March 21, 2013
At first our favorite small eukaryote, S. cerevisiae, might not seem like a great model for cancer studies. After all, budding yeast can’t tell us anything about some of the pathways that go wrong in cancer, like growth factor signaling. And it clearly can’t help explain what happens in specific tissues of the human body. But in other ways, it actually turns out to be a great model.
For example, all the details of cell cycle control were originally worked out in yeast. And now a whole new batch of genes has been found that influence a phenomenon, chromosome instability (CIN), that is important in both yeast and cancer cells.
As the name implies, chromosomes are unstable in cells suffering from CIN. Big chunks of DNA are lost, or break off and fuse to different chromosomes, turning the genome into an aneuploid mess. And this mess has consequences.
CIN can cause new mutations or make old ones have a stronger effect. Eventually these mutations can affect genes that are important for keeping a cell’s growth in line. Once these are compromised, a tumor cell is born.
Since CIN is pretty common in yeast, we might be able to better understand it in cancer cells by studying it in yeast. The Hieter lab at the University of British Columbia has come up with a powerful screen to get yeast to confess why it CINs.
A previous study from the group set the stage by finding a large group of mutants that have CIN phenotypes, implying that those genes are involved in keeping chromosome structure stable. In a new paper in G3: Genes, Genomes, Genetics, van Pel et al. uncovered the network of interactions among the genes in this set, using synthetic genetic array (SGA) technology. And they confirmed that the human homologs of some of these genes interact in the same way as in yeast, making them potential targets for cancer therapies.
The idea behind SGA studies is that if two proteins are involved in the same process, then a strain carrying mutations in both of their genes will be much worse off than a strain carrying either single mutation. In the worst case, the double mutant will be dead. This is known as a synthetic lethal interaction.
Yeast is a great model for doing these sorts of studies on a very large scale. We can construct networks showing how lots of different genes interact, and most importantly, find the genes that are central to many interactions. These “hubs” are likely to be the key players in those processes.
The researchers looked specifically for interactions between genes that are involved with CIN in yeast and are also similar to human cancer-related genes. They came up with various interaction hubs that will be interesting research subjects for a long time to come. In this study, they focused on one of these: genes involved with the DNA replication fork.
One of these in particular, CTF4, is a hub for both physical and genetic interactions. Unfortunately, Ctf4p doesn’t look like a good target for chemotherapy. It’s thought to act as a scaffold, and lacks any known activity that could potentially be inhibited by a drug. However, the interaction network around CTF4 that van Pel et al. uncovered suggests another way to target this hub. If a gene that interacts with CTF4 itself has a synthetic lethal interaction with another gene, and we could re-create the synthetic lethal phenotype in a cancer cell, we might be able to knock out the whole process. And that is just what they found in human cells.
First the authors identified a couple of human genes that were predicted from the yeast screen to be close to human CTF4 in the interaction network and to have a synthetic lethal interaction with each other. They then lowered the expression of one using small interfering RNA (siRNA), and reduced the activity of the other with a known inhibitor. Neither treatment alone had much effect, but combining them significantly reduced cell viability.
Since cancer cells frequently carry mutations in CIN genes, it should be possible to create a synthetic lethal interaction, guided by the yeast interaction network, where one partner is mutated in cancer cells (equivalent to using siRNA in this study) and the other partner is inhibited with a drug. Since it relies on a cancer-specific mutation, this approach has the potential to selectively target cancer cells while not disturbing normal cells, the ultimate goal for chemotherapy.
by Maria Costanzo, Ph.D., Senior Biocurator, SGD
March 05, 2013
Cancer often gets going with chromosome instability. Basically a cell gets a mutation that causes its chromosomes to mutate at a higher rate. Now it and any cells that come from it build mutations faster and faster until they hit on the right combination to make the cell cancerous. An accelerating avalanche of mutations has led to cancer.
There are plenty of obvious candidates for the genes that start these avalanches: genes like those involved in segregating chromosomes and repairing DNA, for example. But there are undoubtedly sleeper genes that no one has really thought of. In a new study out in GENETICS, Minaker and coworkers have used the yeast S. cerevisiae to identify three of these genes — GPN1 (previously named NPA3), GPN2, and GPN3.
A mutation in any one of these genes leads to chromosomal problems. For example, mutations in GPN1 and GPN2 cause defects in sister chromatid cohesion and mutations in GPN3 confer a visible chromosome transmission defect. All of the mutants also show increased sensitivity to hydroxyurea and ultraviolet light, two potent mutagens. And if two of the genes are mutated at once, these defects become more severe. Clearly, mutating GPN1, GPN2, and/or GPN3 leads to an increased risk for even more mutations!
What makes this surprising is what these genes actually do in a cell. They are responsible for getting RNA polymerase II (RNAPII) and RNA polymerase III (RNAPIII) into the nucleus and assembled properly. This was known before for GPN1, but here the authors show that in gpn2 and gpn3 mutants, RNAPII and RNAPIII subunits also fail to get into the nucleus. Genetic and physical interactions between all three GPN proteins suggest that they work together in overlapping ways to get enough RNAPII and RNAPIII chugging away in the nucleus.
So it looks like having too little RNAPII and RNAPIII in the nucleus causes chromosome instability. This is consistent with previous work that shows that mutations in many of the RNAPII subunits have similar effects. Still, these genes would not be the first ones most scientists would look at when trying to find causes of chromosomal instability. Score another point for unbiased screens in yeast leading to a better understanding of human disease.
by D. Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics
June 01, 2012
One reason cancer is so tricky to treat has to do with its adaptability. It can quickly try out new genetic combinations until it hits upon one that can survive whatever treatment a doctor is currently throwing at it. The result is return of the cancer after remission.
One way cancer is able to change its genetics so rapidly has to do with chromosome instability. The number of chromosomes in a cancer cell is much less stable than in a normal cell. This allows the cancer cell to constantly explore a wide range of chromosomal combinations.
It is still an open question how this dynamic instability happens. The gene-centric theory suggests that mutations in key genes are the main driving force. The chromosome-centric model says that having the wrong number of chromosomes is the critical component.
Distinguishing between these two models using cancer cells has proven difficult because these cells always have mutated genes. There is simply no way to look at just chromosome numbers in this system. This is where yeast can help.
In a recent paper published in PLoS Genetics, Zhu and coworkers used yeast to explore whether altered chromosome number was sufficient to explain chromosome instability. They found that chromosome numbers alone can explain some but not all of chromosomal instability.
The authors created various chromosomal combinations in yeast by sporulating isogenic triploid yeast cells. These cells had different numbers of genetically identical chromosomes. They then explored the stability of each chromosome number combination using both FACS and qPCR.
What they found was that chromosome number certainly impacted chromosomal stability. Chromosome number became less and less stable as the chromosome number veered further and further from the haploid state. Of course, once the cells became diploid, stability returned.
The authors explain this with the idea that there is only so much cellular machinery to move chromosomes to the proper place during mitosis. As more and more chromosomes are added to the cell, the machinery becomes increasingly taxed, resulting in more and more errors.
But once the diploid state is reached, all the genes are present to make twice as much mitotic machinery. Now stable chromosome segregation can happen.
This was the broad pattern Zhu and coworkers observed but it certainly wasn’t the whole story. The authors found islands of stability in the chromosomal chaos.
For example, very often when there were equal numbers of chromosome VII (ChrVII) and chromosome X (ChrX), the chromosome number was more stable than predicted. They explored this further and found evidence that suggested that at least part of this was due to the MAD1 gene on ChrVII and the MAD2 gene on ChrX.
Stable chromosome numbers required that these genes be present in a 1:1 ratio. Once the ratio strayed from one, chromosomal instability increased. But these genes don’t explain everything. There were unstable combinations where the MAD1/MAD2 ratio was correct. As might be expected, there are other gene combinations that can lead to instability as well.
So incorrect chromosome number alone can explain the chromosomal instability seen in cancer cells. But genes clearly play a role too, as evidenced by the islands of stability and the MAD1 gene and MAD2 genes. As usual, reality is probably a combination of the two models.
So it looks like chromosome number does play an important role in chromosomal instability. Too many chromosomes may overtax the mitotic machinery so that chromosomes end up mis-segregated.
by D. Barry Starr, Ph.D., Director of Outreach Activities, Stanford Genetics