Integrative discovery of treatments for high-risk neuroblastoma
Artikel i vetenskaplig tidskrift, 2020

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.

Författare

Elin Almstedt

Uppsala universitet

Ramy Elgendy

Uppsala universitet

Neda Hekmati

Uppsala universitet

Emil Rosén

Uppsala universitet

Caroline Wärn

Uppsala universitet

Thale Kristin Olsen

Karolinska Institutet

Cecilia Dyberg

Karolinska Institutet

Milena Doroszko

Uppsala universitet

Ida Larsson

Uppsala universitet

Anders Sundström

Uppsala universitet

Marie Arsenian Henriksson

Karolinska Institutet

Sven Påhlman

Lunds universitet

Daniel Bexell

Lunds universitet

Michael Vanlandewijck

Uppsala universitet

Karolinska Institutet

Per Kogner

Karolinska Institutet

Rebecka Jörnsten

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Cecilia Krona

Uppsala universitet

S. Nelander

Uppsala universitet

Nature Communications

2041-1723 (ISSN)

Vol. 11 1 71

Ämneskategorier

Hematologi

Medicinsk genetik

Cancer och onkologi

DOI

10.1038/s41467-019-13817-8

PubMed

31900415

Mer information

Senast uppdaterat

2020-02-12