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Identify potential driver genes for PAX-FOXO1 fusion-negative rhabdomyosarcoma through frequent gene co-expression network mining.
Zhan, Xiaohui; Liu, Yusong; Jannu, Asha Jacob; Huang, Shaoyang; Ye, Bo; Wei, Wei; Pandya, Pankita H; Ye, Xiufen; Pollok, Karen E; Renbarger, Jamie L; Huang, Kun; Zhang, Jie.
Afiliación
  • Zhan X; Department of Bioinformatics, School of Basic Medicine, Chongqing Medical University, Chongqing, China.
  • Liu Y; College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, China.
  • Jannu AJ; Department of Biostatistics and Health Data Science, Indiana University, School of Medicine, Indianapolis, IN, United States.
  • Huang S; Carmel High School, Indianapolis, IN, United States.
  • Ye B; Department of Bioinformatics, School of Basic Medicine, Chongqing Medical University, Chongqing, China.
  • Wei W; Department of Bioinformatics, School of Basic Medicine, Chongqing Medical University, Chongqing, China.
  • Pandya PH; Department of Pediatrics, Indiana University, School of Medicine, Indianapolis, IN, United States.
  • Ye X; College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, China.
  • Pollok KE; Department of Pediatrics, Indiana University, School of Medicine, Indianapolis, IN, United States.
  • Renbarger JL; Department of Pediatrics, Indiana University, School of Medicine, Indianapolis, IN, United States.
  • Huang K; Department of Biostatistics and Health Data Science, Indiana University, School of Medicine, Indianapolis, IN, United States.
  • Zhang J; Department of Medical and Molecular Genetics, Indiana University, School of Medicine, Indianapolis, IN, United States.
Front Oncol ; 13: 1080989, 2023.
Article en En | MEDLINE | ID: mdl-36793601
ABSTRACT

Background:

Rhabdomyosarcoma (RMS) is a soft tissue sarcoma usually originated from skeletal muscle. Currently, RMS classification based on PAX-FOXO1 fusion is widely adopted. However, compared to relatively clear understanding of the tumorigenesis in the fusion-positive RMS, little is known for that in fusion-negative RMS (FN-RMS).

Methods:

We explored the molecular mechanisms and the driver genes of FN-RMS through frequent gene co-expression network mining (fGCN), differential copy number (CN) and differential expression analyses on multiple RMS transcriptomic datasets.

Results:

We obtained 50 fGCN modules, among which five are differentially expressed between different fusion status. A closer look showed 23% of Module 2 genes are concentrated on several cytobands of chromosome 8. Upstream regulators such as MYC, YAP1, TWIST1 were identified for the fGCN modules. Using in a separate dataset we confirmed that, comparing to FP-RMS, 59 Module 2 genes show consistent CN amplification and mRNA overexpression, among which 28 are on the identified chr8 cytobands. Such CN amplification and nearby MYC (also resides on one of the above cytobands) and other upstream regulators (YAP1, TWIST1) may work together to drive FN-RMS tumorigenesis and progression. Up to 43.1% downstream targets of Yap1 and 45.8% of the targets of Myc are differentially expressed in FN-RMS vs. normal comparisons, which also confirmed the driving force of these regulators.

Discussion:

We discovered that copy number amplification of specific cytobands on chr8 and the upstream regulators MYC, YAP1 and TWIST1 work together to affect the downstream gene co-expression and promote FN-RMS tumorigenesis and progression. Our findings provide new insights for FN-RMS tumorigenesis and offer promising targets for precision therapy. Experimental investigation about the functions of identified potential drivers in FN-RMS are in progress.
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Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Oncol Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Oncol Año: 2023 Tipo del documento: Article