TIGP--Analysis and applications of copy number alterations in cancer genomes
- LecturerDr. Yuh-Shan Jou (Institute of Biomedical Sciences, Academia Sinica)
Host: Miss Elsa Pan - Time2010-11-25 (Thu.) 14:00 – 15:00
- LocationAuditorium 106 at new IIS Building
Abstract
Abstract
Recurrent cancer genome aberrations are indicators of residing crucial
cancer genes. Although recent advances in genomic technologies have led to
a global view of cancer genome aberrations, the identification of target
genes and biomarkers from the aberrant loci remains difficult. To facilitate
searches of cancer genes in human hepatocellular carcinoma (HCC), we
established a comprehensive protocol to analyze copy number alterations
(CNAs) in cancer genomes using high-density single nucleotide polymorphism
arrays with unpaired reference genomes. We identified common HCC genes by
overlapping the shared aberrant loci in multiple cell lines with functional
validation and clinical implications. A total of 653 amplicons and 57
homozygous deletions (HDs) were revealed in 23 cell lines. To search for novel
HCC genes, we overlapped aberrant loci to uncover 6 HDs and 126 amplicons
shared by at least two cell lines. We selected two novel genes, fibronectin
type III domain containing 3B (FNDC3B) at the 3q26.3 overlapped amplicon and
solute carrier family 29 member 2 (SLC29A2) at the 11q13.2 overlapped
amplicon, to investigate their aberrations in HCC tumorigenesis. Aberrant
up-regulation of FNDC3B and SLC29A2 occurred in multiple HCC data sets.
Knockdown of these genes in amplified cells decreased cell proliferation,
anchorage-independent growth, and tumor formation in xenograft models.
Importantly, up-regulation of SLC29A2 in HCC tissues was significantly
associated with advanced stages (P = 0.0031), vascular invasion (P = 0.0353),
and poor patient survival (P = 0.0325). Overexpression of FNDC3B or SLC29A2
in unamplified HCC cells promoted cell proliferation through activation of
the signal transducer and activator of transcription 3 signaling pathway.
CONCLUSION: A standardized genome-wide CNA analysis protocol using data from
user-generated or public domains normalized with unpaired reference genomes
has been established to facilitate high-throughput detection of cancer genes
as significant target genes and biomarkers for cancer diagnosis and therapy.
PMID: 20799341.