![]() Imaging-Based Clusters Are Underpinned by Distinct Repertoires of Genetic Alterations For HIF-1α, a reverse pattern was found, with ovary yellow and ovary green areas displaying high levels of HIF-1α expression (H-scores, 115) compared with ovary blue and omentum blue (H-scores, 75 and 60, respectively Figs 1B and 1C ). Furthermore, distinct patterns and levels of CA-IX expression were observed among these areas, with ovary yellow and green having H-scores of 80, compared with 230 and 195 in ovary blue and omentum blue, respectively. Consistent with the imaging findings, which demonstrated that the ovary blue and omentum blue areas displayed the highest f, an MRI marker of tissue vascularity, CD31 immunohistochemical assessment revealed a higher density of tumor neovascularization (4+) in the ovary blue and omentum blue areas than in the ovary green and ovary yellow areas (2+ Fig 1C ). The expression levels and patterns of the hypoxia-marker HIF-1α and its downstream target CA-IX correlated with the distinct areas defined by multiparametric imaging ( Fig 1C ). In contrast, the ovary blue and omentum blue habitats displayed solid growth patterns and invaded into a reactive desmoplastic stroma however, focal areas of underlying papillary architecture were observed in the ovary blue sample ( Fig 1B ). Although overall the ovarian mass displayed a solid growth pattern, the ovary green and ovary yellow areas showed an underlying papillary architecture ( Fig 1B ). Phenotypic imaging-based clusters were associated with distinct histopathologic growth patterns. Imaging-Based Clusters Are Underpinned by Distinct Growth Patterns and Expression of Hypoxia-Related Markers DW, diffusion-weighted FDG, 18F-fluorodeoxyglucose TIL, tumor-infiltrating lymphocyte. (C) Imaging features associated with the distinct color areas as defined by k-means clustering of standardized uptake values (SUV), diffusion coefficient ( D), dynamic contrast-enhanced DCE parameter ( K trans), and water volume fraction flowing through microvessels ( f) are plotted on top, and the histopathologic features of the distinct imaging-based tumor areas are shown at the bottom. (B) Micrographs of representative hematoxylin and eosin (H and E)–stained sections of the imaging-based HGSOC areas (top row), and immunohistochemical analysis of CD31, Ki-67, CA-IX, and HIF-1α. Half of each imaging-based tissue area was formalin-fixed paraffin-embedded for histopathologic review and immunohistochemical analysis, and the other half was flash-frozen for whole-exome sequencing analysis. The distinct imaging habitats (labeled blue, yellow, and green) were sampled from the surgically removed primary HGSOC and metastatic implant using a three-dimensional (3D) mold. (A) Phenotypically distinct areas of a high-grade serous ovarian cancer (HGSOC) were identified by k-means clustering of imaging features derived from magnetic resonance imaging (MRI) and positron emission tomography (PET)/computed tomography. Study design and histopathologic review of the imaging-based high-grade serous ovarian cancer areas. We evaluated if this phenotypic imaging-based heterogeneity reflects the underlying histologic and/or genetic heterogeneity of the tumor.įIG 1. Phenotypic imaging maps of heterogeneity (ie, imaging habitats) of two HGSOC sites were obtained by combining perfusion, diffusion, and metabolic maps derived from multiparametric imaging. Here we use lesion-specific three-dimensional (3D) molds for phenotypic image-guided tumor sampling to ensure spatial colocation of imaging, histology, and genomic data, critical for understanding tumor biology. Such approaches will be vital for new clinical trials, especially those combining immunologic and genomically targeted therapies. 2- 5 Hence, developing imaging methods for guiding tissue sampling to physiologically and metabolically distinct tumor habitats is desirable. 3, 6 Our understanding of genomic heterogeneity in HGSOC is limited to single biopsies little is known about individual spatial and temporal variation across various tumor sites. 5 These region-specific properties may modulate malignant cell invasion and expansion, thereby shaping evolutionary selection. 4 The physical distribution of malignant clones across the peritoneal cavity may be nonrandom, because some sites harbor genetically diverse clones. 1 Studies have revealed that genomic intratumor heterogeneity correlates with poor survival 2, 3 and specific patterns of malignant cell spread in HGSOC. The overall survival of patients with high-grade serous ovarian cancer (HGSOC) has not improved during the past 20 years. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |