Knockdown of CypA inhibits interleukin-8 (IL-8) and IL-8-mediated proliferation and tumor growth of glioblastoma cells through down-regulated NF-κB

Although cyclophilin A (CypA) has been reported to be over-expressed in cancer cells and solid tumors, its expression and role in glioblastomas have not been studied. Herein, we show that expression of CypA in human glioblastoma cell lines and tissues is significantly higher than in normal human astrocytes and normal counterparts of brain tissue. To determine the role of over-expressed CypA in glioblastoma, stable RNA interference (RNAi)-mediated knockdown of CypA (CypA KD) was performed in gliobastoma cell line U87vIII (U87MG · ΔEGFR). CypA KD stable single clones decrease proliferation, infiltration, migration, and anchorage-independent growth in vitro and with slower growth in vivo as xenografts in immunodeficient nude mice. We have also observed that knockdown of CypA inhibits expression of interleukin-8 (IL-8), a tumorigenic and proangiogenic cytokine. Conversely, enforced expression of CypA in the CypA KD cell line, Ud-12, markedly enhanced IL-8 transcripts and restored Ud-12 proliferation, suggesting that CypA-mediated IL-8 production provides a growth advantage to glioblastoma cells. CypA knockdown-mediated inhibition of IL-8 is due to reduced activity of NF-κB, which is one of the major transcription factors regulating IL-8 expression. These results not only establish the relevance of CypA to glioblastoma growth in vitro and in vivo, but also suggest that small interfering RNA-based CypA knockdown could be an effective therapeutic approach against glioblastomas

Stable interference of EWS–FLI1 in an Ewing sarcoma cell line impairs IGF-1/IGF-1R signalling and reveals TOPK as a new target

BACKGROUND: Ewing sarcoma is a paradigm of solid tumour -bearing chromosomal translocations resulting in fusion proteins that act as deregulated transcription factors. Ewing sarcoma translocations fuse the EWS gene with an ETS transcription factor, mainly FLI1. Most of the EWS–FLI1 target genes still remain unknown and many have been identified in heterologous model systems

Autoimmune hemolytic anemia with gel-based immunohematology tests: neural network analysis

In a previous report, we investigated the capability of commercially available immunohematology tests based on gel technology to add useful information for the diagnosis of autoimmune hemolytic anemia (AIHA). In this report, we analyzed the same casuistic to find useful information on the importance of different immunohematology tests for the AIHA diagnosis, but using the artificial neural network (ANN) analysis. We studied 588 samples with a positive direct antiglobulin test (DAT), of which 52 samples came from patients with AIHA. The samples were analyzed with the ANN using the multilayer perceptron with the backpropagation algorithm. Using the ANN in the observed data set, the predictive value for the presence of AIHAs was 94.7%. The rate of DAT-positive cases that were not AIHA and that were correctly classified was 99.4%. The receiver operating curve area for the model was 0.99. The independent variable importance analysis found that the gel centrifugation test anti-IgG titer was an important contributor to the network performance, but other variables such as the IgG subclasses can also be considered important. The use of the ANN permitted us to identify immunohematology tests that were "hidden" with the common statistical models used previously. This was the case for the IgG subclasses. However, it is very likely that the information given to the network from those tests is quantitative rather than qualitative