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BackgroundOvarian cancer is the leading gynecologic cancer diagnosed in North America and because related symptoms are not disease specific, this often leads to late detection, an advanced disease state, and the need for chemotherapy. Ovarian cancer is frequently sensitive to chemotherapy at diagnosis but rapid development of drug resistance leads to disease progression and ultimately death in the majority of patients.ResultsWe have generated paclitaxel resistant ovarian cell lines from their corresponding native cell lines to determine driver mechanisms of drug resistance using gene expression arrays. These paclitaxel resistant ovarian cells demonstrate: (1) Increased IC50 for paclitaxel and docetaxel (10 to 75-fold) and cross-resistance to anthracyclines (2) Reduced cell apoptosis in the presence of paclitaxel (3) Gene depletion involving mitotic regulators BUB1 mitotic checkpoint serine/threonine kinase, cyclin BI (CCNB1), centromere protein E (CENPE), and centromere protein F (CENPF), and (4) Functional data validating gene depletion among mitotic regulators.ConclusionsWe have generated model systems to explore drug resistance in ovarian cancer, which have revealed a key pathway related to the spindle assembly checkpoint underlying paclitaxel resistance in ovarian cell lines.Electronic supplementary materialThe online version of this article (10.1186/s13048-018-0399-7) contains supplementary material, which is available to authorized users.

BackgroundDrug resistance in breast cancer is the major obstacle to effective treatment with chemotherapy. While upregulation of multidrug resistance genes is an important component of drug resistance mechanisms in vitro, their clinical relevance remains to be determined. Therefore, identifying pathways that could be targeted in the clinic to eliminate anthracycline-resistant breast cancer remains a major challenge.MethodsWe generated paired native and epirubicin-resistant MDA-MB-231, MCF7, SKBR3 and ZR-75-1 epirubicin-resistant breast cancer cell lines to identify pathways contributing to anthracycline resistance. Native cell lines were exposed to increasing concentrations of epirubicin until resistant cells were generated. To identify mechanisms driving epirubicin resistance, we used a complementary approach including gene expression analyses to identify molecular pathways involved in resistance, and small-molecule inhibitors to reverse resistance. In addition, we tested its clinical relevance in a BR9601 adjuvant clinical trial.ResultsCharacterisation of epirubicin-resistant cells revealed that they were cross-resistant to doxorubicin and SN-38 and had alterations in apoptosis and cell-cycle profiles. Gene expression analysis identified deregulation of histone H2A and H2B genes in all four cell lines. Histone deacetylase small-molecule inhibitors reversed resistance and were cytotoxic for epirubicin-resistant cell lines, confirming that histone pathways are associated with epirubicin resistance. Gene expression of a novel 18-gene histone pathway module analysis of the BR9601 adjuvant clinical trial revealed that patients with low expression of the 18-gene histone module benefited from anthracycline treatment more than those with high expression (hazard ratio 0.35, 95 % confidence interval 0.13–0.96, p = 0.042).ConclusionsThis study revealed a key pathway that contributes to anthracycline resistance and established model systems for investigating drug resistance in all four major breast cancer subtypes. As the histone modification can be targeted with small-molecule inhibitors, it represents a possible means of reversing clinical anthracycline resistance.Trial registrationClinicalTrials.gov identifier NCT00003012. Registered on 1 November 1999.Electronic supplementary materialThe online version of this article (doi:10.1186/s13058-016-0676-6) contains supplementary material, which is available to authorized users.

BackgroundTaxanes such as paclitaxel and docetaxel are used successfully to treat breast cancer, usually in combination with other agents. They interfere with microtubules causing cell cycle arrest; however, the mechanisms underlying the clinical effects of taxanes are yet to be fully elucidated.MethodsIsogenic paclitaxel resistant (PACR) MDA‒MB‒231, paclitaxel resistant ZR75‒1 and docetaxel resistant (DOCR) ZR75‒1 cell lines were generated by incrementally increasing taxane dose in native cell lines in vitro. We used aCGH analysis to identify mechanisms driving taxane resistance.ResultsTaxane resistant cell lines exhibited an 18-170 fold increased resistance to taxanes, with the ZR75-1 resistant cell lines also demonstrating cross resistance to anthracyclines. Paclitaxel treatment of native cells resulted in a G2/M block and a decrease in the G1 phase of the cell cycle. However, in the resistant cell lines, minimal changes were present. Functional network analysis revealed that the mitotic prometaphase was lost in the resistant cell lines.ConclusionThis study established a model system for examining taxane resistance and demonstrated that both MDR and mitosis represent common mechanism of taxane resistance.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2407-14-762) contains supplementary material, which is available to authorized users.

Background:Epidermal growth factor receptors contribute to breast cancer relapse during endocrine therapy. Substitution of aromatase inhibitors (AIs) may improve outcomes in HER-positive cancers.Methods:Tissue microarrays were constructed. Quantitative analysis of HER1, HER2, and HER3 was performed. Data were analysed relative to disease-free survival and treatment using outcomes at 2.75 and 6.5 years.Results:Among 4541 eligible samples, 4225 (93%) had complete HER1–3 data. Overall, 5% were HER1-positive, 13% HER2-positive, and 21% HER3-positive; 32% (n=1351) overexpressed at least one HER receptor. In the HER1–3-negative subgroup, the hazard ratio (HR) for upfront exemestane vs tamoxifen at 2.75 years was 0.67 (95% confidence interval (CI), 0.52–0.87), in the HER1–3-positive subgroup, the HR was 1.15 (95% CI, 0.85–1.56). A prospectively planned treatment-by-marker analysis demonstrated a significant interaction between HER1–3 and treatment at 2.75 years (HR=0.58; 95% CI, 0.39–0.87; P=0.008), as confirmed by multivariate regression analysis adjusting for prognostic factors (HR=0.55; 95% CI, 0.36–0.85; P=0.005). This effect was time dependent.Conclusion:In the 2.75 years prior to switching patients initially treated with tamoxifen to exemestane, a significant treatment-by-marker effect exists between AI/tamoxifen treatment and HER1-3 expression, suggesting HER expression could be used to select appropriate endocrine treatment at diagnosis to prevent or delay early relapses.