;ere’s been a revolution in cancer genomics and
genomics research over the past decade, thanks to the
plummeting cost of sequencing and the development of
new technologies. As a result, we understand much more
about the molecular underpinnings of cancer biology, and
this is beginning to in;uence clinical decision making.
Further developing this base of knowledge is really the key
to better implementing precision medicine.
In recent years, there has been a shi; in the treatment of
cancer patients from less targeted, traditional therapies
toward the use of molecularly targeted therapies. ;is
approach to treatment is known as precision medicine.
It is a direct result of genomic analyses in the research
laboratory being used to inform molecularly targeted
drug development. As our understanding of the molecular
dependencies of tumors grows, so, too, will the number of
molecularly targeted drugs.
We are now witnessing great advances as genomic
analyses are increasingly being applied to the clinical
research setting. For example, we are using genomics to
understand the molecular features of a tumor that can
in;uence treatment decisions, tell us about the likelihood
of response or resistance to certain therapies, help with
diagnosis, and give clues about prognosis.
Although genomic analysis doesn’t help all patients,
there is an increasing number of patients for whom it has
impacted clinical decision making. For example, whole-exome sequencing of the tumor from one patient with
advanced lung cancer revealed three potentially clinically
relevant genetic alterations that hadn’t been detected by
standard testing. As a result of our analysis, the treating
physician enrolled the patient in a clinical trial that
stabilized his disease for many months, which was the
best response he had had to date. When that trial ended,
another clinical trial was identi;ed from which he might
bene;t, based on our prior genomic analysis, and as a
result, he continues to do well.
;e use of genomics clinically has become increasingly
important for understanding why there is diversity in
the response of patients to anticancer therapies. We have
always known that some patients respond to certain
therapies and others do not, but in most cases we don’t
know why these di;erences occur. Over the past few years,
we have seen that studying “exceptional responders”—
rare patients with exquisite sensitivity or unexpected long
durations of response to therapies—is a good way to shed
light on this issue.
We have found that in several exceptional responders,
we are able to identify the mutation, or combination
of mutations, that makes these patient’s tumors
extraordinarily responsive to the treatments. ;e next
step is to look for the same or similar mutations in other
patients and enroll them in clinical trials to see if they,
too, might respond well to the therapy. In fact, analysis
of exceptional responders has seeded a number of so-called “basket” trials, in which patients are enrolled based
primarily on the genetic alterations of their tumors as
opposed to an anatomical basis or speci;c clinical features.
Genomic analysis is also key to understanding how tumors
become resistant to molecularly targeted therapies. What
we’ve learned is allowing us to begin to predict which
patients will likely have a tumor that is resistant to a
certain therapy and to identify combinations of therapies
that will overcome resistance.
We are beginning to see genomic analysis move from
the research setting to standard of care, but there are still
challenges that must be overcome if this trend is to increase
dramatically in the next few years. ;e key challenge is
assembling enough data to support meaningful analysis.
Frankly, we need data from sequencing of hundreds of
thousands of tumors, submitted to large, centralized,
shared databases. Moreover, the data have to be interpreted
and annotated, and then communicated so that both
patients and physicians can understand how to use this
information in making the best treatment decisions.
;e ultimate goal is for genomic analysis to be part of the
routine battery of pathological and diagnostic tests run on
tumor tissue from all cancer patients in order to determine
the optimal care for each individual.
42 AACR Cancer Progress Report 2014
IMPACTING CLINICAL CARE THROUGH