lecture 8. functional genomics: gene expression profiling using dna microarrays. part ii

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Lecture 8. Functional Genomics: Gene Expression Profiling using DNA microarrays. Part II Clark EA, Golub TR, Lander ES, Hynes RO.(2000) Genomic analysis of metastasis reveals an essential role for RhoC. Nature. 406:532-535. **Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, Thorsen T, Quist H, Matese JC, Brown, PO, Botstein D, Eystein Lonning P, Borresen-Dale AL. 2001. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. PNAS 98:10869-10874.

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Lecture 8. Functional Genomics: Gene Expression Profiling using DNA microarrays. Part II. Clark EA, Golub TR, Lander ES, Hynes RO.(2000) Genomic analysis of metastasis reveals an essential role for RhoC. Nature . 406:532-535. - PowerPoint PPT Presentation

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Page 1: Lecture 8. Functional Genomics: Gene Expression Profiling using DNA microarrays. Part II

Lecture 8. Functional Genomics: Gene Expression Profiling using DNA microarrays. Part II

Clark EA, Golub TR, Lander ES, Hynes RO.(2000)Genomic analysis of metastasis reveals an essential role for RhoC. Nature. 406:532-535.

**Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, Thorsen T, Quist H, Matese JC, Brown, PO, Botstein D, Eystein Lonning P, Borresen-Dale AL. 2001. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. PNAS 98:10869-10874.

Page 2: Lecture 8. Functional Genomics: Gene Expression Profiling using DNA microarrays. Part II

Golub et al:

Discovery Hypothesis Experimentation

Two ways to Use Gene Expression Profiling

Page 3: Lecture 8. Functional Genomics: Gene Expression Profiling using DNA microarrays. Part II

Clark EA, Golub TR, Lander ES, Hynes RO.(2000)Genomic analysis of metastasis reveals an essential role for RhoC. Nature. 406:532-535

Page 4: Lecture 8. Functional Genomics: Gene Expression Profiling using DNA microarrays. Part II

Making the RNA probe:

1) directly label RNA with tag or isotope2) make cDNA with fluorescent tag3) make ds cDNA and produce cRNA (amplification of signal).

AAAAAAATTTT-T7 promoterRT

mRNA

Page 5: Lecture 8. Functional Genomics: Gene Expression Profiling using DNA microarrays. Part II

Gene Profiling with 7000 gene human chip or 6000 gene mouse chip Discovery: RhoC is upregulated in metastatic tumors

RNAse Protection assayconfirms the results

Page 6: Lecture 8. Functional Genomics: Gene Expression Profiling using DNA microarrays. Part II

Hypothesis: Overexpression of RhoC will increase tumor metastasis

Test: Use a retrovirus vector to introduce RhoC into low metastatic cell line or RhoC dominant negative form into highly metastatic cell line

Parents: low high

+RhoC +RhoC-DN

Page 7: Lecture 8. Functional Genomics: Gene Expression Profiling using DNA microarrays. Part II

In vitro sssays confirm the role of RhoC in cell migration and invasiveness

Page 8: Lecture 8. Functional Genomics: Gene Expression Profiling using DNA microarrays. Part II

Parents: low highRhoC alters cell morphology

+RhoC

+RhoC-DN

Page 9: Lecture 8. Functional Genomics: Gene Expression Profiling using DNA microarrays. Part II

Golub et al:

Discovery Hypothesis Experimentation

Perou et al:

Discovery: Can Gene expression profile be a diagnostic/ prognostic tool for human cancer?

Two ways to Use Gene Expression Profiling

Page 10: Lecture 8. Functional Genomics: Gene Expression Profiling using DNA microarrays. Part II

Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA, Fluge O, Pergamenschikov A, Williams C, Zhu SX, Lonning PE, Borresen-Dale AL, Brown PO, Botstein D. 2000. Molecular portraits of human breast tumours. Nature. 406:747-52.

RNA isolated from 40 breasttumors and four normal breast samples; compared to RNA pooled from 11 different human tumor cell lines; cDNA microarray containing ~8000 gene used. Analysis: Hierarcial clustering

Result: Tumors (top) areheterogeneous and many clusters are found; functional gene clusters among all tumors can be identified

Tumor Clusters

Gene Clusters

Page 11: Lecture 8. Functional Genomics: Gene Expression Profiling using DNA microarrays. Part II

Select genes whose expression differs the MOSTBETWEEN tumor samples:

456 set of “Intrinsic Genes”RepeatCluster analysis With these Genes:

Result:The 40 Tumorsare organizedinto 4 clusters

Tumor Clusters

Gene Clusters

Page 12: Lecture 8. Functional Genomics: Gene Expression Profiling using DNA microarrays. Part II

Sorlie T, et al. 2001.

PNAS 98:10869-10874.

Question: Do Gene Profiles Have Clinical Significance?

RNA from 78 breast tumors,3 benign breast lesions,4 normal breast samplestested with the 456 gene set identified in the previousstudy. Control was the sameas last time {RNA from11 different human tumor cell lines).

Result:

Tumors can be organizedinto 5 (or 6) clusters.

Page 13: Lecture 8. Functional Genomics: Gene Expression Profiling using DNA microarrays. Part II

Clinical Outcome Can be Correlated to Gene Expression Clusters

Overall Survival Relapse Free Survival

49 tumor samples (non-metastatic) correlated to patient survival