title: AngioMap is a novel image analysis algorithm for assessment of plasma cell distribution within bone marrow vascular niche.
abstract: The ability to characterize distribution of neoplastic hematopoietic cells and their progenitors in their native microenvironment is emerging as an important challenge and potential therapeutic target in many disease areas, including multiple myeloma. In multiple myeloma, bone marrow (BM) angiogenesis is typically increased and microvessel density is a known indicator of poor prognosis. However, the difficulty of consistently measuring 3D vessels from 2D cut sections has previously limited the study of spatial distribution of plasma cells (PC) and their interaction with BM microenvironment. The aim of the study is to report a novel method to study myeloma cells spatial distribution within their hematopoietic niche context using readily available tissue sections and standard histology approaches. We utilized a novel whole-tissue image analysis approach to identify vessels, and then applied computational grown regions extended out from each vessel at 15, 35, 55, 75, and 100 μm to identify the spatial distribution of PC on CD34/CD138 double-stained core biopsy slides. Percent PC to total cells (TC) was significantly higher at <15 μm distance compared with those at 16 to 35, 36 to 55, 56 to 75, and 76 to 100 μm distance (P=0.0001). Similarly, PC/TC at <35 μm region was significantly higher compared with 36 to 55 (P=0.0001), 56 to 75 (P≤0.0001), and 76 to 100 (P=0.0002) μm distances. The mean PC/TC differences in the spatial gradient of 36 to 55, 56 to 75, and 76 to 100 μm distance regions were not significant. Our findings suggest possible preferential advantage to neoplastic PC in the proximity of blood vessels compared with other hematopoietic marrow cells. We demonstrate the feasibility of analyzing the spatial distribution of PC, and possibly other hematopoietic/stem cells in their microenvironment, as characterized by the distance to vessels in BM using a novel image analysis approach.
authors: *Department of Pathology, University of Utah †ARUP Reference Lab Research Institute, Salt Lake City, UT ‡Flagship Biosciences, Boulder, CO.
authors: Mohamed E
authors: ME
authors: Salama
authors: Holger
authors: H
authors: Lange
authors: Sheryl R
authors: SR
authors: Tripp
authors: Jessica
authors: J
authors: Kohan
authors: Nicholas D
authors: ND
authors: Landis
authors: Joseph S
authors: JS
authors: Krueger
authors: Steven J
authors: SJ
authors: Potts
mesh_terms: D000328:Adult; D000368:Aged; D018952:Antigens, CD34 / Q000096:biosynthesis; D001853:Bone Marrow / Q000098:blood supply / Q000378:metabolism / Q000473:pathology; D001854:Bone Marrow Cells / Q000378:metabolism / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009101:Multiple Myeloma / Q000098:blood supply / Q000378:metabolism / Q000473:pathology; D009363:Neoplasm Proteins / Q000096:biosynthesis; D010950:Plasma Cells / Q000378:metabolism / Q000473:pathology; D053668:Syndecan-1 / Q000096:biosynthesis
chemical_list: D018952:Antigens, CD34; D009363:Neoplasm Proteins; C508241:SDC1 protein, human; D053668:Syndecan-1