MRD: The Next Frontier in Oncology
Andre Goy, MD
Oncology & Biotech News
Chairman and Director
Lymphoma Division Chief John Theurer Cancer Center at HackensackUMC
Chief Science Officer and Director of Research and Innovation Regional Cancer Care Associates
Professor of Medicine,
The Emergence of MRD and Evolution of TechnologyAchieving a complete response (CR) in oncology translates into a better outcome. The measurement of response to therapy has improved greatly through imaging technology, initially with CT and later with functional imaging. Although the specific criteria differ between solid and liquid tumors, response has been the reference point for patient management, clinical trials, and drug development, with adjustment over the years. In lymphoma, for example, response criteria have been updated no fewer than three times since the mid 1990s,1 with refined parameters such as allowing a residual mass to be called a CR as long as the PET scan is negative. However, in liquid tumors, other sites of disease are important, particularly blood and bone marrow. Flow cytometry allowed—for the first time—the quantification of tumor cells beyond morphology evaluation under the microscope. The more advanced multicolor flow cytometry can reach sensitivity close to molecular biology–based approaches and can be particularly useful in leukemia, though this requires great technical expertise and is still mainly used in the context of clinical trials.2
A number of molecular biology techniques have been tested over the years for diagnostic, prognostic, and MRD purposes, including cytogenetics, fluorescence in-situ hybridization (FISH), comparative genome hybridization (CGH), and Southern blotting, though these are more cumbersome and usually lack the sensitivity required for MRD monitoring. The markers used for DNA-based testing are often chromosomal translocations, such as t(8;21) and t(15;17) in acute myeloid leukemia (AML/acute promyelocytic leukemia [APL]) or t(14;18) and t(11;14) in lymphoma, as examples.
The most commonly used technique for MRD is the allele- specific oligonucleotide PCR (ASO-PCR) based on the fact that both B- and T-cell leukemias or lymphomas exhibit a distinct immunoglobulin (BCR) and TCR gene rearrangement that is specific to a given clone. However, this requires the development of reagents (patient-specific probes) and assay conditions for each individual patient, which is laborious, expensive and time-consuming. On the other hand, mRNA-based tests are used when a DNA test is impractical and though handling of RNA is more difficult (less stable), these translocations present the advantage of not being specific to an individual patient and remain stable throughout the course of the disease. Examples of RT-PCR used include t(9;22) BCR-ABL in chronic myeloid leukemia (CML), t(15;17) PML-RARA in APL, and t(12;21) ETV6-RUNX1 (TEL-AML1) in AML.
Using real-time quantitative PCR (RQ-PCR), investigators in Europe were able to define international standards and obtain reproducible large-scale data sets as part of a multi-center global trials setting that has basically set the gold standard for MRD studies, with sensitivity overall in the range of 10-4 to 10-5.3 Such efforts, which should be commended, confirmed that obtaining a CR, particularly an early molecular CR in mantle cell lymphoma (MCL), had a profound impact on outcome, including overall survival. The more recent development of next-generation sequencing has the potential to transform MRD assessment. Without going into too much detail, this approach allows for quantification of allelic burden by counting the number of wild-type sequences versus mutated sequences (with no need for a sequence-specific probe).4
Clinical Significance of MRDDetermining treatment efficiency: MRD as a prognostic factor of relapse
A number of models (prognostic index, biomarkers) have been developed over time to predict the outcome of a given patient based on baseline clinical presentation. However, these models can be affected by the evolution of therapies (eg, rituximab’s effect on IPI in lymphoma), or are routinely trumped by newer molecular signatures. The best prediction of outcome in any patient with cancer is the actual response to therapy.