Targeted deep sequencing of urothelial bladder cancers and associated urinary DNA: a 23‐gene panel with utility for non‐invasive diagnosis and risk stratification
Objectives To develop a focused panel of somatic mutations (SMs) present in the majority of urothelial bladder cancers (UBCs), to investigate the diagnostic and prognostic utility of this panel, and to compare the identification of SMs in urinary cell‐pellet (cp)DNA and cell‐free (cf)DNA as part of...
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| Veröffentlicht in: | BJU international 2019-09, Vol.124 (3), p.532-544 |
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| creator | Ward, Douglas G. Gordon, Naheema S. Boucher, Rebecca H. Pirrie, Sarah J. Baxter, Laura Ott, Sascha Silcock, Lee Whalley, Celina M. Stockton, Joanne D. Beggs, Andrew D. Griffiths, Mike Abbotts, Ben Ijakipour, Hanieh Latheef, Fathimath N. Robinson, Robert A. White, Andrew J. James, Nicholas D. Zeegers, Maurice P. Cheng, K. K. Bryan, Richard T. |
| description | Objectives
To develop a focused panel of somatic mutations (SMs) present in the majority of urothelial bladder cancers (UBCs), to investigate the diagnostic and prognostic utility of this panel, and to compare the identification of SMs in urinary cell‐pellet (cp)DNA and cell‐free (cf)DNA as part of the development of a non‐invasive clinical assay.
Patients and Methods
A panel of SMs was validated by targeted deep‐sequencing of tumour DNA from 956 patients with UBC. In addition, amplicon and capture‐based targeted sequencing measured mutant allele frequencies (MAFs) of SMs in 314 urine cpDNAs and 153 urine cfDNAs. The association of SMs with grade, stage, and clinical outcomes was investigated by univariate and multivariate Cox models. Concordance between SMs detected in tumour tissue and cpDNA and cfDNA was assessed.
Results
The panel comprised SMs in 23 genes: TERT (promoter), FGFR3, PIK3CA, TP53, ERCC2, RHOB, ERBB2, HRAS, RXRA, ELF3, CDKN1A, KRAS, KDM6A, AKT1, FBXW7, ERBB3, SF3B1, CTNNB1, BRAF, C3orf70, CREBBP, CDKN2A, and NRAS; 93.5–98.3% of UBCs of all grades and stages harboured ≥1 SM (mean: 2.5 SMs/tumour). RAS mutations were associated with better overall survival (P = 0.04). Mutations in RXRA, RHOB and TERT (promoter) were associated with shorter time to recurrence (P 94% of tumour SMs were detected in both cpDNA and cfDNA.
Conclusions
SMs are reliably detected in urinary cpDNA and cfDNA. The technical capability to identify very low MAFs is essential to reliably detect UBC, regardless of the use of cpDNA or cfDNA. This 23‐gene panel shows promise for the non‐invasive diagnosis and risk stratification of UBC. |
| doi_str_mv | 10.1111/bju.14808 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6772022</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2231932464</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4438-488adb001b4f40c05173747523ca45e68f3cb46636266bb172ae7526900f28c23</originalsourceid><addsrcrecordid>eNp1kc1u1DAUhS0Eoj-w4AWQJTawmNZ2HCfDolJp-VUFm1ZiZznOTcaDxx7sZKrZ8Qg8BQ_Gk3CHtBUg4YVt-X4-uuceQp5wdsRxHTfL8YjLmtX3yD6XSs4kZ5_v397ZXO2Rg5yXjOGDKh-SvYKzqlJivk9-XJrUwwAtbQHWNMPXEYJ1oaexo2OKwwK8M5423rQtJGpNsJAyNaGlJudondl9HpMLJm3p-cfTl9RQUfz89r2HAHRtAnh67YYFHQfn3bClXUw0xICECxuT3QZo60wfYnaTbnL5C81DMoPrnMU9hkfkQWd8hsc35yG5evP68uzd7OLT2_dnpxczK2VRz2Rdm7ZBn43sJLOs5FVRyaoUhTWyBFV3hW1wBoUSSjUNr4QBrKo5Y52orSgOycmkux6bFbQWArbh9Tq5FdrT0Tj9dyW4he7jRquqEkzsBJ7fCKSIo8yDXrlswXucQxyzRoTPC4HBIPrsH3QZxxTQHlIoh1GVDKkXE2VTzDlBd9cMZ3qXvsb09e_0kX36Z_d35G3cCBxPwLXzsP2_kn714WqS_AUCz72u</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2277266550</pqid></control><display><type>article</type><title>Targeted deep sequencing of urothelial bladder cancers and associated urinary DNA: a 23‐gene panel with utility for non‐invasive diagnosis and risk stratification</title><source>MEDLINE</source><source>Wiley Online Library Journals Frontfile Complete</source><creator>Ward, Douglas G. ; Gordon, Naheema S. ; Boucher, Rebecca H. ; Pirrie, Sarah J. ; Baxter, Laura ; Ott, Sascha ; Silcock, Lee ; Whalley, Celina M. ; Stockton, Joanne D. ; Beggs, Andrew D. ; Griffiths, Mike ; Abbotts, Ben ; Ijakipour, Hanieh ; Latheef, Fathimath N. ; Robinson, Robert A. ; White, Andrew J. ; James, Nicholas D. ; Zeegers, Maurice P. ; Cheng, K. K. ; Bryan, Richard T.</creator><creatorcontrib>Ward, Douglas G. ; Gordon, Naheema S. ; Boucher, Rebecca H. ; Pirrie, Sarah J. ; Baxter, Laura ; Ott, Sascha ; Silcock, Lee ; Whalley, Celina M. ; Stockton, Joanne D. ; Beggs, Andrew D. ; Griffiths, Mike ; Abbotts, Ben ; Ijakipour, Hanieh ; Latheef, Fathimath N. ; Robinson, Robert A. ; White, Andrew J. ; James, Nicholas D. ; Zeegers, Maurice P. ; Cheng, K. K. ; Bryan, Richard T.</creatorcontrib><description>Objectives
To develop a focused panel of somatic mutations (SMs) present in the majority of urothelial bladder cancers (UBCs), to investigate the diagnostic and prognostic utility of this panel, and to compare the identification of SMs in urinary cell‐pellet (cp)DNA and cell‐free (cf)DNA as part of the development of a non‐invasive clinical assay.
Patients and Methods
A panel of SMs was validated by targeted deep‐sequencing of tumour DNA from 956 patients with UBC. In addition, amplicon and capture‐based targeted sequencing measured mutant allele frequencies (MAFs) of SMs in 314 urine cpDNAs and 153 urine cfDNAs. The association of SMs with grade, stage, and clinical outcomes was investigated by univariate and multivariate Cox models. Concordance between SMs detected in tumour tissue and cpDNA and cfDNA was assessed.
Results
The panel comprised SMs in 23 genes: TERT (promoter), FGFR3, PIK3CA, TP53, ERCC2, RHOB, ERBB2, HRAS, RXRA, ELF3, CDKN1A, KRAS, KDM6A, AKT1, FBXW7, ERBB3, SF3B1, CTNNB1, BRAF, C3orf70, CREBBP, CDKN2A, and NRAS; 93.5–98.3% of UBCs of all grades and stages harboured ≥1 SM (mean: 2.5 SMs/tumour). RAS mutations were associated with better overall survival (P = 0.04). Mutations in RXRA, RHOB and TERT (promoter) were associated with shorter time to recurrence (P < 0.05). MAFs in urinary cfDNA and cpDNA were highly correlated; using a capture‐based approach, >94% of tumour SMs were detected in both cpDNA and cfDNA.
Conclusions
SMs are reliably detected in urinary cpDNA and cfDNA. The technical capability to identify very low MAFs is essential to reliably detect UBC, regardless of the use of cpDNA or cfDNA. This 23‐gene panel shows promise for the non‐invasive diagnosis and risk stratification of UBC.</description><identifier>ISSN: 1464-4096</identifier><identifier>EISSN: 1464-410X</identifier><identifier>DOI: 10.1111/bju.14808</identifier><identifier>PMID: 31077629</identifier><language>eng</language><publisher>England: Wiley Subscription Services, Inc</publisher><subject>Adult ; Aged ; Aged, 80 and over ; AKT1 protein ; Bladder cancer ; BladderCancer ; blcsm ; Cdc4 protein ; Databases, Genetic ; Deoxyribonucleic acid ; detection ; Diagnosis ; DNA ; DNA sequencing ; DNA, Neoplasm - urine ; ErbB-2 protein ; ErbB-3 protein ; Female ; Fibroblast growth factor receptors ; Gene frequency ; High-Throughput Nucleotide Sequencing - methods ; Humans ; Male ; Middle Aged ; Mutation ; Mutation - genetics ; mutations ; p53 Protein ; Prognosis ; Retinoid X receptor α ; Risk Assessment ; Sequence Analysis, DNA ; Translational Science ; Tumors ; Urinary Bladder Neoplasms - diagnosis ; Urinary Bladder Neoplasms - genetics ; Urine</subject><ispartof>BJU international, 2019-09, Vol.124 (3), p.532-544</ispartof><rights>2019 The Authors BJU International published by John Wiley & Sons Ltd on behalf of BJU International</rights><rights>2019 The Authors BJU International published by John Wiley & Sons Ltd on behalf of BJU International.</rights><rights>BJUI © 2019 BJU International</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4438-488adb001b4f40c05173747523ca45e68f3cb46636266bb172ae7526900f28c23</citedby><cites>FETCH-LOGICAL-c4438-488adb001b4f40c05173747523ca45e68f3cb46636266bb172ae7526900f28c23</cites><orcidid>0000-0002-2328-1445 ; 0000-0003-2853-4293 ; 0000-0002-7314-8204</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fbju.14808$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fbju.14808$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31077629$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ward, Douglas G.</creatorcontrib><creatorcontrib>Gordon, Naheema S.</creatorcontrib><creatorcontrib>Boucher, Rebecca H.</creatorcontrib><creatorcontrib>Pirrie, Sarah J.</creatorcontrib><creatorcontrib>Baxter, Laura</creatorcontrib><creatorcontrib>Ott, Sascha</creatorcontrib><creatorcontrib>Silcock, Lee</creatorcontrib><creatorcontrib>Whalley, Celina M.</creatorcontrib><creatorcontrib>Stockton, Joanne D.</creatorcontrib><creatorcontrib>Beggs, Andrew D.</creatorcontrib><creatorcontrib>Griffiths, Mike</creatorcontrib><creatorcontrib>Abbotts, Ben</creatorcontrib><creatorcontrib>Ijakipour, Hanieh</creatorcontrib><creatorcontrib>Latheef, Fathimath N.</creatorcontrib><creatorcontrib>Robinson, Robert A.</creatorcontrib><creatorcontrib>White, Andrew J.</creatorcontrib><creatorcontrib>James, Nicholas D.</creatorcontrib><creatorcontrib>Zeegers, Maurice P.</creatorcontrib><creatorcontrib>Cheng, K. K.</creatorcontrib><creatorcontrib>Bryan, Richard T.</creatorcontrib><title>Targeted deep sequencing of urothelial bladder cancers and associated urinary DNA: a 23‐gene panel with utility for non‐invasive diagnosis and risk stratification</title><title>BJU international</title><addtitle>BJU Int</addtitle><description>Objectives
To develop a focused panel of somatic mutations (SMs) present in the majority of urothelial bladder cancers (UBCs), to investigate the diagnostic and prognostic utility of this panel, and to compare the identification of SMs in urinary cell‐pellet (cp)DNA and cell‐free (cf)DNA as part of the development of a non‐invasive clinical assay.
Patients and Methods
A panel of SMs was validated by targeted deep‐sequencing of tumour DNA from 956 patients with UBC. In addition, amplicon and capture‐based targeted sequencing measured mutant allele frequencies (MAFs) of SMs in 314 urine cpDNAs and 153 urine cfDNAs. The association of SMs with grade, stage, and clinical outcomes was investigated by univariate and multivariate Cox models. Concordance between SMs detected in tumour tissue and cpDNA and cfDNA was assessed.
Results
The panel comprised SMs in 23 genes: TERT (promoter), FGFR3, PIK3CA, TP53, ERCC2, RHOB, ERBB2, HRAS, RXRA, ELF3, CDKN1A, KRAS, KDM6A, AKT1, FBXW7, ERBB3, SF3B1, CTNNB1, BRAF, C3orf70, CREBBP, CDKN2A, and NRAS; 93.5–98.3% of UBCs of all grades and stages harboured ≥1 SM (mean: 2.5 SMs/tumour). RAS mutations were associated with better overall survival (P = 0.04). Mutations in RXRA, RHOB and TERT (promoter) were associated with shorter time to recurrence (P < 0.05). MAFs in urinary cfDNA and cpDNA were highly correlated; using a capture‐based approach, >94% of tumour SMs were detected in both cpDNA and cfDNA.
Conclusions
SMs are reliably detected in urinary cpDNA and cfDNA. The technical capability to identify very low MAFs is essential to reliably detect UBC, regardless of the use of cpDNA or cfDNA. This 23‐gene panel shows promise for the non‐invasive diagnosis and risk stratification of UBC.</description><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>AKT1 protein</subject><subject>Bladder cancer</subject><subject>BladderCancer</subject><subject>blcsm</subject><subject>Cdc4 protein</subject><subject>Databases, Genetic</subject><subject>Deoxyribonucleic acid</subject><subject>detection</subject><subject>Diagnosis</subject><subject>DNA</subject><subject>DNA sequencing</subject><subject>DNA, Neoplasm - urine</subject><subject>ErbB-2 protein</subject><subject>ErbB-3 protein</subject><subject>Female</subject><subject>Fibroblast growth factor receptors</subject><subject>Gene frequency</subject><subject>High-Throughput Nucleotide Sequencing - methods</subject><subject>Humans</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Mutation</subject><subject>Mutation - genetics</subject><subject>mutations</subject><subject>p53 Protein</subject><subject>Prognosis</subject><subject>Retinoid X receptor α</subject><subject>Risk Assessment</subject><subject>Sequence Analysis, DNA</subject><subject>Translational Science</subject><subject>Tumors</subject><subject>Urinary Bladder Neoplasms - diagnosis</subject><subject>Urinary Bladder Neoplasms - genetics</subject><subject>Urine</subject><issn>1464-4096</issn><issn>1464-410X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>EIF</sourceid><recordid>eNp1kc1u1DAUhS0Eoj-w4AWQJTawmNZ2HCfDolJp-VUFm1ZiZznOTcaDxx7sZKrZ8Qg8BQ_Gk3CHtBUg4YVt-X4-uuceQp5wdsRxHTfL8YjLmtX3yD6XSs4kZ5_v397ZXO2Rg5yXjOGDKh-SvYKzqlJivk9-XJrUwwAtbQHWNMPXEYJ1oaexo2OKwwK8M5423rQtJGpNsJAyNaGlJudondl9HpMLJm3p-cfTl9RQUfz89r2HAHRtAnh67YYFHQfn3bClXUw0xICECxuT3QZo60wfYnaTbnL5C81DMoPrnMU9hkfkQWd8hsc35yG5evP68uzd7OLT2_dnpxczK2VRz2Rdm7ZBn43sJLOs5FVRyaoUhTWyBFV3hW1wBoUSSjUNr4QBrKo5Y52orSgOycmkux6bFbQWArbh9Tq5FdrT0Tj9dyW4he7jRquqEkzsBJ7fCKSIo8yDXrlswXucQxyzRoTPC4HBIPrsH3QZxxTQHlIoh1GVDKkXE2VTzDlBd9cMZ3qXvsb09e_0kX36Z_d35G3cCBxPwLXzsP2_kn714WqS_AUCz72u</recordid><startdate>201909</startdate><enddate>201909</enddate><creator>Ward, Douglas G.</creator><creator>Gordon, Naheema S.</creator><creator>Boucher, Rebecca H.</creator><creator>Pirrie, Sarah J.</creator><creator>Baxter, Laura</creator><creator>Ott, Sascha</creator><creator>Silcock, Lee</creator><creator>Whalley, Celina M.</creator><creator>Stockton, Joanne D.</creator><creator>Beggs, Andrew D.</creator><creator>Griffiths, Mike</creator><creator>Abbotts, Ben</creator><creator>Ijakipour, Hanieh</creator><creator>Latheef, Fathimath N.</creator><creator>Robinson, Robert A.</creator><creator>White, Andrew J.</creator><creator>James, Nicholas D.</creator><creator>Zeegers, Maurice P.</creator><creator>Cheng, K. K.</creator><creator>Bryan, Richard T.</creator><general>Wiley Subscription Services, Inc</general><general>John Wiley and Sons Inc</general><scope>24P</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>7QP</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-2328-1445</orcidid><orcidid>https://orcid.org/0000-0003-2853-4293</orcidid><orcidid>https://orcid.org/0000-0002-7314-8204</orcidid></search><sort><creationdate>201909</creationdate><title>Targeted deep sequencing of urothelial bladder cancers and associated urinary DNA: a 23‐gene panel with utility for non‐invasive diagnosis and risk stratification</title><author>Ward, Douglas G. ; Gordon, Naheema S. ; Boucher, Rebecca H. ; Pirrie, Sarah J. ; Baxter, Laura ; Ott, Sascha ; Silcock, Lee ; Whalley, Celina M. ; Stockton, Joanne D. ; Beggs, Andrew D. ; Griffiths, Mike ; Abbotts, Ben ; Ijakipour, Hanieh ; Latheef, Fathimath N. ; Robinson, Robert A. ; White, Andrew J. ; James, Nicholas D. ; Zeegers, Maurice P. ; Cheng, K. K. ; Bryan, Richard T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4438-488adb001b4f40c05173747523ca45e68f3cb46636266bb172ae7526900f28c23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>AKT1 protein</topic><topic>Bladder cancer</topic><topic>BladderCancer</topic><topic>blcsm</topic><topic>Cdc4 protein</topic><topic>Databases, Genetic</topic><topic>Deoxyribonucleic acid</topic><topic>detection</topic><topic>Diagnosis</topic><topic>DNA</topic><topic>DNA sequencing</topic><topic>DNA, Neoplasm - urine</topic><topic>ErbB-2 protein</topic><topic>ErbB-3 protein</topic><topic>Female</topic><topic>Fibroblast growth factor receptors</topic><topic>Gene frequency</topic><topic>High-Throughput Nucleotide Sequencing - methods</topic><topic>Humans</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Mutation</topic><topic>Mutation - genetics</topic><topic>mutations</topic><topic>p53 Protein</topic><topic>Prognosis</topic><topic>Retinoid X receptor α</topic><topic>Risk Assessment</topic><topic>Sequence Analysis, DNA</topic><topic>Translational Science</topic><topic>Tumors</topic><topic>Urinary Bladder Neoplasms - diagnosis</topic><topic>Urinary Bladder Neoplasms - genetics</topic><topic>Urine</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ward, Douglas G.</creatorcontrib><creatorcontrib>Gordon, Naheema S.</creatorcontrib><creatorcontrib>Boucher, Rebecca H.</creatorcontrib><creatorcontrib>Pirrie, Sarah J.</creatorcontrib><creatorcontrib>Baxter, Laura</creatorcontrib><creatorcontrib>Ott, Sascha</creatorcontrib><creatorcontrib>Silcock, Lee</creatorcontrib><creatorcontrib>Whalley, Celina M.</creatorcontrib><creatorcontrib>Stockton, Joanne D.</creatorcontrib><creatorcontrib>Beggs, Andrew D.</creatorcontrib><creatorcontrib>Griffiths, Mike</creatorcontrib><creatorcontrib>Abbotts, Ben</creatorcontrib><creatorcontrib>Ijakipour, Hanieh</creatorcontrib><creatorcontrib>Latheef, Fathimath N.</creatorcontrib><creatorcontrib>Robinson, Robert A.</creatorcontrib><creatorcontrib>White, Andrew J.</creatorcontrib><creatorcontrib>James, Nicholas D.</creatorcontrib><creatorcontrib>Zeegers, Maurice P.</creatorcontrib><creatorcontrib>Cheng, K. K.</creatorcontrib><creatorcontrib>Bryan, Richard T.</creatorcontrib><collection>Wiley Online Library 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>Calcium & Calcified Tissue Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>BJU international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ward, Douglas G.</au><au>Gordon, Naheema S.</au><au>Boucher, Rebecca H.</au><au>Pirrie, Sarah J.</au><au>Baxter, Laura</au><au>Ott, Sascha</au><au>Silcock, Lee</au><au>Whalley, Celina M.</au><au>Stockton, Joanne D.</au><au>Beggs, Andrew D.</au><au>Griffiths, Mike</au><au>Abbotts, Ben</au><au>Ijakipour, Hanieh</au><au>Latheef, Fathimath N.</au><au>Robinson, Robert A.</au><au>White, Andrew J.</au><au>James, Nicholas D.</au><au>Zeegers, Maurice P.</au><au>Cheng, K. K.</au><au>Bryan, Richard T.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Targeted deep sequencing of urothelial bladder cancers and associated urinary DNA: a 23‐gene panel with utility for non‐invasive diagnosis and risk stratification</atitle><jtitle>BJU international</jtitle><addtitle>BJU Int</addtitle><date>2019-09</date><risdate>2019</risdate><volume>124</volume><issue>3</issue><spage>532</spage><epage>544</epage><pages>532-544</pages><issn>1464-4096</issn><eissn>1464-410X</eissn><abstract>Objectives
To develop a focused panel of somatic mutations (SMs) present in the majority of urothelial bladder cancers (UBCs), to investigate the diagnostic and prognostic utility of this panel, and to compare the identification of SMs in urinary cell‐pellet (cp)DNA and cell‐free (cf)DNA as part of the development of a non‐invasive clinical assay.
Patients and Methods
A panel of SMs was validated by targeted deep‐sequencing of tumour DNA from 956 patients with UBC. In addition, amplicon and capture‐based targeted sequencing measured mutant allele frequencies (MAFs) of SMs in 314 urine cpDNAs and 153 urine cfDNAs. The association of SMs with grade, stage, and clinical outcomes was investigated by univariate and multivariate Cox models. Concordance between SMs detected in tumour tissue and cpDNA and cfDNA was assessed.
Results
The panel comprised SMs in 23 genes: TERT (promoter), FGFR3, PIK3CA, TP53, ERCC2, RHOB, ERBB2, HRAS, RXRA, ELF3, CDKN1A, KRAS, KDM6A, AKT1, FBXW7, ERBB3, SF3B1, CTNNB1, BRAF, C3orf70, CREBBP, CDKN2A, and NRAS; 93.5–98.3% of UBCs of all grades and stages harboured ≥1 SM (mean: 2.5 SMs/tumour). RAS mutations were associated with better overall survival (P = 0.04). Mutations in RXRA, RHOB and TERT (promoter) were associated with shorter time to recurrence (P < 0.05). MAFs in urinary cfDNA and cpDNA were highly correlated; using a capture‐based approach, >94% of tumour SMs were detected in both cpDNA and cfDNA.
Conclusions
SMs are reliably detected in urinary cpDNA and cfDNA. The technical capability to identify very low MAFs is essential to reliably detect UBC, regardless of the use of cpDNA or cfDNA. This 23‐gene panel shows promise for the non‐invasive diagnosis and risk stratification of UBC.</abstract><cop>England</cop><pub>Wiley Subscription Services, Inc</pub><pmid>31077629</pmid><doi>10.1111/bju.14808</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-2328-1445</orcidid><orcidid>https://orcid.org/0000-0003-2853-4293</orcidid><orcidid>https://orcid.org/0000-0002-7314-8204</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Adult Aged Aged, 80 and over AKT1 protein Bladder cancer BladderCancer blcsm Cdc4 protein Databases, Genetic Deoxyribonucleic acid detection Diagnosis DNA DNA sequencing DNA, Neoplasm - urine ErbB-2 protein ErbB-3 protein Female Fibroblast growth factor receptors Gene frequency High-Throughput Nucleotide Sequencing - methods Humans Male Middle Aged Mutation Mutation - genetics mutations p53 Protein Prognosis Retinoid X receptor α Risk Assessment Sequence Analysis, DNA Translational Science Tumors Urinary Bladder Neoplasms - diagnosis Urinary Bladder Neoplasms - genetics Urine |
| title | Targeted deep sequencing of urothelial bladder cancers and associated urinary DNA: a 23‐gene panel with utility for non‐invasive diagnosis and risk stratification |
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