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Pluripotent stem cells (PSCs) possess unique characteristics that distinguish them from other cell types. Human embryonic stem (ES) cells are recently gaining attention as a powerful tool for human toxicity assessment without the use of experimental animals, and an embryonic stem cell test (EST) was introduced for this purpose. However, human PSCs have not been thoroughly investigated in terms of drug resistance or compared with other cell types or cell states, such as naïve state, to date. Aiming to close this gap in research knowledge, we assessed and compared several human PSC lines for their resistance to drug exposure. Firstly, we report that RIKEN-2A human induced pluripotent stem (iPS) cells possessed approximately the same sensitivity to selected drugs as KhES-3 human ES cells. Secondly, both ES and iPS cells were several times less resistant to drug exposure than other non-pluripotent cell types. Finally, we showed that iPS cells subjected to naïve-state induction procedures exhibited a sharp increase in drug sensitivity. Upon passage of these naïve-like cells in non-naïve PSC culture medium, their sensitivity to drug exposure decreased. We thus revealed differences in sensitivity to drug exposure among different types or states of PSCs and, importantly, indicated that naïve-state induction could increase this sensitivity.

The loss of nucleus pulposus (NP) precedes the intervertebral disk (IVD) degeneration that causes back pain. Here, we demonstrate that the implantation of human iPS cell-derived cartilaginous tissue (hiPS-Cart) restores this loss by replacing lost NP spatially and functionally. NP cells consist of notochordal NP cells and chondrocyte-like NP cells. Single cell RNA sequencing (scRNA-seq) analysis revealed that cells in hiPS-Cart corresponded to chondrocyte-like NP cells but not to notochordal NP cells. The implantation of hiPS-Cart into a nuclectomized space of IVD in nude rats prevented the degeneration of the IVD and preserved its mechanical properties. hiPS-Cart survived and occupied the nuclectomized space for at least six months after implantation, indicating spatial and functional replacement of lost NP by hiPS-Cart. Further scRNA-seq analysis revealed that hiPS-Cart cells changed their profile after implantation, differentiating into two lineages that are metabolically distinct from each other. However, post-implanted hiPS-Cart cells corresponded to chondrocyte-like NP cells only and did not develop into notochordal NP cells, suggesting that chondrocyte-like NP cells are nearly sufficient for NP function. The data collectively indicate that hiPS-Cart is a candidate implant for regenerating NP spatially and functionally and preventing IVD degeneration., iPS細胞から作った軟骨様髄核により椎間板を再生 --椎間板変性に伴う腰痛疾患を治療しうる新技術--. 京都大学プレスリリース. 2022-04-18.

An alternative model that reliably predicts human-specific toxicity is necessary because the translatability of effects on animal models for human disease is limited to context. Previously, we developed a method that accurately predicts developmental toxicity based on the gene networks of undifferentiated human embryonic stem (ES) cells. Here, we advanced this method to predict adult toxicities of 24 chemicals in six categories (neurotoxins, cardiotoxins, hepatotoxins, two types of nephrotoxins, and non-genotoxic carcinogens) and achieved high predictability (AUC = 0.90–1.00) in all categories. Moreover, we screened for an induced pluripotent stem (iPS) cell line to predict the toxicities based on the gene networks of iPS cells using transfer learning of the gene networks of ES cells, and predicted toxicities in four categories (neurotoxins, hepatotoxins, glomerular nephrotoxins, and non-genotoxic carcinogens) with high performance (AUC = 0.82–0.99). This method holds promise for tailor-made safety evaluations using personalized iPS cells., iPS細胞で人体への毒性物質をオールマイティに検出するStemPanTox. 京都大学プレスリリース. 2022-06-07.

SUMMARYThe assessment of toxic chemicals using animals has limited applicability to humans. Moreover, from the perspective of animal protection, effective alternatives are also desired. Previously, we developed a method that combines developmental toxicity testing based on undifferentiated human embryonic stem (ES) cells (KhES-3) and gene networks. We showed that ≥ 95% accurate predictions could be achieved for neurotoxins, genotoxic carcinogens, and non-genotoxic carcinogens. Here, we expanded this method to predict broad toxicities and predicted the toxicity of 24 chemicals in six categories (neurotoxins, cardiotoxins, hepatotoxins, nephrotoxins [glomerular nephrotoxins/tubular nephrotoxins], and non-genotoxic carcinogens) and achieved high prediction accuracy (AUC = 0.90–1.00) in all categories. Moreover, to develop a testing system with fewer ethical issues, we screened for an induced pluripotent stem (iPS) cell line on the basis of cytotoxic sensitivity and used this line to predict toxicity in the six categories based on the gene networks of iPS cells using transfer learning from the ES cell gene networks. We successfully predicted toxicities in four toxin categories (neurotoxins, hepatotoxins, glomerular nephrotoxins, and non-genotoxic carcinogens) at high accuracy (AUC = 0.82–0.99). These results demonstrate that the prediction of chemical toxicity is possible even with iPS cells by transfer learning once a gene expression database has been developed from an ES cell line. This method holds promise for tailor-made safety evaluations using individual iPS cells.

Summary Despite increasing knowledge on primed and naive pluripotency, the cell signaling that regulates the pluripotency type in stem cells remains not fully understood. Here we show that AMP kinase (AMPK) activators can induce the reversion of primed mouse epiblast stem cells (mEpiSCs) to the naive pluripotent state. The addition of AMPK activators alone or together with leukemia inhibitory factor to primed mEpiSCs induced the appearance of naive-like cells. After passaging in naive culture conditions, the colony morphology, protein expression, and global gene expression profiles indicated the naive state, as did germline transmission ability. Loss-of-function and gain-of-function studies suggested that p38 is a critical downstream target in AMPK activation. Finally, single-cell RNA sequencing analysis revealed that the reversion process through AMPK signaling passes an intermediate naive-like population. In conclusion, the AMPK pathway is a critical driving force in the reversion of primed to naive pluripotency., Graphical abstract, Highlights • AMPK activation can induce mouse primed stem cell reversion to naive state • Reverted cells fully obtain naive pluripotency • p38 is a critical downstream molecule of AMPK pathway in the reversion process • Dppa5 and Dazl are highly expressed in intermediate reversion cells, Cell biology; Stem cells research; Transcriptomics

Summary The past decade has witnessed an extremely rapid increase in the number of newly established stem cell lines. However, due to the lack of a standardized format, data exchange among stem cell line resources has been challenging, and no system can search all stem cell lines across resources worldwide. To solve this problem, we have developed the Integrated Collection of Stem Cell Bank data (ICSCB) (http://icscb.stemcellinformatics.org/), the largest database search portal for stem cell line information, based on the standardized data items and terms of the MIACARM framework. Currently, ICSCB can retrieve >16,000 cell lines from four major data resources in Europe, Japan, and the United States. ICSCB is automatically updated to provide the latest cell line information, and its integrative search helps users collect cell line information for over 1,000 diseases, including many rare diseases worldwide, which has been a formidable task, thereby distinguishing itself from other database search portals., Highlights • Searches >16,000 stem cell lines in Europe, Japan, and US major databases • Data formats standardized by minimum items in MIACARM guidelines • Searches specific stem cell lines according to disease, donor, tissue, etc. • User-friendly website accesses >6,000 diseased stem cell lines from 36 countries, This new and largest stem cell data portal can retrieve >16,000 cell lines from four major stem cell data resources in Europe, Japan, and the United States, is automatically updated to provide the latest cell line information, and, through its integrative search engine, can collect cell line information from specific donors with rare diseases worldwide.

Single-cell RNA-seq (scRNA-seq) analysis is widely used to characterize cell types or detect heterogeneity of cell states at much higher resolutions than ever before. Here we introduce scMontage (https://scmontage.stemcellinformatics.org), a gene expression similarity search server dedicated to scRNA-seq data, which can rapidly compare a query with thousands of samples within a few seconds. The scMontage search is based on Spearman’s rank correlation coefficient and its robustness is ensured by introducing Fisher’s Z-transformation and Z-test. Furthermore, search results are linked to a human cell database SHOGoiN (http://shogoin.stemcellinformatics.org), which enable users to fast access to additional cell-type specific information. The scMontage is available not only as a web server but also as a stand-alone application for user’s own data, and thus it enhances the reliability and throughput of cell analysis and helps users gain new insights into their research.

Toxicity prediction based on stem cells and tissue derived from stem cells plays a very important role in the fields of biomedicine and pharmacology. Here we report on qRT-PCR data obtained by exposing 20 compounds to human embryonic stem (ES) cells. The data are intended to improve toxicity prediction, per category, of various compounds through the use of support vector machines, and by applying gene networks. The accuracy of our system was 97.5-100% in three toxicity categories: neurotoxins (NTs), genotoxic carcinogens (GCs), and non-genotoxic carcinogens (NGCs). We predicted that two uncategorized compounds (bisphenol-A and permethrin) should be classified as follows: bisphenol-A as a non-genotoxic carcinogen, and permethrin as a neurotoxin. These predictions are supported by recent reports, and as such constitute a good outcome. Our results include two important features: 1) The accuracy of prediction was higher when machine learning was carried out using gene networks and activity, rather than the normal quantitative structure-activity relationship (QSAR); and 2) By using undifferentiated ES cells, the late effect of chemical substances was predicted. From these results, we succeeded in constructing a highly effective and highly accurate system to predict the toxicity of compounds using stem cells.

AK2 is an adenylate phosphotransferase that localizes at the intermembrane spaces of the mitochondria, and its mutations cause a severe combined immunodeficiency with neutrophil maturation arrest named reticular dysgenesis (RD). Although the dysfunction of hematopoietic stem cells (HSCs) has been implicated, earlier developmental events that affect the fate of HSCs and/or hematopoietic progenitors have not been reported. Here, we used RD-patient-derived induced pluripotent stem cells (iPSCs) as a model of AK2-deficient human cells. Hematopoietic differentiation from RD-iPSCs was profoundly impaired. RD-iPSC-derived hemoangiogenic progenitor cells (HAPCs) showed decreased ATP distribution in the nucleus and altered global transcriptional profiles. Thus, AK2 has a stage-specific role in maintaining the ATP supply to the nucleus during hematopoietic differentiation, which affects the transcriptional profiles necessary for controlling the fate of multipotential HAPCs. Our data suggest that maintaining the appropriate energy level of each organelle by the intracellular redistribution of ATP is important for controlling the fate of progenitor cells.

Background It has been pointed out that environmental factors or chemicals can cause diseases that are developmental in origin. To detect abnormal epigenetic alterations in DNA methylation, convenient and cost-effective methods are required for such research, in which multiple samples are processed simultaneously. We here present methylated site display (MSD), a unique technique for the preparation of DNA libraries. By combining it with amplified fragment length polymorphism (AFLP) analysis, we developed a new method, MSD-AFLP. Results Methylated site display libraries consist of only DNAs derived from DNA fragments that are CpG methylated at the 5′ end in the original genomic DNA sample. To test the effectiveness of this method, CpG methylation levels in liver, kidney, and hippocampal tissues of mice were compared to examine if MSD-AFLP can detect subtle differences in the levels of tissue-specific differentially methylated CpGs. As a result, many CpG sites suspected to be tissue-specific differentially methylated were detected. Nucleotide sequences adjacent to these methyl-CpG sites were identified and we determined the methylation level by methylation-sensitive restriction endonuclease (MSRE)-PCR analysis to confirm the accuracy of AFLP analysis. The differences of the methylation level among tissues were almost identical among these methods. By MSD-AFLP analysis, we detected many CpGs showing less than 5% statistically significant tissue-specific difference and less than 10% degree of variability. Additionally, MSD-AFLP analysis could be used to identify CpG methylation sites in other organisms including humans. Conclusion MSD-AFLP analysis can potentially be used to measure slight changes in CpG methylation level. Regarding the remarkable precision, sensitivity, and throughput of MSD-AFLP analysis studies, this method will be advantageous in a variety of epigenetics-based research. Electronic supplementary material The online version of this article (doi:10.1186/s12867-017-0083-2) contains supplementary material, which is available to authorized users.

Deciphering the key mechanisms of morphogenesis during embryonic development is crucial to understanding the guiding principles of the body plan and promote applications in biomedical research fields. Although several computational tissue reconstruction methods using cellular gene expression data have been proposed, those methods are insufficient with regard to arranging cells in their correct positions in tissues or organs unless spatial information is explicitly provided. Here, we report SPRESSO, a new in silico three-dimensional (3D) tissue reconstruction method using stochastic self-organizing map (stochastic-SOM) clustering, to estimate the spatial domains of cells in tissues or organs from only their gene expression profiles. With only five gene sets defined by Gene Ontology (GO), we successfully demonstrated the reconstruction of a four-domain structure of mid-gastrula mouse embryo (E7.0) with high reproducibility (success rate = 99%). Interestingly, the five GOs contain 20 genes, most of which are related to differentiation and morphogenesis, such as activin A receptor and Wnt family member genes. Further analysis indicated that Id2 is the most influential gene contributing to the reconstruction. SPRESSO may provide novel and better insights on the mechanisms of 3D structure formation of living tissues via informative genes playing a role as spatial discriminators.

This study proposes new minimum information guidelines, Minimum Information About a Cellular Assay for Regenerative Medicine (MIACARM), for cellular assay data deposition, to promote data exchange and facilitation of practical regenerative medicine., Advances in stem cell research have triggered scores of studies in regenerative medicine in a large number of institutions and companies around the world. However, reproducibility and data exchange among laboratories or cell banks are constrained by the lack of a standardized format for experiments. To enhance information flow in stem cell and derivative cell research, here we propose a minimum information standard to describe cellular assay data to facilitate practical regenerative medicine. Based on the existing Minimum Information About a Cellular Assay, we developed Minimum Information About a Cellular Assay for Regenerative Medicine (MIACARM), which allows for the description of advanced cellular experiments with defined taxonomy of human cell types. By using controlled terms, such as ontologies, MIACARM will provide a platform for cellular assay data exchange among cell banks or registries that have been established at more than 20 sites in the world. Significance Currently, there are more than 20 human cell information storage sites around the world. However, reproducibility and data exchange among different laboratories or cell information providers are usually inadequate or nonexistent because of the lack of a standardized format for experiments. This study, which is the fruit of collaborative work by scientists at stem cell banks and cellular information registries worldwide, including those in the U.S., the U.K., Europe, and Japan, proposes new minimum information guidelines, Minimum Information About a Cellular Assay for Regenerative Medicine (MIACARM), for cellular assay data deposition. MIACARM is intended to promote data exchange and facilitation of practical regenerative medicine.

An increasingly accepted concept is that the progression of colorectal cancer is accompanied by epithelial-mesenchymal transition (EMT). In our study, in order to characterize the properties of EMT in 16 colorectal cancer cell lines, the cells were first orthotopically implanted into nude mice, and the tumors in vivo, as well as cells cultured in vitro, were immunostained for EMT markers. The immunostaining revealed that seven of the cells had an epithelial phenotype with a high expression of E-cadherin, whereas other cells showed opposite patterns, such as a high expression of vimentin (CX-1, COLO205, CloneA, HCT116, and SW48). Among the cells expressing vimentin, some expressed vimentin in the orthotopic tumors but not in the cultured cells (SW480, SW620, and COLO320). We evaluated these findings in combination with microarray analyses, and selected five genes: CHST11, SERPINI1, AGR2, FBP1, and FOXA1. Next, we downregulated the expression of SERPINI1 with siRNA in the cells, the results of which showed reverse-EMT changes at the protein level and in the cellular morphology. Along with immunohistochemical analyses, we confirmed the effect of the intracellular and secreted SERPINI1 protein of SW620 cells, which supported the importance of SERPINI1 in EMT. The development of therapeutic strategies targeting EMT is ongoing, including methods targeting the transforming growth factor-β signaling pathway as well as the Wnt pathway. SERPINI1 is an important regulator of EMT. Our findings help to elucidate the signaling pathways of EMT, hopefully clarifying therapeutic pathways as well.

Renal cell carcinoma (RCC) is one of the most lethal urologic cancers. About one-third of RCC patients already have distal metastasis at the time of diagnosis. There is growing evidence that Hox antisense intergenic RNA (HOTAIR) plays essential roles in metastasis in several types of cancers. However, the precise mechanism by which HOTAIR enhances malignancy remains unclear, especially in RCC. Here, we demonstrated that HOTAIR enhances RCC-cell migration by regulating the insulin growth factor-binding protein 2 (IGFBP2) expression. HOTAIR expression in tumors was significantly correlated with nuclear grade, lymph-node metastasis, and lung metastasis. High HOTAIR expression was associated with a poor prognosis in both our dataset and The Cancer Genome Atlas dataset. Migratory capacity was enhanced in RCC cell lines in a HOTAIR-dependent manner. HOTAIR overexpression accelerated tumorigenicity and lung metastasis in immunodeficient mice. Microarray analysis revealed that IGFBP2 expression was upregulated in HOTAIR-overexpressing cells compared with control cells. The enhanced migration activity of HOTAIR-overexpressing cells was attenuated by IGFBP2 knockdown. IGFBP2 and HOTAIR were co-expressed in clinical RCC samples. Our findings suggest that the HOTAIR-IGFBP2 axis plays critical roles in RCC metastasis and may serve as a novel therapeutic target for advanced RCC.

In this work, we focus on two fundamental problems of toxicogenomics using the data provided by the Japanese toxicogenomics project. First, we analyze to what extent animal studies can be replaced by in in vitro assays. We show that the probeset-level representation achieves poor agreement between in vivo and in vitro data. We present a data collapsing approach to resolve poor data agreement between in vivo and in vitro data, as measured by GSEA analysis and AUC scores. Second, we address the difficult problem of predicting DILI using available microarray data. Using a binary classification framework, our results suggest that rat in vivo data are more informative than human in vitro data to predict DILI.

Various tissues possess tissue-specific stem/progenitor cells, including the inner ears. Stem/progenitor cells of the inner ear can be isolated as so-called otospheres from differentiated cells using a sphere forming assay. Although recent studies have demonstrated the characteristics of otospheres to some extent, most of the features of these cells are unknown. In this report, we describe the findings of transcriptome analyses with a cDNA microarray of otospheres derived from the cochleae of the inner ears of neonatal mice in order to clarify the gene expression profile of otic stem/progenitor cells. There were common transcription factors between otospheres and embryonic stem cells, which were supposed to be due to the stemness of otospheres. In comparison with the cochlear sensory epithelium, the otospheres shared characteristics with the cochlea, although several transcription factors specific for otospheres were identified. These transcription factors are expected to be essential for maintaining the characteristics of otospheres, and appear to be candidate genes that promote the direct conversion of cells into otic stem/progenitor cells.

This article summarizes the recent activity of the International Stem Cell Banking Initiative (ISCBI) held at the California Institute for Regenerative Medicine (CIRM) in California (June 26, 2016) and the Korean National Institutes for Health in Korea (October 19–20, 2016). Through the workshops, ISCBI is endeavoring to support a new paradigm for human medicine using pluripotent stem cells (hPSC) for cell therapies. Priority considerations for ISCBI include ensuring the safety and efficacy of a final cell therapy product and quality assured source materials, such as stem cells and primary donor cells. To these ends, ISCBI aims to promote global harmonization on quality and safety control of stem cells for research and the development of starting materials for cell therapies, with regular workshops involving hPSC banking centers, biologists, and regulatory bodies. Here, we provide a brief overview of two such recent activities, with summaries of key issues raised.

The epithelial-mesenchymal transition (EMT) is a critical step for pancreatic cancer cells as an entry of metastatic disease. Wide variety of cytokines and signaling pathways are involved in this complex process while the entire picture is still cryptic. Recently, miRNA was found to regulate cellular function including EMT by targeting multiple mRNAs. We conducted comprehensive analysis of miRNA expression profiles in invasive ductal adenocarcinoma (IDA), intraductal papillary mucinous adenoma, intraductal papillary mucinous carcinoma, and human pancreatic cancer cell line to elucidate essential miRNAs which regulate invasive growth of pancreatic cancer cells. Along with higher expression of miR-21 which has been shown to be highly expressed in IDA, reduced expression of miR-126 in IDA and pancreatic cancer cell line was detected. The miR-126 was found to target ADAM9 (disintegrin and metalloproteinase domain-containing protein 9) which is highly expressed in pancreatic cancer. The direct interaction between miR-126 and ADAM9 mRNA was confirmed by 3′ untranslated region assay. Reexpression of miR-126 and siRNA-based knockdown of ADAM9 in pancreatic cancer cells resulted in reduced cellular migration, invasion, and induction of epithelial marker E-cadherin. We showed for the first time that the miR-126/ADAM9 axis plays essential role in the inhibition of invasive growth of pancreatic cancer cells. Mol Cancer Res; 10(1); 3–10. ©2011 AACR.

Squid and bovine rhodopsins are G-protein coupled receptors (GPCRs) that activate Gq- and Gt-type G-proteins, respectively. To understand the structural elements of the signal propagation pathway, we performed molecular dynamics (MD) simulations of squid and bovine rhodopsins plus a detailed sequence analysis of class A GPCRs. The computations indicate that although the geometry of the retinal is similar in bovine and squid rhodopsins, the important interhelical hydrogen bond networks are different. In squid rhodopsin, an extended hydrogen bond network that spans ∼13 Å to Tyr315 on the cytoplasmic site is present regardless of the protonation state of Asp80. In contrast, the extended hydrogen bond network is interrupted at Tyr306 in bovine rhodopsin. Those differences in the hydrogen bond network may play significant functional roles in the signal propagation from the retinal binding site to the cytoplasmic site, including transmembrane helix (TM) 6 to which the G-protein binds. The MD calculations demonstrate that the elongated conformation of TM6 in squid rhodopsin is stabilized by salt bridges formed with helix (H) 9. Together with the interhelical hydrogen bonds, the salt bridges between TM6 and H9 stabilize the protein conformation of squid rhodopsin and may hinder the occurrence of large conformational changes that are observed upon activation of bovine rhodopsin.

Predictive toxicology using stem cells or their derived tissues has gained increasing importance in biomedical and pharmaceutical research. Here, we show that toxicity category prediction by support vector machines (SVMs), which uses qRT-PCR data from 20 categorized chemicals based on a human embryonic stem cell (hESC) system, is improved by the adoption of gene networks, in which network edge weights are added as feature vectors when noisy qRT-PCR data fail to make accurate predictions. The accuracies of our system were 97. 5-100% for three toxicity categories: neurotoxins (NTs), genotoxic carcinogens (GCs) and non-genotoxic carcinogens (NGCs). For two uncategorized chemicals, bisphenol-A and permethrin, our system yielded reasonable results: bisphenol-A was categorized as an NGC, and permethrin was categorized as an NT; both predictions were supported by recently published papers. Our study has two important features: (i) as the first study to employ gene networks without using conventional quantitative structure-activity relationships (QSARs) as input data for SVMs to analyze toxicogenomics data in an hESC validation system, it uses additional information of gene-to-gene interactions to significantly increase prediction accuracies for noisy gene expression data; and (ii) using only undifferentiated hESCs, our study has considerable potential to predict late-onset chemical toxicities, including abnormalities that occur during embryonic development., ES細胞と遺伝子ネットワークを用いた、高精度の化合物毒性予測システムの構築. 京都大学プレスリリース. 2016-06-14.

Alternative precursor messenger RNA (pre-mRNA) splicing plays an important role in the generation of functional diversity of the genome. The process of pre-mRNA splicing is regulated by cis- and trans-elements, and their deregulations result in aberrantly spliced individual variants and aberrant expression profiles. Accumulating evidence has revealed that aberrant splicing contributes to a number of diseases including human neoplasms. It is well known that germ line mutations in the cis-element of tumor suppressor genes such as mismatch repair (MMR) genes, the adenomatous polyposis coli (APC) gene and the E-cadherin (CDH1) gene are involved in Lynch syndrome, familial adenomatous polyposis and hereditary diffuse gastric cancer, respectively. In addition, somatic mutations in cis-elements also play a role in tumorigenesis. These genetic alterations including nonsense, missense or silent mutations in cis-elements led to aberrant transcripts by exon skipping, retention of the intron or introduction of a new splice site. The majority of erroneous transcripts with a premature termination codon are eliminated through nonsense-mediated mRNA decay. However, it is difficult to accurately predict the resulting transcripts with current in silico strategies. Correct interpretation of genetic alterations and the investigation of aberrant transcripts are crucial for genetic diagnosis of hereditary diseases and elucidation of the molecular characteristics of neoplasms from a clinical point of view. In this review we summarize the current knowledge of the regulatory mechanism underlying alternative pre-mRNA splicing and aberrant splicing, with particular focus on digestive tract malignancies.

5-Fluorouracil (5-FU) is a key anticancer drug that for its broad antitumor activity, as well as for its synergism with other anticancer drugs, has been used to treat various types of malignancies. In chemotherapeutic regimens, 5-FU has been combined with oxaliplatin, irinotecan and other drugs as a continuous intravenous infusion. Recent clinical chemotherapy studies have shown that several of the regimens with oral 5-FU drugs are not inferior compared to those involving continuous 5-FU infusion chemotherapy, and it is probable that in some regimens continuous 5-FU infusion can be replaced by oral 5-FU drugs. Historically, both the pharmaceutical industry and academia in Japan have been involved in the development of oral 5-FU drugs, and this review will focus on the current knowledge of 5-FU anabolism and catabolism, and the available information about the various orally-administrable 5-FU drugs, including UFT, S-1 and capecitabine. Clinical studies comparing the efficacy and adverse events of S-1 and capecitabine have been reported, and the accumulated results should be utilized to optimize the treatment of cancer patients. On the other hand, it is essential to elucidate the pharmacokinetic mechanism of each of the newly-developed drugs, to correctly select the drugs for each patient in the clinical setting, and to further develop optimized drug derivatives.

Currently 5-fluorouracil (5-FU) plays a central role in the chemotherapeutic regimens for colorectal cancers and thus it is important to understand the mechanisms that determine 5-FU sensitivity. The expression profiles of human colon cancer cell line DLD-1, its 5-FU-resistant subclone DLD-1/FU and a further 21 types of colon cancer cell lines were compared to identify the novel genes defining the sensitivity to 5-FU and to estimate which population of genes is responsible for 5-FU sensitivity. In the hierarchical clustering, DLD-1 and DLD-1/FU were most closely clustered despite over 100 times difference in their 50% inhibitory concentration of 5-FU. In DLD-1/FU, the population of genes differentially expressed compared to DLD-1 was limited to 3.3%, although it ranged from 4.8% to 24.0% in the other 21 cell lines, thus indicating that the difference of 5-FU sensitivity was defined by a limited number of genes. Next, the role of the cellular inhibitor of apoptosis 2 (cIAP2) gene, which was up-regulated in DLD-1/FU, was investigated for 5-FU resistance using RNA interference. The down-regulation of cIAP2 efficiently enhanced 5-FU sensitivity, the activation of caspase 3/7 and apoptosis under exposure to 5-FU. The immunohistochemistry of cIAP2 in cancer and corresponding normal tissues from colorectal cancer patients in stage III revealed that cIAP2 was more frequently expressed in cancer tissues than in normal tissues, and cIAP2-positive patients had a trend toward early recurrence after fluorouracil-based chemotherapy. Although the association between drug sensitivity and the IAP family in colorectal cancer has not yet been discussed, cIAP2 may therefore play an important role as a target therapy in colorectal cancer.

In colorectal cancer (CRC) patients, metastasis to the regional lymph node (LN) is an important first step in the dissemination of cancers. To identify the genes possibly involved in LN metastasis of CRC, we analyzed LN metastases in an orthotopic implantation mouse model with 22 CRC cell lines using Matrigel, an extracellular matrix protein derived from mice sarcoma, and combined the data with gene expression profiles of cDNA microarray of those cell lines. With this implantation analysis, the incidence of LN metastasis was 60% in 228 orthotopically implanted mice and varied from 100% to 0% among the cell lines. KM12c and Clone A showed LN metastasis in all orthotopically implanted mice, but DLD-1, HCT-8, and SW948 did not show LN metastases at all. In contrast, the incidence of liver and lung metastasis in 22 CRC cell lines was 13% and 1%, respectively. Combining those data with cDNA microarray in vitro, we isolated 636 genes that were differentially expressed depending on the incidence of LN metastasis. Among those genes, the expression level of ring finger protein 125 (RNF125), previously known as an E3 ubiquitin ligase in T cell activation, was significantly different between primary tumors in Stage III CRC patients with LN metastasis and Stage II patients without LN metastasis. In conclusion, the orthotopic implantation mice model with Matrigel was useful, and we isolated candidate genes such as RNF125 that possibly play an important role in LN metastasis of CRC cells.

A gene expression module (module for short) is a set of genes with shared expression behavior under certain experimental conditions. Discovering of modules enables us to uncover the function of uncharacterized genes or genetic networks. In recent years, several biclustering methods have been suggested to discover modules from gene expression data matrices, where a bicluster is defined as a subset of genes that exhibit a highly correlated expression pattern over a subset of conditions. Biclustering however involves combinatorial optimization in selecting the rows and columns composing modules. Hence most existing algorithms are based on heuristic or stochastic approaches and produce possibly sub-optimal solutions. In this paper, we propose a novel biclustering method, BiModule, based on a closed itemset enumeration algorithm. By exhaustive enumeration of such biclusters, it is possible to select only biclusters satisfying certain criteria such as a user-specified bicluster size, an enrichment of functional annotation terms, etc. We performed comparative experiments to existing salient biclustering methods to test the validity of biclusters extracted by BiModule using synthetic data and real expression data. We show that BiModule provides high performance compared to the other methods in extracting artificially-embedded modules as well as modules strongly related to GO annotations, protein-protein interactions and metabolic pathways.

Recently there has been a surge of interest in kernel methods such as support vector machine due to their flexibility and high performance. It is important how to define a kernel for kernel methods. Most of kernels are defined by inner-product of feature vectors in some vector space. In this paper we discuss an approach which constructs a kernel matrix from distances between examples instead of feature vectors. Namely, the input data of our algorithm are the distances among examples, not feature vectors. Dissimilar to most of conventional kernels where kernel functions are explicitly given and the kernel matrices are determined by simple calculations, our algorithm rather builds a kernel matrix by maximizing its entropy subject to distance constraints. The maximization problem is convex, so we can always attain to the optimal solution. Experiments using artificial data show the benefits of our algorithm. In addition, we apply this method to analysis of heterogeneous microarray gene expression data, and report the experimental results.

Supplemental Data; International audience; Oleaginous photosynthetic organisms such as microalgae are promising sources for biofuel production through the generation of carbon-neutral sustainable energy. However, the metabolic mechanisms driving high-rate lipid production in these oleaginous organisms remain unclear, thus impeding efforts to improve productivity through genetic modifications. We analyzed the genome and transcriptome of the oleaginous diatom Fistulifera solaris JPCC DA0580. Next-generation sequencing technology provided evidence of an allodiploid genome structure, suggesting unorthodox molecular evolutionary and genetic regulatory systems for reinforcing metabolic efficiencies. Although major metabolic pathways were shared with nonoleaginous diatoms, transcriptome analysis revealed unique expression patterns, such as concomitant upregulation of fatty acid/triacylglycerol biosynthesis and fatty acid degradation (β-oxidation) in concert with ATP production. This peculiar pattern of gene expression may account for the simultaneous growth and oil accumulation phenotype and may inspire novel biofuel production technology based on this oleaginous microalga.

The availability of computerized knowledge on biochemical pathways in the KEGG database opens new opportunities for developing computational methods to characterize and understand higher level functions of complete genomes. Our approach is based on the concept of graphs; for example, the genome is a graph with genes as nodes and the pathway is another graph with gene products as nodes. We have developed a simple method for graph comparison to identify local similarities, termed correlated clusters, between two graphs, which allows gaps and mismatches of nodes and edges and is especially suitable for detecting biological features. The method was applied to a comparison of the complete genomes of 10 microorganisms and the KEGG metabolic pathways, which revealed, not surprisingly, a tendency for formation of correlated clusters called FRECs (functionally related enzyme clusters). However, this tendency varied considerably depending on the organism. The relative number of enzymes in FRECs was close to 50% for Bacillus subtilis and Escherichia coli, but was

Fistulifera sp. strain JPCC DA0580 is a newly sequenced pennate diatom that is capable of simultaneously growing and accumulating lipids. This is a unique trait, not found in other related microalgae so far. It is able to accumulate between 40 to 60% of its cell weight in lipids, making it a strong candidate for the production of biofuel. To investigate this characteristic, we used RNA-Seq data gathered at four different times while Fistulifera sp. strain JPCC DA0580 was grown in oil accumulating and non-oil accumulating conditions. We then adapted gene set enrichment analysis (GSEA) to investigate the relationship between the difference in gene expression of 7,822 genes and metabolic functions in our data. We utilized information in the KEGG pathway database to create the gene sets and changed GSEA to use re-sampling so that data from the different time points could be included in the analysis. Our GSEA method identified photosynthesis, lipid synthesis and amino acid synthesis related pathways as processes that play a significant role in oil production and growth in Fistulifera sp. strain JPCC DA0580. In addition to GSEA, we visualized the results by creating a network of compounds and reactions, and plotted the expression data on top of the network. This made existing graph algorithms available to us which we then used to calculate a path that metabolizes glucose into triacylglycerol (TAG) in the smallest number of steps. By visualizing the data this way, we observed a separate up-regulation of genes at different times instead of a concerted response. We also identified two metabolic paths that used less reactions than the one shown in KEGG and showed that the reactions were up-regulated during the experiment. The combination of analysis and visualization methods successfully analyzed time-course data, identified important metabolic pathways and provided new hypotheses for further research.

We present here a heuristic method toward predicting the expression specificity in the transcriptional process, which is known to be regulated in large part by promoter sequences, by observing the appearance of conserved sequence patterns in a group of known promoters, such as for housekeeping or tissue-specific genes. Statistically conserved patterns were automatically extracted from a set of unaligned sequences up to 200 bp upstream of the transcription initiation site, by a standard procedure using the Markov chain and binomial distribution models. Furthermore, to obtain signal sequences of optimal lengths we devised a method that combines the multiple alignment and the analysis of the information content (or relative entropy). Groups of related promoters were compiled from the EPD eukaryotic promoter database and the EMBL nucleic acid sequence database. Each promoter was examined for its specificity by linear discriminant analysis to test the validity of the extracted patterns. Our method could correctly discriminate 77.6% of the housekeeping gene promoters and 62.9% of the liver promoters.

In silico three-dimensional (3D) reconstruction of tissues/organs based on single-cell profiles is required to comprehensively understand how individual cells are organized in actual tissues/organs. Although several tissue reconstruction methods have been developed, they are still insufficient to map cells on the original tissues in terms of both scale and quality. In this study, we aim to develop a novel informatics approach which can reconstruct whole and various tissues/organs in silico. As the first step of this project, we conducted single-cell transcriptome analysis of 38 individual cells obtained from two mouse blastocysts (E3.5d) and tried to reconstruct blastocyst structures in 3D. In reconstruction step, each cell position is estimated by 3D principal component analysis and expression profiles of cell adhesion genes as well as other marker genes. In addition, we also proposed a reconstruction method without using marker gene information. The resulting reconstructed blastocyst structures implied an indirect relationship between the genes of Myh9 and Oct4.

A wide range of stem cell research towards regenerative medicine has been conducted in a large number of domains in the world over the years. However, those produced data and information are not fully utilized and sometimes causes failure to be reproduced among laboratories or cell banks due to a lack of standardization of cellular assay reporting formats. To maximize a value placed on the information in stem cell and derivative cell research, we have proposed reporting guidelines for describing cellular assay data to pursue the facilitation of practical regenerative medicine named ‘Minimum Information About a Cellular Assay for Regenerative Medicine (MIACARM)’. MIACARM has been developed based on the existing Minimum Information About a Cellular Assay (MIACA) with defined taxonomy of human cell types, which allows for the description of advanced cellular experiments. MIACARM is applicable for exchanging data from not only for basic cellular assay, but also stem cell assay data that are produced and provided by cell banks, registries, or other academic institutions all over the world. And here we would like to introduce our recent progress that is developing stem cell data retrieval system based on MIACARM.

Single-cell analysis provides molecular signatures to define cell identity. To characterize cell types, DNA methylation patterns are often used as a flag of internal molecular status. There are a few reports of single-cell methylome techniques that involves bisulfite conversion. However, the step often causes DNA fragmentation, which leads to severe PCR substrate reduction. Here we developed a new version of single-cell reduced representation bisulfite sequencing (scRRBS) method to recover more CpG sites to be analysed. Our method succeeded to increase of 4.1 times in sample yield and 1.6 times in CpG site coverage. Importantly, our results indicate that the obtained single-cell DNA methylation sites are homogeneous among 12 cells, thus it may provide molecular barcodes for cell types. In summary, we succeed to develop enhanced scRRBS method and it will be more useful tool to define cell identity in the near future.

We are exposed to many environmental chemicals in our daily life. Certain chemicals threaten our health, especially that of embryos and can cause serious developmental problems. To prevent abnormal development and diseases caused by chemicals, it is important to clarify the mechanisms of chemical toxicity in embryonic cells. The gene regulatory network is one of the useful methods for clarifying functional mechanisms in living cells, so we applied a statistical method to infer the gene regulatory network in human embryonic stem cells. In this study, we improved our previously developed SEM approach for inferring a network model from 9 gene expression profiles in human embryonic stem cells, which were exposed to various chemicals. The estimated regulatory models clarified the differences between chemicals, and the shapes of the inferred models reflected the features of the chemical toxicities. The toxicity of acrylamide affected neuronal cell-related genes, while that of diethylnitrosamine disturbed cell differentiation-related genes. On the other hand, the TCDD network reflected feedback regulation, and finally disturbed neuronal cell-related genes. In the Thalidomide network, cell differentiation genes related to axis formation in embyronic cells were affected by thalidomide toxicity.

Alternative pre-mRNA splicing allows exons of pre-mRNA to be spliced in different arrangements to produce functionally distinct mRNAs. More than 95% of human genes encode splice isoforms, some of which exert antagonistic functions. Recent studies revealed that alterations of the splicing machinery can cause the development of neoplasms, and understanding the splicing machinery is crucial for developing novel therapeutic strategies for malignancies. Colorectal cancer patients need novel strategies not only to enhance the efficacy of the currently available agents but also to utilize newly identified therapeutic targets. This review summarizes the current knowledge about the splice isoforms of VEGFA, UGT1A, PXR, cyclin D1, BIRC5 (survivin), DPD, K-RAS, SOX9, SLC39A14 and other genes, which may be possible therapeutic targets for colorectal cancer. Among them, the VEGFA splice isoforms are classified into VEGFAxxx and VEGFAxxxb, which have proangiogenic and antiangiogenic properties, respectively; UGT1A is alternatively spliced into UGT1A1 and other isoforms, which are regulated by pregnane X receptor isoforms and undergo further splicing modifications. Recently, the splicing machinery has been extensively investigated and novel discoveries in this research field are being reported at a rapid pace. The information contained in this review also provides suggestions for how therapeutic strategies targeting alternative splicing can be further developed.

CELLPEDIA is a repository database for current knowledge about human cells. It contains various types of information, such as cell morphologies, gene expression and literature references. The major role of CELLPEDIA is to provide a digital dictionary of human cells for the biomedical field, including support for the characterization of artificially generated cells in regenerative medicine. CELLPEDIA features (i) its own cell classification scheme, in which whole human cells are classified by their physical locations in addition to conventional taxonomy; and (ii) cell differentiation pathways compiled from biomedical textbooks and journal papers. Currently, human differentiated cells and stem cells are classified into 2260 and 66 cell taxonomy keys, respectively, from which 934 parent-child relationships reported in cell differentiation or transdifferentiation pathways are retrievable. As far as we know, this is the first attempt to develop a digital cell bank to function as a public resource for the accumulation of current knowledge about human cells. The CELLPEDIA homepage is freely accessible except for the data submission pages that require authentication (please send a password request to cell-info@cbrc.jp). Database URL: http://cellpedia.cbrc.jp/

Profiles of Chemical Effects on Cells (pCEC) is a toxicogenomics database with a system of classifying chemicals that have effects on human health. This database stores and handles gene expression profiling information and categories of toxicity data. Chemicals are classified according to the specific tissues and cells they affect, the gene expression changes they induce, their toxicity and biological functions in this database system. The pCEC system also analyzes relationships between chemicals and the genes they affect in specific tissues and cells. The reason why we developed pCEC is to support decision-making within the context of environmental regulation. Especially, exposure to environmental chemicals during fetal and newborn development may result in a predisposition to various disorders such as cancer, learning disabilities and allergies later in life. The identification and prediction of hazardous chemicals using limited information are important issues in human health risk management. Therefore, various toxicity information including lethal dose 50 (LD50), toxicity pathways and pathological data were loaded into pCEC. pCEC is also a facility for query, analysis and prediction of unknown toxicochemical reaction pathways and biomarkers which are based on toxicoinformatical data mining approaches. This database is available online at http://project.nies.go.jp/eCA/cgi-bin/index.cgi. The current version of the database has information on the hepatotoxicity, reproductive toxicity and embryotoxicity of chemicals.

We previously reported that bone morphogenetic protein (BMP)-4 induces epithelial-mesenchymal transition in a pancreatic cancer cell line. To further investigate the detailed molecular mechanism of BMP action in pancreatic cancer, we carried out comprehensive microarray analysis in Panc-1 cells. The microarray analysis elucidated novel BMP target genes, and among them, the calcium-binding protein S100P was identified as an upregulated gene. S100P induction by BMP4 was confirmed by real-time reverse transcription-polymerase chain reaction and western blot analysis in Panc-1 and HPDE cells. Short interfering RNA-based knockdown of S100P expression sufficiently repressed BMP4-induced cell migration in Panc-1 cells. Because Panc-1 and HPDE cells express wild-type Smad4, we hypothesized that Smad4 might be indispensable for S100P induction by BMP4. S100P induction by BMP4 was not observed in the Smad4-null cell line BxPC3, and was sufficiently attenuated in short interfering RNA-based Smad4-knockdown Panc-1 cells. Interestingly, detailed promoter analysis revealed that upregulation of S100P by BMP4 was independent of the Smad-binding element, indicating that an additional unknown downstream factor of the Smad4-dependent pathway is necessary for this induction. These findings are the first of their kind, and this Smad4-dependent regulation of S100P by BMP signaling might explain the migratory mechanism of cancer cells, which is still unknown.