Molecular network pathways and functional analysis of tumor signatures associated with development of resistance to viral gene therapy.

Replication-competent attenuated herpes simplex viruses have proven effective in killing many cancer cell lines. However, determinants of resistance to oncolytic therapy are mostly unknown. We developed viral therapy-resistant cells and examined changes in gene-expression pattern compared with therapy-sensitive parental cells. Colon cancer cell line HT29 and hepatoma cell line PLC5 were exposed to increasing concentrations of virus G207. Therapy-resistant cells were isolated and grown in vitro. Tumorigenicity was confirmed by ability of cell lines to form tumors in mice. Human Genome U133A complementary DNA microarray chips were used to determine gene-expression patterns, which were analyzed in the context of molecular network interactions, pathways and gene ontology. In parental cell lines, 90-100% of cells were killed by day 7 at 1.0 multiplicity of infection. In resistant cell lines, cytotoxicity assay confirmed 200- to 400-fold resistance. Microarray analysis confirmed changes in gene expressions associated with resistance: cell surface proteins affecting viral attachment and entry, cellular proteins affecting nucleotide pools and proteins altering apoptotic pathways. These changes would decrease viral infection and replication. Our study identifies gene-expression signatures associated with resistance to oncolytic viral therapy. These data provide potential targets to overcome resistance, and suggest that molecular assays may be useful in selecting patients for trial with this novel treatment.

Phase II trial of neoadjuvant temozolomide in resectable melanoma patients.

BACKGROUND: We treated melanoma patients with temozolomide (TMZ) in the neoadjuvant setting and collected cryopreserved tumor samples before and after treatment. The primary objective was to determine whether the response proportion was higher than previously reported in widely metastatic patients. A secondary objective was to test the feasibility of obtaining adequate tissue before and after treatment for genetic testing. MATERIALS AND METHODS: Chemotherapy-naive melanoma patients who were candidates for surgical resection were eligible. TMZ was administered orally at 75 mg/m(2)/day for 6 weeks of every 8-week cycle. Cycles were repeated until complete response (CR), progression, or stable disease (SD) for two cycles. RESULTS: Of 19 assessable patients, 2 had CRs and 1 had partial response. Four patients had SD; 12 progressed. Tumor O-6-methylguanine-DNA methyltransferase (MGMT) promoter was unmethylated in all nine patients analyzed including from the two CR patients. Pretreatment tumor microarray results were obtained in 16 of 19 patients. CONCLUSIONS: The response proportion to TMZ in the neoadjuvant setting was 16%, not different than in the metastatic setting. Responses were seen even in tumors with a methylated MGMT promoter. Pretreatment cryopreserved tumor adequate for microarray analysis could be obtained in most, but not all, patients. Post-treatment tumor was unavailable in complete responders.

Akt phosphorylation of La regulates specific mRNA translation in glial progenitors.

The Akt signaling pathway activity increases as normal tissue progresses to malignant transformation, and regulates the translation of specific messenger RNAs (mRNAs) through multiple mechanisms. We have identified one such mechanism of Akt-dependent translation control as involving the lupus autoantigen La. La is an RNA-associated protein that contains multiple trafficking elements to support the interaction with RNAs in different subcellular locations. We show here that the La protein is a direct target of the serine/threonine protein kinase Akt on threonine 301, and La nuclear export in mouse glial progenitors, as well as its association with polysomes is modulated by Akt activity. Using a functional approach to determine the network of genes affected by La in the cytoplasm by microarray analysis of polysome-bound mRNAs, we found that La binds 34% of the polysome bound mRNAs and regulates the expression of a specific pool of mRNAs under KRas/Akt activation. Therefore, La appears to be an important contributor to Akt-mediated translational regulation of these transcripts in murine glial cells.

Distinct transcriptional profiles of adipogenesis in vivo and in vitro.

Obesity, defined as an increase in adipose tissue mass, is the most prevalent nutritional disorder in industrialized countries and is a growing problem in developing countries. An increase in adipose tissue mass can be the result of the production of new fat cells through the process of adipogenesis and/or the deposition of increased amounts of cytoplasmic triglyceride per cell. Although much has been learned about the differentiation of adipocytes in vitro, less is known about the molecular basis for the mechanisms regulating adipogenesis in vivo. Here oligonucleotide microarrays have been used to compare the patterns of gene expression in preadipocytes and adipocytes in vitro and in vivo. These data indicate that the cellular programs associated with adipocyte differentiation are considerably more complex than previously appreciated and that a greater number of heretofore uncharacterized gene regulatory events are activated during this process in vitro. In addition, the gene expression changes associated with adipocyte development in vivo and in vitro, while overlapping, are in some respects quite different. These data further suggest that one or more transcriptional programs are activated exclusively in vivo to generate the full adipocyte phenotype. This gene expression survey now sets the stage for further studies to dissect the molecular differences between in vivo and in vitro adipocytes.

Leptin-specific patterns of gene expression in white adipose tissue.

Leptin is a hormone that regulates body weight by decreasing food intake and increasing energy expenditure. ob/ob mice carry leptin mutations and are obese and hyperphagic. Leptin administration to lean and ob/ob mice activates a novel metabolic program that depletes adipose tissue. Although this response is physiologically distinct from that evident after food restriction, the molecular nature of these differences is as yet unknown. Expression monitoring of 6500 genes using oligonucleotide microarrays in wild-type, ob/ob, and transgenic mice expressing low levels of leptin revealed that differences in ambient leptin levels have dramatic effects on the phenotype of white adipose tissue. These data identified a large number of genes that are differentially expressed in ob/ob mice. To delineate the components of the transcriptional program specifically affected by leptin, the level of the same 6500 genes was monitored in wild-type and ob/ob mice at various times after leptin treatment or food restriction. A novel application of k-means clustering identified 8 clusters of adipose tissue genes whose expression was different between leptin treatment and food restriction in ob/ob mice and 10 such clusters in wild-type experiments. One of the clusters was repressed specifically by leptin in both wild-type and ob/ob mice and included several genes known to be regulated by SREBP-1/ADD1. Further studies confirmed that leptin decreases the levels of SREBP-1/ADD1 RNA and transcriptionally active SREBP-1/ADD1 protein in white adipose tissue. Future studies of the molecular basis for the apparent coordinate regulation of the other clusters of leptin-regulated genes may reveal additional mechanisms by which leptin exerts its weight-reducing effects.

Weighted neighbor joining: a likelihood-based approach to distance-based phylogeny reconstruction.

We introduce a distance-based phylogeny reconstruction method called "weighted neighbor joining," or "Weighbor" for short. As in neighbor joining, two taxa are joined in each iteration; however, the Weighbor criterion for choosing a pair of taxa to join takes into account that errors in distance estimates are exponentially larger for longer distances. The criterion embodies a likelihood function on the distances, which are modeled as correlated Gaussian random variables with different means and variances, computed under a probabilistic model for sequence evolution. The Weighbor criterion consists of two terms, an additivity term and a positivity term, that quantify the implications of joining the pair. The first term evaluates deviations from additivity of the implied external branches, while the second term evaluates confidence that the implied internal branch has a positive branch length. Compared with maximum-likelihood phylogeny reconstruction, Weighbor is much faster, while building trees that are qualitatively and quantitatively similar. Weighbor appears to be relatively immune to the "long branches attract" and "long branch distracts" drawbacks observed with neighbor joining, BIONJ, and parsimony.

Landscape approaches for determining the ensemble of folding transition states: success and failure hinge on the degree of frustration.

We present a method for determining structural properties of the ensemble of folding transition states from protein simulations. This method relies on thermodynamic quantities (free energies as a function of global reaction coordinates, such as the percentage of native contacts) and not on "kinetic" measurements (rates, transmission coefficients, complete trajectories); consequently, it requires fewer computational resources compared with other approaches, making it more suited to large and complex models. We explain the theoretical framework that underlies this method and use it to clarify the connection between the experimentally determined Phi value, a quantity determined by the ratio of rate and stability changes due to point mutations, and the average structure of the transition state ensemble. To determine the accuracy of this thermodynamic approach, we apply it to minimalist protein models and compare these results with the ones obtained by using the standard experimental procedure for determining Phi values. We show that the accuracy of both methods depends sensitively on the amount of frustration. In particular, the results are similar when applied to models with minimal amounts of frustration, characteristic of rapid-folding, single-domain globular proteins.

Stretching lattice models of protein folding.

A new class of experiments that probe folding of individual protein domains uses mechanical stretching to cause the transition. We show how stretching forces can be incorporated in lattice models of folding. For fast folding proteins, the analysis suggests a complex relation between the force dependence and the reaction coordinate for folding.

Protein folding mechanisms and the multidimensional folding funnel.

An important idea that emerges from the energy landscape theory of protein folding is that subtle global features of the protein landscape can profoundly affect the apparent mechanism of folding. The relationship between various characteristic temperatures in the phase diagrams and landmarks in the folding funnel at fixed temperatures can be used to classify different folding behaviors. The one-dimensional picture of a folding funnel classifies folding kinetics into four basic scenarios, depending on the relative location of the thermodynamic barrier and the glass transition as a function of a single-order parameter. However, the folding mechanism may not always be quantitatively described by a single-order parameter. Several other order parameters, such as degree of secondary structure formation, collapse and topological order, are needed to establish the connection between minimalist models and proteins in the laboratory. In this article we describe a simple multidimensional funnel based on two-order parameters that measure the degree of collapse and topological order. The appearance of several different "mechanisms" is illustrated by analyzing lattice models with different potentials and sequences with different degrees of design. In most cases, the two-dimensional analysis leads to a classification of mechanisms totally in keeping with the one-dimensional scheme, but a topologically distinct scenario of fast folding with traps also emerges. The nature of traps depends on the relative location of the glass transition surface and the thermodynamic barrier in the multidimensional funnel.

Protein folding funnels: the nature of the transition state ensemble.

BACKGROUND: Energy landscape theory predicts that the folding funnel for a small fast-folding alpha-helical protein will have a transition state half-way to the native state. Estimates of the position of the transition state along an appropriate reaction coordinate can be obtained from linear free energy relationships observed for folding and unfolding rate constants as a function of denaturant concentration. The experimental results of Huang and Oas for lambda repressor, Fersht and collaborators for C12, and Gray and collaborators for cytochrome c indicate a free energy barrier midway between the folded and unfolded regions. This barrier arises from an entropic bottleneck for the folding process. RESULTS: In keeping with the experimental results, lattice simulations based on the folding funnel description show that the transition state is not just a single conformation, but rather an ensemble of a relatively large number of configurations that can be described by specific values of one or a few order parameters (e.g. the fraction of native contacts). Analysis of this transition state or bottleneck region from our lattice simulations and from atomistic models for small alpha-helical proteins by Boczko and Brooks indicates a broad distribution for native contact participation in the transition state ensemble centered around 50%. Importantly, however, the lattice-simulated transition state ensemble does include some particularly hot contacts, as seen in the experiments, which have been termed by others a folding nucleus. CONCLUSIONS: Linear free energy relations provide a crude spectroscopy of the transition state, allowing us to infer the values of a reaction coordinate based on the fraction of native contacts. This bottleneck may be thought of as a collection of delocalized nuclei where different native contacts will have different degrees of participation. The agreement between the experimental results and the theoretical predictions provides strong support for the landscape analysis.

Toward an outline of the topography of a realistic protein-folding funnel.

Experimental information on the structure and dynamics of molten globules gives estimates for the energy landscape's characteristics for folding highly helical proteins, when supplemented by a theory of the helix-coil transition in collapsed heteropolymers. A law of corresponding states relating simulations on small lattice models to real proteins possessing many more degrees of freedom results. This correspondence reveals parallels between "minimalist" lattice results and recent experimental results for the degree of native character of the folding transition state and molten globule and also pinpoints the needs of further experiments.

Funnels, pathways, and the energy landscape of protein folding: a synthesis.

The understanding, and even the description of protein folding is impeded by the complexity of the process. Much of this complexity can be described and understood by taking a statistical approach to the energetics of protein conformation, that is, to the energy landscape. The statistical energy landscape approach explains when and why unique behaviors, such as specific folding pathways, occur in some proteins and more generally explains the distinction between folding processes common to all sequences and those peculiar to individual sequences. This approach also gives new, quantitative insights into the interpretation of experiments and simulations of protein folding thermodynamics and kinetics. Specifically, the picture provides simple explanations for folding as a two-state first-order phase transition, for the origin of metastable collapsed unfolded states and for the curved Arrhenius plots observed in both laboratory experiments and discrete lattice simulations. The relation of these quantitative ideas to folding pathways, to uniexponential vs. multiexponential behavior in protein folding experiments and to the effect of mutations on folding is also discussed. The success of energy landscape ideas in protein structure prediction is also described. The use of the energy landscape approach for analyzing data is illustrated with a quantitative analysis of some recent simulations, and a qualitative analysis of experiments on the folding of three proteins. The work unifies several previously proposed ideas concerning the mechanism protein folding and delimits the regions of validity of these ideas under different thermodynamic conditions.