880409f7-901f-4d68-8a81-e23285e46b5b - samples
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PROVIDER: EGAD00001005972 | EGA |
REPOSITORIES: EGA
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Project description:Pharmacogenomics is a key component of precision medicine. It promises to prevent adverse drug reactions and reduce ineffective treatment by individualizing the choice of drug and dose based on an individual’s genetic profile. The majority of commonly prescribed drugs are metabolized by a small set of Cytochrome P450 (CYP) enzymes. Currently, a subset of genetic biomarkers are used to categorize patients into predefined *-alleles to predict CYP450 enzyme activity. Yet, this approach cannot describe all genetic variability in drug response, with a large degree of unpredictability remaining. We have combined long-read PacBio sequencing with a neural network to improve phenotype prediction in pharmacogenetics.
For 566 breastcancer patients who have used the CYp2D6 substrate tamoxifen as adjuvant therapy, we have sequenced the full CYP2D6 locus using PacBio SMRT sequencing. CYP2D6 enzyme activity can be inferred from the tamoxifen metabolism by using the ratio between the metabolites endoxifen and desmethyltamoxifen (Metabolic ratio (MR)). This MR was used as a proxy for observed CYP2D6 enzyme activity and is regarded as the true phenotype. The PacBio sequencing + neural network approach explained 79% of the interindividual variability in CYP2D6 activity compared to 55% with the conventional approach.
| EGAS00001004224 | EGA
Project description:Background: Current reports suggest that a certain minimum plasma concentration of (Z)-endoxifen is required for breast cancer patient to benefit from tamoxifen therapy. A reliable prediction of which patients are at risk for insufficient exposure to (Z)-endoxifen would be relevant for optimizing treatment, e.g. by adjusting the dose, from the very beginning. The objective of this study was to search for new DNA variants that could be helpful in the preemptive prediction of impaired tamoxifen to endoxifen metabolism. Methods: The molecular ratio (MR) was defined as (Z)-endoxifen plasma concentration divided by the sum of concentrations of tamoxifen and other measured metabolites. The MR of 0.0146, previously delineated as corresponding to (Z)-endoxifen 6 ng/ml efficacy threshold level, was adopted as a cut-off value in a genome-wide association study (GWAS) comprising 287 breast cancer patients receiving tamoxifen 20 mg daily. Multivariate binary logistic regression was used for the pre-selection of variables that showed independent impact on MR and to develop models predictive for MR value below the threshold. Results: In total, 13 GWAS-selected single nucleotide polymorphisms (SNPs) located outside the CYP2D6 gene and two known CYP2D6 variants were significantly associated with the MR value below 0.0146. The strongest association was observed for rs8138080 in WBP2NL (p = 1.78 x 10-15). The minor allele of six SNPs was associated with a decreased risk of impaired tamoxifen metabolism. CYP2D6 genotype was found by Nagelkerke pseudo-R2 to explain 42.7% of a total variation observed in MR, while rs8138080 alone explained 33.7% of this variability. Two alternative models for MR prediction have been developed. The prediction accuracy of Model 1, including rs7245, rs6950784 and rs1320308 in addition to CYP2D6 genotype, was considerably higher than predictive performance of CYP2D6 genotype alone (AUC increase from 0.758 to 0.879). The AUC of 0.830 achieved for the Model 2, developed with the same three SNPs as in Model 1 and rs8138080 instead of CYP2D6 genotype, makes it an interesting, simplified alternative to the costly and time-consuming testing of full CYP2D6 genotype. Conclusions: The four novel SNPs, tested alone or in addition to CYP2D6 genotype, improved the prediction of impaired tamoxifen to endoxifen metabolism, allowing for adjustments in dosing regimen before the treatment begins.
2019-09-18 | GSE129162 | GEO
Project description:Purpose: Endocrine therapies, such as tamoxifen are commonly given to most patients with estrogen receptor (ER) alpha-positive breast carcinoma but are not indicated for persons with ERalpha-negative cancer. The factors responsible for response to tamoxifen in 5-10% of patients with ERalpha-negative tumors are not clear. The aim of the present study was to elucidate the biology and role of the second ER, ERbeta, in patients treated with adjuvant tamoxifen. Experimental Design: We investigated ERbeta by immunohistochemistry in 353 stage II primary breast tumors from patients treated with two years adjuvant tamoxifen, and generated gene expression profiles for a representative subset of 88 tumors. Results: ERbeta was associated with increased survival (distant disease-free survival, P=0.01; overall survival, P=0.22), and in particular within ERalpha-negative patients (P=0.003; P=0.04), but not in the ERalpha-positive subgroup (P=0.49; P=0.88). Lack of ERbeta conferred early relapse (hazard ratio, 14; 95% CI, 1.8-106; P=0.01) within the ERalpha-negative subgroup even after adjustment for other markers. ERalpha was an independent marker only within the ERbeta-negative tumors (hazard ratio, 0.44; 95% CI, 0.21-0.89; P=0.02). An ERbeta gene expression profile was identified and was markedly different from the ERalpha signature. Conclusion: Expression of ERbeta is an independent marker for favorable prognosis after adjuvant tamoxifen treatment in ERalpha-negative breast cancer patients, and involves a gene expression program distinct from ERalpha. These results may be highly clinically significant, because in the U.S. alone, approximately 10,000 women are diagnosed annually with ERalpha-negative/ERbeta-positive breast carcinoma and may benefit from adjuvant tamoxifen. Keywords: Disease state analysis
2007-04-01 | GSE6577 | GEO
Project description:Endocrine resistance in breast cancer is a major clinical problem with poorly understood mechanisms. Mass spectrometry-based proteomics of a clinically-relevant tamoxifen-resistant cell line model identified increased levels of minichromosome maintenance proteins (MCM), including MCM3, as central in cell cycle and DNA replication protein-protein interaction networks associated with tamoxifen resistance. Lowering MCM3 protein expression in tamoxifen-resistant cells restored tamoxifen sensitivity and altered phosphorylation of several cell cycle regulators, such as p53(Ser315, 33), CHK1(Ser317) and cdc25b(Ser323), suggesting that MCM3 activation of important cell cycle-associated proteins overcomes tamoxifen’s anti-proliferative effects. High MCM3 expression in primary tumor tissue from two independent cohorts of ER+ breast cancer patients receiving adjuvant tamoxifen mono-therapy was an independent prognostic marker significantly associated with a shorter recurrence-free survival.
2022-02-22 | PXD001087 | Pride
Project description:About one-third of oestrogen receptor alpha- positive breast cancer patients treated with tamoxifen relapse. Here we identify the nuclear receptor retinoic acid receptor alpha as a marker of tamoxifen resistance. Using quantitative mass spectrometry-based proteomics, we show that retinoic acid receptor alpha protein networks and levels differ in a tamoxifen-sensitive (MCF7) and a tamoxifen-resistant (LCC2) cell line. High intratumoural retinoic acid receptor alpha protein levels also correlate with reduced relapse-free survival in oestrogen receptor alpha-positive breast cancer patients treated with adjuvant tamoxifen solely. A similar retinoic acid receptor alpha expression pattern is seen in a comparable independent patient cohort. An oestrogen receptor alpha and retinoic acid receptor alpha ligand screening reveals that tamoxifen-resistant LCC2 cells have increased sensitivity to retinoic acid receptor alpha ligands and are less sensitive to oestrogen receptor alpha ligands compared with MCF7 cells. Our data indicate that retinoic acid receptor alpha may be a novel therapeutic target and a predictive factor for oestrogen receptor alpha-positive breast cancer patients treated with adjuvant tamoxifen. Peptide and protein identification data set 1: Peptide identification from the MALDI-TOF/TOF data was carried out using the Paragon algorithm in the ProteinPilot 2.0 software package (Applied Biosystems) 46. Default settings for a 4800 instrument were used (i.e., no manual settings for mass tolerance was given). The following parameters were selected in the analysis method: iTRAQ 4plex peptide labelled as sample type, MMTS as alkylating agent of cysteine, trypsin as digesting enzyme, 4800 as instrument, gel based ID and Urea denaturation as special factors, biological modifications as ID focus, and thorough ID as search effort. Peptide identification from the Q-TOF data was carried out using the Spectrum Mill Protein Identification software (Agilent). Data was extracted between MH+ 600 and 4000 Da (Agilent's definition). Scans with the same precursor m/z 90 sec, 0.05 m/z matching with a minimum of 20 peaks in MS2 were merged. Peptide and protein identification data set 2: Proteome discoverer 1.3 with sequest-percolator was used for protein identification. Precursor mass tolerance was set to 10 ppm and for fragments 0.8 Da and 0.02 Da were used for detection in the linear iontrap and the orbitrap, respectively. Oxidized methionine and phosphorylation on S,T and Y was set as dynamic modifications, and carbamidomethylation, N-terminal 8plex iTRAQ, and lysyl 8plex iTRAQ as fixed modifications. Spectra were matched to ensembl 68 limited to human protein sequences, and results were filtered to 1% FDR.
2013-07-24 | PXD000281 | Pride
Project description:Background: Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30-40% of ER+BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings. Results: We developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95%CI: 1.29-3.13; p=0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response. Conclusions: We have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen. Experiment Overall Design: dataset of microarray experiments from primary breast tumors of patients treated by Tamoxifen in adjuvant setting. No replicate, no reference sample.
2008-06-20 | E-GEOD-9195 | biostudies-arrayexpress
Project description:The primary objective is, first, the comparison of tamoxifen and anastrozole and, second, the comparison of zoledronate added to standard adjuvant therapy with controls according to disease-free survival (DFS) in premenopausal patients with non-metastatic breast cancer treated with tamoxifen or anastrozole. To assess whether zoledronate added to standard adjuvant therapy can decrease or even prevent bone loss in patients treated with hormonal blockade combined with an antiestrogen or aromatase inhibitor.
| 2026652 | ecrin-mdr-crc
Project description:The beneficial effect of the selective estrogen receptor (ER) modulator tamoxifen in the treatment and prevention of breast cancer is assumed to be through its ability to antagonize the stimulatory actions of estrogen, although tamoxifen can also have some estrogen-like agonist effects. Here, we report that, in addition to these mixed agonist/antagonist actions, tamoxifen can also selectively regulate a unique set of >60 genes, which are minimally regulated by estradiol (E2) or raloxifene in ERalpha-positive MCF-7 human breast cancer cells. This gene regulation by tamoxifen is mediated by ERalpha and reversed by E2 or ICI 182,780. Introduction of ERbeta into MCF-7 cells reverses tamoxifen action on approximately 75% of these genes. To examine whether these genes might serve as markers of tamoxifen sensitivity and/or the development of resistance, their expression level was examined in breast cancers of women who had received adjuvant therapy with tamoxifen. High expression of two of the tamoxifen-stimulated genes, YWHAZ/14-3-3z and LOC441453, was found to correlate significantly with disease recurrence following tamoxifen treatment in women with ER-positive cancers and hence seem to be markers of a poor prognosis. Our data indicate a new dimension in tamoxifen action, involving gene expression regulation that is tamoxifen preferential, and identify genes that might serve as markers of tumor responsiveness or resistance to tamoxifen therapy. This may have a potential effect on the choice of tamoxifen versus aromatase inhibitors as adjuvant endocrine therapy.
2007-10-02 | E-GEOD-4025 | biostudies-arrayexpress
Project description:Primary objectives: Evaluate the effectiveness of Hepatotest in assessing preoperative liver function in patients with liver metastases who have received chemotherapy. The correlation of active ingredients and metabolites in blood and urine, and liver enzyme activity in liver biopsy will be studied.
Primary endpoints: Correlation of active ingredients and metabolites in blood and urine, and liver enzyme activity in liver biopsy.
| 2532102 | ecrin-mdr-crc
Project description:Cyclic 3',5'-adenosine monophosphate (cAMP) phosphodiesterase (CPD) is an enzyme that catalyzes the hydrolysis of cAMP, a signaling molecule affecting diverse cellular and metabolic processes in bacteria. Some CPDs are also known to function in cAMP-independent manners, while their physiological roles remain largely unknown. Here, we investigated physiological roles of CPD in Shewanella oneidensis MR-1, a model environmental bacterium, and report that CPD is involved in amino-acid metabolism. We found that a CPD-deficient mutant of MR-1 (ΔcpdA) showed decreased expression of genes for the synthesis of methionine, S-adenosylmethionine, and histidine and required these three compounds to grow in minimal media. Interestingly, deletion of adenylate cyclases in ΔcpdA did not restore the ability to grow in minimal media, indicating that the amino acid requirements were not due to the accumulation of cAMP. These results suggest that CPD is involved in the regulation of amino acid metabolism in MR-1 in a cAMP-independent manner.
2018-02-21 | GSE97220 | GEO