Identifying functions and prognostic biomarkers of network motifs marked by diverse chromatin states in human cell lines.

Epigenetic modifications play critical roles in modulating gene expression, yet their roles in regulatory networks in human cell lines remain poorly characterized. We integrated multiomics data to construct directed regulatory networks with nodes and edges labeled with chromatin states in human cell lines. We observed extensive association of diverse chromatin states and network motifs. The gene expression analysis showed that diverse chromatin states of coherent type-1 feedforward loop (C1-FFL) and incoherent type-1 feedforward loops (I1-FFL) contributed to the dynamic expression patterns of targets. Notably, diverse chromatin state compositions could help C1- or I1-FFL to control a large number of distinct biological functions in human cell lines, such as four different types of chromatin state compositions cooperating with K562-associated C1-FFLs controlling "regulation of cytokinesis," "G1/S transition of mitotic cell cycle," "DNA recombination," and "telomere maintenance," respectively. Remarkably, we identified six chromatin state-marked C1-FFL instances (HCFC1-NFYA-ABL1, THAP1-USF1-BRCA2, ZNF263-USF1-UBA52, MYC-ATF1-UBA52, ELK1-EGR1-CCT4, and YY1-EGR1-INO80C) could act as prognostic biomarkers of acute myelogenous leukemia though influencing cancer-related biological functions, such as cell proliferation, telomere maintenance, and DNA recombination. Our results will provide novel insight for better understanding of chromatin state-mediated gene regulation and facilitate the identification of novel diagnostic and therapeutic biomarkers of human cancers.

Systemically identifying and prioritizing risk lncRNAs through integration of pan-cancer phenotype associations.

LncRNAs have emerged as a major class of regulatory molecules involved in normal cellular physiology and disease, our knowledge of lncRNAs is very limited and it has become a major research challenge in discovering novel disease-related lncRNAs in cancers. Based on the assumption that diverse diseases with similar phenotype associations show similar molecular mechanisms, we presented a pan-cancer network-based prioritization approach to systematically identify disease-specific risk lncRNAs by integrating disease phenotype associations. We applied this strategy to approximately 2800 tumor samples from 14 cancer types for prioritizing disease risk lncRNAs. Our approach yielded an average area under the ROC curve (AUC) of 80.66%, with the highest AUC (98.14%) for medulloblastoma. When evaluated using leave-one-out cross-validation (LOOCV) for prioritization of disease candidate genes, the average AUC score of 97.16% was achieved. Moreover, we demonstrated the robustness as well as the integrative importance of this approach, including disease phenotype associations, known disease genes and the numbers of cancer types. Taking glioblastoma multiforme as a case study, we identified a candidate lncRNA gene SNHG1 as a novel disease risk factor for disease diagnosis and prognosis. In summary, we provided a novel lncRNA prioritization approach by integrating pan-cancer phenotype associations that could help researchers better understand the important roles of lncRNAs in human cancers.

The novel kinase inhibitor ponatinib is an effective anti-angiogenic agent against neuroblastoma.

Background High-risk neuroblastoma has poor outcomes with high rates of relapse despite aggressive treatment, and novel therapies are needed to improve these outcomes. Ponatinib is a multi-tyrosine kinase inhibitor that targets many pathways implicated in neuroblastoma pathogenesis. We hypothesized that ponatinib would be effective against neuroblastoma in preclinical models. Methods We evaluated the effects of ponatinib on survival and migration of human neuroblastoma cells in vitro. Using orthotopic xenograft mouse models of human neuroblastoma, we analyzed tumors treated with ponatinib for growth, gross and histologic appearance, and vascularity. Results Ponatinib treatment of neuroblastoma cells resulted in decreased cell viability and migration in vitro. In mice with orthotopic xenograft neuroblastoma tumors, treatment with ponatinib resulted in decreased growth and vascularity. Conclusions Ponatinib reduces neuroblastoma cell viability in vitro and reduces tumor growth and vascularity in vivo. The antitumor effects of ponatinib suggest its potential as a novel therapeutic agent for neuroblastoma, and further preclinical testing is warranted.

Nifurtimox Is Effective Against Neural Tumor Cells and Is Synergistic with Buthionine Sulfoximine.

Children with aggressive neural tumors have poor survival rates and novel therapies are needed. Previous studies have identified nifurtimox and buthionine sulfoximine (BSO) as effective agents in children with neuroblastoma and medulloblastoma. We hypothesized that nifurtimox would be effective against other neural tumor cells and would be synergistic with BSO. We determined neural tumor cell viability before and after treatment with nifurtimox using MTT assays. Assays for DNA ladder formation and poly-ADP ribose polymerase (PARP) cleavage were performed to measure the induction of apoptosis after nifurtimox treatment. Inhibition of intracellular signaling was measured by Western blot analysis of treated and untreated cells. Tumor cells were then treated with combinations of nifurtimox and BSO and evaluated for viability using MTT assays. All neural tumor cell lines were sensitive to nifurtimox, and IC50 values ranged from approximately 20 to 210 µM. Nifurtimox treatment inhibited ERK phosphorylation and induced apoptosis in tumor cells. Furthermore, the combination of nifurtimox and BSO demonstrated significant synergistic efficacy in all tested cell lines. Additional preclinical and clinical studies of the combination of nifurtimox and BSO in patients with neural tumors are warranted.