MicroRNA-based classifiers for diagnosis of oral cavity squamous cell carcinoma in tissue and plasma

Nicklas Juel Pedersen; David Hebbelstrup Jensen; Giedrius Lelkaitis; Katalin Kiss; Birgitte Wittenborg Charabi; Henrik Ullum; Lena Specht; Ane Yde Schmidt; Finn Cilius Nielsen; Christian von Buchwald

doi:10.1016/j.oraloncology.2018.05.020

MicroRNA-based classifiers for diagnosis of oral cavity squamous cell carcinoma in tissue and plasma

Nicklas Juel Pedersen, David Hebbelstrup Jensen, Giedrius Lelkaitis, Katalin Kiss, Birgitte Wittenborg Charabi, Henrik Ullum, Lena Specht, Ane Yde Schmidt, Finn Cilius Nielsen, Christian von Buchwald

Department of Clinical Medicine

20 Citations (Scopus)

Abstract

BACKGROUND: MicroRNAs (miRNAs) hold promise as diagnostic cancer biomarkers. Here we aimed to define the miRNome in oral squamous cell carcinoma (OSCC) and normal oral mucosa (NOM), and to identify and validate new diagnostic miRNAs and miRNA combinations in formalin-fixed paraffin-embedded (FFPE) tissue samples and plasma samples.

METHODS: We performed next-generation miRNA sequencing in FFPE tissue samples of OSCC (n = 80) and NOM (n = 8). Our findings were validated by quantitative polymerase chain reaction (qPCR) analysis of OSCC (n = 195) and NOM (n = 103) FFPE tissue samples, and plasma samples from OSCC patients (n = 55) and healthy persons (n = 18).

RESULTS: The OSCC miRNome included 567 miRNAs, 66 of which were differentially expressed between OSCC and NOM. Using qPCR data, we constructed receiver operating curves to classify patients as NOM or OSCC based on miRNA combinations. The area under the curve was of 0.92 from FFPE tissue (miR-204-5p, miR-370, miR-1307, miR-193b-3p, and miR-144-5p), and 1.0 from plasma samples (miR-30a-5p and miR-769-5p). Model calibration and discrimination were evaluated using 10-fold cross-validation.

CONCLUSIONS: Analysis of the miRNome from many OSCC cases improves our knowledge of the importance of individual miRNAs and their predictive potential in OSCC. We successfully identified miRNA classifiers in FFPE OSCC tissue and plasma with a high discriminatory ability between OSCC and NOM. The proposed combination of miR-30a-5p and miR-769-5p in plasma from OSCC patients could serve as a minimal invasive biomarker for diagnosis and control of T-site recurrences.

Original language	English
Journal	Oral Oncology
Volume	83
Pages (from-to)	46-52
ISSN	1368-8375
DOIs	https://doi.org/10.1016/j.oraloncology.2018.05.020
Publication status	Published - Aug 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.oraloncology.2018.05.020

Cite this

@article{dc797dd2f3fe4b11b33ef9a6e6ef5d8d,

title = "MicroRNA-based classifiers for diagnosis of oral cavity squamous cell carcinoma in tissue and plasma",

abstract = "BACKGROUND: MicroRNAs (miRNAs) hold promise as diagnostic cancer biomarkers. Here we aimed to define the miRNome in oral squamous cell carcinoma (OSCC) and normal oral mucosa (NOM), and to identify and validate new diagnostic miRNAs and miRNA combinations in formalin-fixed paraffin-embedded (FFPE) tissue samples and plasma samples.METHODS: We performed next-generation miRNA sequencing in FFPE tissue samples of OSCC (n = 80) and NOM (n = 8). Our findings were validated by quantitative polymerase chain reaction (qPCR) analysis of OSCC (n = 195) and NOM (n = 103) FFPE tissue samples, and plasma samples from OSCC patients (n = 55) and healthy persons (n = 18).RESULTS: The OSCC miRNome included 567 miRNAs, 66 of which were differentially expressed between OSCC and NOM. Using qPCR data, we constructed receiver operating curves to classify patients as NOM or OSCC based on miRNA combinations. The area under the curve was of 0.92 from FFPE tissue (miR-204-5p, miR-370, miR-1307, miR-193b-3p, and miR-144-5p), and 1.0 from plasma samples (miR-30a-5p and miR-769-5p). Model calibration and discrimination were evaluated using 10-fold cross-validation.CONCLUSIONS: Analysis of the miRNome from many OSCC cases improves our knowledge of the importance of individual miRNAs and their predictive potential in OSCC. We successfully identified miRNA classifiers in FFPE OSCC tissue and plasma with a high discriminatory ability between OSCC and NOM. The proposed combination of miR-30a-5p and miR-769-5p in plasma from OSCC patients could serve as a minimal invasive biomarker for diagnosis and control of T-site recurrences.",

author = "Pedersen, {Nicklas Juel} and Jensen, {David Hebbelstrup} and Giedrius Lelkaitis and Katalin Kiss and Charabi, {Birgitte Wittenborg} and Henrik Ullum and Lena Specht and Schmidt, {Ane Yde} and Nielsen, {Finn Cilius} and {von Buchwald}, Christian",

year = "2018",

month = aug,

doi = "10.1016/j.oraloncology.2018.05.020",

language = "English",

volume = "83",

pages = "46--52",

journal = "Oral Oncology",

issn = "1368-8375",

publisher = "Pergamon Press",

}

TY - JOUR

T1 - MicroRNA-based classifiers for diagnosis of oral cavity squamous cell carcinoma in tissue and plasma

AU - Pedersen, Nicklas Juel

AU - Jensen, David Hebbelstrup

AU - Lelkaitis, Giedrius

AU - Kiss, Katalin

AU - Charabi, Birgitte Wittenborg

AU - Ullum, Henrik

AU - Specht, Lena

AU - Schmidt, Ane Yde

AU - Nielsen, Finn Cilius

AU - von Buchwald, Christian

PY - 2018/8

Y1 - 2018/8

N2 - BACKGROUND: MicroRNAs (miRNAs) hold promise as diagnostic cancer biomarkers. Here we aimed to define the miRNome in oral squamous cell carcinoma (OSCC) and normal oral mucosa (NOM), and to identify and validate new diagnostic miRNAs and miRNA combinations in formalin-fixed paraffin-embedded (FFPE) tissue samples and plasma samples.METHODS: We performed next-generation miRNA sequencing in FFPE tissue samples of OSCC (n = 80) and NOM (n = 8). Our findings were validated by quantitative polymerase chain reaction (qPCR) analysis of OSCC (n = 195) and NOM (n = 103) FFPE tissue samples, and plasma samples from OSCC patients (n = 55) and healthy persons (n = 18).RESULTS: The OSCC miRNome included 567 miRNAs, 66 of which were differentially expressed between OSCC and NOM. Using qPCR data, we constructed receiver operating curves to classify patients as NOM or OSCC based on miRNA combinations. The area under the curve was of 0.92 from FFPE tissue (miR-204-5p, miR-370, miR-1307, miR-193b-3p, and miR-144-5p), and 1.0 from plasma samples (miR-30a-5p and miR-769-5p). Model calibration and discrimination were evaluated using 10-fold cross-validation.CONCLUSIONS: Analysis of the miRNome from many OSCC cases improves our knowledge of the importance of individual miRNAs and their predictive potential in OSCC. We successfully identified miRNA classifiers in FFPE OSCC tissue and plasma with a high discriminatory ability between OSCC and NOM. The proposed combination of miR-30a-5p and miR-769-5p in plasma from OSCC patients could serve as a minimal invasive biomarker for diagnosis and control of T-site recurrences.

AB - BACKGROUND: MicroRNAs (miRNAs) hold promise as diagnostic cancer biomarkers. Here we aimed to define the miRNome in oral squamous cell carcinoma (OSCC) and normal oral mucosa (NOM), and to identify and validate new diagnostic miRNAs and miRNA combinations in formalin-fixed paraffin-embedded (FFPE) tissue samples and plasma samples.METHODS: We performed next-generation miRNA sequencing in FFPE tissue samples of OSCC (n = 80) and NOM (n = 8). Our findings were validated by quantitative polymerase chain reaction (qPCR) analysis of OSCC (n = 195) and NOM (n = 103) FFPE tissue samples, and plasma samples from OSCC patients (n = 55) and healthy persons (n = 18).RESULTS: The OSCC miRNome included 567 miRNAs, 66 of which were differentially expressed between OSCC and NOM. Using qPCR data, we constructed receiver operating curves to classify patients as NOM or OSCC based on miRNA combinations. The area under the curve was of 0.92 from FFPE tissue (miR-204-5p, miR-370, miR-1307, miR-193b-3p, and miR-144-5p), and 1.0 from plasma samples (miR-30a-5p and miR-769-5p). Model calibration and discrimination were evaluated using 10-fold cross-validation.CONCLUSIONS: Analysis of the miRNome from many OSCC cases improves our knowledge of the importance of individual miRNAs and their predictive potential in OSCC. We successfully identified miRNA classifiers in FFPE OSCC tissue and plasma with a high discriminatory ability between OSCC and NOM. The proposed combination of miR-30a-5p and miR-769-5p in plasma from OSCC patients could serve as a minimal invasive biomarker for diagnosis and control of T-site recurrences.

U2 - 10.1016/j.oraloncology.2018.05.020

DO - 10.1016/j.oraloncology.2018.05.020

M3 - Journal article

C2 - 30098778

SN - 1368-8375

VL - 83

SP - 46

EP - 52

JO - Oral Oncology

JF - Oral Oncology

ER -

MicroRNA-based classifiers for diagnosis of oral cavity squamous cell carcinoma in tissue and plasma

Abstract

UN SDGs

Access to Document

Fingerprint

Cite this