Project description:This study constructed a non-gapped bacterial artificial chromosomes (BAC) array containing 3604 BAC clones covering 18 lung cancer-related chromosome imbalance hotspot regions. Using this specialized array, DNA from tumor and normal tissues of 40 Asian and 20 Caucasian non-small cell lung cancer (NSLCL) patients was analyzed by array-comparative genomic hybridization (array-CGH). Block-wise normalization and a Bayes regression approach were used to refine the chromosomal imbalance regions identified by array-CGH. The array-CGH results then analyzed by MetaCore software to identify potential cancer-related genes. Finally, 273 genes showing significantly associated with molecular pathway, cancer biomarker, and gene ontology database, such as ZNF322A on 6p22.1, ARHGAP19 on 10q24.1, FRAT2 on 10q24.1, and PAFAH1B1 on 17p13.3 functioning in MAPK, Rho GTPase, and Wnt, and motility control pathways with frequent copy number gain were selected. This study mapped concisely the novel oncogenes or tumor suppressor genes in lung cancer and revealed insights of difference on chromosomal imbalance between lung cancer from Asian and Caucasian. Clinical samples preparation and DNA extraction: Tissues were collected after obtaining appropriate institutional review board permission and informed consent from the recruited patients. Surgically resected tumor tissue and corresponding normal tissue were collected from 40 patients diagnosed with primary NSCLC admitted to Taipei Veterans General Hospital, Taiwan and 20 Caucasian NSCLC tumor tissues from University of Chicago, USA. Histological classification was determined according to the WHO classification and the tumor-node-metastasis system. Information on the age, sex, tumor type, tumor stage and smoking history of the patients was obtained from hospital records. The genomic DNA was prepared using proteinase K digestion and phenol-chloroform extraction. Array-CGH: The genomic microarray used containing 3604 BAC clones representing the human genome at 18 non-gap chromosome regions. Clone mapping was analyzed using the BAC end pairs database of UCSC Genome Bioinformatics (http://genome.ucsc.edu/). The BAC library used was RP-11, which was provided from Genome Research Center, University of Yang-Ming. The extracted BAC DNA was amplified to 10 μg by Phi29 DNA polymerase reaction (TempliPhi DNA Sequencing Template Amplification Kit, Amersham, Princeton, NJ), and digested by DNaseI (New England Biolabs, Ipswich, MA), and purified by MultiScreen-PCR Plates (Millipore, Danvers, MA). After digestion, the DNA fragments were resolved by gel electrophoresis and the fragment size were optimized to within 0.5–3 kb. Finally, the purified BAC DNA fragments were dotted triplicate in 72 blocks on the glass slides (Corning, NY, USA) with spotting solution (50% DMSO, 50% D2H2O). In brief, approximately 500 ng of tumor genomic DNA and reference DNA (for Asian samples: 28 matched-normal genomic DNA pool; for Caucasian samples: commercial human genomic DNA, Invitrogen) were labeled by random priming using BioPrime DNA Labeling System (Invitrogen) with Cy3-dCTP (tumor) or Cy5-dCTP (reference). Labeled tumor and reference DNA were combined together with 100 μg human Cot-1 DNA (Invitrogen). Hybridization was performed using MAUI hybridization system (BioMcro Systems, Salt Lake City, UT), agitating the hybridization solution for 50 hours at 50℃. The arrays were scanned using scanner GenePix4000B (Axon Instruments, Foster City, CA) and the images were segmented and transformed to Cy3-Cy5 log ratio using GenePix software by Axon Instruments, Inc. (http://www.axon.com). Further data processing, a normalization method called “block-wise normalization”, which normalized the array-CGH data by the log ratio of the self-self hybridization of reference DNA according to the mean and the standard deviations of each array block, was established.

Project description:Interethnic variability in chemotherapy response is becoming increasingly evident, making approaches for customizing chemotherapy treatment to different ethnic populations desirable. At the same time, significant genetic variation has also been observed between ethnic groups, including many germline and somatic pharmacogenetic variants involved in chemotherapy pharmacology. Recently, based on meta-analyses of studies on germline pharmacogenetic variant frequencies and clinical trials, the investigators found that chemotherapy outcomes between Asians and Caucasians colorectal cancer (CRC) patients could potentially be inferred from the frequencies of variants between the ethnic groups and their respective biological functions. In this study, the investigators seek to further clarify the validity of using pharmacogenetic variants to customize chemotherapy between ethnicities through the following specific aims: (1) To verify the differences observed in the frequency of germline pharmacogenetic variants related to chemotherapy between Asian and Caucasian CRC patients, (2) To test whether variations in the frequency of somatic pharmacogenetic gene mutations between Asian and Caucasian CRC patients could be used to infer differences in clinical outcomes between the two ethnicities. (3) (4) For Aim 1, DNA samples from approximately 1000 Asian and Caucasian CRC patients each will be analyzed for the frequency of a panel of germline pharmacogenetic variants identified in our meta-analyses using high-throughput methodology. For Aim 2, meta-analyses will be performed on pharmacogenetic studies and clinical trials to establish the relative frequencies of somatic variants and clinical outcomes in Asian and Caucasian CRC patients. These frequencies will be verified on the same series of DNA samples used in Aim 1. The clinical outcomes inferred from the frequency differences and biological functions will then be compared to those summarized from clinical trials. This data could provide a basis for developing a rational approach to customizing chemotherapy in non-Caucasian populations and improve assessment of drug feasibility in different ethnic populations.If validated, this working hypothesis would be of high clinical interest, giving the opportunity to use this as a DNA prognosis biomarker in CRC. Pharmacogenetic frequencies could be a potentially useful approach for predicting likely chemotherapy outcomes in non-Caucasian populations

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