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17p12 deletion in breast cancer predicts resistance to neoadjuvant chemotherapy

Cited 4 time in Web of Science Cited 4 time in Scopus
Authors

Han, Wonshik; Woo, Jung Hoon; Jeon, Yoon Kyung; Yang, Song-Ju; Cho, Jihyoung; Ko, Eunyoung; Kim, Tae-You; Im, Seock-Ah; Oh, Do-Youn; Park, In-Ae; Hwang, Ki-Tae; Moon, Hyeong-Gon; Yang, Kap-Seok; Noh, Dung-Young

Issue Date
2011-09
Publisher
Spandidos Publications
Citation
Experimental and Therapeutic Medicine, Vol.2 No.5, pp.799-804
Abstract
Numerous studies have attempted to identify gene expression profiles which can be utilized to predict responses to neoadjuvant chemotherapy (NAC), but their findings are not clinically applicable at present. In the present study, we sought to determine DNA copy number alterations (CNAs) in breast cancer tissues which are associated with the response to NAC. Frozen tumor tissues from 63 breast cancer patients were obtained using core needle biopsy prior to NAC (3 cycles of docetaxel plus adriamycin) and were microdissected. Array comparative genomic hybridization (array CGH) with 4,045 bacterial artificial chromosome (BAC) probes was performed to identify the CNAs. Changes in tumor size in response to NAC were measured via magnetic resonance imaging. Fluorescence in situ hybridization (FISH) was conducted to verify array CGH results and for independent validation studies. CNAs at eight chromosomal loci encompassing 24 clones were correlated with changes in tumor size after NAC (p<0.05; t-test). Two CNAs were selected, 17p12 deletion and 17q21.32-33 gain, which were significantly associated with a smaller reduction in tumor size following NAC, via prioritization of the regions containing the candidate genes. In an independent validation set of samples from 39 patients, FISH assay further showed that the 17p12 deletion was markedly associated with smaller changes in tumor size (p=0.006), while the 17q21.32-33 gain was not significant (p=0.309). In conclusion, we successfully identified a 17p12 deletion in breast cancer tissue which can be applied in predicting tumor resistance to NAC.
ISSN
1792-0981
URI
https://hdl.handle.net/10371/177171
DOI
https://doi.org/10.3892/etm.2011.299
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  • College of Medicine
  • Department of Medicine
Research Area Clinical Medicine

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