33 research outputs found

    Utility of patient-derived lymphoblastoid cell lines as an ex vivo capecitabine sensitivity prediction model for breast cancer patients.

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    Capecitabine is commonly used in treating breast cancer; however, therapeutic response varies among patients and there is no clinically validated model to predict individual outcomes. Here, we investigated whether drug sensitivity quantified in ex vivo patients' blood-derived cell lines can predict response to capecitabine in vivo. Lymphoblastoid cell lines (LCLs) were established from a cohort of metastatic breast cancer patients (n = 53) who were prospectively monitored during treatment with single agent capecitabine at 2000 mg/m2/day. LCLs were treated with increasing concentrations of 5'-DFUR, a major capecitabine metabolite, to assess patients' ex vivo sensitivity to this drug. Subsequently, ex vivo phenotype was compared to observed patient disease response and drug induced-toxicities. We acquired an independent cohort of breast cancer cell lines and LCLs derived from the same donors from ATCC, compared their sensitivity to 5'-DFUR. As seen in the patient population, we observed large inter-individual variability in response to 5'-DFUR treatment in patient-derived LCLs. Patients whose LCLs were more sensitive to 5'-DFUR had a significantly longer median progression free survival (9-month vs 6-month, log rank p-value = 0.017). In addition, this significant positive correlation for 5'-DFUR sensitivity was replicated in an independent cohort of 8 breast cancer cell lines and LCLs derived from the same donor. Our data suggests that at least a portion of the individual sensitivity to capecitabine is shared between germline tissue and tumor tissue. It also supports the utility of patient-derived LCLs as a predictive model for capecitabine treatment efficacy in breast cancer patients

    Association between alcohol and cardiovascular disease: Mendelian randomisation analysis based on individual participant data.

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    OBJECTIVE: To use the rs1229984 variant in the alcohol dehydrogenase 1B gene (ADH1B) as an instrument to investigate the causal role of alcohol in cardiovascular disease. DESIGN: Mendelian randomisation meta-analysis of 56 epidemiological studies. PARTICIPANTS: 261 991 individuals of European descent, including 20 259 coronary heart disease cases and 10 164 stroke events. Data were available on ADH1B rs1229984 variant, alcohol phenotypes, and cardiovascular biomarkers. MAIN OUTCOME MEASURES: Odds ratio for coronary heart disease and stroke associated with the ADH1B variant in all individuals and by categories of alcohol consumption. RESULTS: Carriers of the A-allele of ADH1B rs1229984 consumed 17.2% fewer units of alcohol per week (95% confidence interval 15.6% to 18.9%), had a lower prevalence of binge drinking (odds ratio 0.78 (95% CI 0.73 to 0.84)), and had higher abstention (odds ratio 1.27 (1.21 to 1.34)) than non-carriers. Rs1229984 A-allele carriers had lower systolic blood pressure (-0.88 (-1.19 to -0.56) mm Hg), interleukin-6 levels (-5.2% (-7.8 to -2.4%)), waist circumference (-0.3 (-0.6 to -0.1) cm), and body mass index (-0.17 (-0.24 to -0.10) kg/m(2)). Rs1229984 A-allele carriers had lower odds of coronary heart disease (odds ratio 0.90 (0.84 to 0.96)). The protective association of the ADH1B rs1229984 A-allele variant remained the same across all categories of alcohol consumption (P=0.83 for heterogeneity). Although no association of rs1229984 was identified with the combined subtypes of stroke, carriers of the A-allele had lower odds of ischaemic stroke (odds ratio 0.83 (0.72 to 0.95)). CONCLUSIONS: Individuals with a genetic variant associated with non-drinking and lower alcohol consumption had a more favourable cardiovascular profile and a reduced risk of coronary heart disease than those without the genetic variant. This suggests that reduction of alcohol consumption, even for light to moderate drinkers, is beneficial for cardiovascular health

    Identifying and validating a combined mRNA and microRNA signature in response to imatinib treatment in a chronic myeloid leukemia cell line.

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    Imatinib, a targeted tyrosine kinase inhibitor, is the gold standard for managing chronic myeloid leukemia (CML). Despite its wide application, imatinib resistance occurs in 20-30% of individuals with CML. Multiple potential biomarkers have been identified to predict imatinib response; however, the majority of them remain externally uncorroborated. In this study, we set out to systematically identify gene/microRNA (miRNA) whose expression changes are related to imatinib response. Through a Gene Expression Omnibus search, we identified two genome-wide expression datasets that contain expression changes in response to imatinib treatment in a CML cell line (K562): one for mRNA and the other for miRNA. Significantly differentially expressed transcripts/miRNAs post imatinib treatment were identified from both datasets. Three additional filtering criteria were applied 1) miRbase/miRanda predictive algorithm; 2) opposite direction of imatinib effect for genes and miRNAs; and 3) literature support. These criteria narrowed our candidate gene-miRNA to a single pair: IL8 and miR-493-5p. Using PCR we confirmed the significant up-regulation and down-regulation of miR-493-5p and IL8 by imatinib treatment, respectively in K562 cells. In addition, IL8 expression was significantly down-regulated in K562 cells 24 hours after miR-493-5p mimic transfection (p = 0.002). Furthermore, we demonstrated significant cellular growth inhibition after IL8 inhibition through either gene silencing or by over-expression of miR-493-5p (p = 0.0005 and p = 0.001 respectively). The IL8 inhibition also further sensitized K562 cells to imatinib cytotoxicity (p < 0.0001). Our study combined expression changes in transcriptome and miRNA after imatinib exposure to identify a potential gene-miRNA pair that is a critical target in imatinib response. Experimental validation supports the relationships between IL8 and miR-493-5p and between this gene-miRNA pair and imatinib sensitivity in a CML cell line. Our data suggests integrative analysis of multiple omic level data may provide new insight into biomarker discovery as well as mechanisms of imatinib resistance

    Integrative “Omic” Analysis for Tamoxifen Sensitivity through Cell Based Models

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    <div><p>It has long been observed that tamoxifen sensitivity varies among breast cancer patients. Further, ethnic differences of tamoxifen therapy between Caucasian and African American have also been reported. Since most studies have been focused on Caucasian people, we sought to comprehensively evaluate genetic variants related to tamoxifen therapy in African-derived samples. An integrative “omic” approach developed by our group was used to investigate relationships among endoxifen (an active metabolite of tamoxifen) sensitivity, SNP genotype, mRNA and microRNA expressions in 58 HapMap YRI lymphoblastoid cell lines. We identified 50 SNPs that associate with cellular sensitivity to endoxifen through their effects on 34 genes and 30 microRNA expression. Some of these findings are shared in both Caucasian and African samples, while others are unique in the African samples. Among gene/microRNA that were identified in both ethnic groups, the expression of <i>TRAF1</i> is also correlated with tamoxifen sensitivity in a collection of 44 breast cancer cell lines. Further, knock-down <i>TRAF1</i> and over-expression of hsa-let-7i confirmed the roles of hsa-let-7i and <i>TRAF1</i> in increasing tamoxifen sensitivity in the ZR-75-1 breast cancer cell line. Our integrative omic analysis facilitated the discovery of pharmacogenomic biomarkers that potentially affect tamoxifen sensitivity.</p></div

    Biological consequences of <i>IL8</i> inhibition.

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    <p>(<b>A</b>) <i>IL8</i> silencing through siRNA and miR-493-5p mimic resulted in significantly slower cellular proliferation as measured by CellTiter-Glo at 48 hours. (*p<0.05, N = 6). Relative cell growth was calculated by normalizing fluorescence indexes of each time point to the 0 hour control. (<b>B</b>) Cellular response to imatinib treatment curves. Cellular response to imatinib was measured using CellTiter-Glo. p<0.0001 by two way ANOVA, N = 6. Percent survival was calculated by normalizing fluorescence indexes of imatinib treated cells to cells treated with vehicle and plotting on a log(2) scale.</p

    12 predicted imatinib response gene-miRNA pairs based on GEO data.

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    <p>Functional experiments were conducted on the bolded gene/miR pair.</p><p>12 predicted imatinib response gene-miRNA pairs based on GEO data.</p
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