Mutant p53: Multiple Mechanisms Define Biologic Activity in Cancer

The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.

Although it is increasingly evident that cancer is influenced by signals emanating from tumor stroma, little is known regarding how changes in stromal gene expression affect epithelial tumor progression. We used laser capture microdissection to compare gene expression profiles of tumor stroma from 53 primary breast tumors and derived signatures strongly associated with clinical outcome. We present a new stroma-derived prognostic predictor (SDPP) that stratifies disease outcome independently of standard clinical prognostic factors and published expression-based predictors. The SDPP predicts outcome in several published whole tumor-derived expression data sets, identifies poor-outcome individuals from multiple clinical subtypes, including lymph node-negative tumors, and shows increased accuracy with respect to previously published predictors, especially for HER2-positive tumors. Prognostic power increases substantially when the predictor is combined with existing outcome predictors. Genes represented in the SDPP reveal the strong prognostic capacity of differential immune responses as well as angiogenic and hypoxic responses, highlighting the importance of stromal biology in tumor progression.

The p53 tumor suppressor gene is commonly altered in human tumors, predominantly through missense mutations that result in accumulation of mutant p53 protein. These mutations may confer dominant-negative or gain-of-function properties to p53. To ascertain the physiological effects of p53 point mutation, the structural mutant p53R172H and the contact mutant p53R270H (codons 175 and 273 in humans) were engineered into the endogenous p53 locus in mice. p53R270H/+ and p53R172H/+ mice are models of Li-Fraumeni Syndrome; they developed allele-specific tumor spectra distinct from p53+/- mice. In addition, p53R270H/- and p53R172H/- mice developed novel tumors compared to p53-/- mice, including a variety of carcinomas and more frequent endothelial tumors. Dominant effects that varied by allele and function were observed in primary cells derived from p53R270H/+ and p53R172H/+ mice. These results demonstrate that point mutant p53 alleles expressed under physiological control have enhanced oncogenic potential beyond the simple loss of p53 function.