Hiro Takahashi

Gene expression analysis of soft tissue sarcomas: characterization and reclassification of malignant fibrous histiocytoma

In soft tissue sarcomas, the diagnosis of malignant fibrous histiocytoma (MFH) has been a very controversial issue, and MFH is now considered to be reclassified into pleomorphic subtypes of other sarcomas. To characterize MFH genetically, we used an oligonucleotide microarray to analyze gene expression in 105 samples from 10 types of soft tissue tumors. Spindle cell and pleomorphic sarcomas, such as dedifferentiated liposarcoma, myxofibrosarcoma, leiomyosarcoma, malignant peripheral nerve sheath tumor (MPNST), fibrosarcoma and MFH, showed similar gene expression patterns compared to other tumors. Samples from those five sarcoma types could be classified into respective clusters based on gene expression by excluding MFH samples. We calculated distances between MFH samples and other five sarcoma types (dedifferentiated liposarcoma, myxofibrosarcoma, leiomyosarcoma, MPNST and fibrosarcoma) based on differentially expressed genes and evaluated similarities. Three of the 21 MFH samples showed marked similarities to one of the five sarcoma types, which were supported by histological findings. Although most of the remaining 18 MFH samples showed little or no histological resemblance to one of the five sarcoma types, 12 of them showed moderate similarities in terms of gene expression. These results explain the heterogeneity of MFH and show that the majority of MFHs could be reclassified into pleomorphic subtypes of other sarcomas. Taken together, gene expression profiling could be a useful tool to unveil the difference in the underlying molecular backgrounds, which leads to a rational taxonomy and diagnosis of a diverse group of soft tissue sarcomas.

Dual regulation of ETTIN (ARF3) gene expression by AS1-AS2, which maintains the DNA methylation level, is involved in stabilization of leaf adaxial-abaxial partitioning in Arabidopsis

Leaf primordia are generated at the periphery of the shoot apex, developing into flat symmetric organs with adaxial-abaxial polarity, in which the indeterminate state is repressed. Despite the crucial role of the ASYMMETRIC LEAVES1 (AS1)-AS2 nuclear-protein complex in leaf adaxial-abaxial polarity specification, information on mechanisms controlling their downstream genes has remained elusive. We systematically analyzed transcripts by microarray and chromatin immunoprecipitation assays and performed genetic rescue of as1 and as2 phenotypic abnormalities, which identified a new target gene, ETTIN (ETT)/AUXIN RESPONSE FACTOR3 (ARF3), which encodes an abaxial factor acting downstream of the AS1-AS2 complex. While the AS1-AS2 complex represses ETT by direct binding of AS1 to the ETT promoter, it also indirectly activates miR390- and RDR6-dependent post-transcriptional gene silencing to negatively regulate both ETT and ARF4 activities. Furthermore, AS1-AS2 maintains the status of DNA methylation in the ETT coding region. In agreement, filamentous leaves formed in as1 and as2 plants treated with a DNA methylation inhibitor were rescued by loss of ETT and ARF4 activities. We suggest that negative transcriptional, post-transcriptional and epigenetic regulation of the ARFs by AS1-AS2 is important for stabilizing early leaf partitioning into abaxial and adaxial domains.

ASYMMETRIC LEAVES2 and Elongator, a Histone Acetyltransferase Complex, Mediate the Establishment of Polarity in Leaves of Arabidopsis thaliana

Leaf primordia are generated around the shoot apical meristem. Mutation of the ASYMMETRIC LEAVES2 (AS2) gene of Arabidopsis thaliana results in defects in repression of the meristematic and indeterminate state, establishment of adaxial-abaxial polarity and left-right symmetry in leaves. AS2 represses transcription of meristem-specific class 1 KNOX homeobox genes and of the abaxial-determinant genes ETTIN/ARF3, KANADI2 and YABBY5. To clarify the role of AS2 in the establishment of leaf polarity, we isolated mutations that enhanced the polarity defects associated with as2. We describe here the enhancer-of-asymmetric-leaves-two1 (east1) mutation, which caused the formation of filamentous leaves with abaxialized epidermis on the as2-1 background. Levels of transcripts of class 1 KNOX and abaxial-determinant genes were markedly higher in as2-1 east1-1 mutant plants than in the wild-type and corresponding single-mutant plants. EAST1 encodes the histone acetyltransferase ELONGATA3 (ELO3), a component of the Elongator complex. Genetic analysis, using mutations in genes involved in the biogenesis of a trans-acting small interfering RNA (ta-siRNA), revealed that ELO3 mediated establishment of leaf polarity independently of AS2 and the ta-siRNA-related pathway. Treatment with an inhibitor of histone deacetylases (HDACs) caused additive polarity defects in as2-1 east1-1 mutant plants, suggesting the operation of an ELO3 pathway, independent of the HDAC pathway, in the determination of polarity. We propose that multiple pathways play important roles in repression of the expression of class 1 KNOX and abaxial-determinant genes in the development of the adaxial domain of leaves and, thus, in the establishment of leaf polarity.

Changes in mRNA Stability Associated with Cold Stress in Arabidopsis Cells

Control of mRNA half-life is a powerful strategy to adjust individual mRNA levels to various stress conditions, because the mRNA degradation rate controls not only the steady-state mRNA level but also the transition speed of mRNA levels. Here, we analyzed mRNA half-life changes in response to cold stress in Arabidopsis cells using genome-wide analysis, in which mRNA half-life measurements and transcriptome analysis were combined. Half-lives of average transcripts were determined to be elongated under cold conditions. Taking this general shift into account, we identified more than a thousand transcripts that were classified as relatively stabilized or relatively destabilized. The relatively stabilized class was predominantly observed in functional categories that included various regulators involved in transcriptional, post-transcriptional and post-translational processes. On the other hand, the relatively destabilized class was enriched in categories related to stress and hormonal response proteins, supporting the idea that rapid decay of mRNA is advantageous for swift responses to stress. In addition, pentatricopeptide repeat, cyclin-like F-box and Myb transcription factor protein families were significantly over-represented in the relatively destabilized class. The global analysis presented here demonstrates not only the importance of mRNA turnover control in the cold stress response but also several structural characteristics that might be important in the control of mRNA stability.

Identification of novel Arabidopsis thaliana upstream open reading frames that control expression of the main coding sequences in a peptide sequence-dependent manner

Upstream open reading frames (uORFs) are often found in the 5′-leader regions of eukaryotic mRNAs and can negatively modulate the translational efficiency of the downstream main ORF. Although the effects of most uORFs are thought to be independent of their encoded peptide sequences, certain uORFs control translation of the main ORF in a peptide sequence-dependent manner. For genome-wide identification of such peptide sequence-dependent regulatory uORFs, exhaustive searches for uORFs with conserved amino acid sequences have been conducted using bioinformatic analyses. However, whether the conserved uORFs identified by these bioinformatic approaches encode regulatory peptides has not been experimentally determined. Here we analyzed 16 recently identified Arabidopsis thaliana conserved uORFs for the effects of their amino acid sequences on the expression of the main ORF using a transient expression assay. We identified five novel uORFs that repress main ORF expression in a peptide sequence-dependent manner. Mutational analysis revealed that, in four of them, the C-terminal region of the uORF-encoded peptide is critical for the repression of main ORF expression. Intriguingly, we also identified one exceptional sequence-dependent regulatory uORF, in which the stop codon position is not conserved and the C-terminal region is not important for the repression of main ORF expression.

Cancer diagnosis marker extraction for soft tissue sarcomas based on gene expression profiling data by using projective adaptive resonance theory (PART) filtering method

BackgroundRecent 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.ResultsPreviously, 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.ConclusionThe 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.

Construction of robust prognostic predictors by using projective adaptive resonance theory as a gene filtering method

MOTIVATION For establishing prognostic predictors of various diseases using DNA microarray analysis technology, it is desired to find selectively significant genes for constructing the prognostic model and it is also necessary to eliminate non-specific genes or genes with error before constructing the model. RESULTS We applied projective adaptive resonance theory (PART) to gene screening for DNA microarray data. Genes selected by PART were subjected to our FNN-SWEEP modeling method for the construction of a cancer class prediction model. The model performance was evaluated through comparison with a conventional screening signal-to-noise (S2N) method or nearest shrunken centroids (NSC) method. The FNN-SWEEP predictor with PART screening could discriminate classes of acute leukemia in blinded data with 97.1% accuracy and classes of lung cancer with 90.0% accuracy, while the predictor with S2N was only 85.3 and 70.0% or the predictor with NSC was 88.2 and 90.0%, respectively. The results have proven that PART was superior for gene screening. AVAILABILITY The software is available upon request from the authors. CONTACT honda@nubio.nagoya-u.ac.jp

The complex of ASYMMETRIC LEAVES (AS) proteins plays a central role in antagonistic interactions of genes for leaf polarity specification in Arabidopsis

Leaf primordia are born around meristem‐containing stem cells at shoot apices, grow along three axes (proximal–distal, adaxial–abaxial, medial–lateral), and develop into flat symmetric leaves with adaxial–abaxial polarity. Axis development and polarity specification of Arabidopsis leaves require a network of genes for transcription factor‐like proteins and small RNAs. Here, we summarize present understandings of adaxial‐specific genes, ASYMMETRIC LEAVES1 (AS1) and AS2. Their complex (AS1–AS2) functions in the regulation of the proximal–distal leaf length by directly repressing class 1 KNOX homeobox genes (BP, KNAT2) that are expressed in the meristem periphery below leaf primordia. Adaxial–abaxial polarity specification involves antagonistic interaction of adaxial and abaxial genes including AS1 and AS2 for the development of two respective domains. AS1–AS2 directly represses the abaxial gene ETTIN/AUXIN RESPONSE FACTOR3 (ETT/ARF3) and indirectly represses ETT/ARF3 and ARF4 through tasiR‐ARF. Modifier mutations have been identified that abolish adaxialization and enhance the defect in the proximal–distal patterning in as1 and as2. AS1–AS2 and its modifiers synergistically repress both ARFs and class 1 KNOXs. Repression of ARFs is critical for establishing adaxial–abaxial polarity. On the other hand, abaxial factors KANADI1 (KAN1) and KAN2 directly repress AS2 expression. These data delineate a molecular framework for antagonistic gene interactions among adaxial factors, AS1, AS2, and their modifiers, and the abaxial factors ARFs as key regulators in the establishment of adaxial–abaxial polarity. Possible AS1–AS2 epigenetic repression and activities downstream of ARFs are discussed. WIREs Dev Biol 2015, 4:655–671. doi: 10.1002/wdev.196

Prognostic predictor with multiple fuzzy neural models using expression profiles from DNA microarray for metastases of breast cancer

Gene expression profiling data from DNA microarray were analyzed using the fuzzy neural network (FNN) modeling method for predicting the distant metastases of breast cancer. The best model consisting of five genes was able to predict metastases of breast cancer with 94% accuracy. Furthermore, 100% accuracy was achieved by majoritarian decision using only 25 genes from five noninferior models which were constructed independently. From the constructed model, gene expression rules, which may cause distant metastases, were explicitly extracted and 60% of the metastases cases could be explained by this rule. The FNN modeling method described in this paper enables precise extraction of significant biological markers affecting prognosis without prior knowledge.

Knowledge-based Fuzzy Adaptive Resonance Theory and Its Application to the Analysis of Gene Expression in Plants

Gene expression data obtained from DNA microarrays are very useful in revealing the mechanisms that drive life. It is necessary to analyze these data through the use of algorithms, as in clustering and machine-learning. In a previous study, we developed fuzzy adaptive resonance theory (FuzzyART) and applied it to gene expression data, to identify genetic networks. FuzzyART was used as a clustering algorithm that is very suitable for the analysis of biological data; however, although FuzzyART is very useful in the analysis of dozens of gene expression profiles, it is difficult to apply this method to thousands of gene expression profiles, owing to inherent category proliferation and long calculation time. In the present study, we developed a knowledge-based FuzzyART (KB-FuzzyART) to mitigate these problems. We first constructed a gene list-1 from the gene database of Arabidopsis thaliana as knowledge for KB-FuzzyART, because KB-FuzzyART requires any knowledge as input. This method was applied to gene expression data obtained via the microarray analysis of A. thaliana, to identify the downstream genes of ASYMMETRIC LEAVES1 (AS1) and ASYMMETRIC LEAVES2 (AS2), both of which are involved in leaf development. The results of the analysis using KB-FuzzyART showed that the KNAT6 and YABBY5 (YAB5) genes are candidates for downstream factors, after a short calculation time for analysis. These results suggest that our gene list-1 is a very useful database for analyzing the expression profiles of genes that are related to the development of A. thaliana; they also suggest that the KB-FuzzyART has the high potential to function as a new method by which one can select candidate genes from thousands of genes, using gene expression data on mutant strains.