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INVITED ARTICLES
DIAGNOSTICS
The Future of Molecular Medicine: Biomarkers, BATTLEs, and
Big Data
Edward S. Kim, MD, FACP
When I fırst entered the fıeld of lung cancer, the seminal
study published in the New England Journal of Medicine
was a four-arm chemotherapy doublet study that
showed no difference in effectiveness. Conclusions: All the
drugs are the same, so use what you like for patients with
advanced non–small cell lung cancer (NSCLC). 1
Times have changed, and personalized medicine has become
a reality. The era of “molecular medicine” has truly
blossomed. Over the last decade, approximately 40 drug approvals
were based on specifıc tumor biomarkers. 2 Options
for patients have changed dramatically, from cytotoxic chemotherapy
to molecularly targeted therapy. This concept has
been standard for almost 2 decades for those treating patients
with breast cancer (targeting HER2 and/or hormone receptors),
but now patients with melanoma and lung cancer are
included in this discussion. It is astounding how far treatments
for each of these tumor types have progressed in the
past 10 years. Melanoma treatment consisted of chemotherapy
or interleukin-2 and now consists of RAF inhibitors and
targeted immunotherapy, both of which have improved patient
outcomes substantially: response rates and progression-free
survivals have more than doubled. In fact, the progression-free
survivals for molecularly targeted therapies exceed the overall
survival numbers reported for chemotherapies. Lung
cancer treatment has evolved from administration of chemotherapy
yielding poor outcomes to biomarker assessments
such as EGFR, ALK, and ROS1. Treatment with EGFR inhibitors
(gefıtinib, erlotinib, afatinib) 3-5 and ALK-based therapies
(crizotinib, ceritinib) 6,7 have dramatically improved
effıcacy and quality-of-life outcomes. The notion that a patient
with advanced lung cancer could be treated on oral
biologic therapy for over 2 years without undergoing intravenous
chemotherapy is astounding. For example, a patient
with an EGFR mutation present in their tumor is treated with
an EGFR tyrosine kinase inhibitor (TKI). Then the patient
develops a T790 mutation in the tumor and is treated with a
T790 TKI. 8
As our desire for continued discoveries in tumor genetics
increases, more and more data are generated and captured.
Larger organized trials that prospectively capture biomarker
and treatment data have emerged, and data analysis of these
trials has become more complex. Adaptive trial designs, such
as umbrella and basket trials, have become commonplace
across academic cancer institutes and are emerging at
community-based cancer institutes. As biopsies to obtain adequate
amounts of testing for molecular studies are now the
norm, repeat biopsies are now part of the armamentarium of
procedures to best assess the tumor in real time following
treatment. With electronic data capture processes (including
electronic health records [EHRs] and national databases)
also evolving, medicine is now faced with the concept of “Big
Data”: how to collect it, maintain it, integrate EHR big data
with genomic big data, and thus, utilize it.
BIOMARKERS
The principle of identifying biomarkers to help guide patient
treatment has been a longstanding research initiative. Early
biomarkers and panels were largely classifıed as prognostic or
predictive. They were not associated with a specifıc biologic
therapy but rather defıned the tumor characteristics, including
response to therapy. Examples include Ki-67, carcinoembryonic
antigen (CEA), and prostate-specifıc antigen (PSA).
Breast cancer markers, such as hormone receptor status and
HER2, were some of the earliest markers related directly to
therapy. In lung cancer, validated markers associated with
therapy began with elucidating that EGFR mutations were
more prevalent in patients with adenocarcinoma, Asian ethnicity,
and nonsmoking status and were correlated with high
activity of EGFR TKIs (gefıtinib, erlotinib, afatinib). However,
more information was desired by researchers and treating
physicians, and, more importantly, correlation with
specifıc treatments was sought. Tumor registries were created
to collect tissue and test utilizing evolving molecular
From the Levine Cancer Institute, Carolinas HealthCare System, Charlotte, NC.
Disclosures of potential conflicts of interest are found at the end of this article.
Corresponding author: Edward S. Kim, MD, FACP, Levine Cancer Institute, Carolinas HealthCare System, 1021 Morehead Medical Dr., Charlotte, NC 28204; email: edward.kim@carolinashealthcare.org.
© 2015 by American Society of Clinical Oncology.
22 2015 ASCO EDUCATIONAL BOOK | asco.org/edbook