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- Menden, MP, et al.
(författare)
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Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
- 2019
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2674-
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Tidskriftsartikel (refereegranskat)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.
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| 4. |
- Romagnoni, A, et al.
(författare)
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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
- 2019
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
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Tidskriftsartikel (refereegranskat)abstract
- Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
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| 5. |
- Biasoli, Deborah, et al.
(författare)
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A synonymous germline variant in a gene encoding a cell adhesion molecule is associated with cutaneous mast cell tumour development in Labrador and Golden Retrievers
- 2019
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Ingår i: PLOS Genetics. - : PUBLIC LIBRARY SCIENCE. - 1553-7390 .- 1553-7404. ; 15:3
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Tidskriftsartikel (refereegranskat)abstract
- Mast cell tumours are the most common type of skin cancer in dogs, representing a significant concern in canine health. The molecular pathogenesis is largely unknown, but breed-predisposition for mast cell tumour development suggests the involvement of inherited genetic risk factors in some breeds. In this study, we aimed to identify germline risk factors associated with the development of mast cell tumours in Labrador Retrievers, a breed with an elevated risk of mast cell tumour development. Using a methodological approach that combined a genome-wide association study, targeted next generation sequencing, and TaqMan genotyping, we identified a synonymous variant in the DSCAM gene on canine chromosome 31 that is associated with mast cell tumours in Labrador Retrievers. DSCAM encodes a cell-adhesion molecule. We showed that the variant has no effect on the DSCAM mRNA level but is associated with a significant reduction in the level of the DSCAM protein, suggesting that the variant affects the dynamics of DSCAM mRNA translation. Furthermore, we showed that the variant is also associated with mast cell tumours in Golden Retrievers, a breed that is closely related to Labrador Retrievers and that also has a predilection for mast cell tumour development. The variant is common in both Labradors and Golden Retrievers and consequently is likely to be a significant genetic contributor to the increased susceptibility of both breeds to develop mast cell tumours. The results presented here not only represent an important contribution to the understanding of mast cell tumour development in dogs, as they highlight the role of cell adhesion in mast cell tumour tumourigenesis, but they also emphasise the potential importance of the effects of synonymous variants in complex diseases such as cancer. Author summary The combination of various genetic and environmental risk factors makes the understanding of the molecular circuitry behind complex diseases, like cancer, a major challenge. The homogeneous nature of pedigree dog breed genomes makes these dogs ideal for the identification of both simple disease-causing genetic variants and genetic risk factors for complex diseases. Mast cell tumours are the most common type of canine skin cancer, and one of the most common cancers affecting dogs of most breeds. Several breeds, including Labrador Retrievers (which represent one of the most popular dog breeds), have an elevated risk of mast cell tumour development. Here, by using a methodological approach that combined different techniques, we identified a common inherited synonymous variant, that predisposes Labrador Retrievers to mast cell tumour development. Interestingly, we showed that this variant, despite its synonymous nature, appears to have an effect on translation dynamics as it is associated with reduced levels of DSCAM, a cell adhesion molecule. The results presented here reveal dysregulation of cell adhesion to be an important factor in mast cell tumour pathogenesis, and also highlight the important role that synonymous variants can play in complex diseases.
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| 6. |
- Garibaldi, Lucas A., et al.
(författare)
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Trait matching of flower visitors and crops predicts fruit set better than trait diversity
- 2015
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Ingår i: Journal of Applied Ecology. - : Wiley. - 1365-2664 .- 0021-8901. ; 52:6, s. 1436-1444
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Forskningsöversikt (refereegranskat)abstract
- Understanding the relationships between trait diversity, species diversity and ecosystem functioning is essential for sustainable management. For functions comprising two trophic levels, trait matching between interacting partners should also drive functioning. However, the predictive ability of trait diversity and matching is unclear for most functions, particularly for crop pollination, where interacting partners did not necessarily co-evolve. World-wide, we collected data on traits of flower visitors and crops, visitation rates to crop flowers per insect species and fruit set in 469 fields of 33 crop systems. Through hierarchical mixed-effects models, we tested whether flower visitor trait diversity and/or trait matching between flower visitors and crops improve the prediction of crop fruit set (functioning) beyond flower visitor species diversity and abundance. Flower visitor trait diversity was positively related to fruit set, but surprisingly did not explain more variation than flower visitor species diversity. The best prediction of fruit set was obtained by matching traits of flower visitors (body size and mouthpart length) and crops (nectar accessibility of flowers) in addition to flower visitor abundance, species richness and species evenness. Fruit set increased with species richness, and more so in assemblages with high evenness, indicating that additional species of flower visitors contribute more to crop pollination when species abundances are similar.Synthesis and applications. Despite contrasting floral traits for crops world-wide, only the abundance of a few pollinator species is commonly managed for greater yield. Our results suggest that the identification and enhancement of pollinator species with traits matching those of the focal crop, as well as the enhancement of pollinator richness and evenness, will increase crop yield beyond current practices. Furthermore, we show that field practitioners can predict and manage agroecosystems for pollination services based on knowledge of just a few traits that are known for a wide range of flower visitor species. Despite contrasting floral traits for crops world-wide, only the abundance of a few pollinator species is commonly managed for greater yield. Our results suggest that the identification and enhancement of pollinator species with traits matching those of the focal crop, as well as the enhancement of pollinator richness and evenness, will increase crop yield beyond current practices. Furthermore, we show that field practitioners can predict and manage agroecosystems for pollination services based on knowledge of just a few traits that are known for a wide range of flower visitor species. Editor's Choice
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| 7. |
- Guerry, Anne D., et al.
(författare)
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Natural capital and ecosystem services informing decisions : From promise to practice
- 2015
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 112:24, s. 7348-7355
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- The central challenge of the 21st century is to develop economic, social, and governance systems capable of ending poverty and achieving sustainable levels of population and consumption while securing the life-support systems underpinning current and future human well-being. Essential to meeting this challenge is the incorporation of natural capital and the ecosystem services it provides into decision-making. We explore progress and crucial gaps at this frontier, reflecting upon the 10 y since the Millennium Ecosystem Assessment. We focus on three key dimensions of progress and ongoing challenges: raising awareness of the interdependence of ecosystems and human well-being, advancing the fundamental interdisciplinary science of ecosystem services, and implementing this science in decisions to restore natural capital and use it sustainably. Awareness of human dependence on nature is at an all-time high, the science of ecosystem services is rapidly advancing, and talk of natural capital is now common from governments to corporate boardrooms. However, successful implementation is still in early stages. We explore why ecosystem service information has yet to fundamentally change decision-making and suggest a path forward that emphasizes: (i) developing solid evidence linking decisions to impacts on natural capital and ecosystem services, and then to human well-being; (ii) working closely with leaders in government, business, and civil society to develop the knowledge, tools, and practices necessary to integrate natural capital and ecosystem services into everyday decision-making; and (iii) reforming institutions to change policy and practices to better align private short-term goals with societal long-term goals.
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| 8. |
- Mäkeläinen, Suvi, et al.
(författare)
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An ABCA4 loss-of-function mutation causes a canine form of Stargardt disease
- 2019
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Ingår i: PLOS Genetics. - : Public Library of Science. - 1553-7390 .- 1553-7404. ; 15:3
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Tidskriftsartikel (refereegranskat)abstract
- Autosomal recessive retinal degenerative diseases cause visual impairment and blindness in both humans and dogs. Currently, no standard treatment is available, but pioneering gene therapy-based canine models have been instrumental for clinical trials in humans. To study a novel form of retinal degeneration in Labrador retriever dogs with clinical signs indicating cone and rod degeneration, we used whole-genome sequencing of an affected sib-pair and their unaffected parents. A frameshift insertion in the ATP binding cassette subfamily A member 4 (ABCA4) gene (c.4176insC), leading to a premature stop codon in exon 28 (p.F1393Lfs*1395), was identified. In contrast to unaffected dogs, no full-length ABCA4 protein was detected in the retina of an affected dog. The ABCA4 gene encodes a membrane transporter protein localized in the outer segments of rod and cone photoreceptors. In humans, the ABCA4 gene is associated with Stargardt disease (STGD), an autosomal recessive retinal degeneration leading to central visual impairment. A hallmark of STGD is the accumulation of lipofuscin deposits in the retinal pigment epithelium (RPE). The discovery of a canine homozygous ABCA4 loss-of-function mutation may advance the development of dog as a large animal model for human STGD.
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