Published Online:December 10, 2013
Treating lymphoma today starts with an understanding of what is being treated, and the revolution in genetic profiling lets clinicians do that with more precision than ever. But all that data can raise as many questions as it answers, while creating new ones in the ethical realm, according to the physicians who presented “Genomics in Hematology 101 for the Practicing Physician,” an education session at the 55th
American Society of Hematology Annual Meeting and Exposition in New Orleans.
The term “lymphoma” applies to at least 48 different diseases, and within each there can be considerable differences in how the cancer progresses and how patients respond to treatment.1
There was a time when a patient’s risk status at diagnosis was determined based on age, medical history, health status, and bloodwork or other tests. But genomics is rewriting that rulebook, according to presenters Sandeep S. Dave, MD, of Duke University; Richard F. Schlenk, MD, of University Hospital Ulm in Germany; and Stefan K. Bohlander, MD, of the University of Auckland, New Zealand.
What genomics is revealing, the presenters agreed, are the remarkable differences not only between different lymphoma states but within
each; trying to assess a patient’s risk level and treatment prospects without understanding his genetic profile would be akin to flying an airliner without instruments – one might survive but the ride would be bumpy.
Dr Dave used examples from 3 diseases – diffuse large B-cell lymphoma (DLBCL), Burkitt lymphoma (BL), and chronic lymphocytic leukemia (CLL) – to highlight how the different genetic makeup of patients within each disease affected treatment. While DLBCL is a common disease, with 25,000 patients diagnosed and 10,000 deaths a year,1
genomics has shown that DLBCL actually has 2 distinct subtypes with vastly different survival rates. Dr Dave said high-throughput sequencing has recently revealed several hundred mutations, with each affected only a small number of patients.
Burkitt’s lymphoma (BL) affects far fewer patients (only about 2000), but it is aggressive, complex, and hard to diagnose, making it an important disease for researchers to understand genetically. In CLL, meanwhile, several gene mutations, including TP53, NOTCH1
, and SF3B1,
have been linked to poor prognosis. As these differences are better understood, Dr Dave wrote in a companion paper to the session, it is becoming clear that many targeted agents will benefit only a relative handful of cases, making it essential to properly link drugs and patients.1
Understanding a patient’s genetic profile doesn’t end at diagnosis, according to Dr Schlenk. In his review of genomic applications in acute myeloid leukemia (AML), he called for additional testing as the disease progresses, so clinicians can see how the genetic profile has changed and respond accordingly. This is especially important when a patient relapses, Dr Schenk said. As more becomes known about individual mutations and clinical trials are designed around increasingly distinct groups of patients, he predicted that international collaborations would need to form to attract enough patients for each genetic expression being studied.2
Dr Bolander reviewed different levels and forms of genetic testing, and how much more scientists and clinicians can learn today. But with that knowledge comes responsibility, he said. Next-generation sequencing is producing huge amounts of data, but finding the “pearls,”3
comes only when clinicians now where to look. In the meantime, all that data must be stored and protected. Ethical guidelines are needed for gaining informed consent and for handling unexpected news that comes back with results.
“Current recommendations call for reporting only those findings with a high likelihood of causing disease – and for which intervention is possible,” he said. These recommendations, however, “were done with human genetics in mind, not tumor samples.”
Dave SS. Genomic stratification for the treatment of lymphomas. Hematology Am Soc Hematol Edu Program, 2013; 2013:331-334.
Schlenk RF, Dohner, H. Genomic applications in the clinic: use in treatment paradigm of acute myeloid leukemia. Hematology Am Soc Hematol Edu Program, 2013; 2013:324-330.
Bohlander SK. ABCs of genomics. Hematology Am Soc Hematol Edu Program, 2013; 2013:316-323.