Myeloid-derived suppressor cells (MDSCs) are a heterogeneous population of cells that expand during cancer, inflammation and infection, and that have a remarkable ability to suppress T-cell responses. These cells constitute a unique component of the immune system that regulates immune responses in healthy individuals and in the context of various diseases. In this Review, we discuss the origin, mechanisms of expansion and suppressive functions of MDSCs, as well as the potential to target these cells for therapeutic benefit.

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Myeloid-derived suppressor cells as regulators of the immune system.

Stromal Fibroblasts Present in Invasive Human Breast Carcinomas Promote Tumor Growth and Angiogenesis through Elevated SDF-1/CXCL12 Secretion

https://escholarship.org/content/qt5st231s3/qt5st231s3.pdf?t=omsseb

Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy.

In both preclinical and clinical settings, the benefits of angiogenesis inhibitors targeting the vascular endothelial growth factor signalling pathways are at best transitory and followed by restoration of tumour growth and progression. Emerging data support a proposition that two modes of unconventional resistance underlie such results.

/pdf/modes-of-resistance-to-anti-angiogenic-therapy-2rh8qk82eh.pdf

Modes of resistance to anti-angiogenic therapy.

Inflammatory conditions in selected organs increase the risk of cancer. An inflammatory component is present also in the microenvironment of tumors that are not epidemiologically related to inflammation. Recent studies have begun to unravel molecular pathways linking inflammation and cancer. In the tumor microenvironment, smoldering inflammation contributes to proliferation and survival of malignant cells, angiogenesis, metastasis, subversion of adaptive immunity, reduced response to hormones and chemotherapeutic agents. Recent data suggest that an additional mechanism involved in cancer-related inflammation (CRI) is induction of genetic instability by inflammatory mediators, leading to accumulation of random genetic alterations in cancer cells. In a seminal contribution, Hanahan and Weinberg [(2000) Cell, 100, 57-70] identified the six hallmarks of cancer. We surmise that CRI represents the seventh hallmark.

/pdf/cancer-related-inflammation-the-seventh-hallmark-of-cancer-nlqsb6p8oy.pdf

Cancer-related inflammation, the seventh hallmark of cancer: links to genetic instability.

Expansion of myeloid immune suppressor Gr+CD11b+ cells in tumor-bearing host directly promotes tumor angiogenesis

Quantitative pharmacokinetic analysis of DCE-MRI data without an arterial input function: a reference region model

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can assess tumor perfusion, microvascular vessel wall permeability and extravascular–extracellular volume fraction. Analysis of DCE-MRI data is usually based on indicator dilution theory that requires knowledge of the concentration of the contrast agent in the blood plasma, the arterial input function (AIF). A method is presented that compares the tissues of interest (TOI) curve shape to that of a reference region (RR), thereby eliminating the need for direct AIF measurement. By assigning literature values for K trans (the blood perfusion-vessel permeability product) and ve (extravascular–extracellular volume fraction) in a reference tissue, it is possible to extract the K trans and ve values for a TOI without knowledge of the AIF. The operational RR equation for DCE-MRI analysis is derived, and its sensitivity to noise and incorrect assignment of the RR parameters is tested via simulations. The method is robust at noise levels of 10%, returning accurate (F20% in the worst case) and precise (F15% in the worst case) values. Errors in the TOI K trans and ve values scale approximately linearly with the errors in the assigned RR K trans and ve values. The methodology is then applied to a Lewis Lung Carcinoma mouse tumor model. A slowly enhancing TOI yielded K trans =0.039F0.002 min � 1 and ve=0.46F0.01, while a rapidly enhancing region yielded K trans =0.35F0.05 min � 1 and ve=0.31F0.01. Parametric K trans and ve mappings manifested a tumor periphery with elevated K trans (N0.30 min � 1 ) and ve (N0.30) values. The main advantage of the RR approach is that it allows for quantitative assessment of

Original contributions Quantitative pharmacokinetic analysis of DCE-MRI data without an arterial input function: a reference region model

Purpose

To test the repeatability of a reference region (RR) model for the analysis of dynamic contrast-enhanced MRI (DCE-MRI) in a mouse model of cancer at high field.



Materials and Methods

Seven mice were injected with 106 4T1 mammary carcinoma cells and imaged eight to 10 days later on a Varian 7.0T scanner. Two DCE-MRI studies were performed for each mouse (separated by 2.5 hours). The RR model was used to analyze the data, and returned estimates on the perfusion-permeability index (Ktrans) for the RR and the tissue of interest (TOI), as well as the extravascular extracellular volume fraction (ve) for the TOI.



Results

When the first injection was compared with the second injection, all parameters tested were highly correlated (r2 = 0.90, 0.62, 0.82 for the RR Ktrans, TOI Ktrans, and TOI ve, respectively, with P < 0.001 for all). To observe a statistically significant change (at the 5% level) in a treatment study with seven animals in each group, log10 changes of 0.084 and 0.077 in the tumor Ktrans and ve, respectively, are required.



Conclusion

If a reliable arterial input function (AIF) is unavailable, the RR model is a reasonable alternative to measuring MRI contrast-agent (CA) kinetics in mouse models of cancer at high field. J. Magn. Reson. Imaging 2006. © 2006 Wiley-Liss, Inc.

Repeatability of a reference region model for analysis of murine DCE-MRI data at 7T.

Models have been developed for the analysis of dynamic contrast-enhanced MRI (DCE-MRI) data that do not require direct measurements of the arterial input function; such methods are referred to as reference region models. These models typically return estimates of the volume transfer constant (K(trans)) and the extravascular extracellular volume fraction (v(e)). To date such models have assumed a linear relationship between the measured R(1) ( identical with 1/T(1)) and the concentration of contrast agent, a transformation referred to as the fast exchange limit, but this assumption is not valid for all concentrations of an agent. A theory for DCE-MRI reference region models which accounts for water exchange is presented, evaluated in simulations, and applied in tumor-bearing mice. Using reasonable parameter values, simulations show that the assumption of fast exchange can underestimate K(trans) and v(e) by up to 82% and 46%, respectively. By analyzing a large region of interest and a single voxel the new model can return parameters within approximately +/-10% and +/-25%, respectively, of their true values. Analysis of experimental data shows that the new approach returns K(trans) and v(e) values that are up to 90% and 73%, respectively, greater than conventional fast exchange analyses.

Incorporating the effects of transcytolemmal water exchange in a reference region model for DCE-MRI analysis: Theory, simulations, and experimental results

Laura Debusk

Papers

Expansion of myeloid immune suppressor Gr+CD11b+ cells in tumor-bearing host directly promotes tumor angiogenesis

Quantitative pharmacokinetic analysis of DCE-MRI data without an arterial input function: a reference region model

Original contributions Quantitative pharmacokinetic analysis of DCE-MRI data without an arterial input function: a reference region model

Repeatability of a reference region model for analysis of murine DCE-MRI data at 7T.

Incorporating the effects of transcytolemmal water exchange in a reference region model for DCE-MRI analysis: Theory, simulations, and experimental results