Uncovering potential biomarkers in ovarian carcinoma via biclustering of DNA microarray data

Alain B. Tchagang; Ahmed H. Tewfik; Amy P.N. Skubitz; Keith M. Skubitz

doi:10.1109/GENSIPS.2006.353179

Uncovering potential biomarkers in ovarian carcinoma via biclustering of DNA microarray data

Alain B. Tchagang, Ahmed H. Tewfik, Amy P.N. Skubitz, Keith M. Skubitz

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

The NIH/NCI estimates that one out of 57 women will develop ovarian cancer during their lifetime. Ovarian cancer is 90 percent curable when detected early. Unfortunately, many cases of ovarian cancer are not diagnosed until advanced stages because most women do not develop noticeable symptoms. This paper presents an exhaustive identification of all potential biomarkers for the diagnosis of early-stage and/or recurrent ovarian cancer using a unique and comprehensive set of gene expression data. The data set was generated by Gene Logic Inc. from ovarian normal and cancerous tissues as well as non-ovarian tissues collected at the University of Minnesota by Skubitz et al. In particular, the paper shows the ability of a modified biclustering technique combined with sensitivity analysis of gene expression levels to identify all potential biomarkers found by prior studies as well as several more promising candidates that had been missed in the literature. Furthermore, unlike most prior studies, this work screens all candidate biomarkers using two additional techniques: immunohistochemical analysis and reverse transcriptase polymerase chain reaction.

Original language	English (US)
Title of host publication	2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006
Pages	107-108
Number of pages	2
DOIs	https://doi.org/10.1109/GENSIPS.2006.353179
State	Published - 2006
Event	2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006 - College Station, TX, United States Duration: May 28 2006 → May 30 2006

Publication series

Name	2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006

Other

Other	2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006
Country/Territory	United States
City	College Station, TX
Period	5/28/06 → 5/30/06

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10.1109/GENSIPS.2006.353179

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Tchagang, A. B., Tewfik, A. H., Skubitz, A. P. N., & Skubitz, K. M. (2006). Uncovering potential biomarkers in ovarian carcinoma via biclustering of DNA microarray data. In 2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006 (pp. 107-108). Article 4161800 (2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006). https://doi.org/10.1109/GENSIPS.2006.353179

Uncovering potential biomarkers in ovarian carcinoma via biclustering of DNA microarray data. / Tchagang, Alain B.; Tewfik, Ahmed H.; Skubitz, Amy P.N. et al.
2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006. 2006. p. 107-108 4161800 (2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Tchagang, AB, Tewfik, AH, Skubitz, APN & Skubitz, KM 2006, Uncovering potential biomarkers in ovarian carcinoma via biclustering of DNA microarray data. in 2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006., 4161800, 2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006, pp. 107-108, 2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006, College Station, TX, United States, 5/28/06. https://doi.org/10.1109/GENSIPS.2006.353179

Tchagang AB, Tewfik AH, Skubitz APN , Skubitz KM. Uncovering potential biomarkers in ovarian carcinoma via biclustering of DNA microarray data. In 2006 IEEE International Workshop on Genomic Signal Processing and Statstics, GENSIPS 2006. 2006. p. 107-108. 4161800. (2006 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2006). doi: 10.1109/GENSIPS.2006.353179

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title = "Uncovering potential biomarkers in ovarian carcinoma via biclustering of DNA microarray data",

abstract = "The NIH/NCI estimates that one out of 57 women will develop ovarian cancer during their lifetime. Ovarian cancer is 90 percent curable when detected early. Unfortunately, many cases of ovarian cancer are not diagnosed until advanced stages because most women do not develop noticeable symptoms. This paper presents an exhaustive identification of all potential biomarkers for the diagnosis of early-stage and/or recurrent ovarian cancer using a unique and comprehensive set of gene expression data. The data set was generated by Gene Logic Inc. from ovarian normal and cancerous tissues as well as non-ovarian tissues collected at the University of Minnesota by Skubitz et al. In particular, the paper shows the ability of a modified biclustering technique combined with sensitivity analysis of gene expression levels to identify all potential biomarkers found by prior studies as well as several more promising candidates that had been missed in the literature. Furthermore, unlike most prior studies, this work screens all candidate biomarkers using two additional techniques: immunohistochemical analysis and reverse transcriptase polymerase chain reaction.",

author = "Tchagang, {Alain B.} and Tewfik, {Ahmed H.} and Skubitz, {Amy P.N.} and Skubitz, {Keith M.}",

year = "2006",

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language = "English (US)",

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AU - Tchagang, Alain B.

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N2 - The NIH/NCI estimates that one out of 57 women will develop ovarian cancer during their lifetime. Ovarian cancer is 90 percent curable when detected early. Unfortunately, many cases of ovarian cancer are not diagnosed until advanced stages because most women do not develop noticeable symptoms. This paper presents an exhaustive identification of all potential biomarkers for the diagnosis of early-stage and/or recurrent ovarian cancer using a unique and comprehensive set of gene expression data. The data set was generated by Gene Logic Inc. from ovarian normal and cancerous tissues as well as non-ovarian tissues collected at the University of Minnesota by Skubitz et al. In particular, the paper shows the ability of a modified biclustering technique combined with sensitivity analysis of gene expression levels to identify all potential biomarkers found by prior studies as well as several more promising candidates that had been missed in the literature. Furthermore, unlike most prior studies, this work screens all candidate biomarkers using two additional techniques: immunohistochemical analysis and reverse transcriptase polymerase chain reaction.

AB - The NIH/NCI estimates that one out of 57 women will develop ovarian cancer during their lifetime. Ovarian cancer is 90 percent curable when detected early. Unfortunately, many cases of ovarian cancer are not diagnosed until advanced stages because most women do not develop noticeable symptoms. This paper presents an exhaustive identification of all potential biomarkers for the diagnosis of early-stage and/or recurrent ovarian cancer using a unique and comprehensive set of gene expression data. The data set was generated by Gene Logic Inc. from ovarian normal and cancerous tissues as well as non-ovarian tissues collected at the University of Minnesota by Skubitz et al. In particular, the paper shows the ability of a modified biclustering technique combined with sensitivity analysis of gene expression levels to identify all potential biomarkers found by prior studies as well as several more promising candidates that had been missed in the literature. Furthermore, unlike most prior studies, this work screens all candidate biomarkers using two additional techniques: immunohistochemical analysis and reverse transcriptase polymerase chain reaction.

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Uncovering potential biomarkers in ovarian carcinoma via biclustering of DNA microarray data

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