TL;DR:
The findings suggest that RYK expression may serve as an important prognostic or predictor of TMZ response and survival for glioma patients and a combination of RyK expression and MGMT status could serve as a additional biomarker for improved survival.
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Sources: Web Of Science, ORCID, NC State University Libraries
Added: May 29, 2021
2021journal article
High-throughput screening and genome-wide analyses of 44 anticancer drugs in the 1000 Genomes cell lines reveals an association of the NQO1 gene with the response of multiple anticancer drugs
TL;DR:
The NAD(P)H quinone dehydrogenase 1 (NQO1) gene was found to be associated with the dose-response of arsenic trioxide, erlotinib, tramet inib, and a combination treatment of paclitaxel + epirubicin.
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MeSH headings : Breast Neoplasms / drug therapy; Breast Neoplasms / genetics; Breast Neoplasms / pathology; Cell Line, Tumor; Cell Survival / drug effects; Dose-Response Relationship, Drug; Drug Resistance, Neoplasm / genetics; Female; Humans; Middle Aged; Paclitaxel / adverse effects; Paclitaxel / pharmacology; Pharmacogenetics; Racial Groups / genetics; Smoking / adverse effects; Smoking / genetics
TL;DR:
It is indicated that in-vivo smoking status can influence ex- vivo dose-response in LCLs, and more precise measures of covariates may allow for more precise forecasting of clinical effect.
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Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
NATURE COMMUNICATIONS, 10.
By: M. Menden*, D. Wang*, M. Mason*, B. Szalai*, K. Bulusu*, Y. Guan*, T. Yu*, J. Kang* ..., M. Jeon*, R. Wolfinger*, T. Nguyen*, M. Zaslavskiy, I. Jang*, Z. Ghazoui*, M. Ahsen*, R. Vogel*, E. Neto*, T. Norman*, E. Tang*, M. Garnett*, G. Di Veroli*, S. Fawell*, G. Stolovitzky*, J. Guinney*, J. Dry*, J. Saez-Rodriguez*, J. Abante, B. Abecassis, N. Aben, D. Aghamirzaie, T. Aittokallio, F. Akhtari, B. Al-lazikani, T. Alam, A. Allam, C. Allen, M. Almeida, D. Altarawy, V. Alves, A. Amadoz, B. Anchang, A. Antolin, J. Ash, V. Romeo Aznar, W. Ba-alawi, M. Bagheri, V. Bajic, G. Ball, P. Ballester, D. Baptista, C. Bare, M. Bateson, A. Bender, D. Bertrand, B. Wijayawardena, K. Boroevich, E. Bosdriesz, S. Bougouffa, G. Bounova, T. Brouwer, B. Bryant, M. Calaza, A. Calderone, S. Calza, S. Capuzzi, J. Carbonell-Caballero, D. Carlin, H. Carter, L. Castagnoli, R. Celebi, G. Cesareni, H. Chang, G. Chen, H. Chen, H. Chen, L. Cheng, A. Chernomoretz, D. Chicco, K. Cho, S. Cho, D. Choi, J. Choi, K. Choi, M. Choi, M. De Cock, E. Coker, I. Cortes-Ciriano, M. Cserzo, C. Cubuk, C. Curtis, D. Van Daele, C. Dang, T. Dijkstra, J. Dopazo, S. Draghici, A. Drosou, M. Dumontier, F. Ehrhart, F. Eid, M. ElHefnawi, H. Elmarakeby, B. Engelen, H. Engin, I. Esch, C. Evelo, A. Falcao, S. Farag, C. Fernandez-Lozano, K. Fisch, A. Flobak, C. Fornari, A. Foroushani, D. Fotso, D. Fourches, S. Friend, A. Frigessi, F. Gao, X. Gao, J. Gerold, P. Gestraud, S. Ghosh, J. Gillberg, A. Godoy-Lorite, L. Godynyuk, A. Godzik, A. Goldenberg, D. Gomez-Cabrero, M. Gonen, C. Graaf, H. Gray, M. Grechkin, R. Guimera, E. Guney, B. Haibe-Kains, Y. Han, T. Hase, D. He, L. He, L. Heath, K. Hellton, M. Helmer-Citterich, M. Hidalgo, D. Hidru, S. Hill, S. Hochreiter, S. Hong, E. Hovig, Y. Hsueh, Z. Hu, J. Huang, R. Huang, L. Hunyady, J. Hwang, T. Hwang, W. Hwang, Y. Hwang, O. Isayev, O. Walk, J. Jack, S. Jahandideh, J. Ji, Y. Jo, P. Kamola, G. Kanev, L. Karacosta, M. Karimi, S. Kaski, M. Kazanov, A. Khamis, S. Khan, N. Kiani, A. Kim, J. Kim, J. Kim, K. Kim, K. Kim, S. Kim, Y. Kim, Y. Kim, P. Kirk, H. Kitano, G. Klambauer, D. Knowles, M. Ko, A. Kohn-Luque, A. Kooistra, M. Kuenemann, M. Kuiper, C. Kurz, M. Kwon, T. Laarhoven, A. Laegreid, S. Lederer, H. Lee, J. Lee, Y. Lee, E. Leppaho, R. Lewis, J. Li, L. Li, J. Liley, W. Lim, C. Lin, Y. Liu, Y. Lopez, J. Low, A. Lysenko, D. Machado, N. Madhukar, D. De Maeyer, A. Malpartida, H. Mamitsuka, F. Marabita, K. Marchal, P. Marttinen, D. Mason, A. Mazaheri, A. Mehmood, A. Mehreen, M. Michaut, R. Miller, C. Mitsopoulos, D. Modos, M. Van Moerbeke, K. Moo, A. Motsinger-Reif, R. Movva, S. Muraru, E. Muratov, M. Mushthofa, N. Nagarajan, S. Nakken, A. Nath, P. Neuvial, R. Newton, Z. Ning, C. De Niz, B. Oliva, C. Olsen, A. Palmeri, B. Panesar, S. Papadopoulos, J. Park, S. Park, S. Park, Y. Pawitan, D. Peluso, S. Pendyala, J. Peng, L. Perfetto, S. Pirro, S. Plevritis, R. Politi, H. Poon, E. Porta, I. Prellner, K. Preuer, M. Angel Pujana, R. Ramnarine, J. Reid, F. Reyal, S. Richardson, C. Ricketts, L. Rieswijk, M. Rocha, C. Rodriguez-Gonzalvez, K. Roell, D. Rotroff, J. Ruiter, P. Rukawa, B. Sadacca, Z. Safikhani, F. Safitri, M. Sales-Pardo, S. Sauer, M. Schlichting, J. Seoane, J. Serra, M. Shang, A. Sharma, H. Sharma, Y. Shen, M. Shiga, M. Shin, Z. Shkedy, K. Shopsowitz, S. Sinai, D. Skola, P. Smirnov, I. Soerensen, P. Soerensen, J. Song, S. Song, O. Soufan, A. Spitzmueller, B. Steipe, C. Suphavilai, S. Tamayo, D. Tamborero, J. Tang, Z. Tanoli, M. Tarres-Deulofeu, J. Tegner, L. Thommesen, S. Tonekaboni, H. Tran, E. De Troyer, A. Truong, T. Tsunoda, G. Turu, G. Tzeng, L. Verbeke, S. Videla, D. Vis, A. Voronkov, K. Votis, A. Wang, H. Wang, P. Wang, S. Wang, W. Wang, X. Wang, X. Wang, K. Wennerberg, L. Wernisch, L. Wessels, G. Westen, B. Westerman, S. White, E. Willighagen, T. Wurdinger, L. Xie, S. Xie, H. Xu, B. Yadav, C. Yau, H. Yeerna, J. Yin, M. Yu, M. Yu, S. Yun, A. Zakharov, A. Zamichos, M. Zanin, L. Zeng, H. Zenil, F. Zhang, P. Zhang, W. Zhang, H. Zhao, L. Zhao, W. Zheng, A. Zoufir, M. Zucknick
TL;DR:
A large drug combination screen across cancer cell lines is provided to benchmark crowdsourced methods and to computationally predict drug synergies, and genomic rationale for synergy predictions are identified.
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MeSH headings : ATP Binding Cassette Transporter, Subfamily B / genetics; Adult; Age Factors; Aged; Aging / genetics; Anti-HIV Agents / administration & dosage; Anti-HIV Agents / pharmacokinetics; Anti-HIV Agents / therapeutic use; Cyclin-Dependent Kinase Inhibitor p16 / metabolism; Cytochrome P-450 CYP2B6 / genetics; Drug Combinations; Drug Therapy, Combination / methods; Female; Frail Elderly; HIV Infections / drug therapy; HIV Infections / genetics; Humans; Male; Middle Aged; Multidrug Resistance-Associated Proteins / genetics; Pharmacogenomic Testing / methods; Prospective Studies; Young Adult
TL;DR:
Both age and p16INK4a expression interacted with PGx on ATV and TFV disposition, implying potential dose adjustment based on aging may depend on genetic background.
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TL;DR:
The results demonstrate the influence of Neanderthal ancestry-informative markers on cytotoxic response and could be important in identifying biomarkers for personalized medicine or in dissecting the underlying etiology of dose response traits.
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