SLIDES & TRANSCRIPTS
Saturday, December 6, 2003

Highlights of GU SPORES

Phillip Febbo, M.D.

We look at prostate cancer in a relatively simplistic way. We are trying to look at the different categories of prostate cancer as it comes through the clinic. I'm calling it the good, the bad and the ugly here. The good are those patients that are diagnosed with disease, but they will never be affected clinically by the disease. The bad are the patients that are diagnosed and have localized disease and are cured by the people in this room, who perform the operations, as well as some of the radiation oncologists. The ugly are those men that you see in the clinic that you have a pretty good feeling, based on PSA, Gleason and other measures, that it is too late to cure these patients by surgical interventions or local interventions alone.

TOP

At the SPORE, we are looking at this through different mechanisms. We are looking at the host through our genetic epidemiologic project that is performed through the Harvard School of Public Health. We are also looking at it as the normal prostate epithelium transitions into prostate cancer and into metastatic prostate cancer, and working to understand the differences that contribute to that.

We take two approaches. We are using expression analysis in one project, a SNP analysis in another project, and targeted interventions to look at how you can look at metastatic prostate cancer and local prostate cancer that has already developed to try to understand the important changes.

We are also taking the approach of creating cancer. Some of the in vitro work that I will talk about is very early for a SPORE. We do have a development project that helps augment our efforts that are further along and more translational.

TOP

So the specific example I want to talk about has to do with idea. June Chen and colleagues at the Harvard School of Public Health -- June is now at UCSF, has an example of inter-SPORE migration -- identified this in Science in 1998 as circulating levels of IGF being associated with an increased risk of prostate cancer.

They are continuing this work as part of the SPORE project one, and looking further as to what are the downstream implications of having increased levels of IGF 1 circulation. Interestingly enough, this pathway probably activates through the PI3 kinase P10 pathway in prostate cancer and leading through AKT. All of these are now being found to be critical proteins in prostate cancer.

One of the problems with this approach now and fully understanding this pathway is a lot of the reagents yet to exist as far as having really good antibodies to look at P10, to look at phosphorylated AKT and to really understand this pathway. Also, this is one part of the picture.

TOP

One of our projects led by Bill Sellers takes a more -- starts with a more general approach and does SNP analysis. SNP analysis basically looks for regions of loss that are associated with tumor progression. You have seen some presentations about potential tumor suppressor proteins in this conference already, but we are looking for areas where there was an initial mutation and then in the tumor there is loss with progression.

TOP

What this gives you is a great deal of data on these micro arrays. As part of the interdisciplinary approach, you have to work very closely with statisticians and computational analysis, and we now have those people as part of our program.

They published recently. When they looked at the regions in these initial 52 tumors that were most significantly lost, it became very clear that the molecule that is involved in the IGF finding, P10, is also a region targeted for loss in primary tumors. This isn't a discovery, this wasn't known before, but this just shows that as you look at new technologies and new ways to look at tumors, it is always good to see some common findings come up, some known findings to validate.

TOP

We are also taking a look at expression. We have looked at tumor versus normal. They have done this at Michigan , they have done it at Johns Hopkins, we have all looked at it. There are a lot of consistent changes. You have heard about some of the changes, most specifically hepsin, that are found in this method.

TOP

We also looked at gene expression correlated with Gleason . One of the genes most highly correlated with increasing Gleason falls into the IGF pathway. So you see a common theme throughout multiple projects that has to do with IGF BP and the IGF pathway.

TOP

Interestingly enough, we presented a first expression based multi-gene predictor of outcome last year. There are more multi-gene predictors of outcome that have subsequently been published, but again, although not used frequently, IGF BP was in the mix there.

TOP

This data has now been used to look in a separate manuscript to look at gene changes associated with metastases and gene changes associated with the pathway of fatty acid synthase. I think it is really important to note that all this work would not have been possible without the concerted effort of urologists, medical oncologists, molecular biologists and statisticians and computational biologists, and all of this is going on under the SPORE umbrella.

TOP

What is also great is, between the different programs, we can now combine our efforts, where I can work with Bill Sellers to say, you have identified tumors that have lost 10Q, we know some tumors that have retained 10Q, what are the genes that are most specifically changed.

This is a heat map that shows that. A high expression is in red, low expression is in blue. These four tumors are the ones with definition loss and these tumors have retained. You can look at some of the genes that are up in the lost, including her two new.

TOP

That is where it really helps to work with basic laboratories in the development type project such as that of Bill Hahn, where we are trying to re-engineer the prostate cancer using defined elements.

Bill published a couple of years ago that you could use activated RAS, large T and small T tolomerase, to take kidney epithelial cells and transform them. We have now shown that you can take prostate epithelial cells and transform them. These are AR negative and tend to have a basal phenotype, but we have also put androgen receptor into them and find that they are still transformed.

TOP

Interestingly enough, any time you do something like this, you have to worry about the relevance in cancer. One of the ways we have done that is, we have said, when you take the immortalized versus the transformed cells -- again, these are RAS transformed, and that is the only difference -- despite similar growth kinetics on plastic, they have profound gene expression differences. High is red, low is blue, and these are the cells that express RAS, these are the transformed cells, these are the non-transformed but immortalized cells, and there are profound differences.

That is great, that is growing on plastic, they are transformed cells. How relevant is that to prostate cancer? We took these same cells and we clustered our 102 prostate tumor and normal samples that were part of our expression project. What you find is that the same genes that are changed with transformation can vary with much more accuracy than you would expect by random chance alone, separate prostate tumors from prostate normal, suggesting that the downstream expression implications of RAS transformation are reflected in prostate cancer.

However, I just talked about the importance of IGF, the importance of PI3 kinase and P10. RAS we know is not mutated in most Caucasian men or African-American men with prostate cancer. This is somewhat still a somewhat arbitrary and artificial collection.

TOP

We have looked at different complementarity, where we have now put in NIC instead of RAS and we used PI3 kinase instead of small T, and you can transform cells. In fact, these cells perform in three-dimensional culture, very nice three-dimensional cultures, and have great organization.

TOP

Again, you have to ask, if you are playing around with genes in cells, what relevance does it have? So we performed another type of analysis, working with our genomics core, where we asked the same question.

This is a list of top 200 genes that are up in RAS compared to the normal epithelial cells, up in NIC compared to the normal epithelial cells. We asked, are these genes enriched in tumors, local tumors versus benign, or are they enriched in metastatic disease versus benign, and is there any difference between RAS transformed cells and NIC transformed cells.

TOP

What we found is, the RAS transformed cells are somewhat over expressed as a group in both metastatic and local tumors. But the NIC and PI3 kinase specifically transformed cells are much more enriched.

TOP

Finally, these cells now have been put into mice and formed very nice tumors with PI3 kinase.

TOP

Coming back out of the basic science lab, we have taken IGF finding from epidemiology into primary tumors, both at the SNP and at the expression levels, brought it back to the lab to understand it a little better, and make a model. We can now use that model in an automated process to screen chemical libraries for the ability to specifically block the transformation process by PI3 kinase, and thereby identify future potential targets for this pathway.

TOP

Again, this is one example. We have many pathways that we are working on. There is a lot of work that goes beyond here. It is very translational, and it is very multidisciplinary. I just thought I would present that as a single example of our group's efforts.

There are too many people to mention specifically, and my time is over, so I will end there.

TOP