Radiogenomics in Clear Cell Renal Cell Carcinoma: Correlations Between Advanced CT Imaging (Texture Analysis) and MicroRNAs Expression
Purpose: A relevant challenge for the improvement of clear cell renal cell carcinoma management could derive from the identification of novel molecular biomarkers that could greatly improve the diagnosis, prognosis, and treatment choice of these neoplasms. In this study, we investigate whether quant...
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| Veröffentlicht in: | Technology in cancer research & treatment 2019, Vol.18, p.1533033819878458-1533033819878458 |
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| creator | Marigliano, Chiara Badia, Stefano Bellini, Davide Rengo, Marco Caruso, Damiano Tito, Claudia Miglietta, Selenia Palleschi, Giovanni Pastore, Antonio Luigi Carbone, Antonio Fazi, Francesco Petrozza, Vincenzo Laghi, Andrea |
| description | Purpose:
A relevant challenge for the improvement of clear cell renal cell carcinoma management could derive from the identification of novel molecular biomarkers that could greatly improve the diagnosis, prognosis, and treatment choice of these neoplasms. In this study, we investigate whether quantitative parameters obtained from computed tomography texture analysis may correlate with the expression of selected oncogenic microRNAs.
Methods:
In a retrospective single-center study, multiphasic computed tomography examination (with arterial, portal, and urographic phases) was performed on 20 patients with clear cell renal cell carcinoma and computed tomography texture analysis parameters such as entropy, kurtosis, skewness, mean, and standard deviation of pixel distribution were measured using multiple filter settings. These quantitative data were correlated with the expression of selected microRNAs (miR-21-5p, miR-210-3p, miR-185-5p, miR-221-3p, miR-145-5p). Both the evaluations (microRNAs and computed tomography texture analysis) were performed on matched tumor and normal corticomedullar tissues of the same patients cohort.
Results:
In this pilot study, we evidenced that computed tomography texture analysis has robust parameters (eg, entropy, mean, standard deviation) to distinguish normal from pathological tissues. Moreover, a higher coefficient of determination between entropy and miR-21-5p expression was evidenced in tumor versus normal tissue. Interestingly, entropy and miR-21-5p show promising correlation in clear cell renal cell carcinoma opening to a radiogenomic strategy to improve clear cell renal cell carcinoma management.
Conclusion:
In this pilot study, a promising correlation between microRNAs and computed tomography texture analysis has been found in clear cell renal cell carcinoma. A clear cell renal cell carcinoma can benefit from noninvasive evaluation of texture parameters in adjunction to biopsy results. In particular, a promising correlation between entropy and miR-21-5p was found. |
| doi_str_mv | 10.1177/1533033819878458 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6767738</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sage_id>10.1177_1533033819878458</sage_id><sourcerecordid>2312521816</sourcerecordid><originalsourceid>FETCH-LOGICAL-c528t-18a29743c2416ce2659a15dbd8b3d7d6d332c0bb518f0eb811be4225f53c7cb53</originalsourceid><addsrcrecordid>eNp1kU1v1DAQhiNERUvhzglZ4lIOobEdf4QD0hIVqFRAWi1ny7Fng6vE3tpJaf8AvxuvtmxpJU4ejZ955-Mtile4eoexEKeYUVpRKnEjhayZfFIcbVPlNvd0H9f8sHie0mVVEc4pflYcUsx4TQg-Kn4vtXWhBx9GZxJyHrUD6IhaGAa0BK-HXdjqaFyG9HvUhhhh0JMLPqGPMP0C8Ghhr7U3YFG7Quej7p3v0ckKbqY5Alpkmdvk0lukvUVfnYlh-W2R0NnNJkJKWehFcbDWQ4KXd-9x8ePT2ar9Ul58_3zeLi5Kw4icSiw1aURNDakxN0A4azRmtrOyo1ZYbiklpuo6huW6gk5i3EHek60ZNcJ0jB4XH3a6m7kbwRrwU9SD2kQ36nirgnbq4Y93P1UfrhUXXAgqs8DJnUAMVzOkSY0umXwh7SHMSRHSNHUtGd32evMIvQxzzKfIFMWEESwxz1S1o_JRUoqw3g-DK7U1WT02OZe8_neJfcFfVzNQ7oCke7jv-l_BP_qdr1A</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2312521816</pqid></control><display><type>article</type><title>Radiogenomics in Clear Cell Renal Cell Carcinoma: Correlations Between Advanced CT Imaging (Texture Analysis) and MicroRNAs Expression</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Sage Journals GOLD Open Access 2024</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central</source><creator>Marigliano, Chiara ; Badia, Stefano ; Bellini, Davide ; Rengo, Marco ; Caruso, Damiano ; Tito, Claudia ; Miglietta, Selenia ; Palleschi, Giovanni ; Pastore, Antonio Luigi ; Carbone, Antonio ; Fazi, Francesco ; Petrozza, Vincenzo ; Laghi, Andrea</creator><creatorcontrib>Marigliano, Chiara ; Badia, Stefano ; Bellini, Davide ; Rengo, Marco ; Caruso, Damiano ; Tito, Claudia ; Miglietta, Selenia ; Palleschi, Giovanni ; Pastore, Antonio Luigi ; Carbone, Antonio ; Fazi, Francesco ; Petrozza, Vincenzo ; Laghi, Andrea</creatorcontrib><description>Purpose:
A relevant challenge for the improvement of clear cell renal cell carcinoma management could derive from the identification of novel molecular biomarkers that could greatly improve the diagnosis, prognosis, and treatment choice of these neoplasms. In this study, we investigate whether quantitative parameters obtained from computed tomography texture analysis may correlate with the expression of selected oncogenic microRNAs.
Methods:
In a retrospective single-center study, multiphasic computed tomography examination (with arterial, portal, and urographic phases) was performed on 20 patients with clear cell renal cell carcinoma and computed tomography texture analysis parameters such as entropy, kurtosis, skewness, mean, and standard deviation of pixel distribution were measured using multiple filter settings. These quantitative data were correlated with the expression of selected microRNAs (miR-21-5p, miR-210-3p, miR-185-5p, miR-221-3p, miR-145-5p). Both the evaluations (microRNAs and computed tomography texture analysis) were performed on matched tumor and normal corticomedullar tissues of the same patients cohort.
Results:
In this pilot study, we evidenced that computed tomography texture analysis has robust parameters (eg, entropy, mean, standard deviation) to distinguish normal from pathological tissues. Moreover, a higher coefficient of determination between entropy and miR-21-5p expression was evidenced in tumor versus normal tissue. Interestingly, entropy and miR-21-5p show promising correlation in clear cell renal cell carcinoma opening to a radiogenomic strategy to improve clear cell renal cell carcinoma management.
Conclusion:
In this pilot study, a promising correlation between microRNAs and computed tomography texture analysis has been found in clear cell renal cell carcinoma. A clear cell renal cell carcinoma can benefit from noninvasive evaluation of texture parameters in adjunction to biopsy results. In particular, a promising correlation between entropy and miR-21-5p was found.</description><identifier>ISSN: 1533-0346</identifier><identifier>EISSN: 1533-0338</identifier><identifier>DOI: 10.1177/1533033819878458</identifier><identifier>PMID: 31564221</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><subject>Aged ; Biomarkers ; Biomarkers, Tumor ; Carcinoma, Renal Cell - diagnostic imaging ; Carcinoma, Renal Cell - genetics ; Entropy ; Female ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Genomics - methods ; Humans ; Image Processing, Computer-Assisted ; Kidney cancer ; Kidney Neoplasms - diagnostic imaging ; Kidney Neoplasms - genetics ; Male ; MicroRNAs ; MicroRNAs - genetics ; Middle Aged ; Neoplasia ; Neoplasm Staging ; Original ; Renal cell carcinoma ; Retrospective Studies ; Tomography ; Tomography, X-Ray Computed ; Transcriptome</subject><ispartof>Technology in cancer research & treatment, 2019, Vol.18, p.1533033819878458-1533033819878458</ispartof><rights>The Author(s) 2019</rights><rights>The Author(s) 2019. This work is licensed under the Creative Commons Attribution – Non-Commercial License http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2019 2019 SAGE Publications</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c528t-18a29743c2416ce2659a15dbd8b3d7d6d332c0bb518f0eb811be4225f53c7cb53</citedby><cites>FETCH-LOGICAL-c528t-18a29743c2416ce2659a15dbd8b3d7d6d332c0bb518f0eb811be4225f53c7cb53</cites><orcidid>0000-0002-3592-4073 ; 0000-0001-9087-5692</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/PMC6767738/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6767738/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,861,882,4010,21947,27834,27904,27905,27906,44926,45314,53772,53774</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31564221$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Marigliano, Chiara</creatorcontrib><creatorcontrib>Badia, Stefano</creatorcontrib><creatorcontrib>Bellini, Davide</creatorcontrib><creatorcontrib>Rengo, Marco</creatorcontrib><creatorcontrib>Caruso, Damiano</creatorcontrib><creatorcontrib>Tito, Claudia</creatorcontrib><creatorcontrib>Miglietta, Selenia</creatorcontrib><creatorcontrib>Palleschi, Giovanni</creatorcontrib><creatorcontrib>Pastore, Antonio Luigi</creatorcontrib><creatorcontrib>Carbone, Antonio</creatorcontrib><creatorcontrib>Fazi, Francesco</creatorcontrib><creatorcontrib>Petrozza, Vincenzo</creatorcontrib><creatorcontrib>Laghi, Andrea</creatorcontrib><title>Radiogenomics in Clear Cell Renal Cell Carcinoma: Correlations Between Advanced CT Imaging (Texture Analysis) and MicroRNAs Expression</title><title>Technology in cancer research & treatment</title><addtitle>Technol Cancer Res Treat</addtitle><description>Purpose:
A relevant challenge for the improvement of clear cell renal cell carcinoma management could derive from the identification of novel molecular biomarkers that could greatly improve the diagnosis, prognosis, and treatment choice of these neoplasms. In this study, we investigate whether quantitative parameters obtained from computed tomography texture analysis may correlate with the expression of selected oncogenic microRNAs.
Methods:
In a retrospective single-center study, multiphasic computed tomography examination (with arterial, portal, and urographic phases) was performed on 20 patients with clear cell renal cell carcinoma and computed tomography texture analysis parameters such as entropy, kurtosis, skewness, mean, and standard deviation of pixel distribution were measured using multiple filter settings. These quantitative data were correlated with the expression of selected microRNAs (miR-21-5p, miR-210-3p, miR-185-5p, miR-221-3p, miR-145-5p). Both the evaluations (microRNAs and computed tomography texture analysis) were performed on matched tumor and normal corticomedullar tissues of the same patients cohort.
Results:
In this pilot study, we evidenced that computed tomography texture analysis has robust parameters (eg, entropy, mean, standard deviation) to distinguish normal from pathological tissues. Moreover, a higher coefficient of determination between entropy and miR-21-5p expression was evidenced in tumor versus normal tissue. Interestingly, entropy and miR-21-5p show promising correlation in clear cell renal cell carcinoma opening to a radiogenomic strategy to improve clear cell renal cell carcinoma management.
Conclusion:
In this pilot study, a promising correlation between microRNAs and computed tomography texture analysis has been found in clear cell renal cell carcinoma. A clear cell renal cell carcinoma can benefit from noninvasive evaluation of texture parameters in adjunction to biopsy results. In particular, a promising correlation between entropy and miR-21-5p was found.</description><subject>Aged</subject><subject>Biomarkers</subject><subject>Biomarkers, Tumor</subject><subject>Carcinoma, Renal Cell - diagnostic imaging</subject><subject>Carcinoma, Renal Cell - genetics</subject><subject>Entropy</subject><subject>Female</subject><subject>Gene Expression Profiling</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Genomics - methods</subject><subject>Humans</subject><subject>Image Processing, Computer-Assisted</subject><subject>Kidney cancer</subject><subject>Kidney Neoplasms - diagnostic imaging</subject><subject>Kidney Neoplasms - genetics</subject><subject>Male</subject><subject>MicroRNAs</subject><subject>MicroRNAs - genetics</subject><subject>Middle Aged</subject><subject>Neoplasia</subject><subject>Neoplasm Staging</subject><subject>Original</subject><subject>Renal cell carcinoma</subject><subject>Retrospective Studies</subject><subject>Tomography</subject><subject>Tomography, X-Ray Computed</subject><subject>Transcriptome</subject><issn>1533-0346</issn><issn>1533-0338</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>AFRWT</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp1kU1v1DAQhiNERUvhzglZ4lIOobEdf4QD0hIVqFRAWi1ny7Fng6vE3tpJaf8AvxuvtmxpJU4ejZ955-Mtile4eoexEKeYUVpRKnEjhayZfFIcbVPlNvd0H9f8sHie0mVVEc4pflYcUsx4TQg-Kn4vtXWhBx9GZxJyHrUD6IhaGAa0BK-HXdjqaFyG9HvUhhhh0JMLPqGPMP0C8Ghhr7U3YFG7Quej7p3v0ckKbqY5Alpkmdvk0lukvUVfnYlh-W2R0NnNJkJKWehFcbDWQ4KXd-9x8ePT2ar9Ul58_3zeLi5Kw4icSiw1aURNDakxN0A4azRmtrOyo1ZYbiklpuo6huW6gk5i3EHek60ZNcJ0jB4XH3a6m7kbwRrwU9SD2kQ36nirgnbq4Y93P1UfrhUXXAgqs8DJnUAMVzOkSY0umXwh7SHMSRHSNHUtGd32evMIvQxzzKfIFMWEESwxz1S1o_JRUoqw3g-DK7U1WT02OZe8_neJfcFfVzNQ7oCke7jv-l_BP_qdr1A</recordid><startdate>2019</startdate><enddate>2019</enddate><creator>Marigliano, Chiara</creator><creator>Badia, Stefano</creator><creator>Bellini, Davide</creator><creator>Rengo, Marco</creator><creator>Caruso, Damiano</creator><creator>Tito, Claudia</creator><creator>Miglietta, Selenia</creator><creator>Palleschi, Giovanni</creator><creator>Pastore, Antonio Luigi</creator><creator>Carbone, Antonio</creator><creator>Fazi, Francesco</creator><creator>Petrozza, Vincenzo</creator><creator>Laghi, Andrea</creator><general>SAGE Publications</general><general>Sage Publications Ltd</general><scope>AFRWT</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>3V.</scope><scope>7TO</scope><scope>7X7</scope><scope>7XB</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-3592-4073</orcidid><orcidid>https://orcid.org/0000-0001-9087-5692</orcidid></search><sort><creationdate>2019</creationdate><title>Radiogenomics in Clear Cell Renal Cell Carcinoma: Correlations Between Advanced CT Imaging (Texture Analysis) and MicroRNAs Expression</title><author>Marigliano, Chiara ; Badia, Stefano ; Bellini, Davide ; Rengo, Marco ; Caruso, Damiano ; Tito, Claudia ; Miglietta, Selenia ; Palleschi, Giovanni ; Pastore, Antonio Luigi ; Carbone, Antonio ; Fazi, Francesco ; Petrozza, Vincenzo ; Laghi, Andrea</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c528t-18a29743c2416ce2659a15dbd8b3d7d6d332c0bb518f0eb811be4225f53c7cb53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Aged</topic><topic>Biomarkers</topic><topic>Biomarkers, Tumor</topic><topic>Carcinoma, Renal Cell - diagnostic imaging</topic><topic>Carcinoma, Renal Cell - genetics</topic><topic>Entropy</topic><topic>Female</topic><topic>Gene Expression Profiling</topic><topic>Gene Expression Regulation, Neoplastic</topic><topic>Genomics - methods</topic><topic>Humans</topic><topic>Image Processing, Computer-Assisted</topic><topic>Kidney cancer</topic><topic>Kidney Neoplasms - diagnostic imaging</topic><topic>Kidney Neoplasms - genetics</topic><topic>Male</topic><topic>MicroRNAs</topic><topic>MicroRNAs - genetics</topic><topic>Middle Aged</topic><topic>Neoplasia</topic><topic>Neoplasm Staging</topic><topic>Original</topic><topic>Renal cell carcinoma</topic><topic>Retrospective Studies</topic><topic>Tomography</topic><topic>Tomography, X-Ray Computed</topic><topic>Transcriptome</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Marigliano, Chiara</creatorcontrib><creatorcontrib>Badia, Stefano</creatorcontrib><creatorcontrib>Bellini, Davide</creatorcontrib><creatorcontrib>Rengo, Marco</creatorcontrib><creatorcontrib>Caruso, Damiano</creatorcontrib><creatorcontrib>Tito, Claudia</creatorcontrib><creatorcontrib>Miglietta, Selenia</creatorcontrib><creatorcontrib>Palleschi, Giovanni</creatorcontrib><creatorcontrib>Pastore, Antonio Luigi</creatorcontrib><creatorcontrib>Carbone, Antonio</creatorcontrib><creatorcontrib>Fazi, Francesco</creatorcontrib><creatorcontrib>Petrozza, Vincenzo</creatorcontrib><creatorcontrib>Laghi, Andrea</creatorcontrib><collection>Sage Journals GOLD Open Access 2024</collection><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>Oncogenes and Growth Factors Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</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>ProQuest Central Essentials</collection><collection>ProQuest Central</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>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Publicly Available Content Database</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>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Technology in cancer research & treatment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Marigliano, Chiara</au><au>Badia, Stefano</au><au>Bellini, Davide</au><au>Rengo, Marco</au><au>Caruso, Damiano</au><au>Tito, Claudia</au><au>Miglietta, Selenia</au><au>Palleschi, Giovanni</au><au>Pastore, Antonio Luigi</au><au>Carbone, Antonio</au><au>Fazi, Francesco</au><au>Petrozza, Vincenzo</au><au>Laghi, Andrea</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Radiogenomics in Clear Cell Renal Cell Carcinoma: Correlations Between Advanced CT Imaging (Texture Analysis) and MicroRNAs Expression</atitle><jtitle>Technology in cancer research & treatment</jtitle><addtitle>Technol Cancer Res Treat</addtitle><date>2019</date><risdate>2019</risdate><volume>18</volume><spage>1533033819878458</spage><epage>1533033819878458</epage><pages>1533033819878458-1533033819878458</pages><issn>1533-0346</issn><eissn>1533-0338</eissn><abstract>Purpose:
A relevant challenge for the improvement of clear cell renal cell carcinoma management could derive from the identification of novel molecular biomarkers that could greatly improve the diagnosis, prognosis, and treatment choice of these neoplasms. In this study, we investigate whether quantitative parameters obtained from computed tomography texture analysis may correlate with the expression of selected oncogenic microRNAs.
Methods:
In a retrospective single-center study, multiphasic computed tomography examination (with arterial, portal, and urographic phases) was performed on 20 patients with clear cell renal cell carcinoma and computed tomography texture analysis parameters such as entropy, kurtosis, skewness, mean, and standard deviation of pixel distribution were measured using multiple filter settings. These quantitative data were correlated with the expression of selected microRNAs (miR-21-5p, miR-210-3p, miR-185-5p, miR-221-3p, miR-145-5p). Both the evaluations (microRNAs and computed tomography texture analysis) were performed on matched tumor and normal corticomedullar tissues of the same patients cohort.
Results:
In this pilot study, we evidenced that computed tomography texture analysis has robust parameters (eg, entropy, mean, standard deviation) to distinguish normal from pathological tissues. Moreover, a higher coefficient of determination between entropy and miR-21-5p expression was evidenced in tumor versus normal tissue. Interestingly, entropy and miR-21-5p show promising correlation in clear cell renal cell carcinoma opening to a radiogenomic strategy to improve clear cell renal cell carcinoma management.
Conclusion:
In this pilot study, a promising correlation between microRNAs and computed tomography texture analysis has been found in clear cell renal cell carcinoma. A clear cell renal cell carcinoma can benefit from noninvasive evaluation of texture parameters in adjunction to biopsy results. In particular, a promising correlation between entropy and miR-21-5p was found.</abstract><cop>Los Angeles, CA</cop><pub>SAGE Publications</pub><pmid>31564221</pmid><doi>10.1177/1533033819878458</doi><orcidid>https://orcid.org/0000-0002-3592-4073</orcidid><orcidid>https://orcid.org/0000-0001-9087-5692</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Aged Biomarkers Biomarkers, Tumor Carcinoma, Renal Cell - diagnostic imaging Carcinoma, Renal Cell - genetics Entropy Female Gene Expression Profiling Gene Expression Regulation, Neoplastic Genomics - methods Humans Image Processing, Computer-Assisted Kidney cancer Kidney Neoplasms - diagnostic imaging Kidney Neoplasms - genetics Male MicroRNAs MicroRNAs - genetics Middle Aged Neoplasia Neoplasm Staging Original Renal cell carcinoma Retrospective Studies Tomography Tomography, X-Ray Computed Transcriptome |
| title | Radiogenomics in Clear Cell Renal Cell Carcinoma: Correlations Between Advanced CT Imaging (Texture Analysis) and MicroRNAs Expression |
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