Search

Your search keyword '"Pawitan, Yudi"' showing total 963 results
Start Over Author "Pawitan, Yudi"
963 results on '"Pawitan, Yudi"'

103. The transcriptome-wide landscape of molecular subtype-specific mRNA expression profiles in acute myeloid leukemia

Author

Mou, Tian, Pawitan, Yudi, Stahl, Matthias, Vesterlund, Mattias, Deng, Wenjiang, Jafari, Rozbeh, Bohlin, Anna, Österroos, Albin, Siavelis, Loannis, Backvall, Helena, Erkers, Tom, Kiviluoto, Santeri, Seashore-Ludlow, Brinton, Ostling, Paivi, Orre, Lukas M., Kallioniemi, Olli, Lehmann, Sören, Lehtio, Janne, Vu, Trung Nghia, Mou, Tian, Pawitan, Yudi, Stahl, Matthias, Vesterlund, Mattias, Deng, Wenjiang, Jafari, Rozbeh, Bohlin, Anna, Österroos, Albin, Siavelis, Loannis, Backvall, Helena, Erkers, Tom, Kiviluoto, Santeri, Seashore-Ludlow, Brinton, Ostling, Paivi, Orre, Lukas M., Kallioniemi, Olli, Lehmann, Sören, Lehtio, Janne, and Vu, Trung Nghia

Abstract

Molecular classification of acute myeloid leukemia (AML) aids prognostic stratification and clinical management. Our aim in this study is to identify transcriptome-wide mRNAs that are specific to each of the molecular subtypes of AML. We analyzed RNA-sequencing data of 955 AML samples from three cohorts, including the BeatAML project, the Cancer Genome Atlas, and a cohort of Swedish patients to provide a comprehensive transcriptome-wide view of subtype-specific mRNA expression. We identified 729 subtype-specific mRNAs, discovered in the BeatAML project and validated in the other two cohorts. Using unique proteomics data, we also validated the presence of subtype-specific mRNAs at the protein level, yielding a rich collection of potential protein-based biomarkers for the AML community. To enable the exploration of subtype-specific mRNA expression by the broader scientific community, we provide an interactive resource to the public.

Published
2021
Full Text
View/download PDF

104. Associations between autoimmune diseases and amyotrophic lateral sclerosis : a register-based study

Author

Cui, Can, Longinetti, Elisa, Larsson, Henrik, Andersson, John, Pawitan, Yudi, Piehl, Fredrik, Fang, Fang, Cui, Can, Longinetti, Elisa, Larsson, Henrik, Andersson, John, Pawitan, Yudi, Piehl, Fredrik, and Fang, Fang

Abstract

Objective: To assess the associations of 43 autoimmune diseases with the subsequent risk of ALS and further evaluate the contribution of familial confounding to these associations. Methods: We conducted a nationwide register-based nested case-control study including 3561 ALS patients diagnosed during 1990-2013 in Sweden and 35,610 controls that were randomly selected from the general population and individually matched to the cases on age, sex, and county of birth. To evaluate the contribution of familial factors on the studied association, we additionally studied the first-degree relatives (siblings and children) of ALS patients and their controls. Results: Patients with ALS had a 47% higher risk of being previously diagnosed with autoimmune disease (OR 1.47, 95% confidence interval [CI] 1.31-1.64), compared with controls. A positive association was noted for several autoimmune diseases, including myasthenia gravis, polymyositis or dermatomyositis, Guillain-Barre syndrome, type 1 diabetes diagnosed younger than 30 years, multiple sclerosis, and hypothyreosis. The increased risk of any autoimmune disease was greatest during the year before ALS diagnosis, likely due to misdiagnosis. A statistically significantly increased risk was also noted during 2-5 years, but not earlier, before ALS diagnosis. First-degree relatives of ALS patients had however no increased risk of autoimmune diseases compared with first-degree relatives of controls. Conclusions: Although it is difficult to completely remove the potential effects of misdiagnosis, there is likely a positive association between autoimmune disease (such as type 1 diabetes and multiple sclerosis) and ALS, which is not fully explained by shared familial confounding factors., Funding Agencies:Karolinska Institutet (Senior Researcher Award) Karolinska Institutet (Strategic Research Area in Epidemiology) China Scholarship Council

Published
2021
Full Text
View/download PDF

105. Gastrointestinal biopsies and amyotrophic lateral sclerosis : results from a cohort study of 1.1 million individuals

Author

Sun, Jiangwei, Ludvigsson, Jonas F., Roelstraete, Bjorn, Pawitan, Yudi, Fang, Fang, Sun, Jiangwei, Ludvigsson, Jonas F., Roelstraete, Bjorn, Pawitan, Yudi, and Fang, Fang

Abstract

Background: Evidence has accumulated to support the involvement of gastrointestinal (GI) dysfunction, possibly via gut microbial dysbiosis and alterations in the enteric nervous system, in the pathophysiology of different neurodegenerative diseases. However, whether patients with GI dysfunction have altered risk of amyotrophic lateral sclerosis (ALS) remains unknown. Methods: Based on a historical nationwide cohort study-ESPRESSO-in Sweden, we compared the risk of ALS among individuals with a previous GI biopsy finding of normal mucosa or non-specific inflammation, as two conditions of GI dysfunction, to that of individuals without any GI biopsy. We identified all individuals with a GI biopsy result of either normal mucosa (n = 483,442) or non-specific inflammation (n = 566,663) during 1965-2016 in Sweden as the exposed groups. For each exposed individual, we randomly selected up to five controls from the general Swedish population after individual matching by age and sex. Both the exposed and unexposed individuals were followed from date of biopsy (exposed individuals) or date of selection (unexposed individuals) until ALS diagnosis, emigration out of Sweden, death, or 31 December 2016, whichever came first. Stratified Cox regression models were used to estimate hazard ratios (HRs) and their 95% confidence intervals (CIs). Results: Compared to individuals without GI biopsy, individuals with a GI biopsy result of normal mucosa had an increased risk of ALS (HR = 1.22; 95%CI: 1.04-1.42) after excluding the first 2 years of follow-up to alleviate concern of surveillance bias. This increased risk was noted among male (HR = 1.20; 95%CI: 0.94-1.51) and female (HR = 1.23; 95%CI: 1.01-1.50), as well as among younger (<60 years; HR = 1.17; 95%CI: 0.94-1.44) and older (>= 60 years; HR = 1.24; 95%CI: 0.99-1.56) individuals. In contrast, no association was observed for a GI biopsy result of non-specific inflammation (HR = 1.00; 95%CI: 0.88-1.15). Neither of the GI biopsy, Funding Agency:China Scholarship Council

Published
2021
Full Text
View/download PDF

115. The transcriptome‐wide landscape of molecular subtype‐specific mRNA expression profiles in acute myeloid leukemia

Author

Mou, Tian, primary, Pawitan, Yudi, additional, Stahl, Matthias, additional, Vesterlund, Mattias, additional, Deng, Wenjiang, additional, Jafari, Rozbeh, additional, Bohlin, Anna, additional, Österroos, Albin, additional, Siavelis, Loannis, additional, Bäckvall, Helena, additional, Erkers, Tom, additional, Kiviluoto, Santeri, additional, Seashore‐Ludlow, Brinton, additional, Östling, Päivi, additional, Orre, Lukas M., additional, Kallioniemi, Olli, additional, Lehmann, Sören, additional, Lehtiö, Janne, additional, and Vu, Trung Nghia, additional

Published
2021
Full Text
View/download PDF

117. Profiles of histidine-rich glycoprotein associate with age and risk of all-cause mortality

Author

Hong, Mun-Gwan, Dodig-Crnkovic, Tea, Chen, Xu, Drobin, Kimi, Lee, Woojoo, Wang, Yunzhang, Edfors, Fredrik, Kotol, David, Thomas, Cecilia Engel, Sjöberg, Ronald, Odeberg, Jacob, Hamsten, Anders, Silveira, Angela, Hall, Per, Nilsson, Peter, Pawitan, Yudi, Uhlén, Mathias, Pedersen, Nancy L, Hägg, Sara, Magnusson, Patrik KE, Schwenk, Jochen M., Hong, Mun-Gwan, Dodig-Crnkovic, Tea, Chen, Xu, Drobin, Kimi, Lee, Woojoo, Wang, Yunzhang, Edfors, Fredrik, Kotol, David, Thomas, Cecilia Engel, Sjöberg, Ronald, Odeberg, Jacob, Hamsten, Anders, Silveira, Angela, Hall, Per, Nilsson, Peter, Pawitan, Yudi, Uhlén, Mathias, Pedersen, Nancy L, Hägg, Sara, Magnusson, Patrik KE, and Schwenk, Jochen M.

Abstract

Despite recognizing aging as a common risk factor of many human diseases, little is known about its molecular traits. To identify age-associated proteins circulating in human blood, we screened 156 individuals aged 50–92 using exploratory and multiplexed affinity proteomics assays. Profiling eight additional study sets (N = 3,987), performing antibody validation, and conducting a meta-analysis revealed a consistent age association (P = 6.61 × 10−6) for circulating histidine-rich glycoprotein (HRG). Sequence variants of HRG influenced how the protein was recognized in the immunoassays. Indeed, only the HRG profiles affected by rs9898 were associated with age and predicted the risk of mortality (HR = 1.25 per SD; 95% CI = 1.12–1.39; P = 6.45 × 10−5) during a follow-up period of 8.5 yr after blood sampling (IQR = 7.7–9.3 yr). Our affinity proteomics analysis found associations between the particular molecular traits of circulating HRG with age and all-cause mortality. The distinct profiles of this multipurpose protein could serve as an accessible and informative indicator of the physiological processes related to biological aging., QC 20200922

Published
2020
Full Text
View/download PDF

119. Nontrivial Replication of Loci Detected by Multi-Trait Methods

Author

Ning, Zheng, primary, Tsepilov, Yakov A., additional, Sharapov, Sodbo Zh., additional, Wang, Zhipeng, additional, Grishenko, Alexander K., additional, Feng, Xiao, additional, Shirali, Masoud, additional, Joshi, Peter K., additional, Wilson, James F., additional, Pawitan, Yudi, additional, Haley, Chris S., additional, Aulchenko, Yurii S., additional, and Shen, Xia, additional

Published
2021
Full Text
View/download PDF

124. Isoform-level quantification for single-cell RNA sequencing.

Author

Pan, Lu, Dinh, Huy Q, Pawitan, Yudi, and Vu, Trung Nghia

Subjects
RNA sequencing, PROTEIN-protein interactions, SOURCE code, CD14 antigen, GENOMICS, BIOMARKERS
Abstract

Motivation RNA expression at isoform level is biologically more informative than at gene level and can potentially reveal cellular subsets and corresponding biomarkers that are not visible at gene level. However, due to the strong 3ʹ bias sequencing protocol, mRNA quantification for high-throughput single-cell RNA sequencing such as Chromium Single Cell 3ʹ 10× Genomics is currently performed at the gene level. Results We have developed an isoform-level quantification method for high-throughput single-cell RNA sequencing by exploiting the concepts of transcription clusters and isoform paralogs. The method, called Scasa, compares well in simulations against competing approaches including Alevin, Cellranger, Kallisto, Salmon, Terminus and STARsolo at both isoform- and gene-level expression. The reanalysis of a CITE-Seq dataset with isoform-based Scasa reveals a subgroup of CD14 monocytes missed by gene-based methods. Availability and implementation Implementation of Scasa including source code, documentation, tutorials and test data supporting this study is available at Github: https://github.com/eudoraleer/scasa and Zenodo: https://doi.org/10.5281/zenodo.5712503. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

128. Profiles of histidine-rich glycoprotein associate with age and risk of all-cause mortality

Author

Hong, Mun-Gwan, primary, Dodig-Crnković, Tea, additional, Chen, Xu, additional, Drobin, Kimi, additional, Lee, Woojoo, additional, Wang, Yunzhang, additional, Edfors, Fredrik, additional, Kotol, David, additional, Thomas, Cecilia Engel, additional, Sjöberg, Ronald, additional, Odeberg, Jacob, additional, Hamsten, Anders, additional, Silveira, Angela, additional, Hall, Per, additional, Nilsson, Peter, additional, Pawitan, Yudi, additional, Uhlén, Mathias, additional, Pedersen, Nancy L, additional, Hägg, Sara, additional, Magnusson, Patrik KE, additional, and Schwenk, Jochen M, additional

Published
2020
Full Text
View/download PDF

129. Author Reply to Peer Reviews of Profiles of circulating histidine-rich glycoprotein associate with chronological age and risk of all-cause mortality

Author

Schwenk, Jochen M., primary, Magnusson, Patrik K. E., additional, Pedersen, Nancy L., additional, Uhlén, Mathias, additional, Hägg, Sara, additional, Pawitan, Yudi, additional, Nilsson, Peter, additional, Hall, Per, additional, Silveira, Angela, additional, Hamsten, Anders, additional, Odeberg, Jacob, additional, Sjöberg, Ronald, additional, Thomas, Cecilia Engel, additional, Kotol, David, additional, Edfors, Fredrik, additional, Wang, Yunzhang, additional, Lee, Woojoo, additional, Drobin, Kimi, additional, Chen, Xu, additional, Dodig-Crnković, Tea, additional, and Hong, Mun-Gwan, additional

Published
2020
Full Text
View/download PDF

137. The frequency of misattributed paternity in Sweden is low and decreasing: A nationwide cohort study.

Author

Dahlén, Torsten, Zhao, Jingcheng, Magnusson, Patrik K.E., Pawitan, Yudi, Lavröd, Jakob, and Edgren, Gustaf

Subjects
PATERNITY, ABO blood group system, ROYAL succession, COHORT analysis
Abstract

Background: The occurrence of misattributed paternity has consequences throughout society with implications ranging from inheritance and royal succession to transplantation. However, its frequency in Sweden is unknown. Objective: To estimate the contemporary frequency of misattributed paternity in Sweden. Methods: The study was based on nationwide ABO blood group data and a nationwide register of familial relationships in Sweden. These data were analysed using both a frequentist Poisson model and the Bayesian Gibbs model. The conduct of the study was approved by the regional ethics committee in Stockholm, Sweden (reference numbers 2018/167‐31 and 2019‐04656). Results: Nearly two million mother‐father‐offspring family units were included. Overall, the frequency of misattributed paternity was estimated at 1.7% in both models. Misattributed paternity was more common among parents with low educational levels, and has decreased over time to a current 1%. Conclusions: The misattributed paternity rate is similar to the rates in other West European populations. Apart from widespread societal implications, studies on heritability may consider misattributed paternity as a minor source of error. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

138. The philosophy of statistics.

Author

Pawitan, Yudi and Lee, Youngjo

Subjects
*STATISTICS, *STATISTICIANS, *PARADOX, *PUZZLES, *PROBABILITY theory
Abstract

When we interpret statistics, we inevitably incorporate our personal knowledge and philosophical preferences. All statisticians therefore need to understand the philosophical foundation of probability and statistics, say Yudi Pawitan and Youngjo Lee – and puzzles and paradoxes can help [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

140. Estrogen-Dependent Signaling in a Molecularly Distinct Subclass of Aggressive Prostate Cancer

Author

Setlur, Sunita R., Mertz, Kirsten D., Hoshida, Yujin, Demichelis, Francesca, Lupien, Mathieu, Perner, Sven, Sboner, Andrea, Pawitan, Yudi, Andrén, Ove, Johnson, Laura A., Tang, Jeff, Adami, Hans-Olov, Calza, Stefano, Chinnaiyan, Arul M., Rhodes, Daniel, Tomlins, Scott, Fall, Katja, Mucci, Lorelei A., Kantoff, Philip W., Stampfer, Meir J., Andersson, Swen-Olof, Varenhorst, Eberhard, Johansson, Jan-Erik, Brown, Myles, Golub, Todd R., and Rubin, Mark A.

Published
2008

143. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

Author

Menden, Michael P., Wang, Dennis, Mason, Mike J., Szalai, Bence, Bulusu, Krishna C., Guan, Yuanfang, Yu, Thomas, Kang, Jaewoo, Jeon, Minji, Wolfinger, Russ, Nguyen, Tin, Zaslavskiy, Mikhail, Jang, In Sock, Ghazoui, Zara, Ahsen, Mehmet Eren, Vogel, Robert, Neto, Elias Chaibub, Norman, Thea, Tang, Eric K. Y., Garnett, Mathew J., Di Veroli, Giovanni Y., Fawell, Stephen, Stolovitzky, Gustavo, Guinney, Justin, Dry, Jonathan R., Saez-Rodriguez, Julio, Abante, Jordi, Abecassis, Barbara Schmitz, Aben, Nanne, Aghamirzaie, Delasa, Aittokallio, Tero, Akhtari, Farida S., Al-lazikani, Bissan, Alam, Tanvir, Allam, Amin, Allen, Chad, de Almeida, Mariana Pelicano, Altarawy, Doaa, Alves, Vinicius, Amadoz, Alicia, Anchang, Benedict, Antolin, Albert A., Ash, Jeremy R., Romeo Aznar, Victoria, Ba-alawi, Wail, Bagheri, Moeen, Bajic, Vladimir, Ball, Gordon, Ballester, Pedro J., Baptista, Delora, Bare, Christopher, Bateson, Mathilde, Bender, Andreas, Bertrand, Denis, Wijayawardena, Bhagya, Boroevich, Keith A., Bosdriesz, Evert, Bougouffa, Salim, Bounova, Gergana, Brouwer, Thomas, Bryant, Barbara, Calaza, Manuel, Calderone, Alberto, Calza, Stefano, Capuzzi, Stephen, Carbonell-Caballero, Jose, Carlin, Daniel, Carter, Hannah, Castagnoli, Luisa, Celebi, Remzi, Cesareni, Gianni, Chang, Hyeokyoon, Chen, Guocai, Chen, Haoran, Chen, Huiyuan, Cheng, Lijun, Chernomoretz, Ariel, Chicco, Davide, Cho, Kwang-Hyun, Cho, Sunghwan, Choi, Daeseon, Choi, Jaejoon, Choi, Kwanghun, Choi, Minsoo, De Cock, Martine, Coker, Elizabeth, Cortes-Ciriano, Isidro, Cserzo, Miklos, Cubuk, Cankut, Curtis, Christina, Van Daele, Dries, Dang, Cuong C., Dijkstra, Tjeerd, Dopazo, Joaquin, Draghici, Sorin, Drosou, Anastasios, Dumontier, Michel, Ehrhart, Friederike, Eid, Fatma-Elzahraa, ElHefnawi, Mahmoud, Elmarakeby, Haitham A., van Engelen, Bo, Engin, Hatice Billur, de Esch, Iwan, Evelo, Chris, Falcao, Andre O., Farag, Sherif, Fernandez-Lozano, Carlos, Fisch, Kathleen, Flobak, Asmund, Fornari, Chiara, Foroushani, Amir B. K., Fotso, Donatien Chedom, Fourches, Denis, Friend, Stephen, Frigessi, Arnoldo, Gao, Feng, Gao, Xiaoting, Gerold, Jeffrey M., Gestraud, Pierre, Ghosh, Samik, Gillberg, Jussi, Godoy-Lorite, Antonia, Godynyuk, Lizzy, Godzik, Adam, Goldenberg, Anna, Gomez-Cabrero, David, Gonen, Mehmet, de Graaf, Chris, Gray, Harry, Grechkin, Maxim, Guimera, Roger, Guney, Emre, Haibe-Kains, Benjamin, Han, Younghyun, Hase, Takeshi, He, Di, He, Liye, Heath, Lenwood S., Hellton, Kristoffer H., Helmer-Citterich, Manuela, Hidalgo, Marta R., Hidru, Daniel, Hill, Steven M., Hochreiter, Sepp, Hong, Seungpyo, Hovig, Eivind, Hsueh, Ya-Chih, Hu, Zhiyuan, Huang, Justin K., Huang, R. Stephanie, Hunyady, Laszlo, Hwang, Jinseub, Hwang, Tae Hyun, Hwang, Woochang, Hwang, Yongdeuk, Isayev, Olexandr, Walk, Oliver Bear Don't, Jack, John, Jahandideh, Samad, Ji, Jiadong, Jo, Yousang, Kamola, Piotr J., Kanev, Georgi K., Karacosta, Loukia, Karimi, Mostafa, Kaski, Samuel, Kazanov, Marat, Khamis, Abdullah M., Khan, Suleiman Ali, Kiani, Narsis A., Kim, Allen, Kim, Jinhan, Kim, Juntae, Kim, Kiseong, Kim, Kyung, Kim, Sunkyu, Kim, Yongsoo, Kim, Yunseong, Kirk, Paul D. W., Kitano, Hiroaki, Klambauer, Gunter, Knowles, David, Ko, Melissa, Kohn-Luque, Alvaro, Kooistra, Albert J., Kuenemann, Melaine A., Kuiper, Martin, Kurz, Christoph, Kwon, Mijin, van Laarhoven, Twan, Laegreid, Astrid, Lederer, Simone, Lee, Heewon, Lee, Jeon, Lee, Yun Woo, Leppaho, Eemeli, Lewis, Richard, Li, Jing, Li, Lang, Liley, James, Lim, Weng Khong, Lin, Chieh, Liu, Yiyi, Lopez, Yosvany, Low, Joshua, Lysenko, Artem, Machado, Daniel, Madhukar, Neel, De Maeyer, Dries, Malpartida, Ana Belen, Mamitsuka, Hiroshi, Marabita, Francesco, Marchal, Kathleen, Marttinen, Pekka, Mason, Daniel, Mazaheri, Alireza, Mehmood, Arfa, Mehreen, Ali, Michaut, Magali, Miller, Ryan A., Mitsopoulos, Costas, Modos, Dezso, Van Moerbeke, Marijke, Moo, Keagan, Motsinger-Reif, Alison, Movva, Rajiv, Muraru, Sebastian, Muratov, Eugene, Mushthofa, Mushthofa, Nagarajan, Niranjan, Nakken, Sigve, Nath, Aritro, Neuvial, Pierre, Newton, Richard, Ning, Zheng, De Niz, Carlos, Oliva, Baldo, Olsen, Catharina, Palmeri, Antonio, Panesar, Bhawan, Papadopoulos, Stavros, Park, Jaesub, Park, Seonyeong, Park, Sungjoon, Pawitan, Yudi, Peluso, Daniele, Pendyala, Sriram, Peng, Jian, Perfetto, Livia, Pirro, Stefano, Plevritis, Sylvia, Politi, Regina, Poon, Hoifung, Porta, Eduard, Prellner, Isak, Preuer, Kristina, Angel Pujana, Miguel, Ramnarine, Ricardo, Reid, John E., Reyal, Fabien, Richardson, Sylvia, Ricketts, Camir, Rieswijk, Linda, Rocha, Miguel, Rodriguez-Gonzalvez, Carmen, Roell, Kyle, Rotroff, Daniel, de Ruiter, Julian R., Rukawa, Ploy, Sadacca, Benjamin, Safikhani, Zhaleh, Safitri, Fita, Sales-Pardo, Marta, Sauer, Sebastian, Schlichting, Moritz, Seoane, Jose A., Serra, Jordi, Shang, Ming-Mei, Sharma, Alok, Sharma, Hari, Shen, Yang, Shiga, Motoki, Shin, Moonshik, Shkedy, Ziv, Shopsowitz, Kevin, Sinai, Sam, Skola, Dylan, Smirnov, Petr, Soerensen, Izel Fourie, Soerensen, Peter, Song, Je-Hoon, Song, Sang Ok, Soufan, Othman, Spitzmueller, Andreas, Steipe, Boris, Suphavilai, Chayaporn, Tamayo, Sergio Pulido, Tamborero, David, Tang, Jing, Tanoli, Zia-ur-Rehman, Tarres-Deulofeu, Marc, Tegner, Jesper, Thommesen, Liv, Tonekaboni, Seyed Ali Madani, Tran, Hong T., De Troyer, Ewoud, Truong, Amy, Tsunoda, Tatsuhiko, Turu, Gabor, Tzeng, Guang-Yo, Verbeke, Lieven, Videla, Santiago, Vis, Daniel, Voronkov, Andrey, Votis, Konstantinos, Wang, Ashley, Wang, Hong-Qiang Horace, Wang, Po-Wei, Wang, Sheng, Wang, Wei, Wang, Xiaochen, Wang, Xin, Wennerberg, Krister, Wernisch, Lorenz, Wessels, Lodewyk, van Westen, Gerard J. P., Westerman, Bart A., White, Simon Richard, Willighagen, Egon, Wurdinger, Tom, Xie, Lei, Xie, Shuilian, Xu, Hua, Yadav, Bhagwan, Yau, Christopher, Yeerna, Huwate, Yin, Jia Wei, Yu, Michael, Yu, MinHwan, Yun, So Jeong, Zakharov, Alexey, Zamichos, Alexandros, Zanin, Massimiliano, Zeng, Li, Zenil, Hector, Zhang, Frederick, Zhang, Pengyue, Zhang, Wei, Zhao, Hongyu, Zhao, Lan, Zheng, Wenjin, Zoufir, Azedine, Zucknick, Manuela, and Computer Science

Subjects
health care economics and organizations
Abstract

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells. AstraZeneca European Union Horizon 2020 research [668858 PrECISE] Joint Research Center for Computational Biomedicine (Bayer AG) National Institute for Health Research (NIHR) Sheffield Biomedical Research Center, Premium Postdoctoral Fellowship Program of the Hungarian Academy of Sciences Wellcome Trust [102696, 206194] We thank the Genomics of Drug Sensitivity in Cancer and COSMIC teams at the Wellcome Trust Sanger Institute for help with the preparation of the molecular data, Denes Turei for help with Omnipath, and Katjusa Koler for help with matching drug names across combination screens. We thank AstraZeneca for funding and provision of data to the DREAM Consortium to run the challenge, and funding from the European Union Horizon 2020 research (under grant agreement No 668858 PrECISE to J.S.R.), the Joint Research Center for Computational Biomedicine (which is partially funded by Bayer AG) to J.S.R., National Institute for Health Research (NIHR) Sheffield Biomedical Research Center, Premium Postdoctoral Fellowship Program of the Hungarian Academy of Sciences. M.G lab is supported by Wellcome Trust (102696 and 206194).

Published
2019

Catalog

Books, media, physical & digital resources
See catalog results