MicroRNA-128-3p is a novel oncomiR targeting PHF6 in T-cell acute lymphoblastic leukemia.

T-cell acute lymphoblastic leukemia arises from the leukemic transformation of developing thymocytes and results from cooperative genetic lesions. Inactivation of the PHF6 gene is frequently observed in T-cell acute lymphoblastic leukemia, suggesting an important tumor suppressive role for PHF6 in the pathobiology of this leukemia. Although the precise function of PHF6 is still unknown, this gene is most likely involved in chromatin regulation, a strongly emerging theme in T-cell acute lymphoblastic leukemia. In this context, our previous description of a cooperative microRNA regulatory network controlling several well-known T-cell acute lymphoblastic leukemia tumor suppressor genes, including PHF6, is of great importance. Given the high frequency of PHF6 lesions in T-cell acute lymphoblastic leukemia and the integration of PHF6 in this microRNA regulatory network, we aimed to identify novel oncogenic microRNAs in T-cell acute lymphoblastic leukemia which suppress PHF6. To this end, we performed an unbiased PHF6 3'UTR-microRNA library screen and combined the results with microRNA profiling data of samples from patients with T-cell acute lymphoblastic leukemia and normal thymocyte subsets. We selected miR-128-3p as a candidate PHF6-targeting, oncogenic microRNA and demonstrated regulation of PHF6 expression upon modulation of this microRNA in T-cell acute lymphoblastic leukemia cell lines. In vivo evidence of an oncogenic role of this microRNA in T-cell acute lymphoblastic leukemia was obtained through accelerated leukemia onset in a NOTCH1-induced T-cell acute lymphoblastic leukemia mouse model upon miR-128-3p over-expression. We conclude that miR-128-3p is a strong novel candidate oncogenic microRNA in T-cell acute lymphoblastic leukemia which targets the PHF6 tumor suppressor gene.

A high-throughput 3' UTR reporter screening identifies microRNA interactomes of cancer genes.

INTRODUCTION: Despite the established contribution of deregulated microRNA (miRNA) function to carcinogenesis, relatively few miRNA-cancer gene interactions have been validated, making it difficult to appreciate the true complexity of miRNA-cancer gene regulatory networks. RESULTS: In this effort, we identify miRNA interactomes of 17 well-established cancer genes, involved in various cancer types, through a miRNome-wide 3' UTR reporter screening. Using a novel and performant strategy for high-throughput screening data analysis, we identify 390 interactions, quadrupling the size of the known miRNA interactome for the cancer genes under investigation. Clear enrichments of established and predicted interactions underscore the validity of the interactome data set. Interactomes appear to be primarily driven by canonical binding site interactions. Nonetheless, non-canonical binding sites, such as offset 6mer and seed-mismatched or G:U wobble sites, also have regulatory activity, albeit clearly less pronounced. Furthermore, we observe enhanced regulation in the presence of 3' supplementary pairing for both canonical and non-canonical binding sites. CONCLUSIONS: Altogether, the cancer gene-miRNA interactome data set represents a unique resource that will aid in the unraveling of regulatory miRNA networks and the dynamic regulation of key protein-coding cancer genes. In addition, it uncovers aspects of the functional miRNA binding site's architecture and the relative contributions of different binding site types.

MYCN-targeting miRNAs are predominantly downregulated during MYCN­driven neuroblastoma tumor formation.

MYCN is a transcription factor that plays key roles in both normal development and cancer. In neuroblastoma, MYCN acts as a major oncogenic driver through pleiotropic effects regulated by multiple protein encoding genes as well as microRNAs (miRNAs). MYCN activity is tightly controlled at the level of transcription and protein stability through various mechanisms. Like most genes, MYCN is further controlled by miRNAs, but the full complement of all miRNAs implicated in this process has not been determined through an unbiased approach. To elucidate the role of miRNAs in regulation of MYCN, we thus explored the MYCN-miRNA interactome to establish miRNAs controlling MYCN expression levels. We combined results from an unbiased and genome-wide high-throughput miRNA target reporter screen with miRNA and mRNA expression data from patients and a murine neuroblastoma progression model. We identified 29 miRNAs targeting MYCN, of which 12 miRNAs are inversely correlated with MYCN expression or activity in neuroblastoma tumor tissue. The majority of MYCN-targeting miRNAs in neuroblastoma showed a decrease in expression during murine MYCN-driven neuroblastoma tumor development. Therefore, we provide evidence that MYCN-targeting miRNAs are preferentially downregulated in MYCN-driven neuroblastoma, suggesting that MYCN negatively controls the expression of these miRNAs, to safeguard its expression.

Effective Alu repeat based RT-Qpcr normalization in cancer cell perturbation experiments.

BACKGROUND: Measuring messenger RNA (mRNA) levels using the reverse transcription quantitative polymerase chain reaction (RT-qPCR) is common practice in many laboratories. A specific set of mRNAs as internal control reference genes is considered as the preferred strategy to normalize RT-qPCR data. Proper selection of reference genes is a critical issue, especially in cancer cells that are subjected to different in vitro manipulations. These manipulations may result in dramatic alterations in gene expression levels, even of assumed reference genes. In this study, we evaluated the expression levels of 11 commonly used reference genes as internal controls for normalization of 19 experiments that include neuroblastoma, T-ALL, melanoma, breast cancer, non small cell lung cancer (NSCL), acute myeloid leukemia (AML), prostate cancer, colorectal cancer, and cervical cancer cell lines subjected to various perturbations. RESULTS: The geNorm algorithm in the software package qbase+ was used to rank the candidate reference genes according to their expression stability. We observed that the stability of most of the candidate reference genes varies greatly in perturbation experiments. Expressed Alu repeats show relatively stable expression regardless of experimental condition. These Alu repeats are ranked among the best reference assays in all perturbation experiments and display acceptable average expression stability values (M<0.5). CONCLUSIONS: We propose the use of Alu repeats as a reference assay when performing cancer cell perturbation experiments.

A cooperative microRNA-tumor suppressor gene network in acute T-cell lymphoblastic leukemia (T-ALL).

The importance of individual microRNAs (miRNAs) has been established in specific cancers. However, a comprehensive analysis of the contribution of miRNAs to the pathogenesis of any specific cancer is lacking. Here we show that in T-cell acute lymphoblastic leukemia (T-ALL), a small set of miRNAs is responsible for the cooperative suppression of several tumor suppressor genes. Cross-comparison of miRNA expression profiles in human T-ALL with the results of an unbiased miRNA library screen allowed us to identify five miRNAs (miR-19b, miR-20a, miR-26a, miR-92 and miR-223) that are capable of promoting T-ALL development in a mouse model and which account for the majority of miRNA expression in human T-ALL. Moreover, these miRNAs produce overlapping and cooperative effects on tumor suppressor genes implicated in the pathogenesis of T-ALL, including IKAROS (also known as IKZF1), PTEN, BIM, PHF6, NF1 and FBXW7. Thus, a comprehensive and unbiased analysis of miRNA action in T-ALL reveals a striking pattern of miRNA-tumor suppressor gene interactions in this cancer.