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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.

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.

RNA external standards, although important to ensure equivalence across many microarray platforms, have yet to be fully implemented in the research community. In this article, a set of unique RNA external standards (or RNA standards) and probe pairs that were added to total RNA in the samples before amplification and labeling are described. Concentration–response curves of RNA external standards were used across multiple commercial DNA microarray platforms and/or quantitative real-time polymerase chain reaction (RT–PCR) and next-generation sequencing to identify problematic assays and potential sources of variation in the analytical process. A variety of standards can be added in a range of concentrations spanning high and low abundances, thereby enabling the evaluation of assay performance across the expected range of concentrations found in a clinical sample. Using this approach, we show that we are able to confirm the dynamic range and the limit of detection for each DNA microarray platform, RT–PCR protocol, and next-generation sequencer. In addition, the combination of a series of standards and their probes was investigated on each platform, demonstrating that multiplatform calibration and validation is possible.

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.

Uncovering the latent structure of the data is an active research topic in data mining. However, in the distance metric learning framework, previous studies have mainly focused on the classification performance. In this work, we consider the distance metric learning problem in the ranking setting, where predicting the order between the data vectors is more important than predicting the class labels. We focus on two problems: improving the ranking prediction accuracy and identifying the latent structure of the data. The core of our model consists of ranking the data using a Mahalanobis distance function. The additional use of non-negativity constraints and an entropy-based cost function allows us to simultaneously minimize the ranking error while identifying useful meta-features. To demonstrate its usefulness for information retrieval applications, we compare the performance of our method with four other methods on four UCI data sets, three text data sets, and four image data sets. Our approach shows good ranking accuracies, especially when few training data are available. We also use our model to extract and interpret the latent structure of the data sets. In addition, our approach is simple to implement and computationally efficient and can be used for data embedding and visualization.

The treatments and prognoses of pelvic organ carcinomas differ, depending on whether the primary tumor originated in the rectum, urinary bladder, prostate, ovary, or uterus; therefore, it is essential to diagnose pathologically the primary origin and stages of these tumors. To establish the panels of immunohistochemical markers for differential diagnosis, we reviewed 91 of the NCBI articles on these topics and found that the results correlated closely with those of the public protein database, the Human Protein Atlas. The results revealed the panels of immunohistochemical markers for the differential diagnosis of rectal adenocarcinoma, in which [+] designates positivity in rectal adenocarcinoma and [-] designates negativity in rectal adenocarcinoma: from bladder adenocarcinoma, CDX2[+], VIL1[+], KRT7[-], THBD[-] and UPK3A[-]; from prostate adenocarcinoma, CDX2[+], VIL1[+], CEACAM5[+], KLK3(PSA)[-], ACPP(PAP)[-] and SLC45A3(prostein)[-]; and from ovarian mucinous adenocarcinoma, CEACAM5[+], VIL1[+], CDX2[+], KRT7[-] and MUC5AC[-]. The panels of markers distinguishing ovarian serous adenocarcinoma, cervical carcinoma, and endometrial adenocarcinoma were also represented. Such a comprehensive review on the differential diagnosis of carcinomas of pelvic organs has not been reported before. Thus, much information has been accumulated in public databases to provide an invaluable resource for clinicians and researchers.

The apoptosis and antiapoptotic signaling pathways are important for regulating carcinogenesis and cancer progression, and for determining prognosis. Molecules involved in apoptosis represent potential cancer diagnostic markers and therapeutic targets. The inhibitor of apoptosis protein (IAP) family includes several important molecules involved in apoptosis that might represent such targets. Increasing evidence has demonstrated that the IAP family of proteins is integral for antiapoptotic and nuclear factor-κB signal transduction, and enhanced expression of IAPs contributes to colon carcinogenesis and its poor prognosis, as well as to drug resistance of tumors. X-linked IAP, cIAP1, cIAP2, and survivin are prognostic markers of colorectal cancer, and survivin and cIAP2 are also utilized to predict the effect of anticancer treatment in colorectal cancer patients. Novel therapies such as YM155 and LY2181308 targeting survivin, AEG35156 and phenoxodiol targeting X-linked IAP, AT-406 as a Smac mimetic, and survivin peptides are currently being evaluated in clinical trials. This report reviews the involvement of the IAP family in colorectal adenocarcinoma in order to summarize the role of the IAP family members as diagnostic and therapeutic targets, and to provide an overview of the future course of research in this area.

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.

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.

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.

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.

Background/aims Recently the role of tumor-associated macrophages (TAMs) on immunity has been variously discussed. We studied a series of cell surface antigens in TAMs in colorectal cancer tissues and their corresponding normal tissues using flow cytometry to find out prognostic indicators of these patients. Methodology We assessed the numbers of CD14+ macrophages positive for each of the cell surface antigens (CD80, CD86, HLA-DR, CD1a, CD40 and CD83) in cancer tissues and corresponding normal tissues among 31 patients with colorectal cancer, and performed the univariate and multivariate analysis to find out prognostic indicators for overall survival among the patients. Results The numbers of CD80+, CD86+ and HLA-DR+ TAMs in the cancer tissues were higher than those in corresponding normal tissues. Inversely CD40+ and CD83+ macrophages in cancer tissues were less than those in normal tissues. With the multivariate analysis, the number of CD40+ TAMs, as well as lymph node metastasis and distant metastasis, was shown to be an independent prognostic factor of colorectal cancer patients. Conclusions The dense infiltration of CD40+ TAM in colorectal cancer tissues indicates a favorable prognosis, which suggests that CD40 plays an important role in the tumor immunity of colorectal cancer.

Next generation sequencing (NGS) technology has increasingly become the backbone of transcriptomics analysis, but sequencer error causes biases in the read counts. In this paper we establish a framework for predicting true sequences from NGS data. We formulate this task as a classification problem. We define several features, such as log likelihood ratio of estimated true counts, error probability and observed count of the reads. Using a Support Vector Machine (SVM) classifier, we show that on simulated reads these features can achieve 96.35% classification accuracy in discriminating true sequences. Using this framework we provide a way for users to select sequences with a desired precision and recall for their analysis. The feature generation software and the simulated data set can be obtained from (http://seq.cbrc.jp/NGSFeatGen).

Gene clustering is one of the main themes of data mining approaches in bioinformatics. Although it has the power to analyze gene function, interpretation of the results becomes increasingly difficult when the number of experiments (samples) exceeds hundreds or more. A new type of clustering called "biclustering," where genes and experiments are coclustered in a large-scale of gene expression data, has been extensively studied in the last decade. We have developed "SAMURAI," an original program that detects all the biclusters or "gene modules" whose genes have similar expression patterns to query profile using the ultrafast data mining algorithm called Linear-time Closed itemset Miner (LCM). Using chemical toxicity dataset from J&J rat liver experiments, we compiled an exhaustive dictionary of gene modules by searching datasets of gene modules with each chemical exposure experiment as query. Through the module analysis, we found that our program can detect up/down-regulated gene sets that significantly represent particular GO functions or KEGG pathways, thereby unraveling reactions and mechanisms common to different toxicochemical treatments of hepatocytes.

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest fully public repository for high-throughput molecular abundance data, primarily gene expression data. The database has a flexible and open design that allows the submission, storage and retrieval of many data types. These data include microarray-based experiments measuring the abundance of mRNA, genomic DNA and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. GEO currently holds over 30,000 submissions representing approximately half a billion individual molecular abundance measurements, for over 100 organisms. Here, we describe recent database developments that facilitate effective mining and visualization of these data. Features are provided to examine data from both experiment- and gene-centric perspectives using user-friendly Web-based interfaces accessible to those without computational or microarray-related analytical expertise. The GEO database is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.

Purpose The aim of this study was to investigate the association between 5-fluorouracil (5-FU)-related adverse events (AEs) in Japanese patients with gastrointestinal cancer treated with 5-FU and the patient genotypes DPYD, MTHFR, OPRT, and TYMS. Methods Sequence analyses of 33 gene polymorphisms in four genes were performed using genomic DNA extracted from peripheral blood mononuclear cells of 103 patients with gastric (n = 34) or colorectal (n = 69) cancer. The 5-FU-related AEs of 157 regimens in these 103 patients were evaluated based on the medical records of patients in each of three groups: the intravenous administration group (i.v. group, n = 51), oral administration group (p.o. group, n = 106), and all-regimens group (both i.v. and p.o. group, n = 157). The associations between the incidence of AEs and each genotype were statistically analyzed. Results Six single-nucleotide polymorphisms (SNPs) were identified (three SNPs in DPYD: c.496A>G, c.1905+1G>A, and c.2303C>A; two SNPs in MTHFR: c.677C>T and c.1298A>C; and one SNP in OPRT: c.638G>C). Among them, the patients in the all-regimens group carrying any one of three DPYD SNPs showed statistically significant associations with the incidence of AEs of any type and fatigue. Furthermore, the MTHFR SNP c.1298A>C was significantly associated with the incidence of neutropenia. A similar trend was observed in the p.o. group, but not in the i.v. group. Conclusion These findings suggest that the DPYD SNPs c.496A>G, c.1905+1G>A, and c.2303C>A and the MTHFR SNP c.1298A>C may be predictive factors for the occurrence of severe 5-FU-related AEs. Citation Format: Masahide Toshima, Shinobu Ohnuma, Michiiro Tanaka, Koh Miura, Wataru Fujibuchi, Taiki Kajiwara, Toshihiro Komura, Hiroaki Musha, Sho Haneda, Katsuyoshi Kudoh, Atsushi Kohyama, Takeshi Naitoh, Michiaki Unno. Single nucleotide polymorphisms of DPYD and MTHFR predict adverse events associated with 5-fluorouracil in patients with gastrointestinal cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2832. doi:10.1158/1538-7445.AM2014-2832

[Introduction] Inhibition of the apoptotic pathway is one of the factors that may be responsible for carcinogenesis and drug resistance, and the inhibitor of apoptosis protein (IAP) family is thought to prevent apoptosis through inhibition of caspases and pro-caspases and may affect anti-cancer drug sensitivity. [Purposes] The purpose of this study is to clarify the roles of cellular inhibitor of apoptosis 2 (cIAP2) gene, which is a member of IAP family, on apoptosis and 5-FU sensitivity in cancer cells. [Methods and Results] The expression profiles of human colon cancer cell line DLD-1, its 5-FU-resistant subclone DLD-1/FU and further 21 types of colon cancer cell lines were compared. 50% inhibitory concentration (IC50) of 5-FU in DLD-1/FU was over 100 times higher than that in DLD-1. With the analysis of expression profiles among 23 genes, we found that cIAP2 gene was up-regulated in DLD-1/FU compared with DLD-1 and other cell lines with low IC50. Next, the role of the cIAP2 gene 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 5-FU-based chemotherapy. [Conclusion] IAPs are reported to be abnormally regulated and expressed in the majority of human malignancies at elevated levels. Among them, cIAP2 should be a possible therapeutic target in malignancies, especially in colorectal cancer. Citation Format: Koh Miura, Hideaki Karasawa, Wataru Fujibuchi, Shinobu Ohnuma, Michiaki Unno. cIAP2 as a therapeutic target in malignancies. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2190. doi:10.1158/1538-7445.AM2013-2190