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Identifying neoadjuvant chemotherapy (NAC) response in patients with muscle invasive bladder cancer (MIBC) has had limited success based on clinicopathological features and molecular subtyping. Identification of chemotherapy responsive cohorts would facilitate delivery to those most likely to benefit.Develop a molecular signature that can identify MIBC NAC responders (R) and non-responders (NR) using a cohort of known NAC response phenotypes, and better understand differences in molecular pathways and subtype classifications between NAC R and NR.Presented are the messenger RNA (mRNA) and microRNA (miRNA) differential expression profiles from initial transurethral resection of bladder tumor (TURBT) specimens of a discovery cohort of MIBC patients consisting of 7 known NAC R and 11 NR, and a validation cohort consisting of 3 R and 5 NR. Pathological response at time of cystectomy after NAC was used to classify initial TURBT specimens as R (pT0) versus NR (≥pT2). RNA and miRNA from FFPE blocks were sequenced using RNAseq and qPCR, respectively.The discovery cohort had 2309 genes, while the validation cohort had 602 genes and 13 miRNA differentially expressed between R and NR. Gene set enrichment analysis identified mitochondrial gene expression, DNA replication initiation, DNA unwinding in the R discovery cohort and positive regulation of vascular associated smooth muscle cell proliferation in the NR discovery cohort. Canonical correlation (CC) analysis was applied to differentiate R versus NR. 3 CCs (CC13, CC16, and CC17) had an AUCgt;0.65 in the discovery and validation dataset. Gene ontology enrichment showed CC13 as nucleoside triphosphate metabolic process, CC16 as cell cycle and cellular response to DNA damage, CC17 as DNA packaging complex. All patients were classified using established molecular subtypes: Baylor, UNC, CIT, Lund, MD Anderson, TCGA, and Consensus Class. The MD Anderson p53-like subtype, CIT MC4 subtype and Consensus Class stroma rich subtype had the strongest correlation with a NR phenotype, while no subtype had a strong correlation with the R phenotype.Our results identify molecular signatures that can be used to differentiate MIBC NAC R versus NR, salient molecular pathway differences, and highlight the utility of molecular subtyping in relation to NAC response.

Some patients with therapy-related myeloid neoplasms (t-MN) may have unsuspected inherited cancer predisposition syndrome (CPS). We propose a set of clinical criteria to identify t-MN patients with high risk of CPS (HR-CPS). Among 225 t-MN patients with an antecedent non-myeloid malignancy, our clinical criteria identified 52 (23%) HR-CPS patients. Germline whole-exome sequencing identified pathogenic or likely pathogenic variants in 10 of 27 HR-CPS patients compared to 0 of 9 low-risk CPS patients (37% vs. 0%, p = 0.04). These simple clinical criteria identify t-MN patients most likely to benefit from genetic testing for inherited CPS.

Plasmacytoid dendritic cells [pDCs] represent a rare innate immune subset uniquely endowed with the capacity to produce substantial amounts of type-I interferons. This function of pDCs is critical for effective antiviral defenses and has been implicated in autoimmunity. While IFN-I and select cytokines have been recognized as pDC secreted products, a comprehensive agnostic profiling of the pDC secretome in response to a physiologic stimulus has not been reported. We applied LC-MS/MS to catalogue the repertoire of proteins secreted by pDCs in the unperturbed condition and in response to challenge with influenza H1N1. We report the identification of a baseline pDC secretome, and the repertoire of virus-induced proteins including most type-I interferons, various cytokines, chemokines and granzyme B. Additionally, using single-cell RNA-seq [scRNA-seq], we perform multidimensional analyses of pDC transcriptional diversity immediately ex vivo and following stimulation. Our data evidence preexisting pDC heterogeneity, with subsequent highly specialized roles within the pDC population upon stimulation ranging from dedicated cytokine super-producers to cells with APC-like traits. Dynamic expression of transcription factors and surface markers characterize subclusters within activated pDCs. Integrating the proteomic and transcriptomic datasets confirms the pDC-subcluster origin of the proteins identified in the secretome. Our findings represent the most comprehensive molecular characterization of primary human pDCs at baseline, and in response to influenza virus, reported to date.

Background Endometriosis is a common, complex disorder which is underrecognized and subject to prolonged delays in diagnosis. It is accompanied by significant changes in the eutopic endometrial lining. Methods We have undertaken the first single-cell RNA-sequencing (scRNA-Seq) comparison of endometrial tissues in freshly collected menstrual effluent (ME) from 33 subjects, including confirmed endometriosis patients (cases) and controls as well as symptomatic subjects (who have chronic symptoms suggestive of endometriosis but have not been diagnosed). Results We identify a unique subcluster of proliferating uterine natural killer (uNK) cells in ME-tissues from controls that is almost absent from endometriosis cases, along with a striking reduction of total uNK cells in the ME of cases (p −16). In addition, an IGFBP1+ decidualized subset of endometrial stromal cells are abundant in the shed endometrium of controls when compared to cases (p −16) confirming findings of compromised decidualization of cultured stromal cells from cases. By contrast, endometrial stromal cells from cases are enriched in cells expressing pro-inflammatory and senescent phenotypes. An enrichment of B cells in the cases (p = 5.8 × 10−6) raises the possibility that some may have chronic endometritis, a disorder which predisposes to endometriosis. Conclusions We propose that characterization of endometrial tissues in ME will provide an effective screening tool for identifying endometriosis in patients with chronic symptoms suggestive of this disorder. This constitutes a major advance, since delayed diagnosis for many years is a major clinical problem in the evaluation of these patients. Comprehensive analysis of ME is expected to lead to new diagnostic and therapeutic approaches to endometriosis and other associated reproductive disorders such as female infertility.

Objective We have investigated the molecular function of SCAMP5, a candidate risk gene for SLE exclusively expressed in plasmacytoid dendritic cells (pDCs) among peripheral leucocytes. Methods We tested the independence of the association in SCAMP5 with SLE by performing conditional analyses. We profiled the expression pattern of SCAMP5 among circulating leucocytes at the transcript and protein levels. Using lentiviral vectors, we localised the subcellular distribution of SCAMP5 alongside the interferon secretory pathway. We analysed pDCs for the expression of SCAMP5 and interferon production capacity by SCAMP5 genotype. Finally, we examined pDC-specific SCAMP5 isoforms by total RNAseq analysis and examined for genotype-associated quantitative differences therein. Results A conditional analysis revealed evidence of an independent genetic association of SCAMP5 with SLE. Among circulating leucocytes, SCAMP5 is uniquely expressed in pDCs at the transcript and protein levels, with main presence in the Golgi apparatus and minor presence at the cell periphery. In live cells, SCAMP5 displayed dynamic Golgi-cell surface trafficking and localised with the interferon secretory pathway. SCAMP5 did not differ in expression levels in pDCs between genotyped donors; however, a transient interferon secretory defect was noted in pDCs from donors carrying the risk genotype. Conclusions SCAMP5 constitutes a novel SLE risk gene on the basis of genomic data and expression in a cell type widely implicated in SLE pathogenesis. While we could not find evidence of quantitative expression differences in SCAMP5 between genotyped donors, SCAMP5 remains an attractive gene to explore given its highly restricted expression pattern and colocalisation with interferon secretion.

In this article, we discuss the implementation of several computational techniques that are commonly employed to simulate interactions between biomaterials and cellular systems. These methods include molecular dynamics, biopolymer, and homology modeling, which focus on the atomic structure of biomaterials, electronic structure methods, and free-energy simulations. Challenges involved in applying these techniques and connections to cellular experiments are also addressed. These computational methods are important tools in delineating the molecular mechanisms involved in the interactions between biomaterials and tissue, which govern biocompatibility. They have also been applied in the rational design of biomaterials, as molecular-based models predict likely recognition sequences and the corresponding conformations at the interface between material surface and extracellular matrix and cell membrane. Focusing on these molecular mechanisms will lead to new insights into the bioactivity of existing biomaterials and to the development of improved biomaterials for use in bone tissue repair therapies and targeted drug delivery. The chapter concludes with a discussion of recent applications of computational methods to the rational design of biomaterials, including the creation of surfaces with tailored functionality, computational modeling of the attachment function of fibronectin, and model-based design of tunable nanocarriers for drug delivery.

The EGFR (epidermal growth factor receptor)/ErbB/HER (human EGFR) family of kinases contains four homologous receptor tyrosine kinases that are important regulatory elements in key signalling pathways. To elucidate the atomistic mechanisms of dimerization-dependent activation in the ErbB family, we have performed molecular dynamics simulations of the intracellular kinase domains of three members of the ErbB family (those with known kinase activity), namely EGFR, ErbB2 (HER2) and ErbB4 (HER4), in different molecular contexts: monomer against dimer and wild-type against mutant. Using bioinformatics and fluctuation analyses of the molecular dynamics trajectories, we relate sequence similarities to correspondence of specific bond-interaction networks and collective dynamical modes. We find that in the active conformation of the ErbB kinases, key subdomain motions are co-ordinated through conserved hydrophilic interactions: activating bond-networks consisting of hydrogen bonds and salt bridges. The inactive conformations also demonstrate conserved bonding patterns (albeit less extensive) that sequester key residues and disrupt the activating bond network. Both conformational states have distinct hydrophobic advantages through context-specific hydrophobic interactions. We show that the functional (activating) asymmetric kinase dimer interface forces a corresponding change in the hydrophobic and hydrophilic interactions that characterize the inactivating bond network, resulting in motion of the αC-helix through allostery. Several of the clinically identified activating kinase mutations of EGFR act in a similar fashion to disrupt the inactivating bond network. The present molecular dynamics study reveals a fundamental difference in the sequence of events in EGFR activation compared with that described for the Src kinase Hck.

The ErbB/EGFR/HER family of kinases consists of four homologous receptor tyrosine kinases which are important regulatory elements in many cellular processes, including cell proliferation, differentiation, and migration. Somatic mutations in, or over-expression of, the ErbB family is found in many cancers and is correlated with a poor prognosis; particularly, clinically identified mutations found in non-small-cell lung cancer (NSCLC) of ErbB1 have been shown to increase its basal kinase activity and patients carrying these mutations respond remarkably to the small tyrosine kinase inhibitor gefitinib. Here, we analyze the potential effects of the currently catalogued clinically identified mutations in the ErbB family kinase domains on the molecular mechanisms of kinase activation. Recently, we identified conserved networks of hydrophilic and hydrophobic interactions characteristic to the active and inactive conformation, respectively. Here, we show that the clinically identified mutants influence the kinase activity in distinctive fashion by affecting the characteristic interaction networks.

We describe a hierarchical multiscale computational approach based on molecular dynamics simulations, free energy-based molecular docking simulations, deterministic network-based kinetic modeling, and hybrid discrete/continuum stochastic dynamics protocols to study the dimer-mediated receptor activation characteristics of the Erb family receptors, specifically the epidermal growth factor receptor (EGFR). Through these modeling approaches, we are able to extend the prior modeling of EGF-mediated signal transduction by considering specific EGFR tyrosine kinase (EGFRTK) docking interactions mediated by differential binding and phosphorylation of different C-terminal peptide tyrosines on the RTK tail. By modeling signal flows through branching pathways of the EGFRTK resolved on a molecular basis, we are able to transcribe the effects of molecular alterations in the receptor (e.g., mutant forms of the receptor) to differing kinetic behavior and downstream signaling response. Our molecular dynamics simulations show that the drug sensitizing mutation (L834R) of EGFR stabilizes the active conformation to make the system constitutively active. Docking simulations show preferential characteristics (for wildtype vs. mutant receptors) in inhibitor binding as well as preferential enhancement of phosphorylation of particular substrate tyrosines over others. We find that in comparison to the wildtype system, the L834R mutant RTK preferentially binds the inhibitor erlotinib, as well as preferentially phosphorylates the substrate tyrosine Y1068 but not Y1173. We predict that these molecular level changes result in preferential activation of the Akt signaling pathway in comparison to the Erk signaling pathway for cells with normal EGFR expression. For cells with EGFR over expression, the mutant over activates both Erk and Akt pathways, in comparison to wildtype. These results are consistent with qualitative experimental measurements reported in the literature. We discuss these consequences in light of how the network topology and signaling characteristics of altered (mutant) cell lines are shaped differently in relationship to native cell lines.

Multiscale modeling provides a powerful and quantitative platform for investigating the complexity inherent in intracellular signaling pathways and rationalizing the effects of molecular perturbations on downstream signaling events and ultimately, on the cell phenotype. Here we describe the application of a multiscale modeling scheme to the HER3/ErbB3 receptor tyrosine kinase (RTK) signaling network, which regulates critical cellular processes including proliferation, migration and differentiation. The HER3 kinase is a topic of current interest and investigation, as it has been implicated in mechanisms of resistance to tyrosine kinase inhibition (TKI) of EGFR and HER2 in the treatment of many human malignancies. Moreover, the commonly regarded status of HER3 as a catalytically inactive ‘pseudokinase’ has recently been challenged by our previous study, which demonstrated robust residual kinase activity for HER3. Through our multiscale model, we investigate the most significant molecular interactions that contribute to potential mechanisms of HER3 activity and the physiological relevance of this activity to mechanisms of drug resistance in an ErbB-driven tumor cell in silico. The results of our molecular-scale simulations support the characterization of HER3 as a weakly active kinase that, in contrast to its fully-active ErbB family members, depends upon a unique hydrophobic interface to coordinate the alignment of specific catalytic residues required for its activity. Translating our molecular simulation results of the uniquely active behavior of the HER3 kinase into a physiologically relevant environment, our HER3 signaling model demonstrates that even a weak level of HER3 activity may be sufficient to induce AKT signaling and TKI resistance in the context of an ErbB signaling-dependent tumor cell, and therefore therapeutic targeting of HER3 may represent a superior treatment strategy for specific ErbB-driven cancers.

In this chapter, we discuss the implementation of several computational techniques that are commonly employed to simulate interactions between biomaterials and cellular systems. These methods include molecular dynamics and homology modeling, which focus on the atomic structure of biomaterials, electronic structure methods, and free-energy simulations. Challenges involved in applying these techniques and connections to cellular experiments are also addressed. These computational methods are important tools in delineating the molecular mechanisms involved in the interactions between biomaterials and tissue, which govern biocompatibility. They have also been applied in the rational design of biomaterials, as molecular-based models predict likely recognition sequences and the corresponding conformations at the interface between material surface and extracellular matrix and cell membrane. Focusing on these molecular mechanisms will lead to new insights into the bioactivity of existing biomaterials and to the development of improved biomaterials for use in bone tissue repair therapies. The chapter concludes with a discussion of recent applications of computational methods to the rational design of biomaterials, including the creation of surfaces with tailored functionality and computational modeling of the attachment function of fibronectin.

The complexity in intracellular signaling mechanisms relevant for the conquest of many diseases resides at different levels of organization with scales ranging from the subatomic realm relevant to catalytic functions of enzymes to the mesoscopic realm relevant to the cooperative association of molecular assemblies and membrane processes. Consequently, the challenge of representing and quantifying functional or dysfunctional modules within the networks remains due to the current limitations in our understanding of mesoscopic biology, i.e., how the components assemble into functional molecular ensembles. A multiscale approach is necessary to treat a hierarchy of interactions ranging from molecular (nm, ns) to signaling (microm, ms) length and time scales, which necessitates the development and application of specialized modeling tools. Complementary to multiscale experimentation (encompassing structural biology, mechanistic enzymology, cell biology, and single molecule studies) multiscale modeling offers a powerful and quantitative alternative for the study of functional intracellular signaling modules. Here, we describe the application of a multiscale approach to signaling mediated by the ErbB1 receptor which constitutes a network hub for the cell's proliferative, migratory, and survival programs. Through our multiscale model, we mechanistically describe how point-mutations in the ErbB1 receptor can profoundly alter signaling characteristics leading to the onset of oncogenic transformations. Specifically, we describe how the point mutations induce cascading fragility mechanisms at the molecular scale as well as at the scale of the signaling network to preferentially activate the survival factor Akt. We provide a quantitative explanation for how the hallmark of preferential Akt activation in cell-lines harboring the constitutively active mutant ErbB1 receptors causes these cell-lines to be addicted to ErbB1-mediated generation of survival signals. Consequently, inhibition of ErbB1 activity leads to a remarkable therapeutic response in the addicted cell lines.

The EGFR/ErbB/HER family of kinases contains four homologous receptor tyrosine kinases that are important regulatory elements in key signaling pathways. To elucidate the atomistic mechanisms of activation in the ErbB family, we perform molecular dynamics simulations on the three members of the ErbB family with known kinase activity, EGFR, HER2 (ErbB2) and ErbB4, in different molecular contexts: monomer vs. dimer, wildtype vs. mutant. Using bioinformatics and fluctuation analyses of the molecular dynamics trajectories, we relate sequence similarities to similarities in specific bond-interaction networks and similarities in collective dynamical modes. We find that in the active conformation of the ErbB kinases, key loop motions are coordinated through conserved hydrophilic interactions, an activating bond-network consisting of hydrogen bonds and salt bridges. While the inactive conformations show a less extensive inactivating bond network, they sequester key residues and disrupt the activating bond-network. Both conformational states are also stabilized through context-specific hydrophobic interactions. We show that the functional (activating) asymmetric kinase dimer interface forces a corresponding change in the hydrophobic and hydrophilic interactions characterizing the inactivating bond network, resulting in the motion of the αC-helix through allostery. Some of the clinically identified activating kinase mutations of EGFR also act in a similar fashion, disrupting the inactivating bond network. Our molecular dynamics study reveals a fundamental difference in the sequence of events in EGFR activation in comparison to the Src kinase Hck. This work is funded by NSF grants CBET-0730955 and CBET-0853539.