2nd Window NIR Imaging of Radiation Injury Mitigation Provided by Reduced Notch-Dll4 Expression on Vasculature.

PURPOSE: Vascular endothelium plays a central role in the pathogenesis of acute and chronic radiation injuries, yet the mechanisms which promote sustained endothelial dysfunction and contribute to late responding organ failure are unclear. We employed 2nd window (> 1100 nm emission) Near-Infrared (NIR) imaging using indocyanine green (ICG) to track and define the role of the notch ligand Delta-like ligand 4 (Dll4) in mediating vascular injury in two late-responding radiosensitive organs: the lung and kidney. PROCEDURES: Consomic strains of female Salt Sensitive or SS (Dll4-high) and SS with 3rd chromosome inherited from Brown Norway, SS.BN3 (Dll4-low) rats at ages 11-12 weeks were used to demonstrate the impact of reduced Dll4 expression on long-term vascular integrity, renal function, and survival following high-dose 13 Gy partial body irradiation at 42- and 90 days post-radiation. 2nd window dynamic NIR fluorescence imaging with ICG was analyzed with physiology-based pharmacokinetic modeling and confirmed with assays of endothelial Dll4 expression to assess the role of endogenous Dll4 expression on radiation injury protection. RESULTS: We show that SS.BN3 (Dll4-low) rats are relatively protected from vascular permeability disruption compared to the SS (Dll4-high) strain. We further demonstrated that SS.BN3 (Dll4-low) rats have reduced radiation induced loss of CD31+ vascular endothelial cells, and increased Dll4 vascular expression is correlated with vascular dysfunction. CONCLUSIONS: Together, these data suggest Dll4 plays a key role in pathogenesis of radiation-induced vascular injury to the lung and kidney.

X-ray and MR Contrast Bearing Nanoparticles Enhance the Therapeutic Response of Image-Guided Radiation Therapy for Oral Cancer.

INTRODUCTION: Radiation therapy for head and neck squamous cell carcinoma is constrained by radiotoxicity to normal tissue. We demonstrate 100 nm theranostic nanoparticles for image-guided radiation therapy planning and enhancement in rat head and neck squamous cell carcinoma models. METHODS: PEG conjugated theranostic nanoparticles comprising of Au nanorods coated with Gadolinium oxide layers were tested for radiation therapy enhancement in 2D cultures of OSC-19-GFP-luc cells, and orthotopic tongue xenografts in male immunocompromised Salt sensitive or SS rats via both intratumoral and intravenous delivery. The radiation therapy enhancement mechanism was investigated. RESULTS: Theranostic nanoparticles demonstrated both X-ray/magnetic resonance contrast in a dose-dependent manner. Magnetic resonance images depicted optimal tumor-to-background uptake at 4 h post injection. Theranostic nanoparticle + Radiation treated rats experienced reduced tumor growth compared to controls, and reduction in lung metastasis. CONCLUSIONS: Theranostic nanoparticles enable preprocedure radiotherapy planning, as well as enhance radiation treatment efficacy for head and neck tumors.

Automated deep learning auto-segmentation of air volumes for MRI-guided online adaptive radiation therapy of abdominal tumors.

Objective. In the current MR-Linac online adaptive workflow, air regions on the MR images need to be manually delineated for abdominal targets, and then overridden by air density for dose calculation. Auto-delineation of these regions is desirable for speed purposes, but poses a challenge, since unlike computed tomography, they do not occupy all dark regions on the image. The purpose of this study is to develop an automated method to segment the air regions on MRI-guided adaptive radiation therapy (MRgART) of abdominal tumors.Approach. A modified ResUNet3D deep learning (DL)-based auto air delineation model was trained using 102 patients' MR images. The MR images were acquired by a dedicated in-house sequence named 'Air-Scan', which is designed to generate air regions that are especially dark and accentuated. The air volumes generated by the newly developed DL model were compared with the manual air contours using geometric similarity (Dice Similarity Coefficient (DSC)), and dosimetric equivalence using Gamma index and dose-volume parameters.Main results. The average DSC agreement between the DL generated and manual air contours is 99% ± 1%. The gamma index between the dose calculations with overriding the DL versus manual air volumes with density of 0.01 is 97% ± 2% for a local gamma calculation with a tolerance of 2% and 2 mm. The dosimetric parameters from planning target volume-PTV and organs at risk-OARs were all within 1% between when DL versus manual contours were overridden by air density. The model runs in less than five seconds on a PC with 28 Core processor and NVIDIA Quadro®P2000 GPU.Significance: a DL based automated segmentation method was developed to generate air volumes on specialized abdominal MR images and generate results that are practically equivalent to the manual contouring of air volumes.

Auto-detection of necessity for MRI-guided online adaptive replanning using a machine learning classifier.

PURPOSE: MRI-guided adaptive radiation therapy (MRgART), particularly daily online adaptive replanning (OLAR) can substantially improve radiation therapy delivery, however, it can be labor-intensive and time-consuming. Currently, the decision to perform OLAR for a treatment fraction is determined subjectively. In this work, we develop a machine learning algorithm based on structural similarity index measure (SSIM) and change in entropy to quickly and objectively determine whether OLAR is necessary for a daily MRI set. METHODS: A total of 109 daily MRI sets acquired on a 1.5T MR-Linac during MRgART for 22 pancreatic cancer patients each treated with five fractions were retrospectively analyzed. For each daily MRI set, OLAR and reposition (No-OLAR) plans were created and the superior plan with the daily fraction determined per clinical dose-volume criteria. SSIM and entropy maps were extracted from each daily MRI set, with respect to its reference (e.g., dry-run) MRI in the region enclosed by 50-100% isodose surfaces. A total of six common features were extracted from SSIM maps. Pearson's rank correlation coefficient was utilized to rule out redundant SSIM features. A t-test was used to determine significant SSIM features which were combined with the change in entropy to develop anensemble machine classifier with fivefold cross validation. The performance of the classifier was evaluated using the area under the curve (AUC) of the receiver operating characteristic curve. RESULTS: A machine learning classifier model using two SSIM features (mean and full width at half maximum) and change in entropy was determined to be able to significantly discriminate between No-OLAR and OLAR groups. The obtained machine learning ensemble classifier can predict OLAR necessity with a cross validated AUC of 0.93. Misclassification was found primarily for No-OLAR cases with dosimetric plan quality closely comparable to the corresponding OLAR plans, thus, are not a major practical concern. CONCLUSION: A machine learning classifier based on simple first-order image features, that is, SSIM features and change in entropy, was developed to determine when OLAR is necessary for a daily MRI set with practical acceptable prediction accuracy. This classifier may be implemented in the MRgART process to automatically and objectively determine if OLAR is required following daily MRI.

Predicting necessity of daily online adaptive replanning based on wavelet image features for MRI guided adaptive radiation therapy.

PURPOSE: Online adaptive replanning (OLAR) is generally labor-intensive and time-consuming during MRI-guided adaptive radiation therapy (MRgART). This work aims to develop a method to determine OLAR necessity during MRgART. METHODS: A machine learning classifier was developed to predict OLAR necessity based on wavelet multiscale texture features extracted from daily MRIs and was trained and tested with data from 119 daily MRI datasets acquired during MRgART for 24 pancreatic cancer patients treated on a 1.5 T MR-Linac. Spearman correlations, interclass correlation (ICC), coefficient of variance (COV), t-test (p < 0.05), self-organized map (SOM) and maximum stable extremal region (MSER) algorithm were used to determine candidate features, which were used to build the prediction models using Bayesian classifiers. The model performance was judged using the AUC of the ROC curve. RESULTS: Spearman correlation identified 123 features that were not redundant (r < 0.9). Of them 82 showed high ICC for repositioning > 0.6, 67 had a COV greater than 9% for OLAR. Among the 38 features passed the t-test, 25 passed the SOM and 12 passed the MSER. These final 12 features were used to build the classifier model. The combination of 2-3 features at a time was used to build the classifier models. The best performing model was a 3-feature combination, which can predict OLAR necessity with a CV-AUC of 0.98. CONCLUSIONS: A machine learning classifier model based on the wavelet features extracted from daily MRI for pancreatic cancer was developed to automatically and objectively determine if OLAR is necessary for a treatment fraction avoiding unnecessary effort during MRgART.

Development and implementation of an automatic air delineation technique for MRI-guided adaptive radiation therapy.

Objective.Auto-delineation of air regions on daily MRI for MR-guided online adaptive radiotherapy (MRgOART) of abdominal tumors is challenging since the air packets occur randomly and their MR intensities can be similar to some other tissue types. This work reports a new method to auto-delineate air regions on MRI.Approach.The proposed method (named DIFF method) consists of (1) generating a combined volumeVcomb, which is a union of the air-containing organs on a reference MR image offline, (2) transferringVcombfrom the reference MR to a daily MR via DIR, (3) combining the transferredVcombwith a region of high DIR inaccuracy, and (4) applying a threshold to the obtained final combined volume to generate the air volumes. The high DIR inaccuracy region was calculated from the absolute difference between the deformed daily and the reference images. This method was tested on 36 abdominal daily MRI sets acquired from 7 patients on a 1.5 T MR-Linac. The performance of DIFF was compared with alternative auto-air generation methods that (1) does not account for DIR inaccuracies, and (2) uses rigid registration instead of DIR.Main results.The results show that the proposed DIFF method can be fully automated and can be executed within 25 s. The Dice similarity coefficient of manual and DIFF auto-generated air contours was >92% for all cases, while it was 90% for the alternative auto-delineation methods. Dosimetrically, the auto-generated air regions using DIFF resulted in practically identical DVHs as those generated by using manual air contours.Significance.The DIFF method is robust and accurate and can be implemented to automatically consider the inter- and intra- fractional air volume variations during MRgOART for abdominal tumors. The use of DIFF method improves dosimetric accuracy as compared to other methods, especially beneficial for the patients with large daily abdominal air volume variations.

Physiochemical characterization of highly biocompatible, and colloidal LaF3:Yb/Er upconversion nanoparticles.

Highly colloidal upconversion nanoparticles (UCNPs) were synthesized at low temperatures by the thermal decomposition process. The structure, morphology, crystallinity, surface chemistry, and optical properties were systematically optimized and studied through various spectroscopic techniques. X-ray diffraction (XRD) patterns have shown the formation of single-phase, highly purified, well-crystalline, hexagonal LaF3 NPs, while the TEM micrographs show small, irregular sizes, spherically shaped, and aggregated polycrystalline UCNPs with an average crystalline size of about 8-15 nm. The Negative Zeta Potential value exhibits good biocompatibility of the UCNPs, which supports the idea that surface-anchored hydroxyl groups facilitate the stabilization of the NPs in aqueous media, as well as enhance biomolecules' tagging efficiency. The absorption spectrum, Zeta Potential, and hydrodynamic size that were measured in aqueous media illustrate excellent dispersibility, colloidal stability, biocompatibility, and cytotoxicity character of the UCNPs. Zeta potential and MTT assay studies illustrated high biocompatibility, it could be due to the surface-anchored hydroxyl groups. The nanoproduct demonstrates an excellent UC luminescence spectrum (i.e., prominent green emission 4S3/2 → 4I/15/2) upon irradiation by the 980-nm laser diode. TEM micrographs, further, revealed that this optically active material with aqueous sensitivities, porous crystal structure, and excellent UCNPs, could be a favorable candidate for potential photonics-based bio-related applications.

A rapid dynamic in vivo near-infrared fluorescence imaging assay to track lung vascular permeability after acute radiation injury.

To develop a dynamic in vivo near-infrared (NIR) fluorescence imaging assay to quantify sequential changes in lung vascular permeability-surface area product (PS) in rodents. Dynamic NIR imaging methods for determining lung vascular permeability-surface area product were developed and tested on non-irradiated and 13 Gy irradiated rats with/without treatment with lisinopril, a radiation mitigator. A physiologically-based pharmacokinetic (PBPK) model of indocyanine green (ICG) pulmonary disposition was applied to in vivo imaging data and PS was estimated. In vivo results were validated by five accepted assays: ex vivo perfused lung imaging, endothelial filtration coefficient (Kf) measurement, pulmonary vascular resistance measurement, Evan's blue dye uptake, and histopathology. A PBPK model-derived measure of lung vascular permeability-surface area product increased from 2.60 ± 0.40 [CL: 2.42-2.78] mL/min in the non-irradiated group to 6.94 ± 8.25 [CL: 3.56-10.31] mL/min in 13 Gy group after 42 days. Lisinopril treatment lowered PS in the 13 Gy group to 4.76 ± 6.17 [CL: 2.12-7.40] mL/min. A much higher up to 5× change in PS values was observed in rats exhibiting severe radiation injury. Ex vivo Kf (mL/min/cm H2O/g dry lung weight), a measure of pulmonary vascular permeability, showed similar trends in lungs of irradiated rats (0.164 ± 0.081 [CL: 0.11-0.22]) as compared to non-irradiated controls (0.022 ± 0.003 [CL: 0.019-0.025]), with reduction to 0.070 ± 0.035 [CL: 0.045-0.096] for irradiated rats treated with lisinopril. Similar trends were observed for ex vivo pulmonary vascular resistance, Evan's blue uptake, and histopathology. Our results suggest that whole body dynamic NIR fluorescence imaging can replace current assays, which are all terminal. The imaging accurately tracks changes in PS and changes in lung interstitial transport in vivo in response to radiation injury.

Safeguarding COVID-19 and cancer management: drug design and therapeutic approach.

Recent clinical cohort studies have highlighted that there is a three-fold greater SARS-Cov-2 infection risk in cancer patients, and overall mortality in individuals with tumours is increased by 41% with respect to general COVID-19 patients. Thus, access to therapeutics and intensive care is compromised for people with both diseases (comorbidity) and there is risk of delayed access to diagnosis. This comorbidity has resulted in extensive burden on the treatment of patients and health care system across the globe; moreover, mortality of hospitalized patients with comorbidity is reported to be 30% higher than for individuals affected by either disease. In this data-driven review, we aim specifically to address drug discoveries and clinical data of cancer management during the COVID-19 pandemic. The review will extensively address the treatment of COVID-19/cancer comorbidity; treatment protocols and new drug discoveries, including the description of drugs currently available in clinical settings; demographic features; and COVID-19 outcomes in cancer patients worldwide.

Localized and triggered release of oxaliplatin for the treatment of colorectal liver metastasis.

Purpose: The aim of this study was to develop and evaluate a liposome formulation that deliver oxaliplatin under magnetic field stimulus in high concentration to alleviate the off-target effects in a rat model of colorectal liver metastases (CRLM). Materials and Methods: Hybrid liposome-magnetic nanoparticles loaded with Cy5.5 dye and oxaliplatin (L-NIR- Fe3O4/OX) were synthesized by using thermal decomposition method. CRLM (CC-531) cell viability was assessed and rats orthotopically implanted with CC-531 cells were treated with L-NIR-Fe3O4/OX or by drug alone via different routes, up to 3 cycles of alternating magnetic field (AMF). Optical and MR imaging was performed to assess the targeted delivery. Biodistribution and histology was performed to determine the distribution of oxaliplatin. Results: L-NIR-Fe3O4/OX presented a significant increase of oxaliplatin release (~18%) and lower cell viability after AMF exposure (p<0.001). Optical imaging showed a significant release of oxaliplatin among mesenteric vein injected (MV) group of animals. MR imaging on MV injected animals showed R2* changes in the tumor regions at the same regions immediately after infusion compared to the surrounding liver (p<0.001). Biodistribution analysis showed significantly higher levels of oxaliplatin in liver tissues compared to lungs (p<0.001) and intestines (p<0.001) in the MV animals that received AMF after L-NIR- Fe3O4/OX administration. Large tumor necrotic zones and significant improvement in the survival rates were noted in the MV animals treated with AMF. Conclusion: AMF triggers site selective delivery of oxaliplatin at high concentrations and improves survival outcomes in colorectal liver metastasis tumor bearing rats.

NIR-II window tracking of hyperglycemia induced intracerebral hemorrhage in cerebral cavernous malformation deficient mice.

Second near infrared (NIR-II) window fluorescence imaging between 1000 and 1700 nm with reduced scattering and autofluorescence and deep tissue light penetration allows early and non-invasive determination of vascular pathologies. Here, we demonstrate in vivo NIR-II imaging techniques for tracking hyperglycaemia-induced Intracerebral Hemorrhage (ICH) and Blood Brain Barrier (BBB) hyperpermeability in Cerebral Cavernous Malformation (CCM) deficient mice (CCM1+/-). We synthesised PEGylated Ag2S quantum dots (QDs) with a bright fluorescent emission peak centred at 1135 nm under an 808 nm NIR light for dynamic imaging of cerebral vasculature in mice and determined the development of ICH and BBB impairment in hyperglycaemic CCM1+/- mice. In vivo optical imaging was conducted with micro-CT (including k-mean cluster analysis) as well as in vivo permeability assays using FITC-dextran perfusion and IgG staining, respectively. The increased BBB permeability in CCM1+/- mice was further demonstrated to be associated with a high-glucose-caused decrease of CCM1 expressions. This study validates that deep-penetrating NIR-II QDs can be used for the tracking of ICH and BBB hyperpermeability in transgenic mice models of cerebral vascular anomalies.

Heritable modifiers of the tumor microenvironment influence nanoparticle uptake, distribution and response to photothermal therapy.

We report the impact of notch-DLL4-based hereditary vascular heterogeneities on the enhanced permeation and retention (EPR) effect and plasmonic photothermal therapy response in tumors. Methods: We generated two consomic rat strains with differing DLL4 expression on 3rd chromosome. These strains were based on immunocompromised Salt-sensitive or SSIL2Rγ- (DLL4-high) and SS.BN3IL2Rγ- (DLL4-low) rats with 3rd chromosome substituted from Brown Norway rat. We further constructed three novel SS.BN3IL2Rγ- congenic strains by introgressing varying segments of BN chromosome 3 into the parental SSIL2Rγ- strain to localize the role of SSIL2Rγ- DLL4 on tumor EPR effect with precision. We synthesized multimodal theranostic nanoparticles (TNPs) based on Au-nanorods which provide magnetic resonance imaging (MRI), X-ray, and optical contrasts to assess image guided PTT response and quantify host specific therapy response differences in tumors orthotopically xenografted in DLL4-high and -low strains. We tested recovery of therapy sensitivity of PTT resistant strains by employing anti-DLL4 conjugated TNPs in two triple negative breast cancer tumor xenografts. Results: Host strains with high DLL4 allele demonstrated slightly increased tumor nanoparticle uptake but consistently developed photothermal therapy resistance compared to tumors in host strains with low DLL4 allele. Tumor micro-environment with low DLL4 expression altered the geographic distribution of nanoparticles towards closer proximity with vasculature which improved efficacy of PTT in spite of lower overall TNP uptake. Targeting TNPs to tumor endothelium via anti-DLL4 antibody conjugation improved therapy sensitivity in high DLL4 allele hosts for two triple negative human breast cancer xenografts. Conclusions: Inherited DLL4 expression modulates EPR effects in tumors, and molecular targeting of endothelial DLL4 via nanoparticles is an effective personalized nanomedicine strategy.

AMP-Kinase Dysfunction Alters Notch Ligands to Impair Angiogenesis in Neonatal Pulmonary Hypertension.

Decreased angiogenesis contributes to persistent pulmonary hypertension of the newborn (PPHN); mechanisms remain unclear. AMPK (5'AMP activated protein kinase) is a key regulator of cell metabolism. We investigated the hypothesis that a decrease in AMPK function leads to mitochondrial dysfunction and altered balance of notch ligands delta-like 4 (DLL4) and Jagged 1 (Jag1) to impair angiogenesis in PPHN. Studies were done in fetal lambs with PPHN induced by prenatal ductus arteriosus constriction and gestation-matched control lambs. PPHN lambs were treated with saline or AMPK agonist metformin. Angiogenesis was assessed in lungs with micro-computed tomography angiography and histology. AMPK function; expression of mitochondrial electron transport chain (ETC) complex proteins I-V, Dll4, and Jag1; mitochondrial number; and in vitro angiogenesis function were assessed in pulmonary artery endothelial cells (PAEC) from control and PPHN lambs. AMPK function was decreased in PPHN PAEC and lung sections. Expression of mitochondrial transcription factor, PGC-1α, ETC complex proteins I-V, and mitochondrial number were decreased in PPHN. In vitro angiogenesis of PAEC and capillary number and vessel volume fraction in the lung were decreased in PPHN. Expression of DLL4 was increased and Jag1 was decreased in PAEC from PPHN lambs. AMPK agonists A769662 and metformin increased the mitochondrial complex proteins and number, in vitro angiogenesis, and Jag1 levels and decreased DLL4 levels in PPHN PAEC. Infusion of metformin in vivo increased the vessel density in PPHN lungs. Decreased AMPK function contributes to impaired angiogenesis in PPHN by altered balance of notch ligands in PPHN.

Progress in Remotely Triggered Hybrid Nanostructures for Next-Generation Brain Cancer Theranostics.

Progress in nanomedicine has enabled the development of smart hybrid nanostructures (HNSs) for brain cancer theranostics, a novel platform that can diagnose the brain while concurrently beginning primary treatment, initiating secondary treatments where necessary, and monitoring the therapy response. These HNSs can release guest molecules/cargoes directly to brain tumors in response to external physical stimuli. Such physical stimulation is generally referred to as remote stimuli which can be externally applied examples include alternating magnetic field, visible or near-infrared light, ultrasound radiation, X-ray, and radiofrequency. The release of therapeutic cargoes in response to physical stimuli can be performed along with photodynamic therapy, photothermal therapy, phototriggered chemotherapeutics, sonodynamic therapy, electrothermal therapy, and magnetothermal therapy. Herein, we review different HNSs currently used as remotely triggered modalities in brain cancer, such as organic-inorganic HNSs, polymer micelles, and liposomes HNSs. We also summarize underlying mechanisms of remote triggering brain cancer therapeutics including single- and two-photon triggering, thermoresponsive HNSs, photoresponsive HNSs, magnetoresponsive HNSs, and electrically and ultrasound-stimulated HNSs. In addition to a brief synopsis of ongoing research progress on "smart" HNSs-based platforms of novel brain cancer therapeutics, the review offers an up-to-date development in this field for neuro-oncologists, material/nanoscientists, and radiologists so that a rapid clinical impact can be achieved through a convergence of multidisciplinary expertise.

Erratum: Methods for detecting host genetic modifiers of tumor vascular function using dynamic near-infrared fluorescence imaging: errata.

[This corrects the article on p. 543 in vol. 9, PMID: 29552392.].

Methods for detecting host genetic modifiers of tumor vascular function using dynamic near-infrared fluorescence imaging.

Vascular supply is a critical component of the tumor microenvironment (TME) and is essential for tumor growth and metastasis, yet the endogenous genetic modifiers that impact vascular function in the TME are largely unknown. To identify the host TME modifiers of tumor vascular function, we combined a novel genetic mapping strategy [Consomic Xenograft Model] with near-infrared (NIR) fluorescence imaging and multiparametric analysis of pharmacokinetic modeling. To detect vascular flow, an intensified cooled camera based dynamic NIR imaging system with 785 nm laser diode based excitation was used to image the whole-body fluorescence emission of intravenously injected indocyanine green dye. Principal component analysis was used to extract the spatial segmentation information for the lungs, liver, and tumor regions-of-interest. Vascular function was then quantified by pK modeling of the imaging data, which revealed significantly altered tissue perfusion and vascular permeability that were caused by host genetic modifiers in the TME. Collectively, these data demonstrate that NIR fluorescent imaging can be used as a non-invasive means for characterizing host TME modifiers of vascular function that have been linked with tumor risk, progression, and response to therapy.

SERS-fluorescence bimodal nanoprobes for in vitro imaging of fatty acid responsive receptor GPR120.

G-protein-coupled receptor 120 (GPR120), as a member of the rhodopsin family of G-protein-coupled receptors, has been shown to function as a sensor for dietary fat in the gustatory and digestive systems. Its specific role in the chemoreception of fatty acids, which is thought to be crucial in understanding the mechanism surrounding the control of fat intake and, accordingly, in the treatment of obesity, remains unclear. Here we report a novel surface-enhanced Raman spectroscopy (SERS)-fluorescence bimodal microscopic technique for detection and imaging of GPR120 in single living cells. CaMoO4:Eu3+@AuNR hybrid nanoparticles are synthesized and characterized as imaging probes. Biocompatibility and imaging capability of the probes are investigated using a model HEK293 cell line with an inducible GPR120 gene transfection. Cellular distribution of GPR120 is visualized by single-cell SERS and fluorescence imaging. A dose-dependent GPR120 response to linoleic acid treatment is revealed by SERS.

Effective Screening and Classification of Cervical Precancer Biopsy Imagery.

Microscope images of biopsy samples of cervical precancers conventionally discriminated by histopathology, the current "gold standard" for cancer detection, showed that their correlation properties are segregated into different classes. The correlation domains clearly indicate increasing cellular clustering in different grades of precancer compared with their normal counterparts. This trend indicates the probability of pixel distribution of the corresponding tissue images. Because the cell density is not uniform in the higher grades, the skewness (asymmetry of a distribution), kurtosis (sharpness of a distribution), entropy (randomness), and standard deviation are affected. A combination of these parameters effectively improves the diagnosis and quantitatively classifies the normal and all the three grades of precancerous cervical tissue sections significantly. Thus, the statistical analysis of microscope images is a promising approach for early stage tumor detection and quantitative classification of precancerous grades; this can effectively supplement the qualitative analysis by the pathologist.

Host genetic modifiers of nonproductive angiogenesis inhibit breast cancer.

PURPOSE: Multiple aspects of the tumor microenvironment (TME) impact breast cancer, yet the genetic modifiers of the TME are largely unknown, including those that modify tumor vascular formation and function. METHODS: To discover host TME modifiers, we developed a system called the Consomic/Congenic Xenograft Model (CXM). In CXM, human breast cancer cells are orthotopically implanted into genetically engineered consomic xenograft host strains that are derived from two parental strains with different susceptibilities to breast cancer. Because the genetic backgrounds of the xenograft host strains differ, whereas the inoculated tumor cells are the same, any phenotypic variation is due to TME-specific modifier(s) on the substituted chromosome (consomic) or subchromosomal region (congenic). Here, we assessed TME modifiers of growth, angiogenesis, and vascular function of tumors implanted in the SSIL2Rγ and SS.BN3IL2Rγ CXM strains. RESULTS: Breast cancer xenografts implanted in SS.BN3IL2Rγ (consomic) had significant tumor growth inhibition compared with SSIL2Rγ (parental control), despite a paradoxical increase in the density of blood vessels in the SS.BN3IL2Rγ tumors. We hypothesized that decreased growth of SS.BN3IL2Rγ tumors might be due to nonproductive angiogenesis. To test this possibility, SSIL2Rγ and SS.BN3IL2Rγ tumor vascular function was examined by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), micro-computed tomography (micro-CT), and ex vivo analysis of primary blood endothelial cells, all of which revealed altered vascular function in SS.BN3IL2Rγ tumors compared with SSIL2Rγ. Gene expression analysis also showed a dysregulated vascular signaling network in SS.BN3IL2Rγ tumors, among which DLL4 was differentially expressed and co-localized to a host TME modifier locus (Chr3: 95-131 Mb) that was identified by congenic mapping. CONCLUSIONS: Collectively, these data suggest that host genetic modifier(s) on RNO3 induce nonproductive angiogenesis that inhibits tumor growth through the DLL4 pathway.