Сибирский онкологический журнал (Feb 2016)

MICROARRAY ANALYSIS OF DNA COPY NUMBER ABERRATION IN BREAST TUMOR: CORRELATION WITH THE EFFICACY OF NEOADJUVANT CHEMOTHERAPY

  • N. V. Litviakov,
  • М. М. Tsyganov,
  • N. V. Cherdyntseva,
  • Е. М. Slonimskaya,
  • P. V. Ivankovskaya,
  • М. К. Ibragimova,
  • Е. Yu. Garbukov,
  • S. А. Korostelev,
  • О. Yu. Potapova,
  • Е. L. Choinzonov

Journal volume & issue
Vol. 0, no. 3
pp. 19 – 27

Abstract

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This study presents the new evidences for DNA Copy Number Aberration (CNA) within breast tumors and its association with the efficacy of preoperative (neoadjuvant) chemotherapy.Methods. 68 breast cancer patients were treated with 2–4 courses of neoadjuvant chemotherapy. Unbalanced chromosome abnormalities – numeric and structural CNA in biopsy specimens were tested using high-density microarray platform CytoScanTM HD Array (Affymetrix, USA). Immediate tumor response to NAC was measured in accordance with recommendations of WHO.Results. 1q43 amplification correlated with good response to NAC. Partial tumor regression was observed in 83 % (33/39) of patients with 1q43 amplification, whereas no response to NAC was found in 78 % (18/23) of patients with normal 1q43 region (р=0.00085 Fisher test, Bonferroni correction). Among patients with chromosomal deletions at 11q22.1-23.3, 83 % (25/30) manifested the response to NAC, whereas 68 % (23/34) deletion-free persons did not respond to therapy. Combination of amplification and deletion markers increased the sensitivity and specificity for predicting response to NАС. Amplification in 1q43 along with deletion in 18р11.21 loci resulted in partial tumor regression in 92 % (35/38) of patients. In the case of the normal status of these loci, 81 % (21/26) of patients had no response to NAC (р=0.000002).Conclusion. The presence of unbalanced, chromosome abnormalities in 1q, 11q и 18p loci within breast tumors before treatment correlates with good response to NAC and can be used as a marker for predicting response to neoadjuvant chemotherapy with high confidence interval.

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