Ovarian Cancer: How Basic Research Can Lead to New Opportunities for Early Detection and Treatment.
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Transcript of Ovarian Cancer: How Basic Research Can Lead to New Opportunities for Early Detection and Treatment.
Complexity of Gene Expression
40,000-50,000 genes (over 100,000 gene products, andProbably over 1 million different proteins)
Hundreds of TissuesThousands of disease states
Environmental factors
Gene Expression Analysis Techniques
cDNA RDA Subtractive hybridizationDifferential display
MicroarraysSAGEEST
}differentially expressed cDNA fragments
} Global expression profiles
Northern BlottingRT-PCR } “gene-by-gene”
techniques
EST Sequencing
AAAAAAAAAAAAAAAAAAAA
AAAAAAAAAA
AAAAAAAAAATTTTTTTTTTT
Reverse Transcription
Sequence large number of clones
Prepare RNA
Tissue of interest
Serial Analysis of Gene Expression (SAGE) Principle
A short sequence tag (10-14bp) contains sufficient information to uniquely identify
a transcript provided that the tag is obtained from a unique position within
each transcript
SAGE Methodology
1) Sequence tags obtained from a cDNA library can be linked together to form concatemers that can be cloned and
sequenced
2) A count of the number of times a particular tag is observed provides the expression level of the corresponding
transcript
Serial Analysis of Gene Expression (SAGE)Prepare RNA AAAAAAAAAA
AAAAAAAAAA
AAAAAAAAAA
Create Tags
Tissue of interest
Ligate Tags
Sequence concatemers and analyze tag frequency
Cancer and Aging
Life expectancyRoman empire: 25 yearsMiddle ages: 33 years1850: 45 yearsU.S. in 2000: 75 years
Ovarian Cancer
• Believed to originate from a single layer of epithelial cells covering the ovaries
• 25,000 new cases in the U.S. in 2004• 15,000 will die of the disease• Most cases diagnosed as advanced disease• No reliable sensitive markers for early
detection
Prognosis
• Early disease: >90% survival
• Advanced disease: <20% survival
• Only 20% of women diagnosed early
• Early detection would have a significant impact on mortality from ovarian cancer
Therapy
• Standard chemotherapy: cisplatin and taxol
• Half the cases intrinsically resistant
• Many tumors develop resistance to cisplatin
• Mechanisms of drug resistance are unknown
Use of SAGE to Identify Genes Differentially Expressed in
Ovarian Cancer
• May help identify reliable markers
• May provide targets for therapy
• Better understanding of the disease
Summary of SAGE Libraries
Library Sequence Tags Unique tags Genes > 2 tags HOSE 2,290 47,881 16,034 12,778 4,532 IOSE 1,912 47,549 18,004 14,771 5,681 ML10 1,935 55,700 18,727 14,939 6,637 OVT6 2,104 41,620 18,476 15,646 4,799 OVT7 2,089 53,898 19,523 15,858 5,669 OVT8 2,076 32,494 16,363 14,153 3,815 OV1063 2,146 37,862 15,231 12,656 4,746 A2780 1,332 21,587 10,717 9,249 2,761 ES2 1,775 35,352 14,739 12,335 3,952 POOL 2,201 10,554 5,956 5,238 1,627 TOTAL 19,860 384,497 82,533 56,387 28,219
Hough et al. (2000) Cancer Res.
Top 12 Genes Expressed in ES-2
1 TGCAGTCACT 1.25% Collagenase2 TGTGTTGAGA 0.95 % EF-1 3 CCCATCGTCC 0.63 % Cytochrome C oxidase II 4 ATGGCTGGTA 0.59 % Ribosomal S25 GTGAAACCCC 0.52 % GM-CSF receptor CD826 AAGACAGTGG 0.49 % Ribosomal L37a7 AGCACCTCCA 0.48 % EF-28 GCCGGGTGGG 0.43 % Collagenase Stimul. Fact.9 GGATTTGGCC 0.43% Qip110 CCTGTAATCC 0.40 % Gz-selective GTPase-act prt11 TCCAAATCGA 0.39 % Vimentin12 CCCGTCCGGA 0.38 % Ribosomal L13 (EST)
Tag Exp. Level GeneRank
Normal ovary
ovarian cancer
Gene expression differences
Identifying Gene Differentially Expressed in Ovarian Cancer
Genes Consistently Up-regulated
up-regulated gene Fold Function
HLA-DR chain 289 Major histocompatibility complex, class II Cysteine-rich protein 1 123 LIM/double zinc finger Claudin-4 109 Tight junction barrier function ESTs 101 Unknown Surface marker 1 93 Tumor Ag/ Ca
2+ signal transducer
Claudin-3 83 Tight junction barrier function Ceruloplasmin 79 Secreted metalloprotein/ antioxidant HE4 72 Secreted protease inhibitor GPX3 69 Secreted selenoprotein/ peroxidase SLPI 60 Secreted serine protease inhibitor ESTs 56 Unknown IFN-Induced protein 1 49 Receptor for interferon signaling Ep-CAM 48 Tumor Ag/ Ca2+- independent CAM/ proliferation Mucin 1 43 Tumor Ag/ Type- I membrane glycoprotein
Conclusions
• SAGE can be used to identify the thousands of genes expressed in a given tissue
• This information can be used to improve our understanding of biological phenomena such as development , disease, etc
• We have identified several genes differentially expressed in ovarian cancer that may be useful as early markers or as therapeutic targets