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Understanding How the p53 Gene Network Controls the Notorious Behavior of Cancer Cells

Research Summary

Joaquín Espinosa investigates the p53 tumor-suppressor gene network, with the goal of designing novel therapeutic strategies for selective elimination of cancer cells.

A tumor is a Darwinian cosmos. Cancer is driven by cumulative mutations that confer a selective advantage in terms of growth and invasiveness to cells. Because of the stochastic nature of mutations and the underlying genetic variation among individuals, every cancer is as unique as the patient who suffers it. This is painfully evident in the clinic, where patients carrying seemingly identical tumors respond very differently to the same therapy. I want to understand the molecular mechanisms driving this variability and translate this knowledge into more efficient therapies. To achieve this, my research team is embarking on an ambitious dissection of the p53 tumor-suppressor gene network.

Genes are not soloists; rather, they form networks. Recent studies in model organisms provide an updated view of gene networks where flexibility, degeneracy, and redundancy are the norm. This is obvious in cancer. Mutations in genes acting in different networks can lead to acquisition of the same malignant trait. Similar tumors may respond differently to a drug that inhibits a single gene product, which results in various outcomes from patient to patient. On the other hand, multiple mutations in the same or different networks act synergistically to promote cancer development, and these combinations also vary among patients. Therefore, the future of cancer therapeutics lies in personalized, combinatorial strategies. These advanced therapies will, however, require a deep understanding of gene networks relevant to cancer.

The most commonly mutated tumor-suppressor gene is p53. Despite thousands of publications over three decades of research, there is still much that is not known about p53. In particular, one key question remains unanswered: What determines the cellular response to p53 activation? Upon activation by potentially oncogenic stimuli, p53 can orchestrate cellular events as contrary as cell cycle arrest and apoptosis. Deciphering the mechanisms driving this pleiotropy is of paramount importance in the clinical arena, where the apoptotic potential of p53 could be exploited for selective elimination of cancer cells. Many current therapeutic strategies rely on p53, one of the most potent apoptotic factors discovered so far, for efficacy. On the other hand, activation of p53-dependent apoptosis in healthy tissues by chemotherapy or radiation causes many undesired side effects. Acting as a transcription factor, p53 can induce expression of multiple components of the extrinsic and intrinsic apoptotic pathways; however, p53 kills only in specific scenarios.

How is the choice between life and death after p53 activation defined at the molecular level? Many efforts have been invested in this question, but we have not yet reached a satisfactory answer. The p53 molecule has been studied in detail, but the p53 network as a whole remains poorly understood. In our current view, the p53 network contains two operationally defined subnetworks with antagonistic functions: the "survival module" and the "death module." Past research demonstrates that these modules adopt cell-type- and stimulus-specific configurations. For example, p53-dependent cell cycle arrest is mediated mostly by the p53 target genes p21 and 14-3-3σ, which synergistically attenuate p53-dependent apoptosis. However, ablation of p21 and 14-3-3σ does not suffice to drive cells into full-fledged apoptosis upon p53 activation, thus revealing the existence of additional survival factors. On the other hand, ablation of the p53 target genes BAX and PUMA abolishes p53-dependent apoptosis almost completely, but full induction of these genes by endogenous p53 is not sufficient to provoke cell death, which reveals the presence of other important components of the death module.

I propose that the mind-boggling phenomenology attached to p53 can be unraveled via systematic analyses of the survival and death modules and its alternative configurations. To reach this level of understanding, my team is developing the following projects:

1. We are using genetic screens in human cells to identify novel components of distinct functional modules within the p53 network. Using genome-wide short hairpin (shRNA) libraries, we are analyzing the role of every human gene in p53-dependent cell cycle arrest versus apoptosis. We hypothesize that p53 may promote survival or death by different means in different cell types. For example, PUMA may be required for p53-dependent apoptosis in some, but not all, cancer cell types. Conversely, p21 may contribute to survival only in some scenarios. Entire screens are repeated in multiple cell types to discriminate constitutive from facultative components of the two modules. Upon completion, this project will produce a detailed genetic blueprint of the p53 network.

2. We are using functional proteomics to elucidate cell-type- and stimulus-specific configurations of the p53 network. Using quantitative proteomics techniques, we are identifying differences in the proteome between cells bound to undergo p53-dependent cell cycle arrest versus p53-dependent apoptosis. We employ organelle partitioning, phosphopeptide enrichment, and immunopurification methods to answer specific questions: (1) Are there proteins that accumulate differentially in the nucleus, mitochondria, cytosol and at the membranes of cells undergoing p53-dependent arrest versus apoptosis? (2) Are there fate-specific phosphorylation events within the network? (3) How does the set of p53 interactors change in a cell-type- and stimulus-specific manner? Upon completion, this project will produce a detailed picture of the protein plane of the p53 network.

3. We are deciphering the mechanisms by which alternative p53 network configurations determine cell fate choice in response to p53 activation. Using bioinformatics, we are integrating genetics and proteomics data sets into models of the p53 network that allow us to formulate precise hypotheses and embark on true mechanistic studies. We are dissecting how different network configurations are established at the transcriptional, post-transcriptional, and post-translational levels. In these mechanistic studies, we are testing the role of novel p53 cofactors in transcriptional activation of genes within the survival and death modules, investigating how different combinations of BH3-only apoptotic proteins assemble at the mitochondria during cell cycle arrest versus apoptosis, and defining the impact of components of the cell cycle machinery on the apoptotic apparatus.

4. We are determining the impact of alternative configurations of the p53 network in cancer development and in response to p53-based therapies. Because of technical constraints, the projects described above are carried out in vitro, in cell cultures. We will bridge the gap between the Petri dish and the clinic by using animal models of cancer and molecular diagnostics to determine if different configurations of the p53 network alter the ability of cancer cells to form tumors and respond to p53-based therapies. Using xenograft models, we will analyze how precise perturbations in the p53 network affect tumor volume, invasiveness, angiogenic capacity, metastatic potential, and response to drugs reliant on the p53 apoptotic pathway. We will employ molecular diagnostic tools on archived human tissue samples to determine if specific p53 network configurations correlate with tumor type, histopathological grade, and outcome to treatment. In particular, we will test the hypothesis that high expression of components of the survival module or low expression/loss-of-function mutation in components of the death module confers resistance to p53-based therapies.

As of May 30, 2012

Scientist Profile

Early Career Scientist
University of Colorado at Boulder
Cancer Biology, Molecular Biology