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Sustained angiogenesis is essential for the development of solid tumors and metastatic disease. Disruption of signaling pathways that govern tumor vascularity provide a potential avenue to thwart cancer progression. Through phage display-based functional proteomics, immunohistochemical analysis of human pancreatic ductal carcinoma (PDAC) specimens, and in vitro validation, we reveal that hornerin, an S100 fused-type protein, is highly expressed on pancreatic tumor endothelium in a vascular endothelial growth factor (VEGF)-independent manner. Murine-specific hornerin knockdown in PDAC xenografts results in tumor vessels with decreased radii and tortuosity. Hornerin knockdown tumors have significantly reduced leakiness, increased oxygenation, and greater apoptosis. Additionally, these tumors show a significant reduction in growth, a response that is further heightened when therapeutic inhibition of VEGF receptor 2 (VEGFR2) is utilized in combination with hornerin knockdown. These results indicate that hornerin is highly expressed in pancreatic tumor endothelium and alters tumor vessel parameters through a VEGF-independent mechanism., Angiogenesis is essential for solid tumor progression. Here, the authors interrogate the proteome of pancreatic cancer endothelium via phage display and identify hornerin as a critical protein whose expression is essential to maintain the pancreatic cancer vasculature through a VEGF-independent mechanism. more...

Objective: Displacement ENcoding with Stimulated Echoes (DENSE) is an MRI technique developed to encode phase related to myocardial tissue displacements, and the displacement information directly applied towards detecting left-ventricular (LV) myocardial motion during the cardiac cycle. The purpose of this study is to present a novel, three-dimensional (3D) DENSE displacement-based and magnitude image quantization-based, semi-automated detection technique for myocardial wall motion, whose boundaries are used for rapid and automated computation of 3D myocardial strain. Methods: The architecture of this boundary detection algorithm is primarily based on pixelwise spatiotemporal increments in LV tissue displacements during the cardiac cycle and further reinforced by radially searching for pixel-based image gradients in multithreshold quantized magnitude images. This spatiotemporal edge detection methodology was applied to all LV partitions and their subsequent timeframes that lead to full 3D LV reconstructions. It was followed by quantifications of 3D chamber dimensions and myocardial strains, whose rapid computation was the primary motivation behind developing this algorithm. A pre-existing two-dimensional (2D) semi-automated contouring technique was used in parallel to validate the accuracy of the algorithm and both methods tested on DENSE data acquired in (N = 14) healthy subjects. Chamber quantifications between methods were compared using paired t-tests and Bland–Altman analysis established regional strain agreements. Results: There were no significant differences in the results of chamber quantifications between the 3D semi-automated and existing 2D boundary detection techniques. This included comparisons of ejection fractions, which were 0.62 ± 0.04 vs 0.60 ± 0.06 (p = 0.23) for apical, 0.60 ± 0.04 vs 0.59 ± 0.05 (p = 0.76) for midventricular and 0.56 ± 0.04 vs 0.58 ± 0.05 (p = 0.07) for basal segments, that were quantified using the 3D semi-automated and 2D pre-existing methodologies, respectively. Bland–Altman agreement between regional strains generated biases of 0.01 ± 0.06, –0.01 ± 0.01 and 0.0 ± 0.06 for the radial, circumferential and longitudinal directions, respectively. Conclusion: A new, 3D semi-automated methodology for contouring the entire LV and rapidly generating chamber quantifications and regional strains is presented that was validated in relation to an existing 2D contouring technique. Advances in knowledge: This study introduced a scientific tool for rapid, semi-automated generation of clinical information regarding shape and function in the 3D LV. more...

Background Cardiac resynchronization therapy (CRT) is an effective treatment for selected patients with heart failure (HF) and left bundle branch block (LBBB). However, an ongoing major issue with CRT is that 30-50% of treated patients are non-responders. One potential cause of a poor response is implantation of the CRT left-ventricular (LV) pacing lead at a suboptimal location, i.e., a location with scar or where mechanical activation is not delayed [1,2]. This study developed and applied cine DENSE strain imaging [3] to map mechanical activation and detect late-activated segments. Methods Cine DENSE was performed on a 1.5T MRI system in standard short-axis planes in 6 healthy subjects and 16 HF patients with LBBB and nonischemic cardiomyopathy referred to CRT. Circumferential strain (Ecc) was computed using previously described semiautomatic methods [4,5]. Midwall Ecc was arranged into a matrix with 18 rows representing spatial segments of the LV and 30-45 columns representing cardiac phases (Fig 1a). Singular value decomposition (SVD) was applied to denoise the spatiotemporal Ecc matrix, and an active contour method was used to automatically estimate the more...