The multilayer community structure of medulloblastoma

iScience

Andrei Zinovyev¹  Davide Cirillo²  Iker Núñez-Carpintero³  Marianyela Petrizzelli⁴  Alfonso Valencia⁴ 

[1] INSERM, U900, 75005 Paris, France;MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, 75006 Paris, France;Barcelona Supercomputing Center (BSC), C/ Jordi Girona 29, 08034, Barcelona, Spain;Institut Curie, PSL Research University, 75005 Paris, France;

关键词: Proteomics;    Cancer Systems Biology;    Cancer;   

DOI  :  

来源: DOAJ

【 摘 要 】

Summary: Multilayer networks allow interpreting the molecular basis of diseases, which is particularly challenging in rare diseases where the number of cases is small compared with the size of the associated multi-omics datasets. In this work, we develop a dimensionality reduction methodology to identify the minimal set of genes that characterize disease subgroups based on their persistent association in multilayer network communities. We use this approach to the study of medulloblastoma, a childhood brain tumor, using proteogenomic data. Our approach is able to recapitulate known medulloblastoma subgroups (accuracy >94%) and provide a clear characterization of gene associations, with the downstream implications for diagnosis and therapeutic interventions. We verified the general applicability of our method on an independent medulloblastoma dataset (accuracy >98%). This approach opens the door to a new generation of multilayer network-based methods able to overcome the specific dimensionality limitations of rare disease datasets.

【 授权许可】

Unknown