A Better Way to Treat Cancer

A Better Way to Treat Cancer

The secrets of this ancient disease lie in the molecular data hidden within tumors. Mastering that data may be the best way to pinpoint cures and ultimately treat cancer.


As an oncologist whose life’s work has been to develop tailored cancer treatments, I find it frustrating that most patients are still being treated without full insight into what is causing their disease to grow and spread. The five-year survival rate for all common cancers in which there is metastatic disease (spreading) is well under 50% with conventional treatments, and for some diseases, like pancreatic cancer, it is as low as 7%.

I led the clinical development of Gleevec, a targeted drug that stops a mutation that causes chronic myeloid leukemia (CML). This therapy converted a disease with a three- to five-year life expectancy into one where most patients have a normal life span. Now studies are underway to determine when patients can stop taking the drug and continue to do well. It’s an exciting model for cancer drug development, and the plummeting cost of whole genome sequencing has and will continue to create more success stories in precision medicine.

But getting to the point where genetically tailored treatment is a reality for all patients requires a considerable reevaluation of how we share knowledge.

Today, for the few patients who are lucky enough to have their tumor genomes analyzed by sequencing, it can still take months of painstaking analysis—and tens of thousands of dollars—to find the mutations behind that cancer’s growth and then determine an optimal treatment. Even when this is done, the genomic data alone is insufficient to determine how effective a recommended therapy will be.

A tech executive I met through my work at the Knight Cancer Institute at Oregon Health & Science University is a lucky, living prototype of what is possible with precision medicine. But his experience also reflects the challenges.

After 23 years of battling a rare and unidentifiable form of kidney cancer, Eric Dishman, the head of Intel’s INTC 0.58% health care group, was running out of options. He was fortunate enough to have his DNA sequenced, but afterward it took another six months of shipping hard drives of the resulting data across the country for a team of oncologists, computer scientists, and data experts to devise a treatment plan based on his molecular makeup. Following that treatment plan, within months he was miraculously cancer-free and on the path to a kidney transplant that saved his life. The experience motivated Eric to reach out to me to find better ways to deliver precision medicine.

Intel and the Knight Cancer Institute are now united in challenging the global medical and technology communities to achieve cancer precision medicine for patients—in one day’s time—by 2020.

Success would mean transforming how care is delivered so that treatment teams could analyze patients’ cancer cells through genome sequencing and molecular imaging, and then tailor a precision treatment plan within 24 hours.

Today, even at the most advanced cancer centers, this process is largely manual. It’s fraught with a lack of standards and analytics tools and limited by scattered data pools. Making progress will require monumental improvements in clinical workflows, computing efficiency, and how research insights are shared.

In large part, precision medicine is a data science. To maximize accuracy, doctors and researchers need to perform advanced computational analysis on massive data sets to discover which medication or combinations of medications will work best.

Celebrated success stories show the potential. A Washington University researcher’s leukemia repeatedly relapsed and was resistant to treatment until colleagues sequenced his tumor DNA and found a key mutation that responded to a drug that put his disease into remission. A boy in Wisconsin had a mysterious brain infection; sequencing pinpointed an antibiotic that saved his life. A child’s birth defect was completely unknown to science until his tech-savvy parents found similar cases around the world and mobilized genetic researchers to find a way to better control his seizure-like symptoms. Unfortunately, far too few people have access to or can afford these potentially life-saving analyses.

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