Utilizing cox regression model to assess the relations between predefined gene sets and the survival outcome of lung adenocarcinoma

Jo Yang Lu; Pei Chun Chen; Chuhsing K. Hsiao; Eric Y. Chuang; Mong Hsun Tsai; Liang Chuan Lai

doi:10.1109/BIBM.2010.5706566

Utilizing cox regression model to assess the relations between predefined gene sets and the survival outcome of lung adenocarcinoma

Jo Yang Lu^*
, Pei Chun Chen
, Chuhsing K. Hsiao
, Eric Y. Chuang
, Mong Hsun Tsai
, Liang Chuan Lai

^*Corresponding author for this work

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

Abstract

The risks of relapse for lung adenocarcinoma patients were still higher than 30%, even after complete surgical resections in early stages. Although lots of prognosis studies using genome-wide profiling had been published, biological meaning and interactions among the prognostic genes were poorly understood. Therefore, we developed a novel method integrating gene set enrichment analysis and Cox-hazard regression model to investigate the relations between predefined gene sets and the survival outcome in lung cancer. The method was able to select gene sets associated with the survival outcome, clustering of the prognostic genes sets, and selection of a representative gene set from each cluster. Furthermore, kernel matrix was used to visualize the similarities between those representative gene sets. In addition to survival outcome, our method can also use other continuous variables to explore other biological interpretation concealed in the predefined gene sets.

Original language	English
Title of host publication	Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010
Pages	218-221
Number of pages	4
DOIs	https://doi.org/10.1109/BIBM.2010.5706566
State	Published - 2010
Externally published	Yes
Event	2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010 - Hong Kong, China Duration: 18 12 2010 → 21 12 2010

Publication series

Name	Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010

Conference

Conference	2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010
Country/Territory	China
City	Hong Kong
Period	18/12/10 → 21/12/10

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Gene set
Kernel matrix
Regression
Survival

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10.1109/BIBM.2010.5706566

Cite this

Lu, J. Y., Chen, P. C., Hsiao, C. K., Chuang, E. Y., Tsai, M. H., & Lai, L. C. (2010). Utilizing cox regression model to assess the relations between predefined gene sets and the survival outcome of lung adenocarcinoma. In Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010 (pp. 218-221). Article 5706566 (Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010). https://doi.org/10.1109/BIBM.2010.5706566

Lu, Jo Yang ; Chen, Pei Chun ; Hsiao, Chuhsing K. et al. / Utilizing cox regression model to assess the relations between predefined gene sets and the survival outcome of lung adenocarcinoma. Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010. 2010. pp. 218-221 (Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010).

@inproceedings{2a06def0325042f08cd98167b92060b7,

title = "Utilizing cox regression model to assess the relations between predefined gene sets and the survival outcome of lung adenocarcinoma",

abstract = "The risks of relapse for lung adenocarcinoma patients were still higher than 30\%, even after complete surgical resections in early stages. Although lots of prognosis studies using genome-wide profiling had been published, biological meaning and interactions among the prognostic genes were poorly understood. Therefore, we developed a novel method integrating gene set enrichment analysis and Cox-hazard regression model to investigate the relations between predefined gene sets and the survival outcome in lung cancer. The method was able to select gene sets associated with the survival outcome, clustering of the prognostic genes sets, and selection of a representative gene set from each cluster. Furthermore, kernel matrix was used to visualize the similarities between those representative gene sets. In addition to survival outcome, our method can also use other continuous variables to explore other biological interpretation concealed in the predefined gene sets.",

keywords = "Gene set, Kernel matrix, Regression, Survival",

author = "Lu, \{Jo Yang\} and Chen, \{Pei Chun\} and Hsiao, \{Chuhsing K.\} and Chuang, \{Eric Y.\} and Tsai, \{Mong Hsun\} and Lai, \{Liang Chuan\}",

year = "2010",

doi = "10.1109/BIBM.2010.5706566",

language = "英语",

isbn = "9781424483075",

series = "Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010",

pages = "218--221",

booktitle = "Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010",

note = "2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010 ; Conference date: 18-12-2010 Through 21-12-2010",

}

Lu, JY, Chen, PC, Hsiao, CK, Chuang, EY, Tsai, MH & Lai, LC 2010, Utilizing cox regression model to assess the relations between predefined gene sets and the survival outcome of lung adenocarcinoma. in Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010., 5706566, Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010, pp. 218-221, 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010, Hong Kong, China, 18/12/10. https://doi.org/10.1109/BIBM.2010.5706566

Utilizing cox regression model to assess the relations between predefined gene sets and the survival outcome of lung adenocarcinoma. / Lu, Jo Yang; Chen, Pei Chun; Hsiao, Chuhsing K. et al.
Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010. 2010. p. 218-221 5706566 (Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010).

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

TY - GEN

T1 - Utilizing cox regression model to assess the relations between predefined gene sets and the survival outcome of lung adenocarcinoma

AU - Lu, Jo Yang

AU - Chen, Pei Chun

AU - Hsiao, Chuhsing K.

AU - Chuang, Eric Y.

AU - Tsai, Mong Hsun

AU - Lai, Liang Chuan

PY - 2010

Y1 - 2010

N2 - The risks of relapse for lung adenocarcinoma patients were still higher than 30%, even after complete surgical resections in early stages. Although lots of prognosis studies using genome-wide profiling had been published, biological meaning and interactions among the prognostic genes were poorly understood. Therefore, we developed a novel method integrating gene set enrichment analysis and Cox-hazard regression model to investigate the relations between predefined gene sets and the survival outcome in lung cancer. The method was able to select gene sets associated with the survival outcome, clustering of the prognostic genes sets, and selection of a representative gene set from each cluster. Furthermore, kernel matrix was used to visualize the similarities between those representative gene sets. In addition to survival outcome, our method can also use other continuous variables to explore other biological interpretation concealed in the predefined gene sets.

AB - The risks of relapse for lung adenocarcinoma patients were still higher than 30%, even after complete surgical resections in early stages. Although lots of prognosis studies using genome-wide profiling had been published, biological meaning and interactions among the prognostic genes were poorly understood. Therefore, we developed a novel method integrating gene set enrichment analysis and Cox-hazard regression model to investigate the relations between predefined gene sets and the survival outcome in lung cancer. The method was able to select gene sets associated with the survival outcome, clustering of the prognostic genes sets, and selection of a representative gene set from each cluster. Furthermore, kernel matrix was used to visualize the similarities between those representative gene sets. In addition to survival outcome, our method can also use other continuous variables to explore other biological interpretation concealed in the predefined gene sets.

KW - Gene set

KW - Kernel matrix

KW - Regression

KW - Survival

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DO - 10.1109/BIBM.2010.5706566

M3 - 会议稿件

AN - SCOPUS:79952390566

SN - 9781424483075

T3 - Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010

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BT - Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010

T2 - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010

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ER -

Lu JY, Chen PC, Hsiao CK, Chuang EY, Tsai MH, Lai LC. Utilizing cox regression model to assess the relations between predefined gene sets and the survival outcome of lung adenocarcinoma. In Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010. 2010. p. 218-221. 5706566. (Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010). doi: 10.1109/BIBM.2010.5706566

Utilizing cox regression model to assess the relations between predefined gene sets and the survival outcome of lung adenocarcinoma

Abstract

Publication series

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UN SDGs

Keywords

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