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Proteomes. 2017 Feb 3;5(1). pii: E5. doi: 10.3390/proteomes5010005.

Integrated Proteomic and Transcriptomic-Based Approaches to Identifying Signature Biomarkers and Pathways for Elucidation of Daoy and UW228 Subtypes.

Higdon R1,2,3,4, Kala J5, Wilkins D6, Yan JF7, Sethi MK8, Lin L9, Liu S10,11, Montague E12,13,14,15, Janko I16,17,18, Choiniere J19,20,21, Kolker N22,23,24, Hancock WS25,26, Kolker E27,28,29,30, Fanayan S31.

Author information

1
Bioinformatics and High-Throughput Analysis Laboratory, Seattle Children's Research Institute, Seattle, WA 98101, USA. roghig@yahoo.com.
2
Data and Analytics, Seattle Children's Hospital, Seattle, WA 98101, USA. roghig@yahoo.com.
3
Data-Enabled Life Sciences Alliance (DELSA), Seattle, WA 98101, USA. roghig@yahoo.com.
4
High-Throughput Analysis Core, Seattle Children's Research Institute, Seattle, WA 98101, USA. roghig@yahoo.com.
5
Department of Chemistry and Biological Sciences, Macquarie University, Sydney 2109, Australia. jessiekala7@yahoo.com.
6
Department of Chemistry and Biological Sciences, Macquarie University, Sydney 2109, Australia. wilkins.devan@gmail.com.
7
Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA. fangfei3.yan@gmail.com.
8
Department of Chemistry and Biological Sciences, Macquarie University, Sydney 2109, Australia. manveen.sethi@students.mq.edu.au.
9
Beijing Genomics Institute, Shenzhen 518083, Guangdong, China. linl@genomics.org.cn.
10
Beijing Genomics Institute, Shenzhen 518083, Guangdong, China. siqiliu@genomics.org.cn.
11
Chinese Academy of Sciences, Beijing 100101, China. siqiliu@genomics.org.cn.
12
Bioinformatics and High-Throughput Analysis Laboratory, Seattle Children's Research Institute, Seattle, WA 98101, USA. elizabeth.montague@seattlechildrens.org.
13
Data and Analytics, Seattle Children's Hospital, Seattle, WA 98101, USA. elizabeth.montague@seattlechildrens.org.
14
Data-Enabled Life Sciences Alliance (DELSA), Seattle, WA 98101, USA. elizabeth.montague@seattlechildrens.org.
15
High-Throughput Analysis Core, Seattle Children's Research Institute, Seattle, WA 98101, USA. elizabeth.montague@seattlechildrens.org.
16
Data and Analytics, Seattle Children's Hospital, Seattle, WA 98101, USA. imrepnw@live.com.
17
Data-Enabled Life Sciences Alliance (DELSA), Seattle, WA 98101, USA. imrepnw@live.com.
18
High-Throughput Analysis Core, Seattle Children's Research Institute, Seattle, WA 98101, USA. imrepnw@live.com.
19
Bioinformatics and High-Throughput Analysis Laboratory, Seattle Children's Research Institute, Seattle, WA 98101, USA. john.choiniere@gmail.com.
20
Data and Analytics, Seattle Children's Hospital, Seattle, WA 98101, USA. john.choiniere@gmail.com.
21
Data-Enabled Life Sciences Alliance (DELSA), Seattle, WA 98101, USA. john.choiniere@gmail.com.
22
Data and Analytics, Seattle Children's Hospital, Seattle, WA 98101, USA. ncherryus@gmail.com.
23
Data-Enabled Life Sciences Alliance (DELSA), Seattle, WA 98101, USA. ncherryus@gmail.com.
24
High-Throughput Analysis Core, Seattle Children's Research Institute, Seattle, WA 98101, USA. ncherryus@gmail.com.
25
Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA. wi.hancock@neu.edu.
26
Department of Biomedical Sciences, Macquarie University, Sydney NSW 2109, Australia. wi.hancock@neu.edu.
27
Bioinformatics and High-Throughput Analysis Laboratory, Seattle Children's Research Institute, Seattle, WA 98101, USA. egnklkr@gmail.com.
28
Data and Analytics, Seattle Children's Hospital, Seattle, WA 98101, USA. egnklkr@gmail.com.
29
Data-Enabled Life Sciences Alliance (DELSA), Seattle, WA 98101, USA. egnklkr@gmail.com.
30
Departments of Biomedical Informatics and Medical Education and Pediatrics, University of Washington School of Medicine, Seattle, WA 98195, USA. egnklkr@gmail.com.
31
Department of Biomedical Sciences, Macquarie University, Sydney NSW 2109, Australia. susan.fanayan@mq.edu.au.

Abstract

Medulloblastoma (MB) is the most common malignant pediatric brain tumor. Patient survival has remained largely the same for the past 20 years, with therapies causing significant health, cognitive, behavioral and developmental complications for those who survive the tumor. In this study, we profiled the total transcriptome and proteome of two established MB cell lines, Daoy and UW228, using high-throughput RNA sequencing (RNA-Seq) and label-free nano-LC-MS/MS-based quantitative proteomics, coupled with advanced pathway analysis. While Daoy has been suggested to belong to the sonic hedgehog (SHH) subtype, the exact UW228 subtype is not yet clearly established. Thus, a goal of this study was to identify protein markers and pathways that would help elucidate their subtype classification. A number of differentially expressed genes and proteins, including a number of adhesion, cytoskeletal and signaling molecules, were observed between the two cell lines. While several cancer-associated genes/proteins exhibited similar expression across the two cell lines, upregulation of a number of signature proteins and enrichment of key components of SHH and WNT signaling pathways were uniquely observed in Daoy and UW228, respectively. The novel information on differentially expressed genes/proteins and enriched pathways provide insights into the biology of MB, which could help elucidate their subtype classification.

KEYWORDS:

Daoy; SHH subtype; UW228; WNT subtype; medulloblastoma; proteome; transcriptome

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