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Articles by K Hotta
Total Records ( 2 ) for K Hotta
  O Tassy , D Dauga , F Daian , D Sobral , F Robin , P Khoueiry , D Salgado , V Fox , D Caillol , R Schiappa , B Laporte , A Rios , G Luxardi , T Kusakabe , J. S Joly , S Darras , L Christiaen , M Contensin , H Auger , C Lamy , C Hudson , U Rothbacher , M. J Gilchrist , K. W Makabe , K Hotta , S Fujiwara , N Satoh , Y Satou and P. Lemaire

Developmental biology aims to understand how the dynamics of embryonic shapes and organ functions are encoded in linear DNA molecules. Thanks to recent progress in genomics and imaging technologies, systemic approaches are now used in parallel with small-scale studies to establish links between genomic information and phenotypes, often described at the subcellular level. Current model organism databases, however, do not integrate heterogeneous data sets at different scales into a global view of the developmental program. Here, we present a novel, generic digital system, NISEED, and its implementation, ANISEED, to ascidians, which are invertebrate chordates suitable for developmental systems biology approaches. ANISEED hosts an unprecedented combination of anatomical and molecular data on ascidian development. This includes the first detailed anatomical ontologies for these embryos, and quantitative geometrical descriptions of developing cells obtained from reconstructed three-dimensional (3D) embryos up to the gastrula stages. Fully annotated gene model sets are linked to 30,000 high-resolution spatial gene expression patterns in wild-type and experimentally manipulated conditions and to 528 experimentally validated cis-regulatory regions imported from specialized databases or extracted from 160 literature articles. This highly structured data set can be explored via a Developmental Browser, a Genome Browser, and a 3D Virtual Embryo module. We show how integration of heterogeneous data in ANISEED can provide a system-level understanding of the developmental program through the automatic inference of gene regulatory interactions, the identification of inducing signals, and the discovery and explanation of novel asymmetric divisions.

  T Kawaguchi , M Sho , T Tojo , I Yamato , T Nomi , K Hotta , K Hamada , Y Suzaki , S Sugiura , K Kushibe , Y Nakajima and S. Taniguchi

Prostate stem cell antigen was originally identified as an overexpressed gene in prostate cancer and its overexpression correlated with disease progression and prognosis. In this study, we investigated the clinical significance and therapeutic potential of prostate stem cell antigen expression in non-small cell lung cancer.


Prostate stem cell antigen expression was examined by immunohistochemistry in 97 primary tumors and 21 metastatic lymph nodes from non-small cell lung cancer patients who underwent curative resection from January 2001 through March 2003. Therapeutic potential of targeting prostate stem cell antigen was further examined by small interfering RNA method using human lung cancer cell line (A549).


Prostate stem cell antigen protein expression was detected in 94 of 97 primary lesions (97%) and all metastatic lymph nodes. Prostate stem cell antigen expression intensity was positively correlated with advanced pathological T-factor and stage (T1 vs. T2–4, P = 0.014; Stage I vs. Stages II–IV, P = 0.029, respectively). The prognosis of patients with low prostate stem cell antigen expression was significantly better than those with high prostate stem cell antigen expression (5-year disease-free survival rate; 90% vs. 53%, P = 0.001). Finally, small interfering RNA-mediated knockdown of prostate stem cell antigen resulted in the inhibition of lung cancer cell growth.


Prostate stem cell antigen is highly expressed in non-small cell lung cancer and may be functionally important for this fatal disease.

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