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Author Kane, John M. ♦ Magliocco, Anthony ♦ Zhang, Qiang ♦ Wang, Dian ♦ Klimowicz, Alex ♦ Harris, Jonathan ♦ Simko, Jeff ♦ DeLaney, Thomas ♦ Kraybill, William ♦ Kirsch, David G.
Editor Kawai, Akira
Source Hindawi
Content type Text
Publisher Hindawi
File Format PDF
Copyright Year ©2018
Language English
Abstract Background. Sarcoma mortality remains high despite adjuvant chemotherapy. Biomarker predictors of treatment response and outcome could improve treatment selection. Methods. Tissue microarrays (TMAs) were created using pre- and posttreatment tumor from two prospective trials (MGH pilot and RTOG 9514) of neoadjuvant/adjuvant MAID chemotherapy and preoperative radiation. Biomarkers were measured using automated computerized imaging (AQUA or ACIS). Expression was correlated with disease-free survival (DFS), distant disease-free survival (DDFS), and overall survival (OS). Results. Specimens from 60 patients included 23 pretreatment (PRE), 40 posttreatment (POST), and 12 matched pairs (MPs). In the MP set, CAIX, GLUT1, and PARP1 expression significantly decreased following neoadjuvant therapy, but p53 nuclear/cytoplasmic (N/C) ratio increased. In the PRE set, no biomarker expression was associated with DFS, DDFS, or OS. In the POST set, increased p53 N/C ratio was associated with a significantly decreased DFS and DDFS (HR 4.13, p=0.017; HR 4.16, p=0.016), while increased ERCC1 and XPF expression were associated with an improved DFS and DDFS. No POST biomarkers were associated with OS. Conclusions. PRE biomarker expression did not predict survival outcomes. Expression pattern changes after neoadjuvant chemoradiation supports the concepts of tumor reoxygenation, altered HIF-1α signaling, and a p53 nuclear accumulation DNA damage response. Clinical Trial Registration. NRG Oncology RTOG 9514 is registered with ClinicalTrials.gov. The ClinicalTrials.gov Identifier is NCT00002791.
ISSN 1357714X
Learning Resource Type Article
Publisher Date 2018-02-28
Rights License This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
e-ISSN 13691643
Journal Sarcoma
Volume Number 2018
Page Count 10


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