دورية أكاديمية
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Comparison of the Metastasis Predictive Potential of mRNA and Long Non-Coding RNA Profiling in Systemically Untreated Breast Cancer.

التفاصيل البيبلوغرافية
العنوان: Comparison of the Metastasis Predictive Potential of mRNA and Long Non-Coding RNA Profiling in Systemically Untreated Breast Cancer.
المؤلفون: Do TTN; Department of Clinical Genetics, Odense University Hospital, 5000 Odense C, Denmark.; Human Genetics, Department of Clinical Research, University of Southern Denmark, 5000 Odense C, Denmark., Block I; Department of Clinical Genetics, Odense University Hospital, 5000 Odense C, Denmark., Burton M; Department of Clinical Genetics, Odense University Hospital, 5000 Odense C, Denmark.; Human Genetics, Department of Clinical Research, University of Southern Denmark, 5000 Odense C, Denmark.; Clinical Genome Center, University of Southern Denmark & Region of Southern Denmark, 5000 Odense C, Denmark., Sørensen KP; Department of Clinical Genetics, Odense University Hospital, 5000 Odense C, Denmark., Larsen MJ; Department of Clinical Genetics, Odense University Hospital, 5000 Odense C, Denmark.; Human Genetics, Department of Clinical Research, University of Southern Denmark, 5000 Odense C, Denmark., Bak M; Department of Pathology, Odense University Hospital, 5000 Odense C, Denmark.; Department of Pathology, Hospital of Southwest Jutland, 6700 Esbjerg, Denmark., Cold S; Department of Oncology, Odense University Hospital, 5000 Odense C, Denmark., Thomassen M; Department of Clinical Genetics, Odense University Hospital, 5000 Odense C, Denmark.; Human Genetics, Department of Clinical Research, University of Southern Denmark, 5000 Odense C, Denmark.; Clinical Genome Center, University of Southern Denmark & Region of Southern Denmark, 5000 Odense C, Denmark., Tan Q; Human Genetics, Department of Clinical Research, University of Southern Denmark, 5000 Odense C, Denmark.; Epidemiology, Department of Public Health, University of Southern Denmark, 5000 Odense C, Denmark., Kruse TA; Department of Clinical Genetics, Odense University Hospital, 5000 Odense C, Denmark.; Human Genetics, Department of Clinical Research, University of Southern Denmark, 5000 Odense C, Denmark.; Clinical Genome Center, University of Southern Denmark & Region of Southern Denmark, 5000 Odense C, Denmark.
المصدر: Cancers [Cancers (Basel)] 2021 Sep 29; Vol. 13 (19). Date of Electronic Publication: 2021 Sep 29.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101526829 Publication Model: Electronic Cited Medium: Print ISSN: 2072-6694 (Print) Linking ISSN: 20726694 NLM ISO Abbreviation: Cancers (Basel) Subsets: PubMed not MEDLINE
أسماء مطبوعة: Original Publication: Basel, Switzerland : MDPI
مستخلص: Several gene expression signatures based on mRNAs and a few based on long non-coding RNAs (lncRNAs) have been developed to provide prognostic information beyond clinical evaluation in breast cancer (BC). However, the comparison of such signatures for predicting recurrence is very scarce. Therefore, we compared the prognostic utility of mRNAs and lncRNAs in low-risk BC patients using two different classification strategies. Frozen primary tumor samples from 160 lymph node negative and systemically untreated BC patients were included; 80 developed recurrence-i.e., regional or distant metastasis while 80 remained recurrence-free (mean follow-up of 20.9 years). Patients were pairwise matched for clinicopathological characteristics. Classification based on differential mRNA or lncRNA expression using seven individual machine learning methods and a voting scheme classified patients into risk-subgroups. Classification by the seven methods with a fixed sensitivity of ≥90% resulted in specificities ranging from 16-40% for mRNA and 38-58% for lncRNA, and after voting, specificities of 38% and 60% respectively. Classifier performance based on an alternative classification approach of balanced accuracy optimization also provided higher specificities for lncRNA than mRNA at comparable sensitivities. Thus, our results suggested that classification followed by voting improved prognostic power using lncRNAs compared to mRNAs regardless of classification strategy.
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فهرسة مساهمة: Keywords: long non-coding RNA; low-risk breast cancer; lymph node negative; mRNA; machine learning methods; prognostic predictors; systemically untreated patients
تواريخ الأحداث: Date Created: 20211013 Latest Revision: 20211016
رمز التحديث: 20240628
مُعرف محوري في PubMed: PMC8508163
DOI: 10.3390/cancers13194907
PMID: 34638391
قاعدة البيانات: MEDLINE
الوصف
تدمد:2072-6694
DOI:10.3390/cancers13194907