The ability to sequence the genome of thousands of cancerous tumors and compile the data in huge warehouses is giving scientists unprecedented tools for understanding the genetic roots of cancer.
That capability allows them to identify who may be predisposed to develop the disease. It also gives drug companies and clinicians new targets for fighting, managing, and in a handful of cases, curing some of the estimated 200 forms of cancer.
Indeed, the explosion of cancer genomic data prompted the White House to launch its National Cancer Moonshot, a billion-dollar effort led by Vice President Joe Biden to “eliminate cancer as we know it” and “make a decade worth of advances in five years.” But while scientists are enthusiastic about their increased capabilities to make progress in the fight against what one author has called “the emperor of all maladies”—cancer now rivals heart disease as America's No. 1 killer with 589,000 deaths a year—the breadth and depth of the data being generated are posing huge challenges for researchers, oncologists and patients.
The data are complicated to understand, and the process for data collection is unstructured, decentralized, and some argue, only gathered in silos. And much of what is collected remains unanalyzed because there is little consensus on the best ways to pursue data-driven research. Indeed, the current wave of optimism about new discoveries that could lead to cures might ultimately be pulled out to sea by an undercurrent of unanswered questions.
The environment “is exciting, but frustrating,” says Dr. Barrett Rollins, chief scientific officer at the Dana-Farber Cancer Institute in Boston. “While we all see what big data could potentially do, we're frustrated because we don't yet have all the tools or fully understand how to use it.”
It's a time of “profound turbulence,” adds Dr. Julie Vose, president of the American Society of Clinical Oncology, in her introduction to the group's recent report, The State of Cancer Care in America.
The report underscores the struggle to make sense of the “information overload” of genomic data. It states that clinicians don't have answers to the many questions being raised about the risks and benefits of genetic screenings and the role they play in selecting treatments.
In 2015, the Food and Drug Administration approved molecular diagnostic tests for lung and colorectal cancers, a tremendous benefit for some patients with those diagnoses. But while such tests can change the course of treatment for some variants of those diseases, for the majority of cancers, the genomic tests generate inconclusive results or reveal abnormalities for which clinical guidelines and treatments do not exist.
Multidisciplinary teams of clinicians, surgeons, radiation oncologists, geneticists and others have formed molecular tumor boards at some research institutions. They study these abnormalities and offer guidance to clinicians about which tumor types are worth testing and at which stage of the disease. But the opportunities to use genomic testing to inform clinical practice remain few and far between. From the first sequencing of the first human genome in 2003—considered by Modern Healthcare readers as the most significant medical breakthrough of the past 40 years—cancer patients, their oncologists and the research community have believed the new technology would pave the way for understanding the genomic underpinnings of dozens of cancers.
“The opportunity space suddenly exploded,” says Adam Resnick, founding co-director of the Children's Hospital of Pennsylvania's new Center for Data-Driven Discovery in Biomedicine. Sequencing the genome “produced a transformation in the scientific arena,” he says.
