Browsing by Subject "Gene amplification"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Amplification of Distant Estrogen Response Elements Deregulates Target Genes Associated with Tamoxifen Resistance in Breast Cancer
    (Elsevier, 2013) Hsu, Pei-Yin; Hsu, Hang-Kai; Lan, Xun; Juan, Liran; Yan, Pearlly S.; Labanowska, Jadwiga; Heerema, Nyla; Hsiao, Tzu-Hung; Chiu, Yu-Chiao; Chen, Yidong; Liu, Yunlong; Li, Lang; Li, Rong; Thompson, Ian M.; Nephew, Kenneth P.; Sharp, Zelton D.; Kirma, Nameer B.; Jin, Victor X.; Huang, Tim H.-M.; Medical and Molecular Genetics, School of Medicine
    A causal role of gene amplification in tumorigenesis is well known, whereas amplification of DNA regulatory elements as an oncogenic driver remains unclear. In this study, we integrated next-generation sequencing approaches to map distant estrogen response elements (DEREs) that remotely control the transcription of target genes through chromatin proximity. Two densely mapped DERE regions located on chromosomes 17q23 and 20q13 were frequently amplified in estrogen receptor-α-positive luminal breast cancer. These aberrantly amplified DEREs deregulated target gene expression potentially linked to cancer development and tamoxifen resistance. Progressive accumulation of DERE copies was observed in normal breast progenitor cells chronically exposed to estrogenic chemicals. These findings may extend to other DNA regulatory elements, the amplification of which can profoundly alter target transcriptome during tumorigenesis.
  • Thumbnail Image
    Item
    Bottom-up, integrated -omics analysis identifies broadly dosage-sensitive genes in breast cancer samples from TCGA
    (PLOS, 2019-01-17) Kechavarzi, Bobak D.; Wu, Huanmei; Doman, Thompson N.; Biohealth Informatics, School of Informatics and Computing
    The massive genomic data from The Cancer Genome Atlas (TCGA), including proteomics data from Clinical Proteomic Tumor Analysis Consortium (CPTAC), provides a unique opportunity to study cancer systematically. While most observations are made from a single type of genomics data, we apply big data analytics and systems biology approaches by simultaneously analyzing DNA amplification, mRNA and protein abundance. Using multiple genomic profiles, we have discovered widespread dosage compensation for the extensive aneuploidy observed in TCGA breast cancer samples. We do identify 11 genes that show strong correlation across all features (DNA/mRNA/protein) analogous to that of the well-known oncogene HER2 (ERBB2). These genes are generally less well-characterized regarding their role in cancer and we advocate their further study. We also discover that shRNA knockdown of these genes has an impact on cancer cell growth, suggesting a vulnerability that could be used for cancer therapy. Our study shows the advantages of systematic big data methodologies and also provides future research directions.