MSstatsShiny: A GUI for Versatile, Scalable, and Reproducible Statistical Analyses of Quantitative Proteomic Experiments.

Liquid chromatography coupled with bottom-up mass spectrometry (LC-MS/MS)-based proteomics is a versatile technology for identifying and quantifying proteins in complex biological mixtures. Postidentification, analysis of changes in protein abundances between conditions requires increasingly complex and specialized statistical methods. Many of these methods, in particular the family of open-source Bioconductor packages MSstats, are implemented in a coding language such as R. To make the methods in MSstats accessible to users with limited programming and statistical background, we have created MSstatsShiny, an R-Shiny graphical user interface (GUI) integrated with MSstats, MSstatsTMT, and MSstatsPTM. The GUI provides a point and click analysis pipeline applicable to a wide variety of proteomics experimental types, including label-free data-dependent acquisitions (DDAs) or data-independent acquisitions (DIAs), or tandem mass tag (TMT)-based TMT-DDAs, answering questions such as relative changes in the abundance of peptides, proteins, or post-translational modifications (PTMs). To support reproducible research, the application saves user's selections and builds an R script that programmatically recreates the analysis. MSstatsShiny can be installed locally via Github and Bioconductor, or utilized on the cloud at www.msstatsshiny.com. We illustrate the utility of the platform using two experimental data sets (MassIVE IDs MSV000086623 and MSV000085565).

p53 Loss in Breast Cancer Leads to Myc Activation, Increased Cell Plasticity, and Expression of a Mitotic Signature with Prognostic Value.

Loss of p53 function is invariably associated with cancer. Its role in tumor growth was recently linked to its effects on cancer stem cells (CSCs), although the underlying molecular mechanisms remain unknown. Here, we show that c-myc is a transcriptional target of p53 in mammary stem cells (MaSCs) and is activated in breast tumors as a consequence of p53 loss. Constitutive Myc expression in normal mammary cells leads to increased frequency of MaSC symmetric divisions, extended MaSC replicative-potential, and MaSC-reprogramming of progenitors, whereas Myc activation in breast cancer is necessary and sufficient to maintain the expanding pool of CSCs. Concomitant p53 loss and Myc activation trigger the expression of 189 mitotic genes, which identify patients at high risk of mortality and relapse, independently of other risk factors. Altogether, deregulation of the p53:Myc axis in mammary tumors increases CSC content and plasticity and is a critical determinant of tumor growth and clinical aggressiveness.

The tumor suppressor p53 regulates polarity of self-renewing divisions in mammary stem cells.

Stem-like cells may be integral to the development and maintenance of human cancers. Direct proof is still lacking, mainly because of our poor understanding of the biological differences between normal and cancer stem cells (SCs). Using the ErbB2 transgenic model of breast cancer, we found that self-renewing divisions of cancer SCs are more frequent than their normal counterparts, unlimited and symmetric, thus contributing to increasing numbers of SCs in tumoral tissues. SCs with targeted mutation of the tumor suppressor p53 possess the same self-renewal properties as cancer SCs, and their number increases progressively in the p53 null premalignant mammary gland. Pharmacological reactivation of p53 correlates with restoration of asymmetric divisions in cancer SCs and tumor growth reduction, without significant effects on additional cancer cells. These data demonstrate that p53 regulates polarity of cell division in mammary SCs and suggest that loss of p53 favors symmetric divisions of cancer SCs, contributing to tumor growth.