Can transcriptomic alterations drive the evolution of tumors? We asked if changes in gene expression found in all patients arise earlier in tumor development and can be relevant to tumor progression. Our analyses of non-mutated genes from the non-amplified regions of the genome of 158 triple-negative breast cancer (TNBC) cases identified 219 exclusively expression-altered (EEA) genes that may play important role in TNBC. Phylogenetic analyses of these genes predict a “punctuated burst” of multiple gene upregulation events occurring at early stages of tumor development, followed by minimal subsequent changes later in tumor progression. Remarkably, this punctuated burst of expressional changes is instigated by hypoxia-related molecular events, predominantly in two groups of genes that control chromosomal instability (CIN) and those that remodel tumor microenvironment (TME). We conclude that alterations in the transcriptome are not stochastic and that early-stage hypoxia induces CIN and TME remodeling to permit further tumor evolution.
Can transcriptomic alterations drive the evolution of tumors? We rationalize that expressional changes found in all patients arise earlier in tumor development compared to alterations that occur only in limited subsets of patients. Our analyses of non-mutated genes from the nonamplified regions of the genome of 158 triple negative breast cancer (TNBC) cases identified 219 exclusively expression-altered (EEA) genes that may play important role in TNBC.Phylogenetic analyses of these genes predict a "punctuated burst" of multiple gene upregulation events occurring at early stages of tumor development, followed by minimal subsequent changes later in tumor progression. Remarkably, this punctuated burst of expressional changes is instigated by hypoxia-related molecular events, predominantly in two groups of genes that control chromosomal instability (CIN) and remodel tumor microenvironment (TME). We conclude that alterations in the transcriptome are not stochastic and that early stage hypoxia induces CIN and TME remodeling to permit further tumor evolution.
Changes in gene expression have been thought to play a crucial role in various types of cancer. With the advance of high-throughput experimental techniques, many genome-wide studies are underway to analyze underlying mechanisms that may drive the changes in gene expression. It has been observed that the change could arise from altered DNA methylation. However, the knowledge about the degree to which epigenetic changes might cause differences in gene expression in cancer is currently lacking. By considering the change of gene expression as the response of altered DNA methylation, we introduce a novel analytical framework to identify epigenetic subnetworks in which the methylation status of a set of highly correlated genes is predictive of a set of gene expression. By detecting highly correlated modules as representatives of the regulatory scenario underling the gene expression and DNA methylation, the dependency between DNA methylation and gene expression is explored by a Bayesian regression model with the incorporation of g-prior followed by a strategy of an optimal predictor subset selection. The subsequent network analysis indicates that the detected epigenetic subnetworks are highly biologically relevant and contain many verified epigenetic causal mechanisms. Moreover, a survival analysis indicates that they might be effective prognostic factors associated with patient survival time.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.