Search

Colorectal cancer (CRC) has one of the highest cancer incidences and mortality rates. In stage III, postoperative chemotherapy benefits

Background Peripheral nerve reflexes enable organ systems to maintain long-term physiological homeostasis while responding to rapidly changing environmental conditions. Electrical nerve stimulation is commonly used to activate these reflexes and modulate organ function, giving rise to an emerging class of therapeutics called bioelectronic medicines. Dogma maintains that immune cell migration to and from organs is mediated by inflammatory signals (i.e. cytokines or pathogen associated signaling molecules). However, nerve reflexes that regulate immune function have only recently been elucidated, and stimulation of these reflexes for therapeutic effect has not been fully investigated. Methods We utilized both electrical and ultrasound-based nerve stimulation to activate nerve pathways projecting to specific lymph nodes. Tissue and cell analysis of the stimulated lymph node, distal lymph nodes and immune organs is then utilized to measure the stimulation-induced changes in neurotransmitter/neuropeptide concentrations and immune cellularity in each of these sites. Results and conclusions In this report, we demonstrate that activation of nerves and stimulated release of neurotransmitters within a local lymph node results in transient retention of immune cells (e.g. lymphocytes and neutrophils) at that location. Furthermore, such stimulation results in transient changes in neurotransmitter concentrations at distal organs of the immune system, spleen and liver, and mobilization of immune cells into the circulation. This report will enable future studies in which stimulation of these long-range nerve connections between lymphatic and immune organs can be applied for clinical purpose, including therapeutic modulation of cellularity during vaccination, active allergic response, or active auto-immune disease.

Cancer cells’ ability to inhibit apoptosis is key to malignant transformation and limits response to therapy. Here, we performed multiplexed immunofluorescence analysis on tissue microarrays with 373 cores from 168 patients, segmentation of 2.4 million individual cells, and quantification of 18 cell lineage and apoptosis proteins. We identified an enrichment for BCL2 in immune, and BAK, SMAC, and XIAP in cancer cells. Ordinary differential equation-based modeling of apoptosis sensitivity at single-cell resolution was conducted and an atlas of inter- and intra-tumor heterogeneity in apoptosis susceptibility generated. Systems modeling at single-cell resolution identified an enhanced sensitivity of cancer cells to mitochondrial permeabilization and executioner caspase activation compared to immune and stromal cells, but showed significant inter- and intra-tumor heterogeneity.

Motivation Multiplexed immunofluorescence bioimaging of single-cells and their spatial organization in tissue holds great promise to the development of future precision diagnostics and therapeutics. Current multiplexing pipelines typically involve multiple rounds of immunofluorescence staining across multiple tissue slides. This introduces experimental batch effects that can hide underlying biological signal. It is important to have robust algorithms that can correct for the batch effects while not introducing biases into the data. Performance of data normalization methods can vary among different assay pipelines. To evaluate differences, it is critical to have a ground truth dataset that is representative of the assay. Results A new immunoFLuorescence Image NOrmalization method is presented and evaluated against alternative methods and workflows. Multiround immunofluorescence staining of the same tissue with the nuclear dye DAPI was used to represent virtual slides and a ground truth. DAPI was restained on a given tissue slide producing multiple images of the same underlying structure but undergoing multiple representative tissue handling steps. This ground truth dataset was used to evaluate and compare multiple normalization methods including median, quantile, smooth quantile, median ratio normalization and trimmed mean of the M-values. These methods were applied in both an unbiased grid object and segmented cell object workflow to 24 multiplexed biomarkers. An upper quartile normalization of grid objects in log space was found to obtain almost equivalent performance to directly normalizing segmented cell objects by the middle quantile. The developed grid-based technique was then applied with on-slide controls for evaluation. Using five or fewer controls per slide can introduce biases into the data. Ten or more on-slide controls were able to robustly correct for batch effects. Availability and implementation The data underlying this article along with the FLINO R-scripts used to perform the evaluation of image normalizations methods and workflows can be downloaded from https://github.com/GE-Bio/FLINO. Supplementary information Supplementary data are available at Bioinformatics online.

While peripheral glucose sensors are known to relay signals of substrate availability to integrative nuclei in the brain, the importance of these pathways in maintaining energy homeostasis and their contribution to disease remain unknown. Herein, we demonstrate that selective activation of the hepatoportal neural plexus via transient peripheral focused ultrasound (pFUS) induces glucose homeostasis in models of well-established insulin resistant diabetes. pFUS modulates sensory projections to the hindbrain and alters hypothalamic concentrations of neurotransmitters that regulate metabolism, resulting in potentiation of hypothalamic insulin signaling, leptin-independent inhibition of the orexigenic neuropeptide Y system, and therapeutic alteration in autonomic output to peripheral effector organs. Multiomic profiling confirms pFUS-induced modifications of key metabolic functions in liver, pancreas, muscle, adipose, kidney, and intestines. Activation of the hepatic nutrient sensing pathway not only restores nervous system coordination of peripheral metabolism in three different species but does so across these organ systems; several of which are current targets of antidiabetic drug classes. These results demonstrate the potential of hepatic pFUS as a novel/non-pharmacologic therapeutic modality to restore glucose homeostasis in metabolic diseases, including type II diabetes.One Sentence SummaryWe utilize a non-invasive ultrasound technique to activate a liver-brain sensory pathway and demonstrate its potential to induce durable normalization of glucose homeostasis in models of well-established insulin resistant diabetes.

Colorectal cancer (CRC) has one of the highest cancer incidences and mortality rates. In stage III, postoperative chemotherapy benefits in situ multiplexed immunofluorescence imaging and single cell analysis technology (Cell DIVE™). Tissue microarrays (TMAs) with up to three 1mm diameter cores per patient were prepared from 117 stage III CRC patients treated with adjuvant fluoropyrimidine/oxaliplatin chemotherapy. Single sections underwent multilplexed immunofluorescence with Cy3- and Cy5-conjugated antibodies for immune cell markers (CD45, CD3, CD4, CD8, FOXP3, PD1) and cell segmentation markers (DAPI, pan-cytokeratin, AE1, NaKATPase and S6). We applied a probabilistic multi-class, multi-label classification algorithm based on multi-parametric models to build statistical models of protein expression to classify immune cells. Expert annotations of immune cell markers were made on a range of images, and Support Vector Machines (SVM) were used to derive a statistical model for cell classification. Images were also manually scored independently by a Pathologist as ‘high’, ‘moderate’ or ‘low’, for stromal and total immune cell content. Excellent agreement was found between manual and total automated scores (p

Hyperinflammation and uncontrolled cytokine release, which can be seen in severe cases of COVID-19, require therapy to reduce the innate immune response without hindering necessary adaptive immune mechanisms. Here, we show results from the first in-human trials using non-invasive ultrasound stimulation of the spleen to reduce cytokine release in the context of both an acute response in healthy subjects and a chronic inflammatory condition in rheumatoid arthritis patients. Splenic ultrasound results in a reduction in TNF serum levels, as well as IL-1β and IL-8 transcript levels in monocytes. There is also a down regulation of pathways involved in TNF and IL-6 production, and IFNγ- and NFκB-regulated genes. Many of these cytokines or pathways are upregulated in COVID-19 patients. There is also a reduction in chemokine transcript levels and other components of the chemotactic response, suggesting that reduction of cellular migration may contribute to the therapeutic effects of ultrasound. There is no inhibition of the adaptive immune response with ultrasound treatment relating to antibody production. This is consistent with a pre-clinical animal model where enhanced antibody production was achieved with splenic ultrasound. Therefore, this new splenic ultrasound approach has the potential to treat acute and chronic hyper-inflammatory diseases, as it lowers cytokine levels without disrupting the normal adaptive immune response. Portable ultrasound technologies are currently being developed and translated to the clinic to treat various inflammatory disorders, with more recent efforts directed towards combatting the hyperinflammation or ‘cytokine storm’ in COVID-19 patients.

Immunotherapies (IT) require induction, expansion, and maintenance of specific changes to a patient's immune cell repertoire which yield a therapeutic benefit. Recently, mechanistic understanding of these changes at the cellular level has revealed that IT results in complex phenotypic transitions in target cells, and that therapeutic effectiveness may be predicted by monitoring these transitions during therapy. However, monitoring will require unique tools that enable capture, manipulation, and profiling of rare immune cell populations. In this study, we introduce a method of automated and unsupervised separation and processing of rare immune cells, using high-force and multidimensional magnetic ratcheting (MR). We demonstrate capture of target immune cells using samples with up to 1 : 10 000 target cell to background cell ratios from input volumes as small as 25 microliters (i.e. a low volume and low cell frequency sample sparing assay interface). Cell capture is shown to achieve up to 90% capture efficiency and purity, and captured cell analysis is shown using both on-chip culture/activity assays and off-chip ejection and nucleic acid analysis. These results demonstrate that multi-directional magnetic ratcheting offers a unique separation system for dealing with blood cell samples that contain either rare cells or significantly small volumes, and the "sample sparing" capability leads to an expanded spectrum of parameters that can be measured. These tools will be paramount to advancing techniques for immune monitoring under conditions in which both the sample volume and number of antigen-specific target cells are often exceedingly small, including during IT and treatment of allergy, asthma, autoimmunity, immunodeficiency, cell based therapy, transplantation, and infection.

Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated multiplexed immunofluorescence single cell data for 43 protein markers across cancer hallmarks, in addition to cell spatial metrics, genomic sequencing and magnetic resonance imaging (MRI) quantitative features. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion differ between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. Longer overall survival for IDH1mt glioma patients may reflect generalized altered cellular, molecular, spatial heterogeneity which manifest in discernable radiological manifestations.

A new study published in Nature Communications outlines our group's results using focused ultrasound stimulation within peripheral organs to precisely activate autonomic nerve circuits. The concept is demonstrated by modulating two different (and potentially therapeutic) targets in animal models, a neuroimmune connection in the spleen (that modulates blood cytokine concentrations) and a nutrient sensory pathway within the liver (that modulates metabolism). Connected to this work is a companion Nature Communications publication that utilizes an ultrasound stimulus focused on the spleen to reduce disease severity in a serum-transferred rodent model of inflammatory arthritis. These reports highlight the growing evidence that ultrasound energy (previously shown to enable activation or modulation of central nervous system pathways) may be used to perform peripheral neuromodulation. In this commentary, we highlight the main findings and discuss their implications for new forms of ultrasound-based therapy. Though challenges remain, a new noninvasive method for precision neuromodulation could solve many of the challenges facing the nascent field of bioelectronic medicine. That is, the use of ultrasound to directly modulate neurophysiological systems therapeutically may provide alternatives to traditional pharmaceuticals. However, to alter the current pharmaceutical paradigm, the field will need to develop a new understanding of how traditional drug concepts (such as dose and pharmacokinetics-pharmacodynamics) relate to the parameters, protocols, and outcomes of this new stimulation technology.

Colorectal cancer (CRC) has one of the highest Worldwide incidences and mortality rates. Genotoxic chemotherapy following surgery in stage III patients confers treatment benefit to less than 20% of the patients, with more than 50% of stage III patients going on to develop distant metastases. Currently, there are no predictive biomarkers that can identify which stage III patients will recur, which patients will benefit from chemotherapy and which should be redirected towards alternative therapeutic interventions. A major challenge in identifying such a universal biomarker is that CRC is a heterogeneous disease with multiple subtypes. In the current study, we assessed clinically-relevant immune cell populations in the tumour microenvironment (TME) of stage III tumours using a novel hyperplex in situ immunofluorescence imaging technology (Cell DIVETM, GE Healthcare, Issaquah, WA). Tissue microarrays (TMAs) with up to three 1mm diameter cores per patient were prepared from 139 stage III CRC patients treated with adjuvant FOLFOX chemotherapy. Single sections (5 µm) were iteratively stained with Cy3- and Cy5-conjugated antibodies for immune cell markers as well as markers of cell death and metabolism. The images underwent illumination correction, DAPI-based registration and autofluorescence removal. After image quality control corrections, single cell segmentation was performed using a combination of DAPI [nuclear], pan-cytokeratin [epithelial], NaKATPase [membrane] and S6 [cytoplasmic] segmentation markers and an average of ~3,000 stromal cells and ~ 4,000 epithelial were segmented per tumour core. A machine learning-based algorithm for immune cell classification and quantification was used to analyse the immune markers CD45, CD3, CD4, CD8, FOXP3 and PD1 to identify: cytotoxic T cells, T helper cells, regulatory T cells and potential relevance of immune checkpoint therapy. In the tumour tissues, the median proportion of CD3+ segmented cells was ~8%. Classified immune cells were counted within epithelial and stromal regions, with patients categorised as Low, Intermediate and High (based on 75th percentile, respectively) for each cell type. Preliminary survival analyses show that patients with ‘CD8 High' intratumoural cytotoxic T cells have better Disease-Free Survival compared to ‘CD8 Low' patients in this FOLFOX-treated cohort. By combining single-cell data with clinicopathological patient data, we aim to identify immune-, cell death- and metabolism-related signatures that can predict benefit from adjuvant FOLFOX chemotherapy for Stage III CRC patients. Citation Format: Xanthi Stachtea, Andreas Lindner, Manuela Salvucci, Sanghee Cho, Anup Sood, Elizabeth McDonough, Alberto Santamaria-Pang, John Graf, Philip Dunne, Mark Lawler, Jochen Prehn, Fiona Ginty, Daniel Longley. Hyperplexed immunofluorescence analysis (Cell DIVETM) of immune-related tumor heterogeneity in stage III colorectal cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2676.

Background A fundamental limit to the study of the peripheral nervous system and its effect on organ function is the lack of tools to selectively target and stimulate specific neurons. Traditional implant and electrode-based systems remain too large and invasive for use at the organ or sub-organ level (without stimulating or effecting neighboring organs and tissues). Recent progress in optical and genetic tools (such as optogenetics) has provided a new level of molecular specificity and selectivity to the neurons that are stimulated by bioelectronic devices. However, the modified neurons that result from use of these tools (that can be selectively activated based on expression of light, heat, or stimuli sensitive ion channels) often still require stimulation by implantable devices and face difficult scientific, technical, and regulatory hurdles for clinical translation. New Method Herein, we present a new tool for selective activation of neuronal pathways using anatomical site-specific, peripheral focused ultrasound neuromodulation (pFUS). Results We utilize three experimental models to expand upon and further characterize pFUS beyond data outlined to our initial report (Cotero et al., 2019a), and further demonstrate its importance as a new investigative and translational tool. First, we utilized an interconnected microporous gel scaffold to culture isolated dorsal root ganglion (DRG) neurons in an interconnected, three-dimensional in vitro culture. (Griffin et al., 2015, Tay et al., 2018) Using this system, we directly applied ultrasound (US) stimuli and confirmed US activation of peripheral neurons at pressures consistent with recent in vivo observations. (Cotero et al., 2019a, Zachs, 2019, Gigliotti et al., 2013) Next, we tested the capability of pFUS to activate previously reported nerve pathways at multiple locations within the neural circuit, including primary sensory ganglia (i.e. inferior ganglion of the vagus nerve), peripheral ganglia (i.e. sacral ganglia), and within target end-organs. In addition, we compared selective activation of multiple anatomically overlapping neural pathways (i.e. activation of the cholinergic anti-inflammatory pathway (Tracey, 2009, Pavlov and Tracey, 2012) vs. metabolic sensory pathways (O’Hare and Zsombok, 2015, Roh et al., 2016, Pocai et al., 2005) after stimulation of each separate target site. Finally, we utilized an established model of metabolic dysfunction (the LPS-induced inflammation/hyperglycemia model) to demonstrate pFUS capability to stimulate and assess alternative therapeutic stimulation sites (i.e. liver, pancreas, and intestines) in a simple and clinically relevant manner. This is demonstrated by ultrasound induced attenuation of LPS-induced hyperglycemia by stimulation at all three anatomical targets, and mapping of the effect to a specific molecular product of excitable cell types within each stimulus site. Comparison with existing methods The ease-of-use and non-invasive nature of pFUS provides a solution to many of the challenges facing traditional toolsets, such as implantable electrodes and genetic/optogenetic nerve stimulation strategies. Conclusions The pFUS tool described herein provides a fundamental technology for the future study and manipulation of the peripheral nervous and neuroendocrine systems.

Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated data from protein, genomic and MR imaging from 20 treatment-naïve glioma cases and 16 recurrent GBM cases. Multiplexed immunofluorescence (MxIF) was used to generate single cell data for 43 protein markers representing all cancer hallmarks, Genomic sequencing (exome and RNA (normal and tumor) and magnetic resonance imaging (MRI) quantitative features (protocols were T1-post, FLAIR and ADC) from whole tumor, peritumoral edema and enhancing core vs equivalent normal region were also collected from patients. Based on MxIF analysis, 85,767 cells (glioma cases) and 56,304 cells (GBM cases) were used to generate cell-level data for 24 biomarkers. K-means clustering was used to generate 7 distinct groups of cells with divergent biomarker profiles and deconvolution was used to assign RNA data into three classes. Spatial and molecular heterogeneity metrics were generated for the cell data. All features were compared between IDH mt and IDHwt patients and were finally combined to provide a holistic/integrated comparison. Protein expression by hallmark was generally lower in the IDHmt vs wt patients. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion also differed between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. A coherent picture of enhanced angiogenesis in IDHwt tumors was derived from multiple platforms (genomic, proteomic and imaging) and scales from individual proteins to cell clusters and heterogeneity, as well as bulk tumor RNA and imaging features. Longer overall survival for IDH1mt glioma patients may reflect mutation-driven alterations in cellular, molecular, and spatial heterogeneity which manifest in discernable radiological manifestations.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Tools for noninvasively modulating neural signaling in peripheral organs will advance the study of nerves and their effect on homeostasis and disease. Herein, we demonstrate a noninvasive method to modulate specific signaling pathways within organs using ultrasound (U/S). U/S is first applied to spleen to modulate the cholinergic anti-inflammatory pathway (CAP), and US stimulation is shown to reduce cytokine response to endotoxin to the same levels as implant-based vagus nerve stimulation (VNS). Next, hepatic U/S stimulation is shown to modulate pathways that regulate blood glucose and is as effective as VNS in suppressing the hyperglycemic effect of endotoxin exposure. This response to hepatic U/S is only found when targeting specific sub-organ locations known to contain glucose sensory neurons, and both molecular (i.e. neurotransmitter concentration and cFOS expression) and neuroimaging results indicate US induced signaling to metabolism-related hypothalamic sub-nuclei. These data demonstrate that U/S stimulation within organs provides a new method for site-selective neuromodulation to regulate specific physiological functions., Stimulation of peripheral nerve activity may be used to treat metabolic and inflammatory disorders, but current approaches need implanted devices. Here, the authors present a non-invasive approach, and show that ultrasound-mediated stimulation can be targeted to specific sub-organ locations in preclinical models and alter the response of metabolic and inflammatory neural pathways.

This chapter aims to establish a relationship between direct experimental measurements of the hydrogen bonded species present and the contribution of such interactions to the free energy of mixing. Equilibrium constants provide a direct link between stoichiometry, experimental infrared spectroscopic measurements and the free energy of mixing. The chapter provides mixtures of two different types of molecules that each self associate and, in principle, could then form "mixed" chains, each consisting of a distribution of various hydrogen bonded groups analogous to the various distributions found in (covalent) statistical copolymers. It focuses on a chemical repeat unit, or some arbitrary portion of the covalent chain defined so as to contain hydrogen bonding functional group. The chapter considers amorphous polymers at temperatures above their glass transitions. Flory argues that for the treatment of chemical equilibria between polymer species the most appropriate and least ambiguous reference state is that one in which the individual species are separate and oriented.

Background Tumor heterogeneity can manifest itself by sub-populations of cells having distinct phenotypic profiles expressed as diverse molecular, morphological and spatial distributions. This inherent heterogeneity poses challenges in terms of diagnosis, prognosis and efficient treatment. Consequently, tools and techniques are being developed to properly characterize and quantify tumor heterogeneity. Multiplexed immunofluorescence (MxIF) is one such technology that offers molecular insight into both inter-individual and intratumor heterogeneity. It enables the quantification of both the concentration and spatial distribution of 60+ proteins across a tissue section. Upon bioimage processing, protein expression data can be generated for each cell from a tissue field of view. Results The Multi-Omics Heterogeneity Analysis (MOHA) tool was developed to compute tissue heterogeneity metrics from MxIF spatially resolved tissue imaging data. This technique computes the molecular state of each cell in a sample based on a pathway or gene set. Spatial states are then computed based on the spatial arrangements of the cells as distinguished by their respective molecular states. MOHA computes tissue heterogeneity metrics from the distributions of these molecular and spatially defined states. A colorectal cancer cohort of approximately 700 subjects with MxIF data is presented to demonstrate the MOHA methodology. Within this dataset, statistically significant correlations were found between the intratumor AKT pathway state diversity and cancer stage and histological tumor grade. Furthermore, intratumor spatial diversity metrics were found to correlate with cancer recurrence. Conclusions MOHA provides a simple and robust approach to characterize molecular and spatial heterogeneity of tissues. Research projects that generate spatially resolved tissue imaging data can take full advantage of this useful technique. The MOHA algorithm is implemented as a freely available R script (see supplementary information).

Colorectal cancer (CRC) has one of the highest worldwide incidences and mortality rates. About 25% of stage II patients develop recurrence within 5 years. However, use of adjuvant chemotherapy yields minimal therapeutic benefit. Clinical decision-making in this population would be informed by prognostic and predictive biomarkers that help indicate more targeted interventions and/or intensified disease monitoring. Higher cMET expression has been shown to be a prognostic marker in CRC and has been evaluated as a drug target in several cancers, including CRC. cMET acts as the receptor for hepatocyte growth factor (HGF), and is associated with increased proliferation, migration and morphogenesis of epithelial cells via activation of multiple downstream pathways including PI3K/AKT, MAPK and the NF-kB pathways. Here, we investigated whether increased cellular expression of multiple markers in the cMET/adjacent pathways was correlated with clinical outcome. The study population consisted of 283 patients with stage II CRC, without neoadjuvant treatment. Using a multiplexed immunofluorescence method (MxIF) with cell-level quantification (Cell DIVETM, GE Healthcare), 41 biomarkers in the cMET, mTOR, MAPK and associated pathways, and lymphocyte markers were analyzed in an iterative sequence of staining, imaging and dye inactivation, followed by image registration, cell segmentation and biomarker intensity-quantitation. Poor quality images and cells were filtered based on poor segmentation and tissue quality following manual review. Images that did not perfectly register were also excluded. For epithelial cell analysis, all stromal cells were filtered, resulting in a total of 559,952 epithelial cells. K-means clustering was conducted on cMET and related pathways (cMET, pGSK3β, 4EBP1, p4EBP1, S6, pS6, pStat3, pp38MAPK, pNFkBp65, pNFkBp105, EGFR, pERK1/2, HER2, IGF1R, CA-IX, Glut1, SLC7A5 and Ki67). Cluster analysis identified 6 cell clusters with varying expression levels of cMET and other pathway markers. A cluster corresponding to low cMET network activation (cMETLow) was correlated with reduced risk of recurrence (cox pH model Likelihood ratio test p-value = 0.056). Furthermore, MMR proficient patients (who had a higher recurrence rate) had a significantly greater proportion of cells with elevated cMET and related pathway marker (cMETHigh) s(p= 0.007). They also had a significantly lower fraction of infiltrating helper T cells (CD3+CD4+, pvalue 0.076) and CD68+ cells in the epithelial region, compared to MMR deficient patients (p=0.005). Further research will include continuing in-depth analysis of MMR status, cMET pathway and lymphocyte response as well as the role of cellular heterogeneity. In summary, comprehensive cMET pathway analysis using a multiplexed single cell approach indicates for the first time an association between low cMET network activation and superior clinical outcomes. Citation Format: Elizabeth McDonough, Anup Sood, Fiona Ginty, Sanghee Cho, John Graf, Jochen Prehn, Philip Dunne, Andreas Lindner, Manuela Salvucci, Daniel Longley, Mark Lawler, Travis Hollmann, Jinru Shia. Lower cellular activation of cMET signaling network is associated with reduced recurrence risk in stage II colorectal cancer [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr A039. doi:10.1158/1535-7163.TARG-19-A039

We developed and deployed a workflow for generating multi-scale, multiparametric imaging data, feature extraction and/or converting to higher scales which equips multiple analysis approaches to differentiate clinically variable phenotypes of glial tumors. The workflow quantifies spatial heterogeneity (concordance of adjoining cells) and molecular heterogeneity (varied cell states determined by protein abundance) of glial tumors at the genomic, tissue, and medical imaging scales including IDH mutation status and progression/recurrence status. A panel of 24 multiplexed immunofluorescence (MxIF) markers (addressing 9 hallmarks of cancer) was used to profile single cells (in the thousands) in tissue sections from each of 31 glial tumors (ranging from primary grade II to IV, and recurrent grade IV). Pre-resection multi-parameter MR images were feature extracted from discreet habitats (necrosis, enhancing, and edema); whole exome and transcriptome sequencing from bulk viable tumor were analyzed. By MxIF, the various states of individual cells from treatment-naive patient specimens resolved unsupervised into 7 clusters, for which Cluster 2 (including cells from 9 patients) and Cluster 6 (including cells from 8 patients) contained the two larger bundles of patient cases. When separated into IDHmt and IDHwt cases, cells from IDHmt cases frequently contained cell populations dominated by a single cluster (low molecular heterogeneity); cells from cases with IDHwt represented multiple different clusters (high molecular heterogeneity). In grade III astrocytomas, and grade IV recurrent glioblastomas, spatial heterogeneity of the hallmark “inducing angiogenesis” was elevated in the IDHmt tumors compared to IDHwt, while between the same groups, molecular heterogeneity was lower in the IDHmt cases than wild type. Edema from T1w post contrast MR imaging was found to be elevated in IDHwt gliomas relative to IDHmt, while enhancement was reduced in IDHwt compared to IDHmt tumors. The findings demonstrate that IDHmt gliomas, irrespective of grade, show less edema, greater enhancement, and greater spatial heterogeneity of the “inducing angiogenesis” hallmark but lower molecular heterogeneity than IDHwt tumors. Molecular heterogeneity of “cancer invasion” also differed between IDHmt and IDHwt cases. Longer survival duration following diagnosis for patients with IDHmt gliomas may reflect generalized altered molecular and spatial heterogeneity, which is a phenotype evident on medical imaging. [Clinically-annotated specimens originated from the Ohio Brain Tumor Study and the Ivy GBM Clinical Trials Consortium] Citation Format: Michael E. Berens, Jill S. Barnholtz-Sloan, Miribella Rusu, John Graf, Anup Sood, Sanghee Cho, Maria Zavodszky, Sara Byron, Rebecca Halperin, Yi Fritz, Seungchan Kim, Fiona Ginty. Role of IDH mutation status on molecular and spatial heterogeneity in glial tumors across progression and recurrence [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3039.

Increasingly, clinical trials for Alzheimer’s disease (AD) are being conducted earlier in the disease phase and with biomarker confirmation using in vivo amyloid PET imaging or CSF tau and Aβ measures to quantify pathology. However, making such a pre-clinical AD diagnosis is relatively costly and the screening failure rate is likely to be high. Having a blood-based marker that would reduce such costs and accelerate clinical trials through identifying potential participants with likely pre-clinical AD would be a substantial advance. In order to seek such a candidate biomarker, discovery phase proteomic analyses using 2DGE and gel-free LC-MS/MS for high and low molecular weight analytes were conducted on longitudinal plasma samples collected over a 12-year period from non-demented older individuals who exhibited a range of 11C-PiB PET measures of amyloid load. We then sought to extend our discovery findings by investigating whether our candidate biomarkers were also associated with brain amyloid burden in disease, in an independent cohort. Seven plasma proteins, including A2M, Apo-A1, and multiple complement proteins, were identified as pre-clinical biomarkers of amyloid burden and were consistent across three time points (p < 0.05). Five of these proteins also correlated with brain amyloid measures at different stages of the disease (q < 0.1). Here we show that it is possible to detect a plasma based biomarker signature indicative of AD pathology at a stage long before the onset of clinical disease manifestation. As in previous studies, acute phase reactants and inflammatory markers dominate this signature.

An association model describing the thermodynamics of mixing two fluids, each of which hydrogen bonds (self-associates) to itself in the pure state, is discussed. Equations describing the contributions of hydrogen bonding to the free energy of mixing are obtained using a matrix method.

Extracting biologically relevant data from radiology images can enable better monitoring of disease progression and therapy response. The field of radiogenomics is providing new approaches for such genomic/radiology correlations. However, there are several challenges in validation and clinical translation in that few DNA mutations are shared between tumors from different individuals and the differences in scale between imaging and genomic features can limit interpretation of underlying mechanisms. The goals of this work were to i) analyze correlations between low grade glioma (LGG) DNA somatic mutations, using a novel DNA impact scoring approach, and MRI derived imaging features; and ii) to interpret results in context of cancer hallmarks1. Multi-parametric MRI and corresponding DNA data from 32 LGG patients were extracted from The Cancer Genome Atlas (TCGA) and The Cancer Imaging Archive (TCIA). The cohort included 18 males (56%), with mean age of 44 years (range: 21-74 years). An expert radiologist outlined the normal and tumor regions of interest using ITK-Snap tool. The normal region was used as a reference to normalize image intensities in the tumor region. Tumor mean intensity and mean variance were computed from Apparent Diffusion Coefficient (ADC), T1 enhancement ratio (derived from T1 pre- and post- contract MRI), and Fluid-Attenuated Inversion Recovery (FLAIR) images. A novel algorithm was used to compute DNA impact scores for each somatic mutation. The score represents the probability of a DNA variant being pathogenic vs. nonpathogenic. First, the scoring algorithm computes a score for nucleotide base insertions, deletions, or single base changes and then computes the consequence of such changes on amino acid coding, binding sites, splice sites and protein phosphorylation sites. An impact score was then computed based on the individual DNA impact scores of mutations within the gene. Finally, an average DNA impact score was computed at the Cancer Hallmark level using a gene-cancer hallmark map. At gene level, significant positive correlations were found between the ATRX (p=0.0002), TP53 (p=0.02) and ADC mean intensity. At pathway level, regulation of TP53 expression and degradation, and DNA damage response, signal transduction by p53 class mediator, and DNA translocase activity were found to be enriched with genes that correlated with ADC and FLAIR. These pathways also contained genes that were enriched in the following cancer hallmarks: replicative immortality, evading growth suppression and genome instability. The ATRX gene is a member of all three hallmarks and TP53 a member of two. Since ADC is a measure of water diffusion and hence an indirect measure of cellularity, these findings demonstrate that mutations in replication and repair pathways are contributing to imaging features at the tumor level.1 Hanahan, D. and Weinberg, R.A. (2011). Hallmarks of cancer: the next generation. Cell 144(5):646-74. Citation Format: John Graf, Mirabela Rusu, Yunxia Sui, Dattesh Shanbhag, Uday Patil, Jeffrey Kiefer, Jill Barnholtz-Sloan, Michael Berens, Fiona Ginty, Sandeep Gupta, Chinnappa Kodira, Lee Newberg, Sushravya Raghunath, Anup Sood. Interpreting glioma MR imaging and somatic mutations in a cancer hallmark context [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 882. doi:10.1158/1538-7445.AM2017-882

The hallmarks of cancer consist of ten categories that serve as an organizing principle and framework for understanding neoplastic disease. The ten hallmarks include activating invasion and metastasis, avoiding immune destruction, deregulating cellular energetics, enabling replicative immortality, evading growth suppressors, genome instability and mutation, inducing angiogenesis, resisting cell death, sustaining proliferative signaling, and tumor-promoting inflammation. In order to facilitate the use of the hallmarks of cancer in genomic studies, we have undertaken a systematic methodology to map genes to each individual hallmark of cancer. Assignment of genes to the individual hallmarks was performed leveraging gene ontology (GO) annotations. Specifically, for each hallmark, a term list was generated by cancer research experts, with biological terms associated with each hallmark. This term list was used to search and identify matching GO terms. Matched terms were then mapped to the highest, most specific, representative, non-redundant GO term in the GO hierarchy. Genes for each term were restricted by selecting only human taxon, and high confidence experimental evidence codes. For specific GO terms, where present, the Regulation of ‘GO term’ category was included. The genes for each GO term for each hallmark were combined in a non-redundant list of genes for each hallmark. In the case of the evading growth suppressors category, a different strategy was employed. In this instance, genes were identified through ‘tumor suppressor’ gene/protein annotation in the DGIdb resource and UniProt. Additionally, text-mining methods on biomedical research literature were used to defined a high confidence list of genes for this hallmark. As an example use case of the hallmarks we applied them to the analysis of the TCGA Pan-Cancer RNAseq data set. Clustering across the individual hallmarks led to interesting differences within particular tumor tissue types, as well as shared hallmarks for other tumor types. For example, use of the genome instability and mutation hallmark for Pan-Cancer clustering, revealed a tight tissue-based cluster of low-grade gliomas and GBMs. This result suggests the importance of this hallmark expression in this tumor type. This high confidence mapping of genes to hallmarks of cancer provides a unique dataset to facilitate analyses of cancer genome data. Citation Format: Jeff Kiefer, Sara Nasser, John Graf, Chinnappa Kodira, Fiona Ginty, Lee Newberg, Anup Sood, Michael E. Berens. A systematic approach toward gene annotation of the hallmarks of cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3589. doi:10.1158/1538-7445.AM2017-3589

Spectroscopic evidence is presented to indicate that local screening effects are important in polymer mixtures. Essentially, a polymer segment has a locally higher concentration of like segments because of this factor. A simple modification to existing theories is presented to account for this local screening.

In this paper theoretical and experimental studies of the phase behaviour of ternary polymer blends are reviewed. Particular emphasis is placed upon the effect of specific interactions (hydrogen bonds). The association model developed to predict the phase behaviour of binary hydrogen-bonded polymer blends has been extended to ternary polymer blends. Simulations have been performed to illustrate the major effects of ‘physical’ (primarily dispersion) and ‘chemical’ (hydrogen bonding) forces on phase behaviour. Theoretically predicted phase diagrams have also been compared to experimental results obtained from five hydrogen-bonded ternary polymer blend systems. Overall, the agreement is satisfactory. One general conclusion is that it will be very difficult to find ternary polymer blends that exist in a single phase over a wide composition range. Furthermore, in most cases an immiscible binary blend cannot be made homogeneous by introducing a small amount of a third polymer (‘compatibilizer’).

The goal of this study was to provide a feasibility assessment for PET imaging of multiple sclerosis (MS) lesions based on their decreased myelin content relative to the surrounding normal-appearing brain tissue. The imaging agent evaluated for this purpose is a molecule that binds strongly and specifically to myelin basic protein. Physiology-based pharmacokinetic modeling combined with PET image simulation applied to a brain model was used to examine whether such an agent would allow the differentiation of artificial lesions 4–10 mm in diameter from the surrounding normal-looking white and gray matter. Furthermore, we examined how changes in agent properties, model parameters, and experimental conditions can influence imageability, identifying a set of conditions under which imaging of MS lesions might be feasible. Based on our results, we concluded that PET imaging has the potential to become a useful complementary method to MRI for MS diagnosis and therapy monitoring.

The polymer blend system consisting of poly(4-vinylphenol) (PVPh), poly(vinylacetate) (PVAc), and poly(ethylene oxide) (PEO) represents a rare case of a ternary system in which each binary pair is miscible in the amorphous state at 150 o C. Using the concept of competing equilibria, it is shown that the equilibrium constant describing hydrogen bonding between the OH group of PVPh and the ether oxygen of PEO can he determined from quantitative infrared spectroscopic analysis of the fraction of hydrogen-bonded PVAc carbonyl groups in single-phase ternary compositions rich in PVPh

An association model is applied to blends where one component contains secondary alkyl hydroxyl groups. The use of this model requires a knowledge of parameters (equilibrium constants) describing the self-association of the pure component, and the determination of these parameters from infrared studies of model compounds is described. Included is the complication that the self-associating species also contains ether groups, so that the model can be applied to the poly(hydroxy ether of Bisphenol A) (Phenoxy). Phase diagrams and miscibility windows for Phenoxy blends with polyesters and polymethacrylates were calculated

The phase behavior of blends of α-helical rigid rods poly(glutamates) (PMLG, PELG, and PBLG) with poly-(vinylphenol) (PVPh) has been investigated. The equilibrium number of hydrogen bond interactions was found between the side-chain esters of PMLG, PELG, and the OH group of PVPh in blends of these polymers but not found between PBLG and PVPh, indicating that this latter system is phase separated. At high rigid-rod concentrations the miscible blends displayed anisotropy. An association model has been applied to obtain theoretical phase diagram for these systems

This is the first of three papers that deal with coal solubility and swelling. An association model has been applied to coal, and this predicts that the mixing of coal with certain solvents will be determined by a balance between unfavorable «physical» interactions, measured by a Flory χ parameter, and favorable hydrogen bonding interactions. This first paper deals with the determination of χ from solubility parameters. Methods based on group contributions and swelling measurements are assessed. The former suffers from large errors while the latter does not give correct values because of large free-volume differences between coal and most solvents. Even though group contribution methods are flawed when applied to coal, they at least appear to give values in the right range

In this paper we propose a model for coal swelling based on a process called disinterspersion. This allows a calculation of the «molecular weight» or number of aromatic «clusters» between cross-link points under the assumption that rigid chains swell with little or no change in average conformation up to a limit imposed by the geometry of the network. Sample calculations are presented and suggest that for an Illinois No. 6 coal the «molecular weight» between cross-link points is small

A Flory lattice model is used to obtain an expression for the free energy of mixing polymers that hydrogen bond. The derivation is based on the determination of the probability that a mixture of the nonhydrogen bonded chains would spontaneously occur in a configuration equivalent to the hydrogen bonded system. Our result has three parts. The usual contribution to the free energy from mixing covalent chains, a contribution from the hydrogen bonds that is equal to the result that would be obtained if the segments were not covalently linked, and a ‘‘correction’’ term that accounts for the excess entropy of mixing introduced by the second term. A consequence of this model is that there should be no dependence of the equilibrium constants describing hydrogen bonding upon covalent chain length.

A model has been developed and implemented at GE Plastics that predicts a material's color shift when weathered. The material's color shift is due to the summation of color shifts from each individual component. By individually measuring the change in each component's optical coefficients upon weathering and using a multiple light scattering model, one can predict the color shift of a material composed of mixtures of these components. The model has been shown to have a standard deviation of 0.4 to 0.9 when predicting color shifts E*, for PC-polyester copolymers, ABS, and ABS/PC blends using an automotive exterior test, SAE J1885, ASTM D 4674, and ASTM D 4459.

General Electric (GE) traces its beginnings to Thomas A. Edison, who established the Edison Electric Light Company in 1878. GE is a diversified technology, manufacturing, and services company that operates in more than 100 countries around the world, with 250 manufacturing plants in 26 different nations. GE employs 276,000 people worldwide, including 165,000 in the United States. GE Plastics (GEP) is a world leader in versatile, high-performance engineered plastics used in the computer, electronics, office equipment, automotive, building and construction, and other industries. The FormTool software has been considered a success at General Electric due to the project's financial return on investment. This Java tool developed by the GE Corporate Research & Development Center allows color match cases to be selected over the Web. Instead of performing a case selection within GE Plastics by color technicians, customers can perform their own selection process. It is also considered as a technology achievement due to the number of patents obtained and the opportunities it has opened up. GEP is currently working on two new case-based reasoning (CBR) knowledge management tools. The first system allows customers to select the appropriate type of plastic to meet their engineering requirements. The second system helps GE researchers to develop new plastics by providing a common repository for sharing knowledge about experiments and designing new experiments.

A case-based reasoning system for determining what colorants to use for producing a specific color of plastic was created. The selection of colorants needs to take many factors into consideration. A technique that involved fuzzy logic was used to compare the quality of the color match for each factor. The system has been in use for two years at a growing number of GE Plastics sites and has shown significant cost savings.

In the future, we may be faced with the need to provide treatment for an emergent biological threat against which existing vaccines and drugs have limited efficacy or availability. To prepare for this eventuality, our objective was to use a metabolic network-based approach to rapidly identify potential drug targets and prospectively screen and validate novel small-molecule antimicrobials. Our target organism was the fully virulent Francisella tularensis subspecies tularensis Schu S4 strain, a highly infectious intracellular pathogen that is the causative agent of tularemia and is classified as a category A biological agent by the Centers for Disease Control and Prevention. We proceeded with a staggered computational and experimental workflow that used a strain-specific metabolic network model, homology modeling and X-ray crystallography of protein targets, and ligand- and structure-based drug design. Selected compounds were subsequently filtered based on physiological-based pharmacokinetic modeling, and we selected a final set of 40 compounds for experimental validation of antimicrobial activity. We began screening these compounds in whole bacterial cell-based assays in biosafety level 3 facilities in the 20th week of the study and completed the screens within 12 weeks. Six compounds showed significant growth inhibition of F. tularensis, and we determined their respective minimum inhibitory concentrations and mammalian cell cytotoxicities. The most promising compound had a low molecular weight, was non-toxic, and abolished bacterial growth at 13 µM, with putative activity against pantetheine-phosphate adenylyltransferase, an enzyme involved in the biosynthesis of coenzyme A, encoded by gene coaD. The novel antimicrobial compounds identified in this study serve as starting points for lead optimization, animal testing, and drug development against tularemia. Our integrated in silico/in vitro approach had an overall 15% success rate in terms of active versus tested compounds over an elapsed time period of 32 weeks, from pathogen strain identification to selection and validation of novel antimicrobial compounds.

The results of a set of experiments designed to test another facet of the predictive potential of the association model previously developed and used to calculate miscibility windows and maps for hydrogen-bonded polymer blends are presented

Background:Measures of neocortical amyloid burden (NAB) identify individuals who are at substantially greater risk of developing Alzheimer's disease (AD). Blood-based biomarkers predicting NAB would have great utility for the enrichment of AD clinical trials, including large-scale prevention trials.Methods:Nontargeted proteomic discovery was applied to 78 subjects from the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing with a range of NAB values. Technical and independent replications were performed by immunoassay.Results:Seventeen discovery candidates were selected for technical replication. α2-Macroglobulin, fibrinogen γ-chain (FGG), and complement factor H-related protein 1 were confirmed to be associated with NAB. In an independent cohort, FGG plasma levels combined with age predicted NAB had a sensitivity of 59% and specificity of 78%.Conclusion:A single blood protein, FGG, combined with age, was shown to relate to NAB and therefore could have potential for enrichment of clinical trial populations.