Project description:Abstract Background: One of the approaches for conducting genomics research in organisms that do not yet have a proper microarray template is to profile their expression patterns by using cross-species hybridization (CSH). Several different studies using spotted microarray for CSH resulted with contradicting conclusions as to the ability of CSH to reflect biological processes. Results: We used a tomato spotted cDNA microarray to examine the ability of CSH to reflect species specific hybridization (SSH) data. Potato RNA was hybridized to spotted cDNA tomato and potato microarrays to generate heterologous and homologous hybridization data, respectively. The results revealed difficulties in obtaining transcriptomics data from CSH that reflected those obtained from SSH. Nevertheless, once the data was filtered for those corresponding to matching probe sets, by restricting proper cutoffs of probe homology, the CSH transcriptomics data better reflected those of the SSH, to an extent that was quantitated by identification of differentially regulated genes. Conclusions: This study enabled us to outline some considerations regarding evaluation of a microarray as candidate platform for CSH study, performance of CSH and proper data analysis that may allow CSH to reflect to some extent a biological process. Keywords: cross-species hybridization; heterologous hybridization
Project description:The determinants of the genetic complexity of Glioblastoma are poorly understood. We generated murine Glioblastomas by transforming glial progenitors in the adult brain with PDGF expression and PTEN deletion +/- p53 deletion. PDGF+PTEN-/- tumors developed additional deletions of specific genes in up to 100% of the tumors, whereas PDGF+PTEN-/-p53-/- tumors did not. Cross-species comparison with data from tCGA database and published in Verhaak, 2010, showed that consistent genetic deletions observed in mouse tumors were specific to human Proneural Glioblastoma. These findings show that the genetic alterations that accumulate during tumor progression are determined by the initiating genetic alterations and by the cellular context in which they occur.
Project description:The determinants of the genetic complexity of Glioblastoma are poorly understood. We generated murine Glioblastomas by transforming glial progenitors in the adult brain with PDGF expression and PTEN deletion +/- p53 deletion. PDGF+PTEN-/- tumors developed additional deletions of specific genes in up to 100% of the tumors, whereas PDGF+PTEN-/-p53-/- tumors did not. Cross-species comparison with data from tCGA database and published in Verhaak, 2010, showed that consistent genetic deletions observed in mouse tumors were specific to human Proneural Glioblastoma. These findings show that the genetic alterations that accumulate during tumor progression are determined by the initiating genetic alterations and by the cellular context in which they occur. Murine gliomas were induced in vivo by retroviral mediated PDGF overexpression, PTEN deletion with or without p53 deletion using Cre/lox system. Tumors were subsequently harvested for sequencing and aCGH analysis. Paired liver DNA was used for hybridization. For PDGF+PTEN-/- tumors, different timepoints were obtained including 21, 35 days post tumor induction, as well as endstage tumors.
Project description:The growth of a tumor is tightly linked to the distribution of its cells along a continuum of activation states. Here, we systematically decode the activation state architecture (ASA) in a glioblastoma (GBM) patient cohort through comparison to adult murine neural stem cells. Modelling of these data forecasts how tumor cells organize to sustain growth and identifies the rate of activation as the main predictor of growth. Accordingly, patients with a higher quiescence fraction exhibit improved outcomes. Further, DNA methylation arrays enable ASA-related patient stratification. Comparison of healthy and malignant gene expression dynamics reveals dysregulation of the Wnt-antagonist SFRP1 at the quiescence to activation transition. SFRP1 overexpression renders GBM quiescent and increases the overall survival of tumor-bearing mice. Surprisingly, it does so through reprogramming the tumor’s stem-like methylome into an astrocyte-like one. Our findings offer a framework for patient stratification with prognostic value, biomarker identification, and therapeutic avenues to halt GBM progression.
Project description:The growth of a tumor is tightly linked to the distribution of its cells along a continuum of activation states. Here, we systematically decode the activation state architecture (ASA) in a glioblastoma (GBM) patient cohort through comparison to adult murine neural stem cells. Modelling of these data forecasts how tumor cells organize to sustain growth and identifies the rate of activation as the main predictor of growth. Accordingly, patients with a higher quiescence fraction exhibit improved outcomes. Further, DNA methylation arrays enable ASA-related patient stratification. Comparison of healthy and malignant gene expression dynamics reveals dysregulation of the Wnt-antagonist SFRP1 at the quiescence to activation transition. SFRP1 overexpression renders GBM quiescent and increases the overall survival of tumor-bearing mice. Surprisingly, it does so through reprogramming the tumor’s stem-like methylome into an astrocyte-like one. Our findings offer a framework for patient stratification with prognostic value, biomarker identification, and therapeutic avenues to halt GBM progression.