Breast cancer is one of the most common cancers with high incident rate and high mortality rate worldwide. Although different breast cancer cell lines were widely used in laboratory investigations, accumulated evidences have indicated that genomic differences exist between cancer cell lines and tissue samples in the past decades. The abundant molecular profiles of cancer cell lines and tumor samples deposited in the Cancer Cell Line Encyclopedia and The Cancer Genome Atlas now allow a systematical comparison of the breast cancer cell lines with breast tumors. We depicted the genomic characteristics of breast primary tumors based on the copy number variation and gene expression profiles and the breast cancer cell lines were compared to different subgroups of breast tumors. We identified that some of the breast cancer cell lines show high correlation with the tumor group that agrees with previous knowledge, while a big part of them do not, including the most used MCF7, MDA-MB-231, and T-47D. We presented a computational framework to identify cell lines that mostly resemble a certain tumor group for the breast tumor study. Our investigation presents a useful guide to bridge the gap between cell lines and tumors and helps to select the most suitable cell line models for personalized cancer studies. Breast cancer is one of the most frequently diagnosed life-threatening cancers in women with about 235,000 new cases expected in the United States in 2014. Breast cancer is a complex and heterogeneous disease such that they may have different prognoses. It responds to therapy differently despite similarities in histological types, grade, and stage. In the laboratory, the breast cancer is often modelled using established breast cancer cell lines due to their ease of being acquired and used [However, accumulated evidences have pointed out the genomic differences between cancer cell lines and tissue samples in the past decades –4. In thWith the quick development of the whole genome sequencing and other “-omics” techniques, now it becomes possible to systematically explore the relationship between tumor tissues and cancer cell lines and identify the cell lines that most closely resemble particular tumor subtypes. In The Cancer Genome Atlas (TCGA), the genome and expression profiles of at least 500 tissue samples per tumor type are being comprehensively characterized . The BroTraditionally, breast cancer was diagnosed into luminal A, luminal B, HER2+/ER−, basal-like, and normal-like subtypes based on gene expression profiling or immunohistochemical (IHC) characteristic . HoweverUsing the genomic information, the relationship between these primary breast tumors and the breast cancer cell lines was explored. Furthermore, as intrinsic differences exist among the breast tumor, we also attempt to figure out the correlation between the cell lines and different breast tumor groups and design an efficient computational framework which helps to select the most suitable cell line models for a specified tumor type.In our study, we only reserved breast tumor samples or cancer cell lines with both genome-wide DNA copy number information and mRNA expression profiles available. As a curation result, 543 primary breast tumor samples  profiled by TCGA  and 59 bn = 46), PR group , HER group , ERPR group , ERHER group , PRHER group , TP group , and TN group . The PRHER group was removed in the further study as there was only one sample in the group. The expression pattern of the three marker genes in all tumor samples was shown in supplementary Figure  1 in the Supplementary Material available online at http://dx.doi.org/10.1155/2015/901303.Generally, breast cancer may be categorized into luminal A, luminal B, HER2+/ER−, basal-like, and normal-like subtypes based on gene expression profiling or immunohistochemical (IHC) characteristics , 13. HowLevel 3 copy number data was downloaded for breast tumor samples from TCGA (platform: Affymetrix SNP6) , and eacsingle copy deletion (copy number < 1.5),double copy deletion (copy number < 0.5),gain of copy number (copy number > 2.5),amplification (copy number > 3.5).Four classes of abnormal segments were considered based on their estimated copy number :single cWe used data from the Agilent G4502A_07 platform for TCGA, with measurements of 17,814 genes. Differentially expressed genes were selected based on the fold change of gene expression between each groups of tumor samples and the control  under the cutoff of |log2foldchange| > 1 [CCLE expression data was obtained using Affymetrix U133 Plus 2.0 Arrays, with measurements of 18,926 genes. Differentially expressed genes were selected based on the fold change of gene expression between each cell line and the average of expression value of all the cell lines .z-scores  were derived separately for the two data sets from CCLE and TCGA, and only common genes were remained.For the comparison between gene expression data from TCGA and CCLE, robust P value less than 0.05 and genes more than two were considered as significant enriched functions for further analysis.Gene set enrichment analyses were performed for the functional annotation of the differential expressed genes. Functional Annotation Tools in DAVID Bioinformatics Resources  were usehttp://www.cancer.gov/) and literature review, and they are Estrogen Signaling pathway, ERBB pathway, PI3K/Akt/mTOR Signaling pathway, p53 Signaling pathway, Ras Signaling pathway [First, pathways closely related to breast cancer were collected via NCI website  for all groups of tumor samples from TCGA (supplementary Table  2). 399 of the DEGs were overexpressed in all the tumor groups, while 588 of them were underexpressed in all groups . There were only 5 overexpressed genes and 14 underexpressed genes unique for ER group, while there were 254 overexpressed genes and 219 underexpressed genes unique for TN group . Then, the overexpression/underexpression frequency was calculated for each of the 4,843 genes in each group. Notably, 413 of the genes differ greatly in these tumor sample groups (the deviation between the highest and the lowest frequency of the gene across the groups is bigger than 1), and they were significantly enriched in regulation of hormone levels and cell adhesion.We found that totally 384 individual genes show copy number change associated with the alteration in their expression for all tumor sample groups  whereas Among the 59 breast cancer cell lines in CCLE dataset, MCF7, MDA-MB-231, and T-47D are the three most used cell line models for breast cancer account for 82% of current PubMed citations out of the 59 analyzed cell lines . The preFor each cell line, the copy number profiles were compared with the mean copy number profile of each tumor sample group by calculating Spearman correlation coefficients using the 2,426 genes with CNVs profiles in the tumor samples . In thisThen, the gene expression profiles of each cancer cell line were compared with the mean gene expression profile of each tumor sample group by calculating Spearman correlation coefficients using the 4,843 genes differentially expressed in the tumor samples . In thisAdditionally, we examined the overlap ratio of genes that showed copy number change associated with alteration in their expression between each breast cancer cell line and each tumor sample group . This raBreast cancer is a complex disease that manifests as a result of coordinated alterations on genomic, epigenomic, and proteomic levels. Therefore, it is important to take into account the multiple datasets together to optimize strength of biological information across multiple assays relevant to breast cancer. With the accumulated copy number profiles and gene expression profiles for different cancer cell lines and tumor samples, we could evaluate whether a certain breast cancer cell line is a good model for a specific tumor group by integration of these two aspects of information. We designed a ranking aggregation model of the cell lines according to their correlation with each tumor group based on the integration of copy number profiles and gene expression profiles. First, the breast cancer cell lines were ranked in descending order of their similarity with each tumor group using copy number profiles and gene expression profiles, respectively. Then, for each tumor group, the two derived ranking lists of the breast cancer cell lines were fused into one ranking list using R package RankAggreg . In thisFor each tumor group, the cell lines ranked in the top resemble the tumor group best and might be the best cell line models for laboratory studies. Suggested by the final ranking list, the best three cell line models for each breast tumor group were listed as follows: CAMA1, BT483, and HCC202 (ER group); HCC70, HCC1143, and HCC1937 (PR group); MDAMB453, HCC2218, and UACC893 (HER group); MDAMB453, CAL148, and ZR751 (ERHER group); HCC202, BT483, and ZR751 (ERPR group); MDAMB453, MDAMB361, and UACC893 (TP group); HCC1599, HCC70, and HCC1569 (TN group). There results may provide useful clues for future personalized breast cancer study.Similarly, we also evaluated the correlation between all the cancer cell lines in CCLE and breast tumor sample groups, using the copy number information and gene expression profiles (supplementary Tables  4 and 5). From the perspective of either copy number or gene expression profiles, respectively, some breast cancer cell lines were ranked with high correlation with any of the breast tumor groups while, interestingly, we also identified that some lung cancer cell lines and ovary cancer cell lines also present high correlation with at least one of the breast tumor groups.413 of the DEGs differ greatly in the frequency of overexpression/underexpression across the different tumor sample groups. After conducting the gene set functional enrichment analysis, we found these genes were significantly enriched in biological processes including the regulation of hormone levels and cell adhesion. The enrichment in the regulation of hormone levels is expected. As cell adhesion is related to cancer metastasis, we checked the literatures and found that different breast cancer subtypes show disparity in metastasizing to different sites , 32. HowThe integrative genomic study of copy number profiles and gene expression profiles collected on the same set of cancer cell lines and patient samples could serve as an efficient way to depict the characteristics of different tumor types and cancer cell lines. Besides, the integrated investigation of the two perspectives also provides a guide to reveal the relationship between breast cancer cell lines and the tumor samples, as well as selecting the suitable cell lines for the corresponding breast tumor group. In general, the correlation between the cancer cell lines and the tumor sample groups indicated by the two aspects was consistent with each other. The association between copy number variations and gene expression has been investigated by several research groups , 34. As http://www.atcc.org/) which is one of the largest biosources in the world and offers investigators a complex array of human, animal, insect, fish, and stem cell lines, these three cell lines are not from primary breast cancer but are metastatic breast cancer cell lines derived from pleural effusion. Some of the cell lines  have low correlation to any one of the primary tumor groups either calculated using copy number profiles or gene expression profiles. The low correlation probably lies in that they are not originated from primary tumors, or maybe these cell lines were contaminated during their continual culture.Some of the cancer cell lines have high correlation with the preclassified tumor group based on the presence or absence of expression of ER, HER2, and PR in the cell line, while a big part of them does not show this tendency, including the most used MCF7, MDA-MB-231, and T-47D. According to ATCC  for all groups of tumor samples are listed in Supplementary table 1 and Supplementary table 2. The 384 individual genes showed copy number change associated with alteration in their expression for all tumor sample groups are listed in Supplementary table 3. The cor-relation between all the cancer cell lines in CCLE and breast tumor sample groups using copy-number information or gene expression profiles are given in Supplementary table 4 and Supplementary table 5.


Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by extensive synovitis resulting in erosions of articular cartilage and marginal bone that lead to joint destruction. The autoimmune process in RA depends on the activation of immune cells, which use intracellular kinases to respond to external stimuli such as cytokines, immune complexes, and antigens. An intricate cytokine network participates in inflammation and in perpetuation of disease by positive feedback loops promoting systemic disorder. The widespread systemic effects mediated by pro-inflammatory cytokines in RA impact on metabolism and in particular in lymphocyte metabolism. Moreover, RA pathobiology seems to share some common pathways with atherosclerosis, including endothelial dysfunction that is related to underlying chronic inflammation. The extent of the metabolic changes and the types of metabolites seen may be good markers of cytokine-mediated inflammatory processes in RA. Altered metabolic fingerprints may be useful in predicting the development of RA in patients with early arthritis as well as in the evaluation of the treatment response. Evidence supports the role of metabolomic analysis as a novel and nontargeted approach for identifying potential biomarkers and for improving the clinical and therapeutical management of patients with chronic inflammatory diseases. Here, we review the metabolic changes occurring in the pathogenesis of RA as well as the implication of the metabolic features in the treatment response. The elucidation of metabolic pathways in chronic inflammatory conditions, as rheumatoid arthritis (RA), give new insights on pathogenesis, clinical features and complications, and treatment outcome.The systemic effects mediated by pro-inflammatory cytokines in RA impact on metabolism. Moreover, RA pathobiology seems to share some common pathways with atherosclerosis including endothelial dysfunction that is related to the underlying chronic inflammation.In the presence of pathogens or products of inflamed tissues that provoke inflammation, macrophages and lymphocytes rapidly switch from a resting to a highly active state and exhibit a pronounced increase in production of host defence factors resulting in enhanced phagocytosis and antigen presentation.Highly active immune cells undergo metabolic changes with the involvement of the phosphatidylinositol- 3-OH kinase (PI(3)K)–Akt and the mechanistic target of rapamycin (mTOR) pathways.Differences in urine and serum metabolic profiles in patients affected by RA may be useful for the assessment of both disease activity and treatment response.Although the autoimmune process in RA depends on the involvement of immune cells, which utilize intracellular kinases to respond to external stimuli, further research efforts are necessary in order to define more specific biomarkers to be detected in the management of that disease.As the metabolic profile for individual patients is highly dynamic compared with, for example, genes and protein levels, it would be worth studying how these metabolites correlate with disease activity. In the near future, the metabolite profile of individual patients can be used as an important tool for predicting the disease course and improving the treatment.All the oxidative damage markers correlated positively with disease activity in RA. These inflammatory pathways affect not only synovial tissues but also the endothelial structure in blood vessels leading to a vascular dysfunction. However, debated data are reported concerning the possibility of an early diagnosis of the cardiovascular (CV) involvement in RA patients. Thus, more specific biomarkers may facilitate the early detection of CV complications occurring in RA patients.γ agonists) in RA patients still remain unclear.Drugs that act on lipid/glucose metabolisms appear to confer an improvement on inflammatory features in RA patients. However, the significance of statin treatment and the effect of drugs modulating the insulin sensitivity (such as the peroxisome proliferator-activated receptor (PPAR)-1 RA is considered an autoimmune disease since the production of the rheumatoid factor (RF), an autoantibody directed against determinants on the Fc fragment of immunoglobulin (Ig) G molecules, was first observed. The most relevant autoantibodies appear to be the anti-citrullinated protein antibodies (ACPA). Citrullination is the critical step for the recognition of several proteins , highly expressed in the synovial membrane during inflammation, by ACPA. The pathogenesis of RA  loci. In particular, the DRβ1 chain, called 'shared epitope' (SE), is associated with the production of ACPA and with the disease.5 Signal transducer and activator of transcription 4 (STAT4) is a member of the STAT family of transcription factors.6 This molecule has a key role for the interleukin (IL)-12 signaling in T cells and natural killer (NK) cells, leading to the production of interferon (IFN)-γ and the differentiation of T helper (Th)1 and Th17 cells.7 Other candidate genes associated with RA are cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4), the α and β chain of the IL-2 receptor (IL-2RA and IL-2RB), IFN regulatory factor 5 (IRF5), the locus located between tumor necrosis factor (TNF) receptor-associated factor 1 and C5 genes (TRAF1/C5), the gene near TNF-α -induced protein (TNFAIP3), and the co-stimulatory molecules CD40 and CD28.8 Several environmental factors have been studied in RA and the interaction between genetic and environmental factors has been demonstrated in RA. Smoking, infections, sex hormones, birth weight, alcohol intake and socioeconomic status can modify the risk for RA.10 The synovial membrane is a connective tissue formed by two main layers, the synovial lining and the synovial sublining. The synovial lining is composed by two types of synoviocytes, called macrophage-like and fibroblast-like synoviocytes, because of their surface marker expression and morphology. The synovial sublining is a soft, loose connective tissue that facilitates smooth movement of the joints. It contains blood and lymph vessels, nerve fibres and few cells including macrophages, fibroblasts and adipocytes.12 In RA patients, the synovial membrane is characterized by cellular hyperplasia, increased vascularity and an infiltrate of inflammatory cells that invasively grow and destroy the adjacent cartilage and bone. The synovial hyperplasia, called 'pannus' is an increased thickening of the lining layer caused by the combination of cellular proliferation in situ, influx of cells from the circulation and reduced apoptosis with increased oxygen demand and consequent local hypoxia. Inadequate oxygenation drives the inflammatory response and the mechanisms of angiogenesis.14 This process promotes further infiltration of inflammatory cells, production of inflammatory mediators and matrix degradation.17 The infiltrate in RA synovitis is composed by CD4+ T cells, B cells, plasma cells, NK cells, dendritic cells (DCs) and mast cells. Lymphoid aggregates of variable size and organization level are present in 50–60% of RA patients even if they are not specific of the disease. The development of the inflammatory process in RA involves many different cell types and a complex cytokine network. CD4+ T cells, upon activation and expansion, develop into different T helper cell subsets with different cytokine profile and distinct effector functions. Activated T cells that secrete IFN-γ, IL-2, IL-12, IL-18, TNF-α and granulocyte-macrophage colony-stimulating factor (GM-CSF), typically considered Th1 cytokines, are produced in the synovial fluid and expressed in the synovial membrane.18 Moreover, IL-17, which is produced by Th17 and mast cells, has been detected in RA synovial fluid.19 These cytokines activate macrophages to secrete other pro-inflammatory cytokines such as IL-1β,20 IL-6, TNF-α and IL-12, induce the nuclear factor (NF)-κB ligand (RANKL) expression on T cells, promote the differentiation of B cells and stimulate the release of matrix metalloproteases (MMPs) provoking the degradation of the cartilage and the activation of osteoclasts leading to the bone resorption.21 Macrophages are the most important source of those cytokines, however, many studies demonstrate that also cell contact interactions,23 between synovial T lymphocytes and adjacent macrophages or fibroblasts, represent an alternative route to generate cytokines.24 Clinically, RA manifests with a symmetric polyarthritis characterized by synovitis that involves the small and large joints.25 Despite articular and periarticular manifestations being predominant, RA may affect many organs and tissues.26 Large epidemiological studies from the last several decades have confirmed that RA patients are 30–60% more likely to suffer from cardiovascular diseases (CVD) than subjects from the general population.28 The impact of traditional risk factors on the development of CVD in RA is an area of active research. Disability, as measured by the Health Assessment Questionnaire (HAQ), is a predictor of both overall and CV mortality; thus, HAQ remission should be included among the major outcomes for defining remission in all RA cohorts.29 Collectively, evidence suggests that risk scores developed for the general population based on traditional CV risk factors, such as hypertension, type 2 diabetes mellitus (T2DM) or hyperlipidemia levels are unlikely to accurately estimate CV risk in RA, highlighting the need for RA-specific risk prediction tools.30 In this context, RA disease activity scores, inflammatory markers and extra-articular manifestations have repeatedly shown significant associations with metabolic disorders and increased CV risk.30Rheumatoid arthritis (RA) is a chronic inflammatory and systemic disease characterized by extensive synovitis resulting in erosions of articular cartilage and marginal bone that lead to joint destruction.is of RA  is a multh century gives insight into disorders in which there are obvious dysfunctions in metabolism, such as diabetes and atherosclerosis. Furthermore, alterations in metabolic regulation are now seen to be just as important in other diseases, such as cancer and inflammatory conditions.33 Studies on the metabolism of activated macrophages began in the 1960s. Monocytes from peritoneal exudates were shown to depend mainly on glycolysis as a source of metabolic energy, whereas in vitro culture of monocytes caused a significant increase in glycolysis.34 In 1982, a study showed that in an in vivo model (graft versus host) of immune activation, lymphocytes exhibited increased glycolysis, which was shown to be important for proliferation, together with a marked increase in glutamine use.35 Activated macrophages have been shown to have a high hexokinase activity, the first enzyme involved in glycolysis and in the pentose phosphate pathway. Glycolysis and glutamine metabolism are also markedly increased during phagocytosis.36 More recent studies have confirmed and extended these early findings. A shift towards aerobic glycolysis occurs in macrophages and DCs activated by the bacterial product lipopolysaccharide, acting through Toll-like receptor 4 (TLR4), in inflammatory macrophages and in Th17 lymphocytes.38 On the other hand, cells that limit inflammation, such as regulatory T cells (Treg),39 anti-inflammatory macrophages and quiescent memory T cells that carry the CD8 antigen, exhibit oxidative metabolism with more limited rates of glycolysis.40 Metabolomics is the scientific study of chemical processes comprising metabolites that involves the rapid, high throughput characterization of the small molecule metabolites found in an organism. Instead of monitoring a handful of biochemicals, comprehensive biochemical profiling analyzes the change in hundreds of biochemicals including metabolites in the cells and components in the media. The metabolome is defined as those molecules with an atomic mass less than 1.5 kDa. Because no single analytical method can accommodate the chemical diversity of the entire metabolome, various methods such as nuclear magnetic resonance spectroscopy and mass spectrometry have been used, with the latter coupled to an array of separation techniques including gas and liquid chromatography.41 This metabolomic approach allows the analysis across different reactors over time that can help to identify and address rate-limiting media nutrients and biochemicals related to cell toxicity.43 The feasibility of metabolomics for biomarker discovery is supported by the assumption that metabolites are important players in biological systems and that inflammation and diseases cause the disruption of biochemical pathways. Inflammation is triggered in response to tissue injury or infection, and mounting an inflammatory response is an energy-intensive process. In the presence of pathogens or the products of inflamed tissues that provoke inflammation,44 macrophages and lymphocytes rapidly switch from a resting state to a highly active state, exhibiting a pronounced increase in production of host defence factors, enhancing phagocytosis and antigen presentation.45 It is perhaps not surprising that such highly active cells undergo metabolic changes similar to those seen in tumor cells. The similarity between the metabolism that occurs in tumor cells and activated T cells has already been pointed out, with particular roles for the phosphatidylinositol- 3-OH kinase (PI(3)K)–Akt and the mechanistic target of rapamycin (mTOR) pathways, as well as the transcription factor c-myc.46 One difference between metabolic pathways in tumor cells and inflammatory cells is that the changes in tumor cells are driven largely by mutations, whereas those in inflammatory cells are driven by extracellular signals. In the last few years, several lines of evidence suggested that several metabolic changes in cells that participate in inflammation are needed to obtain polarization and activation of cells as lymphocytes.47 The products of inflamed tissues that provoke inflammation can activate T cells.35 Indeed, T cells are prime examples of how cell metabolism can be dramatically altered to support the specific needs and functions of each cell state. A shift towards high glycolysis is a hallmark of inflammatory cells, whereas oxidative phosphorylation is a hallmark of anti-inflammatory cells. Increased glycolysis in lymphocytes grown in culture was shown as early as 1966.34 This has also been shown in cells that carry the CD4 antigen, in which CD28 signalling increases glycolysis through the activation of PI(3)K and Akt.48 Glucose uptake and glycolysis are increased in Th17 cell β-oxidation (as well as Th2 and Th1 cells) compared with Treg cells, which in turn have increased membrane potential and oxidize lipids at a higher rate than other subsets of cells that carry the CD4 antigen.50 There is, however, likely to be a gradation towards either glycolysis or oxidative metabolism because Th17 cells still exhibit some lipid oxidation. A central feature that allows this flexibility in metabolism is direct regulation of metabolic pathways by cell-extrinsic signals that drive T-cell survival, growth and proliferation.51 In each case, if metabolism fails to match the demands of the cell, cell function is impaired, or cell can undergo apoptosis.52 Conversely, excess metabolism may prevent apoptosis, exacerbate cell function, and thus promote T-cell hyper-reactivity, leading to autoimmunity and inflammatory diseases.54 Thus, it is critical to appreciate how T-cell metabolism is regulated, and how alterations in cell metabolism impact T-cell function and fate.55 Metabolomic changes in T lymphocytes are summarized in Metabolism is viewed simply as a mean to generate a store of energy by catabolism, and to generate macromolecules for cell maintenance and growth through anabolic pathways. The elucidation of metabolic pathways in the 2056 Thus, the extent of the metabolic changes and the types of metabolites seen may represent good markers of cytokine-mediated inflammatory process in RA. Evidences support the role of metabolomic analysis in RA patients as a novel and non-targeted approach for identifying potential biomarkers.57 Using the metabolomic approach, the identification of several metabolites may provide insights into RA disease mechanisms and highlight their potential as markers of disease activity, metabolic and CV complications, and response to therapy.59The widespread systemic effects mediated by pro-inflammatory cytokines in RA impact on metabolism. Many of metabolites that are particularly correlated with inflammation may contribute to the increased prevalence of metabolic syndrome (MetS) and atherosclerosis associated with RA.60 The major components of MetS include insulin resistance (IR), central obesity, dyslipidemia and hypertension.61 It is widely accepted that MetS identifies central obesity as the main risk factor for CVD and T2DM. Various diagnostic criteria for MetS have been proposed by different organizations. Standard criteria are based on having three or more of the following five risk factors: high waist circumference , high triglycerides (≥150 mg/dl), low HDL-cholesterol , high blood pressure (systolic ≥130 mm Hg or diastolic ≥85 mm Hg or medication use), and high blood glucose (≥100 mg/dl or presences of diabetes or medication use).62 Evidence concerning the prevalence of MetS in RA showed that MetS is significantly more prevalent in RA patients than in controls, and evidence documented an association between RA disease activity and MetS.64 Thus, MetS might determine inflammatory milieu leading to the occurrence of more severe RA. Recently, it has been described that abdominal obesity is associated with high disease activity, high disability, physical inactivity and poor mental health in a cohort of 200 RA patients.65 Evidence clarified that adipose tissue is a dynamic endocrine organ that releases several bioactive substances including some pro-inflammatory cytokines like TNF-α and IL-6, and specific cytokines, termed adipokines, that may have a key role in RA pathogenesis.28 Adipokines were recently proposed as novel biomarkers and regulators of MetS: they are pleiotropic molecules that contribute to the so-called low-grade inflammatory state creating a cluster of metabolic aberrations. RA is associated with increased production of adipokines that are produced mainly in adipose tissue but also in synovial cells. Among the different adipokines, leptin and adiponectin were identified as relevant factors involved in interactions between metabolism and rheumatic disorders.66 Leptin is mainly produced by adipocytes, and its circulating levels positively correlate with white adipose tissue (WAT) mass and body mass index. Leptin has been associated with RA owing to its ability to modulate bone and cartilage metabolism although it is still unclear whether leptin can damage or protect joint structures in RA. In fact, leptin is generally considered to be pro-inflammatory; on the other hand, it has also been reported to be associated with reduced radiographic joint damage, and this effect could be related to its anabolic effects. Kontunen et al.67 registered higher leptin levels in subjects with arthritis and MetS than in patients with arthritis without MetS. This suggests that leptin is associated with MetS but not directly with arthritis, although a marked increase in plasma levels of leptin in patients with RA was noted. Moreover, in RA, leptin is able to modulate the activity of multiple immune cells.68 Besides leptin, adiponectin is another adipokine that seems to be involved in RA pathobiology. It shows anti-inflammatory, insulin-sensitizing and anti-atherogenic properties.69 Adiponectin levels have been found to be higher in RA patients than in healthy controls; moreover, synovial fluid levels of adiponectin were significantly higher in RA than in osteoarthritis patients.70 Evidence reported that in RA, adiponectin promotes inflammation through cytokine synthesis, attraction of inflammatory cells to the synovium and recruitment of prodestructive cells via chemokines, thus promoting matrix destruction at sites of cartilage invasion.71 Frommer et al.71 described that the different isoforms of adiponectin can induce gene expression and protein synthesis in human RA synovial fibroblasts, lymphocytes, endothelial cells and chondrocytes, supporting the concept of adiponectin being involved in the pathophysiologic modulation of RA effector cells. Recent findings suggest that visfatin, also called pre-B cell colony enhancing factor, may act as a regulator of the inflammation and joint destruction in animal models and resulted increased in serum and sinovial fluid.74 Serum and synovial fluid visfatin concentrations were reported to be higher in RA patients compared with healthy controls as well as its expression by rheumatoid synoviocytes at sites of attachment and invasion into both cartilage and bone.75 Evidences suggest that B-cell activating factor (BAFF), which has been shown to participate in B-cell survival and B- and T-cell maturation, is synthesized also by mature adipocytes and that the expression of its receptors is upregulated under pro-inflammatory conditions. Those findings suggest that BAFF may be considered as a new adipokine representing a link between obesity and inflammation.76 WAT also produces TNF-α and IL-6 that correlate with IR and MetS.77 Changes in lipid profiles in the blood of RA patients have been widely described, and have been suggested to be a major contributing factor to the accelerated atherosclerosis associated with RA.78 Serum levels of lipids and lactate are important discriminators of inflammatory burden in early arthritis and also reflect inflammatory disease activity in patients with synovitis.56 Madsen et al.79 compared the serum metabolic profile of patients with RA with that of healthy controls and patients with psoriatic arthritis (PsA) and found that RA or PsA patients could be distinguished with good specificity and sensitivity according to their metabolic profile. Recent evidences demonstrate that serum metabolic fingerprint of patients with active established RA differs from that of healthy controls.56 Authors report that 3-hydroxybutyrate results elevated in RA patients suggesting an increased level of lipolysis compared with controls.56 Also urinary metabolites can be analyzed as markers of cytokine-mediated inflammatory processes in RA. Urinary histamine have been suggested as a discriminator in urinary metabolites: the sources of the discriminanting histamine could be the mast cells at the synovial infiltrates and the histidine degradation related to the direct effects of TNF in accelerating muscle breakdown.81 Differences in the metabolic profiles of baseline urine metabolites, such as histamine, glutamine, phenylacetic acid, xanthine, xanthurenic acid and creatinine, were demonstrated in patients with RA who had a good response to anti-TNF therapy compared with those who had not.58 Those findings suggest the relevance of the development of novel approaches for the optimization of the RA therapy.Metabolic syndrome (MetS) is a cluster of cardiometabolic disorders that result from the increasing prevalence of obesity.82 Atherosclerosis is an inflammatory condition and starts as a response to injury favoring ED. The ED is defined as impaired endothelium-dependent blood-vessel dilation in response to a stimulus and is associated with increased expression of adhesion molecules, pro-inflammatory cytokines, pro-thrombotic factors, oxidative stress upregulation and abnormal vascular tone modulation. Over the last decade, a role for ED in the CV complications of inflammatory diseases has been hypothesized and several studies were performed in order to evaluate ED as a marker for risk of CV events in patients with chronic inflammatory diseases like RA.83 The inflammatory cascades consist in the release of pro-inflammatory cytokines, and reactive oxygen species (ROS) appear responsible for the association between RA and atherosclerosis. Inflammatory cells are able to generate oxidants, including superoxide, which are critical in non-specific host defense against pathogens such as bacteria, viruses and cancer cells. ROS and their byproducts are also implicated in arterial dysfunction via the inactivation of nitric oxide (NO), a potent vasodilator and antiaggregating molecule produced by the endothelium resulting in induction of vascular damage.84 All of the ROS cause an imbalance of redox state within the inflamed tissue, resulting in the activation of NF-κB and the transcription of several pro-inflammatory cytokines including TNFα, IL-1 and IL-6, which have key roles in the progression of RA and therefore are therapeutic drug targets.85 In RA, ROS have been attributed to directly contribute towards the destructive, proliferative synovitis.86 Synovial fluid and peripheral blood of RA patients display high levels of ROS and ROS-generated molecules that oxidize and degrade the major components of cartilage and bone, including collagen and hyaluronic acid.87 All the oxidative damage markers correlated positively with the disease activity score calculated on 28 joints.86 These inflammatory pathways affect the endothelial structure in blood vessels as well as synovial tissues in RA causing vascular dysfunction. Low circulating endothelial progenitor cells (EPCs) have been described in many conditions associated with increased CV risk, including RA. Recent evidence reports that circulating EPC counts in RA patients are reduced compared with non-RA controls and closely associated not only with bone erosion but also with ED assessed by brachial flow-mediated dilation (FMD).88 Authors reported that levels of asymmetric dimethylarginine (ADMA), an endogenous inhibitor of NO synthase (NOS), are elevated in the serum of RA patients and are related with the Homeostasis Model Assessment (HOMA) index.89 In this context, ADMA, by blocking NO generation, initiates and promotes processes involved in atherogenesis and may reflect an important pathway linking abnormal insulin metabolism with ED in RA.89 Evidence indirectly supports that remission in RA allows diminished CV morbidity. Patients with active RA, but not those in remission, had significantly increased levels of CV risk markers -probrain natriuretic peptide (BNP), hypertension, total cholesterol, reactive hyperaemia index, measures of arterial stiffness and intima media thickness -IMT) than the control group.90 As the IR is increased in RA patients, independent of obesity, recent studies have examined the association between IR and NT-proBNP in RA. The prevalence of IR was confirmed to be higher among RA patients than controls and IR results associated with higher, rather than the expected lower, concentrations of NT-proBNP. Moreover, authors hypothesized that this may be related to increased serum levels of IL-6 suggesting that IL-6 may be mechanistically involved in the relationship between IR and NT-proBNP in RA.91RA pathobiology seems to share some common pathways with atherosclerosis, including endothelial dysfunction (ED) that is related to underlying chronic inflammation and presents in the early phases of the disease.92 Methotrexate (MTX) is a potent antimetabolite drug that interferes with the metabolism of folic acid by the inhibition of dihydrofolate reductase and represents the first-line treatment in inflammatory arthritis.93 MTX, as compared with nonsteroidal anti-inflammatory drugs that merely alleviate temporarily the symptoms of joint inflammation, changes the course of the disease, retarding or even preventing the development of bone erosions. As TNF-α has a central role in the pathogenesis of RA, anti-TNF-α drugs are frequently used in forms of RA that are resistant to traditional therapeutic approaches and have acquired a prominent place in the management of rheumatologic conditions.100 Current immunosuppressive therapies act on both the adaptive and the innate immunity leading to an improvement on disease outcome.101 In this context, corticosteroids, MTX, sulfasalazine, leflunomide and cyclosporine A, which are used in the management of RA, exert a modulation of T-cell functions because of their effects on pro-inflammatory Th1-driven cytokines and on Th1/Th2 immune-mediated response. RA medications such as corticosteroids as well as nonsteroidal anti-inflammatory drugs and DMARDs may interfere with metabolic homeostasis conferring some CV risk.102 Data about the effect of synthetic DMARDs and/or biological DMARDs in this context remain controversial. An increasing number of studies are performed to explore the effect of antagonizing TNF-α and IL-6 on the CV outcomes in RA patients.105 Clinical trials concerning the metabolic effects of RA treatments are reported in α therapy in RA patients, and interestingly, the restoration of EPC counts seems to be attenuated in patients with a higher bone erosion score compared with those with a lower bone erosion score, despite a similar improvement in disease activity.106 Evidences report that there were differences in the metabolic profiles of urine samples of patients with RA who responded to anti-TNF therapy compared with those who did not.58 Moreover, different anti-TNF-α agents seem to alter metabolites differently because of their specific mechanisms of actions. Those findings suggest that metabolomic techniques can predict outcome to anti-TNF therapy in patients with RA, providing a sensitivity and specificity for response that has potential clinical utility.58 Drugs that act on lipid/glucose metabolisms appear to confer an improvement on inflammatory features in RA patients -γ agonists) are ongoing in order to provide new potential treatment to improve both the inflammatory status and the CV outcome in RA patients (The therapy management of RA rests primarily based on the use of disease-modifying antirheumatic drugs (DMARDs). These agents are commonly characterized by their capacity to reduce or reverse signs and symptoms, disability, impairment of quality of life, inability to work and progression of joint damage, and thus to interfere with the entire disease process.patients . In thispatients .58 Both synthetic and biological DMARDs are reported to be effective in the treatment of inflammatory arthritis; however, although there is a very good response of some patients to certain therapy, there is also a complete lack of response in a large number of other patients.108 As the biological effects of those treatments and the mechanisms underlining the cell response are still not well understood, a more detailed understanding of the biochemical changes in the immune cells is required to elucidate toxicity pathways, the oxidative stress effects and the response mechanisms triggered by treatments. Therefore, the analysis of the potential effects of the drugs on the metabolome by analyzing the global metabolic changes associated with certain therapy can be a reliable goal. As the metabolic profile for individual patients is highly dynamic compared with, for example, genes and protein levels, it is relevant to study how these metabolites correlate with disease activity. It is possible that the metabolite profile of individual patients can be used as a tool for predicting the RA disease course and thereby facilitates the early diagnosis of the CV complications in order to improve the effectiveness of the treatment to be introduced.The widespread systemic effects mediated by pro-inflammatory cytokines in RA impact on metabolism. Altered metabolic fingerprints may be useful in predicting the development of RA in patients with early arthritis as well as the response to the therapy.


As such, the present work aims at integrating genotoxicity and oxidative DNA damage induced by sediment-bound toxicants in HepG2 cells with oxidative stress-related effects observed in three species collected from an impacted estuary. Distinct patterns were observed in cells exposed to crude mixtures of sediment contaminants from the urban/industrial area comparatively to the ones from the rural/riverine area of the estuary, with respect to oxidative DNA damage and oxidative DNA damage. The extracts obtained with the most polar solvent and the crude extracts caused the most significant oxidative DNA damage in HepG2 cells, as measured by the formamidopyrimidine-DNA glycosylase (FPG)-modified Comet assay. This observation suggests that metals and unknown toxicants more hydrophilic than polycyclic aromatic hydrocarbons may be important causative agents, especially in samples from the rural part of the estuary, where oxidative DNA damage was the most significant. Clams, sole, and cuttlefish responded differentially to environmental agents triggering oxidative stress, albeit yielding results accordant with the oxidative DNA damage observed in HepG2 cells. Overall, the integration of in vivo biomarker responses and Comet assay data in HepG2 cells yielded a comparable pattern, indicating that the in vitro FPG-modified Comet assay may be an effective and complementary line-of-evidence in ERA even in particularly challenging, natural, scenarios such as estuarine environments.The application of the Comet assay in environmental monitoring remains challenging in face of the complexity of environmental stressors, e.g., when dealing with estuarine sediments, that hampers the drawing of cause-effect relationships. Although the  Ever since the original publication of the protocol by in vitro approaches with fish cell lines exposed to aquatic sediment extracts to determine the genotoxic potential of bioavailable pollutants  produced directly or indirectly as a consequence of exposure to xenobiotics. As such, oxidative stress biomarkers allow a pertinent approach to evaluate sub-individual effects of toxicological challenge and therefore enable an overall assessment of the effects of environmental contaminants or their mixtures . The present study aims essentially at comparing the performance, as ecotoxicological indicators, of the formamidopyrimidine-DNA glycosylase (FPG)-modified Comet assay in HpG2 cells exposed to sediment-bound contaminants with that of common oxidative stress-related biomarkers determined in three distinct organisms collected from an impacted estuarine area. Ultimately, it was intended to contribute for the validation of the data produced by the in vitro Comet assay as a LOE in ERA strategies. For this purpose, the present study integrates and re-interprets the findings from recent research on the Sado Estuary , taken as the case study, and presents for the first time data from the in vitro analysis of sediment extract fractioning.Studies attempting to integrate DNA damage retrieved from the Figure 1). Part of the estuary is classified as a natural reserve and, besides industry and shipping, the estuary is also very important for tourism, fisheries, and aquaculture. The river itself transports to the estuary fertilizers, pesticides from run-offs of the agriculture grounds upstream and metals from pyrite mining areas. The estuary has been judged to be globally moderately impacted by pollutants albeit ecotoxicologically diversified . On its turn, the southern region (Sado 2), where the mouth of the river Sado is situated, is essentially agricultural . The reference sediment (R) was collected from a sandy shellfish bed with high oceanic influence, from where clams were collected (see Ruditapes decussatus) were collected from sites R and S1 upon sediment collection. Fish , and cuttlefish  were collected from acknowledged fishing grounds in Sado 1 and Sado 2 . Fish and cuttlefish biomarkers were contrasted to data of animals collected outside the estuary, within the same geographical region. However, sediment analyses  from this external area yielded similar results to that of sediment R, which was found to be essentially devoid of any significant contamination, in spite of its proximity to sites N1 and N2. For such reason, oxidative stress biomarker data from fish and cuttlefish were geographically allocated to site R, for computational purposes. In order to congregate sediment toxicant levels into more manageable indices, these data were used to estimate sediment quality guideline quotients (SQG-Qs) for each class of contaminants and for total contamination, according to Table 1 summarizes the main sediment contamination data and respective SQG-Qs. Sediment data were retrieved from Sediment samples were collected from five different sites within the Sado estuary between spring 2007 and spring 2010. Sites N1 and N2 (Sado 1) are located off Setúbal’s harbor and industrial belt, respectively. Sites S1 and S2 (Sado 2), in the southern part of the estuary are located near an agricultural region with direct influence from the River Sado ; fraction 3 with DCM, and fraction 4 with methanol (the most polar solvent). The solvents were afterward evaporated at 45°C and the extracts reconstituted in dimethyl sulfoxide (DMSO). The concentrations of the extracts were estimated as mg sediment equivalent (SEQ) per mL of cell culture medium.Sediment contaminant extraction follows the protocol of The human hepatocellular carcinoma cell line (HepG2) was obtained from the American Type Culture Collection (ATCC ref. HB-8065) and cultured as described in S-transferase (GST) activity in fish; lipid peroxidation, GST activity, total glutathione (GSHt), and reduced/oxidized glutathione ratio (GSH/GSSG) in cuttlefish. Details of the procedures can be found in Table 2.The multiple oxidative stress-related biomarker responses in wild organisms were retrieved from 50) for cytotoxicity and genotoxicity was estimated for crude and fractionated extracts to allow the comparison of their relative cytotoxic and genotoxic potencies (see 50 (with and without FPG treatment) was estimated by considering the highest measured %DNA in tail throughout the experiments as the maximal effect, since the %DNA in tail should not reach 100%. The EC50 values were estimated from normalized data through log-logistic regression and were computed using Stat4Tox 1.0 (Joint Research Centre of the European Commission), built for the R platform  estimates for each biomarker and organism. The scores were used to calculate the area (A) connecting consecutive coordinates (data points) in star plots. The IBR for each area  and S for each species were then calculated through the sum of the respective A values. See The integrated biomarker response (IBR) indice was computed to integrate oxidative-stress biomarker responses determined in cuttlefish digestive gland , flatfish liver , and clam digestive gland , according to the method described by http://www.hidrografico.pt). In order to obtain a general overview of the sediments’ contamination status, SQG-Q values for total contamination, metals, and organic toxicants were used for the analysis. The approach included also the EC50 estimates obtained from the Comet assay data (with and without FPG treatment) plus the global IBR for each area . Interpolation of data points to raster layers was achieved through the inverse distance weight (IDW) algorithm from minimum–maximum normalized values.Data were mapped through a geographical information system (GIS) approach using QGis 2.0 and the digital map for mainland coastal waters (EPSG:4326 – WGS 84 coordinate system) made available by the Hydrographic Institute of the Portuguese Navy  and the Kruskall–Wallis Median Test adaptation for multiple comparisons , was highly variable. All extracts from the reference sediment (R) failed to yield significant cytotoxicity at the tested concentrations. Similar results were obtained for fractions 2 and 3 of any sediment. The lowest EC50 estimates, indicating higher cytotoxic potency, were obtained for fraction 1 (crude extract) of samples N1 and N2 (Sado 1 area). The cytotoxicity data were used to select the dose-range for genotoxicity testing, in order to avoid interference from cytotoxic events causing DNA strand breakage.The cytotoxicity of the different extracts, as evaluated by ECFigure 2. Non-oxidative strand breakage  tended to increase with extract concentration, especially following exposure to extract fractions 1 and 4. Overall, DNA strand breakage was accentuated by the FPG-linked Comet assay . The increase in total DNA damage in FPG-treated HepG2 cells was more pronounced following exposure to extracts S1 and S2 , attaining approximately 30% of DNA in the nucleoids’ tail. Conversely, no sizable effects were observed in cells exposed to any of the extracts from sediment R.Examples of Comet nucleoids from exposed HepG2 cells are given in 50 estimates for DNA strand breakage revealed distinct trends between estuarine areas, sediment samples, and oxidative/non-oxidative damage (Table 4). Cells exposed to the crude extracts of Sado 1 sediment samples N1 and N2 yielded the lowest EC50 estimates for both FPG-treated and non-treated samples (meaning higher DNA damage at similar SEQ). In general, the FPG-modified Comet assay, which includes oxidative damage, resulted in decreased EC50 estimates. Furthermore, comparing data from the FPG-modified Comet assay to the conventional assay evidenced that the highest increase in oxidative DNA strand breakage occurred following exposure to sediment extract S1, fraction 1 , and S2, fraction 1 (DCM:methanol) as well, for which no computable EC50 could even be retrieved from the conventional Comet assay. Overall, fractions 2 (n-hexane) and 3 (DCM) failed to produce estimates due to low induction of genotoxic effects. No EC50 values could be estimated from data of cells exposed to any of the fractions from the reference sediment (R). No correlations were found between cytotoxicity EC50 and DNA strand breakage EC50 estimates, with or without FPG-treatment .The ECTable 2). In accordance, distinct IBR scores were obtained from each surveyed species. However, the aggregated results indicate a similar trend to increase oxidative stress responses and effects in animals collected from the impacted sites Sado 1 (IBR = 2.10) and Sado 2 (IBR = 2.72), compared to the reference scenario (IBR = 0.01), when combining all three species . Clams, for which lipid peroxidation and CAT activity were surveyed, yielded higher IBR scores for Sado 2 , similarly to fish , for which GST was added. Conversely, cuttlefish, for which lipid peroxidation, GST activity, GSHt, and reduced/oxidized glutathione ratio were surveyed, yielded higher IBR for Sado 1 .Clam, fish, and cuttlefish yielded distinct patterns of oxidative biochemical damage (measured through lipid peroxidation) and responses to oxidative stress  and Sado 2  areas , with the reference site evidencing a clear distinction from its immediate surroundings. The distinction between Sado 1 and Sado 2 is more obvious for organic contaminants, of which PAHs  are the most representative . These contaminants were best represented in Sado 1 sediments N1 and N2, in line with the findings retrieved from the conventional Comet assay . Oxidative DNA strand breakage increased most notoriously in HepG2 cells exposed to sediments from Sado 2 . Accordingly, animals from Sado 2 yielded comparatively the highest combined IBR value for oxidative stress-related biomarkers . In agreement with the spatial distribution of data, cluster analyses combining sediment and biological data grouped sites N1 and N2 within the same cluster, both belonging to Sado 1 whereas sites S1 and S2 (Sado 2) constituted a clearly distinct group. Still, the Reference site (R) exhibited a closer relation to Sado 2 than to Sado 1 sites . Oxidative DNA damage caused by exposure to fraction 1 was best correlated to IBR and, together with SQG-Qs for metals and total toxicants, formed a distinct cluster from the one (cluster 2) comprising SQG-Qs for organic toxicants, non-oxidative DNA damage, and oxidative DNA damage resulting from exposure to the extract fractions 4 (methanol).Spatial distribution of data for sediment contamination plus Comet assay and IBR results are presented in Figure 6), for oxidative stress biomarkers analyzed in local species . This indicates a relationship, as potential lines-of-evidence, between two distinct sets of oxidative effects, i.e., biochemical and genetic, determined in wild animals, and HepG2 cells, respectively.The present work showed that estuaries, even if regarded as moderately impacted, may be highly heterogeneous with respect to the distribution of pollutants which, consequently, is translated into a complex pattern of biological effects and responses to toxicants. Oxidative DNA damage was found to be associated to IBR estimates . However, any potential link between oxidative DNA damage in cells and biochemical oxidative stress in wild organisms remains elusive, since organisms hold specific abilities to cope with exposure to toxicants and the oxidative stress hitherto derived.Overall, the results indicate that oxidative effects endured by wild organisms and HepG2 cells are better associated either to total contamination or to metals (the best represented toxicants), than to well-known genotoxicants like PAHs. It must be emphasized that sediment contamination, with particular respect to organic contaminants (among which PAHs are the best represented), was globally higher in sediments N1 and N2 . Nonetheless, the increment of DNA strand breakage in FPG-treated cells relatively to the standard assay was higher in HepG2 cells after exposure to extracts from Sado 2 , indicating a higher level of oxidative DNA damage. This observation is accordant with the present IBR results and also as disclosed by the original research with cells with unfractionated extracts . The same authors then hypothesized that one of the factors involved in such inhibition was the complex interaction of toxicants . Altogether, when comparing the effects on fish and human cells, it may be inferred that oxidative stress occurs indeed as a consequence of exposure to toxicants from Sado 1, whether translated into oxidative DNA lesions or biochemical damage. This information is in agreement with higher levels of contamination by organic compounds, especially PAHs, since metals presented similar values between the two main areas of the estuary (Table 1). On the other hand, molluscs provided consistent, albeit opposite, responses that are related to habitat and behavior. Clams (sedentary burrowers) from Sado 1 were collected from the precise same site than sediment R (the “clean” reference sediment); so, not surprisingly the IBR score was lower in comparison to clams collected from Sado 2 . On its turn, cuttlefish  was consistently responsive to background contamination of Sado 1. Yet, these animals are a novelty within the field of research and little is known about its physiological responses to chemical challenge (see Past research to determine the effects of sediment contamination in the Sado Estuary based on a multi-biomarker approach in soles exposed omarkers . Opposit50 estimates (oxidative and non-oxidative DNA damage) and SQG-Qs for organic and inorganic toxicants indicate that this extraction method was efficient for the bulk of toxicants . However, in the present study, fractions 2 (n-hexane) and 3 (dichloromethane) yielded only marginal results. Considering that metals are indeed the most significant toxicants determined in Sado sediments from contaminated areas, the results are in line with SQG-Qs (Table 1), since exposure to fraction 2 should mean exposure to PAHs and other highly hydrophobic substances. Moreover, it was observed that sediments from Sado 2 (S1 and S2) account primarily for oxidative DNA damage in HepG2 cells, showing that distinct sets of sediment toxicants were retrieved from both Sado areas . Most likely, Sado 2 sediments contain important levels of more hydrophilic toxicants, such as metals and potentially unsurveyed organic substances, either able to cause oxidative DNA damage or some type of alkylating lesions that might have been converted in strand breaks following FPG treatment  to extracts  from marine sediments and observed that extracts obtained with more polar solvents were more genotoxic (as determined through the standard Comet assay) than those obtained with n-hexane. The same authors discussed that reduced metabolic activation could, at least in part, contribute to explain the results. As such, it is possible, though, that enhanced metabolic activation in HepG2 cells could have rendered more significant results for the tests with fractions 2 and 3 (prepared with more hydrophobic solvents) than actually measured (Table 4), even though these cells are generally acknowledged to retain the mechanisms involved in PAH bioactivation (with production of ROS as by-products) by CYP mixed-function oxidases . It must also be noticed that cytotoxicity in HepG2 cells exposed to the different extracts was not clearly related to DNA damage, which is in accordance with other works dealing with in vitro exposures to whole marine sediment extracts , particularly in HepG2 cells exposed to the crude and methanolic extracts. From the results, it may be inferred that sediment extract fractioning combined with the enzyme-modified Comet assay is a potentially valuable toxicity identification evaluation (TIE) strategy to monitor environmental genotoxicants, in the sense that by removing causative agents, cause–effect relationships may be sought through a break-down approach  or their mixtures  is an expanding tool in ERA, with the potential to become a LOE within its own right if proper validation through realistic case studies is achieved. Not dismissing the clear need to endeavor future research, the present work showed that the enzyme-modified Comet assay applied to HepG2 cells in a practical ERA context can yield results that are overall consistent and complementary with oxidative stress biomarkers analyzed in field-collected organisms. As such, the deployment of the in vitro Comet assay in human carcinoma cell lines and its combination with more traditional LOEs may meet its purpose even in scenarios where establishing cause–effect relationships is likely hampered by challenging circumstances such as the presence of complex mixtures of toxicants.In the present work, an integrative assessment of genotoxic effects triggered by sediment-bound contaminants with oxidative stress biomarkers in three different species collected from an impacted estuary was conducted, consisting of an innovative combination of cell and whole-organism responses. The The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Several candidate circulating factors and their effects on podocytes have been proposed but are still not sufficient to explain whole mechanisms and clinical features in MCD. Another circulating factor disease is focal segmental glomerulosclerosis (FSGS), and it is not clear if this is a distinct entity, or on the same spectrum, implicating the same circulating factor(s). These patients are mostly steroid resistant and often have a rapid relapse after transplantation. In clinical practice, predicting relapse or disease activity and response to steroids is important and is an area where novel biomarkers can be developed based on our growing knowledge of podocyte signaling pathways. In this review, we discuss recent findings in genetics and podocyte biology in MCD.Minimal change disease (MCD) is an important cause of nephrotic syndrome and is characterized by massive proteinuria and hypoalbuminemia, resulting in edema and hypercholesterolemia. The podocyte plays a key role in filtration and its disruption results in a dramatic loss of function leading to proteinuria. Immunologic disturbance has been suggested in the pathogenesis of MCD. Because of its clinical features, such as recurrent relapse/remission course, steroid response in most patients, and rare familial cases, a genetic defect has been thought to be less likely in MCD. Recent progress in whole-exome sequencing reveals pathogenic mutations in familial cases in steroid-sensitive nephrotic syndrome (SSNS) and sheds light on possible mechanisms and key molecules in podocytes in MCD. On the other hand, in the majority of cases, the existence of circulating permeability factors has been implicated along with T lymphocyte dysfunction. Observations of benefit with rituximab added B cell involvement to the disease. Animal models are unsatisfactory, and the humanized mouse may be a good model that well reflects MCD pathophysiology to investigate suggested “T cell dysfunction” directly related to podocytes Proteinuria in MCD is typically reversible with corticosteroid therapy2. T cell dysfunction and circulating factors have long been implicated as a cause of the podocyte dysfunction in MCD3, but their nature still remains to be elucidated.Minimal change disease (MCD) is characterized by massive proteinuria without histological evidence of immune-mediated damage in the glomeruli. The glomerular podocyte plays a key role in filtration and its loss of function results in loss of protein, mainly albumin or smaller proteins, into the urine with high selectivity4. These findings give us clues to focus on target molecules on the podocyte to deduce what those circulating factors may be. At the same time, we can utilize those molecules as biomarkers not only as a diagnostic tool but also in predicting the disease activity or prognosis. This allows us to administer more accurate and precise treatment to patients with MCD while minimizing side effects caused by drugs.Recent progress in genetics and cell biology has revealed the molecular mechanisms of dysfunction in podocytes5. In this article, known pathogenesis and mechanisms underlying MCD are reviewed.Alongside MCD as one circulating factor disease is a subset of patients with the histological finding of focal segmental glomerulosclerosis (FSGS). These patients are mostly steroid resistant, and therefore the term steroid-resistant nephrotic syndrome (SRNS) is also used here. These patients often have a rapid relapse after transplantation, indicating another circulating factor disease. It is likely that at least a subset of patients with MCD progress to FSGS/SRNS, with a consistent circulating factor in both. The most compelling evidence for this is the observation that patients with initial steroid sensitivity (assumed to be MCD at that stage) who over subsequent years develop steroid resistance/FSGS, and renal failure, have a 90% chance of post-transplant disease recurrence – the archetypal manifestation of circulating factor disease6 and around 15–20% of cases in adults7, and is characterized by massive proteinuria and hypoalbuminemia, resulting in edema and hypercholesterolemia. Histological findings of the disease in glomeruli are typically normal by light microscopy and only electron microscopy shows effacement of podocyte foot processes without electron-dense immune deposits8. These manifestations are typically reversible with the use of corticosteroid therapy in steroid-sensitive nephrotic syndrome (SSNS), so that progressive loss of renal function is rare.MCD is the most common cause of nephrotic syndrome in children9. A genetic defect cannot explain these phenomena in MCD.The incidence of MCD in childhood is twofold higher in boys, with a prevalence that is inversely proportional to age. Relapse occurs in 50–80% of patients, and recurrent relapse tends to lessen after adolescence10 and 29.5% of familial SRNS cases11 are caused by gene mutation. More than 24 genes are currently known to be pathogenic in SRNS12 and have already been clinically utilized in practice in SRNS cases.Familial cases are rather rare in MCD, therefore the genetic background of SSNS is largely unknown, while 23.6% of SRNS cases13, which contributes to endocytosis and the transcytosis of cholesterol and albumin14. Lipopolysaccharide (LPS)-induced caveolin-1 phosphorylation was reported to lead to the increase of transcellular permeability15.Recently, using whole-exome sequencing, several mutations were found in pedigrees with SSNS, which shed light on new mechanisms of podocyte disruption in MCD. Epithelial membrane protein 2 (EMP2) is known to regulate the amount of caveolin-1KANK gene were identified in familial SSNS and in sporadic SRNS cases16. Kidney ankyrin repeat-containing protein (KANK) family proteins have essential roles in podocyte/nephrocyte function and regulate Rho GTPase activity. KANK2 interacted with Rho GDP dissociation inhibitor alpha (ARHGDIA), a known regulator of Rho GTPases in podocytes found to be dysfunctional in SRNS17. Knockdown of KANK2 in cultured podocytes increased active GTP-bound RHOA and decreased migration.More recently, recessive mutations in theIn these cases, we might have evidence of overlap of SSNS and SRNS. Also, it is important to know the mechanisms of how corticosteroid and immunosuppressants have their effect on nephrotic syndrome caused by single gene mutation.et al. employed unique methods and established a nephrotic syndrome model by injecting CD34+ peripheral stem cells obtained from FSGS and MCD patients18 rather than injecting the supernatant of T cells or peripheral blood mononuclear cells (PBMCs) obtained from the patients19. The injected cells successfully induced the engraftment of human CD45 leukocytes in the thymus, and only the injection of CD34+ stem cells from patients induced albuminuria. Interestingly, stem-cell-injected mice did not have CD3+ mature T cells, suggesting that the cells responsible for the pathogenesis of idiopathic nephrotic syndrome are more likely to be immature differentiating cells rather than mature peripheral T cells. Naïve T cells (Th0s) have been focused on to investigate the difference in DNA methylation in MCD patients20. The change in DNA methylation patterns from remission to relapse occurs predominantly in Th0s. Epigenetic involvement in the pathogenesis of minimal change nephrotic syndrome in T cells has also been suggested in a report showing that nuclear factor related to kappaB binding protein (NFRKB) was highly expressed in the nuclear compartment in T lymphocytes of MCD patients during relapse and that NFRKB promotes hypomethylation of genomic DNA in HEK cells transfected with NFRKB expression plasmid21.T cell dysfunction has long been postulated and many types of cytokines have been investigated. One of the difficulties in examining a hypothesis that immunological disruption underlies MCD in the laboratory is the lack of an animal model that reflects the pathophysiological mechanism. Haddad23 -α are indicated as possible triggers to activate Hpx in MCD38.Hemopexin (Hpx) is a circulating plasma protease that is synthesized in the liver. The active isoform of Hpx is increased in children with MCD39, Hpx may act via the family of protease-activated receptors. There are also matrix metalloproteinases among those proteins that have Hpx homology domains. Recent studies investigated the possibility of a matrix metalloproteinase–protease-activated receptor 1 (PAR1) signaling axis40. It was recently reported that proteases present in nephrotic plasma obtained from patients with FSGS can activate PAR1, leading to the podocin-dependent phosphorylation of the actin-associated protein vasodilator-stimulated phosphoprotein (VASP) in human podocytes and increased cell migration, suggesting a novel role for proteases and PARs in the pathogenesis of FSGS42. Although the exact component(s) of FSGS plasma that causes this response remains unknown, the soluble urokinase plasminogen activator receptor (suPAR) has been identified as a potential circulating factor in FSGS via activation of β3 integrin in podocytes and promotes cell motility45. However, correlation of disease activity with suPAR levels has been inconsistent in subsequent reports47. Urinary suPAR was increased in MCD relapse, but it is thought it may simply be a surrogate for proteinuria48. These factors are found in FSGS but are potentially also relevant to MCD; this needs experimental verification.Because it has serine protease activity49.CD80 (B7-1) is a T cell co-stimulatory molecule involved in antigen processing that is also unexpectedly expressed on podocytes in certain experimental and clinical disease states. Podocyte CD80 activation through Toll-like receptor (TLR) 3 and 4 by LPS, independent of T cells, causes proteinuria and foot process effacement50. Sera from MCD patients in relapse, but not in remission, stimulated CD80 expression in cultured podocytes51. The factor(s) in patients’ serum that stimulates podocytes is unknown. Most recently, it was reported that no significant up-regulation of podocyte CD80 was detected in MCD and FSGS patients' biopsies compared with controls using different primary antibodies and immunohistochemical assays, suggesting further confirmation is needed with CD80 in MCD52.Urinary CD80 levels are increased in MCD during relapse but are not increased in FSGS patients or MCD patients in remission54. The effect on the podocyte was actin cytoskeleton disruption and activation of β3 integrin. In MCD, it has been suggested that TNF-α synthesis in peripheral mononuclear cells from relapse is increased55. Genome-wide DNA methylation analysis was performed in naïve T helper cells both in relapse and in remission of MCD20 and it was found that the promoter region of TNF-α from relapse has a significant reduction in DNA methylation compared to that from remission in the same individuals, indicating predisposition of TNF-α synthesis in relapse in MCD .TNF-α is suggested to be one of the circulating factors that exists in patient plasma of post-transplant recurrent FSGSSummarizing the data, an excess factor or missing/imbalance of factors in relapse plasma could be the primary cause of MCD, and interesting candidates with biological plausibility are Hpx, suPAR, and TNF-α. PAR1 or uPAR and β3 integrin are therefore potentially activated by circulating factors, and VASP-p is in the pathway downstream of PAR1 or integrins. CD80 is a product of podocyte stimulation by circulating factors. Reorganization of actin by Hpx is dependent on nephrin. The structural changes in actin result in foot process effacement and increase of permeability, which is the core feature in the disease.The circulating factors might be secreted by peripheral blood cells such as T or B cells by mesangial or endothelial cells in a paracrine manner or by the podocyte itself in an autocrine manner.Pathogenic gene mutation analysis in familial MCD has started to reveal insights into underlying mechanisms of pathophysiology in the podocyte, such as endocytosis or Rho GTPase, related to permeability.We have less evidence of circulating factor activity or from genetic disease in MCD compared to FSGS, perhaps because of less disease severity and lower availability of patient samples in MCD. In terms of circulating factor diseases, findings in FSGS can be examined in relation to MCD. A humanized mouse model might give us a good tool to investigate T cell dysfunction directly related to podocytes.There are several candidates for biomarkers to predict disease activity or steroid response that allow us to choose precise and acceptable treatment for each individual patient while reducing the side effects of long-term treatment.New components might be inducible targeting of a specific molecule that is involved in the pathogenesis of MCD both for screening and for treatment.MCD, minimal change disease; SSNS, steroid-sensitive nephrotic syndrome; FSGS, focal segmental glomerulosclerosis; SRNS, steroid-resistant nephrotic syndrome; EMP2, epithelial membrane protein 2; LPS, lipopolysaccharide; KANK, kidney ankyrin repeat-containing protein; ARHGDIA, Rho GDP dissociation inhibitor (GDI) alpha; Th0s, naïve T cells; NFRKB, nuclear factor related to kappaB binding protein; Th17, helper T subset 17; Treg, regulatory T cell; PBMC, peripheral mononuclear cell; PAR1, protease activated receptor 1; VASP, vasodilator stimulated phosphoprotein; suPAR, soluble urokinase plasminogen activator receptor; TLR, Toll-like receptor; TNF-α, tumor necrosis factor alpha.


Newborn neurons are continuously added to the hippocampal dentate gyrus throughout adulthood. In this review, we analyze the maturational stages that newborn granule neurons go through, with a focus on their unique morphological features during each stage under both physiological and pathological circumstances. In addition, the influence of deleterious  and neuroprotective  stimuli on the maturation of these cells will be examined. Finally, the regulation of this process by proteins involved in neurodegenerative and neurological disorders such as Glycogen synthase kinase 3β, Disrupted in Schizophrenia 1 (DISC-1), Glucocorticoid receptor, pro-inflammatory mediators, Presenilin-1, Amyloid precursor protein, Cyclin-dependent kinase 5 (CDK5), among others, will be evaluated. Given the recently acquired relevance of the dendritic branch as a functional synaptic unit required for memory storage, a full understanding of the morphological alterations observed in newborn neurons may have important consequences for the prevention and treatment of the cognitive and affective alterations that evolve in conjunction with impaired adult hippocampal neurogenesis. Despite increasing knowledge regarding the developmental steps that control the proliferation, differentiation, and integration of adult-born granule neurons in the hippocampal circuit, the regulatory genes required for morphological maturation and neurite growth of newborn granule cells remain largely unknown. Given that alterations in adult hippocampal neurogenesis (AHN) may be key components in hippocampus-associated neurological diseases, such as major depression  of the hippocampal dentate gyrus (DG) ] and send them toward the CA3  have been reported to be more similar to those of primates than to those of rodents , an experimental manipulation that consists of a combination of physical activity, social interaction, and cognitive stimulation, is neuroprotective under both physiological and pathological circumstances . Several studies have shown that blocking CREB signaling leads to a dramatic decrease in hippocampal neurogenesis and dendritic arborization in newborn neurons  present a marked sprouting toward the IML -expressing neuroblasts undergo changes in the pilocarpine model of epilepsy  protein, a molecule that determines susceptibility to schizophrenia, is crucial during embryogenesis due to its stimulatory actions on the non-canonical Wnt signaling pathway and its inhibition of glycogen synthase kinase 3-β (GSK-3β)  serves many beneficial homeostatic functions  is highly expressed by hippocampal neurons, especially by CA1 and CA2 pyramidal and granule neurons  has been described to exert equivalent suppressive effects on AHN  and the intracellular tangles formed mainly by hyperphosphorylated Tau protein. The molecular pathways responsible for these two types of aberrant structures converge in a common step, namely the dysregulation of GSK-3β activity   and the regulatory proteins P35, P25, and P39  are considered a risk factor for the development of this disease  increases health and lifespan ; and the Alzheimer's Association .This study was funded by grants from the Spanish Ministry of Health (SAF-2014-5040-P), and the The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Since the earliest observations of cells undergoing mitosis, it has been clear that there is an intimate relationship between the cell cycle and nuclear chromatin architecture. The nuclear envelope and chromatin undergo robust assembly and disassembly during the cell cycle, and transcriptional and post-transcriptional regulation of histone biogenesis and chromatin modification is controlled in a cell cycle-dependent manner. Chromatin binding proteins and chromatin modifications in turn influence the expression of critical cell cycle regulators, the accessibility of origins for DNA replication, DNA repair, and cell fate. In this review we aim to provide an integrated discussion of how the cell cycle machinery impacts nuclear architecture and vice-versa. We highlight recent advances in understanding cell cycle-dependent histone biogenesis and histone modification deposition, how cell cycle regulators control histone modifier activities, the contribution of chromatin modifications to origin firing for DNA replication, and newly identified roles for nucleoporins in regulating cell cycle gene expression, gene expression memory and differentiation. We close with a discussion of how cell cycle status may impact chromatin to influence cell fate decisions, under normal contexts of differentiation as well as in instances of cell fate reprogramming. Chromatin serves as a platform for numerous cellular signals to influence gene expression. Post-translational modifications (PTMs) of histone proteins or covalent modifications of nucleotides influence a cell’s transcriptional program, which ultimately impacts cellular behavior and cell fate. Chromatin modifications are converted into transcriptional instructions by the interplay of modification “writers,” “erasers” and “readers” residing, often together, in a multitude of chromatin remodeling complexes that interact directly or indirectly with transcription factor complexes . Like trWork by many groups over the past 10 years, including the extensive chromatin modification and accessibility mapping performed through the Encyclopedia of DNA Elements (ENCODE) and model systems-based ModENCODE projects have clarified that: chromatin accessibility and chromatin modifications are predictive of gene expression, DNA replication timing is correlated with an accessible chromatin structure, and chromatin is dynamic during fate acquisition and cellular reprogramming to pluripotency  are actively synthesized during S-phase, in a manner coordinated with the replication of DNA. The speed of DNA replication is in fact tied to the rate of histone biosynthesis , suggestThe onset and shut down of histone gene transcription is tightly regulated, in a manner elegantly coordinated with the core cell cycle machinery . Entry iDrosophila. The histone gene-specific epigenetic repressor in late S-phase (HERS) protein becomes phosphorylated by the late S-G2 Cyclin complex CyclinA/Cdk1, which localizes it to the histone genes where it acts to silence histone genes after S-phase . SLBP is involved in several aspects of histone mRNA metabolism, including histone pre-mRNA maturation, translation and degradation . PerhapsThe DNA replication machinery is exquisitely regulated to ensure that the genomic DNA is copied only once within the cell cycle, with the interesting exception of highly specialized cells which re-replicate specific genomic regions to amplify certain genes . ReplicaA fundamental question about DNA replication is where on the genome replication starts. Unlike prokaryotes and yeast, metazoans have no obvious DNA sequence to designate origins of replication. Furthermore, there are estimated to be 30,000–50,000 potential origins of replication in the human genome, only about 10% of which are used within a given adult somatic cell cycle, suggesting most potential origins lie dormant . This vaDrosophila, mouse and human cells, and there is a strong correlation between origins and regions of active transcription . H4K20Me levels fluctuate during the cell cycle, peaking during M and early G1 and plummeting during S phase . The higNot only is ORC binding and origin licensing impacted by the chromatin state, but origins are fired in a sequential way, such that some regions of the genome replicate early while others replicate late in S phase . Such diXenopus , as well as an H3K27Me3 binding subunit Extra sexcombs, (or EED in humans). Importantly, EED binding to the H3K27Me3 modification stimulates the methyltransferase activity of EZH2, thereby providing an intuitive way for the PRC2 complex to propagate the H3K27Me3 modification  approach. In this assay, proteins or histone PTMs that are within 30–40 nm of replication forks containing PCNA generate a fluorescent signal, with a sensitivity that allows visualization of single molecule interactions in vivo , TrxG, Pc, Caf-1, LID, UTX, and HP1 are tightly associated with the replication forks, and are located on nascent DNA during S phase. However, their corresponding histone PTMs were not associated with replication forks, nor detectable on nascent DNA until ∼1 hr after the passage of replication fork, which is already G2 phase at this stage of development. This suggests that it is the PTM writers that remain associated with nascent chromatin during replication which must act to re-establish PTMs later. Thus, it seems the chromatin binding of the PTM writers rather than the PTMs themselves may serve as a true, inherited epigenetic mark. Although surprising, this work is consistent with a previous study showing that Polycomb remains bound to replicating chromatin in vitro , the same PTM mentioned earlier to promote pre-RC formation, is also required for proper chromosome condensation . H4K20meWhile chromatin impacts cell cycle events like origin firing and chromosome segregation at mitosis, the cell cycle machinery also impacts chromatin by regulating the histone modifiers. The activity of certain histone modifiers fluctuates in a cell cycle-dependent manner. Perhaps the best-studied example of this is the regulation of the H4K20 mono-methyltransferase PR-Set7 and its opposing de-methylase, PHF8 . Both PRDrosophila, is the major methyltransferase for H3 Lysine 27 and plays a crucial role in differentiation gene silencing through interaction with the Polycomb Repressive Complex 2  in  2 PRC2; . EZH2 is 2 PRC2; , and is  2 PRC2; . Several 2 PRC2; . However 2 PRC2; . Thus, t 2 PRC2; . To fullThese specific examples of the cell cycle machinery impacting chromatin modifiers are likely to be only the tip of the iceberg. The Cyclin/Cdk complexes themselves have hundreds of targets, many of which are uncharacterized or remain to be identified . In addiChromatin is not organized randomly within the nucleus during interphase, and microscopic observations of mammalian nuclei revealed that condensed chromatin is localized preferentially in the nuclear periphery, interrupted by stretches of less condensed chromatin at the nuclear pore complexes (NPCs). This distribution of heterochromatin-euchromatin led to the hypothesis that the more open chromatin near nuclear pores represents actively transcribed regions, and that this interaction facilitates the coupling of transcription with mRNA export, a process termed “gene gating” . ConsistDrosophila salivary glands, Nup98 and Nup50 can be observed bound to decondensed chromatin and sites of active transcription microscopically. Nup98 and another Nup, Sec13, are localized to transcribed genes prior to the initiation of transcription, and an RNAi knockdown of Sec13 or Nup98 reduces transcription and RNA polymerase II recruitment, demonstrating functional roles for this binding  complex, required for silencing of subtelomeres . The mamThe localization of chromatin to the nuclear periphery, away from pores is suggested to be transcriptionally repressive in yeast and mammals . Using tHeterochromatin tethering along the nuclear periphery is mediated by lamins, nuclear cytoskeleton filaments, that connect chromatin to the inner nuclear membrane of the nuclear envelope . Lamin-aA detailed analysis of LAD positioning during the cell cycle was performed using a modified Dam-ID approach, to permanently mark chromatin regions that associate with nuclear lamina, and track their position even after detachment and through the cell cycle . The stuThis profound and surprising result raises the question of how such stochastic changes in chromatin dynamics during each cell cycle, and presumably gene expression, can possibly be reconciled with seemingly organized and predictable changes in cell fate during development. One possibility is that LADs may be primarily used to modulate gene expression in postmitotic cells, although studies performed in proliferating fibroblasts suggest this may not be the case . ImportaIn metazoan cells where an “open mitosis” takes place, the nuclear envelope breaks down at the onset of mitosis. This involves the disassembly of NPCs, lamin depolymerization, and incorporation of nuclear envelope membranes into the endoplasmic reticulum ER  also known as ELYS, a scaffold nucleoporin which has a DNA binding domain for recruiting factors to chromatin . SubsequApart from the assembly of NPCs, their distribution in the nuclear membrane during cell cycle progression changes as well. During G1, right after completion of mitosis, NPCs are distributed unequally through nuclear surface, generating “pore-free islands” . These “How is chromatin tethered to the nuclear pores or nuclear lamina properly replicated during S-phase? The anchoring of chromatin to NPCs turns out to have both positive and negative impacts on genome integrity during replication. For example, replication forks with persistent double strand breaks (DSBs) relocate to NPCs for repair . The assWhile recruitment to pores can promote DNA repair, paradoxically, the anchoring of actively transcribed genes to NPCs can also be a source of replication stress. It is thought that as the DNA replication fork proceeds, it will eventually meet the NPC- tethered region actively transcribing genes. The inflexibility of tethered DNA can become a source of tension as the unwinding of DNA occurs during replication fork progression , and theThe act of DNA replication during S-phase can also be a source of DNA damage  which ifIn vivo, the propensity for embryonic neural stem cells to self-renew vs. produce differentiated daughters also varies with changes in the cell cycle  tumor suppressor, a critical regulator of the restriction point and cell cycle entry . Human EA view of the molecular signaling mechanisms that coordinate cell fate decisions with the core cell cycle machinery in ES cells is just beginning to emerge. Work with human ES cells has now revealed a pathway connecting CyclinD/Cdk4 activity to the TGF-β/Smad signaling pathway. TGF-β signaling promotes endoderm fate in human ES cells, but only during a permissive window in early G1. The capacity for endoderm differentiation drops-off upon cell cycle entry, in a manner correlated with increasing G1 CyclinD/Cdk4 activity. Pauklin and Vallier reconciled these observations by showing that CyclinD/Cdk4 regulates the chromatin association of the TGF-β responsive transcription factors Smad 2 and 3. Smad2/3 associate with chromatin in early G1 allowing for expression of TGF-β target genes, but CyclinD/Cdk4–dependent phosphorylation of residues in the Smad2/3 linker regions prevents them from binding chromatin upon cell cycle entry . This siThe ability to monitor differentiation and cell cycle dynamics in real-time, at the single-cell level, has been made possible by the use of the Fluorescent Ubiquitylation-based Cell-Cycle Indicator (FUCCI) system . This syIn contrast to the better-known repressive cytosine methylation 5mC, 5hmC is instead associated with active promoters, increased gene expression and genes poised for rapid expression . The celWhile differentiation and lineage restriction of pluripotent cells seems to be increased during the G1-phase of the cell cycle, multiple lines of evidence suggest the acquisition of pluripotency or potential for nuclear reprogramming is increased during mitosis . An incrXenopus, the use of nuclei that have recently undergone mitosis was shown to increase origin accessibility in the oocyte, which poises the donor nuclei for the rapid S-phase entry and progression required during early Xenopus development (Xenopus egg extracts, specifically at the metaphase stage, to increase the efficiency of reprogramming mouse fibroblast nuclei to pluripotency. Permeabilized mouse embryonic fibroblasts exposed to mitotic egg extract, but not interphase extract, exhibit decreased histone modifications such as H3K9, H3K4, and H4K20 di- and trimethylation and increased expression of pluripotency-associated genes. When somatic cell nuclear transfer was subsequently performed with the mouse fibroblast nuclei exposed to the mitotic extract, a fourfold increase in reprogramming efficiency was observed (In studies using somatic nuclear transfer in elopment . Later wobserved . This abXenopus oocytes, and the activation of mammalian pluripotency genes is used as a readout of reprogramming. They find, consistent with the reprogramming studies of others (How exactly does the mitotic status of a donor nucleus facilitate cell fate reprogramming? f others , that trf others . This mif others  seems nef others . Future The work of Extensive connections between the cell cycle machinery and chromatin clearly exist, which impact gene expression and thus, cell fate decisions in important ways. While the use of asynchronous cell culture or mixed lineage tissues has sometimes hampered our ability to see these connections, new tools such as Chromatin Conformation Capture, the FUCCI system, the PLA and modified versions of DamID, are being used in ways that allow detailed views of the cell cycle, chromatin state and cell fate acquisition that were previously impossible. But several key questions remain unresolved. For example, does the gene expression profile of a cell, and thus cell fate, control important facets of the cell cycle such as origin choice and DNA replication timing? Or does the cell cycle status of a cell instead determine its gene expression possibilities and therefore limit choices in cell fate? If the latter is true, how can cell fate be so robustly maintained in some instances of regeneration or in cases of cell cycle disruption during development? As we learn more about the truly plastic nature of cell fate, we expect to find that the cell cycle influences the probability of acquiring certain cell fate programs, but that multiple cell cycle and cell fate states can be compatible under specific conditions. Future work will continue to uncover new molecular connections between the cell cycle machinery and developmental signaling pathways, to help us finally understand how the cell cycle impacts cell fate.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.