RIZ1 is a histone methyltransferase whose expression and activity are reduced in many cancers. In chronic myelogenous leukemia (CML), blastic transformation is associated with loss of heterozygosity in the region where RIZ1 is located and with decreased RIZ1 expression. Forced RIZ1 expression in model CML blast crisis (BC) cell lines decreases proliferation, increases apoptosis and enhances differentiation. We characterized molecular mechanisms that may contribute to potential CML tumor suppressor properties of RIZ1. Several RIZ1-regulated genes involved in insulin-like growth factor-1 (IGF-1) signaling were identified using cDNA microarrays. RIZ1 was shown to associate with promoter regions of IGF-1 and to increase histone H3 lysine 9 methylation using chromatin immunoprecipitation assays. IGF-1-blocking antibody was used to demonstrate the importance of autocrine IGF-1 signaling in CML-BC cell line viability. Forced RIZ1 expression in CML-BC cell lines decreases IGF-1 receptor activation and activation of downstream signaling components extracellular signal-regulated kinase 1/2 and AKT. These results highlight the therapeutic potential of inhibiting IGF-1 pathway in the acute phase of CML.
In most cases, the application of machine learning techniques to biological sequence data requires a vector representation of the sequences. Extracting the numerical features from sequence data can be time consuming, especially if the user lacks programming skills. To this end, we propose a Weka package called WeSeqMiner, which provides several useful filters for extracting numerical features from sequence data for use in the Weka machine learning workbench. Motivated with an example, we show that the WeSeqMiner package integrates well with the Weka API, allowing transformations to be incorporated into Weka workflows for predictive model generation. WeSeqMiner can be installed by pointing the Weka package manager to the URL github.com/djhogan/WeSeqMiner/raw/master/WeSeqMiner.zip. The Javadoc for WeSeqMiner classes can be accessed at djhogan.github.io/seqminer.
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