Literature DB >> 30267407

Functional genomics identifies AMPD2 as a new prognostic marker for undifferentiated pleomorphic sarcoma.

Martin F Orth1, Julia S Gerke1, Thomas Knösel2, Annelore Altendorf-Hofmann3, Julian Musa1, Rebeca Alba-Rubio1, Stefanie Stein1, Tilman L B Hölting1, Florencia Cidre-Aranaz1, Laura Romero-Pérez1, Marlene Dallmayer1, Michaela C Baldauf1, Aruna Marchetto1, Giuseppina Sannino1, Maximilian M L Knott1,2, Fabienne Wehweck1,2, Shunya Ohmura1, Jing Li1, Michiyuki Hakozaki4, Thomas Kirchner2,5,6, Thomas Dandekar7, Elke Butt8, Thomas G P Grünewald1,2,5,6.   

Abstract

Soft-tissue sarcomas are rare, heterogeneous, and often aggressive mesenchymal cancers. Many of them are associated with poor outcome, partially because biomarkers that can identify high-risk patients are lacking. Studies on sarcomas are often limited by small sample-sizes rendering the identification of biomarkers difficult when focusing on individual cohorts. However, the increasing number of publicly available 'omics' data opens inroads to overcome this obstacle. Here, we combine transcriptome analyses, immunohistochemistry, and functional assays to show that high adenosine monophosphate deaminase 2 (AMPD2) is a robust prognostic biomarker for worse outcome in undifferentiated pleomorphic sarcoma (UPS). Gene expression and survival data for UPS from two independent studies were subjected to survival association-testing. Genes, whose high expression was significantly correlated with worse outcome in both cohorts, were considered as biomarker candidates. The best candidate, AMPD2, was validated in a tissue microarray. Analysis of DNA copy-number data and matched transcriptomes indicated that high AMPD2 expression is significantly correlated with gains at the AMPD2 locus. Gene set enrichment analyses of AMPD2 co-expressed genes in both transcriptome datasets suggested that AMPD2-high UPS are enriched in tumorigenic signatures. Consistently, knockdown of AMPD2 by RNA interference in an UPS cell line inhibited proliferation in vitro and tumorigenicity in vivo. Collectively, we provide evidence that AMPD2 may serve as a biomarker for outcome prediction in UPS. Our study exemplifies how the integration of 'omics' data, immunohistochemistry, and functional experiments can identify novel biomarkers even in a rare sarcoma, which may serve as a blueprint for biomarker identification for other rare cancers.
© 2018 UICC.

Entities:  

Keywords:  AMPD2; Undifferentiated pleomorphic sarcoma; biomarker; prognostics

Mesh:

Substances:

Year:  2018        PMID: 30267407     DOI: 10.1002/ijc.31903

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  7 in total

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Journal:  Nat Rev Endocrinol       Date:  2020-06-03       Impact factor: 43.330

Review 2.  A scoping review and proposed workflow for multi-omic rare disease research.

Authors:  Katie Kerr; Helen McAneney; Laura J Smyth; Caitlin Bailie; Shane McKee; Amy Jayne McKnight
Journal:  Orphanet J Rare Dis       Date:  2020-04-28       Impact factor: 4.123

3.  Development and validation of prognostic markers in sarcomas base on a multi-omics analysis.

Authors:  Yongchun Song; Kui Yang; Tuanhe Sun; Ruixiang Tang
Journal:  BMC Med Genomics       Date:  2021-01-28       Impact factor: 3.063

Review 4.  Application of Multi-Omics Approach in Sarcomas: A Tool for Studying Mechanism, Biomarkers, and Therapeutic Targets.

Authors:  Zijian Zou; Wei Sun; Yu Xu; Wanlin Liu; Jingqin Zhong; Xinyi Lin; Yong Chen
Journal:  Front Oncol       Date:  2022-07-08       Impact factor: 5.738

Review 5.  On the Relevance of Soft Tissue Sarcomas Metabolic Landscape Mapping.

Authors:  Miguel Esperança-Martins; Iola F Duarte; Mara Rodrigues; Joaquim Soares do Brito; Dolores López-Presa; Luís Costa; Isabel Fernandes; Sérgio Dias
Journal:  Int J Mol Sci       Date:  2022-09-28       Impact factor: 6.208

6.  A Prognostic Model Based on Six Metabolism-Related Genes in Colorectal Cancer.

Authors:  Yuan-Lin Sun; Yang Zhang; Yu-Chen Guo; Zi-Hao Yang; Yue-Chao Xu
Journal:  Biomed Res Int       Date:  2020-08-31       Impact factor: 3.411

7.  Cross-ancestry GWAS meta-analysis identifies six breast cancer loci in African and European ancestry women.

Authors:  Babatunde Adedokun; Zhaohui Du; Guimin Gao; Thomas U Ahearn; Kathryn L Lunetta; Gary Zirpoli; Jonine Figueroa; Esther M John; Leslie Bernstein; Wei Zheng; Jennifer J Hu; Regina G Ziegler; Sarah Nyante; Elisa V Bandera; Sue A Ingles; Michael F Press; Sandra L Deming-Halverson; Jorge L Rodriguez-Gil; Song Yao; Temidayo O Ogundiran; Oladosu Ojengbede; William Blot; Melissa A Troester; Katherine L Nathanson; Anselm Hennis; Barbara Nemesure; Stefan Ambs; Peter N Fiorica; Lara E Sucheston-Campbell; Jeannette T Bensen; Lawrence H Kushi; Gabriela Torres-Mejia; Donglei Hu; Laura Fejerman; Manjeet K Bolla; Joe Dennis; Alison M Dunning; Douglas F Easton; Kyriaki Michailidou; Paul D P Pharoah; Qin Wang; Dale P Sandler; Jack A Taylor; Katie M O'Brien; Cari M Kitahara; Adeyinka G Falusi; Chinedum Babalola; Joel Yarney; Baffour Awuah; Beatrice Addai-Wiafe; Stephen J Chanock; Andrew F Olshan; Christine B Ambrosone; David V Conti; Elad Ziv; Olufunmilayo I Olopade; Montserrat Garcia-Closas; Julie R Palmer; Christopher A Haiman; Dezheng Huo
Journal:  Nat Commun       Date:  2021-07-07       Impact factor: 14.919

  7 in total

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