Literature DB >> 20213408

Molecular classification of osteosarcoma.

Ching C Lau1.   

Abstract

Genomic technologies are now being used to identify new molecular markers or signatures for both diagnostic and prognostic purposes. Recently, we reported the molecular classification of pediatric osteosarcoma by expression profiling in an attempt to identify a signature that could predict the chemoresistance of a tumor before treatment is initiated. We identified a 45-gene signature that discriminates between good and poor responders to chemotherapy in osteosarcoma. Using this classifier, we can predict with 100% accuracy the chemoresponse of osteosarcoma patients prior to the initiation of treatment. These encouraging results suggest that the genomic approach will revolutionize the diagnosis and prognostication of osteosarcoma patients and improve their outcome through predictive, personalized care.

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Year:  2009        PMID: 20213408     DOI: 10.1007/978-1-4419-0284-9_26

Source DB:  PubMed          Journal:  Cancer Treat Res        ISSN: 0927-3042


  4 in total

1.  Synergistic relationship between dipeptidyl peptidase IV and neutral endopeptidase expression and the combined prognostic significance in osteosarcoma patients.

Authors:  Hongtao Zhang; Haibin Lin; Xiaoqiong Mo; Guoli Chen; Lijun Lin
Journal:  Med Oncol       Date:  2013-05-18       Impact factor: 3.064

Review 2.  Caveolin-1 in sarcomas: friend or foe?

Authors:  Miguel Sáinz-Jaspeado; Juan Martin-Liberal; Laura Lagares-Tena; Silvia Mateo-Lozano; Xavier Garcia del Muro; Oscar M Tirado
Journal:  Oncotarget       Date:  2011-04

3.  Role of Topoisomerases in Pediatric High Grade Osteosarcomas: TOP2A Gene Is One of the Unique Molecular Biomarkers of Chemoresponse.

Authors:  Aurelia Nguyen; Christelle Lasthaus; Eric Guerin; Luc Marcellin; Erwan Pencreach; Marie-Pierre Gaub; Dominique Guenot; Natacha Entz-Werle
Journal:  Cancers (Basel)       Date:  2013-06-04       Impact factor: 6.639

4.  SLC25A22 Promotes Proliferation and Metastasis of Osteosarcoma Cells via the PTEN Signaling Pathway.

Authors:  Ming-Wei Chen; Xue-Jian Wu
Journal:  Technol Cancer Res Treat       Date:  2018-01-01
  4 in total

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