Dataset Information

The database of chromosome imbalance regions and genes resided in lung cancer from Asian and Caucasian identified by array-comparative genomic hybridization.

ABSTRACT: Cancer-related genes show racial differences. Therefore, identification and characterization of DNA copy number alteration regions in different racial groups helps to dissect the mechanism of tumorigenesis.Array-comparative genomic hybridization (array-CGH) was analyzed for DNA copy number profile in 40 Asian and 20 Caucasian lung cancer patients. Three methods including MetaCore analysis for disease and pathway correlations, concordance analysis between array-CGH database and the expression array database, and literature search for copy number variation genes were performed to select novel lung cancer candidate genes. Four candidate oncogenes were validated for DNA copy number and mRNA and protein expression by quantitative polymerase chain reaction (qPCR), chromogenic in situ hybridization (CISH), reverse transcriptase-qPCR (RT-qPCR), and immunohistochemistry (IHC) in more patients.We identified 20 chromosomal imbalance regions harboring 459 genes for Caucasian and 17 regions containing 476 genes for Asian lung cancer patients. Seven common chromosomal imbalance regions harboring 117 genes, included gain on 3p13-14, 6p22.1, 9q21.13, 13q14.1, and 17p13.3; and loss on 3p22.2-22.3 and 13q13.3 were found both in Asian and Caucasian patients. Gene validation for four genes including ARHGAP19 (10q24.1) functioning in Rho activity control, FRAT2 (10q24.1) involved in Wnt signaling, PAFAH1B1 (17p13.3) functioning in motility control, and ZNF322A (6p22.1) involved in MAPK signaling was performed using qPCR and RT-qPCR. Mean gene dosage and mRNA expression level of the four candidate genes in tumor tissues were significantly higher than the corresponding normal tissues (P<0.001~P=0.06). In addition, CISH analysis of patients indicated that copy number amplification indeed occurred for ARHGAP19 and ZNF322A genes in lung cancer patients. IHC analysis of paraffin blocks from Asian Caucasian patients demonstrated that the frequency of PAFAH1B1 protein overexpression was 68% in Asian and 70% in Caucasian.Our study provides an invaluable database revealing common and differential imbalance regions at specific chromosomes among Asian and Caucasian lung cancer patients. Four validation methods confirmed our database, which would help in further studies on the mechanism of lung tumorigenesis.

SUBMITTER: Lo FY

PROVIDER: S-EPMC3488578 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature

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The database of chromosome imbalance regions and genes resided in lung cancer from Asian and Caucasian identified by array-comparative genomic hybridization.

Lo Fang-Yi FY Chang Jer-Wei JW Chang I-Shou IS Chen Yann-Jang YJ Hsu Han-Shui HS Huang Shiu-Feng Kathy SF Tsai Fang-Yu FY Jiang Shih Sheng SS Kanteti Rajani R Nandi Suvobroto S Salgia Ravi R Wang Yi-Ching YC

BMC cancer 20120612

<h4>Background</h4>Cancer-related genes show racial differences. Therefore, identification and characterization of DNA copy number alteration regions in different racial groups helps to dissect the mechanism of tumorigenesis.<h4>Methods</h4>Array-comparative genomic hybridization (array-CGH) was analyzed for DNA copy number profile in 40 Asian and 20 Caucasian lung cancer patients. Three methods including MetaCore analysis for disease and pathway correlations, concordance analysis between array- ...[more]

PMID: 22691236

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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:Breast cancer is a profoundly heterogeneous disease with respect to biological and clinical behavior. Gene expression profiling has been used to dissect this complexity and stratify tumors into intrinsic gene expression subtypes associated with distinct biology, patient outcome and different genomic alterations. Additionally, breast tumors occurring in individuals with germline BRCA1 or BRCA2 mutations typically fall into distinct subtypes. We applied global DNA copy number and gene expression profiling in 359 breast tumors. All tumors were classified according to intrinsic gene expression subtypes and included cases from genetically predisposed women. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was used to identify significant DNA copy number aberrations and genomic subgroups of breast cancer. We identified 31 genomic regions that were highly amplified in >1% of the 359 breast tumors. Several amplicons were found to co-occur, the 8p12 and 11q13.3 regions being the most frequent combination besides amplicons on the same chromosomal arm. Unsupervised hierarchical clustering with 133 significant GISTIC regions (66 and 67 with DNA copy number gain and loss, respectively) revealed six genomic subtypes, termed: 17q12, basal-complex, luminal-simple, luminal-complex, amplifier and mixed subtype. Four of them had striking similarity to intrinsic gene expression subtypes and showed association to conventional tumor biomarkers and clinical outcome. However, luminal A-classified tumors were distributed in two main genomic subtypes, luminal-simple and luminal-complex, the former group having better prognosis while the latter group included also luminal B and the majority of BRCA2-mutated tumors. The basal-complex subtype displayed extensive genomic homogeneity and harbored the majority of BRCA1-mutated tumors. The 17q12 subtype comprised mostly HER2-amplified and HER2-enriched subtype tumors and had the worst prognosis. The amplifier and mixed subtypes contained tumors from all gene expression subtypes, the former being enriched for 8p12-amplified cases while the mixed subtype included many tumors with predominantly DNA copy number losses and poor prognosis. Genomic profiling of 359 breast tumors using tiling BAC aCGH. A number of cases were hybridized as replicates or replicate as dye-swaps. Gene expression profiling of 359 breast tumors using 55K oligonucleotide microarrays.

Project description:INTRODUCTION: Breast cancer is a profoundly heterogeneous disease with respect to biologic and clinical behavior. Gene-expression profiling has been used to dissect this complexity and to stratify tumors into intrinsic gene-expression subtypes, associated with distinct biology, patient outcome, and genomic alterations. Additionally, breast tumors occurring in individuals with germline BRCA1 or BRCA2 mutations typically fall into distinct subtypes. METHODS: We applied global DNA copy number and gene-expression profiling in 359 breast tumors. All tumors were classified according to intrinsic gene-expression subtypes and included cases from genetically predisposed women. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was used to identify significant DNA copy-number aberrations and genomic subgroups of breast cancer. RESULTS: We identified 31 genomic regions that were highly amplified in > 1% of the 359 breast tumors. Several amplicons were found to co-occur, the 8p12 and 11q13.3 regions being the most frequent combination besides amplicons on the same chromosomal arm. Unsupervised hierarchical clustering with 133 significant GISTIC regions revealed six genomic subtypes, termed 17q12, basal-complex, luminal-simple, luminal-complex, amplifier, and mixed subtypes. Four of them had striking similarity to intrinsic gene-expression subtypes and showed associations to conventional tumor biomarkers and clinical outcome. However, luminal A-classified tumors were distributed in two main genomic subtypes, luminal-simple and luminal-complex, the former group having a better prognosis, whereas the latter group included also luminal B and the majority of BRCA2-mutated tumors. The basal-complex subtype displayed extensive genomic homogeneity and harbored the majority of BRCA1-mutated tumors. The 17q12 subtype comprised mostly HER2-amplified and HER2-enriched subtype tumors and had the worst prognosis. The amplifier and mixed subtypes contained tumors from all gene-expression subtypes, the former being enriched for 8p12-amplified cases, whereas the mixed subtype included many tumors with predominantly DNA copy-number losses and poor prognosis. CONCLUSIONS: Global DNA copy-number analysis integrated with gene-expression data can be used to dissect the complexity of breast cancer. This revealed six genomic subtypes with different clinical behavior and a striking concordance to the intrinsic subtypes. These genomic subtypes may prove useful for understanding the mechanisms of tumor development and for prognostic and treatment prediction purposes.

Dataset Information

The database of chromosome imbalance regions and genes resided in lung cancer from Asian and Caucasian identified by array-comparative genomic hybridization.

Publications

The database of chromosome imbalance regions and genes resided in lung cancer from Asian and Caucasian identified by array-comparative genomic hybridization.

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