Functional oncogene signatures guide rationally designed combination therapies to synergistically induce breast cancer cell death

Laboratory Models for Investigating Breast Cancer Therapy Resistance and Metastasis

While numerous therapies are highly efficacious in early-stage breast cancers and in particular subsets of breast cancers, therapeutic resistance and metastasis unfortunately arise in many patients. In many cases, tumors that are resistant to standard of care therapies, as well as tumors that have metastasized, are treatable but incurable with existing clinical strategies. Both therapy resistance and metastasis are multi-step processes during which tumor cells must overcome diverse environmental and selective hurdles. Mechanisms by which tumor cells achieve this are numerous and include acquisition of invasive and migratory capabilities, cell-intrinsic genetic and/or epigenetic adaptations, clonal selection, immune evasion, interactions with stromal cells, entering a state of dormancy or senescence, and maintaining self-renewal capacity. To overcome therapy resistance and metastasis in breast cancer, the ability to effectively model each of these mechanisms in the laboratory is essential. Herein we review historic and the current state-of-the-art laboratory model systems and experimental approaches used to investigate breast cancer metastasis and resistance to standard of care therapeutics. While each model system has inherent limitations, they have provided invaluable insights, many of which have translated into regimens undergoing clinical evaluation. We will discuss the limitations and advantages of a variety of model systems that have been used to investigate breast cancer metastasis and therapy resistance and outline potential strategies to improve experimental modeling to further our knowledge of these processes, which will be crucial for the continued development of effective breast cancer treatments.

A Review of DUSP26: Structure, Regulation and Relevance in Human Disease

Dual specificity phosphatases (DUSPs) play a crucial role in the regulation of intracellular signalling pathways, which in turn influence a broad range of physiological processes. DUSP malfunction is increasingly observed in a broad range of human diseases due to deregulation of key pathways, most notably the MAP kinase (MAPK) cascades. Dual specificity phosphatase 26 (DUSP26) is an atypical DUSP with a range of physiological substrates including the MAPKs. The residues that govern DUSP26 substrate specificity are yet to be determined; however, recent evidence suggests that interactions with a binding partner may be required for DUSP26 catalytic activity. DUSP26 is heavily implicated in cancer where, akin to other DUSPs, it displays both tumour-suppressive and -promoting properties, depending on the context. Here we review DUSP26 by evaluating its transcriptional patterns, protein crystallographic structure and substrate binding, as well as its physiological role(s) and binding partners, its role in human disease and the development of DUSP26 inhibitors.

Development and implementation of the SUM breast cancer cell line functional genomics knowledge base

Several years ago, the SUM panel of human breast cancer cell lines was developed, and these cell lines have been distributed to hundreds of labs worldwide. Our lab and others have developed extensive omics data sets from these cells. More recently, we performed genome-scale shRNA essentiality screens on the entire SUM line panel, as well as on MCF10A cells, MCF-7 cells, and MCF-7LTED cells. These gene essentiality data sets allowed us to perform orthogonal analyses that functionalize the otherwise descriptive genomic data obtained from traditional genomics platforms. To make these omics data sets available to users of the SUM lines, and to allow users to mine these data sets, we developed the SUM Breast Cancer Cell Line Knowledge Base. This knowledge base provides information on the derivation of each cell line, provides protocols for the proper maintenance of the cells, and provides a series of data mining tools that allow rapid identification of the oncogene signatures for each line, the enrichment of KEGG pathways with screen hit and gene expression data, an analysis of protein and phospho-protein expression for the cell lines, as well as a gene search tool and a functional-druggable signature tool. Recently, we expanded our database to include genomic data for an additional 27 commonly used breast cancer cell lines. Thus, the SLKBase provides users with deep insights into the biology of human breast cancer cell lines that can be used to develop strategies for the reverse engineering of individual breast cancer cell lines.

Eukaryotic initiation factor 4E-binding protein as an oncogene in breast cancer

BACKGROUND

Eukaryotic Initiation Factor 4E-Binding Protein (EIF4EBP1, 4EBP1) is overexpressed in many human cancers including breast cancer, yet the role of 4EBP1 in breast cancer remains understudied. Despite the known role of 4EBP1 as a negative regulator of cap-dependent protein translation, 4EBP1 is predicted to be an essential driving oncogene in many cancer cell lines in vitro, and can act as a driver of cancer cell proliferation. EIF4EBP1 is located within the 8p11-p12 genomic locus, which is frequently amplified in breast cancer and is known to predict poor prognosis and resistance to endocrine therapy.

METHODS

Here we evaluated the effect of 4EBP1 targeting using shRNA knock-down of expression of 4EBP1, as well as response to the mTORC targeted drug everolimus in cell lines representing different breast cancer subtypes, including breast cancer cells with the 8p11-p12 amplicon, to better define a context and mechanism for oncogenic 4EBP1.

RESULTS

Using a genome-scale shRNA screen on the SUM panel of breast cancer cell lines, we found 4EBP1 to be a strong hit in the 8p11 amplified SUM-44 cells, which have amplification and overexpression of 4EBP1. We then found that knock-down of 4EBP1 resulted in dramatic reductions in cell proliferation in 8p11 amplified breast cancer cells as well as in other luminal breast cancer cell lines, but had little or no effect on the proliferation of immortalized but non-tumorigenic human mammary epithelial cells. Kaplan-Meier analysis of EIF4EBP1 expression in breast cancer patients demonstrated that overexpression of this gene was associated with reduced relapse free patient survival across all breast tumor subtypes.

CONCLUSIONS

These results are consistent with an oncogenic role of 4EBP1 in luminal breast cancer and suggests a role for this protein in cell proliferation distinct from its more well-known role as a regulator of cap-dependent translation.

Personalized Cancer Care: Risk Prediction, Early Diagnosis, Progression, and Therapy

At the annual prestigious International Symposium of the Fritz-Bender Foundation, Munich, 18-20 May, 2016, researchers, clinicians, and students discussed the state of the art and future perspectives of genomic medicine in cancer. Genomic medicine (also known as precision medicine/oncology) should help clinicians to provide a more precise diagnosis and therapy in oncology for individual patients. The meeting focused on next-generation sequencing methods, analytical computational analysis of big data, and data mining on the way to translational and evidence-based medicine. The meeting covered the social and ethical impact of genomic medicine as well as news and views on antibody targeting of intracellular proteins, on the architecture of intracellular proteins and their impact on carcinogenesis, and on the adaptation of tumor therapy in due consideration of tumor evolution. Subheadings like "Genetic Profiling of Patients and Risk Prediction," "Molecular Profiling of Tumors and Metastases," "Tumor-Host Microenvironment Interaction and Metabolism," and "Targeted Therapy" were subsumed under the main heading of "Personalized Cancer Care."