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Akademický článek

Prognosis prediction via histological evaluation of cellular heterogeneity in glioblastoma

Autor: Mari Kirishima, Seiya Yokoyama, Toshiaki Akahane, Nayuta Higa, Hiroyuki Uchida, Hajime Yonezawa, Kei Matsuo, Junkoh Yamamoto, Koji Yoshimoto, Ryosuke Hanaya, Akihide Tanimoto

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)

Abstract Glioblastomas (GBMs) are the most aggressive types of central nervous system tumors. Although certain genomic alterations have been identified as prognostic biomarkers of GBMs, the histomorphological features that predict their prognosis rem

Externí odkaz: https://doaj.org/article/ca1a6b39034b432fb711dd4038deb0be

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Akademický článek

Distribution and favorable prognostic implication of genomic EGFR alterations in IDH‐wildtype glioblastoma

Autor: Nayuta Higa, Toshiaki Akahane, Taiji Hamada, Hajime Yonezawa, Hiroyuki Uchida, Ryutaro Makino, Shoji Watanabe, Tomoko Takajo, Seiya Yokoyama, Mari Kirishima, Kei Matsuo, Shingo Fujio, Ryosuke Hanaya, Akihide Tanimoto, Koji Yoshimoto

Publikováno v: Cancer Medicine, Vol 12, Iss 1, Pp 49-60 (2023)

Abstract Background We aimed to evaluate the mutation profile, transcriptional variants, and prognostic impact of the epidermal growth factor receptor (EGFR) gene in isocitrate dehydrogenase (IDH)‐wildtype glioblastomas (GBMs). Methods We sequenced

Externí odkaz: https://doaj.org/article/4c6bd20f275d4736930ec1130baa61f2

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Akademický článek

Gallbladder microbiota composition is associated with pancreaticobiliary and gallbladder cancer prognosis

Autor: Mari Kirishima, Seiya Yokoyama, Kei Matsuo, Taiji Hamada, Michiko Shimokawa, Toshiaki Akahane, Tomoyuki Sugimoto, Hirohito Tsurumaru, Matsujiro Ishibashi, Yuko Mataki, Takao Ootsuka, Mitsuharu Nomoto, Chihiro Hayashi, Akihiko Horiguchi, Michiyo Higashi, Akihide Tanimoto

Publikováno v: BMC Microbiology, Vol 22, Iss 1, Pp 1-12 (2022)

Abstract Background The microbial population of the intestinal tract and its relationship to specific diseases has been extensively studied during the past decade. However, reports characterizing the bile microbiota are rare. This study aims to inves

Externí odkaz: https://doaj.org/article/3635136ddd324a79ae425cae022b3c01

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Akademický článek

An oncogenic splice variant of PDGFRα in adult glioblastoma as a therapeutic target for selective CDK4/6 inhibitors

Autor: Taiji Hamada, Toshiaki Akahane, Seiya Yokoyama, Nayuta Higa, Mari Kirishima, Kei Matsuo, Michiko Shimokawa, Koji Yoshimoto, Akihide Tanimoto

Publikováno v: Scientific Reports, Vol 12, Iss 1, Pp 1-12 (2022)

Abstract Understanding human genome alterations is necessary to optimize genome-based cancer therapeutics. However, some newly discovered mutations remain as variants of unknown significance (VUS). Here, the mutation c.1403A > G in exon 10 of the pla

Externí odkaz: https://doaj.org/article/6674d42c09f94f549df969b2710ed483

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Distribution and favorable prognostic implication of genomic EGFR alterations in IDH ‐wildtype glioblastoma

Publikováno v: Cancer Medicine. 12:49-60

We aimed to evaluate the mutation profile, transcriptional variants, and prognostic impact of the epidermal growth factor receptor (EGFR) gene in isocitrate dehydrogenase (IDH)-wildtype glioblastomas (GBMs).We sequenced EGFR, evaluated the EGFR splic

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c7a49443720c10914aa55dd3e41c7ff6
https://doi.org/10.1002/cam4.4939

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Supplementary figure 3 from Predicted Prognosis of Patients with Pancreatic Cancer by Machine Learning

Autor: Akihide Tanimoto, Michael A. Hollingsworth, Surinder K. Batra, Marko Kornmann, Suguru Yonezawa, Toshiaki Akahane, Tomoyuki Sugimoto, Tsubasa Hiraki, Michiko Horinouchi, Hiroshi Kurahara, Kosei Maemura, Kei Matsuo, Michiyo Higashi, Taiji Hamada, Seiya Yokoyama

Cox proportional hazard regression analysis on a comparison between Cluster 1 and other clusters as selected by cluster analysis of the methylation status of mucin genes MUC1, MUC2, and MUC4 in non-neoplastic regions (A) and neoplastic regions (B). R

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::842c1ae972b9022a3cc8c4e33644c085
https://doi.org/10.1158/1078-0432.22471671

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Supplementary figure 1 from Predicted Prognosis of Patients with Pancreatic Cancer by Machine Learning

Cox proportional hazard regression analysis on a comparison between Cluster 1 and Cluster 2 selected by cluster analysis of mRNA expression levels of MUC1, MUC2, and MUC4 in non-neoplastic regions (A) and neoplastic regions (B). Red solid line: Clust

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a832f500fcfe5351051267d048e5f85b
https://doi.org/10.1158/1078-0432.22471677

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Data from Predicted Prognosis of Patients with Pancreatic Cancer by Machine Learning

Purpose:Pancreatic cancer remains a disease of high mortality despite advanced diagnostic techniques. Mucins (MUC) play crucial roles in carcinogenesis and tumor invasion in pancreatic cancers. MUC1 and MUC4 expression are related to the aggressive b

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::275a3477b875f77fa3b8a32713218634
https://doi.org/10.1158/1078-0432.c.6527958

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