A Signature of 14 Long Non-Coding RNAs (lncRNAs) as a Step towards Precision Diagnosis for NSCLC
LncRNAs have arisen as new players in the world of non-coding RNA. Disrupted expression of these molecules can be tightly linked to the onset, promotion and progression of cancer. The present study estimated the usefulness of 14 lncRNAs (HAGLR, ADAMTS9-AS2, LINC00261, MCM3AP-AS1, TP53TG1, C14orf132,...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-01-01
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| Series: | Cancers |
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| Online Access: | https://www.mdpi.com/2072-6694/14/2/439 |
| _version_ | 1797495284365787136 |
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| author | Anetta Sulewska Jacek Niklinski Radoslaw Charkiewicz Piotr Karabowicz Przemyslaw Biecek Hubert Baniecki Oksana Kowalczuk Miroslaw Kozlowski Patrycja Modzelewska Piotr Majewski Elzbieta Tryniszewska Joanna Reszec Zofia Dzieciol-Anikiej Cezary Piwkowski Robert Gryczka Rodryg Ramlau |
| author_facet | Anetta Sulewska Jacek Niklinski Radoslaw Charkiewicz Piotr Karabowicz Przemyslaw Biecek Hubert Baniecki Oksana Kowalczuk Miroslaw Kozlowski Patrycja Modzelewska Piotr Majewski Elzbieta Tryniszewska Joanna Reszec Zofia Dzieciol-Anikiej Cezary Piwkowski Robert Gryczka Rodryg Ramlau |
| author_sort | Anetta Sulewska |
| collection | DOAJ |
| description | LncRNAs have arisen as new players in the world of non-coding RNA. Disrupted expression of these molecules can be tightly linked to the onset, promotion and progression of cancer. The present study estimated the usefulness of 14 lncRNAs (HAGLR, ADAMTS9-AS2, LINC00261, MCM3AP-AS1, TP53TG1, C14orf132, LINC00968, LINC00312, TP73-AS1, LOC344887, LINC00673, SOX2-OT, AFAP1-AS1, LOC730101) for early detection of non-small-cell lung cancer (NSCLC). The total RNA was isolated from paired fresh-frozen cancerous and noncancerous lung tissue from 92 NSCLC patients diagnosed with either adenocarcinoma (LUAD) or lung squamous cell carcinoma (LUSC). The expression level of lncRNAs was evaluated by a quantitative real-time PCR (qPCR). Based on Ct and delta Ct values, logistic regression and gradient boosting decision tree classifiers were built. The latter is a novel, advanced machine learning algorithm with great potential in medical science. The established predictive models showed that a set of 14 lncRNAs accurately discriminates cancerous from noncancerous lung tissues (AUC value of 0.98 ± 0.01) and NSCLC subtypes (AUC value of 0.84 ± 0.09), although the expression of a few molecules was statistically insignificant (SOX2-OT, AFAP1-AS1 and LOC730101 for tumor vs. normal tissue; and TP53TG1, C14orf132, LINC00968 and LOC730101 for LUAD vs. LUSC). However for subtypes discrimination, the simplified logistic regression model based on the four variables (delta Ct AFAP1-AS1, Ct SOX2-OT, Ct LINC00261, and delta Ct LINC00673) had even stronger diagnostic potential than the original one (AUC value of 0.88 ± 0.07). Our results demonstrate that the 14 lncRNA signature can be an auxiliary tool to endorse and complement the histological diagnosis of non-small-cell lung cancer. |
| first_indexed | 2024-03-10T01:46:36Z |
| format | Article |
| id | doaj.art-d98ee682315544098b361a9f5e75872d |
| institution | Directory Open Access Journal |
| issn | 2072-6694 |
| language | English |
| last_indexed | 2024-03-10T01:46:36Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cancers |
| spelling | doaj.art-d98ee682315544098b361a9f5e75872d2023-11-23T13:15:04ZengMDPI AGCancers2072-66942022-01-0114243910.3390/cancers14020439A Signature of 14 Long Non-Coding RNAs (lncRNAs) as a Step towards Precision Diagnosis for NSCLCAnetta Sulewska0Jacek Niklinski1Radoslaw Charkiewicz2Piotr Karabowicz3Przemyslaw Biecek4Hubert Baniecki5Oksana Kowalczuk6Miroslaw Kozlowski7Patrycja Modzelewska8Piotr Majewski9Elzbieta Tryniszewska10Joanna Reszec11Zofia Dzieciol-Anikiej12Cezary Piwkowski13Robert Gryczka14Rodryg Ramlau15Department of Clinical Molecular Biology, Medical University of Bialystok, 15-269 Bialystok, PolandDepartment of Clinical Molecular Biology, Medical University of Bialystok, 15-269 Bialystok, PolandDepartment of Clinical Molecular Biology, Medical University of Bialystok, 15-269 Bialystok, PolandBiobank, Medical University of Bialystok, 15-269 Bialystok, PolandFaculty of Mathematics and Information Science, Warsaw University of Technology, 00-662 Warsaw, PolandFaculty of Mathematics and Information Science, Warsaw University of Technology, 00-662 Warsaw, PolandDepartment of Clinical Molecular Biology, Medical University of Bialystok, 15-269 Bialystok, PolandDepartment of Thoracic Surgery, Medical University of Bialystok, 15-269 Bialystok, PolandBiobank, Medical University of Bialystok, 15-269 Bialystok, PolandDepartment of Microbiological Diagnostics and Infectious Immunology, Medical University of Bialystok, 15-269 Bialystok, PolandDepartment of Microbiological Diagnostics and Infectious Immunology, Medical University of Bialystok, 15-269 Bialystok, PolandBiobank, Medical University of Bialystok, 15-269 Bialystok, PolandBiobank, Medical University of Bialystok, 15-269 Bialystok, PolandDepartment of Thoracic Surgery, Poznan University of Medical Sciences, 60-569 Poznan, PolandDepartment of Oncology, Poznan University of Medical Sciences, 60-569 Poznan, PolandDepartment of Oncology, Poznan University of Medical Sciences, 60-569 Poznan, PolandLncRNAs have arisen as new players in the world of non-coding RNA. Disrupted expression of these molecules can be tightly linked to the onset, promotion and progression of cancer. The present study estimated the usefulness of 14 lncRNAs (HAGLR, ADAMTS9-AS2, LINC00261, MCM3AP-AS1, TP53TG1, C14orf132, LINC00968, LINC00312, TP73-AS1, LOC344887, LINC00673, SOX2-OT, AFAP1-AS1, LOC730101) for early detection of non-small-cell lung cancer (NSCLC). The total RNA was isolated from paired fresh-frozen cancerous and noncancerous lung tissue from 92 NSCLC patients diagnosed with either adenocarcinoma (LUAD) or lung squamous cell carcinoma (LUSC). The expression level of lncRNAs was evaluated by a quantitative real-time PCR (qPCR). Based on Ct and delta Ct values, logistic regression and gradient boosting decision tree classifiers were built. The latter is a novel, advanced machine learning algorithm with great potential in medical science. The established predictive models showed that a set of 14 lncRNAs accurately discriminates cancerous from noncancerous lung tissues (AUC value of 0.98 ± 0.01) and NSCLC subtypes (AUC value of 0.84 ± 0.09), although the expression of a few molecules was statistically insignificant (SOX2-OT, AFAP1-AS1 and LOC730101 for tumor vs. normal tissue; and TP53TG1, C14orf132, LINC00968 and LOC730101 for LUAD vs. LUSC). However for subtypes discrimination, the simplified logistic regression model based on the four variables (delta Ct AFAP1-AS1, Ct SOX2-OT, Ct LINC00261, and delta Ct LINC00673) had even stronger diagnostic potential than the original one (AUC value of 0.88 ± 0.07). Our results demonstrate that the 14 lncRNA signature can be an auxiliary tool to endorse and complement the histological diagnosis of non-small-cell lung cancer.https://www.mdpi.com/2072-6694/14/2/439lncRNAlung cancerdiagnosisbiomarkersepigenetics |
| spellingShingle | Anetta Sulewska Jacek Niklinski Radoslaw Charkiewicz Piotr Karabowicz Przemyslaw Biecek Hubert Baniecki Oksana Kowalczuk Miroslaw Kozlowski Patrycja Modzelewska Piotr Majewski Elzbieta Tryniszewska Joanna Reszec Zofia Dzieciol-Anikiej Cezary Piwkowski Robert Gryczka Rodryg Ramlau A Signature of 14 Long Non-Coding RNAs (lncRNAs) as a Step towards Precision Diagnosis for NSCLC Cancers lncRNA lung cancer diagnosis biomarkers epigenetics |
| title | A Signature of 14 Long Non-Coding RNAs (lncRNAs) as a Step towards Precision Diagnosis for NSCLC |
| title_full | A Signature of 14 Long Non-Coding RNAs (lncRNAs) as a Step towards Precision Diagnosis for NSCLC |
| title_fullStr | A Signature of 14 Long Non-Coding RNAs (lncRNAs) as a Step towards Precision Diagnosis for NSCLC |
| title_full_unstemmed | A Signature of 14 Long Non-Coding RNAs (lncRNAs) as a Step towards Precision Diagnosis for NSCLC |
| title_short | A Signature of 14 Long Non-Coding RNAs (lncRNAs) as a Step towards Precision Diagnosis for NSCLC |
| title_sort | signature of 14 long non coding rnas lncrnas as a step towards precision diagnosis for nsclc |
| topic | lncRNA lung cancer diagnosis biomarkers epigenetics |
| url | https://www.mdpi.com/2072-6694/14/2/439 |
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