Molecular Classification of Breast Cancer Utilizing Long Non-Coding RNA (lncRNA) Transcriptomes Identifies Novel Diagnostic lncRNA Panel for Triple-Negative Breast Cancer

Breast cancer remains the world’s most prevalent cancer, responsible for around 685,000 deaths globally despite international research efforts and advances in clinical management. While estrogen receptor positive (ER+), progesterone receptor positive (PR+), and human epidermal growth factor receptor...

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Autores principales:	Hibah Shaath, Ramesh Elango, Nehad M. Alajez
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	triple-negative breast cancer TNBC diagnosis long non-coding RNA lncRNA gene signature Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/b05c47be7d9949e3b11cd1b24ada95ee
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spelling	oai:doaj.org-article:b05c47be7d9949e3b11cd1b24ada95ee2021-11-11T15:28:52ZMolecular Classification of Breast Cancer Utilizing Long Non-Coding RNA (lncRNA) Transcriptomes Identifies Novel Diagnostic lncRNA Panel for Triple-Negative Breast Cancer10.3390/cancers132153502072-6694https://doaj.org/article/b05c47be7d9949e3b11cd1b24ada95ee2021-10-01T00:00:00Zhttps://www.mdpi.com/2072-6694/13/21/5350https://doaj.org/toc/2072-6694Breast cancer remains the world’s most prevalent cancer, responsible for around 685,000 deaths globally despite international research efforts and advances in clinical management. While estrogen receptor positive (ER+), progesterone receptor positive (PR+), and human epidermal growth factor receptor positive (HER2+) subtypes are easily classified and can be targeted, there remains no direct diagnostic test for triple-negative breast cancer (TNBC), except for the lack of receptors expression. The identification of long non-coding RNAs (lncRNAs) and the roles they play in cancer progression has recently proven to be beneficial. In the current study, we utilize RNA sequencing data to identify lncRNA-based biomarkers associated with TNBC, ER+ subtypes, and normal breast tissue. The Marker Finder algorithm identified the lncRNA transcript panel most associated with each molecular subtype and the receiver operating characteristic (ROC) analysis was used to validate the diagnostic potential (area under the curve (AUC) of ≥8.0 and <i>p</i> value < 0.0001). Focusing on TNBC, findings from the discovery cohort were validated in an additional two cohorts, identifying 13 common lncRNA transcripts enriched in TNBC. Binary regression analysis identified a four lncRNA transcript signature (ENST00000425820.1, ENST00000448208.5, ENST00000521666.1, and ENST00000650510.1) with the highest diagnostic power for TNBC. The ENST00000671612.1 lncRNA transcript correlated with worse refractory free survival (RFS). Our data provides a step towards finding a novel diagnostic lncRNA-based panel for TNBC with potential therapeutic implications.Hibah ShaathRamesh ElangoNehad M. AlajezMDPI AGarticletriple-negative breast cancerTNBCdiagnosislong non-coding RNAlncRNAgene signatureNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENCancers, Vol 13, Iss 5350, p 5350 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	triple-negative breast cancer TNBC diagnosis long non-coding RNA lncRNA gene signature Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	triple-negative breast cancer TNBC diagnosis long non-coding RNA lncRNA gene signature Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Hibah Shaath Ramesh Elango Nehad M. Alajez Molecular Classification of Breast Cancer Utilizing Long Non-Coding RNA (lncRNA) Transcriptomes Identifies Novel Diagnostic lncRNA Panel for Triple-Negative Breast Cancer
description	Breast cancer remains the world’s most prevalent cancer, responsible for around 685,000 deaths globally despite international research efforts and advances in clinical management. While estrogen receptor positive (ER+), progesterone receptor positive (PR+), and human epidermal growth factor receptor positive (HER2+) subtypes are easily classified and can be targeted, there remains no direct diagnostic test for triple-negative breast cancer (TNBC), except for the lack of receptors expression. The identification of long non-coding RNAs (lncRNAs) and the roles they play in cancer progression has recently proven to be beneficial. In the current study, we utilize RNA sequencing data to identify lncRNA-based biomarkers associated with TNBC, ER+ subtypes, and normal breast tissue. The Marker Finder algorithm identified the lncRNA transcript panel most associated with each molecular subtype and the receiver operating characteristic (ROC) analysis was used to validate the diagnostic potential (area under the curve (AUC) of ≥8.0 and <i>p</i> value < 0.0001). Focusing on TNBC, findings from the discovery cohort were validated in an additional two cohorts, identifying 13 common lncRNA transcripts enriched in TNBC. Binary regression analysis identified a four lncRNA transcript signature (ENST00000425820.1, ENST00000448208.5, ENST00000521666.1, and ENST00000650510.1) with the highest diagnostic power for TNBC. The ENST00000671612.1 lncRNA transcript correlated with worse refractory free survival (RFS). Our data provides a step towards finding a novel diagnostic lncRNA-based panel for TNBC with potential therapeutic implications.
format	article
author	Hibah Shaath Ramesh Elango Nehad M. Alajez
author_facet	Hibah Shaath Ramesh Elango Nehad M. Alajez
author_sort	Hibah Shaath
title	Molecular Classification of Breast Cancer Utilizing Long Non-Coding RNA (lncRNA) Transcriptomes Identifies Novel Diagnostic lncRNA Panel for Triple-Negative Breast Cancer
title_short	Molecular Classification of Breast Cancer Utilizing Long Non-Coding RNA (lncRNA) Transcriptomes Identifies Novel Diagnostic lncRNA Panel for Triple-Negative Breast Cancer
title_full	Molecular Classification of Breast Cancer Utilizing Long Non-Coding RNA (lncRNA) Transcriptomes Identifies Novel Diagnostic lncRNA Panel for Triple-Negative Breast Cancer
title_fullStr	Molecular Classification of Breast Cancer Utilizing Long Non-Coding RNA (lncRNA) Transcriptomes Identifies Novel Diagnostic lncRNA Panel for Triple-Negative Breast Cancer
title_full_unstemmed	Molecular Classification of Breast Cancer Utilizing Long Non-Coding RNA (lncRNA) Transcriptomes Identifies Novel Diagnostic lncRNA Panel for Triple-Negative Breast Cancer
title_sort	molecular classification of breast cancer utilizing long non-coding rna (lncrna) transcriptomes identifies novel diagnostic lncrna panel for triple-negative breast cancer
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/b05c47be7d9949e3b11cd1b24ada95ee
work_keys_str_mv	AT hibahshaath molecularclassificationofbreastcancerutilizinglongnoncodingrnalncrnatranscriptomesidentifiesnoveldiagnosticlncrnapanelfortriplenegativebreastcancer AT rameshelango molecularclassificationofbreastcancerutilizinglongnoncodingrnalncrnatranscriptomesidentifiesnoveldiagnosticlncrnapanelfortriplenegativebreastcancer AT nehadmalajez molecularclassificationofbreastcancerutilizinglongnoncodingrnalncrnatranscriptomesidentifiesnoveldiagnosticlncrnapanelfortriplenegativebreastcancer
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Molecular Classification of Breast Cancer Utilizing Long Non-Coding RNA (lncRNA) Transcriptomes Identifies Novel Diagnostic lncRNA Panel for Triple-Negative Breast Cancer

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