-
[show abstract]
[hide abstract]
ABSTRACT: We designed a study to investigate genetic relationships between primary tumors of oral squamous cell carcinoma (OSCC) and their lymph node metastases, and to identify genomic copy number aberrations (CNAs) related to lymph node metastasis. For this purpose, we collected a total of 42 tumor samples from 25 patients and analyzed their genomic profiles by array-based comparative genomic hybridization. We then compared the genetic profiles of metastatic primary tumors (MPTs) with their paired lymph node metastases (LNMs), and also those of LNMs with non-metastatic primary tumors (NMPTs). Firstly, we found that although there were some distinctive differences in the patterns of genomic profiles between MPTs and their paired LNMs, the paired samples shared similar genomic aberration patterns in each case. Unsupervised hierarchical clustering analysis grouped together 12 of the 15 MPT-LNM pairs. Furthermore, similarity scores between paired samples were significantly higher than those between non-paired samples. These results suggested that MPTs and their paired LNMs are composed predominantly of genetically clonal tumor cells, while minor populations with different CNAs may also exist in metastatic OSCCs. Secondly, to identify CNAs related to lymph node metastasis, we compared CNAs between grouped samples of MPTs and LNMs, but were unable to find any CNAs that were more common in LNMs. Finally, we hypothesized that subpopulations carrying metastasis-related CNAs might be present in both the MPT and LNM. Accordingly, we compared CNAs between NMPTs and LNMs, and found that gains of 7p, 8q and 17q were more common in the latter than in the former, suggesting that these CNAs may be involved in lymph node metastasis of OSCC. In conclusion, our data suggest that in OSCCs showing metastasis, the primary and metastatic tumors share similar genomic profiles, and that cells in the primary tumor may tend to metastasize after acquiring metastasis-associated CNAs.
PLoS ONE 01/2013; 8(2):e56165. · 4.09 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: We propose a computationally efficient method for cross-validation of the Support Vector Regression (SVR) by generalizing
the decremental algorithm of SVR. Incremental and decremental algorithm of Support Vector Machines (SVM) 2, 8, 9) efficiently update the trained SVM model when a single data point is added to or removed from the training set. The computational
cost of leave-one-out cross-validation can be reduced using the decremental algorithm. However, when we perform leave-m-out cross-validation (m >1), we have to repeatedly apply the decremental algorithm for each data point. In this paper, we extend the decremental
algorithm of SVR8, 9) in such a way that several data points can be removed more efficiently. Experimental results indicate that the proposed approach
can reduce the computational cost. In particular, we observed that the number of breakpoints, which is the main computational
cost of the involved path-following, were reduced from O(m){\mathcal O}(m) to O(Öm){\mathcal O}(\sqrt{m}).
New Generation Computing 04/2012; 27(4):307-318. · 0.94 Impact Factor
-
Keiko Matsuura,
Chisato Nakada,
Mizuho Mashio,
Takahiro Narimatsu,
Taichiro Yoshimoto,
Masato Tanigawa,
Yoshiyuki Tsukamoto,
Naoki Hijiya, Ichiro Takeuchi,
Takeo Nomura,
Fuminori Sato,
Hiromitsu Mimata,
Masao Seto,
Masatsugu Moriyama
[show abstract]
[hide abstract]
ABSTRACT: Clinical outcome of patients with high-grade ccRCC (clear cell renal cell carcinoma) remains still poor despite recent advances in treatment strategies. Molecular mechanism of pathogenesis in developing high-grade ccRCC must be clarified. In the present study, we found that SAV1 was significantly downregulated with copy number loss in high-grade ccRCCs. Therefore, we investigated the SAV1 function on cell proliferation and apoptosis in vitro. Furthermore, we attempted to clarify the downstream signaling which is regulated by SAV1.
We performed array CGH and gene expression analysis of 8 RCC cell lines (786-O, 769-P, KMRC-1, KMRC-2, KMRC-3, KMRC-20, TUHR4TKB, and Caki-2), and expression level of mRNA was confirmed by quantitative RT-PCR (qRT-PCR) analysis. We next re-expressed SAV1 in 786-O cells, and analyzed its colony-forming activity. Then, we transfected siRNAs of SAV1 into the kidney epithelial cell line HK2 and renal proximal tubule epithelial cells (RPTECs), and analyzed their proliferation and apoptosis. Furthermore, the activity of YAP1, which is a downstream molecule of SAV1, was evaluated by western blot analysis, reporter assay and immunohistochemical analysis.
We found that SAV1, a component of the Hippo pathway, is frequently downregulated in high-grade ccRCC. SAV1 is located on chromosome 14q22.1, where copy number loss had been observed in 7 of 12 high-grade ccRCCs in our previous study, suggesting that gene copy number loss is responsible for the downregulation of SAV1. Colony-forming activity by 786-O cells, which show homozygous loss of SAV1, was significantly reduced when SAV1 was re-introduced exogenously. Knockdown of SAV1 promoted proliferation of HK2 and RPTEC. Although the phosphorylation level of YAP1 was low in 786-O cells, it was elevated in SAV1-transduced 786-O cells. Furthermore, the transcriptional activity of the YAP1 and TEAD3 complex was inhibited in SAV1-transduced 786-O cells. Immunohistochemistry frequently demonstrated nuclear localization of YAP1 in ccRCC cases with SAV1 downregulation, and it was preferentially detected in high-grade ccRCC.
Taken together, downregulation of SAV1 and the consequent YAP1 activation are involved in the pathogenesis of high-grade ccRCC. It is an attractive hypothesis that Hippo signaling could be candidates for new therapeutic target.
BMC Cancer 12/2011; 11:523. · 3.01 Impact Factor
-
Kennosuke Karube,
Masao Nakagawa,
Shinobu Tsuzuki, Ichiro Takeuchi,
Keiichiro Honma,
Yasuhiro Nakashima,
Norio Shimizu,
Young-Hyeh Ko,
Yasuo Morishima,
Koichi Ohshima,
Shigeo Nakamura,
Masao Seto
[show abstract]
[hide abstract]
ABSTRACT: Oligo-array comparative genomic hybridization (CGH) and gene-expression profiling of natural killer (NK)-cell neoplasms were used in an effort to delineate the molecular pathogenesis involved. Oligo-array CGH identified two 6q21 regions that were most frequently deleted (14 of 39 or 36%). One of these regions included POPDC3, PREP, PRDM1, ATG5, and AIM1, whereas the other included LACE1 and FOXO3. All genes located in these regions, except for POPDC3 and AIM1, were down-regulated in neoplastic samples, as determined by gene-expression analysis, and were therefore considered to be candidate tumor-suppressor genes. A20 and HACE1, the well-known tumor-suppressor genes located on 6q21-23, were included as candidate genes because they also demonstrated frequent genomic deletions and down-regulated expression. The Tet-Off NK cell line NKL was subsequently established for functional analyses. Seven candidate genes were transduced into Tet-Off NKL and forced re-expression was induced. Re-expression of FOXO3 and PRDM1 suppressed NKL proliferation, but this was not the case after re-expression of the other genes. This effect was confirmed using another NK cell line, SNK10. Furthermore, genomic analyses detected nonsense mutations of PRDM1 that led to functional inactivation in one cell line and one clinical sample. PRDM1 and FOXO3 are considered to play an important role in the pathogenesis of NK-cell neoplasms.
Blood 06/2011; 118(12):3195-204. · 9.90 Impact Factor
-
Akiko Kuroda,
Yoshiyuki Tsukamoto,
Lam Tung Nguyen,
Tsuyoshi Noguchi, Ichiro Takeuchi,
Masahiro Uchida,
Tomohisa Uchida,
Naoki Hijiya,
Chisato Nakada,
Tadayoshi Okimoto,
Masaaki Kodama,
Kazunari Murakami,
Keiko Matsuura,
Masao Seto,
Hisao Ito,
Toshio Fujioka,
Masatsugu Moriyama
[show abstract]
[hide abstract]
ABSTRACT: Genomic copy number aberrations (CNAs) in gastric cancer have already been extensively characterized by array comparative genomic hybridization (array CGH) analysis. However, involvement of genomic CNAs in the process of submucosal invasion and lymph node metastasis in early gastric cancer is still poorly understood. In this study, to address this issue, we collected a total of 59 tumor samples from 27 patients with submucosal-invasive gastric cancers (SMGC), analyzed their genomic profiles by array CGH, and compared them between paired samples of mucosal (MU) and submucosal (SM) invasion (23 pairs), and SM invasion and lymph node (LN) metastasis (9 pairs). Initially, we hypothesized that acquisition of specific CNA(s) is important for these processes. However, we observed no significant difference in the number of genomic CNAs between paired MU and SM, and between paired SM and LN. Furthermore, we were unable to find any CNAs specifically associated with SM invasion or LN metastasis. Among the 23 cases analyzed, 15 had some similar pattern of genomic profiling between SM and MU. Interestingly, 13 of the 15 cases also showed some differences in genomic profiles. These results suggest that the majority of SMGCs are composed of heterogeneous subpopulations derived from the same clonal origin. Comparison of genomic CNAs between SMGCs with and without LN metastasis revealed that gain of 11q13, 11q14, 11q22, 14q32 and amplification of 17q21 were more frequent in metastatic SMGCs, suggesting that these CNAs are related to LN metastasis of early gastric cancer. In conclusion, our data suggest that generation of genetically distinct subclones, rather than acquisition of specific CNA at MU, is integral to the process of submucosal invasion, and that subclones that acquire gain of 11q13, 11q14, 11q22, 14q32 or amplification of 17q21 are likely to become metastatic.
PLoS ONE 01/2011; 6(7):e22313. · 4.09 Impact Factor
-
International Joint Conference on Neural Networks, IJCNN 2010, Barcelona, Spain, 18-23 July, 2010; 01/2010
-
International Joint Conference on Neural Networks, IJCNN 2010, Barcelona, Spain, 18-23 July, 2010; 01/2010
-
Masahiro Uchida,
Yoshiyuki Tsukamoto,
Tomohisa Uchida,
Yuta Ishikawa,
Takayuki Nagai,
Naoki Hijiya,
Lam Tung Nguyen,
Chisato Nakada,
Akiko Kuroda,
Tadayoshi Okimoto,
Masaaki Kodama,
Kazunari Murakami,
Tsuyoshi Noguchi,
Keiko Matsuura,
Masato Tanigawa,
Masao Seto,
Hisao Ito,
Toshio Fujioka, Ichiro Takeuchi,
Masatsugu Moriyama
[show abstract]
[hide abstract]
ABSTRACT: Although genomic copy number aberrations (CNAs) of gastric carcinoma at the advanced stage have already been extensively characterized by array comparative genomic hybridization (array CGH) analysis, those of gastric carcinoma in situ (CIS) are still poorly understood. Furthermore, no reports have demonstrated correlations between CNAs and histopathological features of gastric adenoma. In this study, we investigated CNAs of 20 gastric CISs (Vienna category 4.2) and 20 adenomas including seven low-grade adenomas (LGA; Vienna category 3) and 13 high-grade adenomas (HGA; Vienna category 4.1), using oligonucleotide-based array CGH. The most frequent aberrations in CIS were gains at 8q (85%) and 20q (50%), and losses at 5q (50%) and 17p (50%), suggesting that these CNAs are involved in the development of CIS. We found that the pattern of CNAs in HGA was quite different from that in LGA. The most frequent CNAs in HGA were gains at 8q (62%) and 7pq (54%), whereas those in LGA were gain at 7q21.3-q22.1 (57%) and loss at 5q (43%). Interestingly, gains at 8q and 7pq, both of which occurred most frequently in HGA, were not detected in any cases of LGA. Of note, 8q gain was detected most frequently in both HGA and CIS but was undetected in LGA. Since HGA is believed to have a higher risk of progression to invasive carcinoma than LGA, these data suggest that 8q gain is important for the malignant transformation of gastric adenoma.
The Journal of Pathology 01/2010; 221(1):96-105. · 6.32 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: In many microarray studies, gene set selection is an important preliminary step for subsequent main task such as tumor classification, cancer subtype identification, etc. In this paper, we investigate the possibility of using metric learning as an alternative to gene set selection. We develop a simple metric learning algorithm aiming to use it for microarray data analysis. Exploiting a property of the algorithm, we introduce a novel approach for extending the metric learning to be adaptive. We apply the algorithm to previously studied microarray data on malignant lymphoma subtype identification.
Journal of Physics Conference Series 12/2009; 197(1):012008.
-
[show abstract]
[hide abstract]
ABSTRACT: Gaussian mixture model (GMM) is widely used in many applications because it can approximate various forms of probability distributions. In this paper, we are concerned with GMM estimation problem using the variational Bayes (VB) method. In this approach, one can only find local optima because the free energy function of the problem is multimodal. In order to find better solutions, deterministic annealing was recently adapted to the VB method (DAVB method). In this paper, we offer an alternative approach to the DAVB method for GMM estimation problem. We propose a multi-directional search method from the primitive initial point (PIP), which is defined as the solution of the DAVB method at the highest temperature. Investigation on the curvature information of the original (not annealed) free energy function reveals that the PIP is a saddle point. An efficient multi-directional search strategy from the neighborhoods of the PIP is proposed using the eigen-analysis of the Hessian matrix. Numerical experiments using real data sets demonstrate the effectiveness of our method.
Neural networks: the official journal of the International Neural Network Society 09/2009; 23(3):356-64. · 1.88 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: Peripheral T-cell lymphoma, unspecified (PTCL-U) comprises histopathologically and clinically heterogeneous groups. The purpose of this study was to identify subgroups with distinct genetic, histopathologic, and prognostic features.
We used array comparative genomic hybridization (CGH) for high-resolution analysis of 51 PTCL-U patients and the array data for examining possible correlations of histopathologic and clinical features. Moreover, we compared the genetic, histopathologic, and prognostic features of the PTCL-U cases with those of 59 cases of lymphoma-type adult T-cell leukemia/lymphoma (ATLL).
We identified 32 regions with frequent genomic imbalance, 1 region with high copy number gain at 14q32.2, and 1 region with homozygous loss at 9p21.3. Gains of 7p and 7q and loss of 9p21.3 showed a significant association with poor prognosis. PTCL-U cases with genomic imbalance showed distinct histopathologic and prognostic features compared with such cases without alteration and a marked genetic, histopathologic, and prognostic resemblance to lymphoma-type ATLL.
The array CGH enabled us to identify the frequently altered genomic regions with strong prognostic power among PTCL-U cases. A correlative analysis using the array CGH data disclosed a subgroup in PTCL-U with genomic alterations and with histopathologic and clinical relevance. In addition to histopathologic similarity, the strong genetic and prognostic resemblance between PTCL-U cases with genomic imbalance detected by array CGH and lymphoma-type ATLL seems to support the notion that the former may constitute a distinct PTCL-U subgroup.
Clinical Cancer Research 02/2009; 15(1):30-8. · 7.74 Impact Factor
-
New Generation Comput. 01/2009; 27:307-318.
-
Neural Information Processing, 16th International Conference, ICONIP 2009, Bangkok, Thailand, December 1-5, 2009, Proceedings, Part I; 01/2009
-
Neural Information Processing, 16th International Conference, ICONIP 2009, Bangkok, Thailand, December 1-5, 2009, Proceedings, Part I; 01/2009
-
[show abstract]
[hide abstract]
ABSTRACT: The differentiation of biologically and clinically different malignant lymphoma diseases or subtypes is crucial because it leads to better prognostication and therapeutic decision-making. Attempts have been made at subtype classification for diagnosing lymphomas on the basis of gene-expression profiling. Although array-based comparative genomic hybridization (array CGH) has identified a characteristic genomic alteration pattern for each disease entity, it has not been clear whether each patient with certain genomic alterations can be classified by array CGH data.
Data on copy number gains and losses for 46 diffuse large B-cell lymphomas and 29 mantle cell lymphomas were used. The gene expressions of the diffuse large B-cell lymphomas cases were profiled and hierarchical clustering revealed that 28 of them were of the activated B-cell type and 18 were of the germinal center-B-cell type. Using these data, we developed a computer algorithm to classify lymphoma diseases or subtypes on the basis of copy number gains and losses.
The method correctly classified 88% of the diffuse large B-cell lymphomas and mantle cell lymphomas, and 83% of the activated B-cell and germinal center-B-cell subtypes. These results demonstrate that copy number gains and losses detected by array CGH can be used for classifying lymphomas into biologically and clinically distinct diseases or subtypes.
Our computer algorithm based on array CGH data successfully classified diffuse large B-cell lymphomas and mantle cell lymphomas and activated B-cell and germinal center-B-cell subtypes with high accuracy. An important finding is that the regions automatically identified by the computer algorithm were located in the critical regions that are likely to be involved in the development of lymphoma.
Haematologica 12/2008; 94(1):61-9. · 6.42 Impact Factor
-
Knowledge-Based Intelligent Information and Engineering Systems, 12th International Conference, KES 2008, Zagreb, Croatia, September 3-5, 2008, Proceedings, Part III; 01/2008
-
[show abstract]
[hide abstract]
ABSTRACT: Approximately 70% of gastric mucosa-associated lymphoid tissue (MALT) lymphomas can be successfully treated with H. pylori eradication. The translocation t(11;18)(q21;q21) characteristic of MALT lymphoma is recognized as a marker for H. pylori independency, but this marker is found in only a half of the MALT lymphomas resistant to H. pylori eradication. Detailed analyses of the genomic features of eradication resistant as well as responsive groups are important for understanding their molecular basis. We performed array-based comparative genomic hybridization (array-CGH) for 29 gastric MALT lymphomas treated with H. pylori eradication. These comprised ten cases of t(11;18) positive MALT, nine cases of t(11;18) negative MALT with H. pylori dependency, and ten cases of t(11;18) negative MALT with H. pylori independency. Array-CGH analysis demonstrated that no significant genetic alterations were found in t(11;18) positive MALT lymphomas, but numerous genomic alterations were detected in t(11;18) negative MALT lymphomas. Many of these alterations were similar to those found in diffuse large B-cell lymphoma with trisomy 3 being the most recurrent alteration. Within the t(11;18) negative MALT lymphoma without large cell components group, genomic imbalances occurred more frequently in the H. pylori independent than in the H. pylori dependent group (P = 0.02). Genomic imbalances are associated with H. pylori independency in t(11;18) negative gastric MALT lymphomas. They may thus play an important role in the development of H. pylori independency.
Genes Chromosomes and Cancer 09/2007; 46(8):784-90. · 3.31 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: Gaussian mixture model (GMM) is one of the important models to approximate probability distributions. There are various methods
for Gaussian mixture estimation such as the EM algorithm, sampling method, and the Bayes method. In this paper, we are concerned
with the Gaussian mixture estimation problem using the variational Bayes (VB), which is an approximation of the Bayes method.
In the VB, it is important to choose its initial values carefully since the objective function of the problem is multimodal.
In this paper, we propose a method which employs primitive initial point (PIP) as an initial value of the VB and performs multi-directional search from the PIP. We present the motivation and rationale
of our method and demonstrate its effectiveness through numerical experiments using real data sets.
KeywordsGaussian mixture estimation-variational Bayes-primitive initial point-deterministic annealing
01/1970: pages 159-166;
