20 Clinical OMICs May/June 2017 www.clinicalomics.com
Helen Albert,
Contributing Editor
The Power of
One
Narrowing focus to the single-cell genomics
level targets cancer complexity on its own terms.
T
he potential of genomic sequencing technology to help in the fight against
cancer was recognized at an early stage, with the first report of cancer
genome sequencing in breast and colorectal tumors appearing in 2006, just
five years after completion of the Human Genome Project.
Since then, efforts such as the Cancer Genome Project in the U.K. and the Cancer
Genome Atlas in the U.S., have collected genetic information about many differ-
ent cancer types, helping to significantly increase knowledge of cancer genomics.
The increased efficiency and rapid cost reduction of sequencing technology and
analysis techniques over the same period has also contributed to the fast pace of
development in the field.
Cancer sequencing efforts to date have consistently demonstrated how genet-
ically diverse tumors can be. This heterogeneity can make it difficult to discover
which mutations trigger tumor development, complicating efforts to develop
therapies that target specific mutations and to better understand drug resistance.
Today, researchers are quickly adopting a relatively new method of cancer
researcher, that has the promise to unlock the riddle of tumor heterogeneity—sin-
gle-cell sequencing. Nicholas Navin, Ph.D., pioneered single-cell cancer genome
sequencing while working on breast cancer cells in 2010. This work, published in
Nature in 2011, transformed the field of cancer genomics. This approach allowed
researchers to zoom in on individual cells within a given tumor and sequence
their DNA.
Paul Robson, Ph.D., director of Single Cell Genomics at the Jackson Laboratory
for Genomic Medicine in Farmington, CT explained the value of these techniques
to Clinical Omics: "Single cell genomics…allows you to study the heterogeneity of
cancer mutations and how they might evolve over time or in response to therapy.
"Cells with different sets of mutations may respond differently to cancer drugs
or may be more likely to give rise to metastatic cells. Understanding mutational
features at single-cell resolution and how they behave in response to therapy