Integrative discovery of treatments for high-risk neuroblastoma
(2020) In Nature Communications 11.- Abstract
Despite advances in the molecular exploration of paediatric cancers, approximately 50% of children with high-risk neuroblastoma lack effective treatment. To identify therapeutic options for this group of high-risk patients, we combine predictive data mining with experimental evaluation in patient-derived xenograft cells. Our proposed algorithm, TargetTranslator, integrates data from tumour biobanks, pharmacological databases, and cellular networks to predict how targeted interventions affect mRNA signatures associated with high patient risk or disease processes. We find more than 80 targets to be associated with neuroblastoma risk and differentiation signatures. Selected targets are evaluated in cell lines derived from high-risk... (More)
Despite advances in the molecular exploration of paediatric cancers, approximately 50% of children with high-risk neuroblastoma lack effective treatment. To identify therapeutic options for this group of high-risk patients, we combine predictive data mining with experimental evaluation in patient-derived xenograft cells. Our proposed algorithm, TargetTranslator, integrates data from tumour biobanks, pharmacological databases, and cellular networks to predict how targeted interventions affect mRNA signatures associated with high patient risk or disease processes. We find more than 80 targets to be associated with neuroblastoma risk and differentiation signatures. Selected targets are evaluated in cell lines derived from high-risk patients to demonstrate reversal of risk signatures and malignant phenotypes. Using neuroblastoma xenograft models, we establish CNR2 and MAPK8 as promising candidates for the treatment of high-risk neuroblastoma. We expect that our method, available as a public tool (targettranslator.org), will enhance and expedite the discovery of risk-associated targets for paediatric and adult cancers.
(Less)
- author
- organization
- publishing date
- 2020-01-03
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Nature Communications
- volume
- 11
- article number
- 71
- publisher
- Nature Publishing Group
- external identifiers
-
- scopus:85077479931
- pmid:31900415
- ISSN
- 2041-1723
- DOI
- 10.1038/s41467-019-13817-8
- language
- English
- LU publication?
- yes
- id
- 14af58c2-76d0-44db-9287-bc7b7db80798
- date added to LUP
- 2020-01-21 17:05:15
- date last changed
- 2024-04-17 02:20:38
@article{14af58c2-76d0-44db-9287-bc7b7db80798, abstract = {{<p>Despite advances in the molecular exploration of paediatric cancers, approximately 50% of children with high-risk neuroblastoma lack effective treatment. To identify therapeutic options for this group of high-risk patients, we combine predictive data mining with experimental evaluation in patient-derived xenograft cells. Our proposed algorithm, TargetTranslator, integrates data from tumour biobanks, pharmacological databases, and cellular networks to predict how targeted interventions affect mRNA signatures associated with high patient risk or disease processes. We find more than 80 targets to be associated with neuroblastoma risk and differentiation signatures. Selected targets are evaluated in cell lines derived from high-risk patients to demonstrate reversal of risk signatures and malignant phenotypes. Using neuroblastoma xenograft models, we establish CNR2 and MAPK8 as promising candidates for the treatment of high-risk neuroblastoma. We expect that our method, available as a public tool (targettranslator.org), will enhance and expedite the discovery of risk-associated targets for paediatric and adult cancers.</p>}}, author = {{Almstedt, Elin and Elgendy, Ramy and Hekmati, Neda and Rosén, Emil and Wärn, Caroline and Olsen, Thale Kristin and Dyberg, Cecilia and Doroszko, Milena and Larsson, Ida and Sundström, Anders and Arsenian Henriksson, Marie and Påhlman, Sven and Bexell, Daniel and Vanlandewijck, Michael and Kogner, Per and Jörnsten, Rebecka and Krona, Cecilia and Nelander, Sven}}, issn = {{2041-1723}}, language = {{eng}}, month = {{01}}, publisher = {{Nature Publishing Group}}, series = {{Nature Communications}}, title = {{Integrative discovery of treatments for high-risk neuroblastoma}}, url = {{http://dx.doi.org/10.1038/s41467-019-13817-8}}, doi = {{10.1038/s41467-019-13817-8}}, volume = {{11}}, year = {{2020}}, }