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Conditional HIF-1 induction produces multistage neovascularization with stage-specific sensitivity to VEGFR inhibitors and myeloid cell independence.

ABSTRACT: Neovascularization is a crucial component of tumor growth and ischemia. Although prior work primarily used disease models, delineation of neovascularization in the absence of disease can reveal intrinsic mechanisms of microvessel regulation amenable to manipulation in illness. We created a conditional model of epithelial HIF-1 induction in adult mice (TetON-HIF-1 mice). Longitudinal photoacoustic microscopy (L-PAM) was coincidentally developed for noninvasive, label-free serial imaging of red blood cell-perfused vasculature in the same mouse for weeks to months. TetON-HIF-1 mice evidenced 3 stages of neovascularization: development, maintenance, and transgene-dependent regression. Regression occurred despite extensive and tight pericyte coverage. L-PAM mapped microvascular architecture and quantified volumetric changes in neocapillary morphogenesis, arteriovenous remodeling, and microvessel regression. Developmental stage endothelial proliferation down-regulation was associated with a DNA damage checkpoint consisting of p53, p21, and endothelial ?-H2AX induction. The neovasculature was temporally responsive to VEGFR2 immuno-blockade, with the developmental stage sensitive, and the maintenance stage resistant, to DC101 treatment. L-PAM analysis also pinpointed microvessels ablated or resistant to VEGFR2 immuno-blockade. HIF-1-recruited myeloid cells did not mediate VEGFR2 inhibitor resistance. Thus, HIF-1 neovascularization in the absence of disease is self-regulated via cell autonomous endothelial checkpoints, and resistant to angiogenesis inhibitors independent of myeloid cells.

SUBMITTER: Oladipupo SS

PROVIDER: S-EPMC3087536 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature

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Conditional HIF-1 induction produces multistage neovascularization with stage-specific sensitivity to VEGFR inhibitors and myeloid cell independence.

Oladipupo Sunday S SS Hu Song S Santeford Andrea C AC Yao Junjie J Kovalski Joanna R JR Shohet Ralph V RV Maslov Konstantin K Wang Lihong V LV Arbeit Jeffrey M JM

Blood 20110209 15

Neovascularization is a crucial component of tumor growth and ischemia. Although prior work primarily used disease models, delineation of neovascularization in the absence of disease can reveal intrinsic mechanisms of microvessel regulation amenable to manipulation in illness. We created a conditional model of epithelial HIF-1 induction in adult mice (TetON-HIF-1 mice). Longitudinal photoacoustic microscopy (L-PAM) was coincidentally developed for noninvasive, label-free serial imaging of red bl ...[more]

PMID: 21307392

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Project description:Functional connectivity concerns the correlated activity between neuronal populations in spatially segregated regions of the brain, which may be studied using functional magnetic resonance imaging (fMRI). This coupled activity is conveniently expressed using covariance, but this measure fails to distinguish between direct and indirect effects. A popular alternative that addresses this issue is partial correlation, which regresses out the signal of potentially confounding variables, resulting in a measure that reveals only direct connections. Importantly, provided the data are normally distributed, if two variables are conditionally independent given all other variables, their respective partial correlation is zero. In this paper, we propose a probabilistic generative model that allows us to estimate functional connectivity in terms of both partial correlations and a graph representing conditional independencies. Simulation results show that this methodology is able to outperform the graphical LASSO, which is the de facto standard for estimating partial correlations. Furthermore, we apply the model to estimate functional connectivity for twenty subjects using resting-state fMRI data. Results show that our model provides a richer representation of functional connectivity as compared to considering partial correlations alone. Finally, we demonstrate how our approach can be extended in several ways, for instance to achieve data fusion by informing the conditional independence graph with data from probabilistic tractography. As our Bayesian formulation of functional connectivity provides access to the posterior distribution instead of only to point estimates, we are able to quantify the uncertainty associated with our results. This reveals that while we are able to infer a clear backbone of connectivity in our empirical results, the data are not accurately described by simply looking at the mode of the distribution over connectivity. The implication of this is that deterministic alternatives may misjudge connectivity results by drawing conclusions from noisy and limited data.

Dataset Information

Conditional HIF-1 induction produces multistage neovascularization with stage-specific sensitivity to VEGFR inhibitors and myeloid cell independence.

Publications

Conditional HIF-1 induction produces multistage neovascularization with stage-specific sensitivity to VEGFR inhibitors and myeloid cell independence.

Similar Datasets

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