Project description:Cell plasticity is emerging as a key regulator of tumor progression and metastasis. During carcinoma dissemination epithelial cells undergo epithelial to mesenchymal transition (EMT) processes characterized by the acquisition of migratory/invasive properties, while the reverse, mesenchymal to epithelial transition (MET) process, is also essential for metastasis outgrowth. Different transcription factors, called EMT-TFs, including Snail, bHLH and Zeb families are drivers of the EMT branch of epithelial plasticity, and can be post-transcriptionally downregulated by several miRNAs, as the miR-200 family. The specific or redundant role of different EMT-TFs and their functional interrelations are not fully understood. To study the interplay between different EMT-TFs, comprehensive gain and loss-of-function studies of Snail1, Snail2 and/or Zeb1 factors were performed in the prototypical MDCK cell model system. We here describe that Snail1 and Zeb1 are mutually required for EMT induction while continuous Snail1 and Snail2 expression, but not Zeb1, is needed for maintenance of the mesenchymal phenotype in MDCK cells. In this model system, EMT is coordinated by Snail1 and Zeb1 through transcriptional and epigenetic downregulation of the miR-200 family. Interestingly, Snail1 is involved in epigenetic CpG DNA methylation of the miR-200 loci, essential to maintain the mesenchymal phenotype. The present results thus define a novel functional interplay between Snail and Zeb EMT-TFs in miR200f regulation providing a molecular link to their previous involvement in the generation of EMT process in vivo. Expression analysis of MDCK over-expression EMT-TF Analysis of 7 overexpression MDCK cells each of them using biological rpelicates (MDCK-E47, Snail2, Snail1, Twist1, Tiwst2, Zeb1, Zeb2)
Project description:Cell plasticity is emerging as a key regulator of tumor progression and metastasis. During carcinoma dissemination epithelial cells undergo epithelial to mesenchymal transition (EMT) processes characterized by the acquisition of migratory/invasive properties, while the reverse, mesenchymal to epithelial transition (MET) process, is also essential for metastasis outgrowth. Different transcription factors, called EMT-TFs, including Snail, bHLH and Zeb families are drivers of the EMT branch of epithelial plasticity, and can be post-transcriptionally downregulated by several miRNAs, as the miR-200 family. The specific or redundant role of different EMT-TFs and their functional interrelations are not fully understood. To study the interplay between different EMT-TFs, comprehensive gain and loss-of-function studies of Snail1, Snail2 and/or Zeb1 factors were performed in the prototypical MDCK cell model system. We here describe that Snail1 and Zeb1 are mutually required for EMT induction while continuous Snail1 and Snail2 expression, but not Zeb1, is needed for maintenance of the mesenchymal phenotype in MDCK cells. In this model system, EMT is coordinated by Snail1 and Zeb1 through transcriptional and epigenetic downregulation of the miR-200 family. Interestingly, Snail1 is involved in epigenetic CpG DNA methylation of the miR-200 loci, essential to maintain the mesenchymal phenotype. The present results thus define a novel functional interplay between Snail and Zeb EMT-TFs in miR200f regulation providing a molecular link to their previous involvement in the generation of EMT process in vivo. Expression analysis of MDCK over-expression EMT-TF
Project description:Comparative oncology is a developing research discipline that is being used to assist our understanding of human neoplastic diseases. Companion canines are a preferred animal oncology model due to spontaneous tumor development and similarity to human disease at the pathophysiological level. We use a paired RNA sequencing (RNA-Seq)/microarray analysis of a set of four normal canine lymph nodes and ten canine lymphoma fine needle aspirates to identify technical biases and variation between the technologies and convergence on biological disease pathways. Surrogate Variable Analysis (SVA) provides a formal multivariate analysis of the combined RNA-Seq/microarray data set. Applying SVA to the data allows us to decompose variation into contributions associated with transcript abundance, differences between the technology, and latent variation within each technology. A substantial and highly statistically significant component of the variation reflects transcript abundance, and RNA-Seq proved more sensitive for detection of transcripts expressed at low levels. Latent random variation among RNA-Seq samples is also distinct in character from that impacting microarray samples. In particular, we observed variation between RNA-Seq samples that reflects transcript GC content. Platform-independent variable decomposition without a priori knowledge of the sources of variation using SVA represents a generalizable method for accomplishing cross-platform data analysis. We identified genes differentially expressed between normal lymph nodes of disease free dogs and a subset of the diseased dogs diagnosed with B-cell lymphoma using each technology. There is statistically significant overlap between the RNA-Seq and microarray sets of differentially expressed genes. Analysis of overlapping genes in the context of biological systems suggests elevated expression and activity of PI3K signaling in B-cell lymphoma biopsies compared with normal biopsies, consistent with literature describing successful use of drugs targeting this pathway in lymphomas.
Project description:Comparative oncology is a developing research discipline that is being used to assist our understanding of human neoplastic diseases. Companion canines are a preferred animal oncology model due to spontaneous tumor development and similarity to human disease at the pathophysiological level. We use a paired RNA sequencing (RNA-Seq)/microarray analysis of a set of four normal canine lymph nodes and ten canine lymphoma fine needle aspirates to identify technical biases and variation between the technologies and convergence on biological disease pathways. Surrogate Variable Analysis (SVA) provides a formal multivariate analysis of the combined RNA-Seq/microarray data set. Applying SVA to the data allows us to decompose variation into contributions associated with transcript abundance, differences between the technology, and latent variation within each technology. A substantial and highly statistically significant component of the variation reflects transcript abundance, and RNA-Seq proved more sensitive for detection of transcripts expressed at low levels. Latent random variation among RNA-Seq samples is also distinct in character from that impacting microarray samples. In particular, we observed variation between RNA-Seq samples that reflects transcript GC content. Platform-independent variable decomposition without a priori knowledge of the sources of variation using SVA represents a generalizable method for accomplishing cross-platform data analysis. We identified genes differentially expressed between normal lymph nodes of disease free dogs and a subset of the diseased dogs diagnosed with B-cell lymphoma using each technology. There is statistically significant overlap between the RNA-Seq and microarray sets of differentially expressed genes. Analysis of overlapping genes in the context of biological systems suggests elevated expression and activity of PI3K signaling in B-cell lymphoma biopsies compared with normal biopsies, consistent with literature describing successful use of drugs targeting this pathway in lymphomas. RNA was extracted from 10 lymphoma fine needle aspirates attained from companion canines. 4 normal lymph node samples were obtained from a Beagle breeding colony at Pfizer, including two samples that were taken from the same dog but different lymph nodes. This Series represents the Affymetrix gene expression only, not RNA-Seq referenced above. RNA-Seq data have been submitted to SRA as SRA059558.