Cell Mass and Stiffness As Integrative Biomarkers of Cell State in Mantle Cell Lymphoma

Background: Mantle cell lymphoma (MCL) manifests extensive clinical phenotypic heterogeneity, ranging from indolent to aggressive, rapidly progressive disease. Molecular, genomic, transcriptomic, and immunophenotypic variation, as well as the presence of multiple subclones at diagnosis reflect the clinical diversity seen among MCL patients and make it challenging to define therapies that optimally align with individual patient risk. Biophysical phenotypes of cells, such as mass, density and stiffness, are valuable markers of changes in their intrinsic properties and closely associated with cellular states and functions, which have proven useful in elucidating fundamental processes in cell growth and development. We integrate single-cell biophysical features, which provide more granularity than canonical immunophenotypes, to further refine the biological characterization of MCL with the goal of defining rapid ex vivo biomarkers of clinical response or resistance.

Methods: We utilize a device called suspended microchannel resonator (SMR) to perform biophysical measurements (mass, stiffness and density) of individual cells. We characterized the biophysical properties of MCL cells from representative sites, including peripheral blood, bone marrow and lymph nodes, of human clinical specimens and, additionally, spleen from six patient-derived xenografts (PDX) models of MCL. Furthermore, to identify genes that covary with lymphoma cell biophysical heterogeneity, we linked the biophysical measurements of individual MCL cells from the matched spleen, peripheral blood, bone marrow, and liver tissues of three carefully curated PDX models of MCL to downstream single-cell RNA-sequencing (SMR-scRNA-Seq).

Results: We observed inter- and intra-tumor heterogeneity in mass and stiffness within each lymphoma specimen. Interestingly, these biophysical features reflect underlying histopathologic phenotypes, with higher mass and higher stiffness measured in blastoid and pleomorphic diseases as opposed to the smaller classical variant. By coupling biophysical measurement with transcriptomic profiling at single-cell resolution, we found that mass is strongly associated with the expression of genes annotated for cell division, cell cycle, and B-cell activation such as CCNB1, CDK1, CENPF, BLK, CD79A. Similarly, cell stiffness correlated with B-cell activation signatures and B-cell receptor signaling pathway activity, especially in the highly proliferative models. Functional genomics assays are ongoing to validate the contribution of these target pathways to MCL biophysical changes.

To further define how B-cell activation impacts cellular biophysical properties, we profiled the biophysical properties of normal mature B-cell developmental stages from naïve B-cells to plasma cells. We found that cells at each differentiation stage possess a unique combination of mass, stiffness, and density. Highlighting the dynamic nature of these properties, B-cells undergo significant biophysical change after activation, with buoyant mass quadrupling upon activation and then rapidly decreasing by half. Preliminary data further reveal that mature B-cells lose approximately 25% of their stiffness after activation before reverting to their original stiffness after immunoglobulin class switching and even increasing in stiffness at the plasma cell stage. Most MCL cells are conventionally thought to derive from naïve pre-germinal center B cells, but our analysis revealed biophysical profiles overlapping strongly with more mature B cell states, suggesting that lymphomagenesis may entail reprogramming the machinery regulating cell mass and stiffness. We are now generating biophysical, transcriptomic, and genomic measurements within primary specimens from patients with MCL undergoing combined therapy targeting BTK, BCL2, and CD20 to assess their potential for inclusion within integrated predictive biomarkers.

Conclusions: We established the biophysical landscape of MCL and non-malignant B-lymphoid cells to sharpen biological characterization and resolve tumor heterogeneity. We did so using a unique single-cell platform integrating transcriptomic and biophysical features as rapid, quantitative, and label-free measurements of live-cell state and phenotypic composition in pursuit of functionally integrated predictive biomarkers.