Predicting the clinical outcome of oral potentially malignant disorders using transcriptomic-based molecular pathology
Background This study was undertaken to develop and validate a gene expression signature that characterises oral potentially malignant disorders (OPMD) with a high risk of undergoing malignant transformation. Methods Patients with oral epithelial dysplasia at one hospital were selected as the ‘train...
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| Veröffentlicht in: | British journal of cancer 2021-08, Vol.125 (3), p.413-421 |
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| creator | Sathasivam, Hans Prakash Kist, Ralf Sloan, Philip Thomson, Peter Nugent, Michael Alexander, John Haider, Syed Robinson, Max |
| description | Background
This study was undertaken to develop and validate a gene expression signature that characterises oral potentially malignant disorders (OPMD) with a high risk of undergoing malignant transformation.
Methods
Patients with oral epithelial dysplasia at one hospital were selected as the ‘training set’ (
n
= 56) whilst those at another hospital were selected for the ‘test set’ (
n
= 66). RNA was extracted from formalin-fixed paraffin-embedded (FFPE) diagnostic biopsies and analysed using the NanoString nCounter platform. A targeted panel of 42 genes selected on their association with oral carcinogenesis was used to develop a prognostic gene signature. Following data normalisation, uni- and multivariable analysis, as well as prognostic modelling, were employed to develop and validate the gene signature.
Results
A prognostic classifier composed of 11 genes was developed using the training set. The multivariable prognostic model was used to predict patient risk scores in the test set. The prognostic gene signature was an independent predictor of malignant transformation when assessed in the test set, with the high-risk group showing worse prognosis [Hazard ratio = 12.65,
p
= 0.0003].
Conclusions
This study demonstrates proof of principle that RNA extracted from FFPE diagnostic biopsies of OPMD, when analysed on the NanoString nCounter platform, can be used to generate a molecular classifier that stratifies the risk of malignant transformation with promising clinical utility. |
| doi_str_mv | 10.1038/s41416-021-01411-z |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8329212</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2557305177</sourcerecordid><originalsourceid>FETCH-LOGICAL-c474t-8c3f3be083a581e281ccf8a79ec88432ee24e59fca0c1f9a23b309b09df81a643</originalsourceid><addsrcrecordid>eNp9kctuFTEMhiMEoqeFF2CBIrFOyWWmSTZIqCoXqRIsYB1lMp45qTLJkGQqnT49oacU2LCyLf_-bOtH6BWj54wK9bZ0rGMXhHJGaMsYuXuCdqwXnDDF5VO0o5RKQjWnJ-i0lJtWaqrkc3QihJZcdv0O3X7NMHpXfZxx3QN2wUfvbMBpqy4tgNOEU271mirE6m0IB7zY4OdoY8WjLymPkAveyj0i21hc9mtNi3dksAVGvKQAbgs249XWfQppPrxAzyYbCrx8iGfo-4erb5efyPWXj58v318T18muEuXEJAagStheMeCKOTcpKzU4pTrBAXgHvZ6cpY5N2nIxCKoHqsdJMXvRiTP07shdt2GB0bUX2jNmzX6x-WCS9ebfTvR7M6dbowTXnPEGePMAyOnHBqWam7Tl2G42vO-loD2Tsqn4UeVyKiXD9LiBUfPLK3P0yjSvzL1X5q4Nvf77tseR3-Y0gTgKSmvFGfKf3f_B_gTnvaSm</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2557305177</pqid></control><display><type>article</type><title>Predicting the clinical outcome of oral potentially malignant disorders using transcriptomic-based molecular pathology</title><source>MEDLINE</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central</source><creator>Sathasivam, Hans Prakash ; Kist, Ralf ; Sloan, Philip ; Thomson, Peter ; Nugent, Michael ; Alexander, John ; Haider, Syed ; Robinson, Max</creator><creatorcontrib>Sathasivam, Hans Prakash ; Kist, Ralf ; Sloan, Philip ; Thomson, Peter ; Nugent, Michael ; Alexander, John ; Haider, Syed ; Robinson, Max</creatorcontrib><description>Background
This study was undertaken to develop and validate a gene expression signature that characterises oral potentially malignant disorders (OPMD) with a high risk of undergoing malignant transformation.
Methods
Patients with oral epithelial dysplasia at one hospital were selected as the ‘training set’ (
n
= 56) whilst those at another hospital were selected for the ‘test set’ (
n
= 66). RNA was extracted from formalin-fixed paraffin-embedded (FFPE) diagnostic biopsies and analysed using the NanoString nCounter platform. A targeted panel of 42 genes selected on their association with oral carcinogenesis was used to develop a prognostic gene signature. Following data normalisation, uni- and multivariable analysis, as well as prognostic modelling, were employed to develop and validate the gene signature.
Results
A prognostic classifier composed of 11 genes was developed using the training set. The multivariable prognostic model was used to predict patient risk scores in the test set. The prognostic gene signature was an independent predictor of malignant transformation when assessed in the test set, with the high-risk group showing worse prognosis [Hazard ratio = 12.65,
p
= 0.0003].
Conclusions
This study demonstrates proof of principle that RNA extracted from FFPE diagnostic biopsies of OPMD, when analysed on the NanoString nCounter platform, can be used to generate a molecular classifier that stratifies the risk of malignant transformation with promising clinical utility.</description><identifier>ISSN: 0007-0920</identifier><identifier>EISSN: 1532-1827</identifier><identifier>DOI: 10.1038/s41416-021-01411-z</identifier><identifier>PMID: 33972745</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>631/67/1536/1665/3016 ; 631/67/1665/3016 ; Aged ; Biomedical and Life Sciences ; Biomedicine ; Biopsy ; Cancer Research ; Carcinogenesis ; Cell Transformation, Neoplastic - genetics ; Cell Transformation, Neoplastic - pathology ; Clinical outcomes ; Drug Resistance ; Dysplasia ; Epidemiology ; Female ; Gene expression ; Gene Expression Profiling - methods ; Gene Expression Regulation, Neoplastic ; Gene Regulatory Networks ; Genetic transformation ; Humans ; Male ; Middle Aged ; Molecular Medicine ; Mouth Neoplasms - genetics ; Mouth Neoplasms - pathology ; Oncology ; Paraffin ; Paraffin Embedding ; Patients ; Prognosis ; Proof of Concept Study ; Risk groups ; Sequence Analysis, RNA ; Survival Analysis ; Tissue Fixation</subject><ispartof>British journal of cancer, 2021-08, Vol.125 (3), p.413-421</ispartof><rights>The Author(s), under exclusive licence to Cancer Research UK 2021</rights><rights>2021. The Author(s), under exclusive licence to Cancer Research UK.</rights><rights>The Author(s), under exclusive licence to Cancer Research UK 2021.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c474t-8c3f3be083a581e281ccf8a79ec88432ee24e59fca0c1f9a23b309b09df81a643</citedby><cites>FETCH-LOGICAL-c474t-8c3f3be083a581e281ccf8a79ec88432ee24e59fca0c1f9a23b309b09df81a643</cites><orcidid>0000-0003-3973-6501 ; 0000-0001-6685-5480 ; 0000-0003-3729-5693 ; 0000-0003-4491-6865</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8329212/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8329212/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33972745$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sathasivam, Hans Prakash</creatorcontrib><creatorcontrib>Kist, Ralf</creatorcontrib><creatorcontrib>Sloan, Philip</creatorcontrib><creatorcontrib>Thomson, Peter</creatorcontrib><creatorcontrib>Nugent, Michael</creatorcontrib><creatorcontrib>Alexander, John</creatorcontrib><creatorcontrib>Haider, Syed</creatorcontrib><creatorcontrib>Robinson, Max</creatorcontrib><title>Predicting the clinical outcome of oral potentially malignant disorders using transcriptomic-based molecular pathology</title><title>British journal of cancer</title><addtitle>Br J Cancer</addtitle><addtitle>Br J Cancer</addtitle><description>Background
This study was undertaken to develop and validate a gene expression signature that characterises oral potentially malignant disorders (OPMD) with a high risk of undergoing malignant transformation.
Methods
Patients with oral epithelial dysplasia at one hospital were selected as the ‘training set’ (
n
= 56) whilst those at another hospital were selected for the ‘test set’ (
n
= 66). RNA was extracted from formalin-fixed paraffin-embedded (FFPE) diagnostic biopsies and analysed using the NanoString nCounter platform. A targeted panel of 42 genes selected on their association with oral carcinogenesis was used to develop a prognostic gene signature. Following data normalisation, uni- and multivariable analysis, as well as prognostic modelling, were employed to develop and validate the gene signature.
Results
A prognostic classifier composed of 11 genes was developed using the training set. The multivariable prognostic model was used to predict patient risk scores in the test set. The prognostic gene signature was an independent predictor of malignant transformation when assessed in the test set, with the high-risk group showing worse prognosis [Hazard ratio = 12.65,
p
= 0.0003].
Conclusions
This study demonstrates proof of principle that RNA extracted from FFPE diagnostic biopsies of OPMD, when analysed on the NanoString nCounter platform, can be used to generate a molecular classifier that stratifies the risk of malignant transformation with promising clinical utility.</description><subject>631/67/1536/1665/3016</subject><subject>631/67/1665/3016</subject><subject>Aged</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Biopsy</subject><subject>Cancer Research</subject><subject>Carcinogenesis</subject><subject>Cell Transformation, Neoplastic - genetics</subject><subject>Cell Transformation, Neoplastic - pathology</subject><subject>Clinical outcomes</subject><subject>Drug Resistance</subject><subject>Dysplasia</subject><subject>Epidemiology</subject><subject>Female</subject><subject>Gene expression</subject><subject>Gene Expression Profiling - methods</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Gene Regulatory Networks</subject><subject>Genetic transformation</subject><subject>Humans</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Molecular Medicine</subject><subject>Mouth Neoplasms - genetics</subject><subject>Mouth Neoplasms - pathology</subject><subject>Oncology</subject><subject>Paraffin</subject><subject>Paraffin Embedding</subject><subject>Patients</subject><subject>Prognosis</subject><subject>Proof of Concept Study</subject><subject>Risk groups</subject><subject>Sequence Analysis, RNA</subject><subject>Survival Analysis</subject><subject>Tissue Fixation</subject><issn>0007-0920</issn><issn>1532-1827</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kctuFTEMhiMEoqeFF2CBIrFOyWWmSTZIqCoXqRIsYB1lMp45qTLJkGQqnT49oacU2LCyLf_-bOtH6BWj54wK9bZ0rGMXhHJGaMsYuXuCdqwXnDDF5VO0o5RKQjWnJ-i0lJtWaqrkc3QihJZcdv0O3X7NMHpXfZxx3QN2wUfvbMBpqy4tgNOEU271mirE6m0IB7zY4OdoY8WjLymPkAveyj0i21hc9mtNi3dksAVGvKQAbgs249XWfQppPrxAzyYbCrx8iGfo-4erb5efyPWXj58v318T18muEuXEJAagStheMeCKOTcpKzU4pTrBAXgHvZ6cpY5N2nIxCKoHqsdJMXvRiTP07shdt2GB0bUX2jNmzX6x-WCS9ebfTvR7M6dbowTXnPEGePMAyOnHBqWam7Tl2G42vO-loD2Tsqn4UeVyKiXD9LiBUfPLK3P0yjSvzL1X5q4Nvf77tseR3-Y0gTgKSmvFGfKf3f_B_gTnvaSm</recordid><startdate>20210803</startdate><enddate>20210803</enddate><creator>Sathasivam, Hans Prakash</creator><creator>Kist, Ralf</creator><creator>Sloan, Philip</creator><creator>Thomson, Peter</creator><creator>Nugent, Michael</creator><creator>Alexander, John</creator><creator>Haider, Syed</creator><creator>Robinson, Max</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><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>3V.</scope><scope>7RV</scope><scope>7TO</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AN0</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-3973-6501</orcidid><orcidid>https://orcid.org/0000-0001-6685-5480</orcidid><orcidid>https://orcid.org/0000-0003-3729-5693</orcidid><orcidid>https://orcid.org/0000-0003-4491-6865</orcidid></search><sort><creationdate>20210803</creationdate><title>Predicting the clinical outcome of oral potentially malignant disorders using transcriptomic-based molecular pathology</title><author>Sathasivam, Hans Prakash ; Kist, Ralf ; Sloan, Philip ; Thomson, Peter ; Nugent, Michael ; Alexander, John ; Haider, Syed ; Robinson, Max</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c474t-8c3f3be083a581e281ccf8a79ec88432ee24e59fca0c1f9a23b309b09df81a643</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>631/67/1536/1665/3016</topic><topic>631/67/1665/3016</topic><topic>Aged</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Biopsy</topic><topic>Cancer Research</topic><topic>Carcinogenesis</topic><topic>Cell Transformation, Neoplastic - genetics</topic><topic>Cell Transformation, Neoplastic - pathology</topic><topic>Clinical outcomes</topic><topic>Drug Resistance</topic><topic>Dysplasia</topic><topic>Epidemiology</topic><topic>Female</topic><topic>Gene expression</topic><topic>Gene Expression Profiling - methods</topic><topic>Gene Expression Regulation, Neoplastic</topic><topic>Gene Regulatory Networks</topic><topic>Genetic transformation</topic><topic>Humans</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Molecular Medicine</topic><topic>Mouth Neoplasms - genetics</topic><topic>Mouth Neoplasms - pathology</topic><topic>Oncology</topic><topic>Paraffin</topic><topic>Paraffin Embedding</topic><topic>Patients</topic><topic>Prognosis</topic><topic>Proof of Concept Study</topic><topic>Risk groups</topic><topic>Sequence Analysis, RNA</topic><topic>Survival Analysis</topic><topic>Tissue Fixation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sathasivam, Hans Prakash</creatorcontrib><creatorcontrib>Kist, Ralf</creatorcontrib><creatorcontrib>Sloan, Philip</creatorcontrib><creatorcontrib>Thomson, Peter</creatorcontrib><creatorcontrib>Nugent, Michael</creatorcontrib><creatorcontrib>Alexander, John</creatorcontrib><creatorcontrib>Haider, Syed</creatorcontrib><creatorcontrib>Robinson, Max</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>British Nursing Database</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>British journal of cancer</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sathasivam, Hans Prakash</au><au>Kist, Ralf</au><au>Sloan, Philip</au><au>Thomson, Peter</au><au>Nugent, Michael</au><au>Alexander, John</au><au>Haider, Syed</au><au>Robinson, Max</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting the clinical outcome of oral potentially malignant disorders using transcriptomic-based molecular pathology</atitle><jtitle>British journal of cancer</jtitle><stitle>Br J Cancer</stitle><addtitle>Br J Cancer</addtitle><date>2021-08-03</date><risdate>2021</risdate><volume>125</volume><issue>3</issue><spage>413</spage><epage>421</epage><pages>413-421</pages><issn>0007-0920</issn><eissn>1532-1827</eissn><abstract>Background
This study was undertaken to develop and validate a gene expression signature that characterises oral potentially malignant disorders (OPMD) with a high risk of undergoing malignant transformation.
Methods
Patients with oral epithelial dysplasia at one hospital were selected as the ‘training set’ (
n
= 56) whilst those at another hospital were selected for the ‘test set’ (
n
= 66). RNA was extracted from formalin-fixed paraffin-embedded (FFPE) diagnostic biopsies and analysed using the NanoString nCounter platform. A targeted panel of 42 genes selected on their association with oral carcinogenesis was used to develop a prognostic gene signature. Following data normalisation, uni- and multivariable analysis, as well as prognostic modelling, were employed to develop and validate the gene signature.
Results
A prognostic classifier composed of 11 genes was developed using the training set. The multivariable prognostic model was used to predict patient risk scores in the test set. The prognostic gene signature was an independent predictor of malignant transformation when assessed in the test set, with the high-risk group showing worse prognosis [Hazard ratio = 12.65,
p
= 0.0003].
Conclusions
This study demonstrates proof of principle that RNA extracted from FFPE diagnostic biopsies of OPMD, when analysed on the NanoString nCounter platform, can be used to generate a molecular classifier that stratifies the risk of malignant transformation with promising clinical utility.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>33972745</pmid><doi>10.1038/s41416-021-01411-z</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0003-3973-6501</orcidid><orcidid>https://orcid.org/0000-0001-6685-5480</orcidid><orcidid>https://orcid.org/0000-0003-3729-5693</orcidid><orcidid>https://orcid.org/0000-0003-4491-6865</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | British journal of cancer, 2021-08, Vol.125 (3), p.413-421 |
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| language | eng |
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| source | MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central |
| subjects | 631/67/1536/1665/3016 631/67/1665/3016 Aged Biomedical and Life Sciences Biomedicine Biopsy Cancer Research Carcinogenesis Cell Transformation, Neoplastic - genetics Cell Transformation, Neoplastic - pathology Clinical outcomes Drug Resistance Dysplasia Epidemiology Female Gene expression Gene Expression Profiling - methods Gene Expression Regulation, Neoplastic Gene Regulatory Networks Genetic transformation Humans Male Middle Aged Molecular Medicine Mouth Neoplasms - genetics Mouth Neoplasms - pathology Oncology Paraffin Paraffin Embedding Patients Prognosis Proof of Concept Study Risk groups Sequence Analysis, RNA Survival Analysis Tissue Fixation |
| title | Predicting the clinical outcome of oral potentially malignant disorders using transcriptomic-based molecular pathology |
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