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Publication Number
US-12607623-B2
Publication Date
2026-04-21
Expiration Date
Abstract
Various methods for isolating cell populations from adipocyte tissue and/or blood and quantifying levels of vascular endothelial growth factor receptors (VEGFR) on the isolated cell populations are provided. Also provided are methods of evaluating or modifying angiogenic therapy in a subject.
Core Innovation
The described invention determines the suitability of an anti-angiogenesis treatment in an obese subject by measuring vascular endothelial growth factor (VEGF) receptor levels on cells obtained from adipose tissue. The method isolates stromal vascular fraction (SVF) from an adipocyte tissue sample obtained from the subject and isolates a subpopulation of cells from the SVF using flow cytometry. VEGF receptors are then quantified on the isolated subpopulation of cells to support a candidate-selection decision.
A subject is identified as a candidate for anti-angiogenesis treatment if the levels of VEGF on the isolated subpopulation of cells exceed specified thresholds for VEGFR1 or VEGFR3 per cell. The method then treats the subject identified as a candidate with an anti-VEGF drug, specifically bevacizumab. The approach uses quantified VEGF receptor information to guide administration of anti-angiogenesis therapy in obese subjects.
The patent further refines quantification and analysis by using quantitative flow cytometry approaches that enable absolute receptor quantification on cells. In addition, cell-by-cell analysis is described using a Bayesian Information Criterion model with a Gaussian mixture model structure to derive a cell heterogeneity parameter. The analysis may be extended beyond flow cytometry to additional cell-by-cell analysis techniques including surface plasma resonance and computational modeling.
Claims Coverage
The independent claim covers a complete decision-and-treatment workflow for obese subjects using SVF isolation, flow-cytometric subpopulation isolation, VEGF receptor quantification, threshold-based candidate identification for anti-angiogenesis therapy, and subsequent bevacizumab treatment. The dependent claims refine how cell subpopulations are selected, how VEGF receptors are quantified, and how heterogeneity/classification is modeled, including specific modeling constraints and additional analysis modalities.
Anti-angiogenesis treatment suitability determination using SVF-derived VEGFR thresholds
A method determining the suitability of an anti-angiogenesis treatment in an obese subject by isolating stromal vascular fraction (SVF) from an adipocyte tissue sample, isolating a subpopulation of cells from the SVF using flow cytometry, quantifying levels of vascular endothelial growth factor (VEGF) receptors on cells, identifying the subject as a candidate if the levels of VEGF on the isolated subpopulation of cells exceed a threshold of 24,900 VEGFR1/cell or 25,000 VEGFR3/cell, and treating the subject identified as a candidate with anti-VEGF drug bevacizumab.
Marker-based isolation of SVF cell subpopulations
The method further includes labeling SVF cells with CD31, CD45, and CD146 markers and isolating specific cell populations based on CD31/CD146/CD45 marker combinations to classify adipose tissue macrophages, endothelial cells, blood cells, endothelial progenitor cells, preadipocytes, and unclassified cells.
Absolute quantification of VEGF receptors using PE calibration beads
The method quantifies VEGF receptors by using phycoerythrin (PE)-conjugated calibration beads to convert a mean PE fluorescence intensity into an absolute number of PE molecules per cell, where PE molecules per cell are proportional to the number of VEGF receptors per cell.
Cell heterogeneity parameter derived from BIC modeling of cell-by-cell VEGFR profiles
The method performs cell-by-cell quantitative flow cytometry analysis of the stromal vascular fraction by measuring VEGF receptor concentrations and optionally free VEGF receptor ligand concentrations, using a Bayesian Information Criterion model to derive a cell heterogeneity parameter, and comparing it to one or more cell heterogeneity reference values to classify the cells.
BIC model applied to a Gaussian mixture model with log-normal sub-distributions
The method applies a Bayesian Information Criterion model to analyze a Gaussian mixture model made up of 1-9 log-normal Gaussian sub-distributions.
Cell-by-cell analysis using flow cytometry, surface plasma resonance, and computational modeling
The method further includes performing cell-by-cell analysis of the SVF cell population using one or more selected techniques including flow cytometry, surface plasma resonance, and computational modeling.
Overall claim coverage centers on selecting obese subjects for anti-angiogenesis therapy by quantifying VEGFR1/VEGFR3 levels on SVF-derived cell subpopulations and comparing those quantifications to specified per-cell thresholds for candidate identification, followed by bevacizumab treatment. Dependent claims support the quantification and decision process via marker-based SVF subpopulation isolation, PE-calibration absolute receptor quantification, and BIC-based modeling of cell heterogeneity from cell-by-cell VEGFR profiles, with additional optional analysis modalities including surface plasma resonance and computational modeling.
Stated Advantages
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