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Supplementary Figure and Table Legend from Detection of Elevated Plasma Levels of Epidermal Growth Factor Receptor Before Breast Cancer Diagnosis among Hormone Therapy Users

PDF file - 48K, Peptide sequences from proteins identified in immune complexes.

We assessed the autoantibody repertoire of a mouse model engineered to develop breast cancer and the repertoire of autoantibodies in human plasmas collected at a preclinical time point and at the time of clinical diagnosis of breast cancer. In seeking to identify common pathways, networks, and protein families associated with the humoral response, we elucidated the dynamic nature of tumor antigens and autoantibody interactions. Lysate proteins from an immortalized cell line from a MMTV-neu mouse model and from MCF7 human breast cancers were spotted onto nitrocellulose microarrays and hybridized with mouse and human plasma samples, respectively. Immunoglobulin-based plasma immunoreactivity against glycolysis and spliceosome proteins was a predominant feature observed both in tumor-bearing mice and in prediagnostic human samples. Interestingly, autoantibody reactivity was more pronounced further away than closer to diagnosis. We provide evidence for dynamic changes in autoantibody reactivity with tumor development and progression that may depend, in part, on the extent of antigen–antibody interactions. Cancer Res; 73(5); 1502–13. ©2012 AACR.

Supplementary Figure 1 from Detection of Elevated Plasma Levels of Epidermal Growth Factor Receptor Before Breast Cancer Diagnosis among Hormone Therapy Users

PDF file - 81K

PDF file - 54K, Coefficients from linear regression models used for ROC analysis.

SUMMARY Transcriptional programming of the innate immune response is pivotal for host protection. However, the transcriptional mechanisms that link pathogen sensing with innate activation remain poorly under-stood. During HIV-1 infection, human dendritic cells (DCs) can detect the virus through an innate sensing pathway, leading to antiviral interferon and DC maturation. Here, we develop an iterative experimental and computational approach to map the HIV-1 innate response circuitry in monocyte-derived DCs (MDDCs). By integrating genome-wide chromatin accessibility with expression kinetics, we infer a gene regulatory network that links 542 transcription factors with 21,862 target genes. We observe that an interferon response is required, yet insufficient, to drive MDDC maturation and identify PRDM1 and RARA as essential regulators of the interferon response and MDDC maturation, respectively. Our work provides a resource for interrogation of regulators of HIV replication and innate immunity, highlighting complexity and cooperativity in the regulatory circuit controlling the response to infection., Graphical Abstract, In Brief Pathogen sensing leads to host transcriptional reprogramming to protect against infection. However, it is unclear how transcription factor activity is coordinated across the genome. Johnson et al. integrate chromatin accessibility and gene expression data to infer and validate a gene regulatory network that directs the innate immune response to HIV.

Antigen presenting cells such as myeloid dendritic cells (DCs) are key sentinels of the innate immune system. In response to pathogen recognition and innate immune stimulation, DCs transition from an immature to a mature state that is characterized by widespread changes in host gene expression, which include the upregulation of cytokines, chemokines, and costimulatory factors to protect against infection. Several transcription factors are known to drive these gene expression changes, but the mechanisms that negatively regulate DC maturation are less well understood. Here, we identify the transcription factor Interleukin Enhancer Binding Factor 3 (ILF3) as a negative regulator of innate immune responses and DC maturation. Depletion of ILF3 in primary human monocyte-derived DCs (MDDCs) led to increased expression of maturation markers and potentiated innate responses during stimulation with viral mimetics or classic innate agonists. Conversely, overexpression of short or long ILF3 isoforms (NF90 and NF110) suppressed DC maturation and innate immune responses. Through mutagenesis experiments, we found that a nuclear localization sequence in ILF3, and not its dual double-stranded RNA-binding domains (dsRBDs), was required for this function. Mutation of the domain associated with zinc finger (DZF) motif of ILF3’s NF110 isoform blocked its ability to suppress DC maturation. Moreover, RNA-seq analysis indicated that ILF3 regulates genes associated with cholesterol homeostasis in addition to genes associated with DC maturation. Together, our data establish ILF3 as a transcriptional regulator that restrains DC maturation and limits innate immune responses through a mechanism that may intersect with lipid metabolism. 1. NF90 and NF110 isoforms of ILF3 restrain monocyte-derived DC maturation. 2. ILF3 dampens innate sensing of HIV-1 and other PAMPs stimulating TLR7/8 and cGAS. 3. NF110-ILF3 regulates genes associated with DC maturation and cholesterol homeostasis.

Despite widespread use of the bacille Calmette-Guerin (BCG) vaccine, tuberculosis (TB) remains a leading cause of global mortality from a single infectious agent (Mycobacterium tuberculosis or Mtb). Here, over two independent Mtb challenge studies, we demonstrate that subcutaneous vaccination of rhesus macaques (RMs) with rhesus cytomegalovirus vectors encoding Mtb antigen inserts (hereafter referred to as RhCMV/TB)-which elicit and maintain highly effector-differentiated, circulating and tissue-resident Mtb-specific CD4+ and CD8+ memory T cell responses-can reduce the overall (pulmonary and extrapulmonary) extent of Mtb infection and disease by 68%, as compared to that in unvaccinated controls, after intrabronchial challenge with the Erdman strain of Mtb at ∼1 year after the first vaccination. Fourteen of 34 RhCMV/TB-vaccinated RMs (41%) across both studies showed no TB disease by computed tomography scans or at necropsy after challenge (as compared to 0 of 17 unvaccinated controls), and ten of these RMs were Mtb-culture-negative for all tissues, an exceptional long-term vaccine effect in the RM challenge model with the Erdman strain of Mtb. These results suggest that complete vaccine-mediated immune control of highly pathogenic Mtb is possible if immune effector responses can intercept Mtb infection at its earliest stages.

Alveolar macrophages (AMs) are the first cells to be infected during Mycobacterium tuberculosis (M.tb.) infection. Thus, the AM response to infection is the first of many steps leading to initiation of the adaptive immune response required for efficient control of infection. A hallmark of M.tb. infection is the slow initiation of the adaptive response, yet the mechanisms responsible for this are largely unknown. To study the initial AM response to infection, we developed a system to identify, sort, and analyze M.tb.-infected AMs from the lung within the first 10 days of infection. In contrast to what has been previously described using in vitro systems, M.tb.-infected AMs up-regulate a cell-protective antioxidant transcriptional signature that is dependent on the lung environment but not bacterial virulence. Computational approaches including pathway analysis and transcription factor motif enrichment analysis identify NRF2 as a master regulator of the response. Using knockout mouse models, we demonstrate that NRF2 drives expression of the cell-protective signature in AMs and impairs the control of early bacterial growth. AMs up-regulate a substantial pro-inflammatory response to M.tb. infection only 10 days after infection, yet comparisons with bystander AMs from the same infected animals demonstrate that M.tb.-infected AMs generate a less robust inflammatory response than the uninfected cells around them. Our findings demonstrate that the initial macrophage response to M.tb. in the lung is far less inflammatory than has previously been described by in vitro systems and may impede the overall host response to infection.

SummaryTranscriptional programming of the innate immune response is pivotal for host protection. However, the transcriptional mechanisms that link pathogen sensing with innate activation remain poorly understood. During infection with HIV-1, human dendritic cells (DCs) can detect the virus through an innate sensing pathway leading to antiviral interferon and DC maturation. Here, we developed an iterative experimental and computational approach to map the innate response circuitry during HIV-1 infection. By integrating genome-wide chromatin accessibility with expression kinetics, we inferred a gene regulatory network that links 542 transcription factors with 21,862 target genes. We observed that an interferon response is required, yet insufficient to drive DC maturation, and identified PRDM1 and RARA as essential regulators of the interferon response and DC maturation, respectively. Our work provides a resource for interrogation of regulators of HIV replication and innate immunity, highlighting complexity and cooperativity in the regulatory circuit controlling the DC response to infection.Graphical Abstract

Alveolar macrophages (AMs) are the first cells to be infected duringMycobacterium tuberculosis(Mtb) infection. Thus the AM response to infection is the first of many steps leading to initiation of the adaptive immune response, which is required for efficient control of infection. A hallmark of Mtb infection is the delay of the adaptive response, yet the mechanisms responsible for this delay are largely unknown. We developed a system to identify, sort and analyze Mtb-infected AMs from the lung within the first 10 days of infection. In contrast to what has been previously described usingin vitrosystems, we find that Mtb-infected AMs up-regulate a cell-protective antioxidant transcriptional signature that is dependent on the lung environment and not dependent on bacterial virulence. Computational approaches including pathway analysis and transcription factor binding motif enrichment analysis identify Nrf2 as a master regulator of the response of AMs to Mtb infection. Using knock-out mouse models, we demonstrate that Nrf2 drives the expression of the cell protective transcriptional program and impairs the ability of the host to control bacterial growth over the first 10 days of infection. Mtb-infected AMs exhibit a highly delayed pro-inflammatory response, and comparisons with uninfected AMs from the same infected animals demonstrate that inflammatory signals in the lung environment are blocked in the Mtb-infected cells. Thus, we have identified a novel lung-specific transcriptional response to Mtb infection that impedes AMs from responding rapidly to intracellular infection and thereby hinders the overall immune response.One Sentence SummaryIn response to Mtb infectionin vivo, alveolar macrophages fail to up-regulate the canonical pro-inflammatory innate response and instead induce an Nrf2-dependent cell protective transcriptional program, which in turn impairs the host’s control of bacterial growth.

Alveolar macrophages (AMs) are the first cells to be infected during Mycobacterium tuberculosis (M.tb.) infection. Thus the AM response to infection is the first of many steps leading to initiation of the adaptive immune response, required for efficient control of infection. A hallmark of M.tb. infection is the slow initiation of the adaptive response, yet the mechanisms responsible for this are largely unknown. To study the initial AM response to infection, we developed a system to identify, sort and analyze M.tb.-infected AMs from the lung within the first 10 days of infection. In contrast to what has been previously described using in vitro systems, M.tb.-infected AMs up-regulate a cell-protective antioxidant transcriptional signature that is dependent on the lung environment but not bacterial virulence. Computational approaches including pathway analysis and transcription factor motif enrichment analysis identify NRF2 as a master regulator of the response. Using knock-out mouse models, we demonstrate that NRF2 drives expression of the cell protective signature in AMs and impairs the control of early bacterial growth. AMs up-regulate a significant pro-inflammatory response to M.tb. infection only 10 days following infection, yet comparisons with bystander AMs from the same infected animals demonstrate that M.tb.-infected AMs generate a less robust inflammatory response than the uninfected cells around them. Our findings demonstrate that the initial macrophage response to M.tb. in the lung is far less inflammatory than has previously been described by in vitro systems and may impede the overall host response to infection.

Transcriptional programming of the innate immune response is pivotal for host protection. However, the transcriptional mechanisms that link pathogen sensing with innate activation remain poorly understood. During infection with HIV-1, human dendritic cells (DCs) can detect the virus through an innate sensing pathway leading to antiviral type I interferon and DC maturation. Here, we have developed an iterative experimental and computational approach to map the innate response circuitry during HIV-1 infection. By integrating genome-wide chromatin accessibility with expression kinetics, we have inferred a gene regulatory network that links 542 transcription factors (TFs) with 21,862 target genes. Through genetic perturbation and drug treatments we identify PRDM1 and RARA as essential regulators of the interferon response and DC maturation, respectively. Our work provides a resource for interrogation of regulators of HIV replication and innate immunity, highlighting the complexity and cooperativity in the regulatory circuit controlling the DC response to HIV-1 infection.

Although the identification of peripheral blood biomarkers would enhance early detection strategies for breast cancer, the discovery of protein markers has been challenging. In this study, we sought to identify coordinated changes in plasma proteins associated with breast cancer based on large-scale quantitative mass spectrometry. We analyzed plasma samples collected up to 74 weeks before diagnosis from 420 estrogen receptor (ER)+ cases and matched controls enrolled in the Women's Health Initiative cohort. A gene set enrichment analysis was applied to 467 quantified proteins, linking their corresponding genes to particular biologic pathways. On the basis of differences in the concentration of individual proteins, glycolysis pathway proteins exhibited a statistically significant difference between cases and controls. In particular, the enrichment was observed among cases in which blood was drawn closer to diagnosis (effect size for the 0–38 weeks prediagnostic group, 1.91; P, 8.3E-05). Analysis of plasmas collected at the time of diagnosis from an independent set of cases and controls confirmed upregulated levels of glycolysis proteins among cases relative to controls. Together, our findings indicate that the concomitant release of glycolysis proteins into the plasma is a pathophysiologic event that precedes a diagnosis of ER+ breast cancer. Cancer Res; 72(8); 1935–42. ©2012 AACR.

High-throughput technologies can now identify hundreds of candidate protein biomarkers for any disease with relative ease. However, because there are no assays for the majority of proteins and de novo immunoassay development is prohibitively expensive, few candidate biomarkers are tested in clinical studies. We tested whether the analytical performance of a biomarker identification pipeline based on targeted mass spectrometry would be sufficient for data-dependent prioritization of candidate biomarkers, de novo development of assays and multiplexed biomarker verification. We used a data-dependent triage process to prioritize a subset of putative plasma biomarkers from >1,000 candidates previously identified using a mouse model of breast cancer. Eighty-eight novel quantitative assays based on selected reaction monitoring mass spectrometry were developed, multiplexed and evaluated in 80 plasma samples. Thirty-six proteins were verified as being elevated in the plasma of tumor-bearing animals. The analytical performance of this pipeline suggests that it should support the use of an analogous approach with human samples.

Applying advanced proteomic technologies to prospectively collected specimens from large studies is one means of identifying preclinical changes in plasma proteins that are potentially relevant to the early detection of diseases such as breast cancer. We conducted 14 independent quantitative proteomics experiments comparing pooled plasma samples collected from 420 estrogen receptor–positive (ER+) breast cancer patients ≤17 months before their diagnosis and matched controls. Based on the more than 3.4 million tandem mass spectra collected in the discovery set, 503 proteins were quantified, of which 57 differentiated cases from controls with a P value of

Summary Myeloid dendritic cells (DCs) have the innate capacity to sense pathogens and orchestrate immune responses. However, DCs do not mount efficient immune responses to HIV-1, primarily due to restriction of virus reverse transcription, which prevents accumulation of viral cDNA and limits its detection through the cGAS-STING pathway. By allowing reverse transcription to proceed, we find that DCs detect HIV-1 in distinct phases, before and after virus integration. Blocking integration suppresses, but does not abolish, activation of the transcription factor IRF3, downstream interferon (IFN) responses, and DC maturation. Consistent with two stages of detection, HIV-1 "primes" chromatin accessibility of innate immune genes before and after integration. Once primed, robust IFN responses can be unmasked by agonists of the innate adaptor protein, MyD88, through a process that requires cGAS, STING, IRF3, and nuclear factor κB. Thus, HIV-1 replication increases material available for sensing, and discrete inflammatory inputs tune cGAS signaling to drive DC maturation.

Objective We attempted to elucidate possible pathogenetic mechanisms in scleroderma by analysis of gene expression patterns of purified monocytes and lymphocytes, as well as protein profiles of cytokines and growth factors. Methods Expression analysis was performed on messenger RNA (mRNA) from cells that had been purified with magnetic beads. Plasma samples from the same patients were used for multiplex cytokine analysis. Potential sources of proteins were also examined by in situ hybridization of skin specimens. Results A total of 1,800 genes from monocytes and 863 genes from CD4+ T cells were differentially expressed in scleroderma patients. As observed by other investigators using unfractionated peripheral blood cells from patients with autoimmune connective tissue diseases, the cell type–specific analyses of our scleroderma samples showed expression of genes suggesting the presence of interferon-α (IFNα), despite the apparent absence of this cytokine in plasma. IFNα RNA was, however, expressed at enhanced levels in vascular and perivascular cells in scleroderma skin samples. While levels of interleukin-1α (IL-1α) and IL-16 were among 10 proteins found to be significantly elevated in scleroderma patients, none of the large panel of plasma cytokines we analyzed correlated with the expression levels of putative IFN response genes. Conclusion The pattern of up-regulation of mRNA in both the monocytes and CD4 lymphocytes of scleroderma patients, together with the detection of IFNα RNA in the microvasculature, suggests that leukocytes respond to this cytokine locally in the vessels. Detection of high levels of IL-1α and IL-16 in plasma and the independence of these protein levels from the IFN signature, implicates an independent contribution of other cytokines to immune activation and/or inflammation in scleroderma.

Interaction between the E2 protein and E1 helicase of human papillomaviruses (HPVs) is essential for the initiation of viral DNA replication. We recently described a series of small molecules that bind to the N-terminal transactivation domain (TAD) of HPV type 11 E2 and inhibits its interaction with E1 in vitro and in cellular assays. Here we report the crystal structures of both the HPV11 TAD and of a complex between this domain and an inhibitor, at 2.5- and 2.4-A resolution, respectively. The HPV11 TAD structure is very similar to that of the analogous domain of HPV16. Inhibitor binding caused no significant alteration of the protein backbone, but movements of several amino acid side chains at the binding site, in particular those of Tyr-19, His-32, Leu-94, and Glu-100, resulted in the formation of a deep hydrophobic pocket that accommodates the indandione moiety of the inhibitor. Mutational analysis provides functional evidence for specific interactions between Tyr-19 and E1 and between His-32 and the inhibitor. A second inhibitor molecule is also present at the binding pocket. Although evidence is presented that this second molecule makes only weak interactions with the protein and is likely an artifact of crystallization, its presence defines additional regions of the binding pocket that could be exploited to design more potent inhibitors.

Metabolic diseases such as obesity and atherosclerosis result from complex interactions between environmental factors and genetic variants. A panel of chromosome substitution strains (CSSs) was developed to characterize genetic and dietary factors contributing to metabolic diseases and other biological traits and biomedical conditions. Our goal here was to identify quantitative trait loci (QTLs) contributing to obesity, energy expenditure, and atherosclerosis. Parental strains C57BL/6 and A/J together with a panel of 21 CSSs derived from these progenitors were subjected to chronic feeding of rodent chow and atherosclerotic (females) or diabetogenic (males) test diets, and evaluated for a variety of metabolic phenotypes including several traits unique to this report, namely fat pad weights, energy balance, and atherosclerosis. A total of 297 QTLs across 35 traits were discovered, two of which provided significant protection from atherosclerosis, and several dozen QTLs modulated body weight, body composition, and circulating lipid levels in females and males. While several QTLs confirmed previous reports, most QTLs were novel. Finally, we applied the CSS quantitative genetic approach to energy balance, and identified three novel QTLs controlling energy expenditure and one QTL modulating food intake. Overall, we identified many new QTLs and phenotyped several novel traits in this mouse model of diet-induced metabolic diseases.

It is common practice to adjust the maximum step size during Monte Carlo simulations to achieve a target fraction of accepted trial moves. Although simulation experts are well aware that this procedure is technically incorrect, the continuing publication of studies that employ it indicates that the pitfalls are not more widely known, or at least are assumed to be negligible. In this pedagogical Letter, it is shown that dynamic step size adjustment may lead to unwanted correlations and statistical undersampling of flat regions of the potential energy surface, thereby violating balance and producing systematic errors. A variety of examples highlight the conditions where the problem is likely to be worst.

We assessed the autoantibody repertoire of a mouse model engineered to develop breast cancer and the repertoire of autoantibodies in human plasmas collected at a preclinical time point and at the time of clinical diagnosis of breast cancer. In seeking to identify common pathways, networks, and protein families associated with the humoral response, we elucidated the dynamic nature of tumor antigens and autoantibody interactions. Lysate proteins from an immortalized cell line from a MMTV-neu mouse model and from MCF7 human breast cancers were spotted onto nitrocellulose microarrays and hybridized with mouse and human plasma samples, respectively. Immunoglobulin-based plasma immunoreactivity against glycolysis and spliceosome proteins was a predominant feature observed both in tumor-bearing mice and in prediagnostic human samples. Interestingly, autoantibody reactivity was more pronounced further away than closer to diagnosis. We provide evidence for dynamic changes in autoantibody reactivity with tumor development and progression that may depend, in part, on the extent of antigen–antibody interactions. Cancer Res; 73(5); 1502–13. ©2012 AACR.

In an attempt to identify prostate cancer biomarkers with greater diagnostic and prognostic capabilities, we have developed an integrative proteomic discovery workflow focused on N-linked glycoproteins that refines the target selection process. In this work, hydrazide-based chemistry was used to identify N-linked glycopeptides from 22Rv1 prostate cancer cells cultured in vitro, which were compared with glycopeptides identified from explanted 22Rv1 murine tumor xenografts. One hundred and four human glycoproteins were identified in the former analysis and 75 in the latter, with 40 proteins overlapping between data sets. Of the 40 overlapping proteins, 80% have multiple literature references to the neoplastic process and ∼40% to prostatic neoplasms. These include a number of well-known prostate cancer-associated biomarkers, such as prostate-specific membrane antigen (PSMA). By integrating gene expression data and available literature, we identified members of the overlap data set that deserve consideration as potential prostate cancer biomarkers. Specifically, the identification of the extracellular domain of protein tyrosine phosphatase receptor type F (PTPRF) was of particular interest due to the direct involvement of PTPRF in the control of β-catenin signaling, as well as dramatically elevated gene expression levels in the prostate compared to other tissues. In this investigation, we demonstrate that the PTPRF E-subunit is more abundant in human prostate tumor tissue compared to normal control and also detectable in murine plasma by immunoblot and ELISA. Specifically, PTPRF distinguishes between animals xenografted with the 22Rv1 cells and control animals as early as 14 days after implantation. This result suggests that the ectodomain of PTPRF has the potential to function as a novel plasma or tissue-based biomarker for prostate cancer. The workflow described adds to the literature of potential biomarker candidates for prostate cancer and demonstrates a pathway to developing new diagnostic assays.

Background We used intensive modern proteomics approaches to identify predictive proteins in ovary cancer. We identify up-regulated proteins in both serum and peritoneal fluid. To evaluate the overall performance of the approach we track the behavior of 20 validated markers across these experiments. Methodology Mass spectrometry based quantitative proteomics following extensive protein fractionation was used to compare serum of women with serous ovarian cancer to healthy women and women with benign ovarian tumors. Quantitation was achieved by isotopically labeling cysteine amino acids. Label-free mass spectrometry was used to compare peritoneal fluid taken from women with serous ovarian cancer and those with benign tumors. All data were integrated and annotated based on whether the proteins have been previously validated using antibody-based assays. Findings We selected 54 quantified serum proteins and 358 peritoneal fluid proteins whose case-control differences exceeded a predefined threshold. Seventeen proteins were quantified in both materials and 14 are extracellular. Of 19 validated markers that were identified all were found in cancer peritoneal fluid and a subset of 7 were quantified in serum, with one of these proteins, IGFBP1, newly validated here. Conclusion Proteome profiling applied to symptomatic ovarian cancer cases identifies a large number of up-regulated serum proteins, many of which are or have been confirmed by immunoassays. The number of currently known validated markers is highest in peritoneal fluid, but they make up a higher percentage of the proteins observed in both serum and peritoneal fluid, suggesting that the 10 additional markers in this group may be high quality candidates.

The classical 19th century thermodynamic inequalities of Clausius and Helmholtz are applied to the calculation of entropy and free energy changes by computer simulation. The irreversibility of finite-time thermodynamic paths is exploited to obtain upper and lower bounds on these quantities. Schrodinger's microscopic interpretation of heat and work provides the basis for a literal implementation of the key historical concepts on the computer using the Monte Carlo algorithm of Metropolis. Coupling schemes, paths, and reference states are variationally optimized to improve the convergence of the simulated properties, and a newly introduced variational flexibility, metric scaling, is overviewed. Reasons for expecting limiting power laws for the convergence are outlined.

Multiple TLR agonists have been shown to have antitumor effects in animal models. However, the therapeutic efficacy of TLR agonist monotherapy in cancer treatment has been limited, and the mechanisms of failure remain unknown. We demonstrate that topical treatment with a TLR-7 agonist, imiquimod, can elicit significant regression of spontaneous breast cancers in neu transgenic mice, a model of human HER-2/neu+ breast cancer. However, tumor growth progressed once imiquimod therapy was ended. Gene expression analysis using tumor-derived RNA demonstrated that imiquimod induced high levels of IL-10 in addition to TNF-α and IFN-γ. Elevated levels of circulating IL-10 were also detected in sera from imiquimod-treated mice. Elevated serum IL-10 appeared to be derived from IL-10 and dual cytokine secreting (IFN-γ+ and IL-10+) CD4+ T cells rather than CD4+CD25+Foxp3+ T regulatory cells, which were also induced by imiquimod treatment. Blockade of IL-10, but not TGF-β, enhanced the antitumor effect of imiquimod by significantly prolonging survival in treated mice. These data suggest that the excessive inflammation induced by TLR agonists may result in a self-regulatory immunosuppression via IL-10 induction and that blocking IL-10 could enhance the therapeutic efficacy of these agents.

The highly variable clinical phenotype observed in patients homozygous for the C282Y mutation of the hereditary hemochromatosis gene (HFE) is likely due to the influence of non-HFE modifier genes. The primary functional abnormality causing iron overload in hemochromatosis is hyper-absorption of dietary iron. We found that iron absorption in inbred mice varies in a strain-specific manner, as does the pattern of iron distribution to the liver and spleen. A/J mice absorbed approximately twice the amount of 59Fe delivered by gavage compared to the C57BL/6 strain. Genetic comparisons between A/J and C57BL/6 were facilitated by the availability of consomic chromosome substitution strains (CSS). Each CSS has an individual chromosome pair from A/J on an otherwise C57BL/6J background. We found that iron absorption and iron content in liver and in spleen were continuous variables suggesting that each trait is under multigenic control. No trait co-segregated among the CSS. Chromosome 5 from A/J, however, imparted the highest iron absorption phenotype and multiple CSS had absorption levels equivalent to A/J. Chromosomes 9 and X were associated with high spleen iron content. These data suggest that multiple genes contribute to the regulation of iron absorption and that individual organ iron phenotypes are independently regulated.

The streptavidin–biotin system has provided a unique opportunity to investigate the molecular details of ligand dissociation pathways. An underlying mechanistic question is whether ligand dissociation proceeds with a relatively ordered process of bond breaking and ligand escape. Here we report a joint computational and crystallographic study of the earliest events in biotin dissociation. In molecular dynamics potential of mean force simulations, a water molecule from a defined access channel intercalated into the hydrogen bond between Asp 128 and biotin, bridging them and stabilizing an intermediate state. In forced biotin dissociation simulations, this event led to subsequent bond breaking steps and ligand escape. In equilibrium simulations, the water molecule was sometimes observed to move back to the access channel with re-formation of the biotin hydrogen bond. Analysis of streptavidin crystal structures revealed a close overlap of crystallographically defined and simulated waters in the water access channel. These results suggest that biotin dissociation is initiated by stochastic coupling of water entry with lengthening of a specific biotin hydrogen-bonding interaction.

The classical 19th century thermodynamic inequalities of Clausius and Helmholtz are applied to the calculation of entropy and free energy changes by computer simulation. The irreversibility of finite-time thermodynamic paths is exploited to obtain upper and lower bounds on these quantities. Schrodinger's microscopic interpretation of heat and work provides the basis for a literal implementation of the key historical concepts on the computer using the Monte Carlo algorithm of Metropolis. Coupling schemes, paths, and reference states are variationally optimized to improve the convergence of the simulated properties, and a newly introduced variational flexibility, metric scaling, is overviewed. Reasons for expecting limiting power laws for the convergence are outlined.

We assessed the circulating autoantibody repertoire in breast cancer using genetically engineered mouse models and human plasmas collected at a pre-clinical time point and at the time of clinical diagnosis of breast cancer. We aimed to identify common pathways, networks and protein families associated with the humoral response to tumors and to elucidate the dynamic nature of tumor antigens and autoantibody interactions in ER+ and triple negative breast cancer. Lysate proteins from immortalized mouse cell lines from MMTV-neu and C3(1)-T mouse models and from the MCF7 and MDA-MB-231 human breast cancer cell lines were spotted onto nitrocellulose microarrays and hybridized with mouse and human plasma samples, respectively. Ig-based plasma immunoreactivity against glycolysis and spliceosome proteins was a predominant feature observed both in MMTV-neu tumor bearing mice and in pre-diagnostic ER+ human samples. A cytoskeletal signature was uniquely observed in C3(1)-T mice and in human patients with triple negative breast cancer. We provide evidence for dynamic changes in autoantibody reactivity and in antigen-antibody interactions with tumor development and progression. Citation Format: Jon Ladd, Melissa Johnson, Timothy Chao, Alice Chin, Sharon Pitteri, Jianning Mao, Lynn M. Amon, Martin McIntosh, Paul Lampe, Christopher Li, Ross Prentice, Nora Disis, Samir Hanash. Dynamics changes in antigen-autoantibody profiles involving glycolysis and spliceosome proteins precede a diagnosis of ER+ and triple negative breast cancer among post-menopausal women. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2491. doi:10.1158/1538-7445.AM2013-2491

Integrative proteomics and genomics supports a role for interferon gamma in the pathogenesis of Kaposi sarcoma and finds multiple candidate diagnostic proteins for early detection or prevention Lynn Amon, Jennifer Gross, Jackson Orem, Innocent Mutyaba, Warren Phipps, Kurt Diem, Meei-Li Huang, Lawrence Corey, Martin McIntosh, Corey Casper From 12 International Conference on Malignancies in AIDS and Other Acquired Immunodeficiencies (ICMAOI) Bethesda, MD, USA. 26-27 April, 2010

Background Women's Health Initiative randomized trials of postmenopausal hormone therapy reported intervention effects on several clinical outcomes, with some important differences between estrogen alone and estrogen plus progestin. The biologic mechanisms underlying these effects, and these differences, have yet to be fully elucidated. Methods Baseline serum samples were compared with samples drawn 1 year later for 50 women assigned to active hormone therapy in both the estrogen-plus-progestin and estrogen-alone randomized trials, by applying an in-depth proteomic discovery platform to serum pools from 10 women per pool. Results In total, 378 proteins were quantified in two or more of the 10 pooled serum comparisons, by using strict identification criteria. Of these, 169 (44.7%) showed evidence (nominal P < 0.05) of change in concentration between baseline and 1 year for one or both of estrogen-plus-progestin and estrogen-alone groups. Quantitative changes were highly correlated between the two hormone-therapy preparations. A total of 98 proteins had false discovery rates < 0.05 for change with estrogen plus progestin, compared with 94 for estrogen alone. Of these, 84 had false discovery rates