Mxi1 and mxi1-0 antagonize N-myc function and independently mediate apoptosis in neuroblastoma

Mxi1-0 Promotes Hypoxic Pulmonary Hypertension Via ERK/c-Myc-dependent Proliferation of Arterial Smooth Muscle Cells

Background: Hypoxic pulmonary hypertension (HPH) is a challenging lung arterial disorder with remarkably high incidence and mortality, and so far patients have failed to benefit from therapeutics clinically available. Max interacting protein 1–0 (Mxi1-0) is one of the functional isoforms of Mxi1. Although it also binds to Max, Mxi1-0, unlike other Mxi1 isoforms, cannot antagonize the oncoprotein c-Myc because of its unique proline rich domain (PRD). While Mxi1-0 was reported to promote cell proliferation via largely uncharacterized mechanisms, it is unknown whether and how it plays a role in the pathogenesis of HPH.

Methods: GEO database was used to screen for genes involved in HPH development, and the candidate players were validated through examination of gene expression in clinical HPH specimens. The effect of candidate gene knockdown or overexpression on cultured pulmonary arterial cells, e.g., pulmonary arterial smooth muscle cells (PASMCs), was then investigated. The signal pathway(s) underlying the regulatory role of the candidate gene in HPH pathogenesis was probed, and the outcome of targeting the aforementioned signaling was evaluated using an HPH rat model.

Results: Mxi1 was significantly upregulated in the PASMCs of HPH patients. As the main effector isoform responding to hypoxia, Mxi1-0 functions in HPH to promote PASMCs proliferation. Mechanistically, Mxi1-0 improved the expression of the proto-oncogene c-Myc via activation of the MEK/ERK pathway. Consistently, both a MEK inhibitor, PD98059, and a c-Myc inhibitor, 10058F4, could counteract Mxi1-0-induced PASMCs proliferation. In addition, targeting the MEK/ERK signaling significantly suppressed the development of HPH in rats.

Conclusion: Mxi1-0 potentiates HPH pathogenesis through MEK/ERK/c-Myc-mediated proliferation of PASMCs, suggesting its applicability in targeted treatment and prognostic assessment of clinical HPH.

Gene Expression Profiling to Delineate the Anticancer Potential of a New Alkaloid Isopicrinine From Rhazya stricta

Background:Rhazya stricta has been used as a folkloric medicinal herb for treating various diseases such as diabetes, inflammatory disorders, and sore throat. Several studies have revealed the potential of this plant as an important source of phytochemicals with anticancer properties. Objective: The present study was designed to isolate a novel anticancer compound from Rhazya stricta and elucidate its mechanism of action using genomics approach. Methods:Rhazya stricta leaves extract was prepared, and several alkaloids were purified and characterized. These alkaloids were screened for their anticancer potential. One of the alkaloids, termed as isopicrinine, showed efficient cytotoxicity against MCF7 breast cancer cell line and was selected for further analysis. RNA-Seq transcription profiling was conducted to identify the affected genes and cellular pathways in MCF7 cells after treatment with isopicrinine alkaloid. Results: In vitro studies revealed that newly identified isopicrinine alkaloid possess efficient anticancer activity. Exposure of MCF7 cells with isopicrinine affected the expression of various genes involved in p53 signaling pathway. One of the crucial proapoptotic genes, significantly upregulated in MCF7 after exposure to alkaloid, was PUMA (p53 upregulated modulator of apoptosis), which is involved in p53-dependent and -independent apoptosis. Moreover, exposure of sublethal dose of isopicrinine alkaloid in breast cancer cell line led to the downregulation of survivin, which is involved in negative regulation of apoptosis. Besides, several genes involved in mitosis and cell proliferation were significantly downregulated. Conclusion: In this article, we report the determination of a new alkaloid isopicrinine from the aerial parts of Rhazya stricta with anticancer property. This compound has the potential to be developed as a drug for curing cancer.

Unveiling MYCN regulatory networks in neuroblastoma via integrative analysis of heterogeneous genomics data

MYCN, an oncogenic transcription factor of the Myc family, is a major driver of neuroblastoma tumorigenesis. Due to the difficulty in drugging MYCN directly, revealing the molecules in MYCN regulatory networks will help to identify effective therapeutic targets for neuroblastoma therapy. Here we perform ChIP-sequencing and small RNA-sequencing of neuroblastoma cells to determine the MYCN-binding sites and MYCN-associated microRNAs, and integrate various types of genomic data to construct MYCN regulatory networks. The overall analysis indicated that MYCN-regulated genes were involved in a wide range of biological processes and could be used as signatures to identify poor-prognosis MYCN-non-amplified patients. Analysis of the MYCN binding sites showed that MYCN principally served as an activator. Using a computational approach, we identified 32 MYCN co-regulators, and some of these findings are supported by previous studies. Moreover, we investigated the interplay between MYCN transcriptional and microRNA post-transcriptional regulations and identified several microRNAs, such as miR-124-3p and miR-93-5p, which may significantly contribute to neuroblastoma pathogenesis. We also found MYCN and its regulated microRNAs acted together to repress the tumor suppressor genes. This work provides a comprehensive view of MYCN regulations for exploring therapeutic targets in neuroblastoma, as well as insights into the mechanism of neuroblastoma tumorigenesis.

Transcriptome analysis of hypoxic cancer cells uncovers intron retention in EIF2B5 as a mechanism to inhibit translation

Cells adjust to hypoxic stress within the tumor microenvironment by downregulating energy-consuming processes including translation. To delineate mechanisms of cellular adaptation to hypoxia, we performed RNA-Seq of normoxic and hypoxic head and neck cancer cells. These data revealed a significant down regulation of genes known to regulate RNA processing and splicing. Exon-level analyses classified > 1,000 mRNAs as alternatively spliced under hypoxia and uncovered a unique retained intron (RI) in the master regulator of translation initiation, EIF2B5. Notably, this intron was expressed in solid tumors in a stage-dependent manner. We investigated the biological consequence of this RI and demonstrate that its inclusion creates a premature termination codon (PTC), that leads to a 65kDa truncated protein isoform that opposes full-length eIF2Bε to inhibit global translation. Furthermore, expression of 65kDa eIF2Bε led to increased survival of head and neck cancer cells under hypoxia, providing evidence that this isoform enables cells to adapt to conditions of low oxygen. Additional work to uncover -cis and -trans regulators of EIF2B5 splicing identified several factors that influence intron retention in EIF2B5: a weak splicing potential at the RI, hypoxia-induced expression and binding of the splicing factor SRSF3, and increased binding of total and phospho-Ser2 RNA polymerase II specifically at the intron retained under hypoxia. Altogether, these data reveal differential splicing as a previously uncharacterized mode of translational control under hypoxia and are supported by a model in which hypoxia-induced changes to cotranscriptional processing lead to selective retention of a PTC-containing intron in EIF2B5.

A positive feedback loop between ROS and Mxi1-0 promotes hypoxia-induced VEGF expression in human hepatocellular carcinoma cells

VEGF expression induced by hypoxia plays a critical role in promoting tumor angiogenesis. However, the molecular mechanism that modulates VEGF expression under hypoxia is still poorly understood. In this study, we found that VEGF induction in hypoxic HepG2 cells is ROS-dependent. ROS mediates hypoxia-induced VEGF by upregulation of Mxi1-0. Furthermore, PI3K/AKT/HIF-1α signaling pathway is involved in ROS-mediated Mxi1-0 and VEGF expression in hypoxic HepG2 cells. Finally, Mxi1-0 could in turn regulate ROS generation in hypoxic HepG2 cells, creating a positive feedback loop. Taken together, this study demonstrate a positive regulatory feedback loop in which ROS mediates hypoxia-induced Mxi1-0 via activation of PI3K/AKT/HIF-1α pathway, events that in turn elevate ROS generation and promote hypoxia-induced VEGF expression. These findings could provide a rationale for designing new therapies based on inhibition of hepatocellular carcinoma (HCC) angiogenesis.

Integrating transcriptional and protein interaction networks to prioritize condition-specific master regulators

BACKGROUND

Genome-wide libraries of yeast deletion strains have been used to screen for genes that drive phenotypes such as stress response. A surprising observation emerging from these studies is that the genes with the largest changes in mRNA expression during a state transition are not those that drive that transition. Here, we show that integrating gene expression data with context-independent protein interaction networks can help prioritize master regulators that drive biological phenotypes.

RESULTS

Genes essential for survival had previously been shown to exhibit high centrality in protein interaction networks. However, the set of genes that drive growth in any specific condition is highly context-dependent. We inferred regulatory networks from gene expression data and transcription factor binding motifs in Saccharomyces cerevisiae, and found that high-degree nodes in regulatory networks are enriched for transcription factors that drive the corresponding phenotypes. We then found that using a metric combining protein interaction and transcriptional networks improved the enrichment for drivers in many of the contexts we examined. We applied this principle to a dataset of gene expression in normal human fibroblasts expressing a panel of viral oncogenes. We integrated regulatory interactions inferred from this data with a database of yeast two-hybrid protein interactions and ranked 571 human transcription factors by their combined network score. The ranked list was significantly enriched in known cancer genes that could not be found by standard differential expression or enrichment analyses.

CONCLUSIONS

There has been increasing recognition that network-based approaches can provide insight into critical cellular elements that help define phenotypic state. Our analysis suggests that no one network, based on a single data type, captures the full spectrum of interactions. Greater insight can instead be gained by exploring multiple independent networks and by choosing an appropriate metric on each network. Moreover we can improve our ability to rank phenotypic drivers by combining the information from individual networks. We propose that such integrative network analysis could be used to combine clinical gene expression data with interaction databases to prioritize patient- and disease-specific therapeutic targets.