sscMap: An extensible Java application for connecting small-molecule drugs using gene-expression signatures

Background: Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures. Results: This paper introduces sscMap (statistically significant connections' map), a Java application designed to undertake connectivity mapping tasks using the recently published method. The software is bundled with a default collection of reference gene-expression profiles based on the publicly available dataset from the Broad Institute Connectivity Map 02, which includes data from over 7000 Affymetrix microarrays, for over 1000 small-molecule compounds, and 6100 treatment instances in 5 human cell lines. In addition, the application allows users to add their custom collections of reference profiles and is applicable to a wide range of other 'omics technologies. Conclusions: The utility of sscMap is two fold. First, it serves to make statistically significant connections between a user-supplied gene signature and the 6100 core reference profiles based on the Broad Institute expanded dataset. Second, it allows users to apply the same improved method to custom-built reference profiles which can be added to the database for future referencing. The software can be freely downloaded from http://purl.oclc.org/NET/sscMapComment: 3 pages, 1 table, 1 eps figur

A novel aspirin prodrug inhibits NFκB activity and breast cancer stem cell properties

INTRODUCTION: Activation of cyclooxygenase (COX)/prostaglandin and nuclear factor κB (NFκB) pathways can promote breast tumor initiation, growth, and progression to drug resistance and metastasis. Thus, anti-inflammatory drugs have been widely explored as chemopreventive and antineoplastic agents. Aspirin (ASA), in particular, is associated with reduced breast cancer incidence but gastrointestinal toxicity has limited its usefulness. To improve potency and minimize toxicity, ASA ester prodrugs have been developed, in which the carboxylic acid of ASA is masked and ancillary pharmacophores can be incorporated. To date, the effects of ASA and ASA prodrugs have been largely attributed to COX inhibition and reduced prostaglandin production. However, ASA has also been reported to inhibit the NFκB pathway at very high doses. Whether ASA prodrugs can inhibit NFκB signaling remains relatively unexplored. METHODS: A library of ASA prodrugs was synthesized and screened for inhibition of NFκB activity and cancer stem-like cell (CSC) properties, an important PGE2-and NFκB-dependent phenotype of aggressive breast cancers. Inhibition of NFκB activity was determined by dual luciferase assay, RT-QPCR, p65 DNA binding activity and Western blots. Inhibition of CSC properties was determined by mammosphere growth, CD44(+)CD24(−)immunophenotype and tumorigenicity at limiting dilution. RESULTS: While we identified multiple ASA prodrugs that are capable of inhibiting the NFκB pathway, several were associated with cytotoxicity. Of particular interest was GTCpFE, an ASA prodrug with fumarate as the ancillary pharmacophore. This prodrug potently inhibits NFκB activity without innate cytotoxicity. In addition, GTCpFE exhibited selective anti-CSC activity by reducing mammosphere growth and the CD44(+)CD24(−)immunophenotype. Moreover, GTCpFE pre-treated cells were less tumorigenic and, when tumors did form, latency was increased and growth rate was reduced. Structure-activity relationships for GTCpFE indicate that fumarate, within the context of an ASA prodrug, is essential for anti-NFκB activity, whereas both the ASA and fumarate moieties contributed to attenuated mammosphere growth. CONCLUSIONS: These results establish GTCpFE as a prototype for novel ASA-and fumarate-based anti-inflammatory drugs that: (i) are capable of targeting CSCs, and (ii) may be developed as chemopreventive or therapeutic agents in breast cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12885-015-1868-7) contains supplementary material, which is available to authorized users

A simple and robust method for connecting small-molecule drugs using gene-expression signatures

Interaction of a drug or chemical with a biological system can result in a gene-expression profile or signature characteristic of the event. Using a suitably robust algorithm these signatures can potentially be used to connect molecules with similar pharmacological or toxicological properties. The Connectivity Map was a novel concept and innovative tool first introduced by Lamb et al to connect small molecules, genes, and diseases using genomic signatures [Lamb et al (2006), Science 313, 1929-1935]. However, the Connectivity Map had some limitations, particularly there was no effective safeguard against false connections if the observed connections were considered on an individual-by-individual basis. Further when several connections to the same small-molecule compound were viewed as a set, the implicit null hypothesis tested was not the most relevant one for the discovery of real connections. Here we propose a simple and robust method for constructing the reference gene-expression profiles and a new connection scoring scheme, which importantly allows the valuation of statistical significance of all the connections observed. We tested the new method with the two example gene-signatures (HDAC inhibitors and Estrogens) used by Lamb et al and also a new gene signature of immunosuppressive drugs. Our testing with this new method shows that it achieves a higher level of specificity and sensitivity than the original method. For example, our method successfully identified raloxifene and tamoxifen as having significant anti-estrogen effects, while Lamb et al's Connectivity Map failed to identify these. With these properties our new method has potential use in drug development for the recognition of pharmacological and toxicological properties in new drug candidates.Comment: 8 pages, 2 figures, and 2 tables; supplementary data supplied as a ZIP fil

Estrogenic effects of herbal medicines from Costa Rica used for the management of menopausal symptoms

Objective: Outcomes from the Women's Health Initiative have demonstrated adverse effects associated with hormone therapy and have prioritized the need to develop new alternative treatments for the management of menopause and osteoporosis. To this end, we have been investigating natural herbal medicines used by Costa Rican women to manage menopausal symptoms. Methods: Seventeen plant species were collected and extracted in Costa Rica. To establish possible mechanisms of action and to determine their potential future use for menopause or osteoporosis, we investigated the estrogenic activities of the herbal extracts in an estrogen-reporter gene estrogen receptor (ER) β-Chemically Activated Luciferase Expression assay in U2-OS cells and in reporter and endogenous gene assays in MCF-7 cells. Results: Six of the plant extracts bound to the ERs. Four of the six extracts stimulated reporter gene expression in the ER-β-Chemically Activated Luciferase Expression assay. All six extracts modulated expression of endogenous genes in MCF-7 cells, with four extracts acting as estrogen agonists and two extracts, Pimenta dioica and Smilax domingensis, acting as partial agonist/antagonists by enhancing estradiol-stimulated pS2 mRNA expression but reducing estradiol-stimulated PR and PTGES mRNA expression. Both P. dioica and S. domingensis induced a 2ERE-luciferase reporter gene in transient transfected MCF-7 cells, which was inhibited by the ER antagonist ICI 182,780. Conclusions: This work presents a plausible mechanism of action for many of the herbal medicines used by Costa Rican women to treat menopausal symptoms. However, it further suggests that studies of safety and efficacy are needed before these herbs should be used as alternative therapies to hormone therapy.UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones en Productos Naturales (CIPRONA

Estrogen receptor-β: why may it influence clinical outcome in estrogen receptor-α positive breast cancer?

In the previous issue of the journal, Lin and coworkers present data demonstrate that increased expression of estrogen receptor (ER)-β in ER-α-positive breast cancer cells antagonizes a defined group of ER-α/estrogen stimulated genes that are involved in cell cycle regulation and DNA replication. Similar expression patterns for these genes were found human ER-α positive breast tumors expressing higher levels or ER-β, and this correlated with better clinical outcome. The implications for these data, which suggest that ER-β is a positive actor and diagnostic marker for therapeutic outcome, are discussed

An Integrated Bioinformatics Approach Identifies Elevated Cyclin E2 Expression and E2F Activity as Distinct Features of Tamoxifen Resistant Breast Tumors

Approximately half of estrogen receptor (ER) positive breast tumors will fail to respond to endocrine therapy. Here we used an integrative bioinformatics approach to analyze three gene expression profiling data sets from breast tumors in an attempt to uncover underlying mechanisms contributing to the development of resistance and potential therapeutic strategies to counteract these mechanisms. Genes that are differentially expressed in tamoxifen resistant vs. sensitive breast tumors were identified from three different publically available microarray datasets. These differentially expressed (DE) genes were analyzed using gene function and gene set enrichment and examined in intrinsic subtypes of breast tumors. The Connectivity Map analysis was utilized to link gene expression profiles of tamoxifen resistant tumors to small molecules and validation studies were carried out in a tamoxifen resistant cell line. Despite little overlap in genes that are differentially expressed in tamoxifen resistant vs. sensitive tumors, a high degree of functional similarity was observed among the three datasets. Tamoxifen resistant tumors displayed enriched expression of genes related to cell cycle and proliferation, as well as elevated activity of E2F transcription factors, and were highly correlated with a Luminal intrinsic subtype. A number of small molecules, including phenothiazines, were found that induced a gene signature in breast cancer cell lines opposite to that found in tamoxifen resistant vs. sensitive tumors and the ability of phenothiazines to down-regulate cyclin E2 and inhibit proliferation of tamoxifen resistant breast cancer cells was validated. Our findings demonstrate that an integrated bioinformatics approach to analyze gene expression profiles from multiple breast tumor datasets can identify important biological pathways and potentially novel therapeutic options for tamoxifen-resistant breast cancers