Anne Geske Lindhard Christensen

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

The CD44hi 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 CD44hi 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 CD44hi/CD24− mesenchymal-like basal B cells, the CD44hi/CD24lo 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

BackgroundOver 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.ResultsWe 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.ConclusionWith 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 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 β‐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/β‐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