Elucidation of Altered Pathways in Tumor-Initiating Cells of Triple-Negative Breast Cancer: A Useful Cell Model System for Drug Screening.

A limited number of cancer cells within a tumor are thought to have self-renewing and tumor-initiating capabilities that produce the remaining cancer cells in a heterogeneous tumor mass. Elucidation of central pathways preferentially used by tumor-initiating cells/cancer stem cells (CSCs) may allow their exploitation as potential cancer therapy targets. We used single cell cloning to isolate and characterize four isogenic cell clones from a triple-negative breast cancer cell line; two exhibited mesenchymal-like and two epithelial-like characteristics. Within these pairs, one, but not the other, resulted in tumors in immunodeficient NOD/Shi-scid/IL-2 Rγ null mice and efficiently formed mammospheres. Quantitative proteomics and phosphoproteomics were used to map signaling pathways associated with the tumor-initiating ability. Signaling associated with apoptosis was suppressed in tumor-initiating versus nontumorigenic counterparts with pro-apoptotic proteins, such as Bcl2-associated agonist of cell death (BAD), FAS-associated death domain protein (FADD), and myeloid differentiation primary response protein (MYD88), downregulated in tumor-initiating epithelial-like cells. Functional studies confirmed significantly lower apoptosis in tumor-initiating versus nontumorigenic cells. Moreover, central pathways, including ß-catenin and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB)-related signaling, exhibited increased activation in the tumor-initiating cells. To evaluate the CSC model as a tool for drug screening, we assessed the effect of separately blocking NF-κB and Wnt/ß-catenin signaling and found markedly reduced mammosphere formation, particularly for tumor-initiating cells. Similar reduction was also observed using patient-derived primary cancer cells. Furthermore, blocking NF-κB signaling in mice transplanted with tumor-initiating cells significantly reduced tumor outgrowth. Our study demonstrates that suppressed apoptosis, activation of pathways associated with cell viability, and CSCs are the major differences between tumor-initiating and nontumorigenic cells independent of their epithelial-like/mesenchymal-like phenotype. These altered pathways may provide targets for future drug development to eliminate CSCs, and the cell model may be a useful tool in such drug screenings. Stem Cells 2017;35:1898-1912.

Functional heterogeneity within the CD44 high human breast cancer stem cell-like compartment reveals a gene signature predictive of distant metastasis.

The CD44(hi) compartment in human breast cancer is enriched in tumor-initiating cells; however, the functional heterogeneity within this subpopulation remains poorly defined. We used a triple-negative breast cancer cell line with a known bilineage phenotype to isolate and clone CD44(hi) single cells that exhibited mesenchymal/basal B and luminal/basal A features, respectively. Herein, we demonstrate in this and other triple-negative breast cancer cell lines that, rather than CD44(hi)/CD24(-) mesenchymal-like basal B cells, the CD44(hi)/CD24(lo) epithelioid basal A cells retained classic cancer stem cell features, such as tumor-initiating capacity in vivo, mammosphere formation and resistance to standard chemotherapy. These results complement previous findings using oncogene-transformed normal mammary cells showing that only cell clones with a mesenchymal phenotype exhibit cancer stem cell features. Further, we performed comparative quantitative proteomic and gene array analyses of these cells and identified potential novel markers of breast cancer cells with tumor-initiating features, such as lipolysis-stimulated lipoprotein receptor (LSR), RAB25, S100A14 and mucin 1 (MUC1), as well as a novel 31-gene signature capable of predicting distant metastasis in cohorts of estrogen receptor-negative human breast cancers. These findings strongly favor functional heterogeneity in the breast cancer cell compartment and hold promise for further refinements of prognostic marker profiling. Our work confirms that, in addition to cancer stem cells with mesenchymal-like morphology, those tumor-initiating cells with epithelial-like morphology should also be the focus of drug development.

KeyPathwayMiner 4.0: condition-specific pathway analysis by combining multiple omics studies and networks with Cytoscape.

BACKGROUND: Over the last decade network enrichment analysis has become popular in computational systems biology to elucidate aberrant network modules. Traditionally, these approaches focus on combining gene expression data with protein-protein interaction (PPI) networks. Nowadays, the so-called omics technologies allow for inclusion of many more data sets, e.g. protein phosphorylation or epigenetic modifications. This creates a need for analysis methods that can combine these various sources of data to obtain a systems-level view on aberrant biological networks. RESULTS: We present a new release of KeyPathwayMiner (version 4.0) that is not limited to analyses of single omics data sets, e.g. gene expression, but is able to directly combine several different omics data types. Version 4.0 can further integrate existing knowledge by adding a search bias towards sub-networks that contain (avoid) genes provided in a positive (negative) list. Finally the new release now also provides a set of novel visualization features and has been implemented as an app for the standard bioinformatics network analysis tool: Cytoscape. CONCLUSION: With KeyPathwayMiner 4.0, we publish a Cytoscape app for multi-omics based sub-network extraction. It is available in Cytoscape's app store http://apps.cytoscape.org/apps/keypathwayminer or via http://keypathwayminer.mpi-inf.mpg.de.

Elucidation of epithelial-mesenchymal transition-related pathways in a triple-negative breast cancer cell line model by multi-omics interactome analysis.

In life sciences, and particularly biomedical research, linking aberrant pathways exhibiting phenotype-specific alterations to the underlying physical condition or disease is an ongoing challenge. Computationally, a key approach for pathway identification is data enrichment, combined with generation of biological networks. This allows identification of intrinsic patterns in the data and their linkage to a specific context such as cellular compartments, diseases or functions. Identification of aberrant pathways by traditional approaches is often limited to biological networks based on either gene expression, protein expression or post-translational modifications. To overcome single omics analysis, we developed a set of computational methods that allow a combined analysis of data collections from multiple omics fields utilizing hybrid interactome networks. We apply these methods to data obtained from a triple-negative breast cancer cell line model, combining data sets of gene and protein expression as well as protein phosphorylation. We focus on alterations associated with the phenotypical differences arising from epithelial-mesenchymal transition in two breast cancer cell lines exhibiting epithelial-like and mesenchymal-like morphology, respectively. Here we identified altered protein signaling activity in a complex biologically relevant network, related to focal adhesion and migration of breast cancer cells. We found dysregulated functional network modules revealing altered phosphorylation-dependent activity in concordance with the phenotypic traits and migrating potential of the tested model. In addition, we identified Ser267 on zyxin, a protein coupled to actin filament polymerization, as a potential in vivo phosphorylation target of cyclin-dependent kinase 1.

Serotonin regulates C. elegans fat and feeding through independent molecular mechanisms.

We investigated serotonin signaling in C. elegans as a paradigm for neural regulation of energy balance and found that serotonergic regulation of fat is molecularly distinct from feeding regulation. Serotonergic feeding regulation is mediated by receptors whose functions are not required for fat regulation. Serotonergic fat regulation is dependent on a neurally expressed channel and a G protein-coupled receptor that initiate signaling cascades that ultimately promote lipid breakdown at peripheral sites of fat storage. In turn, intermediates of lipid metabolism generated in the periphery modulate feeding behavior. These findings suggest that, as in mammals, C. elegans feeding behavior is regulated by extrinsic and intrinsic cues. Moreover, obesity and thinness are not solely determined by feeding behavior. Rather, feeding behavior and fat metabolism are coordinated but independent responses of the nervous system to the perception of nutrient availability.