NF-κB regulates mesenchymal transition for the induction of non-small cell lung cancer initiating cells.

The epithelial-to-mesenchymal transition (EMT) is a de-differentiation process that has been implicated in metastasis and the generation of cancer initiating cells (CICs) in solid tumors. To examine EMT in non-small cell lung cancer (NSCLC), we utilized a three dimensional (3D) cell culture system in which cells were co-stimulated with tumor necrosis factor alpha (TNF) and transforming growth factor beta (TGFß). NSCLC spheroid cultures display elevated expression of EMT master-switch transcription factors, TWIST1, SNAI1/Snail1, SNAI2/Slug and ZEB2/Sip1, and are highly invasive. Mesenchymal NSCLC cultures show CIC characteristics, displaying elevated expression of transcription factors KLF4, SOX2, POU5F1/Oct4, MYCN, and KIT. As a result, these putative CIC display a cancer "stem-like" phenotype by forming lung metastases under limiting cell dilution. The pleiotropic transcription factor, NF-κB, has been implicated in EMT and metastasis. Thus, we set out to develop a NSCLC model to further characterize the role of NF-κB activation in the development of CICs. Here, we demonstrate that induction of EMT in 3D cultures results in constitutive NF-κB activity. Furthermore, inhibition of NF-κB resulted in the loss of TWIST1, SNAI2, and ZEB2 induction, and a failure of cells to invade and metastasize. Our work indicates that NF-κB is required for NSCLC metastasis, in part, by transcriptionally upregulating master-switch transcription factors required for EMT.

A system for studying evolution of life-like virtual organisms.

BACKGROUND: Fitness landscapes, the dependences of fitness on the genotype, are of critical importance for the evolution of living beings. Unfortunately, fitness landscapes that are relevant to the evolution of complex biological functions are very poorly known. As a result, the existing theory of evolution is mostly based on postulated fitness landscapes, which diminishes its usefulness. Attempts to deduce fitness landscapes from models of actual biological processes led, so far, to only limited success. RESULTS: We present a model system for studying the evolution of biological function, which makes it possible to attribute fitness to genotypes in a natural way. The system mimics a very simple cell and takes into account the basic properties of gene regulation and enzyme kinetics. A virtual cell contains only two small molecules, an organic nutrient A and an energy carrier X, and proteins of five types--two transcription factors, two enzymes, and a membrane transporter. The metabolism of the cell consists of importing A from the environment and utilizing it in order to produce X and an unspecified end product. The genome may carry an arbitrary number of genes, each one encoding a protein of one of the five types. Both major mutations that affect whole genes and minor mutations that affect individual characteristics of genes are possible. Fitness is determined by the ability of the cell to maintain homeostasis when its environment changes. The system has been implemented as a computer program, and several numerical experiments have been performed on it. Evolution of the virtual cells usually involves a rapid initial increase of fitness, which eventually slows down, until a fitness plateau is reached. The origin of a wide variety of genetic networks is routinely observed in independent experiments performed under the same conditions. These networks can have different, including very high, levels of complexity and often include large numbers of non-essential genes. CONCLUSION: The described system displays a rich repertoire of biologically sensible behaviors and, thus, can be useful for investigating a number of unresolved issues in evolutionary biology, including evolution of complexity, modularity and redundancy, as well as for studying the general properties of genotype-to-fitness maps. REVIEWERS: This article was reviewed by Drs. Eugene Koonin, Shamil Sunyaev and Arcady Mushegian.