Protein tyrosine phosphatase mu regulates glioblastoma cell growth and survival in vivo

Department of Molecular Biology and Microbiology, School of Medicine, Case Western Reserve University, Cleveland, Ohio 44106-4960, USA.
Neuro-Oncology (Impact Factor: 5.56). 04/2012; 14(5):561-73. DOI: 10.1093/neuonc/nos066
Source: PubMed


Glioblastoma multiforme (GBM) is the most lethal primary brain tumor. Extensive proliferation and dispersal of GBM tumor cells
within the brain limits patient survival to approximately 1 year. Hence, there is a great need for the development of better
means to treat GBM. Receptor protein tyrosine phosphatase (PTP)µ is proteolytically cleaved in GBM to yield fragments that
promote dispersal of GBM cells. While normal brain tissue retains expression of full-length PTPµ, low-grade human astrocytoma
samples have varying amounts of full-length PTPµ and cleaved PTPµ. In the highest-grade astrocytomas (i.e., GBM), PTPµ is
completely proteolyzed into fragments. We demonstrate that short hairpin RNA mediated knockdown of full-length PTPµ and PTPµ
fragments reduces glioma cell growth and survival in vitro. The reduction in growth and survival following PTPµ knockdown
is enhanced when cells are grown in the absence of serum, suggesting that PTPµ may regulate autocrine signaling. Furthermore,
we show for the first time that reduction of PTPµ protein expression decreases the growth and survival of glioma cells in
vivo using mouse xenograft flank and i.c. tumor models. Inhibitors of PTPµ could be used to reduce the growth and survival
of GBM cells in the brain, representing a promising therapeutic target for GBM.

  • Source
    • "Therefore, intracellular PTPRK may take advantage of other mechanism, such as regulating cofactors of β-catenin transcriptional complex, to accomplish this. Although the function of intracellular PTPRM has not been characterized , the fact that PTPRM is highly cleaved in gliomas and its downregulation inhibits glioma cell growth and migration indicates that intracellular PTPRM is important for tumor progression [20] [26]. Hence, it is reasonable that endogenous PTPRU promote growth and motility of gastirc cancer cells through β-catenin signaling . "
    [Show abstract] [Hide abstract]
    ABSTRACT: Protein tyrosine phosphatase receptor U (PTPRU) has been shown to be a tumor suppressor in colon cancer by dephosphorylating β-catenin and reducing the activation of β-catenin signaling. Here, we investigate the expression of PTPRU protein in gastric cancer cell lines, gastric cancer tissues and respective adjacent non-cancer tissues and find that the 130kDa nuclear-localized PTPRU fragment is the main PTPRU isoform in gastric cancer cells, whereas the full-length PTPRU is relatively lowly expressed. The level of the 130kDa PTPRU is higher in gastric cancer tissues than in adjacent non-cancer tissues. Knockdown of endogenous PTPRU in gastric cancer cells using lentivirus-delivered specific shRNA results in the attenuation of cell growth, migration, invasion and adhesion. Knockdown of PTPRU also inhibits tyrosine phosphorylation and transcriptional activity of β-catenin as well as levels of focal adhesion proteins and lysine methylation of histone H3. These results indicate that PTPRU is required for gastric cancer progression and may serve as a potential therapeutic target.
    Full-text · Article · Oct 2014 · International journal of clinical and experimental pathology
  • Source
    • "As shown in Figure 3, the top ranked genes for the OD and Zscore methods, PTPRM and TDRD9, exhibited clear gene-level over-expression. We note that knockdown of PTPRM has been previously suggested to decrease cell growth and survival in glioblastoma multiforme [60], suggesting its possible inclusion in a future iteration of the siRNA panel. Less seems to be known about TDRD9. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Patient-specific aberrant expression patterns in conjunction with functional screening assays can guide elucidation of the cancer genome architecture and identification of therapeutic targets. Since most statistical methods for expression analysis are focused on differences between experimental groups, the performance of approaches for patient-specific expression analyses are currently less well characterized. A comparison of methods for the identification of genes that are dysregulated relative to a single sample in a given set of experimental samples, to our knowledge, has not been performed. We systematically evaluated several methods including variations on the nearest neighbor based outlying degree method, as well as the Zscore and a robust variant for their suitability to detect patient-specific events. The methods were assessed using both simulations and expression data from a cohort of pediatric acute B lymphoblastic leukemia patients. We first assessed power and false discovery rates using simulations and found that even under optimal conditions, high effect sizes (>4 unit differences) were necessary to have acceptable power for any method (>0.9) though high false discovery rates (>0.1) were pervasive across simulation conditions. Next we introduced a technical factor into the simulation and found that performance was reduced for all methods and that using weights with the outlying degree could provide performance gains depending on the number of samples and genes affected by the technical factor. In our use case that highlights the integration of functional assays and aberrant expression in a patient cohort (the identification of gene dysregulation events associated with the targets from a siRNA screen), we demonstrated that both the outlying degree and the Zscore can successfully identify genes dysregulated in one patient sample. However, only the outlying degree can identify genes dysregulated across several patient samples. Our results show that outlying degree methods may be a useful alternative to the Zscore or Rscore in a personalized medicine context especially in small to medium sized (between 10 and 50 samples) expression datasets with moderate to high sample-to-sample variability. From these results we provide guidelines for detection of aberrant expression in a precision medicine context.
    Full-text · Article · Nov 2013 · Genome Medicine
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Tumors contain a vastly complicated cellular network that relies on local communication to execute malignant programs. The molecular cues that are involved in cell-cell adhesion orchestrate large-scale tumor behaviors such as proliferation and invasion. We have recently begun to appreciate that many tumors contain a high degree of cellular heterogeneity and are organized in a cellular hierarchy, with a cancer stem cell (CSC) population identified at the apex in multiple cancer types. CSCs reside in unique microenvironments or niches that are responsible for directing their behavior through cellular interactions between CSCs and stromal cells, generating a malignant social network. Identifying cell-cell adhesion mechanisms in this network has implications for the basic understanding of tumorigenesis and the development of more effective therapies. In this review, we will discuss our current understanding of cell-cell adhesion mechanisms used by CSCs and how these local interactions have global consequences for tumor biology.
    Preview · Article · Jul 2012 · Cell adhesion & migration
Show more