty (SB) transposon system. Here, we followed up by investigating the genetic role of ZNF217 in osteosarcoma initiation and progression through the establishment of a novel genetically engineered mouse model, in vitro assays, orthotopic mouse studies, and paired these findings with preclinical studies using a small-molecule inhibitor. Throughout, we demonstrate that ZNF217 is coupled to numerous facets of osteosarcoma transformation, including proliferation, cell motility, and anchorage independent growth, and ultimately promoting osteosarcoma growth, progression, and metastasis in part through positive modulation of PI3K–AKT survival signaling. Pharmacologic blockade of AKT signaling with nucleoside analogue triciribine in ZNF217⁺ orthotopically injected osteosarcoma cell lines reduced tumor growth and metastasis. Our data demonstrate that triciribine treatment may be a relevant and efficacious therapeutic strategy for patients with osteosarcoma with ZNF217⁺ and p-AKT rich tumors. With the recent revitalization of triciribine for clinical studies in other solid cancers, our study provides a rationale for further evaluation preclinically with the purpose of clinical evaluation in patients with incurable, ZNF217⁺ osteosarcoma.

Voltage-sensitive potassium channels play an important role in controlling membrane potential and ionic homeostasis in the gut and have been implicated in gastrointestinal (GI) cancers. Through large-scale analysis of 897 patients with gastro-oesophageal adenocarcinomas (GOAs) coupled with in vitro models, we findKCNQfamily genes are mutated in ∼30% of patients, and play therapeutically targetable roles in GOA cancer growth.KCNQ1andKCNQ3mediate the WNT pathway and MYC to increase proliferation through resultant effects on cadherin junctions. This also highlights novel roles ofKCNQ3in non-excitable tissues. We also discover that activity of KCNQ3 sensitises cancer cells to existing potassium channel inhibitors and that inhibition of KCNQ activity reduces proliferation of GOA cancer cells. These findings reveal a novel and exploitable role of potassium channels in the advancement of human cancer, and highlight that supplemental treatments for GOAs may exist through KCNQ inhibitors.

Background: Breast cancers are heterogeneous in nature, including many molecular subtypes, each displaying varying characteristics in clinical outcomes as well as in responses to treatments. Subtyping requires absolute precision for the application of precision medicine; however, this is not an easy task, given the dimensionality as well as noise in miRNA expression profiles. Even though miRNAs display potential as a biological marker for subtyping breast cancers, feature selection and optimizing learning algorithms would help harness their potential as a diagnostic tool. Methods: We propose the Adaptive Hill Climbing Artificial Lemming Algorithm (AHALA), a hybrid optimization framework that integrates the global search capability of the Artificial Lemming Algorithm with an adaptive hill-climbing local search strategy. Low-variance filtering and differential gene expression analysis were first applied to reduce dimensionality and enhance biological relevance. AHALA was then used to optimize deep neural network hyperparameters for miRNA-based multi-class breast cancer subtype classification. The method was validated using TCGA breast cancer miRNA expression data and benchmarked against state-of-the-art optimization algorithms using the CEC2021 test suite. Results: AHALA had a high classification performance measure for each type of breast cancer with a mean accuracy of 95.74%, precision of 95.98%, recall of 95.74%, F1 measure of 95.74%, and AUC value of 0.9682. The new algorithm had superior convergence and significance compared with other optimization algorithms. Feature selection revealed miRNAs that belong to each subtype, such as hsa-miR-190b, hsa-miR-429, hsa-miR-505-3p, hsa-miR-3614-5p, and hsa-miR-935. Conclusions: The AHALA framework offers a potent and efficient method of performing miRNA-based subtyping of breast cancer that integrates global exploration and local search to its advantage. Its high level of classification, stability, and ability to identify biologically important biomarkers mark this method as promising.