Gareth Bond: Human Cancer Genetics
There is great heterogeneity between individuals in their risk of developing cancer, disease progression and responses to therapy. Specific single nucleotide polymorphisms (SNPs) are associated with human cancers. They have the potential to help us identify individuals more at risk of developing cancer, and better target preventative or therapeutic strategies.
Q: Why doesn't everyone have the same risk of developing cancer?
Gareth Bond: We don't really know the answer to that question. We know there are certain families that have a very strong familial clustering of cancer, meaning that a lot of family members have cancer. There has been a lot of work done on those families and we have identified mutations that seem to predispose those family members to developing cancer, like the case of Angela Jolie that has recently been in the press because she has taken measures to prevent or decrease her risk of developing certain cancers. The focus of my group is to start to look at the genetic basis of cancer in the broader populations, in those families where we don't see that strong clustering of cancer.
Q: What is an SNP?
GB: An SNP, pronounced SNiP, or single-nucleotide polymorphism, is a type of mutation that is found at a very high frequency (most or all people) within certain populations. It is the type of frequent genetic variant that we want to characterise to see how they are impacting cancer, not just the risk but progression and response to therapies, so that we can start using that genetic information that is in the broader population to inform decisions and ultimately improve survival.
Q: How has the field evolved in the last five or ten years?
GB: In the past ten years anyone who touches genetics will know about the revolution that we call genomics. Genomics is underpinned by these wonderful chemistries that have evolved where we can read genomic DNA quickly and efficiently and at much lower cost. That has revolutionised everything and allowed us to go deep into the genomes of hundreds and thousands, up to millions of individuals worldwide and find out which ones are actually causing, for instance, cancer and seeing how that can affect patient outcome.
Q. Can you give an example of a SNP altering cancer risk?
GB: The biggest one, which is not as high frequency as I would like in terms of my laboratory, is the BRCA1 mutation. A definition of high frequency is at least 1% of the population; indeed there are certain populations in the Western World that have such a high frequency of this breast cancer associated mutations, or BRCA, like Angelina Jolie and her family has. That is such a wonderful example of people who don't have cancer yet, coming into the clinic, identifying the mutation, and we can offer interventions that will ultimately prolong life and ameliorate suffering to a certain extent. For us, that is a poster child of a variant that is found in quite a lot of people and that we can use to improve health.
Q: Why is your research important and why should we put money into it?
GB: Cancer is definitely an illness that we don't have a handle on yet. 50% of all cancers are curable but that still means that we have a quite long way to go. Any type of biomarker, or any type of marker or information that we can glean from a patient to help is of value. What we are trying to do is use genetic markers to develop a "star trek type" of technology where all we have to do is take a cheek swab or blood sample and we get useful information. It's early days for that now but I hope it will be the case in my lifetime.
Q: How does your research fit into translational medicine within the Department?
GB: My goal is that it becomes translational quite quickly. As a biologist that is a very naive thing to say and I need a lot of help from wonderful clinicians and scientists here at the University to help me translate the information that we are gleaning from our computers and our lab benches to the clinic. The most utility that we can glean in is biomarkers and informing. We know that people are different in their risk for cancers, but who actually has a higher risk and why is that? Can we intervene somehow in preventative or therapeutic strategies and use that genetic information to help inform that decision? That's how we hope to translate from bench to the clinic.