Contributions
Abstract: P649
Type: Poster
Abstract Category: Pathology and pathogenesis of MS - 25 Biomarkers
Background: Ofatumumab is the first fully human, highly potent and subcutaneously (s.c.) administered anti-CD20 monoclonal antibody in development for MS. A Phase 2b dose-finding study demonstrated high MRI efficacy and helped to identify an optimal dose for the ongoing Phase 3 trials. An effective depletion of B cells was observed in cynomolgus monkeys treated s.c. with ofatumumab. Here, we analysed single-cell mRNA expression and applied machine learning algorithm to determine the effect of ofatumumab treatment on mRNA expression patterns in B cells isolated from lymph nodes.
Objective: To identify novel anti-CD20 therapy markers in response to ofatumumab treatment in cynomolgus monkeys by using single-cell genomics technology.
Methods: Cynomolgus monkeys received human equivalent doses of ofatumumab (1mg/kg, s.c.) on Days 0, 7 and 14. Axillary lymph node biopsies were collected at various time points until Day 90. Single-cell mRNA analysis was performed on fluorescence-activated cell-sorted CD20+ B cells. The mRNA expression patterns were analysed with machine learning algorithms (t-distributed stochastic neighbor embedding [t-SNE]), which enables the similarity of cells to be expressed by the proximity of dots in a 2-D graph. A set of 96 detectable lymphocyte RNA markers was selected to generate clusters of related B cells.
Results: In cynomolgus monkeys, s.c. injection of low-dose ofatumumab induced a strong depletion of B cells from Days 2‒21, followed by a repletion starting 2 weeks after the last injection. Single-cell analysis of mRNA marker expression in 595 isolated CD20+ cells showed five t-SNE-defined cell clusters in untreated monkeys. Ofatumumab induced a new cell cluster and strongly enhanced a second cluster found at baseline. Upon repletion both clusters diminished, approaching cluster properties similar to baseline. No control markers such as CD4 or CD28 were detected in any of the six clusters. Cells in the new cluster expressed mRNA markers linked to the cell cycle/proliferation, such as CBX2, cyclin E1, cyclin A, AURKA, MK167 and FFM2, which were not expressed by the other clusters.
A more refined cluster analysis is under way.
Conclusions: Single-cell mRNA expression analysis in small-size samples is a new approach for identifying B-cell subsets, independent of known marker sets. Transcriptional expression analysis in MS and animal models may improve our molecular understanding of ofatumumab treatment effects on B-cell subsets and their role.
Disclosure: Funding source: This study was funded by Novartis Pharma AG, Basel, Switzerland.
All authors are employees of Novartis;
Paul Smith was an employee of Novartis at the time of study conduct.
Abstract: P649
Type: Poster
Abstract Category: Pathology and pathogenesis of MS - 25 Biomarkers
Background: Ofatumumab is the first fully human, highly potent and subcutaneously (s.c.) administered anti-CD20 monoclonal antibody in development for MS. A Phase 2b dose-finding study demonstrated high MRI efficacy and helped to identify an optimal dose for the ongoing Phase 3 trials. An effective depletion of B cells was observed in cynomolgus monkeys treated s.c. with ofatumumab. Here, we analysed single-cell mRNA expression and applied machine learning algorithm to determine the effect of ofatumumab treatment on mRNA expression patterns in B cells isolated from lymph nodes.
Objective: To identify novel anti-CD20 therapy markers in response to ofatumumab treatment in cynomolgus monkeys by using single-cell genomics technology.
Methods: Cynomolgus monkeys received human equivalent doses of ofatumumab (1mg/kg, s.c.) on Days 0, 7 and 14. Axillary lymph node biopsies were collected at various time points until Day 90. Single-cell mRNA analysis was performed on fluorescence-activated cell-sorted CD20+ B cells. The mRNA expression patterns were analysed with machine learning algorithms (t-distributed stochastic neighbor embedding [t-SNE]), which enables the similarity of cells to be expressed by the proximity of dots in a 2-D graph. A set of 96 detectable lymphocyte RNA markers was selected to generate clusters of related B cells.
Results: In cynomolgus monkeys, s.c. injection of low-dose ofatumumab induced a strong depletion of B cells from Days 2‒21, followed by a repletion starting 2 weeks after the last injection. Single-cell analysis of mRNA marker expression in 595 isolated CD20+ cells showed five t-SNE-defined cell clusters in untreated monkeys. Ofatumumab induced a new cell cluster and strongly enhanced a second cluster found at baseline. Upon repletion both clusters diminished, approaching cluster properties similar to baseline. No control markers such as CD4 or CD28 were detected in any of the six clusters. Cells in the new cluster expressed mRNA markers linked to the cell cycle/proliferation, such as CBX2, cyclin E1, cyclin A, AURKA, MK167 and FFM2, which were not expressed by the other clusters.
A more refined cluster analysis is under way.
Conclusions: Single-cell mRNA expression analysis in small-size samples is a new approach for identifying B-cell subsets, independent of known marker sets. Transcriptional expression analysis in MS and animal models may improve our molecular understanding of ofatumumab treatment effects on B-cell subsets and their role.
Disclosure: Funding source: This study was funded by Novartis Pharma AG, Basel, Switzerland.
All authors are employees of Novartis;
Paul Smith was an employee of Novartis at the time of study conduct.