Abstract P1-04-10: Using the allele specific copy number profile to predict the poor prognosis breast cancer patients of Taiwanese
Authors: W Shia, D Chen
Journal: Cancer Research (2017)

Abstract Introduction:Strategies are needed for the identification of a poor response to treatment and determination of appropriate strategies for breast cancer patients. As an integral component in the tumor's genetic profile, knowledge of somatic copy number aberrations can lead to insights into the tumor's genetic history and may allow for more accurate prognosis and most appropriate treatment for the patient. By quantifying the number of copies of each allele at each variant loci rather than the total number of chromosome copies, allele-specific copy number (AsCN) estimation is an important step to the characterization of tumor genomes. In this study, AsCN profile was generated and used to predict the poor prognosis breast cancer patients. Methods: The blood DNA samples from 56 Taiwanese breast cancer patients were collected from Sep 2005 to May 2015. There are 24 patients were administrated with chemotherapy (42.85%), and 9 patients were recurrent (16.07%), 5 patients were metastasis (8.92%). Affymetrix Human SNP 6.0 microarray chip was utilized to detect the alleles and copy number (CN) variations. The state of CN was distinguished from the intensity of the CN probe on the array. These states of CN were created from unpaired analysis with reference samples (HAPMAP Asian 44 samples), and utilized BRLMM-P+ algorithm from Affymetrix. The AsCN profile of patients were established with HMM algorithm, and analyzed by unpaired analysis in Partek Genomic Suite 6.6 (Partek Inc., St. Louis, MO, USA). The final result was reported after combined the AsCN result with the segmentation result of copy number variation (CNV) analysis. Two segmentation algorithms were utilized to determine the CNV region. First is circular segmentation algorithm, with minimum 10 genomic markers in each segment and P-value threshold &amp;lt; 0.0001. Second algorithm is hidden Markov model segmentation (HMM), with the parameter sigma equal to 0.99 and likelihood equal to 0.985. Results: Four allele-specific imbalance regions which located on gene ABCB11 in 2q31.1, PREX2 in 8q13.2, GPHN in 14q23.3, and mir8062 in 20p 12.3 were detected and highly related to the poor prognosis of chemotherapy. The mean of CN state of these regions was lower than 1.2. The most significant region is the located on gene mir8062 in 20p12.3 (hsa-mir-8062), 22 of 54 patients were detected to bring this imbalance region on genome. The function of this miRNA is not clear now, and needs more investigated. Conclusions: We have demonstrated the feasibility of finding the association of allele-specific imbalance regions on genome with the poor prognosis in breast cancer by generating the AsCN profile from patients. This preliminary result shows these alleles-specific imbalance regions of the genome have the possibility of playing the important role in the recurrent and metastasis of breast cancer. Citation Format: Shia W, Chen D. Using the allele specific copy number profile to predict the poor prognosis breast cancer patients of Taiwanese [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-04-10.