Science AdvancesCancer BiologyPeer-reviewed journal article
Integrating Single-Cell Biophysical and Transcriptomic Features to Resolve Functional Heterogeneity in Mantle Cell Lymphoma
Ye ZhangiD, Lydie L. DebaizeiD, Adam LangenbucheriD, Jenalyn WeekesiD, Ioulia VogiatziiD, Teemu P. MiettineniD, Mingzeng ZhangiD, Emily SumpenaiD, Huiyun Liu, Sarah Marie DuquetteiD, Liam R. HackettiD, Jeremy Zhang, Sona BaghiyaniD, Robert Allyn ReddiD, Martin J. AryeeiD, Matthew Steven DavidsiD, Austin Injae KimiD, Christine E. RyaniD, David M. WeinstockiD, Scott R. ManalisiD, Mark Alan MurakamiiD
Abstract
Intra-tumor heterogeneity impacts disease progression and therapeutic resistance but remains poorly characterized by conventional histologic, immunophenotypic, and molecular approaches. Single-cell biophysical properties distinguish functional phenotypes complementary to these approaches, providing additional insight into cellular diversity. Here we link both buoyant mass and stiffness to gene expression to identify clinically relevant phenotypes within primary mantle cell lymphoma (MCL) cells, employing MCL as a model of biological and clinical diversity in human cancer. Linked measurements reveal that buoyant mass and stiffness characterize B-cell development states from naive to plasma cell and correlate with expression of oncogenic B-cell receptor signaling genes such as BLK and CD79A. Additionally, changes in cell buoyant mass within primary patient specimens ex vivo correlate with sensitivity to Brutons Tyrosine Kinase inhibitors in vivo in MCL and chronic lymphocytic leukemia, another B-cell malignancy. These findings highlight the value of biophysical properties as biomarkers of response in pursuit of future precision therapeutic strategies.
- organism: human
- assay: scRNA-seq
- assay: metabolomics
- research focus: cell type annotation
- research focus: differential expression
- research focus: drug response / drug discovery
- approach: experimental assay
- approach: statistical model
- Citations
- 2
- FWCI
- 1.33
- Field percentile
- top 17%
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