 all KRAS mutant cancers equally. The combined inhibition worked better at shrinking tumors comprised of differentiated epithelial cells compared to those that displayed mesenchymal features. This distinction could provide a clinical biomarker for predicting which patients may respond to the combination – predictability that is key to personalized cancer therapy.
A Mixed and Evolving Population
Just as lung tumors, for example, have genetic heterogeneity, an individual tumor has cellular heterogeneity, with different cells playing different roles in growth, invasion, drug sensitivity, and relapse. David Langenau, PhD (MGH), is exploring this concept using zebrafish to visualize the dynamic process of tumor development and relapse. (See accompanying article Visualizing the Birth of Cancer in Zebrafish.) “In assessing genes associated with relapse in humans, we often compare the primary tumor to the relapsed tumor and assess how the whole bulk of the tumor is different at relapse,” he explains. “But each cancer cell could have different mutations at relapse, and we don’t know which mutations are drivers of relapse growth and which are passenger mutations that have no effect on tumor growth."
To gain a more linear view, Langenau transplanted a single leukemia cell into zebrafish and tracked its evolution into the full spectrum of leukemia cells over time. “Amazingly only a handful of genes – about 19 – seemed important to the evolution,” he says, and they were active in only a minority of tumor cells. Those cells may be tumor-propagating cells, with some properties of stem cells in their ability to differentiate into the other heterogeneous cell types of the tumor, and they may be responsible for tumorigenesis, metastasis, resistance, and/or relapse. Langenau is now testing these genes to see if they are potential targets for therapy in leukemia.
Dark Matter Does Matter
Until recently, most gene sequencing projects focused on protein-coding regions, to great payoff. For example, determining that the majority of metastatic melanomas had a mutation affecting BRAF led to a new targeted therapy (vemurafenib) for this aggressive disease. But genes actually account for only about 2% of the genome. With the increased power of whole genome sequencing technology, the importance of some of the non-coding ‘dark matter’ is coming to light. David Altshuler, MD, PhD (MGH, Broad), helped develop technologies to probe the whole genome for single DNA changes, called single nucleotide polymorphisms or SNPs, that influence hereditary human traits, ranging from height and weight to the risk of developing heart disease, diabetes, or cancer. Surprisingly, most of these risk variants were outside of genes, and many appeared to be in regulatory elements known as promoters and enhancers. Promoters essentially prepare genes for expression, while enhancers are dimmer dials for the level of expression.
How Enhancers Interact With Their Target Genes
Matthew Freedman studies enhancers, which are regulatory elements that often occur a long distance from the gene they regulate. Enhancers and genes are thought to interact when they come into contact because of how the DNA strands loop inside the nucleus. Chromosome Conformation Capture (3C) is a technique that determines which regions of the genome physically interact with each other, and then re-configures the DNA sequence into a format amenable to copying by polymerase chain reaction (PCR) for further study. Credit: Matthew Freedman.
As a postdoctoral researcher, Matthew Freedman, MD (DFCI), worked with Altshuler on whole genome sequencing, and now in his own lab he studies SNPs affecting enhancers. Freedman wants to connect cancer-risk enhancers to the genes they regulate. But whereas promoters can be found adjacent to the gene they regulate, enhancers can occur a long distance from the gene they influence, even on a different chromosome, which complicates the task.
However, enhancers interact with genes by coming into physical contact as DNA strands loop and twist in the nucleus, and a method called Ch