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While the past decade has seen meaningful improvements in clinical outcomes for multiple myeloma patients, a subset of patients do not benefit from current therapeutics for unclear reasons. Many gene expression-based models of risk have been developed, but each model uses a different combination of genes and often involve assaying many genes making them difficult to implement. We organized the Multiple Myeloma DREAM Challenge, a crowdsourced effort to develop models of rapid progression in newly diagnosed myeloma patients and to benchmark these against previously published models. This effort lead to more robust predictors and found that incorporating specific demographic and clinical features improved gene expression-based models of high risk. Furthermore, post challenge analysis identified a novel expression-based risk marker and histone modifier,PHF19, which featured prominently in several independent models. Lastly, we show that a simple four feature predictor composed of age, International Staging System stage (ISS), and expression ofPHF19andMMSETperforms similarly to more complex models with many more gene expression features included.Key pointsMost comprehensive and unbiased assessment of prognostic biomarkers in MM resulting in a robust and parsimonious model.Identification ofPHF19as the expression based biomarker most strongly associated with rapid progression in MM patients.

Avadomide is a cereblon E3 ligase modulator and a potent antitumor and immunomodulatory agent. Avadomide trials are challenged by neutropenia as a major adverse event and a dose-limiting toxicity. Intermittent dosing schedules supported by preclinical data provide a strategy to reduce frequency and severity of neutropenia; however, the identification of optimal dosing schedules remains a clinical challenge. Quantitative systems pharmacology (QSP) modeling offers opportunities for virtual screening of efficacy and toxicity levels produced by alternative dose and schedule regimens, thereby supporting decision-making in translational drug development. We formulated a QSP model to capture the mechanism of avadomide-induced neutropenia, which involves cereblon-mediated degradation of transcription factor Ikaros, resulting in a maturation block of the neutrophil lineage. The neutropenia model was integrated with avadomide-specific pharmacokinetic and pharmacodynamic models to capture dose-dependent effects. Additionally, we generated a disease-specific virtual patient population to represent the variability in patient characteristics and response to treatment observed for a diffuse large B-cell lymphoma trial cohort. Model utility was demonstrated by simulating the avadomide effect in the virtual population for various dosing schedules and determining the incidence of high-grade neutropenia, its duration, and the probability of recovery to low-grade neutropenia.

Background The tumor microenvironment (TME) is increasingly appreciated as an important determinant of cancer outcome, including in multiple myeloma (MM). However, most myeloma microenvironment studies have been based on bone marrow (BM) aspirates, which often do not fully reflect the cellular content of BM tissue itself. To address this limitation in myeloma research, we systematically characterized the whole bone marrow (WBM) microenvironment during premalignant, baseline, on treatment, and post-treatment phases. Methods and findings Between 2004 and 2019, 998 BM samples were taken from 436 patients with newly diagnosed MM (NDMM) at the University of Arkansas for Medical Sciences in Little Rock, Arkansas, United States of America. These patients were 61% male and 39% female, 89% White, 8% Black, and 3% other/refused, with a mean age of 58 years. Using WBM and matched cluster of differentiation (CD)138-selected tumor gene expression to control for tumor burden, we identified a subgroup of patients with an adverse TME associated with 17 fewer months of progression-free survival (PFS) (95% confidence interval [CI] 5–29, 49–69 versus 70–82 months, χ2 p = 0.001) and 15 fewer months of overall survival (OS; 95% CI –1 to 31, 92–120 versus 113–129 months, χ2 p = 0.036). Using immunohistochemistry-validated computational tools that identify distinct cell types from bulk gene expression, we showed that the adverse outcome was correlated with elevated CD8+ T cell and reduced granulocytic cell proportions. This microenvironment develops during the progression of premalignant to malignant disease and becomes less prevalent after therapy, in which it is associated with improved outcomes. In patients with quantified International Staging System (ISS) stage and 70-gene Prognostic Risk Score (GEP-70) scores, taking the microenvironment into consideration would have identified an additional 40 out of 290 patients (14%, premutation p = 0.001) with significantly worse outcomes (PFS, 95% CI 6–36, 49–73 versus 74–90 months) who were not identified by existing clinical (ISS stage III) and tumor (GEP-70) criteria as high risk. The main limitations of this study are that it relies on computationally identified cell types and that patients were treated with thalidomide rather than current therapies. Conclusions In this study, we observe that granulocyte signatures in the MM TME contribute to a more accurate prognosis. This implies that future researchers and clinicians treating patients should quantify TME components, in particular monocytes and granulocytes, which are often ignored in microenvironment studies., Author summary Why was this study done? The cells around a tumor, also known as the tumor microenvironment (TME), can help a tumor grow by suppressing the immune system or fight a tumor by mounting an immune response. Most studies of multiple myeloma (MM) have focused on the tumor itself, rather than the bone marrow (BM) TME in which the tumor is growing. We hypothesized that the MM TME held clues that could help us better treat patients. What did the researchers do and find? We used a gene-expression–based computational technique to determine which cell types were present in patient BM. Patients with BM lacking a family of innate immune cells called granulocytes presented with worse outcomes compared to other patients. As MM progresses from a predisease to a cancerous state, the percentage of granulocytes decreases; the patients with the fewest granulocytes had more serious diseases. What do these findings mean? If granulocytes help myeloma patients respond to therapy, then addressing the decline in granulocytes may improve MM treatment. Patients with MM and few granulocytes in their BM should be watched for worse outcomes.

Avadomide is a cereblon E3 ligase modulator and a potent antitumor and immunomodulatory agent. Avadomide trials are challenged by neutropenia as a major adverse event and a dose-limiting toxicity. Intermittent dosing schedules supported by preclinical data provide a strategy to reduce frequency and severity of neutropenia; however, the identification of optimal dosing schedules remains a clinical challenge. Quantitative systems pharmacology (QSP) modeling offers opportunities for virtual screening of efficacy and toxicity levels produced by alternative dose and schedule regimens, thereby supporting decision-making in translational drug development. We formulated a QSP model to capture the mechanism of avadomide-induced neutropenia, which involves cereblon-mediated degradation of transcription factor Ikaros, resulting in a maturation block of the neutrophil lineage. The neutropenia model was integrated with avadomide-specific pharmacokinetic and pharmacodynamic models to capture dose-dependent effects. Additionally, we generated a disease-specific virtual patient population to represent the variability in patient characteristics and response to treatment observed for a diffuse large B-cell lymphoma trial cohort. Model utility was demonstrated by simulating the avadomide effect in the virtual population for various dosing schedules and determining the incidence of high-grade neutropenia, its duration, and the probability of recovery to low-grade neutropenia. Supplementary Information The online version contains supplementary material available at 10.1208/s12248-021-00623-8.

The maintenance and function of tissues in health and disease depends on cell-cell communication. This work shows how high-level features, representing cell-cell communication, can be defined and used to associate certain signaling ‘axes’ with clinical outcomes. Using cell-sorted gene expression data, we generated a scaffold of cell-cell interactions and define a probabilistic method for creating per-patient weighted graphs based on gene expression and cell deconvolution results. With this method, we generated over 9,000 graphs for TCGA patient samples, each representing likely channels of intercellular communication in the tumor microenvironment. It was shown that particular edges were strongly associated with disease severity and progression, in terms of survival time and tumor stage. Within individual tumor types, there are predominant cell types and the collection of associated edges were found to be predictive of clinical phenotypes. Additionally, genes associated with differentially weighted edges were enriched in Gene Ontology terms associated with tissue structure and immune response. Code, data, and notebooks are provided to enable the application of this method to any expression dataset (https://github.com/IlyaLab/Pan-Cancer-Cell-Cell-Comm-Net).

Despite recent advancements in the treatment of multiple myeloma (MM), nearly all patients ultimately relapse and many become refractory to their previous therapies. Although many therapies exist with diverse mechanisms of action, it is not yet clear how the differences in MM biology across patients impacts the likelihood of success for existing therapies and those in the pipeline. Therefore, we not only need the ability to predict which patients are at high risk for disease progression, but also a means to understand the mechanisms underlying their risk. We hypothesized that knowledge of the biological networks that give rise to MM, specifically the transcriptional regulatory network (TRN) and the mechanisms by which mutations impact gene regulation, would enable improved predictions of disease progression and actionable insights for treatment. Here we present a method to infer TRNs from multi-omics data and apply it to the generation of a MM TRN that links chromosomal abnormalities and somatic mutations to downstream effects on gene expression via perturbation of transcriptional regulators. We find that 141 genetic programs underlie the disease and that the activity profile of these programs fall into one of 25 distinct transcriptional states. These transcriptional signatures prove to be more predictive of outcomes than do mutations and reveal plausible mechanisms for relapse, including the establishment of an immuno-suppressive microenvironment. Moreover, we observe subtype-specific vulnerabilities to interventions with existing drugs and motivate the development of new targeted therapies that appear especially promising for relapsed refractory MM.

Background Mechanistic models, when combined with pertinent data, can improve our knowledge regarding important molecular and cellular mechanisms found in cancer. These models make the prediction of tissue-level response to drug treatment possible, which can lead to new therapies and improved patient outcomes. Here we present a data-driven multiscale modeling framework to study molecular interactions between cancer, stromal, and immune cells found in the tumor microenvironment. We also develop methods to use molecular data available in The Cancer Genome Atlas to generate sample-specific models of cancer. Results By combining published models of different cells relevant to pancreatic ductal adenocarcinoma (PDAC), we built an agent-based model of the multicellular pancreatic tumor microenvironment, formally describing cell type–specific molecular interactions and cytokine-mediated cell-cell communications. We used an ensemble-based modeling approach to systematically explore how variations in the tumor microenvironment affect the viability of cancer cells. The results suggest that the autocrine loop involving EGF signaling is a key interaction modulator between pancreatic cancer and stellate cells. EGF is also found to be associated with previously described subtypes of PDAC. Moreover, the model allows a systematic exploration of the effect of possible therapeutic perturbations; our simulations suggest that reducing bFGF secretion by stellate cells will have, on average, a positive impact on cancer apoptosis. Conclusions The developed framework allows model-driven hypotheses to be generated regarding therapeutically relevant PDAC states with potential molecular and cellular drivers indicating specific intervention strategies.

Luspatercept is a recombinant fusion protein that binds and sequesters several endogenous transforming growth factor-beta superfamily ligands, including growth differentiation factor 11, thereby diminishing Smad2/3 signaling in target cells involved in erythropoiesis. Luspatercept, and its murine analog RAP-536, have been shown to act as erythroid maturation agents via their effects on late-stage erythropoiesis by inducing erythroblast maturation, leading to increases in red blood cells (RBCs) and hemoglobin (Hb). This study demonstrated that thalassemic (th3/+) reticulocytes are unstable, and that RAP-536, in addition to its function as an erythroid maturation agent, modulates the maturation of wild-type (WT) and th3/+ reticulocytes. Furthermore, RAP-536 treatment increased RBCs and decreased bilirubin in a mouse model of alpha-thalassemia (129S-Hba-a1tm1Led/J). To examine whether acute RAP-536 treatment acts on reticulocytes and alters reticulocyte levels in blood, the blood of WT mice was analyzed 3, 12, and 24 hours, and 2, 3, 4, and 7 days after a single dose of RAP-536 (10 or 30 mg/kg) or vehicle. RAP-536 treatment increased RBCs, Hb, and hematocrit significantly at all time points, compared with vehicle. However, in mice treated with RAP-536, reticulocytes in blood decreased significantly on Days 2, 3, and 4 and returned to normal baseline levels on Day 7. Analysis of reticulocyte subpopulations in blood 3 days after RAP-536 treatment showed that the relative percentages of immature reticulocytes (CD71+ or high RNA content) within the blood reticulocyte population decreased, suggesting that reticulocytes released from the bone marrow (BM) were more mature and/or reticulocytes matured faster in blood. A quantitative pharmacology (QP) model was developed to explore which RAP-536-induced modulations of erythropoiesis in WT mice can simulate the experimental observations. The model represents erythroblast, reticulocyte, and RBC (erythrocyte) maturation stages in BM, peripheral blood, and spleen, in the presence or absence of a RAP-536 effect. The QP model consists of a system of ordinary differential equations, with homeostatic parameter values assigned from literature or experimental measures, and RAP-536-perturbed parameter values regressed by fitting the model to erythropoiesis data of RAP-536-treated WT mice. Comparison of model parameters for homeostatic versus RAP-536-perturbed states indicated that RAP-536 leads to an increase in the erythroblast-to-reticulocyte and reticulocyte-to-RBC conversion rates, the transfer of BM reticulocytes to blood, and a delayed increase in erythroblast production. To directly test whether RAP-536 treatment affects reticulocyte development in blood, comparative blood transfusion experiments were performed. Biotinylated GFP+ blood from WT mice (C57BL/6-Tg(UBC-GFP)30Scha/J) and biotinylated GFP− blood from th3/+ beta-thalassemic mice (B6.129P2-Hbb-b1tm1Unc Hbb-b2tm1Unc/J) were co-transfused into GFP− WT recipient mice (C57BL/6J), which were subsequently treated with RAP-536 or vehicle. In the donor reticulocyte population, th3/+ reticulocyte percentage decreased continuously up to 3 days after transfusion, suggesting that many of the th3/+ reticulocytes were eliminated before they could form RBCs. However, compared with vehicle, RAP-536 treatment led to increased persistence of the relative percentages of th3/+ reticulocytes (Figure A). Consequently, 7 days after transfusion, when most reticulocytes have matured to RBCs, the percentage of th3/+ RBC among donor RBCs was higher with RAP-536 (Figure B). Finally, treatment of an alpha-thalassemia mouse model (129S-Hba-a1tm1Led/J) with RAP-536 10 mg/kg for 8 weeks increased RBCs and hematocrit and reduced serum bilirubin, compared with vehicle. These results suggest that RAP-536 is, as previously shown, an erythroid maturation agent, which also modulates reticulocyte maturation in blood. In WT mice, RAP-536 modulated blood reticulocyte dynamics consistent with faster maturation. RAP-536 also prolonged the persistence of th3/+ reticulocytes and maintained a higher frequency of th3/+ RBCs. These data, together with the finding that RAP-536 reduces hemolysis in an experimental alpha-thalassemia disease model, suggest that luspatercept has the potential to improve anemias associated with hemolysis and/or reticulocytosis. Disclosures Acar: Bristol Myers Squibb: Ended employment in the past 24 months. Jupelli:Bristol Myers Squibb: Current Employment. Abbiati:Bristol Myers Squibb: Current Employment. Ramanathan:Acceleron Pharma: Current Employment, Current equity holder in publicly-traded company. Santini:Bristol Myers Squibb: Current equity holder in publicly-traded company, Ended employment in the past 24 months. Ratushny:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Dunshee:Bristol Myers Squibb: Current equity holder in publicly-traded company, Ended employment in the past 24 months; Genentech Inc.: Current Employment, Current equity holder in publicly-traded company. Lopes de Menezes:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. MacBeth:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Suragani:Acceleron Pharma: Current Employment, Current equity holder in publicly-traded company. Loos:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Schwickart:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company.

Failure to clear antigens causes CD8+ T cells to become increasingly hypo-functional, a state known as exhaustion. We combined manually extracted information from published literature with gene expression data from diverse model systems to infer a set of molecular regulatory interactions that underpin exhaustion. Topological analysis and simulation modeling of the network suggests CD8+ T cells undergo 2 major transitions in state following stimulation. The time cells spend in the earlier pro-memory/proliferative (PP) state is a fixed and inherent property of the network structure. Transition to the second state is necessary for exhaustion. Combining insights from network topology analysis and simulation modeling, we predict the extent to which each node in our network drives cells towards an exhausted state. We demonstrate the utility of our approach by experimentally testing the prediction that drug-induced interference with EZH2 function increases the proportion of pro-memory/proliferative cells in the early days post-activation.

The ability to reliably and reproducibly measure any protein of the human proteome in any tissue or cell type would be transformative for understanding systems-level properties as well as specific pathways in physiology and disease. Here, we describe the generation and verification of a compendium of highly specific assays that enable quantification of 99.7% of the 20,277 annotated human proteins by the widely accessible, sensitive, and robust targeted mass spectrometric method selected reaction monitoring, SRM. This human SRMAtlas provides definitive coordinates that conclusively identify the respective peptide in biological samples. We report data on 166,174 proteotypic peptides providing multiple, independent assays to quantify any human protein and numerous spliced variants, non-synonymous mutations, and post-translational modifications. The data are freely accessible as a resource at http://www.srmatlas.org/, and we demonstrate its utility by examining the network response to inhibition of cholesterol synthesis in liver cells and to docetaxel in prostate cancer lines.

Pancreatic ductal adenocarcinoma (PDAC) remains a difficult disease to treat, with few therapies available that target specific patient subgroups. Translational studies in pancreatic cancer can be technically challenging due to biopsy specimen characteristics including low tumor cellularity and dense fibrotic stroma. Resected primary pancreatic tumors obtained during the phase 3 APACT clinical trial (NCT01964430 adjuvant nab-paclitaxel + gemcitabine versus gemcitabine monotherapy n = 866) are a unique resource for characterizing molecular and immune subtypes among PDAC tumors and their association with treatment outcomes in the adjuvant chemotherapy setting. Tumor-infiltrating immune cells were assessed in serial sections of 453 tumors by dual-chromogen immuno-histochemical (IHC) staining (CD4 CD8 CD20 CD163 CMAF CD56 FoxP3 PD-1 PD-L1). Image alignment, segmentation, and spatial localization of stained cells relative to a pan-cytokeratin staining-based tumor epithelial mask was performed using a commercial analysis platform. Expression profiles were obtained for 515 macrodissected tumor biopsy regions by RNA-seq. Transcriptional subtypes were assigned based on schema previously reported by Moffit and Bailey, and molecular pathway correlates were characterized using gene set enrichment analysis. Based on immunochemical staining, higher intratumoral CD8+ or lower CD163+ cell densities were associated with modestly longer disease-free or overall survival in patients treated with nab-paclitaxel plus gemcitabine. The combination of both high CD8+ and low CD163+ cell density was notably associated with longer overall survival compared to other subjects treated with the combination regimen (mOS>55months versus 36 months HR=0.46 p= Citation Format: Thomas Lila, Andrew Biankin, Andrew Browne, David J. Reiss, Brian Lu, Daniel Pierce, Alexander Ratushny, Kao-tai Tsai, Sneh Lata, Sitharthan Kamalakaran, Tomas Babak, Brian Fox, Sam Danziger, Konstantinos Mavrommatis, Matthew W. B. Trotter, David Chang, Fadi Towfic. Multi-omic Profiling of primary pancreatic adenocarcinomas obtained from the APACT adjuvant trial of nab-paclitaxel + gemcitabine vs gemcitabine [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2020 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2020;80(22 Suppl):Abstract nr PO-008.

The R47H variant in the microglial TREM2 receptor is a strong risk factor for Alzheimer’s disease (AD). Loss-of-function mutations in TREM2 or its adaptor TYROBP cause polycystic lipomembranous osteodysplasia with sclerosing leukoencephalopathy, a systemic disease with early onset dementia. To characterize processes affected by the R47H we performed integrative network analysis of genes expressed in brains of AD patients with TREM2 R47H and sporadic AD without the TREM2 variant. In AD patients with TREM2 R47H we identified upregulation of interferon type I response and pro-inflammatory pathways, accompanied by induction of NKG2D stress ligands. In contrast, sporadic AD brains had few perturbed microglial and immune genes. In a human myeloid cell line, THP1, overexpression of normal TREM2 or its knockout revealed a profound effect of TREM2 dosage on gene networks. The effect of TREM2 R47H was complex, consistent with a partial loss of activity in conjunction with some dominant effect on pathways related to vasculature and angiogenesis. Changing the dosage of normal TREM2 in THP1 cells affected the IFN type 1 response signature, however, overexpression of TREM2 R47H was not sufficient to stimulate this pathway. We conclude that TREM2 is involved in control of the IFN type I response in myeloid cells and that its activation in TREM2 R47H AD brains is likely due to a reduced dosage of the normal TREM2 allele. Our findings indicate existence of a microglia-driven AD subtype caused by malfunction of TREM2 and possibly other genes of its network that is distinguished by gene expression phenotype.

The nuclear pore complex is an ancient component of the eukaryotic cell. We show here that an FG nucleoporin, TbNup53b, in trypanosomes has an association with the splicing machinery and roles in gene expression, indicating that moonlighting roles for nucleoporins are highly ancient and present in the earliest eukaryotes., Components of the nuclear periphery coordinate a multitude of activities, including macromolecular transport, cell-cycle progression, and chromatin organization. Nuclear pore complexes (NPCs) mediate nucleocytoplasmic transport, mRNA processing, and transcriptional regulation, and NPC components can define regions of high transcriptional activity in some organisms at the nuclear periphery and nucleoplasm. Lineage-specific features underpin several core nuclear functions and in trypanosomatids, which branched very early from other eukaryotes, unique protein components constitute the lamina, kinetochores, and parts of the NPCs. Here we describe a phenylalanine-glycine (FG)-repeat nucleoporin, TbNup53b, that has dual localizations within the nucleoplasm and NPC. In addition to association with nucleoporins, TbNup53b interacts with a known trans-splicing component, TSR1, and has a role in controlling expression of surface proteins including the nucleolar periphery-located, procyclin genes. Significantly, while several nucleoporins are implicated in intranuclear transcriptional regulation in metazoa, TbNup53b appears orthologous to components of the yeast/human Nup49/Nup58 complex, for which no transcriptional functions are known. These data suggest that FG-Nups are frequently co-opted to transcriptional functions during evolution and extend the presence of FG-repeat nucleoporin control of gene expression to trypanosomes, suggesting that this is a widespread and ancient eukaryotic feature, as well as underscoring once more flexibility within nucleoporin function.

It is known that environmental context influences the degree of regulation at the transcriptional and post-transcriptional levels. However, the principles governing the differential usage and interplay of regulation at these two levels are not clear. Here, we show that the integration of transcriptional and post-transcriptional regulatory mechanisms in a characteristic network motif drives efficient environment-dependent state transitions. Through phenotypic screening, systems analysis, and rigorous experimental validation, we discovered an RNase (VNG2099C) in Halobacterium salinarum that is transcriptionally co-regulated with genes of the aerobic physiologic state but acts on transcripts of the anaerobic state. Through modelling and experimentation we show that this arrangement generates an efficient state-transition switch, within which RNase-repression of a transcriptional positive autoregulation (RPAR) loop is critical for shutting down ATP-consuming active potassium uptake to conserve energy required for salinity adaptation under aerobic, high potassium, or dark conditions. Subsequently, we discovered that many Escherichia coli operons with energy-associated functions are also putatively controlled by RPAR indicating that this network motif may have evolved independently in phylogenetically distant organisms. Thus, our data suggest that interplay of transcriptional and post-transcriptional regulation in the RPAR motif is a generalized principle for efficient environment-dependent state transitions across prokaryotes.

Introduction: It is strikingly difficult to develop successful treatments for PDAC; even with curative resection, most patients die from early occult metastases. Prior studies identified the presence of tumor-infiltrating lymphocytes (TILs) in primary PDAC tumors as having prognostic significance in the PDAC adjuvant setting, sharpening the questions of what fraction of patients have immune-infiltrated tumors and what therapeutic strategies should be pursued in these patients vs. the non-infiltrated group. The phase 3 APACT trial evaluated the use of adjuvant nab-paclitaxel plus gemcitabine vs. gemcitabine in 866 patients with PDAC who had undergone primary tumor resection, with the primary endpoint of disease-free survival evaluated by independent review. We extended studies of the tumor microenvironment of PDAC to a large set of resected APACT primary tumors in an effort to further refine features of tumor or immune infiltrate that influence disease progression and to determine if chemotherapy regimen–specific predictive signatures are identifiable. Tissue analyses for a large subset of APACT samples included RNA-seq, DNA-seq, multiplexed immunohistochemistry (IHC), and proteomics. Methods: We imaged and quantified markers for tumor cells, 7 different immune cells, and 2 immune checkpoint markers using bright-field chromogenic multiplexed IHC from pretreatment samples for more than 500 APACT primary tumor samples. We computationally defined the tumor, tumor margin, and distal stromal (> 150 μm from tumor boundary) regions, and quantified densities and distributions of immune cells in these regions. As part of an initial analysis of more than 400 samples, we applied both unsupervised clustering and supervised classification to these IHC measurements to identify patient subgroups with similar spatial arrangements of immune cells relative to tumor regions. Results: The preliminary analysis of normalized cell densities across all 3 tissue regions revealed 3 patient subgroups: one in which immune cells are mixed within the tumor regions; a second where immune cells approach the tumor boundary but are depleted within the tumor; and a third in which immune cells are depleted in both tumor and its margin, remaining at high densities only in the distal stromal regions. Within these latter subgroups, CD20+, CD4+, and CD8+ cells were more prevalently depleted from tumor and/or margin, whereas CD163+ and CD163+CMAF+ cells showed less of this arrangement. Nearly 85% of patients fell in the second or third patient group. Conclusions: We are pursuing analyses of these data in conjunction with upcoming molecular and genetic profiling data to further elucidate the association of the immune cell populations and these subgroups with clinical outcomes. These data will provide an unprecedented opportunity for exploratory analysis and discovery of immune, molecular, and genetic biomarkers for PDAC patient stratification. Citation Format: David J. Reiss, Thomas Lila, Suzana Couto, Sitharthan Kamalakaran, Yan Ren, Doug Bowman, Amber Ortiz, Maria Wang, Clifton Drew, Kao-Tai Tsai, Mathieu Marella, Brian Fox, Garth McGrath, Matthew Trotter, Fadi Towfic, Ian Cushman, Alexander Ratushny, Brian Lu, Daniel Pierce, Jim Cassidy. Spatial organization of pancreatic ductal adenocarcinoma (PDAC)–associated immune cells from the Adjuvant Pancreatic Adenocarcinoma Clinical Trial (APACT) study [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2019 Sept 6-9; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2019;79(24 Suppl):Abstract nr A43.

Immune cell infiltration of tumors can be an important component for determining patient outcomes, e.g. by inferring immune cell presence by deconvolving gene expression data drawn from a heterogenous mix of cell types. One particularly powerful family of deconvolution techniques uses signature matrices of genes that uniquely identify each cell type as determined from cell type purified gene expression data. Many methods of this type have been recently published, often including new signature matrices appropriate for a single purpose, such as investigating a specific type of tumor. The package ADAPTS helps users make the most of this expanding knowledge base by introducing a framework for cell type deconvolution. ADAPTS implements modular tools for customizing signature matrices for new tissue types by adding custom cell types or building new matrices de novo, including from single cell RNAseq data. It includes a common interface to several popular deconvolution algorithms that use a signature matrix to estimate the proportion of cell types present in heterogenous samples. ADAPTS also implements a novel method for clustering cell types into groups that are hard to distinguish by deconvolution and then re-splitting those clusters using hierarchical deconvolution. We demonstrate that the techniques implemented in ADAPTS improve the ability to reconstruct the cell types present in a single cell RNAseq data set in a blind predictive analysis. ADAPTS is currently available for use in R on CRAN and GitHub.

Background: DLBCL has traditionally been classified by cell of origin (COO) subcategories based on tumor gene expression profiles which include Activated B-Cell (ABC) and Germinal Center B-Cell (GCB). Recently, using tumor samples from patients treated with RCHOP, new classification models have focused on DNA alterations. However, a comprehensive integrative approach using a large transcriptomic data set across both newly diagnosed (nd) and relapsed/refractory (r/r) DLBCL is yet to be accomplished. A robust clustering of this type will allow for identification of biologically driven DLBCL patient subgroups and may predict patient outcome and inform treatment approaches. Methods: RNAseq was performed on a total of 882 DLBCL tumor FFPE biopsies from 2 ndDLBCL cohorts (cohort 1 and 2) and 2 r/r DLBCL cohorts (cohorts 3 and 4). Cohort 1 (N=267) was commercially sourced and served as the discovery cohort. Cohort 2 (N=340) was from the Mayo/Iowa Lymphoma SPORE Molecular Epidemiology Resource (MER) and served as the replication cohort. Cohort 3 (N=189) was from the CC-122-ST-001 and CC-122-DLBCL-001 clinical trials (NCT01421524 and NCT02031419), and cohort 4 (N=86) was from r/r patients from the MER. Clustering input consisted of gene expression data, gene set variation analysis (GSVA) scores computed from the hallmark gene sets of MSigDB gene sets, as well as immune cell abundance estimates from a DLBCL-specific deconvolution method. An integrative clustering method iClusterPlus was applied to the input data to identify patient subgroups. A multinomial generalized linear model classifier was trained on the discovery dataset and applied to cohorts 2, 3, and 4 to assess patterns of gene expression and clinical features among the subgroups. Results: Integrative clustering identified 8 subgroups of ndDLBCL patients (DLBCL1-8; D1-D8) in cohort 1. Classifiers trained on cohort 1 were applied to cohort 2 and the same 8 clusters were identified. Among RCHOP treated patients in cohort 2, subgroups D4 (p Within D4, 92% of patients were ABC, representing a high risk subset of ABC patients. The mEFS in D4 ABCs was 38.2 months, while mEFS of non-D4 ABCs was not reached (p2, compared to 33% of non-D4 with IPI>2 (p D8 represented a high-risk subset which was 73% GCB. The mEFS of D8 GCBs was 5.4 months, while mEFS of non-D8 GCBs was not reached (p In the r/r DLBCL setting, D1-D8 were all present, with an increased prevalence of D4 and D8 in Cohort 3 (30% and 17%, respectively) and Cohort 4 (30% and 14%) compared to the newly diagnosed setting. Mutational data for these cohorts has been collected and is being interpreted in the context of the discovered subgroups. Conclusion: A novel integrative clustering of transformed gene expression data revealed 8 biologically homogeneous groups, two of which had inferior outcomes when treated with RCHOP therapy. Furthermore, these two subgroups were more prevalent in r/r DLBCL. This classification allows for the transcriptomic identification of high-risk patients underserved by RCHOP therapy. *Ortiz, Wenzl and Stokes contributed equally **Gandhi and Novak contributed equally Disclosures Ortiz: Celgene Corporation: Employment, Equity Ownership. Stokes:Celgene Corporation: Employment, Equity Ownership. Huang:Celgene Corporation: Employment, Equity Ownership. Maurer:Celgene: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding. Towfic:Celgene Corporation: Employment, Equity Ownership. Hagner:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Ratushny:Celgene Corporation: Employment, Equity Ownership. McConnell:Celgene Corporation: Employment, Equity Ownership. Danziger:Celgene Corporation: Employment, Equity Ownership. Stong:Celgene Corporation: Employment, Equity Ownership. Lata:Celgene Corporation: Employment, Equity Ownership. Kamalakaran:Celgene Corporation: Employment, Equity Ownership. Mavrommatis:Celgene Corporation: Employment, Equity Ownership. Trotter:Celgene Corporation: Employment, Equity Ownership. Czuczman:Celgene Corporation: Employment, Equity Ownership. Ansell:Seattle Genetics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding. Cerhan:NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding. Nowakowski:Genentech, Inc.: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding. Gandhi:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Novak:Celgene Coorperation: Research Funding.

This chapter summarizes several theoretical studies on the potential for oscillatory behavior of HIV infection at molecular and cellular levels. It discusses the biological relevance of oscillatory systems in the HIV life cycle and touches upon broader perspectives for further theoretical and experimental exploration of system dynamics. The potential interference of HIV oscillatory dynamics at different scales and levels as well as interaction and coevolution with the complex host immune system is also discussed.

The nuclear lamina is a filamentous structure subtending the nuclear envelope and required for chromatin organization, transcriptional regulation and maintaining nuclear structure. The trypanosomatid coiled-coil NUP-1 protein is a lamina component functionally analogous to lamins, the major lamina proteins of metazoa. There is little evidence for shared ancestry, suggesting the presence of a distinct lamina system in trypanosomes. To find additional trypanosomatid lamina components we identified NUP-1 interacting proteins by affinity capture and mass-spectrometry. Multiple components of the nuclear pore complex (NPC) and a second coiled-coil protein, which we termed NUP-2, were found. NUP-2 has a punctate distribution at the nuclear periphery throughout the cell cycle and is in close proximity to NUP-1, the NPCs and telomeric chromosomal regions. RNAi-mediated silencing of NUP-2 leads to severe proliferation defects, gross alterations to nuclear structure, chromosomal organization and nuclear envelope architecture. Further, transcription is altered at telomere-proximal variant surface glycoprotein (VSG) expression sites (ESs), suggesting a role in controlling ES expression, although NUP-2 silencing does not increase VSG switching. Transcriptome analysis suggests specific alterations to Pol I-dependent transcription. NUP-1 is mislocalized in NUP-2 knockdown cells and vice versa, implying that NUP-1 and NUP-2 form a co-dependent network and identifying NUP-2 as a second trypanosomatid nuclear lamina component.

Living systems have a complex hierarchical organization that can be viewed as a set of dynamically interacting subsystems. Thus, to simulate the internal nature and dynamics of the whole biological system we should use the iterative way for a model reconstruction, which is a consistent composition and combination of its elementary subsystems. In accordance with this bottom-up approach, we have developed MAMMOTh (MAthematical Models of bioMOlecular sysTems) database that allows integrating manually curated mathematical models of biomolecular systems, which are fit to the experimental data. The database entries are organized as building blocks in a way that the model parts can be used in different combinations to describe systems with higher organizational level (metabolic pathways and/or transcription regulatory networks). The database supports export of single model or their combinations in SBML or Mathematica standards. The database currently contains more than 100 mathematical models for Escherichia coli elementary subsystems (enzymatic reactions and gene expression regulatory processes) that can be combined in at least 5100 complex/sophisticated models concerning such biological processes as: de novo nucleotide biosynthesis, aerobic/anaerobic respiration, and nitrate/nitrite utilization in E. coli. All current models are functionally interconnected and sufficiently complement public model resources.

Antiviral responses must be tightly regulated to rapidly defend against infection while minimizing inflammatory damage. Type 1 interferons (IFN-I) are crucial mediators of antiviral responses1 and their transcription is regulated by a variety of transcription factors2; principal amongst these is the family of interferon regulatory factors (IRFs)3. The IRF gene regulatory networks are complex and contain multiple feedback loops. The tools of systems biology are well suited to elucidate the complex interactions that give rise to precise coordination of the interferon response. Here we have used an unbiased systems approach to predict that a member of the forkhead family of transcription factors, FOXO3, is a negative regulator of a subset of antiviral genes. This prediction was validated using macrophages isolated from Foxo3-null mice. Genome-wide location analysis combined with gene deletion studies identified the Irf7 gene as a critical target of FOXO3. FOXO3 was identified as a negative regulator of Irf7 transcription and we have further demonstrated that FOXO3, IRF7 and IFN-I form a coherent feed-forward regulatory circuit. Our data suggest that the FOXO3-IRF7 regulatory circuit represents a novel mechanism for establishing the requisite set points in the interferon pathway that balances the beneficial effects and deleterious sequelae of the antiviral response.

Introduction The multiple myeloma (MM) tumor microenvironment (TME) strongly influences patient outcomes as evidenced by the success of immunomodulatory therapies. To develop precision immunotherapeutic approaches, it is essential to identify and enumerate TME cell types and understand their dynamics. Methods We estimated the population of immune and other non-tumor cell types during the course of MM treatment at a single institution using gene expression of paired CD138-selected bone marrow aspirates and whole bone marrow (WBM) core biopsies from 867 samples of 436 newly diagnosed MM patients collected at 5 time points: pre-treatment (N=354), post-induction (N=245), post-transplant (N=83), post-consolidation (N=51), and post-maintenance (N=134). Expression profiles from the aspirates were used to infer the transcriptome contribution of immune and stromal cells in the WBM array data. Unsupervised clustering of these non-tumor gene expression profiles across all time points was performed using the R package ConsensusClusterPlus with Bayesian Information Criterion (BIC) to select the number of clusters. Individual cell types in these TMEs were estimated using the DCQ algorithm and a gene expression signature matrix based on the published LM22 leukocyte matrix (Newman et al., 2015) augmented with 5 bone marrow- and myeloma-specific cell types. Results Our deconvolution approach accurately estimated percent tumor cells in the paired samples compared to estimates from microscopy and flow cytometry (PCC = 0.63, RMSE = 9.99%). TME clusters built on gene expression data from all 867 samples resulted in 5 unsupervised clusters covering 91% of samples. While the fraction of patients in each cluster changed during treatment, no new TME clusters emerged as treatment progressed. These clusters were associated with progression free survival (PFS) (p-Val = 0.020) and overall survival (OS) (p-Val = 0.067) when measured in pre-transplant samples. The most striking outcomes were represented by Cluster 5 (N = 106) characterized by a low innate to adaptive cell ratio and shortened patient survival (Figure 1, 2). This cluster had worse outcomes than others (estimated mean PFS = 58 months compared to 71+ months for other clusters, p-Val = 0.002; estimate mean OS = 105 months compared with 113+ months for other clusters, p-Val = 0.040). Compared to other immune clusters, the adaptive-skewed TME of Cluster 5 is characterized by low granulocyte populations and high antigen-presenting, CD8 T, and B cell populations. As might be expected, this cluster was also significantly enriched for ISS3 and GEP70 high risk patients, as well as Del1p, Del1q, t12;14, and t14:16. Importantly, this TME persisted even when the induction therapy significantly reduced the tumor load (Table 1). At post-induction, outcomes for the 69 / 245 patients in Cluster 5 remain significantly worse (estimate mean PFS = 56 months compared to 71+ months for other clusters, p-Val = 0.004; estimate mean OS = 100 months compared to 121+ months for other clusters, p-Val = 0.002). The analysis of on-treatment samples showed that the number of patients in Cluster 5 decreases from 30% before treatment to 12% after transplant, and of the 63 patients for whom we have both pre-treatment and post-transplant samples, 18/20 of the Cluster 5 patients moved into other immune clusters; 13 into Cluster 4. The non-5 clusters (with better PFS and OS overall) had higher amounts of granulocytes and lower amounts of CD8 T cells. Some clusters (1 and 4) had increased natural killer (NK) cells and decreased dendritic cells, while other clusters (2 and 3) had increased adipocytes and increases in M2 macrophages (Cluster 2) or NK cells (Cluster 3). Taken together, the gain of granulocytes and adipocytes was associated with improved outcome, while increases in the adaptive immune compartment was associated with poorer outcome. Conclusions We identified distinct clusters of patient TMEs from bulk transcriptome profiles by computationally estimating the CD138- fraction of TMEs. Our findings identified differential immune and stromal compositions in patient clusters with opposing clinical outcomes and tracked membership in those clusters during treatment. Adding this layer of TME to the analysis of myeloma patient baseline and on-treatment samples enables us to formulate biological hypotheses and may eventually guide therapeutic interventions to improve outcomes for patients. Disclosures Danziger: Celgene Corporation: Employment, Equity Ownership. McConnell:Celgene Corporation: Employment. Gockley:Celgene Corporation: Employment. Young:Celgene Corporation: Employment, Equity Ownership. Schmitz:Celgene Corporation: Employment, Equity Ownership. Reiss:Celgene Corporation: Employment, Equity Ownership. Davies:MMRF: Honoraria; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; TRM Oncology: Honoraria; Abbvie: Consultancy; ASH: Honoraria; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria. Copeland:Celgene Corporation: Employment, Equity Ownership. Fox:Celgene Corporation: Employment, Equity Ownership. Fitch:Celgene Corporation: Employment, Equity Ownership. Newhall:Celgene Corporation: Employment, Equity Ownership. Barlogie:Celgene: Consultancy, Research Funding; Dana Farber Cancer Institute: Other: travel stipend; Multiple Myeloma Research Foundation: Other: travel stipend; International Workshop on Waldenström's Macroglobulinemia: Other: travel stipend; Millenium: Consultancy, Research Funding; European School of Haematology- International Conference on Multiple Myeloma: Other: travel stipend; ComtecMed- World Congress on Controversies in Hematology: Other: travel stipend; Myeloma Health, LLC: Patents & Royalties: : Co-inventor of patents and patent applications related to use of GEP in cancer medicine licensed to Myeloma Health, LLC. Trotter:Celgene Research SL (Spain), part of Celgene Corporation: Employment, Equity Ownership. Hershberg:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Dervan:Celgene Corporation: Employment, Equity Ownership. Ratushny:Celgene Corporation: Employment, Equity Ownership. Morgan:Takeda: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Research Funding.

Introduction The multistep progression of multiple myeloma from a normal plasma cell to a system with the features of invasive cancer provides a unique opportunity to understand the co-evolution of the malignant clone within its microenvironment. Understanding these changes is becoming increasingly important as we attempt to design early intervention strategies and to precisely leverage emerging immunotherapeutic modalities to prevent and treat disease progression. In this work, we used mass cytometry (CyTOF) to generate a high-resolution map of the BM microenvironment and how it changes during the transition from health through pre-malignancy to disease. This approach allows us to both understand microenvironmental patterns that correlate with rapid disease progression as well as to generate new hypotheses about permissive and protective immune-phenotypes that might reveal novel immunologic drug targets. Methods To understand the immunologic characteristics of monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), newly diagnosed multiple myeloma (NDMM) and relapsed-refractory multiple myeloma (RRMM), we profiled BM aspirates from 79 patients using mass cytometry by time of flight (CyTOF). Furthermore, we compared the BM compartment of pre-malignant, malignant, and relapsed disease states to the BM of healthy donors using a 37-marker pan-immune panel. In this panel, we used antibodies against several immune lineages, tumor antigens, and functional surface markers, including co-stimulatory and co-inhibitory receptors. Cell clusters defined by Citrus analysis of CyTOF data were combined into an evolutionarily optimized decision tree by evtree to identify cluster interactions that strongly partition patient samples. Results During MGUS, when the tumor plasma cells are Conclusions Immune dysregulation is thought to be a major contributor to the progression and outcome of patients with MGUS, SMM, and MM. Using CyTOF, we have begun to benchmark the content of the immune microenvironment across the myeloma continuum. Based on this cross-sectional analysis we hypothesize that it is important to further interrogate whether the losses in the CD4 memory and effector populations we described correlate with outcomes after therapy with either CAR T or T cell engager trials that are currently ongoing, and whether reconstituting these cell types could provide a meaningful treatment strategy. Disclosures Young: Celgene Corporation: Employment, Equity Ownership. Danziger:Celgene Corporation: Employment, Equity Ownership. Fitch:Celgene Corporation: Employment, Equity Ownership. Schmitz:Celgene Corporation: Employment, Equity Ownership. Gockley:Celgene Corporation: Employment. McConnell:Celgene Corporation: Employment. Reiss:Celgene Corporation: Employment, Equity Ownership. Copeland:Celgene Corporation: Employment, Equity Ownership. Newhall:Celgene Corporation: Employment, Equity Ownership. Hershberg:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Foy:Celgene Corporation: Employment, Equity Ownership. Ratushny:Celgene Corporation: Employment, Equity Ownership. Dervan:Celgene Corporation: Employment, Equity Ownership. Morgan:Takeda: Consultancy, Honoraria; Janssen: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria.

In yeast, β-oxidation of fatty acids (FAs) takes place in the peroxisome, an organelle whose size and number are controlled in response to environmental cues. The expression of genes required for peroxisome assembly and function is controlled by a transcriptional regulatory network that is induced by FAs such as oleate. The core FA-responsive transcriptional network consists of carbon source-sensing transcription factors that regulate key target genes through an overlapping feed-forward network motif (OFFNM). However, a systems-level understanding of the function of this network architecture in regulating dynamic FA-induced gene expression is lacking. The specific role of the OFFNM in regulating the dynamic and cell-population transcriptional response to oleate was investigated using a kinetic model comprised of four core transcription factor genes (ADR1, OAF1, PIP2, and OAF3) and two reporter genes (CTA1 and POT1) that are indicative of peroxisome induction. Simulations of the model suggest that 1), the intrinsic Adr1p-driven feed-forward loop reduces the steady-state expression variability of target genes; 2), the parallel Oaf3p-driven inhibitory feed-forward loop modulates the dynamic response of target genes to a transiently varying oleate concentration; and 3), heterodimerization of Oaf1p and Pip2p does not appear to have a noise-reducing function in the context of oleate-dependent expression of target genes. The OFFNM is highly overrepresented in the yeast regulome, suggesting that the specific functions described for the OFFNM, or other properties of this motif, provide a selective advantage.

A mathematical model for suppression of the hepatitis C virus RNA replicon replication in Huh-7 cell culture in the presence of potential drugs was built. There was a good agreement between the experimental and theoretical kinetic data for the decrease in the level of viral RNA in the cell in the presence of the competitive HCV NS3 protease inhibitor. Using the model, we verified the estimates for the efficiency of the effect of potential drugs on replication of viral RNA and viral protein processing. It was demonstrated that the tested drugs are most efficient at the replication step of viral RNA. The efficiency of the combined action of real and putative inhibitors target on the host and viral proteins was also studied. It was found that the action of the inhibitor at low concentrations on the host factors considerably enhances the suppressive effect on viral RNA replication in the presence of even the low affine NS3 protease inhibitors. The developed mathematical model may serve as a tool for the evaluation of the efficiency of potential drugs on the HCV genome.

Nowadays, search for efficient pharmaceuticals against hepatitis C virus (HCV) is an urgent task. In addition to conventional medicines, such as interferon and ribavirin, new specific drugs are being developed. Recently, it has been shown that a peptidomimetic substance, competitive inhibitor of viral NS3 protease, efficiently suppresses replication of the viral RNA replicon in Huh-7 cells. Computer simulation of the operation of the gene network comprising major processes of the viral RNA in the cell provides grounds for analysis of the HCV life cycle and search for key targets for efficient attack with drugs. The gene network of viral RNA replication in Huh-7 cells in the presence of a highly specific and efficient viral NS3 protease inhibitor has been reconstructed by analysis of reported experimental results and application of the GenNet technology. A mathematical model describing the operation of this network has been developed. The kinetics of the decrease in the level of viral RNA in the presence of the inhibitor predicted on the basis of this model is close to experimental results.

The study of normal and pathological states of the gene network regulating cholesterol biosynthesis in the cell is a topical problem. Impairments of this system play a key role in the development of hypercholesterolemia and atherosclerosis of humans and various animals. Knowledge of the behavior of this system under various conditions is necessary to develop optimal strategies for correcting various pathologies while taking into account the genotype-specific distinctions of individuals and the targets for pharmacological regulation. The model simulating cholesterol biosynthesis in the cell and its exchange with blood plasma cholesterol developed earlier using a generalized chemical kinetic approach was used for the analysis of a mutational portrait of this system. The sensitivity of the stationary content of free cholesterol to mutational changes in the rates of molecular processes running within the gene network was analyzed. The resilience of the free cholesterol concentration to a wide range of mutations in the gene network was demonstrated. In addition, it was shown that the mutations hitting regulatory processes changed the stationary content of free cholesterol to the largest degree.

Systems cell biology melds high-throughput experimentation with quantitative analysis and modeling to understand many critical processes that contribute to cellular organization and dynamics. Recently, there have been several advances in technology and in the application of modeling approaches that enable the exploration of the dynamic properties of cells. Merging technology and computation offers an opportunity to objectively address unsolved cellular mechanisms, and has revealed emergent properties and helped to gain a more comprehensive and fundamental understanding of cell biology.

Development of methods for mathematical simulation of biological systems and building specific simulations is an important trend of bioinformatics. Here we describe the method of generalized chemokinetic simulation generating flexible and adequate simulations of various biological systems. Adequate simulations of complex nonlinear gene networks—control system of cholesterol by synthesis in the cell and erythrocyte differentiation and maturation—are given as examples. The simulations were expressed in terms of unit processes—biochemical reactions. Optimal sets of parameters were determined and the systems were numerically simulated under various conditions. The simulations allow us to study the possible functional conditions of these gene networks, calculate the consequences of mutations, and define optimal strategies for their correction including therapeutic ones. A graphical user interface for these simulations is available at http://wwwmgs.bionet.nsc.ru/systems/MGL/GeneNet/

The type I interferon (IFN) response protects cells from viral infection by inducing hundreds of interferon-stimulated genes (ISGs), some of which encode direct antiviral effectors. Recent screening studies have begun to catalogue ISGs with antiviral activity against several RNA and DNA viruses. However, antiviral ISG specificity across multiple distinct classes of viruses remains largely unexplored. Here we used an ectopic expression assay to screen a library of more than 350 human ISGs for effects on 14 viruses representing 7 families and 11 genera. We show that 47 genes inhibit one or more viruses, and 25 genes enhance virus infectivity. Comparative analysis reveals that the screened ISGs target positive-sense single-stranded RNA viruses more effectively than negative-sense single-stranded RNA viruses. Gene clustering highlights the cytosolic DNA sensor cyclic GMP-AMP synthase (cGAS, also known as MB21D1) as a gene whose expression also broadly inhibits several RNA viruses. In vitro, lentiviral delivery of enzymatically active cGAS triggers a STING-dependent, IRF3-mediated antiviral program that functions independently of canonical IFN/STAT1 signalling. In vivo, genetic ablation of murine cGAS reveals its requirement in the antiviral response to two DNA viruses, and an unappreciated contribution to the innate control of an RNA virus. These studies uncover new paradigms for the preferential specificity of IFN-mediated antiviral pathways spanning several virus families.

Copper (Cu) is an important enzyme co-factor that is also extremely toxic at high intracellular concentrations, making active efflux mechanisms essential for preventing Cu accumulation. Here, we have investigated the mechanistic role of metallochaperones in regulating Cu efflux. We have constructed a computational model of Cu trafficking and efflux based on systems analysis of the Cu stress response of Halobacterium salinarum. We have validated several model predictions via assays of transcriptional dynamics and intracellular Cu levels, discovering a completely novel function for metallochaperones. We demonstrate that in addition to trafficking Cu ions, metallochaperones also function as buffers to modulate the transcriptional responsiveness and efficacy of Cu efflux. This buffering function of metallochaperones ultimately sets the upper limit for intracellular Cu levels and provides a mechanistic explanation for previously observed Cu metallochaperone mutation phenotypes., Author Summary Copper (Cu) toxicity is a problem of medical, agricultural, and environmental significance. Cu toxicity severely inhibits growth of plant roots significantly affecting their morphology; Cu overload also accounts for some of the most common metal-metabolism abnormalities and neuropsychiatric problems including Wilson's and Menkes diseases. There is a large body of literature on how Cu enters and exits the cell; the kinetic and structural details of Cu translocation between trafficking, sensing, metabolic, and pumping proteins; and phenotypes associated with defects in metalloregulatory and efflux functions. Although the role of metallochaperones in Cu-cytotoxicity has been poorly studied, it has been observed that in animals deletion of metallochaperones results in elevated intracellular Cu levels along with overexpression of the P1-type ATPase efflux pump, ultimately causing malformation with high mortality. These observations are mechanistically explained by a predictive model of the Cu circuit in Halobacterium salinarum, which serves as an excellent model system for Cu trafficking and regulation in organisms with multiple chaperones. Constructed through iterative modeling and experimentation, this model accurately recapitulates known dynamical properties of the Cu circuit and predicts that intracellular Cu-buffering emerges as a consequence of the interplay of paralogous metallochaperones that traffic and allocate Cu to distinct targets.

NUP1, the first example of a nuclear lamin analog in nonmetazoans, performs roles similar to those of lamins in maintaining the structure and organization of the nucleus in Trypanosoma brucei., A unifying feature of eukaryotic nuclear organization is genome segregation into transcriptionally active euchromatin and transcriptionally repressed heterochromatin. In metazoa, lamin proteins preserve nuclear integrity and higher order heterochromatin organization at the nuclear periphery, but no non-metazoan lamin orthologues have been identified, despite the likely presence of nucleoskeletal elements in many lineages. This suggests a metazoan-specific origin for lamins, and therefore that distinct protein elements must compose the nucleoskeleton in other lineages. The trypanosomatids are highly divergent organisms and possess well-documented but remarkably distinct mechanisms for control of gene expression, including polycistronic transcription and trans-splicing. NUP-1 is a large protein localizing to the nuclear periphery of Trypanosoma brucei and a candidate nucleoskeletal component. We sought to determine if NUP-1 mediates heterochromatin organization and gene regulation at the nuclear periphery by examining the influence of NUP-1 knockdown on morphology, chromatin positioning, and transcription. We demonstrate that NUP-1 is essential and part of a stable network at the inner face of the trypanosome nuclear envelope, since knockdown cells have abnormally shaped nuclei with compromised structural integrity. NUP-1 knockdown also disrupts organization of nuclear pore complexes and chromosomes. Most significantly, we find that NUP-1 is required to maintain the silenced state of developmentally regulated genes at the nuclear periphery; NUP-1 knockdown results in highly specific mis-regulation of telomere-proximal silenced variant surface glycoprotein (VSG) expression sites and procyclin loci, indicating a disruption to normal chromatin organization essential to life-cycle progression. Further, NUP-1 depletion leads to increased VSG switching and therefore appears to have a role in control of antigenic variation. Thus, analogous to vertebrate lamins, NUP-1 is a major component of the nucleoskeleton with key roles in organization of the nuclear periphery, heterochromatin, and epigenetic control of developmentally regulated loci., Author Summary Eukaryotes—fungi, plants, animals, and many unicellular organisms—are defined by the presence of a cell nucleus that contains the chromosomes and is enveloped by a lipid membrane lined on the inner face with a protein network called the lamina. Among other functions, the lamina serves as an anchorage site for the ends of chromosomes. In multicellular animals (metazoa), the lamina comprises a few related proteins called lamins, which are very important for many functions related to the nucleus; abnormal lamins result in multiple nuclear defects and diseases, including inappropriate gene expression and premature aging. Until now, however, lamins had been found only in metazoa; no protein of equivalent function had been identified in plants, fungi, or unicellular organisms. Here, we describe a protein from African trypanosomes—the single-cell parasites that cause sleeping sickness—that fulfils many lamin-like roles, including maintaining nuclear structure and organizing the chromosomes of this organism. We show that this protein, which we call NUP-1 for nuclear periphery protein-1, is vital for the antigenic variation mechanisms that allow the parasite to escape the host immune response. We propose that NUP-1 is a lamin analogue that performs similar functions in trypanosomes to those of authentic lamins in metazoa. These findings, we believe, have important implications for understanding the evolution of the nucleus.

Mathematical and computational models have become indispensable tools for integrating and interpreting heterogeneous biological data, understanding fundamental principles of biological system functions, genera-ting reliable testable hypotheses, and identifying potential diagnostic markers and therapeutic targets. Thus, such tools are now routinely used in the theoretical and experimental systematic investigation of biological system dynamics. Here, we discuss model building as an essential part of the theoretical and experimental analysis of biomolecular network dynamics. Specifically, we describe a procedure for defining kinetic equations and parameters of biomolecular processes, and we illustrate the use of fractional activity functions for modeling gene expression regulation by single and multiple regulators. We further discuss the evaluation of model complexity and the selection of an optimal model based on information criteria. Finally, we discuss the critical roles of sensitivity, robustness analysis, and optimal experiment design in the model building cycle.

Phosphorylation of proteins is a key posttranslational modification in cellular signaling, regulating many aspects of cellular responses. We used a quantitative, integrated, phosphoproteomics approach to characterize the cellular responses of the yeast Saccharomyces cerevisiae to the fatty acid oleic acid, a molecule with broad human health implications and a potent inducer of peroxisomes. A combination of cryolysis and urea solubilization was used to minimize the opportunity for reorientation of the phosphoproteome, and hydrophilic interaction liquid chromatography and IMAC chemistries were used to fractionate and enrich for phosphopeptides. Using these approaches, numerous phosphorylated peptides specific to oleate-induced and glucose-repressed conditions were identified and mapped to known signaling pathways. These include several transcription factors, two of which, Pip2p and Cst6p, must be phosphorylated for the normal transcriptional response of fatty acid-responsive loci encoding peroxisomal proteins. The phosphoproteome data were integrated with results from genome-wide assays studying the effects of signaling molecule deletions and known protein-protein interactions to generate a putative fatty acid-responsive signaling network. In this network, the most highly connected nodes are those with the largest effects on cellular responses to oleic acid. These properties are consistent with a scale-free topology, demonstrating that scale-free properties are conserved in condition-specific networks.

The histone variant H2A.Z (Htz1p) has been implicated in transcriptional regulation in numerous organisms, including Saccharomyces cerevisiae. Genome-wide transcriptome profiling and chromatin immunoprecipitation studies identified a role for Htz1p in the rapid and robust activation of many oleate-responsive genes encoding peroxisomal proteins, in particular POT1, POX1, FOX2, and CTA1. The Swr1p-, Gcn5p-, and Chz1p-dependent association of Htz1p with these promoters in their repressed states appears to establish an epigenetic marker for the rapid and strong expression of these highly inducible promoters. Isw2p also plays a role in establishing the nucleosome state of these promoters and associates stably in the absence of Htz1p. An analysis of the nucleosome dynamics and Htz1p association with these promoters suggests a complex mechanism in which Htz1p-containing nucleosomes at fatty acid-responsive promoters are disassembled upon initial exposure to oleic acid leading to the loss of Htz1p from the promoter. These nucleosomes reassemble at later stages of gene expression. While these new nucleosomes do not incorporate Htz1p, the initial presence of Htz1p appears to mark the promoter for sustained gene expression and the recruitment of TATA-binding protein.

Development of an in silico cell is an urgent task of systems biology. The core of this cell should consist of mathematical models of intracellular events, including enzymatic reactions and control of gene expression. For example, the minimal model of the E. coli cell should include description of about one thousand enzymatic reactions and regulation of expression of approximately the same number of genes. In many cases detailed mechanisms of molecular processes are not known. In this study, we propose a generalized Hill function method for modeling molecular events. The proposed approach is a method of kinetic data approximation in view of additional data on structure functional features of molecular genetic systems and actually does not demand knowledge of their detailed mechanisms. Generalized Hill function models of an enzymatic reaction catalyzed by the tryptophan-sensitive 3-deoxy-d-arabino-heptulosonate-7-phosphate synthase and the cydAB operon expression regulation are presented.

The GeneNet system is designed for collection and analysis of the data on gene and metabolic networks, signal transduction pathways and kinetic characteristics of elementary processes. In the past 2 years, the GeneNet structure was considerably improved: (i) the current version of the database is now implemented using ORACLE9i; (ii) the capacities to describe the structure of the protein complexes and the interactions between the units are increased; (iii) two tables with kinetic constants and more detailed descriptions of certain reactions were added; and (iv) a module for kinetic modeling was supplemented. The current SRS release of the GeneNet database contains 37 graphical maps of gene networks, as well as descriptions of 1766 proteins, 1006 genes, 241 small molecules and 3254 relationships between gene network units, and 552 kinetic constants. Information distributed between 16 interlinked tables was obtained by annotating 1980 journal publications. SRS release of the GeneNet database, the graphical viewer and the modeling section are available at http://wwwmgs.bionet.nsc.ru/mgs/gnw/genenet/.