Copy number changes can be a predictor for hemoglobin reduction after S-1 monotherapy in gastric cancer

Hei Cheul Jeung, Sun Young Rha, Chan Hee Park, Chong Kun Im, Sang Joon Shin, Joong Bae Ahn, Sung Hoon Noh, Jae Kyung Roh, Hyun Cheol Chung

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Amemia is a unique side effect in Korean gastric cancer patients after S-1 monotherapy. We studied gastric cancer patients from a phase II trial of S-1 monotherapy with a 2-week treatment and 1-week rest schedule. Patients from a phase II trial of S-1 monotherapy with a 4-week treatment and 2-week rest were used as a reference group. The patients were categorized into two groups based on the degree of hemoglobin reduction per cycle of S-1: the mild reduction group (MRG ΔHb/cycle ≤1.0) or severe reduction group (SRG ΔHb/cycle >1.0). ΔHb/cycle was calculated from maximum reduction of hemoglobin per one cycle of the treatment. Microarray-CGH was performed using a 17K cDNA microarray containing 15,723 unique genes. We selected genes with copy number variation defined as amplification (log2R/G >0.68) or deletion (log2R/G <-0.68), and a genetic aberration frequency difference of ≥30% between the MRG and the SRG. There were no differences in clinical factors, S-1 treatment-related factors (dose, dose intensity), toxicity, S-1 metabolism-related gene copy numbers (CYP2A6, DPD), or progression-free survival between the MRG and the SRG. Three genes were selected from microarray-CGH and logistic regression model: logit LN(Z) = (1.321) + (1.038 × PTX1) + (0.211 × MYO5A) + (0.516 × ZNF664). In the SRG, all 3 genes showed a trend of higher copy numbers than the MRG. There were no common anemia-related genes identified from different chemotherapy schedule of S-1 monotherapy. The logistics obtained from 3 genes predicted the hemoglobin reduction with an accuracy of 78%. The AUC was 0.744 for the final regression model. The combined copy number changes of the 3 genes can be developed into a biomarker in predicting S-1 treatment-related anemia.

Original languageEnglish
Pages (from-to)787-796
Number of pages10
JournalInternational journal of oncology
Volume34
Issue number3
DOIs
Publication statusPublished - 2009

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

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