Author
Yves Pommier
Other affiliations: Purdue University, Kyushu University, University of Düsseldorf ...read more
Bio: Yves Pommier is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Topoisomerase & DNA. The author has an hindex of 123, co-authored 789 publications receiving 58898 citations. Previous affiliations of Yves Pommier include Purdue University & Kyushu University.
Topics: Topoisomerase, DNA, Camptothecin, DNA damage, Integrase
Papers published on a yearly basis
Papers
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TL;DR: The mechanisms and molecular determinants of tumour response to TOP1 inhibitor are reviewed, and rational combinations of TOP1 inhibitors with other drugs are considered based on current knowledge of repair and checkpoint pathways that are associated with TOP1-mediated DNA damage.
Abstract: Nuclear DNA topoisomerase I (TOP1) is an essential human enzyme. It is the only known target of the alkaloid camptothecin, from which the potent anticancer agents irinotecan and topotecan are derived. As camptothecins bind at the interface of the TOP1-DNA complex, they represent a paradigm for interfacial inhibitors that reversibly trap macromolecular complexes. Several camptothecin and non-camptothecin derivatives are being developed to further increase anti-tumour activity and reduce side effects. The mechanisms and molecular determinants of tumour response to TOP1 inhibitors are reviewed, and rational combinations of TOP1 inhibitors with other drugs are considered based on current knowledge of repair and checkpoint pathways that are associated with TOP1-mediated DNA damage.
1,854 citations
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TL;DR: This study shows that PARP inhibitors trap the PARP1 and PARP2 enzymes at damaged DNA, providing a new mechanistic foundation for the rational application ofPARP inhibitors in cancer therapy.
Abstract: Small-molecule inhibitors of PARP are thought to mediate their antitumor effects as catalytic inhibitors that block repair of DNA single-strand breaks (SSB). However, the mechanism of action of PARP inhibitors with regard to their effects in cancer cells is not fully understood. In this study, we show that PARP inhibitors trap the PARP1 and PARP2 enzymes at damaged DNA. Trapped PARP-DNA complexes were more cytotoxic than unrepaired SSBs caused by PARP inactivation, arguing that PARP inhibitors act in part as poisons that trap PARP enzyme on DNA. Moreover, the potency in trapping PARP differed markedly among inhibitors with niraparib (MK-4827) > olaparib (AZD-2281) >> veliparib (ABT-888), a pattern not correlated with the catalytic inhibitory properties for each drug. We also analyzed repair pathways for PARP-DNA complexes using 30 genetically altered avian DT40 cell lines with preestablished deletions in specific DNA repair genes. This analysis revealed that, in addition to homologous recombination, postreplication repair, the Fanconi anemia pathway, polymerase β, and FEN1 are critical for repairing trapped PARP-DNA complexes. In summary, our study provides a new mechanistic foundation for the rational application of PARP inhibitors in cancer therapy.
1,587 citations
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TL;DR: This review focuses on the molecular and biochemical characteristics of topoisomerases and their inhibitors and discusses the common mechanism of action ofTopoisomerase poisons by interfacial inhibition and trapping of topisomerase cleavage complexes.
1,587 citations
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TL;DR: Gene-drug relationships for the clinical agents 5-fluorouracil and L-asparaginase exemplify how variations in the transcript levels of particular genes relate to mechanisms of drug sensitivity and resistance.
Abstract: We used cDNA microarrays to assess gene expression profiles in 60 human cancer cell lines used in a drug discovery screen by the National Cancer Institute. Using these data, we linked bioinformatics and chemoinformatics by correlating gene expression and drug activity patterns in the NCI60 lines. Clustering the cell lines on the basis of gene expression yielded relationships very different from those obtained by clustering the cell lines on the basis of their response to drugs. Gene-drug relationships for the clinical agents 5-fluorouracil and L-asparaginase exemplify how variations in the transcript levels of particular genes relate to mechanisms of drug sensitivity and resistance. This is the first study to integrate large databases on gene expression and molecular pharmacology.
1,457 citations
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TL;DR: In this paper, the authors used histone H2AX phosphorylation on a serine four residues from the carboxyl terminus (producing gammaH2AX) as a sensitive marker for DNA double-strand breaks (DSBs).
Abstract: Histone H2AX phosphorylation on a serine four residues from the carboxyl terminus (producing gammaH2AX) is a sensitive marker for DNA double-strand breaks (DSBs). DSBs may lead to cancer but, paradoxically, are also used to kill cancer cells. Using gammaH2AX detection to determine the extent of DSB induction may help to detect precancerous cells, to stage cancers, to monitor the effectiveness of cancer therapies and to develop novel anticancer drugs.
1,349 citations
Cited by
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28,685 citations
28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。
18,940 citations
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TL;DR: In this article, the maximal statistical dependency criterion based on mutual information (mRMR) was proposed to select good features according to the maximal dependency condition. But the problem of feature selection is not solved by directly implementing mRMR.
Abstract: Feature selection is an important problem for pattern classification systems. We study how to select good features according to the maximal statistical dependency criterion based on mutual information. Because of the difficulty in directly implementing the maximal dependency condition, we first derive an equivalent form, called minimal-redundancy-maximal-relevance criterion (mRMR), for first-order incremental feature selection. Then, we present a two-stage feature selection algorithm by combining mRMR and other more sophisticated feature selectors (e.g., wrappers). This allows us to select a compact set of superior features at very low cost. We perform extensive experimental comparison of our algorithm and other methods using three different classifiers (naive Bayes, support vector machine, and linear discriminate analysis) and four different data sets (handwritten digits, arrhythmia, NCI cancer cell lines, and lymphoma tissues). The results confirm that mRMR leads to promising improvement on feature selection and classification accuracy.
8,078 citations
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TL;DR: The current status of botanical screening efforts, as well as in vivo studies of their effectiveness and toxicity, are summarized and the structure and antimicrobial properties of phytochemicals are addressed.
Abstract: The use of and search for drugs and dietary supplements derived from plants have accelerated in recent years. Ethnopharmacologists, botanists, microbiologists, and natural-products chemists are combing the Earth for phytochemicals and “leads” which could be developed for treatment of infectious diseases. While 25 to 50% of current pharmaceuticals are derived from plants, none are used as antimicrobials. Traditional healers have long used plants to prevent or cure infectious conditions; Western medicine is trying to duplicate their successes. Plants are rich in a wide variety of secondary metabolites, such as tannins, terpenoids, alkaloids, and flavonoids, which have been found in vitro to have antimicrobial properties. This review attempts to summarize the current status of botanical screening efforts, as well as in vivo studies of their effectiveness and toxicity. The structure and antimicrobial properties of phytochemicals are also addressed. Since many of these compounds are currently available as unregulated botanical preparations and their use by the public is increasing rapidly, clinicians need to consider the consequences of patients self-medicating with these preparations.
7,486 citations
05 Aug 2003
TL;DR: This work derives an equivalent form, called minimal-redundancy-maximal-relevance criterion (mRMR), for first-order incremental feature selection, and presents a two-stage feature selection algorithm by combining mRMR and other more sophisticated feature selectors (e.g., wrappers).
7,075 citations