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A risk stratification model based on four novel biomarkers predicts prognosis for patients with renal cell carcinoma.
http://hdl.handle.net/10422/00012834
http://hdl.handle.net/10422/00012834e43a58c0-fd3a-4440-971f-6aa83fdb4467
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
s12957-020-02046-9 (4.4 MB)
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This article is licensed under a Creative Commons Attribution 4.0 International License,
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
| Item type | 学術雑誌論文 / Journal Article(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2020-11-06 | |||||
| タイトル | ||||||
| タイトル | A risk stratification model based on four novel biomarkers predicts prognosis for patients with renal cell carcinoma. | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | ADP-ribosylation factor-like 4C (ARL4C) | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Epithelial cell transforming 2 (ECT2) | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Global transcriptome analysis | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Multiple biomarkers | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Prognostic model | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Renal cell carcinoma (RCC) | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | STEAP3 metalloreductase (STEAP3) | |||||
| キーワード | ||||||
| 言語 | en | |||||
| 主題Scheme | Other | |||||
| 主題 | Superoxide dismutase 2 (SOD2) | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | journal article | |||||
| 著者 |
KUBOTA, Shigehisa
× KUBOTA, Shigehisa× Yoshida, Tetsuya× KAGEYAMA, Susumu× ISONO, Takahiro× YUASA, Takeshi× YONESE, Junji× KUSHIMA, Ryoji× KAWAUCHI, Akihiro× CHANO, Tokuhiro |
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| 著者別名 |
窪田, 成寿
× 窪田, 成寿× 吉田, 哲也× 影山, 進× 礒野, 高敬× 湯浅, 健× 九嶋, 亮治× 河内, 明宏× 茶野, 徳宏 |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | Background: Accurate prediction of the prognosis of RCC using a single biomarker is challenging due to the genetic heterogeneity of the disease. However, it is essential to develop an accurate system to allow better patient selection for optimal treatment strategies. ARL4C, ECT2, SOD2, and STEAP3 are novel molecular biomarkers identified in earlier studies as survival-related genes by comprehensive analyses of 43 primary RCC tissues and RCC cell lines. |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | Methods: To develop a prognostic model based on these multiple biomarkers, the expression of four biomarkers ARL4C, ECT2, SOD2, and STEAP3 in primary RCC tissue were semi-quantitatively investigated by immunohistochemical analysis in an independent cohort of 97 patients who underwent nephrectomy, and the clinical significance of these biomarkers were analyzed by survival analysis using Kaplan-Meier curves. The prognostic model was constructed by calculation of the contribution score to prognosis of each biomarker on Cox regression analysis, and its prognostic performance was validated. |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | Results: Patients whose tumors had high expression of the individual biomarkers had shorter cancer-specific survival (CSS) from the time of primary nephrectomy. The prognostic model based on four biomarkers segregated the patients into a high- and low-risk scored group according to defined cut-off value. This approach was more robust in predicting CSS compared to each single biomarker alone in the total of 97 patients with RCC. Especially in the 36 metastatic RCC patients, our prognostic model could more accurately predict early events within 2 years of diagnosis of metastasis. In addition, high risk-scored patients with particular strong SOD2 expression had a much worse prognosis in 25 patients with metastatic RCC who were treated with molecular targeting agents. |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | Conclusions: Our findings indicate that a prognostic model based on four novel biomarkers provides valuable data for prediction of clinical prognosis and useful information for considering the follow-up conditions and therapeutic strategies for patients with primary and metastatic RCC. |
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| 書誌情報 |
en : World Journal of Surgical Oncology 巻 18, 号 1, p. 270, 発行日 2020-10-22 |
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| 出版者 | ||||||
| 出版者 | BioMed Central Ltd | |||||
| ISSN | ||||||
| 収録物識別子タイプ | ISSN | |||||
| 収録物識別子 | 14777819 | |||||
| PMID | ||||||
| 関連タイプ | isIdenticalTo | |||||
| 識別子タイプ | PMID | |||||
| 関連識別子 | 33092599 | |||||
| PMCID | ||||||
| 識別子タイプ | URI | |||||
| 関連識別子 | http://www.ncbi.nlm.nih.gov/pmc/articles/pmc7584101/ | |||||
| 関連名称 | PMC7584101 | |||||
| DOI | ||||||
| 関連タイプ | isIdenticalTo | |||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | https://doi.org/10.1186/s12957-020-02046-9 | |||||
| 関連名称 | 10.1186/s12957-020-02046-9 | |||||
| 権利 | ||||||
| 権利情報 | © The Author(s). 2020 | |||||
| 著者版フラグ | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
| 資源タイプ | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | Journal Article | |||||
