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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Structure-Based Discovery of 4-(6-Methoxy-2-methyl-4-(quinolin-4-yl)-9 H -pyrimido[4,5- b ]indol-7-yl)-3,5-dimethylisoxazole (CD161) as a Potent and Orally Bioavailable BET Bromodomain Inhibitor

We have designed and synthesized 9H-pyrimido[4,5-b]indole-containing compounds to obtain potent and orally bioavailable BET inhibitors. By incorporation of an indole or a quinoline moiety to the 9H-pyrimido[4,5-b]indole core, we identified a series of small molecules showing high binding affinities to BET proteins and low nanomolar potencies in inhibition of cell growth in acute leukemia cell lines. One such compound, 4-(6-methoxy-2-methyl-4-(quinolin-4-yl)-9H-pyrimido[4,5-b]indol-7-yl)-3,5-dimethylisoxazole (31) has excellent microsomal stability and good oral pharmacokinetics in rats and mice. Orally administered, 31 achieves significant antitumor activity in the MV4;11 leukemia and MDA-MB-231 triple-negative breast cancer xenograft models in mice. Determination of the cocrystal structure of 31 with BRD4 BD2 provides a structural basis for its high binding affinity to BET proteins. Testing its binding affinities against other bromodomain-containing proteins shows that 31 is a highly selective inhibitor of BET proteins. Here, our data show that 31 is a potent, selective, and orally active BET inhibitor.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

AI-enabled, implantable, multichannel wireless telemetry for photodynamic therapy

Photodynamic therapy (PDT) offers several advantages for treating cancers, but its efficacy is highly dependent on light delivery to activate a photosensitizer. Advances in wireless technologies enable remote delivery of light to tumors, but suffer from key limitations, including low levels of tissue penetration and photosensitizer activation. Here, we introduce DeepLabCut (DLC)-informed low-power wireless telemetry with an integrated thermal/light simulation platform that overcomes the above constraints. The simulator produces an optimized combination of wavelengths and light sources, and DLC-assisted wireless telemetry uses the parameters from the simulator to enable adequate illumination of tumors through high-throughput (<20 mice) and multi-wavelength operation. Together, they establish a range of guidelines for effective PDT regimen design. In vivo Hypericin and Foscan mediated PDT, using cancer xenograft models, demonstrates substantial suppression of tumor growth, warranting further investigation in research and/or clinical settings.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Silica bioreplication preserves three-dimensional spheroid structures of human pluripotent stem cells and HepG2 cells

Three-dimensional (3D) cell cultures produce more in vivo-like multicellular structures such as spheroids that cannot be obtained in two-dimensional (2D) cell cultures. Thus, they are increasingly employed as models for cancer and drug research, as well as tissue engineering. It has proven challenging to stabilize spheroid architectures for detailed morphological examination. Here we overcome this issue using a silica bioreplication (SBR) process employed on spheroids formed from human pluripotent stem cells (hPSCs) and hepatocellular carcinoma HepG2 cells cultured in the nanofibrillar cellulose (NFC) hydrogel. The cells in the spheroids are more round and tightly interacting with each other than those in 2D cultures, and they develop microvilli-like structures on the cell membranes as seen in 2D cultures. Furthermore, SBR preserves extracellular matrix-like materials and cellular proteins. In conclusion, these findings provide the first evidence of intact hPSC spheroid architectures and similar fine structures to 2D-cultured cells, providing a pathway to enable our understanding of morphogenesis in 3D cultures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Novel technologies and theoretical models in radiation therapy of cancer patients using 6.3 MeV fast neutrons produced by U-120 cyclotron

The analysis of clinical use of neutron therapy with 6 MeV fast neutrons compared to conventional radiation therapy was carried out. The experience of using neutron and mixed neutron and photon therapy in patients with different radio-resistant malignant tumors shows the necessity of further studies and development of the novel approaches to densely-ionizing radiation. The results of dosimetry and radiobiological studies have been the basis for planning clinical programs for neutron therapy. Clinical trials over the past 30 years have shown that neutron therapy successfully destroys radio-resistant cancers, including salivary gland tumors, adenoidcystic carcinoma, inoperable sarcomas, locally advanced head and neck tumors, and locally advanced prostate cancer. Radiation therapy with 6.3 MeV fast neutrons used alone and in combination with photon therapy resulted in improved long-term treatment outcomes in patients with radio-resistant malignant tumors.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Targeted inhibition of gut bacterial β-glucuronidase activity enhances anticancer drug efficacy

Irinotecan treats a range of solid tumors, but its effectiveness is severely limited by gastrointestinal (GI) tract toxicity caused by gut bacterial β-glucuronidase (GUS) enzymes. Targeted bacterial GUS inhibitors have been shown to partially alleviate irinotecan-induced GI tract damage and resultant diarrhea in mice. Here, we unravel the mechanistic basis for GI protection by gut microbial GUS inhibitors using in vivo models. We use in vitro, in fimo, and in vivo models to determine whether GUS inhibition alters the anticancer efficacy of irinotecan. We demonstrate that a single dose of irinotecan increases GI bacterial GUS activity in 1 d and reduces intestinal epithelial cell proliferation in 5 d, both blocked by a single dose of a GUS inhibitor. In a tumor xenograft model, GUS inhibition prevents intestinal toxicity and maintains the antitumor efficacy of irinotecan. Remarkably, GUS inhibitor also effectively blocks the striking irinotecan-induced bloom of Enterobacteriaceae in immune-deficient mice. In a genetically engineered mouse model of cancer, GUS inhibition alleviates gut damage, improves survival, and does not alter gut microbial composition; however, by allowing dose intensification, it dramatically improves irinotecan’s effectiveness, reducing tumors to a fraction of that achieved by irinotecan alone, while simultaneously promoting epithelial regeneration. These results indicate that targeted gut microbial enzyme inhibitors can improve cancer chemotherapeutic outcomes by protecting the gut epithelium from microbial dysbiosis and proliferative crypt damage.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

BioMart Central Portal: an open database network for the biological community

BioMart Central Portal is a first of its kind, community-driven effort to provide unified access to dozens of biological databases spanning genomics, proteomics, model organisms, cancer data, ontology information and more. Anybody can contribute an independently maintained resource to the Central Portal, allowing it to be exposed to and shared with the research community, and linking it with the other resources in the portal. Users can take advantage of the common interface to quickly utilize different sources without learning a new system for each. The system also simplifies cross-database searches that might otherwise require several complicated steps. Several integrated tools streamline common tasks, such as converting between ID formats and retrieving sequences. The combination of a wide variety of databases, an easy-to-use interface, robust programmatic access and the array of tools make Central Portal a one-stop shop for biological data querying. Here, we describe the structure of Central Portal and show example queries to demonstrate its capabilities. Database URL: http://central.biomart.org.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

The BioMart community portal: an innovative alternative to large, centralized data repositories

The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

SU-C-207B-06: Comparison of Registration Methods for Modeling Pathologic Response of Esophageal Cancer to Chemoradiation Therapy

Purpose: To compare linear and deformable registration methods for evaluation of tumor response to Chemoradiation therapy (CRT) in patients with esophageal cancer. Methods: Linear and multi-resolution BSpline deformable registration were performed on Pre-Post-CRT CT/PET images of 20 patients with esophageal cancer. For both registration methods, we registered CT using Mean Square Error (MSE) metric, however to register PET we used transformation obtained using Mutual Information (MI) from the same CT due to being multi-modality. Similarity of Warped-CT/PET was quantitatively evaluated using Normalized Mutual Information and plausibility of DF was assessed using inverse consistency Error. To evaluate tumor response four groups of tumor features were examined: (1) Conventional PET/CT e.g. SUV, diameter (2) Clinical parameters e.g. TNM stage, histology (3)spatial-temporal PET features that describe intensity, texture and geometry of tumor (4)all features combined. Dominant features were identified using 10-fold cross-validation and Support Vector Machine (SVM) was deployed for tumor response prediction while the accuracy was evaluated by ROC Area Under Curve (AUC). Results: Average and standard deviation of Normalized mutual information for deformable registration using MSE was 0.2±0.054 and for linear registration was 0.1±0.026, showing higher NMI for deformable registration. Likewise for MI metric, deformable registration had 0.13±0.035 comparing to linear counterpart with 0.12±0.037. Inverse consistency error for deformable registration for MSE metric was 4.65±2.49 and for linear was 1.32±2.3 showing smaller value for linear registration. The same conclusion was obtained for MI in terms of inverse consistency error. AUC for both linear and deformable registration was 1 showing no absolute difference in terms of response evaluation. Conclusion: Deformable registration showed better NMI comparing to linear registration, however inverse consistency of transformation was lower in linear registration. We do not expect to see significant difference when warping PET images using deformable or linear registration. This work was supported in part by the National Cancer Institute Grants R01CA172638.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-TeP3-03: Dose Enhancement of Gold Nanoparticle in Proton Therapy: A Monte Carlo Study Based On the Transmission Electron Microscopy Imaging

Purpose: Gold nanoparticle (GNP) is a promising radiosensitizer that selectively boosts tumor dose in radiotherapy. Transmission electron microscopy (TEM) imaging observations recently revealed for the first time that GNP exists in vivo in the form of highly localized vesicles, instead of hypothetical uniform distribution. This work investigates the corresponding difference of energy deposition in proton therapy. Methods: First, single vesicles of various radii were constructed by packing GNPs (as Φ50 nm gold spheres) in spheres and were simulated, as well as a single GNP. The radial energy depositions (REDs) were scored using 100 concentric spherical shells from 0.1µm to 10µm, 0.1µm thickness each, for both vesicles and GNP, and compared. TEM images, 8 days after injection in a PC3 prostate cancer murine model, were used to extract position/dimension of vesicles, as well as contours of cytoplasmic and nucleus membranes. Vesicles were then constructed based on the TEM images. A 100 MeV proton beam was studied by using the Geant4-DNA code, which simulates all energy deposition events. Results: The vesicle REDs, normalized to the same proton energy loss as in a single GNP, are larger (smaller) than that of a single GNP when radius >2µm (<2µm). The peak increase (at about 3µm radius) is about 10% and 18% for Φ1µm and Φ1.6µm vesicles respectively, relative to a single GNP. The TEM-based simulation resulted in a larger energy deposition (by about one order of magnitude) that follows completely different pattern from that of hypothetical GNP distributions (regular dotted pattern in extracellular and/or extranucleus regions). Conclusion: The in vivo energy deposition, both in pattern and magnitude, of proton therapy is greatly affected by the true distribution of the GNP, as illustrated by the presence of GNP vesicles compared to hypothetical scenarios. Work supported by NSERC Discovery Grant #435510, Canada.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Modeling precision treatment of breast cancer

Background: First-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets. Results: We used least squares-support vector machines and random forest algorithms to identify molecular features associated with responses of a collection of 70 breast cancer cell lines to 90 experimental or approved therapeutic agents. The datasets analyzed included measurements of copy number aberrations, mutations, gene and isoform expression, promoter methylation and protein expression. Transcriptional subtype contributed strongly to response predictors for 25% of compounds, and adding other molecular data types improved prediction for 65%. No single molecular dataset consistently out-performed the others, suggesting that therapeutic response is mediated at multiple levels in the genome. Response predictors were developed and applied to TCGA data, and were found to be present in subsets of those patient samples. Conclusions: These results suggest that matching patients to treatments based on transcriptional subtype will improve response rates, and inclusion of additional features from other profiling data types may provide additional benefit. Further, we suggest a systems biology strategy for guiding clinical trials so that patient cohorts most likely to respond to new therapies may be more efficiently identified.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Open questions: The disrupted circuitry of the cancer cell

Every new decade of biology brings with it a change in outlook driven by new technologies and fresh perspectives. Such is the case for cancer and how we consider the disease. The advent of molecular biology led to the identification of altered signaling molecules and 'oncogenes' that were proposed to drive uncontrolled cell proliferation. The rise of cell biology and new imaging and culturing technologies led to the idea that disruptions in the extracellular environment prime cells for transformation. In the current genomics era, cancer is most commonly seen as a genetic disorder where an unstable genome gives rise to a variety of different cell variants that are selected for proliferation and survival. All of these views are partially correct, of course, and are simply different ways of saying that genetic alterations in cancer cells result in a loss of growth homeostasis. They also take the view that molecular changes 'drive' a cell to grow uncontrollably, rather than tip the balance from one normal state (quiescence) to another (proliferation). Underlying this oversimplification is a profound ignorance of what controls homeostatic cell growth in the first place and how specific mutations impact it.

cancer↗
DOE OSTI2024

Exposed Phosphatidylserine as a Biomarker for Clear Identification of Breast Cancer Brain Metastases in Mouse Models

Brain metastasis is the most common intracranial malignancy in adults. The prognosis is extremely poor, partly because most patients have more than one brain lesion, and the currently available therapies are nonspecific or inaccessible to those occult metastases due to an impermeable blood–tumor barrier (BTB). Phosphatidylserine (PS) is externalized on the surface of viable endothelial cells (ECs) in tumor blood vessels. In this study, we have applied a PS-targeting antibody to assess brain metastases in mouse models. Fluorescence microscopic imaging revealed that extensive PS exposure was found exclusively on vascular ECs of brain metastases. The highly sensitive and specific binding of the PS antibody enables individual metastases, even micrometastases containing an intact BTB, to be clearly delineated. Furthermore, the conjugation of the PS antibody with a fluorescence dye, IRDye 800CW, or a radioisotope, 125I, allowed the clear visualization of individual brain metastases by optical imaging and autoradiography, respectively. In conclusion, we demonstrated a novel strategy for targeting brain metastases based on our finding that abundant PS exposure occurs on blood vessels of brain metastases but not on normal brain, which may be useful for the development of imaging and targeted therapeutics for brain metastases.

Oncology↗
NASA NTRS2018

Track Structure and the Quality Factor for Space Radiation Cancer Risk

A major risk from exposure to space radiation is the induction of cancer and it is from estimates of this risk that the maximum career flight times of NASA space crew members are restricted by a permissible exposure limit. For the purpose of demonstrating compliance with the career limit, NASA has developed a cancer risk projection model for exposure-induced fatal cancer, in which the formulation and numerical values of the quality factor (QFNASA) are substantially different from those of the quality factor (Q) or radiation weighting factor (wR) routinely applied for radiation protection on earth. The quality factor is used to account for the increased effectiveness of radiations of high linear energy transfer (LET), compared to the effectiveness of low-LET γ-rays derived from epidemiological studies of the atomic-bomb survivors. The need for a special approach for space radiation is dictated by the special characteristics of the charged particles from solar radiation and especially the charged particles of high energy and charge (HZE) in galactic cosmic rays (GCR). This article considers aspects of radiation track structure in relation to the relative biological effectiveness (RBE) of HZE particles and the quality factor used for space radiation. The NASA quality factor (QFNASA) is composed of two terms, which can be interpreted as broadly representing the low- and the high-ionization-density components of the HZE particle tracks. These are discussed in turn as they relate to available experimental evidence on the biological effectiveness of such components. Also briefly described are subsequent published proposals for a reformulation of the quality factor to relate more directly to the acute γ-ray exposures from the atomic bombs and for further refinement of the parameter values (and their uncertainties) that determine the shape of the quality factor function. Other recent developments are also mentioned.

Mullenax, Carol A.↗
DOE OSTI2014

Effect of Antigen Shedding on Targeted Delivery of Immunotoxins in Solid Tumors from a Mathematical Model

Most cancer-specific antigens used as targets of antibody-drug conjugates and immunotoxins are shed from the cell surface (Zhang & Pastan (2008) Clin. Cancer Res. 14: 7981-7986), although at widely varying rates and by different mechanisms (Dello Sbarba & Rovida (2002) Biol. Chem. 383: 69–83). Why many cancer-specific antigens are shed and how the shedding affects delivery efficiency of antibody-based protein drugs are poorly understood questions at present. Before a detailed numerical study, it was assumed that antigen shedding would reduce the efficacy of antibody-drug conjugates and immunotoxins. However, our previous study using a comprehensive mathematical model showed that antigen shedding can significantly improve the efficacy of the mesothelin-binding immunotoxin, SS1P (anti-mesothelin-Fv-PE38), and suggested that receptor shedding can be a general mechanism for enhancing the effect of inter-cellular signaling molecules. Here, we improved this model and applied it to both SS1P and another recombinant immunotoxin, LMB-2, which targets CD25. We show that the effect of antigen shedding is influenced by a number of factors including the number of antigen molecules on the cell surface and the endocytosis rate. The high shedding rate of mesothelin is beneficial for SS1P, for which the antigen is large in number and endocytosed rapidly. On the other hand, the slow shedding of CD25 is beneficial for LMB-2, for which the antigen is small in number and endocytosed slowly.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-D-207B-07: Development of a CT-Radiomics Based Early Response Prediction Model During Delivery of Chemoradiation Therapy for Pancreatic Cancer

Purpose: Pilot study developing a CT-texture based model for early assessment of treatment response during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Methods: Daily CT data acquired for 24 pancreatic head cancer patients using CT-on-rails, during the routine CT-guided CRT delivery with a radiation dose of 50.4 Gy in 28 fractions, were analyzed. The pancreas head was contoured on each daily CT. Texture analysis was performed within the pancreas head contour using a research tool (IBEX). Over 1300 texture metrics including: grey level co-occurrence, run-length, histogram, neighborhood intensity difference, and geometrical shape features were calculated for each daily CT. Metric-trend information was established by finding the best fit of either a linear, quadratic, or exponential function for each metric value verses accumulated dose. Thus all the daily CT texture information was consolidated into a best-fit trend type for a given patient and texture metric. Linear correlation was performed between the patient histological response vector (good, medium, poor) and all combinations of 23 patient subgroups (statistical jackknife) determining which metrics were most correlated to response and repeatedly reliable across most patients. Control correlations against CT scanner, reconstruction kernel, and gated/nongated CT images were also calculated. Euclidean distance measure was used to group/sort patient vectors based on the data of these trend-response metrics. Results: We found four specific trend-metrics (Gray Level Coocurence Matrix311-1InverseDiffMomentNorm, Gray Level Coocurence Matrix311-1InverseDiffNorm, Gray Level Coocurence Matrix311-1 Homogeneity2, and Intensity Direct Local StdMean) that were highly correlated with patient response and repeatedly reliable. Our four trend-metric model successfully ordered our pilot response dataset (p=0.00070). We found no significant correlation to our control parameters: gating (p=0.7717), scanner (p=0.9741), and kernel (p=0.8586). Conclusion: We have successfully created a CT-texture based early treatment response prediction model using the CTs acquired during the delivery of chemoradiation therapy for pancreatic cancer. Future testing is required to validate the model with more patient data.

60 APPLIED LIFE SCIENCES↗