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Development of a long non-coding RNA signature for prediction of response to neoadjuvant chemoradiotherapy in locally advanced rectal adenocarcinoma
Standard treatment for locally advanced rectal adenocarcinoma (LARC) includes a combination of chemotherapy with pyrimidine analogues, such as capecitabine, and radiation therapy, followed by surgery. Currently no clinically useful genomic predictors of benefit from neoadjuvant chemoradiotherapy (nC...
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| Published in: | PloS one 2020-02, Vol.15 (2), p.e0226595 |
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| creator | Ferrando, Lorenzo Cirmena, Gabriella Garuti, Anna Scabini, Stefano Grillo, Federica Mastracci, Luca Isnaldi, Edoardo Marrone, Ciro Gonella, Roberta Murialdo, Roberto Fiocca, Roberto Romairone, Emanuele Ballestrero, Alberto Zoppoli, Gabriele |
| description | Standard treatment for locally advanced rectal adenocarcinoma (LARC) includes a combination of chemotherapy with pyrimidine analogues, such as capecitabine, and radiation therapy, followed by surgery. Currently no clinically useful genomic predictors of benefit from neoadjuvant chemoradiotherapy (nCRT) exist for LARC. In this study we assessed the expression of 8,127 long noncoding RNAs (lncRNAs), poorly studied in LARC, to infer their ability in classifying patients' pathological complete response (pCR). We collected and analyzed, using lncRNA-specific Agilent microarrays a consecutive series of 61 LARC cases undergoing nCRT. Potential lncRNA predictors in responders and non-responders to nCRT were identified with LASSO regression, and a model was optimized using k-fold cross-validation after selection of the three most informative lncRNA. 11 lncRNAs were differentially expressed with false discovery rate < 0.01 between responders and non-responders to NACT. We identified lnc-KLF7-1, lnc-MAB21L2-1, and LINC00324 as the most promising variable subset for classification building. Overall sensitivity and specificity were 0.91 and 0.94 respectively, with an AUC of our ROC curve = 0.93. Our study shows for the first time that lncRNAs can accurately predict response in LARC undergoing nCRT. Our three-lncRNA based signature must be independently validated and further analyses must be conducted to fully understand the biological role of the identified signature, but our results suggest lncRNAs may be an ideal biomarker for response prediction in the studied setting. |
| doi_str_mv | 10.1371/journal.pone.0226595 |
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Currently no clinically useful genomic predictors of benefit from neoadjuvant chemoradiotherapy (nCRT) exist for LARC. In this study we assessed the expression of 8,127 long noncoding RNAs (lncRNAs), poorly studied in LARC, to infer their ability in classifying patients' pathological complete response (pCR). We collected and analyzed, using lncRNA-specific Agilent microarrays a consecutive series of 61 LARC cases undergoing nCRT. Potential lncRNA predictors in responders and non-responders to nCRT were identified with LASSO regression, and a model was optimized using k-fold cross-validation after selection of the three most informative lncRNA. 11 lncRNAs were differentially expressed with false discovery rate < 0.01 between responders and non-responders to NACT. We identified lnc-KLF7-1, lnc-MAB21L2-1, and LINC00324 as the most promising variable subset for classification building. Overall sensitivity and specificity were 0.91 and 0.94 respectively, with an AUC of our ROC curve = 0.93. Our study shows for the first time that lncRNAs can accurately predict response in LARC undergoing nCRT. Our three-lncRNA based signature must be independently validated and further analyses must be conducted to fully understand the biological role of the identified signature, but our results suggest lncRNAs may be an ideal biomarker for response prediction in the studied setting.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0226595</identifier><identifier>PMID: 32023246</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adenocarcinoma ; Adenocarcinoma - genetics ; Adenocarcinoma - pathology ; Adenocarcinoma - therapy ; Aged ; Analysis ; Biology and life sciences ; Biomarkers ; Cancer treatment ; Chemoradiotherapy ; Chemotherapy ; Classification ; Colorectal cancer ; Consent ; Female ; Gene expression ; Gene Expression Regulation, Neoplastic ; Hospital patients ; Humans ; Instrument industry (Equipment) ; Internal medicine ; Male ; Medicine ; Medicine and Health Sciences ; Middle Aged ; Neoadjuvant Therapy ; Neoplasm Recurrence, Local - genetics ; Neoplasm Recurrence, Local - pathology ; Neoplasm Recurrence, Local - therapy ; NMR ; Non-coding RNA ; Nuclear magnetic resonance ; Principal Component Analysis ; Pyrimidines ; Radiation ; Radiation (Physics) ; Radiation therapy ; Radiotherapy ; Rectal Neoplasms - genetics ; Rectal Neoplasms - pathology ; Rectal Neoplasms - therapy ; Rectum ; Regression analysis ; Regression models ; Research and Analysis Methods ; RNA ; RNA, Long Noncoding - genetics ; RNA, Long Noncoding - metabolism ; Setting (Literature) ; Support Vector Machine ; Surgery ; Surgical outcomes ; Time</subject><ispartof>PloS one, 2020-02, Vol.15 (2), p.e0226595</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Ferrando et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2020 Ferrando et al 2020 Ferrando et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c725t-6c6eed48fac752a5741840f22df18945f5ae88405c281dc387bd72193727e04e3</citedby><cites>FETCH-LOGICAL-c725t-6c6eed48fac752a5741840f22df18945f5ae88405c281dc387bd72193727e04e3</cites><orcidid>0000-0002-4025-7930 ; 0000-0002-1055-7254 ; 0000-0002-1619-1708</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2351474453/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2351474453?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,315,733,786,790,891,25783,27957,27958,37047,44625,53827,53829,75483</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32023246$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Batra, Surinder K.</contributor><creatorcontrib>Ferrando, Lorenzo</creatorcontrib><creatorcontrib>Cirmena, Gabriella</creatorcontrib><creatorcontrib>Garuti, Anna</creatorcontrib><creatorcontrib>Scabini, Stefano</creatorcontrib><creatorcontrib>Grillo, Federica</creatorcontrib><creatorcontrib>Mastracci, Luca</creatorcontrib><creatorcontrib>Isnaldi, Edoardo</creatorcontrib><creatorcontrib>Marrone, Ciro</creatorcontrib><creatorcontrib>Gonella, Roberta</creatorcontrib><creatorcontrib>Murialdo, Roberto</creatorcontrib><creatorcontrib>Fiocca, Roberto</creatorcontrib><creatorcontrib>Romairone, Emanuele</creatorcontrib><creatorcontrib>Ballestrero, Alberto</creatorcontrib><creatorcontrib>Zoppoli, Gabriele</creatorcontrib><title>Development of a long non-coding RNA signature for prediction of response to neoadjuvant chemoradiotherapy in locally advanced rectal adenocarcinoma</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Standard treatment for locally advanced rectal adenocarcinoma (LARC) includes a combination of chemotherapy with pyrimidine analogues, such as capecitabine, and radiation therapy, followed by surgery. Currently no clinically useful genomic predictors of benefit from neoadjuvant chemoradiotherapy (nCRT) exist for LARC. In this study we assessed the expression of 8,127 long noncoding RNAs (lncRNAs), poorly studied in LARC, to infer their ability in classifying patients' pathological complete response (pCR). We collected and analyzed, using lncRNA-specific Agilent microarrays a consecutive series of 61 LARC cases undergoing nCRT. Potential lncRNA predictors in responders and non-responders to nCRT were identified with LASSO regression, and a model was optimized using k-fold cross-validation after selection of the three most informative lncRNA. 11 lncRNAs were differentially expressed with false discovery rate < 0.01 between responders and non-responders to NACT. We identified lnc-KLF7-1, lnc-MAB21L2-1, and LINC00324 as the most promising variable subset for classification building. Overall sensitivity and specificity were 0.91 and 0.94 respectively, with an AUC of our ROC curve = 0.93. Our study shows for the first time that lncRNAs can accurately predict response in LARC undergoing nCRT. Our three-lncRNA based signature must be independently validated and further analyses must be conducted to fully understand the biological role of the identified signature, but our results suggest lncRNAs may be an ideal biomarker for response prediction in the studied setting.</description><subject>Adenocarcinoma</subject><subject>Adenocarcinoma - genetics</subject><subject>Adenocarcinoma - pathology</subject><subject>Adenocarcinoma - therapy</subject><subject>Aged</subject><subject>Analysis</subject><subject>Biology and life sciences</subject><subject>Biomarkers</subject><subject>Cancer treatment</subject><subject>Chemoradiotherapy</subject><subject>Chemotherapy</subject><subject>Classification</subject><subject>Colorectal cancer</subject><subject>Consent</subject><subject>Female</subject><subject>Gene expression</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Hospital patients</subject><subject>Humans</subject><subject>Instrument industry 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Anna</au><au>Scabini, Stefano</au><au>Grillo, Federica</au><au>Mastracci, Luca</au><au>Isnaldi, Edoardo</au><au>Marrone, Ciro</au><au>Gonella, Roberta</au><au>Murialdo, Roberto</au><au>Fiocca, Roberto</au><au>Romairone, Emanuele</au><au>Ballestrero, Alberto</au><au>Zoppoli, Gabriele</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development of a long non-coding RNA signature for prediction of response to neoadjuvant chemoradiotherapy in locally advanced rectal adenocarcinoma</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2020-02-05</date><risdate>2020</risdate><volume>15</volume><issue>2</issue><spage>e0226595</spage><pages>e0226595-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><notes>Competing Interests: The authors have declared that no competing interests exist.</notes><abstract>Standard treatment for locally advanced rectal adenocarcinoma (LARC) includes a combination of chemotherapy with pyrimidine analogues, such as capecitabine, and radiation therapy, followed by surgery. Currently no clinically useful genomic predictors of benefit from neoadjuvant chemoradiotherapy (nCRT) exist for LARC. In this study we assessed the expression of 8,127 long noncoding RNAs (lncRNAs), poorly studied in LARC, to infer their ability in classifying patients' pathological complete response (pCR). We collected and analyzed, using lncRNA-specific Agilent microarrays a consecutive series of 61 LARC cases undergoing nCRT. Potential lncRNA predictors in responders and non-responders to nCRT were identified with LASSO regression, and a model was optimized using k-fold cross-validation after selection of the three most informative lncRNA. 11 lncRNAs were differentially expressed with false discovery rate < 0.01 between responders and non-responders to NACT. We identified lnc-KLF7-1, lnc-MAB21L2-1, and LINC00324 as the most promising variable subset for classification building. Overall sensitivity and specificity were 0.91 and 0.94 respectively, with an AUC of our ROC curve = 0.93. Our study shows for the first time that lncRNAs can accurately predict response in LARC undergoing nCRT. Our three-lncRNA based signature must be independently validated and further analyses must be conducted to fully understand the biological role of the identified signature, but our results suggest lncRNAs may be an ideal biomarker for response prediction in the studied setting.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>32023246</pmid><doi>10.1371/journal.pone.0226595</doi><tpages>e0226595</tpages><orcidid>https://orcid.org/0000-0002-4025-7930</orcidid><orcidid>https://orcid.org/0000-0002-1055-7254</orcidid><orcidid>https://orcid.org/0000-0002-1619-1708</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2020-02, Vol.15 (2), p.e0226595 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2351474453 |
| source | Publicly Available Content Database; PubMed Central |
| subjects | Adenocarcinoma Adenocarcinoma - genetics Adenocarcinoma - pathology Adenocarcinoma - therapy Aged Analysis Biology and life sciences Biomarkers Cancer treatment Chemoradiotherapy Chemotherapy Classification Colorectal cancer Consent Female Gene expression Gene Expression Regulation, Neoplastic Hospital patients Humans Instrument industry (Equipment) Internal medicine Male Medicine Medicine and Health Sciences Middle Aged Neoadjuvant Therapy Neoplasm Recurrence, Local - genetics Neoplasm Recurrence, Local - pathology Neoplasm Recurrence, Local - therapy NMR Non-coding RNA Nuclear magnetic resonance Principal Component Analysis Pyrimidines Radiation Radiation (Physics) Radiation therapy Radiotherapy Rectal Neoplasms - genetics Rectal Neoplasms - pathology Rectal Neoplasms - therapy Rectum Regression analysis Regression models Research and Analysis Methods RNA RNA, Long Noncoding - genetics RNA, Long Noncoding - metabolism Setting (Literature) Support Vector Machine Surgery Surgical outcomes Time |
| title | Development of a long non-coding RNA signature for prediction of response to neoadjuvant chemoradiotherapy in locally advanced rectal adenocarcinoma |
| url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-09-21T17%3A03%3A20IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Development%20of%20a%20long%20non-coding%20RNA%20signature%20for%20prediction%20of%20response%20to%20neoadjuvant%20chemoradiotherapy%20in%20locally%20advanced%20rectal%20adenocarcinoma&rft.jtitle=PloS%20one&rft.au=Ferrando,%20Lorenzo&rft.date=2020-02-05&rft.volume=15&rft.issue=2&rft.spage=e0226595&rft.pages=e0226595-&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0226595&rft_dat=%3Cgale_plos_%3EA613247713%3C/gale_plos_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c725t-6c6eed48fac752a5741840f22df18945f5ae88405c281dc387bd72193727e04e3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2351474453&rft_id=info:pmid/32023246&rft_galeid=A613247713&rfr_iscdi=true |