To Measure is to Predict: Characterization of Response to Therapy in Plasma Cell Disorders

Abstract

For decades, treatment choices were few, and those available were tailored merely to a patient’s age and comorbidities. Currently, treatment choices are adapted to clinical parameters and cytogenetic features. The work presented in this thesis contributes to a future in which therapeutic strategies in MM will become ever more adapted to the individual patient. Different chapters of this thesis have focused on either unravelling disease biology to reveal novel biomarkers of therapy response or ex vivo treatment of patient-derived MM cells to measure drug sensitivity. Ultimately, some combination of both strategies might prove best in informing clinicians on choice of therapy in patients with relapsed MM. I envisage a future in which choices of first or second lines of therapy are determined by measuring the presence or activity of a certain biological predictive biomarker. As such, we will use therapy regimens based on a patient’s biological disease characteristics. Then, as a patient progresses through multiple lines of relapse and collects many new mutations, we can use ex vivo drug sensitivity measurements to choose the best kind of treatment from the basket of drugs that have not been used yet. Alternatively, we can use ex vivo models to test whether the myeloma clone is still, or again, sensitive for a drug that has been previously used. For every approach to prediction of response to therapy, we’ll need to measure to predict.