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To develop artificial intelligence (AI) system that assists in checking endotracheal tube (ETT) placement on chest X-rays (CXRs) and evaluate whether it can move into clinical validation as a quality improvement tool.A retrospective data set including 2000 de-identified images from intensive care unit patients was split into 1488 for training and 512 for testing. AI was developed to automatically identify the ETT, trachea, and carina using semantically embedded neural networks that combine a declarative knowledge base with deep neural networks. To check the ETT tip placement, a "safe zone" was computed as the region inside the trachea and 3-7 cm above the carina. Two AI outputs were evaluated: (1) ETT overlay, (2) ETT misplacement alert messages. Clinically relevant performance metrics were compared against prespecified thresholds of85% overlay accuracy and positive predictive value (PPV)30% and negative predictive value NPV95% for alerts to move into clinical validation.An ETT was present in 285 of 512 test cases. The AI detected 95% (271/285) of ETTs, 233 (86%) of these with accurate tip localization. The system (correctly) did not generate an ETT overlay in 221/227 CXRs where the tube was absent for an overall overlay accuracy of 89% (454/512). The alert messages indicating that either the ETT was misplaced or not detected had a PPV of 83% (265/320) and NPV of 98% (188/192).The chest X-ray AI met prespecified performance thresholds to move into clinical validation.

Diseases are a manifestation of how thousands of proteins interact. In several diseases, such as cancer and Alzheimer’s disease, proteome-wide disturbances in protein-protein interactions are caused by alterations to chaperome scaffolds termed epichaperomes. Epichaperome-directed chemical probes may be useful for detecting and reversing defective chaperomes. Here we provide structural, biochemical, and functional insights into the discovery of epichaperome probes, with a focus on their use in central nervous system diseases. We demonstrate on-target activity and kinetic selectivity of a radiolabeled epichaperome probe in both cells and mice, together with a proof-of-principle in human patients in an exploratory single group assignment diagnostic study (ClinicalTrials.gov Identifier: NCT03371420). The clinical study is designed to determine the pharmacokinetic parameters and the incidence of adverse events in patients receiving a single microdose of the radiolabeled probe administered by intravenous injection. In sum, we introduce a discovery platform for brain-directed chemical probes that specifically modulate epichaperomes and provide proof-of-principle applications in their use in the detection, quantification, and modulation of the target in complex biological systems., Here, the authors show structural, biochemical, and functional insights into the discovery of epichaperome‐ directed chemical probes for use in central nervous system diseases. Probes emerging from this work have translated to human clinical studies in Alzheimer’s disease and cancer.

Cellular transformation is accompanied by extensive re-wiring of many biological processes leading to augmented levels of distinct types of cellular stress, including proteotoxic stress. Cancer cells critically depend on stress-relief pathways for their survival. However, the mechanisms underlying the transcriptional initiation and maintenance of the oncogenic stress response remain elusive. Here, we show that the expression of heat shock transcription factor 1 (HSF1) and the downstream mediators of the heat shock response is transcriptionally upregulated in T-cell acute lymphoblastic leukemia (T-ALL). Hsf1 ablation suppresses the growth of human T-ALL and eradicates leukemia in mouse models of T-ALL, while sparing normal hematopoiesis. HSF1 drives a compact transcriptional program and among the direct HSF1 targets, specific chaperones and co-chaperones mediate its critical role in T-ALL. Notably, we demonstrate that the central T-ALL oncogene NOTCH1 hijacks the cellular stress response machinery by inducing the expression of HSF1 and its downstream effectors. The NOTCH1 signaling status controls the levels of chaperone/co-chaperone complexes and predicts the response of T-ALL patient samples to HSP90 inhibition. Our data demonstrate an integral crosstalk between mediators of oncogene and non-oncogene addiction and reveal critical nodes of the heat shock response pathway that can be targeted therapeutically.

A copper-mediated synthesis of diaryl sulfides utilizing Cu(I)-thiophene-2-carboxylate (CuTC) is described. We demonstrate the use of CuTC as a soluble, non-basic catalyst in the coupling of aryl iodides and aryl thiols in the synthesis of synthetically advanced diaryl sulfides. This method allows for the successful coupling of challenging substrates including ortho-substituted and heteroaryl iodides and thiols. Additionally, most of the aryl iodide substrates used here contain the privileged piperazine scaffold bound to a pyrimidine, pyridine, or phenyl ring and thus this method allows for the elaboration of complex piperazine scaffolds into molecules of biological interest. The method described here enables the incorporation of late-stage structural diversity into diaryl sulfides containing the piperazine ring, thus enhancing the number and nature of derivatives available for SAR investigation.

The hsp90 chaperones govern the function of essential client proteins critical for normal cell function as well as cancer initiation and progression. Hsp90 activity is driven by ATP, which binds to the N-terminal domain and induces large conformational changes that are required for client maturation. Inhibitors targeting the ATP-binding pocket of the N-terminal domain have anticancer effects, but most bind with similar affinity to cytosolic Hsp90α and Hsp90β, endoplasmic reticulum Grp94, and mitochondrial Trap1, the four cellular hsp90 paralogs. Paralog-specific inhibitors may lead to drugs with fewer side effects. The ATP-binding pockets of the four paralogs are flanked by three side pockets, termed sites 1, 2, and 3, which differ between the paralogs in their accessibility to inhibitors. Previous insights into the principles governing access to sites 1 and 2 have resulted in development of paralog-selective inhibitors targeting these sites, but the rules for selective targeting of site 3 are less clear. Earlier studies identified 5′N-ethylcarboxamido adenosine (NECA) as a Grp94-selective ligand. Here we use NECA and its derivatives to probe the properties of site 3. We found that derivatives that lengthen the 5′ moiety of NECA improve selectivity for Grp94 over Hsp90α. Crystal structures reveal that the derivatives extend further into site 3 of Grp94 compared with their parent compound and that selectivity is due to paralog-specific differences in ligand pose and ligand-induced conformational strain in the protein. These studies provide a structural basis for Grp94-selective inhibition using site 3.

Heat shock proteins (HSPs) present as a double edged sword. While they play an important role in maintaining protein homeostasis in a normal cell, cancer cells have evolved to co-opt HSP function to promote their own survival. As a result, HSPs such as HSP90 have attracted a great deal of interest as a potential anticancer target. These efforts have resulted in over 20 distinct compounds entering clinical evaluation for the treatment of cancer. However, despite the potent anticancer activity demonstrated in preclinical models, to date no HSP90 inhibitor has obtained regulatory approval. In this review we discuss the unique challenges faced in targeting HSPs that have likely contributed to their lack of progress in the clinic and suggest ways to overcome these so that the enormous potential of these compounds to benefit patients can finally be realized. We also provide a guideline for the future development of HSP-targeted agents based on the many lessons learned during the last two decades in developing HSP90 inhibitors.

The chaperome is a large and diverse protein machinery composed of chaperone proteins and a variety of helpers, such as the co-chaperones, folding enzymes and scaffolding and adapter proteins. Heat shock protein 90s and 70s (HSP90s and HSP70s), the most abundant chaperome members in human cells, are also the most complex. As we have learned to appreciate, their functions are context dependent and manifested through a variety of conformations that each recruit a subset of co-chaperone, scaffolding and folding proteins and which are further diversified by the post-translational modifications each carry, making their study through classic genetic and biochemical techniques quite a challenge. Chemical biology tools and techniques have been developed over the years to help decipher the complexities of the HSPs and this review will provide an overview of such efforts with focus on HSP90 and HSP70.

Heat shock protein 70 (Hsp70) is a family of proteins with key roles in regulating malignancy. Cancer cells rely on Hsp70 to inhibit apoptosis, regulate senescence and autophagy, and maintain the stability of numerous onco-proteins. Despite these important biological functions in cancer, robust chemical tools that enable the analysis of the Hsp70-regulated proteome in a tumor-by-tumor manner are yet unavailable. Here we take advantage of a recently reported Hsp70 ligand to design and develop an affinity purification chemical toolset for potential use in the investigation of the endogenous Hsp70-interacting proteome in cancer. We demonstrate that these tools lock Hsp70 in complex with onco-client proteins and effectively isolate Hsp70 complexes for identification through biochemical techniques. Using these tools we provide proof-of-concept analyses that glimpse into the complex roles played by Hsp70 in maintaining a multitude of cell-specific malignancy-driving proteins.

Human protein isoprenylcysteine carboxyl methyltransferase (hIcmt) is the enzyme responsible for the α-carboxyl methylation of the C-termimal isoprenylated cysteine of CaaX proteins, including Ras proteins. This specific posttranslational methylation event has been shown to be important for cellular transformation by oncogenic Ras isoforms. This finding led to interest in hIcmt inhibitors as potential anti-cancer agents. Previous analog studies based on N-acetyl-S-farnesylcysteine identified two prenylcysteine-based low micromolar inhibitors (1a and 1b) of hIcmt, each bearing a phenoxyphenyl amide modification. In this study, a focused library of analogs of 1a and 1b was synthesized and screened versus hIcmt, delineating structural features important for inhibition. Kinetic characterization of the most potent analogs 1a and 1b established that both inhibitors exhibited mixed-mode inhibition and that the competitive component predominated. Using the Cheng – Prusoff method, the Ki values were determined from the IC50 values. Analog 1a has a KIC of 1.4 ± 0.2 μM and a KIU of 4.8 ± 0.5 μM while 1b has a KIC of 0.5 ± 0.07 μM and a KIU of 1.9 ± 0.2 μM. Cellular evaluation of 1b revealed that it alters the subcellular localization of GFP-KRas, and also inhibits both Ras activation and Erk phosphorylation in Jurkat cells.

Background: Manually importing and analyzing image data can be time-consuming, prone to human error, and costly for large clinical trial datasets. This can lead to delays in quality control (QC) feedback to imaging sites and in obtaining data analysis results. Herein we describe the creation and application of a high-throughput review process for import, classification, labeling and QC of large multimodal clinical trial image datasets.Methods: Automated methods were used to remove patient identifying information, extract image header data, and filter image data for usability. A convolutional neural net was applied to estimate anatomy for CT images. Internal scores were assigned for each image series to identify the optimal series for labeling and reading of each anatomical region. Image QC reports were automatically generated for all patients.Results: In combined studies for which 204,492 series were received, 27,841 series were identified as usable and 13,415 series were labeled. Using this high-throughput method, total work-hours required per time point were reduced by an approximate factor of ten when compared to traditional review and labeling methods. Our anatomic classification system identified 95.7% of image series correctly, with the remaining series being manually corrected before labeling and analysis.Conclusions: A high-throughput image analysis pipeline was implemented in a large combined dataset of clinical trial image series. This pipeline can be applied across other studies and modalities for fast image data characterization, labeling and QC.

Grp94 is involved in the regulation of a restricted number of proteins and represents a potential target in a host of diseases, including cancer, septic shock, autoimmune diseases, chronic inflammatory conditions, diabetes, coronary thrombosis, and stroke. We have recently identified a novel allosteric pocket located in the Grp94 N-terminal binding site that can be used to design ligands with a 2-log selectivity over the other Hsp90 paralogs. Here we perform extensive SAR investigations in this ligand series and rationalize the affinity and paralog selectivity of choice derivatives by molecular modeling. We then use this to design 18c, a derivative with good potency for Grp94 (IC50 = 0.22 μM) and selectivity over other paralogs (>100- and 33-fold for Hsp90α/β and Trap-1, respectively). The paralog selectivity and target-mediated activity of 18c was confirmed in cells through several functional readouts. Compound 18c was also inert when tested against a large panel of kinases. We show that 18c has biological activity in several cellular models of inflammation and cancer and also present here for the first time the in vivo profile of a Grp94 inhibitor.

Medical image processing has emerged as a powerful way to simulate fluid flows through realistic models of complex patient-specific geometries without relying upon simplifying geometric approximations. However, image-based flow modeling processes traditionally involve several steps (e.g. image segmentation, surface mesh generation, volumetric flow mesh generation, and finally computational simulation) that must often be performed using separate pieces of software. This work presents an alternative methodology in which the entire image-based flow modeling process takes place on a Cartesian domain with the image embedded as an implicit surface, circumventing the need for complex surface meshes and body-fitted flow meshes. The complete framework is demonstrated with flow calculations performed in a computed tomography (CT) image reconstruction of an intracranial aneurysm (ICA). Flow calculations are compared against calculations performed following a standard multi-step route using the Vascular Modeling Toolkit (VMTK) [1, 2] and Fluent™ (Ansys, Inc., Lebanon, NH).Copyright © 2013 by ASME

Biomedical flow computations in patient-specific geometries require integrating image acquisition and processing with fluid flow solvers. Typically, image-based modeling processes involve several steps, such as image segmentation, surface mesh generation, volumetric flow mesh generation, and finally, computational simulation. These steps are performed separately, often using separate pieces of software, and each step requires considerable expertise and investment of time on the part of the user. In this paper, an alternative framework is presented in which the entire image-based modeling process is performed on a Cartesian domain where the image is embedded within the domain as an implicit surface. Thus, the framework circumvents the need for generating surface meshes to fit complex geometries and subsequent creation of body-fitted flow meshes. Cartesian mesh pruning, local mesh refinement, and massive parallelization provide computational efficiency; the image-to-computation techniques adopted are chosen to be suitable for distributed memory architectures. The complete framework is demonstrated with flow calculations computed in two 3D image reconstructions of geometrically dissimilar intracranial aneurysms. The flow calculations are performed on multiprocessor computer architectures and are compared against calculations performed with a standard multistep route.

Isoprenylcysteine carboxyl methyltransferases (Icmts) are a class of integral membrane protein methyltransferases localized to the endoplasmic reticulum (ER) membrane in eukaryotes. The Icmts from human (hIcmt) and Saccharomyces cerevisiae (Ste14p) catalyze the α-carboxyl methyl esterification step in the post-translational processing of CaaX proteins, including the yeast a-factor mating pheromones and both human and yeast Ras proteins. Herein, we evaluated synthetic analogs of two well-characterized Icmt substrates, N-acetyl-S-farnesyl-L-cysteine (AFC) and the yeast a-factor peptide mating pheromone, that contain photoactive benzophenone moieties in either the lipid or peptide portion of the molecule. The AFC based-compounds were substrates for both hIcmt and Ste14p, whereas the a-factor analogs were only substrates for Ste14p. However, the a-factor analogs were found to be micromolar inhibitors of hIcmt. Together, these data suggest that the Icmt substrate binding site is dependent upon features in both the isoprenyl moiety and upstream amino acid composition. Furthermore, these data suggest that hIcmt and Ste14p have overlapping, yet distinct, substrate specificities. Photocrosslinking and neutravidin-agarose capture experiments with these analogs revealed that both hIcmt and Ste14p were specifically photolabeled to varying degrees with all of the compounds tested. Our data suggest that these analogs will be useful for the future identification of the Icmt substrate binding sites.

Coronary Artery Disease (CAD) is one of the leading causes of death in developed countries. The link between Wall Shear Stress (WSS) and CAD development is well established, with studies indicating the accumulation of lesions in regions of low WSS, flow separation, and in the regions where there is departure from axially aligned unidirectional flow [5]. It has been well established that blood flow patterns are highly affected by branch flows, as bifurcations are one of the leading locations of plaque accumulation [5]. Computational fluid dynamics (CFD) is an important tool for quantifying hemodynamics.Copyright © 2011 by ASME

Background: Heat shock protein 70 family members play an important role in cancer. They are up-regulated in wide variety of tumors and the increased Hsp70 protein expression correlates with metastases, resistance to treatment and poor prognosis. Multiple mechanisms explain cancer cells dependence on Hsp70, such as inhibition of apoptosis by Hsp70, induction of autophagy and control of stability of onco-proteins. These Hsp70 activities are mediated in cancer by its ability to chaperone and interact with a large number of proteins in a cell-specific, context dependent manner. Hypothesis: Reagents that enable the capture of tumor-specific Hsp70 complexes facilitate the identification of context-dependent Hsp70 interactomes. Results: Our laboratory recently reported the identification of a novel allosteric site located in the nucleotide binding domain of Hsp70 (Chem Biol 2013). It has also reported the discovery of ligands that bind to the allosteric pocket of Hsp70, inhibit its function in cancer cells and result in anti-cancer activity (J Med Chem 2013). Structure-activity relationship studies in this ligand series gave insights on the attachment of specific linkers for the design of Hsp70-related chemical tools. Here we present the design of Hsp70-directed reagents and use biochemical and cell-based methods to validate Hsp70-directed affinity purification probes. We demonstrate that these tools lock Hsp70 in complex with onco-client proteins and effectively isolate Hsp70 complexes for identification through biochemical techniques. Using these tools we provide proof-of-concept analyses that glimpse into the complex roles played by Hsp70 in maintaining a multitude of cell-specific malignancy-driving proteins. Significance: The knowledge derived from the use of such reagents will be extremely valuable not only to understand tumor-specific roles of Hsp70 and associated mechanisms but also to develop rational strategies for the clinical implementation of these agents to cancer treatment. They may also provide clues on the altered functional proteome in individual tumors, a quest yet elusive by today's proteomics methods. Citation Format: Anna A. Rodina, Tony Taldone, Yanlong Kang, Pallav Patel, John Koren, Pengrong Yan, Erica DaGama Gomes, Chenghua Yang, Maulik Patel, Liza Shrestha, Stefan Ochiana, Ronnie Maharaj, Alexander Gozman, Marc Cox, Hediye Erdjument-Bromage, Ronald Hendrickson, Leandro Cerchietti, Ari Melnick, Monica Guzman, Gabriela Chiosis. Development of chemical tools to study the endogenous Hsp70 interactome in malignant cells. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1733. doi:10.1158/1538-7445.AM2015-1733

Background: Hsp70, a molecular chaperone responsible, in part, for the folding of nascent peptides following translation, has been implicated as a survival factor and a poor prognostic marker in cancer cells. These pro-cancer mechanisms originate in the ability of Hsp70 to preserve and maintain oncogenic and transformative proteins responsible for the cancer phenotype. Hsp70 is a stress response protein such that expression increases under proteomic/proteotoxic stress events. This increased expression is also evident in cancer cells, an environment under proteomic stress brought on by transformation, and is known to be protective against programmed cell death. Hypothesis: We predict that by interrupting the chaperoning capacity of Hsp70 through allosteric inhibition, we can destabilize oncogenic proteins dependent on Hsp70 for structure and function. Additionally, as Hsp70 is a survival factor, we believe that a loss of Hsp70 activity will result in cancer specific cell death both in vitro and in vivo. Approach: Using chemical tools, primarily novel allosteric Hsp70 inhibiting small molecules, we will determine the fate of oncogenic proteins dependent on Hsp70 for stability. We will also examine the cellular response to the disruption of cancer-specific networks which require Hsp70. In vivo tumor models will be used to examine the pharmacokinetics and pharmacodynamics of small molecule Hsp70 inhibitors and to evaluate the therapeutic potential of Hsp70 inhibition. Significance: The stress response machinery is responsible for the stability of proteins, maintenance of signaling pathways, and evasion from programmed cell death while a cell is under stress; stressors including oncogenic transformation. These pathways maintained by the molecular chaperones have been directly linked to deleterious cancer phenotypes including aggressiveness and the emergence of therapeutic resistances. Targeted therapeutics, and uniquely those targeting the molecular chaperone system, can provide therapeutic options capable of ablating the specific mechanisms involved in proteomic stability and cell survival unique to each tumor cell; effects which can be delivered with minimal effect to normal tissue. This work highlights the potential for therapeutics targeting Hsp70 as anti-cancer agents. Citation Format: John Koren, Chao Xu, Anna Rodina, Liza Shrestha, Tony Taldone, Gabriela Chiosis. Allosteric Hsp70-family inhibitors as targeted anticancer therapeutics. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1740. doi:10.1158/1538-7445.AM2015-1740