The effect of anti-cancer drugs difficult to predict

Biotechnology
Be wary of using gene analyses of cell lines to predict the effect of anti-cancer drugs. That is the conclusion reached in an article recently published in Nature. The problem is that this is already common practice in many places.

It would constitute a huge leap forward in cancer research if we were able to predict which new or existing anti-cancer drugs would have the greatest effect on all the different forms of cancer known today. This was actually the goal of two extensive cell line studies published in Nature in 2012. Data from these studies are already being used in preclinical trials, but the problem is that the findings from the two studies contradict each other—which makes them unusable in practice.

This is demonstrated by a new study that has recently been published in Nature, and, according to Nicolai Birkbak—a researcher at DTU and a member of the international team responsible for the study—the conclusion is unlikely to find favour among either pharmaceutical companies or research institutions.

“We have compared the two biggest-ever cell line studies, the Cancer Genome Project and the Cancer Cell line Encyclopedia. Both studies test the effect of a wide range of chemotherapeutic substances against a very large number of cell lines to establish whether this enormous dataset makes it possible to predict the effect of a specific medicine, depending on which genes in the cancer cells are active,” explains Nicolai Birkbak, postdoc at the Centre for Biological Sequence Analysis at DTU Systems Biology.

What is really interesting is that the two studies overlap. Around 500 cell lines and 17 substances feature in both studies, which gave Nicolai Birkbak and his fellow researchers from Boston and Montreal the idea of examining the results to determine whether they were consistent—and thus establish whether the methods were robust enough to be suitable for use in making predictions.

Findings contradict each other

"Following a thorough analysis of the two studies, we can show that the genomic data in both studies are identical, which means that the cell lines are actually the same and thus directly comparable. However, inconsistencies start to arise when measuring the sensitivity of the cell lines to specific substances. For example, one of the studies concludes that a cell line is resistant to a specific substance, while the other reaches the opposite conclusion. So what can you believe? They have to reach the same conclusion if these data can be used to predict an effect,” says Nicolai Birkbak.

The researchers behind the new investigation cannot explain definitively why the two studies arrive at such different conclusions.

"The non-alignment of the results may be due to differences in the approach to measuring sensitivity. This means that we have to go back to the drawing board to find new and standardized methods for measuring cell line sensitivity if we want to conduct wide-ranging sensitivity studies that produce viable results. And this conclusion is certain to be rather unpopular when so many people are currently working with these data. I, myself, have worked with them in connection with a study of breast cancer,” relates Nicolai Birkbak.

Cell cycle may impact sensitivity

Another problem is actually using cancer cell lines as model organisms.

Cell lines are living organisms, and we have long been aware that cancer cell lines in particular are not always stable. Personally, I believe that the cell cycle may play a key role in this context. We know that the sensitivity of a cell to specific substances depends on where it is in its cycle. So it might be necessary to take this into account in order to be able to predict an effect, and this is quite complicated as it involves ‘resetting’ all the cells in your cell lines. Cancer cells can certainly be used to obtain new and important knowledge about cancer. You just have to be very aware of their limitations,” concludes Nicolai Birkbak.

Facts about cell lines:

A cell line is a collection of identical cells that can be infinitely cultivated in vitro (in a test tube or Petri dish, for example). Cancer cell lines originally stem from a tumour in a human subject, and the cells can be kept alive artificially for years and shared between laboratories all over the world.