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A Panel of MicroRNA Signature as a Tool for Predicting Survival of Patients with Urothelial Carcinoma of the Bladder

Introduction and Objectives. MicroRNA (miRNA) expression is altered in urologic malignancies, including urothelial carcinoma of the bladder (UCB). Individual miRNAs have been shown to modulate multiple signaling pathways that contribute to BC. To identify a panel of miRNA signature that can predict...

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Published in:Disease markers 2018-01, Vol.2018 (2018), p.1-6
Main Authors: Saito, Kenkichi, Tanda, Naoki, Minami, Koichiro, Hirano, Hajime, Nomi, Hayahito, Kato, Ryuji, Hayashi, Tetsuya, Azuma, Haruhito, Uchimoto, Taizo, Takai, Tomoaki, Takahara, Kiyoshi, Komura, Kazumasa, Ibuki, Naokazu, Akao, Yukihiro, Uehara, Hirofumi, Inamoto, Teruo, Yoshikawa, Yuki
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cites cdi_FETCH-LOGICAL-c499t-4cc64ff8985f0b79e5ecec448ae1b42cbd416a6e1bd09d0ab70e69e85b1d32883
container_end_page 6
container_issue 2018
container_start_page 1
container_title Disease markers
container_volume 2018
creator Saito, Kenkichi
Tanda, Naoki
Minami, Koichiro
Hirano, Hajime
Nomi, Hayahito
Kato, Ryuji
Hayashi, Tetsuya
Azuma, Haruhito
Uchimoto, Taizo
Takai, Tomoaki
Takahara, Kiyoshi
Komura, Kazumasa
Ibuki, Naokazu
Akao, Yukihiro
Uehara, Hirofumi
Inamoto, Teruo
Yoshikawa, Yuki
description Introduction and Objectives. MicroRNA (miRNA) expression is altered in urologic malignancies, including urothelial carcinoma of the bladder (UCB). Individual miRNAs have been shown to modulate multiple signaling pathways that contribute to BC. To identify a panel of miRNA signature that can predict aggressive phenotype from normal nonaggressive counterpart using miRNA expression levels and to assess the prognostic value of this specific miRNA markers in patients with UCB. Methods. To determine candidate miRNAs as prognostic biomarkers for dividing aggressive type of UCB, miRNA expression was profiled in patients’ samples with an aggressive phenotype or nonaggressive phenotype using 3D-Gene miRNA labeling kit (Toray, Japan). To create a prognostic index model, we used the panel of 9-miRNA signature based on Cancer Genome Atlas (TCGA) data portal (TCGA Data Portal (https://tcgadata.nci.nih.gov/tcga/tcgaHome2.jsp)). miRNA expression data and corresponding clinical data, including outcome and staging information of 84 UCB patients, were obtained. The Kaplan-Meier and log-rank test were performed to quantify the survival functions in two groups. Results. Deregulation of nine miRNAs (hsa-miR-99a-5p, hsa-miR-100-5p, hsa-miR-125b-5p, hsa-miR-145-5p, hsa-miR-4324, hsa-miR-34b-5p, hsa-miR-29c-3p, hsa-miR-135a-3p, and hsa-miR-33b-3p) was determined in UCB patients with aggressive phenotype compared with nonaggressive subject. To validate the prognostic power of the nine-signature miRNAs using the TCGA dataset of bladder cancer, the survival status and tumor miRNA expression of all 84 TCGA UCB patients were ranked according to the prognostic score values. Of nine miRNAs, six were associated with high risk (hsa-miR-99a-5p, hsa-miR-100-5p, hsa-miR-125b-5p, hsa-miR-4324, hsa-miR-34b-5p, and hsa-miR-135a-3p) and three were shown to be protective (hsa-miR-145-5p, hsa-miR-29c-3p, and hsa-miR-33b-3p). Patients with the high-risk miRNA signature exhibited poorer OS than patients expressing the low-risk miRNA profile (HR = 7.05, p
doi_str_mv 10.1155/2018/5468672
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MicroRNA (miRNA) expression is altered in urologic malignancies, including urothelial carcinoma of the bladder (UCB). Individual miRNAs have been shown to modulate multiple signaling pathways that contribute to BC. To identify a panel of miRNA signature that can predict aggressive phenotype from normal nonaggressive counterpart using miRNA expression levels and to assess the prognostic value of this specific miRNA markers in patients with UCB. Methods. To determine candidate miRNAs as prognostic biomarkers for dividing aggressive type of UCB, miRNA expression was profiled in patients’ samples with an aggressive phenotype or nonaggressive phenotype using 3D-Gene miRNA labeling kit (Toray, Japan). To create a prognostic index model, we used the panel of 9-miRNA signature based on Cancer Genome Atlas (TCGA) data portal (TCGA Data Portal (https://tcgadata.nci.nih.gov/tcga/tcgaHome2.jsp)). miRNA expression data and corresponding clinical data, including outcome and staging information of 84 UCB patients, were obtained. The Kaplan-Meier and log-rank test were performed to quantify the survival functions in two groups. Results. Deregulation of nine miRNAs (hsa-miR-99a-5p, hsa-miR-100-5p, hsa-miR-125b-5p, hsa-miR-145-5p, hsa-miR-4324, hsa-miR-34b-5p, hsa-miR-29c-3p, hsa-miR-135a-3p, and hsa-miR-33b-3p) was determined in UCB patients with aggressive phenotype compared with nonaggressive subject. To validate the prognostic power of the nine-signature miRNAs using the TCGA dataset of bladder cancer, the survival status and tumor miRNA expression of all 84 TCGA UCB patients were ranked according to the prognostic score values. Of nine miRNAs, six were associated with high risk (hsa-miR-99a-5p, hsa-miR-100-5p, hsa-miR-125b-5p, hsa-miR-4324, hsa-miR-34b-5p, and hsa-miR-135a-3p) and three were shown to be protective (hsa-miR-145-5p, hsa-miR-29c-3p, and hsa-miR-33b-3p). Patients with the high-risk miRNA signature exhibited poorer OS than patients expressing the low-risk miRNA profile (HR = 7.05, p&lt;0.001). Conclusions. The miRNA array identified nine dysregulated miRNAs from clinical samples. This panel of nine-miRNA signature provides predictive and prognostic value of patients with UCB.</description><identifier>ISSN: 0278-0240</identifier><identifier>EISSN: 1875-8630</identifier><identifier>DOI: 10.1155/2018/5468672</identifier><identifier>PMID: 30026881</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Aged ; Aged, 80 and over ; Biomarkers ; Biomarkers, Tumor - genetics ; Biomarkers, Tumor - metabolism ; Bladder ; Bladder cancer ; Cancer ; Cancer therapies ; Carcinoma ; Carcinoma - genetics ; Carcinoma - metabolism ; Carcinoma - pathology ; Chemotherapy ; Deregulation ; Genetic aspects ; Genomes ; Genomics ; Humans ; HyperText Markup Language ; Male ; Medical prognosis ; Medical research ; Medicine ; Medicine, Experimental ; Metastasis ; MicroRNA ; MicroRNAs ; MicroRNAs - genetics ; MicroRNAs - metabolism ; miRNA ; Patient outcomes ; Patients ; Phenotypes ; Prognosis ; Rank tests ; Ribonucleic acid ; Risk ; RNA ; Servers ; Survival ; Survival Analysis ; Systematic review ; Transcriptome ; Urinary Bladder Neoplasms - genetics ; Urinary Bladder Neoplasms - metabolism ; Urinary Bladder Neoplasms - pathology ; Urothelial carcinoma ; Urothelium - metabolism ; Urothelium - pathology ; Web portals</subject><ispartof>Disease markers, 2018-01, Vol.2018 (2018), p.1-6</ispartof><rights>Copyright © 2018 Teruo Inamoto et al.</rights><rights>COPYRIGHT 2018 John Wiley &amp; Sons, Inc.</rights><rights>Copyright © 2018 Teruo Inamoto et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. http://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2018 Teruo Inamoto et al. 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c499t-4cc64ff8985f0b79e5ecec448ae1b42cbd416a6e1bd09d0ab70e69e85b1d32883</citedby><cites>FETCH-LOGICAL-c499t-4cc64ff8985f0b79e5ecec448ae1b42cbd416a6e1bd09d0ab70e69e85b1d32883</cites><orcidid>0000-0002-1351-1315</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30026881$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Miyamoto, Hiroshi</contributor><contributor>Hiroshi Miyamoto</contributor><creatorcontrib>Saito, Kenkichi</creatorcontrib><creatorcontrib>Tanda, Naoki</creatorcontrib><creatorcontrib>Minami, Koichiro</creatorcontrib><creatorcontrib>Hirano, Hajime</creatorcontrib><creatorcontrib>Nomi, Hayahito</creatorcontrib><creatorcontrib>Kato, Ryuji</creatorcontrib><creatorcontrib>Hayashi, Tetsuya</creatorcontrib><creatorcontrib>Azuma, Haruhito</creatorcontrib><creatorcontrib>Uchimoto, Taizo</creatorcontrib><creatorcontrib>Takai, Tomoaki</creatorcontrib><creatorcontrib>Takahara, Kiyoshi</creatorcontrib><creatorcontrib>Komura, Kazumasa</creatorcontrib><creatorcontrib>Ibuki, Naokazu</creatorcontrib><creatorcontrib>Akao, Yukihiro</creatorcontrib><creatorcontrib>Uehara, Hirofumi</creatorcontrib><creatorcontrib>Inamoto, Teruo</creatorcontrib><creatorcontrib>Yoshikawa, Yuki</creatorcontrib><title>A Panel of MicroRNA Signature as a Tool for Predicting Survival of Patients with Urothelial Carcinoma of the Bladder</title><title>Disease markers</title><addtitle>Dis Markers</addtitle><description>Introduction and Objectives. MicroRNA (miRNA) expression is altered in urologic malignancies, including urothelial carcinoma of the bladder (UCB). Individual miRNAs have been shown to modulate multiple signaling pathways that contribute to BC. To identify a panel of miRNA signature that can predict aggressive phenotype from normal nonaggressive counterpart using miRNA expression levels and to assess the prognostic value of this specific miRNA markers in patients with UCB. Methods. To determine candidate miRNAs as prognostic biomarkers for dividing aggressive type of UCB, miRNA expression was profiled in patients’ samples with an aggressive phenotype or nonaggressive phenotype using 3D-Gene miRNA labeling kit (Toray, Japan). To create a prognostic index model, we used the panel of 9-miRNA signature based on Cancer Genome Atlas (TCGA) data portal (TCGA Data Portal (https://tcgadata.nci.nih.gov/tcga/tcgaHome2.jsp)). miRNA expression data and corresponding clinical data, including outcome and staging information of 84 UCB patients, were obtained. The Kaplan-Meier and log-rank test were performed to quantify the survival functions in two groups. Results. Deregulation of nine miRNAs (hsa-miR-99a-5p, hsa-miR-100-5p, hsa-miR-125b-5p, hsa-miR-145-5p, hsa-miR-4324, hsa-miR-34b-5p, hsa-miR-29c-3p, hsa-miR-135a-3p, and hsa-miR-33b-3p) was determined in UCB patients with aggressive phenotype compared with nonaggressive subject. To validate the prognostic power of the nine-signature miRNAs using the TCGA dataset of bladder cancer, the survival status and tumor miRNA expression of all 84 TCGA UCB patients were ranked according to the prognostic score values. Of nine miRNAs, six were associated with high risk (hsa-miR-99a-5p, hsa-miR-100-5p, hsa-miR-125b-5p, hsa-miR-4324, hsa-miR-34b-5p, and hsa-miR-135a-3p) and three were shown to be protective (hsa-miR-145-5p, hsa-miR-29c-3p, and hsa-miR-33b-3p). Patients with the high-risk miRNA signature exhibited poorer OS than patients expressing the low-risk miRNA profile (HR = 7.05, p&lt;0.001). Conclusions. The miRNA array identified nine dysregulated miRNAs from clinical samples. 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genetics</subject><subject>MicroRNAs - metabolism</subject><subject>miRNA</subject><subject>Patient outcomes</subject><subject>Patients</subject><subject>Phenotypes</subject><subject>Prognosis</subject><subject>Rank tests</subject><subject>Ribonucleic acid</subject><subject>Risk</subject><subject>RNA</subject><subject>Servers</subject><subject>Survival</subject><subject>Survival Analysis</subject><subject>Systematic review</subject><subject>Transcriptome</subject><subject>Urinary Bladder Neoplasms - genetics</subject><subject>Urinary Bladder Neoplasms - metabolism</subject><subject>Urinary Bladder Neoplasms - pathology</subject><subject>Urothelial carcinoma</subject><subject>Urothelium - metabolism</subject><subject>Urothelium - pathology</subject><subject>Web portals</subject><issn>0278-0240</issn><issn>1875-8630</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNqNkc1vEzEQxS0EomngxhlZ4kiX2l7b670ghYgvqUBE27M1651NXG3WxetNxX-PQ0ILN06jmfnN09M8Ql5w9oZzpc4F4-ZcSW10JR6RGTeVKowu2WMyY6IyBROSnZDTcbxhjIta1k_JScmY0MbwGUkLuoIBexo6-sW7GL5_XdBLvx4gTREpjBToVQg97UKkq4itd8kPa3o5xZ3fwe-7FSSPQxrpnU8beh1D2mDv824J0fkhbGFP5SF910PbYnxGnnTQj_j8WOfk-sP7q-Wn4uLbx8_LxUXhZF2nQjqnZdeZ2qiONVWNCh06KQ0gb6RwTSu5Bp2bltUtg6ZiqGs0quFtKYwp5-TtQfd2arbYumwyQm9vo99C_GkDePvvZvAbuw47q1nJWX7inLw6CsTwY8Ix2ZswxSF7toJpYbhhlXqg1tCj9UMXspjb-tHZhTKVVspomamzA5WfPI4Ru3sfnNl9knafpD0mmfGXf3u_h_9El4HXB2Djhxbu_H_KYWawgweaq1KWVfkLlCWv2w</recordid><startdate>20180101</startdate><enddate>20180101</enddate><creator>Saito, Kenkichi</creator><creator>Tanda, Naoki</creator><creator>Minami, Koichiro</creator><creator>Hirano, Hajime</creator><creator>Nomi, Hayahito</creator><creator>Kato, Ryuji</creator><creator>Hayashi, Tetsuya</creator><creator>Azuma, Haruhito</creator><creator>Uchimoto, Taizo</creator><creator>Takai, Tomoaki</creator><creator>Takahara, Kiyoshi</creator><creator>Komura, Kazumasa</creator><creator>Ibuki, Naokazu</creator><creator>Akao, Yukihiro</creator><creator>Uehara, Hirofumi</creator><creator>Inamoto, Teruo</creator><creator>Yoshikawa, Yuki</creator><general>Hindawi Publishing Corporation</general><general>Hindawi</general><general>John Wiley &amp; Sons, Inc</general><general>Hindawi Limited</general><scope>ADJCN</scope><scope>AHFXO</scope><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QL</scope><scope>7QO</scope><scope>7TK</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-1351-1315</orcidid></search><sort><creationdate>20180101</creationdate><title>A Panel of MicroRNA Signature as a Tool for Predicting Survival of Patients with Urothelial Carcinoma of the Bladder</title><author>Saito, Kenkichi ; Tanda, Naoki ; Minami, Koichiro ; Hirano, Hajime ; Nomi, Hayahito ; Kato, Ryuji ; Hayashi, Tetsuya ; Azuma, Haruhito ; Uchimoto, Taizo ; Takai, Tomoaki ; Takahara, Kiyoshi ; Komura, Kazumasa ; Ibuki, Naokazu ; Akao, Yukihiro ; Uehara, Hirofumi ; Inamoto, Teruo ; Yoshikawa, Yuki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c499t-4cc64ff8985f0b79e5ecec448ae1b42cbd416a6e1bd09d0ab70e69e85b1d32883</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Biomarkers</topic><topic>Biomarkers, Tumor - 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e-Marefa Academic and Statistical Periodicals</collection><collection>معرفة - المحتوى العربي الأكاديمي المتكامل - e-Marefa Academic Complete</collection><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Disease markers</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Saito, Kenkichi</au><au>Tanda, Naoki</au><au>Minami, Koichiro</au><au>Hirano, Hajime</au><au>Nomi, Hayahito</au><au>Kato, Ryuji</au><au>Hayashi, Tetsuya</au><au>Azuma, Haruhito</au><au>Uchimoto, Taizo</au><au>Takai, Tomoaki</au><au>Takahara, Kiyoshi</au><au>Komura, Kazumasa</au><au>Ibuki, Naokazu</au><au>Akao, Yukihiro</au><au>Uehara, Hirofumi</au><au>Inamoto, Teruo</au><au>Yoshikawa, Yuki</au><au>Miyamoto, Hiroshi</au><au>Hiroshi Miyamoto</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Panel of MicroRNA Signature as a Tool for Predicting Survival of Patients with Urothelial Carcinoma of the Bladder</atitle><jtitle>Disease markers</jtitle><addtitle>Dis Markers</addtitle><date>2018-01-01</date><risdate>2018</risdate><volume>2018</volume><issue>2018</issue><spage>1</spage><epage>6</epage><pages>1-6</pages><issn>0278-0240</issn><eissn>1875-8630</eissn><abstract>Introduction and Objectives. MicroRNA (miRNA) expression is altered in urologic malignancies, including urothelial carcinoma of the bladder (UCB). Individual miRNAs have been shown to modulate multiple signaling pathways that contribute to BC. To identify a panel of miRNA signature that can predict aggressive phenotype from normal nonaggressive counterpart using miRNA expression levels and to assess the prognostic value of this specific miRNA markers in patients with UCB. Methods. To determine candidate miRNAs as prognostic biomarkers for dividing aggressive type of UCB, miRNA expression was profiled in patients’ samples with an aggressive phenotype or nonaggressive phenotype using 3D-Gene miRNA labeling kit (Toray, Japan). To create a prognostic index model, we used the panel of 9-miRNA signature based on Cancer Genome Atlas (TCGA) data portal (TCGA Data Portal (https://tcgadata.nci.nih.gov/tcga/tcgaHome2.jsp)). miRNA expression data and corresponding clinical data, including outcome and staging information of 84 UCB patients, were obtained. The Kaplan-Meier and log-rank test were performed to quantify the survival functions in two groups. Results. Deregulation of nine miRNAs (hsa-miR-99a-5p, hsa-miR-100-5p, hsa-miR-125b-5p, hsa-miR-145-5p, hsa-miR-4324, hsa-miR-34b-5p, hsa-miR-29c-3p, hsa-miR-135a-3p, and hsa-miR-33b-3p) was determined in UCB patients with aggressive phenotype compared with nonaggressive subject. To validate the prognostic power of the nine-signature miRNAs using the TCGA dataset of bladder cancer, the survival status and tumor miRNA expression of all 84 TCGA UCB patients were ranked according to the prognostic score values. Of nine miRNAs, six were associated with high risk (hsa-miR-99a-5p, hsa-miR-100-5p, hsa-miR-125b-5p, hsa-miR-4324, hsa-miR-34b-5p, and hsa-miR-135a-3p) and three were shown to be protective (hsa-miR-145-5p, hsa-miR-29c-3p, and hsa-miR-33b-3p). Patients with the high-risk miRNA signature exhibited poorer OS than patients expressing the low-risk miRNA profile (HR = 7.05, p&lt;0.001). Conclusions. The miRNA array identified nine dysregulated miRNAs from clinical samples. This panel of nine-miRNA signature provides predictive and prognostic value of patients with UCB.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Publishing Corporation</pub><pmid>30026881</pmid><doi>10.1155/2018/5468672</doi><tpages>6</tpages><orcidid>https://orcid.org/0000-0002-1351-1315</orcidid><oa>free_for_read</oa></addata></record>
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identifier ISSN: 0278-0240
ispartof Disease markers, 2018-01, Vol.2018 (2018), p.1-6
issn 0278-0240
1875-8630
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6031086
source Wiley-Blackwell Open Access Titles(OpenAccess)
subjects Aged
Aged, 80 and over
Biomarkers
Biomarkers, Tumor - genetics
Biomarkers, Tumor - metabolism
Bladder
Bladder cancer
Cancer
Cancer therapies
Carcinoma
Carcinoma - genetics
Carcinoma - metabolism
Carcinoma - pathology
Chemotherapy
Deregulation
Genetic aspects
Genomes
Genomics
Humans
HyperText Markup Language
Male
Medical prognosis
Medical research
Medicine
Medicine, Experimental
Metastasis
MicroRNA
MicroRNAs
MicroRNAs - genetics
MicroRNAs - metabolism
miRNA
Patient outcomes
Patients
Phenotypes
Prognosis
Rank tests
Ribonucleic acid
Risk
RNA
Servers
Survival
Survival Analysis
Systematic review
Transcriptome
Urinary Bladder Neoplasms - genetics
Urinary Bladder Neoplasms - metabolism
Urinary Bladder Neoplasms - pathology
Urothelial carcinoma
Urothelium - metabolism
Urothelium - pathology
Web portals
title A Panel of MicroRNA Signature as a Tool for Predicting Survival of Patients with Urothelial Carcinoma of the Bladder
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