Download Genomic analysis of metastasis reveals an essential role for RhoC

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.
Two ways to Use Gene Expression Profiling
Golub et al:
Discovery
Hypothesis
Experimentation
Clark EA, Golub TR, Lander ES, Hynes RO.(2000)
Genomic analysis of metastasis reveals an essential role for RhoC. Nature. 406:532-535
Making the RNA probe:
1) directly label RNA with tag or isotope
2) make cDNA with fluorescent tag
3) make ds cDNA and produce cRNA
(amplification of signal).
mRNA
AAAAAAA
TTTT-T7
RT
promoter
Gene Profiling with 7000 gene human chip or
6000 gene mouse chip
Discovery: RhoC is upregulated in
metastatic tumors
RNAse Protection assay
confirms the results
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:
+RhoC
low
high
+RhoC-DN
In vitro sssays confirm the role of RhoC in cell migration and invasiveness
RhoC alters cell morphology
Parents: low
high
+RhoC-DN
+RhoC
Two ways to Use Gene Expression Profiling
Golub et al:
Discovery
Hypothesis
Experimentation
Perou et al:
Discovery: Can Gene expression profile be a
diagnostic/ prognostic tool for human cancer?
Tumor Clusters
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, BorresenDale AL, Brown PO,
Botstein D. 2000.
Molecular portraits of
human breast tumours.
Nature. 406:747-52.
RNA isolated from 40 breast
tumors 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) are
heterogeneous and many
clusters are found; functional
gene clusters among all
tumors can be identified
Gene
Clusters
Tumor Clusters
Select genes whose
expression differs the MOST
BETWEEN tumor samples:
456 set of
“Intrinsic Genes”
Repeat
Cluster analysis
With these Genes:
Result:
The 40 Tumors
are organized
into 4 clusters
Gene
Clusters
Question: Do Gene Profiles Have Clinical Significance?
Sorlie T, et al. 2001.
PNAS 98:10869-10874.
RNA from 78 breast tumors,
3 benign breast lesions,
4 normal breast samples
tested with the 456 gene
set identified in the previous
study. Control was the same
as last time {RNA from
11 different human tumor
cell lines).
Result:
Tumors can be organized
into 5 (or 6) clusters.
Clinical Outcome Can be
Correlated to Gene Expression Clusters
49 tumor samples (non-metastatic) correlated to patient survival
Overall Survival
Relapse Free Survival