When the first draft of the human genome project was published in 2001, it justifiably sparked much acclaim and anticipation. It marked a new era in science, one fraught with expectation, not least of which was that the revealed genetic code would, in time, lead to new therapies for treating myriad diseases, including cancer.
And, in fact, there has been much progress toward that end. A lot has been learned — and a lot more remains to be learned. As scientists turned their attention to parsing cancer genomes, they discovered them to be startlingly complex, involving thousands of cellular mutations. Even more confoundingly, these genomes vary: patients with the same type of cancer will have tumors containing strikingly different combinations of mutations.
This reality has proved a daunting obstacle to the development of new cancer drugs and treatments. It has spawned an ongoing debate about how best to understand and define the biological mechanisms driving different cancers:
n Do we simply need more data? Should researchers sequence larger cohorts of patients in the search for commonalities?
n Or will the answers be found in more efficiently extracting insights from the genomic data we already have?
No doubt there is value in the first idea, but I — and others — believe that at least some answers lie right in front of us, in the pieces of the genomic puzzle we have gathered but need to fit together correctly.
One way we are doing this is through a new effort, Cancer Cell Map Initiative (CCMI), launched earlier this year. You can read about it in detail in the journal Molecular Cell at bit.ly/cancercellmap
It is a collaboration between investigators at UC San Diego School of Medicine and the Moores Cancer Center, led by Trey Ideker, Ph.D., co-leader of the Cancer Genomes and Networks program and founder of the UC San Diego Center for Computational Biology & Informatics, and counterparts at UC San Francisco, led by Nevan Krogan, Ph.D., director of the California Institute for Quantitative Biosciences at UC San Francisco.
Progress in genome sequencing has made it possible to decipher hundreds of mutations found in a patient’s tumor. The challenge now is to identify which of these mutations (and other molecular and genetic alterations) is central to that patient’s condition, diagnosis and treatment. It’s a bit like separating out meaningful signals from surrounding noise.
CCMI is based upon the idea that those signals not only exist, but that they are elemental to any lasting answers. They represent the hallmark networks and pathways that all cancers use to survive and grow. Identify them, learn how they function and work together, and you have the foundation for transformative therapies and cures. This scientific field of study is called computational biology (also bioinformatics and “big data”).
UC San Diego recently added major strength to this critical analytic aspect of cancer research and care with the recruitment of Jill Mesirov, Ph.D., a world leader in cancer computational biology who comes to the university and Moores Cancer Center from the Broad Institute at MIT and Harvard.
Cancer is a disease of pathways. Signals between cells — or even between different parts of cells — goes awry, gets corrupted or not sent at all, resulting in a terrible cascade of biological events. Many of these signaling pathways — and the molecular and genetic players involved — are known. “We have the genomic information already,” Ideker said. “The bottleneck is how to interpret the cancer genomes.”
The approach of Ideker and colleagues at UC San Diego, UCSF and elsewhere is to take a step back and look at the big picture. How do these different cancer pathways connect to form a map of malignancy? They are making great strides toward answering that question using tools and concepts, from high throughput sequencing machines to stem cells and gene editing, all unimaginable not so long ago.
From the resulting descriptive networks, the next step will be to create predictive networks: the ability to know what will happen when different sets of mutations combine.
“We’re going to draw the complete wiring diagram of a cancer cell,” said Krogan at the announcement of the CCMI. If you know how something works from the inside out, you’re a long way toward being able to fix it — and maybe prevent it from becoming broken in the first place.
CCMI, which notably received a founding donation from Fred Luddy, a member of the Moores Cancer Center Board of Visitors, and his Family Foundation, is the best kind of collaborative team science. It draws upon the strengths of many institutions, including the vast resources and databases of the National Cancer Institute, the innovations of San Diego-based Human Longevity Inc. (co-founded by UC San Diego alum and human genome project pioneer J. Craig Venter) and many deeply talented people across the state and country, in academia and industry.
CCMI is but a step. The journey to curing cancer is long. Soon, though, we hope to have a new and very useful map.