A general calculus of fitness landscapes finds genes under selection in cancers.

Genetic variants drive the evolution of traits and diseases. We previously modeled these variants as small displacements in fitness landscapes and estimated their functional impact by differentiating the evolutionary relationship between genotype and phenotype. Conversely, here we integrate these derivatives to identify genes steering specific traits. Over cancer cohorts, integration identified 460 likely tumor-driving genes. Many have literature and experimental support but had eluded prior genomic searches for positive selection in tumors. Beyond providing cancer insights, these results introduce a general calculus of evolution to quantify the genotype-phenotype relationship and discover genes associated with complex traits and diseases.

A Countable-Type Branching Process Model for the Tug-of-War Cancer Cell Dynamics.

We consider a time-continuous Markov branching process of proliferating cells with a countable collection of types. Among-type transitions are inspired by the Tug-of-War process introduced by McFarland et al. (Proc Natl Acad Sci 111(42):15138-15143, 2014) as a mathematical model for competition of advantageous driver mutations and deleterious passenger mutations in cancer cells. We introduce a version of the model in which a driver mutation pushes the type of the cell L-units up, while a passenger mutation pulls it 1-unit down. The distribution of time to divisions depends on the type (fitness) of cell, which is an integer. The extinction probability given any initial cell type is strictly less than 1, which allows us to investigate the transition between types (type transition) in an infinitely long cell lineage of cells. The analysis leads to the result that under driver dominance, the type transition process escapes to infinity, while under passenger dominance, it leads to a limit distribution. Implications in cancer cell dynamics and population genetics are discussed.

Detection and characterization of constitutive replication origins defined by DNA polymerase epsilon.

BACKGROUND: Despite the process of DNA replication being mechanistically highly conserved, the location of origins of replication (ORI) may vary from one tissue to the next, or between rounds of replication in eukaryotes, suggesting flexibility in the choice of locations to initiate replication. Lists of human ORI therefore vary widely in number and location, and there are currently no methods available to compare them. Here, we propose a method of detection of ORI based on somatic mutation patterns generated by the mutator phenotype of damaged DNA polymerase epsilon (POLE). RESULTS: We report the genome-wide localization of constitutive ORI in POLE-mutated human tumors using whole genome sequencing data. Mutations accumulated after many rounds of replication of unsynchronized dividing cell populations in tumors allow to identify constitutive origins, which we show are shared with high fidelity between individuals and tumor types. Using a Smith-Waterman-like dynamic programming approach, we compared replication origin positions obtained from multiple different methods. The comparison allowed us to define a consensus set of replication origins, identified consistently by multiple ORI detection methods. Many DNA features co-localized with the consensus set of ORI, including chromatin loop anchors, G-quadruplexes, S/MARs, and CpGs. Among all features, the H2A.Z histone exhibited the most significant association. CONCLUSIONS: Our results show that mutation-based detection of replication origins is a viable approach to determining their location and associated sequence features.

Mathematical model predicts response to chemotherapy in advanced non-resectable non-small cell lung cancer patients treated with platinum-based doublet.

We developed a computational platform including machine learning and a mechanistic mathematical model to find the optimal protocol for administration of platinum-doublet chemotherapy in a palliative setting. The platform has been applied to advanced metastatic non-small cell lung cancer (NSCLC). The 42 NSCLC patients treated with palliative intent at Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, were collected from a retrospective cohort of patients diagnosed in 2004-2014. Patients were followed-up, for three years. Clinical data collected include complete information about the clinical course of the patients including treatment schedule, response according to RECIST classification, and survival. The core of the platform is the mathematical model, in the form of a system of ordinary differential equations, describing dynamics of platinum-sensitive and platinum-resistant cancer cells and interactions reflecting competition for space and resources. The model is simulated stochastically by sampling the parameter values from a joint probability distribution function. The machine learning model is applied to calibrate the mathematical model and to fit it to the overall survival curve. The model simulations faithfully reproduce the clinical cohort at three levels long-term response (OS), the initial response (according to RECIST criteria), and the relationship between the number of chemotherapy cycles and time between two consecutive chemotherapy cycles. In addition, we investigated the relationship between initial and long-term response. We showed that those two variables do not correlate which means that we cannot predict patient survival solely based on the initial response. We also tested several chemotherapy schedules to find the best one for patients treated with palliative intent. We found that the optimal treatment schedule depends, among others, on the strength of competition among various subclones in a tumor. The computational platform developed allows optimizing chemotherapy protocols, within admissible limits of toxicity, for palliative treatment of metastatic NSCLC. The simplicity of the method allows its application to chemotherapy optimization in different cancers.

Analysis of two mechanisms of telomere maintenance based on the theory of g-Networks and stochastic automata networks.

*: Background Telomeres, which are composed of repetitive nucleotide sequences at the end of chromosomes, behave as a division clock that measures replicative senescence. Under the normal physiological condition, telomeres shorten with each cell division, and cells use the telomere lengths to sense the number of divisions. Replicative senescence has been shown to occur at approximately 50-70 cell divisions, which is termed the Hayflick's limit. However, in cancer cells telomere lengths are stabilized, thereby allowing continual cell replication by two known mechanisms: activation of telomerase and Alternative Lengthening of Telomeres (ALT). The connections between the two mechanisms are complicated and still poorly understood. *: Results In this research, we propose that two different approaches, G-Networks and Stochastic Automata Networks, which are stochastic models motivated by queueing theory, are useful to identify a set of genes that play an important role in the state of interest and to infer their previously unknown correlation by obtaining both stationary and joint transient distributions of the given system. Our analysis using G-Network detects five statistically significant genes (CEBPA, FOXM1, E2F1, c-MYC, hTERT) with either mechanism, contrasted to normal cells. A new algorithm is introduced to show how the correlation between two genes of interest varies in the transient state according not only to each mechanism but also to each cell condition. *: Conclusions This study expands our existing knowledge of genes associated with mechanisms of telomere maintenance and provides a platform to understand similarities and differences between telomerase and ALT in terms of the correlation between two genes in the system. This is particularly important because telomere dynamics plays a major role in many physiological and disease processes, including hematopoiesis.

Effect of the unfolded protein response and oxidative stress on mutagenesis in CSF3R: a model for evolution of severe congenital neutropenia to myelodysplastic syndrome/acute myeloid leukemia.

Severe congenital neutropenia (SCN) is a rare blood disorder characterised by abnormally low levels of circulating neutrophils. The most common recurrent mutations that cause SCN involve neutrophil elastase (ELANE). The treatment of choice for SCN is the administration of granulocyte-colony stimulating factor (G-CSF), which increases the neutrophil number and improves the survival and quality of life. Long-term survival is however linked to the development of myelodysplastic syndrome/acute myeloid leukemia (MDS/AML). About 70% of MDS/AML patients acquire nonsense mutations affecting the cytoplasmic domain of CSF3R (the G-CSF receptor). About 70% of SCN patients with AML harbour additional mutations in RUNX1. We hypothesised that this coding region of CSF3R constitutes a hotspot vulnerable to mutations resulting from excessive oxidative stress or endoplasmic reticulum (ER) stress. We used the murine Ba/F3 cell line to measure the effect of induced oxidative or ER stress on the mutation rate in our hypothesised hotspot of the exogenous human CSF3R, the corresponding region in the endogenous Csf3r, and Runx1. Ba/F3 cells transduced with the cDNA for partial C-terminal of CSF3R fused in-frame with a green fluorescent protein (GFP) tag were subjected to stress-inducing treatment for 30 days (~51 doubling times). The amplicon-based targeted deep sequencing data for days 15 and 30 samples show that although there was increased mutagenesis observed in all the three genes of interest (partial CSF3R, Csf3r and Runx1), there were more mutations in the GFP region compared with the partial CSF3R region. Our findings also indicate that there is no correlation between the stress-inducing chemical treatments and mutagenesis in Ba/F3 cells. Our data suggest that oxidative or ER stress induction does not promote genomic instability, affecting partial C-terminal of the transduced CSF3R, the endogenous Csf3R and the endogenous Runx1 in Ba/F3 cells that could account for these targets to being mutational hotspots. We conclude that other mechanisms to acquire mutations of CSF3R that help drive the evolution of SCN to MDS/AML.

Heat shock response regulates stimulus-specificity and sensitivity of the pro-inflammatory NF-κB signalling.

BACKGROUND: Ability to adapt to temperature changes trough the Heat Shock Response (HSR) pathways is one of the most fundamental and clinically relevant cellular response systems. Heat Shock (HS) affects the signalling and gene expression responses of the Nuclear Factor κB (NF-κB) transcription factor, a critical regulator of proliferation and inflammation, however, our quantitative understanding of how cells sense and adapt to temperature changes is limited. METHODS: We used live-cell time-lapse microscopy and mathematical modelling to understand the signalling of the NF-κB system in the human MCF7 breast adenocarcinoma cells in response to pro-inflammatory Interleukin 1ß (IL1ß) and Tumour Necrosis Factor α (TNFα) cytokines, following exposure to a 37-43 °C range of physiological and clinical temperatures. RESULTS: We show that exposure to 43 °C 1 h HS inhibits the immediate NF-κB signalling response to TNFα and IL1ß stimulation although uptake of cytokines is not impaired. Within 4 h after HS treatment IL1ß-induced NF-κB responses return to normal levels, but the recovery of the TNFα-induced responses is still affected. Using siRNA knock-down of Heat Shock Factor 1 (HSF1) we show that this stimulus-specificity is conferred via the Inhibitory κB kinase (IKK) signalosome where HSF1-dependent feedback regulates TNFα, but not IL1ß-mediated IKK recovery post HS. Furthermore, we demonstrate that through the temperature-dependent denaturation and recovery of IKK, TNFα and IL1ß-mediated signalling exhibit different temperature sensitivity and adaptation to repeated HS when exposed to a 37-43 °C temperature range. Specifically, IL1ß-mediated NF-κB responses are more robust to temperature changes in comparison to those induced by TNFα treatment. CONCLUSIONS: We demonstrate that the kinetics of the NF-κB system following temperature stress is cytokine specific and exhibit differential adaptation to temperature changes. We propose that this differential temperature sensitivity is mediated via the IKK signalosome, which acts as a bona fide temperature sensor trough the HSR cross-talk. This novel quantitative understanding of NF-κB and HSR interactions is fundamentally important for the potential optimization of therapeutic hyperthermia protocols. Video Abstract.

Mathematical modelling reveals unexpected inheritance and variability patterns of cell cycle parameters in mammalian cells.

The cell cycle is the fundamental process of cell populations, it is regulated by environmental cues and by intracellular checkpoints. Cell cycle variability in clonal cell population is caused by stochastic processes such as random partitioning of cellular components to progeny cells at division and random interactions among biomolecules in cells. One of the important biological questions is how the dynamics at the cell cycle scale, which is related to family dependencies between the cell and its descendants, affects cell population behavior in the long-run. We address this question using a "mechanistic" model, built based on observations of single cells over several cell generations, and then extrapolated in time. We used cell pedigree observations of NIH 3T3 cells including FUCCI markers, to determine patterns of inheritance of cell-cycle phase durations and single-cell protein dynamics. Based on that information we developed a hybrid mathematical model, involving bifurcating autoregression to describe stochasticity of partitioning and inheritance of cell-cycle-phase times, and an ordinary differential equation system to capture single-cell protein dynamics. Long-term simulations, concordant with in vitro experiments, demonstrated the model reproduced the main features of our data and had homeostatic properties. Moreover, heterogeneity of cell cycle may have important consequences during population development. We discovered an effect similar to genetic drift, amplified by family relationships among cells. In consequence, the progeny of a single cell with a short cell cycle time had a high probability of eventually dominating the population, due to the heritability of cell-cycle phases. Patterns of epigenetic heritability in proliferating cells are important for understanding long-term trends of cell populations which are either required to provide the influx of maturing cells (such as hematopoietic stem cells) or which started proliferating uncontrollably (such as cancer cells).

Mutation, drift and selection in single-driver hematologic malignancy: Example of secondary myelodysplastic syndrome following treatment of inherited neutropenia.

Cancer development is driven by series of events involving mutations, which may become fixed in a tumor via genetic drift and selection. This process usually includes a limited number of driver (advantageous) mutations and a greater number of passenger (neutral or mildly deleterious) mutations. We focus on a real-world leukemia model evolving on the background of a germline mutation. Severe congenital neutropenia (SCN) evolves to secondary myelodysplastic syndrome (sMDS) and/or secondary acute myeloid leukemia (sAML) in 30-40%. The majority of SCN cases are due to a germline ELANE mutation. Acquired mutations in CSF3R occur in >70% sMDS/sAML associated with SCN. Hypotheses underlying our model are: an ELANE mutation causes SCN; CSF3R mutations occur spontaneously at a low rate; in fetal life, hematopoietic stem and progenitor cells expands quickly, resulting in a high probability of several tens to several hundreds of cells with CSF3R truncation mutations; therapeutic granulocyte colony-stimulating factor (G-CSF) administration early in life exerts a strong selective pressure, providing mutants with a growth advantage. Applying population genetics theory, we propose a novel two-phase model of disease development from SCN to sMDS. In Phase 1, hematopoietic tissues expand and produce tens to hundreds of stem cells with the CSF3R truncation mutation. Phase 2 occurs postnatally through adult stages with bone marrow production of granulocyte precursors and positive selection of mutants due to chronic G-CSF therapy to reverse the severe neutropenia. We predict the existence of the pool of cells with the mutated truncated receptor before G-CSF treatment begins. The model does not require increase in mutation rate under G-CSF treatment and agrees with age distribution of sMDS onset and clinical sequencing data.

Stationary Distribution of Telomere Lengths in Cells with Telomere Length Maintenance and its Parametric Inference.

Telomeres are nucleotide caps located at the ends of each eukaryotic chromosome. Under normal physiological conditions as well as in culture, they shorten during each DNA replication round. Short telomeres initiate a proliferative arrest of cells termed 'replicative senescence'. However, cancer cells possessing limitless replication potential can avoid senescence by the telomere maintenance mechanism, which offsets telomeric loss. Therefore, cancer cells have sufficiently long telomeres even though their lengths are significantly shorter than their normal counterparts. This implies that the attrition and elongation rates play crucial roles in deciding whether and when cells ultimately become carcinogenic. In this research, we propose a concise mathematical model that shows the shortest telomere length at each cell division and prove mathematical conditions related to the attrition and elongation rates, which are necessary and sufficient for the existence of stationary distribution of telomere lengths. Moreover, we estimate the parameters of the telomere length maintenance process based on frequentist and Bayesian approaches. This study expands our knowledge of the mathematical relationship between the telomere attrition and elongation rates in cancer cells, which is important because the telomere length dynamics is a useful biomarker of cancer diagnosis and prognosis.

A mathematical model as a tool to identify microRNAs with highest impact on transcriptome changes.

BACKGROUND: Rapid changes in the expression of many messenger RNA (mRNA) species follow exposure of cells to ionizing radiation. One of the hypothetical mechanisms of this response may include microRNA (miRNA) regulation, since the amounts of miRNAs in cells also vary upon irradiation. To address this possibility, we designed experiments using cancer-derived cell lines transfected with luciferase reporter gene containing sequences targeted by different miRNA species in its 3'- untranslated region. We focus on the early time-course response (1 h past irradiation) to eliminate secondary mRNA expression waves. RESULTS: Experiments revealed that the irradiation-induced changes in the mRNA expression depend on the miRNAs which interact with mRNA. To identify the strongest interactions, we propose a mathematical model which predicts the mRNA fold expression changes, caused by perturbation of microRNA-mRNA interactions. Model was applied to experimental data including various cell lines, irradiation doses and observation times, both ours and literature-based. Comparison of modelled and experimental mRNA expression levels given miRNA level changes allows estimating how many and which miRNAs play a significant role in transcriptome response to stress conditions in different cell types. As an example, in the human melanoma cell line the comparison suggests that, globally, a major part of the irradiation-induced changes of mRNA expression can be explained by perturbed miRNA-mRNA interactions. A subset of about 30 out of a few hundred miRNAs expressed in these cells appears to account for the changes. These miRNAs play crucial roles in regulatory mechanisms observed after irradiation. In addition, these miRNAs have a higher average content of GC and a higher number of targeted transcripts, and many have been reported to play a role in the development of cancer. CONCLUSIONS: Our proposed mathematical modeling approach may be used to identify miRNAs which participate in responses of cells to ionizing radiation, and other stress factors such as extremes of temperature, exposure to toxins, and drugs.

Quantitative analysis reveals crosstalk mechanisms of heat shock-induced attenuation of NF-κB signaling at the single cell level.

Elevated temperature induces the heat shock (HS) response, which modulates cell proliferation, apoptosis, the immune and inflammatory responses. However, specific mechanisms linking the HS response pathways to major cellular signaling systems are not fully understood. Here we used integrated computational and experimental approaches to quantitatively analyze the crosstalk mechanisms between the HS-response and a master regulator of inflammation, cell proliferation, and apoptosis the Nuclear Factor κB (NF-κB) system. We found that populations of human osteosarcoma cells, exposed to a clinically relevant 43°C HS had an attenuated NF-κB p65 response to Tumor Necrosis Factor α (TNFα) treatment. The degree of inhibition of the NF-κB response depended on the HS exposure time. Mathematical modeling of single cells indicated that individual crosstalk mechanisms differentially encode HS-mediated NF-κB responses while being consistent with the observed population-level responses. In particular "all-or-nothing" encoding mechanisms were involved in the HS-dependent regulation of the IKK activity and IκBα phosphorylation, while others involving transport were "analogue". In order to discriminate between these mechanisms, we used live-cell imaging of nuclear translocations of the NF-κB p65 subunit. The single cell responses exhibited "all-or-nothing" encoding. While most cells did not respond to TNFα stimulation after a 60 min HS, 27% showed responses similar to those not receiving HS. We further demonstrated experimentally and theoretically that the predicted inhibition of IKK activity was consistent with the observed HS-dependent depletion of the IKKα and IKKß subunits in whole cell lysates. However, a combination of "all-or-nothing" crosstalk mechanisms was required to completely recapitulate the single cell data. We postulate therefore that the heterogeneity of the single cell responses might be explained by the cell-intrinsic variability of HS-modulated IKK signaling. In summary, we show that high temperature modulates NF-κB responses in single cells in a complex and unintuitive manner, which needs to be considered in hyperthermia-based treatment strategies.

Gene characteristics predicting missense, nonsense and frameshift mutations in tumor samples.

BACKGROUND: Because driver mutations provide selective advantage to the mutant clone, they tend to occur at a higher frequency in tumor samples compared to selectively neutral (passenger) mutations. However, mutation frequency alone is insufficient to identify cancer genes because mutability is influenced by many gene characteristics, such as size, nucleotide composition, etc. The goal of this study was to identify gene characteristics associated with the frequency of somatic mutations in the gene in tumor samples. RESULTS: We used data on somatic mutations detected by genome wide screens from the Catalog of Somatic Mutations in Cancer (COSMIC). Gene size, nucleotide composition, expression level of the gene, relative replication time in the cell cycle, level of evolutionary conservation and other gene characteristics (totaling 11) were used as predictors of the number of somatic mutations. We applied stepwise multiple linear regression to predict the number of mutations per gene. Because missense, nonsense, and frameshift mutations are associated with different sets of gene characteristics, they were modeled separately. Gene characteristics explain 88% of the variation in the number of missense, 40% of nonsense, and 23% of frameshift mutations. Comparisons of the observed and expected numbers of mutations identified genes with a higher than expected number of mutations- positive outliers. Many of these are known driver genes. A number of novel candidate driver genes was also identified. CONCLUSIONS: By comparing the observed and predicted number of mutations in a gene, we have identified known cancer-associated genes as well as 111 novel cancer associated genes. We also showed that adding the number of silent mutations per gene reported by genome/exome wide screens across all cancer type (COSMIC data) as a predictor substantially exceeds predicting accuracy of the most popular cancer gene predicting tool - MutsigCV.

RRAD, IL4I1, CDKN1A, and SERPINE1 genes are potentially co-regulated by NF-κB and p53 transcription factors in cells exposed to high doses of ionizing radiation.

BACKGROUND: The cellular response to ionizing radiation involves activation of p53-dependent pathways and activation of the atypical NF-κB pathway. The crosstalk between these two transcriptional networks include (co)regulation of common gene targets. Here we looked for novel genes potentially (co)regulated by p53 and NF-κB using integrative genomics screening in human osteosarcoma U2-OS cells irradiated with a high dose (4 and 10 Gy). Radiation-induced expression in cells with silenced TP53 or RELA (coding the p65 NF-κB subunit) genes was analyzed by RNA-Seq while radiation-enhanced binding of p53 and RelA in putative regulatory regions was analyzed by ChIP-Seq, then selected candidates were validated by qPCR. RESULTS: We identified a subset of radiation-modulated genes whose expression was affected by silencing of both TP53 and RELA, and a subset of radiation-upregulated genes where radiation stimulated binding of both p53 and RelA. For three genes, namely IL4I1, SERPINE1, and CDKN1A, an antagonistic effect of the TP53 and RELA silencing was consistent with radiation-enhanced binding of both p53 and RelA. This suggested the possibility of a direct antagonistic (co)regulation by both factors: activation by NF-κB and inhibition by p53 of IL4I1, and activation by p53 and inhibition by NF-κB of CDKN1A and SERPINE1. On the other hand, radiation-enhanced binding of both p53 and RelA was observed in a putative regulatory region of the RRAD gene whose expression was downregulated both by TP53 and RELA silencing, which suggested a possibility of direct (co)activation by both factors. CONCLUSIONS: Four new candidates for genes directly co-regulated by NF-κB and p53 were revealed.

Irradiation with UV-C inhibits TNF-α-dependent activation of the NF-κB pathway in a mechanism potentially mediated by reactive oxygen species.

Pathways depending on the NF-κB transcription factor are essential components of cellular response to stress. Plethora of stimuli modulating NF-κB includes inflammatory signals, ultraviolet radiation (UV) and reactive oxygen species (ROS), yet interference between different factors affecting NF-κB remains relatively understudied. Here, we aim to characterize the influence of UV radiation on TNF-α-induced activity of the NF-κB pathway. We document inhibition of TNF-α-induced activation of NF-κB and subsequent suppression of NF-κB-regulated genes in cells exposed to UV-C several hours before TNF-α stimulation. Accumulation of ROS and subsequent activation of NRF2, p53, AP-1 and NF-κB-dependent pathways, with downstream activation of antioxidant mechanisms (e.g., SOD2 and HMOX1 expression), is observed in the UV-treated cells. Moreover, NF-κB inhibition is not observed if generation of UV-induced ROS is suppressed by chemical antioxidants. It is noteworthy that stimulation with TNF-α also generates a wave of ROS, which is suppressed in cells pre-treated by UV. We postulate that irradiation with UV-C activates antioxidant mechanisms, which in turn affect ROS-mediated activation of NF-κB by TNF-α. Considering a potential cross talk between p53 and NF-κB, we additionally compare observed effects in p53-proficient and p53-deficient cells and find the UV-mediated suppression of TNF-α-activated NF-κB in both types of cells.

ITD assembler: an algorithm for internal tandem duplication discovery from short-read sequencing data.

BACKGROUND: Detection of tandem duplication within coding exons, referred to as internal tandem duplication (ITD), remains challenging due to inefficiencies in alignment of ITD-containing reads to the reference genome. There is a critical need to develop efficient methods to recover these important mutational events. RESULTS: In this paper we introduce ITD Assembler, a novel approach that rapidly evaluates all unmapped and partially mapped reads from whole exome NGS data using a De Bruijn graphs approach to select reads that harbor cycles of appropriate length, followed by assembly using overlap-layout-consensus. We tested ITD Assembler on The Cancer Genome Atlas AML dataset as a truth set. ITD Assembler identified the highest percentage of reported FLT3-ITDs when compared to other ITD detection algorithms, and discovered additional ITDs in FLT3, KIT, CEBPA, WT1 and other genes. Evidence of polymorphic ITDs in 54 genes were also found. Novel ITDs were validated by analyzing the corresponding RNA sequencing data. CONCLUSIONS: ITD Assembler is a very sensitive tool which can detect partial, large and complex tandem duplications. This study highlights the need to more effectively look for ITD's in other cancers and Mendelian diseases.

Pharmacogenetic characterization of naturally occurring germline NT5C1A variants to chemotherapeutic nucleoside analogs.

BACKGROUND: Mutations or alterations in expression of the 5' nucleotidase gene family can lead to altered responses to treatment with nucleoside analogs. While investigating leukemia susceptibility genes, we discovered a very rare p.L254P NT5C1A missense variant in the substrate recognition motif. Given the paucity of cellular drug response data from the NT5C1A germline variation, we characterized p.L254P and eight rare variants of NT5C1A from genomic databases. MATERIALS AND METHODS: Through lentiviral infection, we created HEK293 cell lines that stably overexpress wild-type NT5C1A, p.L254P, or eight NT5C1A variants reported in the National Heart Lung and Blood Institute Exome Variant Server (one truncating and seven missense). IC50 values were determined by cytotoxicity assays after exposure to chemotherapeutic nucleoside analogs (cladribine, gemcitabine, 5-fluorouracil). In addition, we used structure-based homology modeling to generate a three-dimensional model for the C-terminal region of NT5C1A. RESULTS: The p.R180X (truncating), p.A214T, and p.L254P missense changes were the only variants that significantly impaired protein function across all nucleotide analogs tested (>5-fold difference vs. wild-type; P<0.05). Several of the remaining variants individually showed differential effects (both more and less resistant) across the analogs tested. The homology model provided a structural framework to understand the impact of NT5C1A mutants on catalysis and drug processing. The model predicted active site residues within NT5C1A motif III and we experimentally confirmed that p.K314 (not p.K320) is required for NT5C1A activity. CONCLUSION: We characterized germline variation and predicted protein structures of NT5C1A. Individual missense changes showed considerable variation in response to the different nucleoside analogs tested, which may impact patients' responses to treatment.

Genetic demographic networks: Mathematical model and applications.

Recent improvement in the quality of genetic data obtained from extinct human populations and their ancestors encourages searching for answers to basic questions regarding human population history. The most common and successful are model-based approaches, in which genetic data are compared to the data obtained from the assumed demography model. Using such approach, it is possible to either validate or adjust assumed demography. Model fit to data can be obtained based on reverse-time coalescent simulations or forward-time simulations. In this paper we introduce a computational method based on mathematical equation that allows obtaining joint distributions of pairs of individuals under a specified demography model, each of them characterized by a genetic variant at a chosen locus. The two individuals are randomly sampled from either the same or two different populations. The model assumes three types of demographic events (split, merge and migration). Populations evolve according to the time-continuous Moran model with drift and Markov-process mutation. This latter process is described by the Lyapunov-type equation introduced by O'Brien and generalized in our previous works. Application of this equation constitutes an original contribution. In the result section of the paper we present sample applications of our model to both simulated and literature-based demographies. Among other we include a study of the Slavs-Balts-Finns genetic relationship, in which we model split and migrations between the Balts and Slavs. We also include another example that involves the migration rates between farmers and hunters-gatherers, based on modern and ancient DNA samples. This latter process was previously studied using coalescent simulations. Our results are in general agreement with the previous method, which provides validation of our approach. Although our model is not an alternative to simulation methods in the practical sense, it provides an algorithm to compute pairwise distributions of alleles, in the case of haploid non-recombining loci such as mitochondrial and Y-chromosome loci in humans.

NF-κB and IRF pathways: cross-regulation on target genes promoter level.

BACKGROUND: The NF-κB and IRF transcription factor families are major players in inflammation and antiviral response and act as two major effectors of the innate immune response (IIR). The regulatory mechanisms of activation of these two pathways and their interactions during the IIR are only partially known. RESULTS: Our in silico findings report that there is cross-regulation between both pathways at the level of gene transcription regulation, mediated by the presence of binding sites for both factors in promoters of genes essential for these pathways. These findings agree with recent experimental data reporting crosstalk between pathways activated by RIG-I and TLR3 receptors in response to pathogens. CONCLUSIONS: We present an extended crosstalk diagram of the IRF - NF-κB pathways. We conclude that members of the NF-κB family may directly impact regulation of IRF family, while IRF members impact regulation of NF-κB family rather indirectly, via other transcription factors such as AP-1 and SP1.