An ex vivo platform to guide drug combination treatment in relapsed/refractory lymphoma

Abstract

Although combination therapy is the standard of care for relapsed/refractory non-Hodgkin’s lymphoma (RR-NHL), combination treatment chosen for an individual patient is empirical, and response rates remain poor in individuals with chemotherapy-resistant disease. Here, we evaluate an experimental-analytic method, quadratic phenotypic optimization platform (QPOP), for prediction of patient-specific drug combination efficacy from a limited quantity of biopsied tumor samples. In this prospective study, we enrolled 71 patients with RR-NHL (39 B cell NHL and 32 NK/T cell NHL) with a median of two prior lines of treatment, at two academic hospitals in Singapore from November 2017 to August 2021. Fresh biopsies underwent ex vivo testing using a panel of 12 drugs with known efficacy against NHL to identify effective single and combination treatments. Individualized QPOP reports were generated for 67 of 75 patient samples, with a median turnaround time of 6 days from sample collection to report generation. Doublet drug combinations containing copanlisib or romidepsin were most effective against B cell NHL and NK/T cell NHL samples, respectively. Off-label QPOP-guided therapy offered at physician discretion in the absence of standard options ( n = 17) resulted in five complete responses. Among patients with more than two prior lines of therapy, the rates of progressive disease were lower with QPOP-guided treatments than with conventional chemotherapy. Overall, this study shows that the identification of patient-specific drug combinations through ex vivo analysis was achievable for RR-NHL in a clinically applicable time frame. These data provide the basis for a prospective clinical trial evaluating ex vivo–guided combination therapy in RR-NHL.

Resistance to vincristine in DLBCL by disruption of p53‐induced cell cycle arrest and apoptosis mediated by KIF18B and USP28

“…2 To address this issue, clinical trials have investigated ex vivo platforms for pharmacological testing as an approach to identifying personalized treatment options. 45,46 We show that genome-wide CRISPR screening using a drug as selective pressure can be used to identify drug targets that result in substantial synergistic effects. CRISPR screening excels as a high-throughput method that simultaneous testing of thousands of drug targets using only a fraction of the cells required for testing single drugs one or two at a time.…”

“…The heterogeneity of DLBCL makes it challenging to predict the best treatment strategy, especially for high‐risk patients 2 . To address this issue, clinical trials have investigated ex vivo platforms for pharmacological testing as an approach to identifying personalized treatment options 45,46 . We show that genome‐wide CRISPR screening using a drug as selective pressure can be used to identify drug targets that result in substantial synergistic effects.…”

Resistance to vincristine in cancerous B-cells by disruption of p53-dependent mitotic surveillance

“…2 To address this issue, clinical trials have investigated ex vivo platforms for pharmacological testing as an approach to identifying personalized treatment options. 45,46 We show that genome-wide CRISPR screening using a drug as selective pressure can be used to identify drug targets that result in substantial synergistic effects. CRISPR screening excels as a high-throughput method that enables simultaneous testing of thousands of drug targets using only a fraction of the cells required for testing single drugs one or two at a time.…”

The Drug Efficacy Testing in Ex Vivo 3D Cultures (DETECt) platform enables rapid identification of effective drugs and drug combinations for ovarian cancer patients

“…Successful implementation of fPM-based treatment allocation has been demonstrated in previous studies with the majority addressing hematological malignancies [3][4][5]. However, to date there are few reports describing the use of fPM to tailor combination treatments for individual patients [6] and the application of these techniques to solid tumors has advanced more slowly, perhaps due to the challenges reviewed by Letai and colleagues [7]. Instead, recent approaches to drug testing in solid tumors have included patient-derived xenograft (PDX), patient-derived cell (PDC), and patient-derived organoid (PDO) models [8,9].…”