Combined genomic expressions as a diagnostic factor for oral squamous cell carcinoma

Ki Yeol Kim, Xianglan Zhang, Inho Cha

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Trends in genetics are transforming in order to identify differential coexpressions of correlated gene expression rather than the significant individual gene. Moreover, it is known that a combined biomarker pattern improves the discrimination of a specific cancer. The identification of the combined biomarker is also necessary for the early detection of invasive oral squamous cell carcinoma (OSCC). To identify the combined biomarker that could improve the discrimination of OSCC, we explored an appropriate number of genes in a combined gene set in order to attain the highest level of accuracy. After detecting a significant gene set, including the pre-defined number of genes, a combined expression was identified using the weights of genes in a gene set. We used the Principal Component Analysis (PCA) for the weight calculation. In this process, we used three public microarray datasets. One dataset was used for identifying the combined biomarker, and the other two datasets were used for validation. The discrimination accuracy was measured by the out-of-bag (OOB) error. There was no relation between the significance and the discrimination accuracy in each individual gene. The identified gene set included both significant and insignificant genes. One of the most significant gene sets in the classification of normal and OSCC included MMP1, SOCS3 and ACOX1. Furthermore, in the case of oral dysplasia and OSCC discrimination, two combined biomarkers were identified. The combined expression revealed good performance in the validation datasets. The combined genomic expression achieved better performance in the discrimination of different conditions than a single significant gene. Therefore, it could be expected that accurate diagnosis for cancer could be possible with a combined biomarker.

Original languageEnglish
Pages (from-to)317-322
Number of pages6
JournalGenomics
Volume103
Issue number5-6
DOIs
Publication statusPublished - 2014 Jan 1

Fingerprint

Squamous Cell Carcinoma
Genes
Biomarkers
Weights and Measures
Principal Component Analysis
Neoplasms
Gene Expression
Datasets

All Science Journal Classification (ASJC) codes

  • Genetics

Cite this

Kim, Ki Yeol ; Zhang, Xianglan ; Cha, Inho. / Combined genomic expressions as a diagnostic factor for oral squamous cell carcinoma. In: Genomics. 2014 ; Vol. 103, No. 5-6. pp. 317-322.
@article{fd0508d6e33d4cafbb4084738d80acbc,
title = "Combined genomic expressions as a diagnostic factor for oral squamous cell carcinoma",
abstract = "Trends in genetics are transforming in order to identify differential coexpressions of correlated gene expression rather than the significant individual gene. Moreover, it is known that a combined biomarker pattern improves the discrimination of a specific cancer. The identification of the combined biomarker is also necessary for the early detection of invasive oral squamous cell carcinoma (OSCC). To identify the combined biomarker that could improve the discrimination of OSCC, we explored an appropriate number of genes in a combined gene set in order to attain the highest level of accuracy. After detecting a significant gene set, including the pre-defined number of genes, a combined expression was identified using the weights of genes in a gene set. We used the Principal Component Analysis (PCA) for the weight calculation. In this process, we used three public microarray datasets. One dataset was used for identifying the combined biomarker, and the other two datasets were used for validation. The discrimination accuracy was measured by the out-of-bag (OOB) error. There was no relation between the significance and the discrimination accuracy in each individual gene. The identified gene set included both significant and insignificant genes. One of the most significant gene sets in the classification of normal and OSCC included MMP1, SOCS3 and ACOX1. Furthermore, in the case of oral dysplasia and OSCC discrimination, two combined biomarkers were identified. The combined expression revealed good performance in the validation datasets. The combined genomic expression achieved better performance in the discrimination of different conditions than a single significant gene. Therefore, it could be expected that accurate diagnosis for cancer could be possible with a combined biomarker.",
author = "Kim, {Ki Yeol} and Xianglan Zhang and Inho Cha",
year = "2014",
month = "1",
day = "1",
doi = "10.1016/j.ygeno.2013.11.007",
language = "English",
volume = "103",
pages = "317--322",
journal = "Genomics",
issn = "0888-7543",
publisher = "Academic Press Inc.",
number = "5-6",

}

Combined genomic expressions as a diagnostic factor for oral squamous cell carcinoma. / Kim, Ki Yeol; Zhang, Xianglan; Cha, Inho.

In: Genomics, Vol. 103, No. 5-6, 01.01.2014, p. 317-322.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Combined genomic expressions as a diagnostic factor for oral squamous cell carcinoma

AU - Kim, Ki Yeol

AU - Zhang, Xianglan

AU - Cha, Inho

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Trends in genetics are transforming in order to identify differential coexpressions of correlated gene expression rather than the significant individual gene. Moreover, it is known that a combined biomarker pattern improves the discrimination of a specific cancer. The identification of the combined biomarker is also necessary for the early detection of invasive oral squamous cell carcinoma (OSCC). To identify the combined biomarker that could improve the discrimination of OSCC, we explored an appropriate number of genes in a combined gene set in order to attain the highest level of accuracy. After detecting a significant gene set, including the pre-defined number of genes, a combined expression was identified using the weights of genes in a gene set. We used the Principal Component Analysis (PCA) for the weight calculation. In this process, we used three public microarray datasets. One dataset was used for identifying the combined biomarker, and the other two datasets were used for validation. The discrimination accuracy was measured by the out-of-bag (OOB) error. There was no relation between the significance and the discrimination accuracy in each individual gene. The identified gene set included both significant and insignificant genes. One of the most significant gene sets in the classification of normal and OSCC included MMP1, SOCS3 and ACOX1. Furthermore, in the case of oral dysplasia and OSCC discrimination, two combined biomarkers were identified. The combined expression revealed good performance in the validation datasets. The combined genomic expression achieved better performance in the discrimination of different conditions than a single significant gene. Therefore, it could be expected that accurate diagnosis for cancer could be possible with a combined biomarker.

AB - Trends in genetics are transforming in order to identify differential coexpressions of correlated gene expression rather than the significant individual gene. Moreover, it is known that a combined biomarker pattern improves the discrimination of a specific cancer. The identification of the combined biomarker is also necessary for the early detection of invasive oral squamous cell carcinoma (OSCC). To identify the combined biomarker that could improve the discrimination of OSCC, we explored an appropriate number of genes in a combined gene set in order to attain the highest level of accuracy. After detecting a significant gene set, including the pre-defined number of genes, a combined expression was identified using the weights of genes in a gene set. We used the Principal Component Analysis (PCA) for the weight calculation. In this process, we used three public microarray datasets. One dataset was used for identifying the combined biomarker, and the other two datasets were used for validation. The discrimination accuracy was measured by the out-of-bag (OOB) error. There was no relation between the significance and the discrimination accuracy in each individual gene. The identified gene set included both significant and insignificant genes. One of the most significant gene sets in the classification of normal and OSCC included MMP1, SOCS3 and ACOX1. Furthermore, in the case of oral dysplasia and OSCC discrimination, two combined biomarkers were identified. The combined expression revealed good performance in the validation datasets. The combined genomic expression achieved better performance in the discrimination of different conditions than a single significant gene. Therefore, it could be expected that accurate diagnosis for cancer could be possible with a combined biomarker.

UR - http://www.scopus.com/inward/record.url?scp=84902144276&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84902144276&partnerID=8YFLogxK

U2 - 10.1016/j.ygeno.2013.11.007

DO - 10.1016/j.ygeno.2013.11.007

M3 - Article

C2 - 24321173

AN - SCOPUS:84902144276

VL - 103

SP - 317

EP - 322

JO - Genomics

JF - Genomics

SN - 0888-7543

IS - 5-6

ER -