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An Ectopic Network of Transcription Factors Regulated by Hippo Signaling Drives Growth and Invasion of a Malignant Tumor Model.

Current biology : CB | 2016

Cancer cells have abnormal gene expression profiles; however, to what degree these are chaotic or driven by structured gene regulatory networks is often not known. Here we studied a model of Ras-driven invasive tumorigenesis in Drosophila epithelial tissues and combined in vivo genetics with next-generation sequencing and computational modeling to decipher the regulatory logic of tumor cells. Surprisingly, we discovered that the bulk of the tumor-specific gene expression is controlled by an ectopic network of a few transcription factors that are overexpressed and/or hyperactivated in tumor cells. These factors are Stat, AP-1, the bHLH proteins Myc and AP-4, the nuclear hormone receptor Ftz-f1, the nuclear receptor coactivator Taiman/SRC3, and Mef2. Notably, many of these transcription factors also are hyperactivated in human tumors. Bioinformatic analysis predicted that these factors directly regulate the majority of the tumor-specific gene expression, that they are interconnected by extensive cross-regulation, and that they show a high degree of co-regulation of target genes. Indeed, the factors of this network were required in multiple epithelia for tumor growth and invasiveness, and knockdown of several factors caused a reversion of the tumor-specific expression profile but had no observable effect on normal tissues. We further found that the Hippo pathway effector Yorkie was strongly activated in tumor cells and initiated cellular reprogramming by activating several transcription factors of this network. Thus, modeling regulatory networks identified an ectopic and ordered network of master regulators that control a large part of tumor cell-specific gene expression.

Pubmed ID: 27476594 RIS Download

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Associated grants

  • Agency: NIH HHS, United States
    Id: P40 OD018537
  • Agency: NIGMS NIH HHS, United States
    Id: R01 GM084947

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GraphPad Prism (tool)

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Statistical analysis software that combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization. Designed for biological research applications in pharmacology, physiology, and other biological fields for data analysis, hypothesis testing, and modeling.

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Bloomington Drosophila Stock Center (tool)

RRID:SCR_006457

Collects, maintains and distributes Drosophila melanogaster strains for research. Emphasis is placed on genetic tools that are useful to a broad range of investigations. These include basic stocks of flies used in genetic analysis such as marker, balancer, mapping, and transposon-tagging strains; mutant alleles of identified genes, including a large set of transposable element insertion alleles; defined sets of deficiencies and a variety of other chromosomal aberrations; engineered lines for somatic and germline clonal analysis; GAL4 and UAS lines for targeted gene expression; enhancer trap and lacZ-reporter strains with defined expression patterns for marking tissues; and a collection of transposon-induced lethal mutations.

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