Although many single nucleotide polymorphisms (SNPs) have been identified to be associated with metabolic syndrome (MetS), there was only a slight improvement in the ability to predict future MetS by the simply addition of SNPs to clinical risk markers. To improve the ability to predict future MetS, combinational effects, such as SNP—SNP interaction, SNP—environment interaction, and SNP—clinical parameter (SNP × CP) interaction should be also considered. We performed a case-control study to explore novel SNP × CP interactions as risk markers for MetS based on health check-up data of Japanese male employees. We selected 99 SNPs that were previously reported to be associated with MetS and components of MetS; subsequently, we genotyped these SNPs from 360 cases and 1983 control subjects. First, we performed logistic regression analyses to assess the association of each SNP with MetS. Of these SNPs, five SNPs were significantly associated with MetS (P < 0.05): LRP2 rs2544390, rs1800592 between UCP1 and TBC1D9, APOA5 rs662799, VWF rs7965413, and rs1411766 between MYO16 and IRS2. Furthermore, we performed multiple logistic regression analyses, including an SNP term, a CP term, and an SNP × CP interaction term for each CP and SNP that was significantly associated with MetS. We identified a novel SNP × CP interaction between rs7965413 and platelet count that was significantly associated with MetS [SNP term: odds ratio (OR) = 0.78, P = 0.004; SNP × CP interaction term: OR = 1.33, P = 0.001]. This association of the SNP × CP interaction with MetS remained nominally significant in multiple logistic regression analysis after adjustment for either the number of MetS components or MetS components excluding obesity. Our results reveal new insight into platelet count as a risk marker for MetS.
Human bone marrow mesenchymal stem cells (hBMSCs) represents one of the most frequently applied cell sources for clinical bone regeneration. To achieve the greatest therapeutic effect, it is crucial to evaluate the osteogenic differentiation potential of the stem cells during their culture before the implantation. However, the practical evaluation of stem cell osteogenicity has been limited to invasive biological marker analysis that only enables assaying a single end-point. To innovate around invasive quality assessments in clinical cell therapy, we previously explored and demonstrated the positive predictive value of using time-course images taken during differentiation culture for hBMSC bone differentiation potential. This initial method establishes proof of concept for a morphology-based cell evaluation approach, but reveals a practical limitation when considering the need to handle large amounts of image data. In this report, we aimed to scale-down our proposed method into a more practical, efficient modeling scheme that can be more broadly implemented by physicians on the frontiers of clinical cell therapy. We investigated which morphological features are critical during the osteogenic differentiation period to assure the performance of prediction models with reduced burden on image acquisition. To our knowledge, this is the first detailed characterization that describes both the critical observation period and the critical number of time-points needed for morphological features to adequately model osteogenic potential. Our results revealed three important observations: (i) the morphological features from the first 3 days of differentiation are sufficiently informative to predict bone differentiation potential, both activities of alkaline phosphatase and calcium deposition, after 3 weeks of continuous culture; (ii) intervals of 48 h are sufficient for measuring critical morphological features; and (iii) morphological features are most accurately predictive when early morphological features from the first 3 days of differentiation are combined with later features (after 10 days of differentiation). Biotechnol. Bioeng. 2014;111: 1430–1439.
image-based analysis; mesenchymal stem cell; non-invasive analysis; osteogenic differentiation; prediction
In vitro three dimensional (3D) cancer models were developed to observe the invasive capacity of melanoma cell spheroids co-cultured with the vascular-formed endothelial cell network. An array-like multicellular pattern of mouse melanoma cell line B16F1 was developed by magnetic cell labeling using a pin-holder device for allocation of magnetic force. When the B16F1 patterned together with a vascular network of human umbilical vein epithelial cells (HUVEC), spreading and progression were observed along the HUVEC network. The B16F1 cells over 80 µm distance from HUVEC remain in a compact spheroid shape, while B16F1 in the proximity of HUVEC aggressively changed their morphology and migrated. The mRNA expression levels of IL-6, MDR-1 and MMP-9 in B16F1 increased along with the distance the HUVEC network, and these expressions were increased by 5, 3 and 2-fold in the B16F1 close to HUVEC (within 80 µm distance) as compared to that far from HUVEC (over 80 µm distance). Our results clearly show that malignancy of tumor cells is enhanced in proximity to vascular endothelial cells and leads to intravasation.
Precise quantification of cellular potential of stem cells, such as human bone marrow–derived mesenchymal stem cells (hBMSCs), is important for achieving stable and effective outcomes in clinical stem cell therapy. Here, we report a method for image-based prediction of the multiple differentiation potentials of hBMSCs. This method has four major advantages: (1) the cells used for potential prediction are fully intact, and therefore directly usable for clinical applications; (2) predictions of potentials are generated before differentiation cultures are initiated; (3) prediction of multiple potentials can be provided simultaneously for each sample; and (4) predictions of potentials yield quantitative values that correlate strongly with the experimental data. Our results show that the collapse of hBMSC differentiation potentials, triggered by in vitro expansion, can be quantitatively predicted far in advance by predicting multiple potentials, multi-lineage differentiation potentials (osteogenic, adipogenic, and chondrogenic) and population doubling potential using morphological features apparent during the first 4 days of expansion culture. In order to understand how such morphological features can be effective for advance predictions, we measured gene-expression profiles of the same early undifferentiated cells. Both senescence-related genes (p16 and p21) and cytoskeleton-related genes (PTK2, CD146, and CD49) already correlated to the decrease of potentials at this stage. To objectively compare the performance of morphology and gene expression for such early prediction, we tested a range of models using various combinations of features. Such comparison of predictive performances revealed that morphological features performed better overall than gene-expression profiles, balancing the predictive accuracy with the effort required for model construction. This benchmark list of various prediction models not only identifies the best morphological feature conversion method for objective potential prediction, but should also allow clinicians to choose the most practical morphology-based prediction method for their own purposes.
Circulating tumor cells (CTCs) in the blood of patients with epithelial malignancies provide a promising and minimally invasive source for early detection of metastasis, monitoring of therapeutic effects and basic research addressing the mechanism of metastasis. In this study, we developed a new filtration-based, sensitive CTC isolation device. This device consists of a 3-dimensional (3D) palladium (Pd) filter with an 8 µm-sized pore in the lower layer and a 30 µm-sized pocket in the upper layer to trap CTCs on a filter micro-fabricated by precise lithography plus electroforming process. This is a simple pump-less device driven by gravity flow and can enrich CTCs from whole blood within 20 min. After on-device staining of CTCs for 30 min, the filter cassette was removed from the device, fixed in a cassette holder and set up on the upright fluorescence microscope. Enumeration and isolation of CTCs for subsequent genetic analysis from the beginning were completed within 1.5 hr and 2 hr, respectively. Cell spike experiments demonstrated that the recovery rate of tumor cells from blood by this Pd filter device was more than 85%. Single living tumor cells were efficiently isolated from these spiked tumor cells by a micromanipulator, and KRAS mutation, HER2 gene amplification and overexpression, for example, were successfully detected from such isolated single tumor cells. Sequential analysis of blood from mice bearing metastasis revealed that CTC increased with progression of metastasis. Furthermore, a significant increase in the number of CTCs from the blood of patients with metastatic breast cancer was observed compared with patients without metastasis and healthy volunteers. These results suggest that this new 3D Pd filter-based device would be a useful tool for the rapid, cost effective and sensitive detection, enumeration, isolation and genetic analysis of CTCs from peripheral blood in both preclinical and clinical settings.
The diagnosis and treatment of soft tissue sarcomas (STSs) has been particularly difficult, because STSs are a group of highly heterogeneous tumors in terms of histopathology, histological grade, and primary site. Recent advances in genome technologies have provided an excellent opportunity to determine the complete biological characteristics of neoplastic tissues, resulting in improved diagnosis, treatment selection, and investigation of therapeutic targets. We had previously developed a novel bioinformatics method for marker gene selection and applied this method to gene expression data from STS patients. This previous analysis revealed that the extracted gene combination of macrophage migration inhibitory factor (MIF) and stearoyl-CoA desaturase 1 (SCD1) is an effective diagnostic marker to discriminate between subtypes of STSs with highly different outcomes. In the present study, we hypothesize that the combination of MIF and SCD1 is also a prognostic marker for the overall outcome of STSs. To prove this hypothesis, we first analyzed microarray data from 88 STS patients and their outcomes. Our results show that the survival rates for MIF- and SCD1-positive groups were lower than those for negative groups, and the p values of the log-rank test are 0.0146 and 0.00606, respectively. In addition, survival rates are more significantly different (p = 0.000116) between groups that are double-positive and double-negative for MIF and SCD1. Furthermore, in vitro cell growth inhibition experiments by MIF and SCD1 inhibitors support the hypothesis. These results suggest that the gene set is useful as a prognostic marker associated with tumor progression.
Diabetes mellitus (DM) is considered to be a risk factor for dementia including Alzheimer's disease (AD). However, the molecular mechanism underlying this risk is not well understood. We examined gene expression profiles in postmortem human brains donated for the Hisayama study. Three-way analysis of variance of microarray data from frontal cortex, temporal cortex, and hippocampus was performed with the presence/absence of AD and vascular dementia, and sex, as factors. Comparative analyses of expression changes in the brains of AD patients and a mouse model of AD were also performed. Relevant changes in gene expression identified by microarray analysis were validated by quantitative real-time reverse-transcription polymerase chain reaction and western blotting. The hippocampi of AD brains showed the most significant alteration in gene expression profile. Genes involved in noninsulin-dependent DM and obesity were significantly altered in both AD brains and the AD mouse model, as were genes related to psychiatric disorders and AD. The alterations in the expression profiles of DM-related genes in AD brains were independent of peripheral DM-related abnormalities. These results indicate that altered expression of genes related to DM in AD brains is a result of AD pathology, which may thereby be exacerbated by peripheral insulin resistance or DM.
animal model; hippocampus; insulin; microarray; postmortem brains
Angiogenic cell therapy represents a novel strategy for ischemic diseases, but some patients show poor responses. We investigated the therapeutic potential of an induced pluripotent stem (iPS) cell sheet created by a novel magnetite tissue engineering technology (Mag-TE) for reparative angiogenesis. Mouse iPS cell-derived Flk-1+ cells were incubated with magnetic nanoparticle-containing liposomes (MCLs). MCL-labeled Flk-1+ cells were mixed with diluted extracellular matrix (ECM) precursor and a magnet was placed on the reverse side. Magnetized Flk-1+ cells formed multi-layered cell sheets according to magnetic force. Implantation of the Flk-1+ cell sheet accelerated revascularization of ischemic hindlimbs relative to the contralateral limbs in nude mice as measured by laser Doppler blood flow and capillary density analyses. The Flk-1+ cell sheet also increased the expressions of VEGF and bFGF in ischemic tissue. iPS cell-derived Flk-1+ cell sheets created by this novel Mag-TE method represent a promising new modality for therapeutic angiogenesis.
Human bone marrow mesenchymal stem cells (hBMSCs) are widely used cell source for clinical bone regeneration. Achieving the greatest therapeutic effect is dependent on the osteogenic differentiation potential of the stem cells to be implanted. However, there are still no practical methods to characterize such potential non-invasively or previously. Monitoring cellular morphology is a practical and non-invasive approach for evaluating osteogenic potential. Unfortunately, such image-based approaches had been historically qualitative and requiring experienced interpretation. By combining the non-invasive attributes of microscopy with the latest technology allowing higher throughput and quantitative imaging metrics, we studied the applicability of morphometric features to quantitatively predict cellular osteogenic potential. We applied computational machine learning, combining cell morphology features with their corresponding biochemical osteogenic assay results, to develop prediction model of osteogenic differentiation. Using a dataset of 9,990 images automatically acquired by BioStation CT during osteogenic differentiation culture of hBMSCs, 666 morphometric features were extracted as parameters. Two commonly used osteogenic markers, alkaline phosphatase (ALP) activity and calcium deposition were measured experimentally, and used as the true biological differentiation status to validate the prediction accuracy. Using time-course morphological features throughout differentiation culture, the prediction results highly correlated with the experimentally defined differentiation marker values (R>0.89 for both marker predictions). The clinical applicability of our morphology-based prediction was further examined with two scenarios: one using only historical cell images and the other using both historical images together with the patient's own cell images to predict a new patient's cellular potential. The prediction accuracy was found to be greatly enhanced by incorporation of patients' own cell features in the modeling, indicating the practical strategy for clinical usage. Consequently, our results provide strong evidence for the feasibility of using a quantitative time series of phase-contrast cellular morphology for non-invasive cell quality prediction in regenerative medicine.
Exploitation of biological properties unique to cancer cells may provide a novel approach to overcome difficult challenges to the treatment of advanced melanoma. In order to develop melanoma-targeted chemothermoimmunotherapy, a melanogenesis substrate, N-propionyl-4-S-cysteaminylphenol (NPrCAP), sulfur-amine analogue of tyrosine, was conjugated with magnetite nanoparticles. NPrCAP was exploited from melanogenesis substrates, which are expected to be selectively incorporated into melanoma cells and produce highly reactive free radicals through reacting with tyrosinase, resulting in chemotherapeutic and immunotherapeutic effects by oxidative stress and apoptotic cell death. Magnetite nanoparticles were conjugated with NPrCAP to introduce thermotherapeutic and immunotherapeutic effects through nonapoptotic cell death and generation of heat shock protein (HSP) upon exposure to alternating magnetic field (AMF). During these therapeutic processes, NPrCAP was also expected to provide melanoma-targeted drug delivery system.
Lifestyle-related diseases represented by metabolic syndrome develop as results of complex interaction. By using health check-up data from two large studies collected during a long-term follow-up, we searched for risk factors associated with the development of metabolic syndrome.
In our original study, we selected 77 case subjects who developed metabolic syndrome during the follow-up and 152 healthy control subjects who were free of lifestyle-related risk components from among 1803 Japanese male employees. In a replication study, we selected 2196 case subjects and 2196 healthy control subjects from among 31343 other Japanese male employees. By means of a bioinformatics approach using a fuzzy neural network (FNN), we searched any significant combinations that are associated with MetS. To ensure that the risk combination selected by FNN analysis was statistically reliable, we performed logistic regression analysis including adjustment.
We selected a combination of an elevated level of γ-glutamyltranspeptidase (γ-GTP) and an elevated white blood cell (WBC) count as the most significant combination of risk factors for the development of metabolic syndrome. The FNN also identified the same tendency in a replication study. The clinical characteristics of γ-GTP level and WBC count were statistically significant even after adjustment, confirming that the results obtained from the fuzzy neural network are reasonable. Correlation ratio showed that an elevated level of γ-GTP is associated with habitual drinking of alcohol and a high WBC count is associated with habitual smoking.
This result obtained by fuzzy neural network analysis of health check-up data from large long-term studies can be useful in providing a personalized novel diagnostic and therapeutic method involving the γ-GTP level and the WBC count.
Data mining; Combinational risk factor; Fuzzy neural network; Glutamyltranspeptidase; Lifestyle disease; Personalized diagnostic method; White blood cell
Melanogenesis substrate, N-propionyl-cysteaminylphenol (NPrCAP), is selectively incorporated into melanoma cells and inhibits their growth by producing cytotoxic free radicals. Magnetite nanoparticles also disintegrate cancer cells and generate heat shock protein (HSP) upon exposure to an alternating magnetic field (AMF). This study tested if a chemo-thermo-immunotherapy (CTI therapy) strategy can be developed for better management of melanoma by conjugating NPrCAP on the surface of magnetite nanoparticles (NPrCAP/M). We examined the feasibility of this approach in B16 mouse melanoma and evaluated the impact of exposure temperature, frequency, and interval on the inhibition of re-challenged melanoma growth. The therapeutic protocol against the primary transplanted tumor with or without AMF exposure once a day every other day for a total of three treatments not only inhibited the growth of the primary transplant but also prevented the growth of the secondary, re-challenge transplant. The heat-generated therapeutic effect was more significant at a temperature of 43°C than either 41°C or 46°C. NPrCAP/M with AMF exposure, instead of control magnetite alone or without AMF exposure, resulted in the most significant growth inhibition of the re-challenge tumor and increased the life span of the mice. HSP70 production was greatest at 43°C compared to that with 41°C or 46°C. CD8+T cells were infiltrated at the site of the re-challenge melanoma transplant.
We have developed magnetic cationic liposomes (MCLs) that contained magnetic nanoparticles as heating mediator for applying them to local hyperthermia. The heating performance of the MCLs is significantly affected by the property of the incorporated magnetite nanoparticles. We estimated heating capacity of magnetite nanoparticles by measuring its specific absorption rate (SAR) against irradiation of the alternating magnetic field (AMF).
Magnetite nanoparticles which have various specific-surface-area (SSA) are dispersed in the sample tubes, subjected to various AMF and studied SAR.
Heat generation of magnetite particles under variable AMF conditions was summarized by the SSA. There were two maximum SAR values locally between 12 m2/g to 190 m2/g of the SSA in all ranges of applied AMF frequency and those values increased followed by the intensity of AMF power. One of the maximum values was observed at approximately 90 m2/g of the SSA particles and the other was observed at approximately 120 m2/g of the SSA particles. A boundary value of the SAR for heat generation was observed around 110 m2/g of SSA particles and the effects of the AMF power were different on both hand. Smaller SSA particles showed strong correlation of the SAR value to the intensity of the AMF power though larger SSA particles showed weaker correlation.
Those results suggest that two maximum SAR value stand for the heating mechanism of magnetite nanoparticles represented by hysteresis loss and relaxation loss.
We have developed magnetite cationic liposomes (MCLs) and applied them as a mediator of local hyperthermia. MCLs can generate heat under an alternating magnetic field (AMF). In this study, the in vivo effect of hyperthermia mediated by MCLs was examined using 7,12-dimethylbenz(a)anthracene (DMBA)-induced rat mammary cancer as a spontaneous cancer model.
MCLs were injected into the mammary cancer and then subjected to an AMF.
Four rats in 20 developed mammary tumors at more than 1 site in the body. The first-developed tumor in each of these 4 rats was selected and heated to over 43°C following administration of MCLs by an infusion pump. After a series of 3 hyperthermia treatments, treated tumors in 3 of the 4 rats were well controlled over a 30-day observation period. One of the 4 rats exhibited regrowth after 2 weeks. In this rat, there were 3 sites of tumor regrowth. Two of these regrowths were reduced in volume and regressed completely after 31 days, although the remaining one grew rapidly. These results indicated hyperthermia-induced immunological antitumor activity mediated by the MCLs.
Our results suggest that hyperthermic treatment using MCLs is effective in a spontaneous cancer model.
Recent advances in genome technologies have provided an excellent opportunity to determine the complete biological characteristics of neoplastic tissues, resulting in improved diagnosis and selection of treatment. To accomplish this objective, it is important to establish a sophisticated algorithm that can deal with large quantities of data such as gene expression profiles obtained by DNA microarray analysis.
Previously, we developed the projective adaptive resonance theory (PART) filtering method as a gene filtering method. This is one of the clustering methods that can select specific genes for each subtype. In this study, we applied the PART filtering method to analyze microarray data that were obtained from soft tissue sarcoma (STS) patients for the extraction of subtype-specific genes. The performance of the filtering method was evaluated by comparison with other widely used methods, such as signal-to-noise, significance analysis of microarrays, and nearest shrunken centroids. In addition, various combinations of filtering and modeling methods were used to extract essential subtype-specific genes. The combination of the PART filtering method and boosting – the PART-BFCS method – showed the highest accuracy. Seven genes among the 15 genes that are frequently selected by this method – MIF, CYFIP2, HSPCB, TIMP3, LDHA, ABR, and RGS3 – are known prognostic marker genes for other tumors. These genes are candidate marker genes for the diagnosis of STS. Correlation analysis was performed to extract marker genes that were not selected by PART-BFCS. Sixteen genes among those extracted are also known prognostic marker genes for other tumors, and they could be candidate marker genes for the diagnosis of STS.
The procedure that consisted of two steps, such as the PART-BFCS and the correlation analysis, was proposed. The results suggest that novel diagnostic and therapeutic targets for STS can be extracted by a procedure that includes the PART filtering method.
DNA microarray analysis showed that yfiD, yggB, and yggE genes were up-regulated when superoxide dismutase (SOD)-deficient Escherichia coli IM303 (I4) was cultivated under the oxidative stress generated by photoexcited TiO2, and pYFD, pYGB, and pYGE were constructed by inserting the respective genes into a pUC 19 vector. The content of reactive oxygen species (ROS) in IM303 (I4) cells carrying pYGE was reduced to 31% of ROS content in the control cells with pUC 19. In the culture of wild-type strain, E. coli MM294, in the medium with paraquat (10 μmol/l), maximum specific growth rate of the cells with pYGE was about five times higher than that of the control cells, with a decreased ROS content in the former cells. The introduction of pYGE also suppressed the occurrence of the cells with altered amino acid requirement in the culture of MM294 cells with paraquat.
Gene expression profiles were collected from Escherichia coli strains (OST3410, TK33, and TK31) before and after exposure to organic solvents, and the six genes that showed higher gene expression were selected. Among these genes, glpC encoding the anaerobic glycerol-3-phosphate dehydrogenase subunit C remarkably increased the organic solvent tolerance.
Screening of various gene markers such as single nucleotide polymorphism (SNP) and correlation between these markers and development of multifactorial disease have previously been studied. Here, we propose a susceptible marker-selectable artificial neural network (ANN) for predicting development of allergic disease.
To predict development of childhood allergic asthma (CAA) and select susceptible SNPs, we used an ANN with a parameter decreasing method (PDM) to analyze 25 SNPs of 17 genes in 344 Japanese people, and select 10 susceptible SNPs of CAA. The accuracy of the ANN model with 10 SNPs was 97.7% for learning data and 74.4% for evaluation data. Important combinations were determined by effective combination value (ECV) defined in the present paper. Effective 2-SNP or 3-SNP combinations were found to be concentrated among the 10 selected SNPs.
ANN can reliably select SNP combinations that are associated with CAA. Thus, the ANN can be used to characterize development of complex diseases caused by multiple factors. This is the first report of automatic selection of SNPs related to development of multifactorial disease from SNP data of more than 300 patients.
We have developed magnetite cationic liposomes (MCLs) and applied them to local hyperthermia as a mediator. MCLs have a positive charge and generate heat under an alternating magnetic field (AMF) by hysteresis loss. In this study, the effect of hyperthermia using MCLs was examined in an in vivo study of hamster osteosarcoma.
MCLs were injected into the osteosarcoma and then subjected to an AMF.
The tumor was heated at over 42°C, but other normal tissues were not heated as much. Complete regression was observed in 100% of the treated group hamsters, whereas no regression was observed in the control group hamsters. At day 12, the average tumor volume of the treated hamsters was about 1/1000 of that of the control hamsters. In the treated hamsters, no regrowth of osteosarcomas was observed over a period of 3 months after the complete regression.
These results suggest that this treatment is effective for osteosarcoma.
The use of the gadd153promoter to induce expression of a reporter geneunder heat stress conditions was investigated,since the results of previous studies have suggestedthat the gadd153promoter is likely to be activated by the indirecteffects of hyperthermia, that is, by DNA damage thatoccurs when reactive oxygen species are produced byheat stress. The optimum temperature for a significantinduction was found to be between 41 and 43 °C andincreased expression of the reporter gene was observedat about 24 h after the heat treatment. Under theseconditions, the cell integrity was not alteredmorphologically and the growth stopped temporarily,while the viability was maintained. A second increasein expression occurred at a later stage when the cellswere severely damaged at 43–45 °C. Atthese temperatures, the cellular morphology showedsignificant alteration and the growth was stronglyarrested. This is likely to be due to a differentmechanism which could involve DNA repair processes. Itis expected that this method of induction can beexploited to drive the production of a protein ofinterest in a cancer treatment program that includes hyperthermia.
We investigated the enhancement of cytokine expression by heat treatment in transiently transfected glioma cells. The cells were transfected with plasmid bearing the interferon (IFN)-β gene under control of the MMTV promoter, which is inducible by glucocorticoid (dexamethasone). Then magnetite particles (10 nm diameter) as intracellular heating material were incorporated to the cells as the form of magnetoliposome. After 5 hours of incorporation, alternative magnetic field (384Oe, 118kHz) was applied for intracellular heating. IFN-β secreted in the medium was assayed and its concentration was compared to the extracellular heating induced expression, both in the presence and absence of dexamethasone. Higher IFN-β concentration was detected in intracellular heating even at lower temperature, 39 °C, than 43 °C in extracellular heating. The IFN-β expression level reached in the presence of dexamethasone was about three times higher than in the absence of inducer. In intracellular heating of 60 min, the surviving cell number reduced until 20%.
heat shock inducible promoter; hyperthermia; interferon-β; magnetoliposome