Novel Biomarkers from genes in the apoptotic pathway for Prediction of HCC Progression using Association Rule Mining

Tasneem A. Gameel; Sherine Rady; Khaled A. ElBahnasy; Sanaa M. Kamal

doi:10.1145/3328833.3328863

Novel Biomarkers from genes in the apoptotic pathway for Prediction of HCC Progression using Association Rule Mining

Tasneem A. Gameel
, Sherine Rady
, Khaled A. ElBahnasy
, Sanaa M. Kamal

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

1 Scopus citations

Abstract

Liver cancer, a main cause of death, is extremely difficult to be diagnosed at its early stages. On a positive side, predicting the disease development or progression by analyzing medical data can be helpful for the future early diagnosis and accordingly the increase of the patients' survival. Medical investigation and researchers raise that Single nucleotide polymorphisms in certain apoptosis-related genes are related to the cancer development. The objective of this paper is to find quantitative associations between apoptotic gene-related polymorphisms and the progression level of the liver cancer. To find these associations, Association rule mining is applied using the Frequent Pattern algorithm. An experimental study on an Egyptian cohort of 1246 patients with advanced cirrhosis and liver cancer resulted in associations which can serve as novel biomarkers. It has been found that CDKN2A and HLA-DP genes have relation to the HCC development with a confidence value 0.55, and CDKN1B and Il28b, are related to the liver cancer progression with a confidence value 0.54.

Original language	English
Title of host publication	ICSIE 2019 - Proceedings of 2019 8th International Conference on Software and Information Engineering
Publisher	Association for Computing Machinery
Pages	217-221
Number of pages	5
ISBN (Electronic)	9781450361057
DOIs	https://doi.org/10.1145/3328833.3328863
State	Published - 9 Apr 2019
Externally published	Yes
Event	8th International Conference on Software and Information Engineering, ICSIE 2019 - Cairo, Egypt Duration: 9 Apr 2019 → 12 Apr 2019

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	8th International Conference on Software and Information Engineering, ICSIE 2019
Country/Territory	Egypt
City	Cairo
Period	9/04/19 → 12/04/19

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Association rule mining
CDKN1B
CDKN2A
FP growth
HLA-DP
Hepatocellular Carcinoma
IL28b
SNP
Telomerase

Access to Document

10.1145/3328833.3328863

Cite this

Gameel, T. A., Rady, S., ElBahnasy, K. A., & Kamal, S. M. (2019). Novel Biomarkers from genes in the apoptotic pathway for Prediction of HCC Progression using Association Rule Mining. In ICSIE 2019 - Proceedings of 2019 8th International Conference on Software and Information Engineering (pp. 217-221). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3328833.3328863

Gameel, Tasneem A. ; Rady, Sherine ; ElBahnasy, Khaled A. et al. / Novel Biomarkers from genes in the apoptotic pathway for Prediction of HCC Progression using Association Rule Mining. ICSIE 2019 - Proceedings of 2019 8th International Conference on Software and Information Engineering. Association for Computing Machinery, 2019. pp. 217-221 (ACM International Conference Proceeding Series).

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title = "Novel Biomarkers from genes in the apoptotic pathway for Prediction of HCC Progression using Association Rule Mining",

abstract = "Liver cancer, a main cause of death, is extremely difficult to be diagnosed at its early stages. On a positive side, predicting the disease development or progression by analyzing medical data can be helpful for the future early diagnosis and accordingly the increase of the patients' survival. Medical investigation and researchers raise that Single nucleotide polymorphisms in certain apoptosis-related genes are related to the cancer development. The objective of this paper is to find quantitative associations between apoptotic gene-related polymorphisms and the progression level of the liver cancer. To find these associations, Association rule mining is applied using the Frequent Pattern algorithm. An experimental study on an Egyptian cohort of 1246 patients with advanced cirrhosis and liver cancer resulted in associations which can serve as novel biomarkers. It has been found that CDKN2A and HLA-DP genes have relation to the HCC development with a confidence value 0.55, and CDKN1B and Il28b, are related to the liver cancer progression with a confidence value 0.54.",

keywords = "Association rule mining, CDKN1B, CDKN2A, FP growth, HLA-DP, Hepatocellular Carcinoma, IL28b, SNP, Telomerase",

author = "Gameel, \{Tasneem A.\} and Sherine Rady and ElBahnasy, \{Khaled A.\} and Kamal, \{Sanaa M.\}",

note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 8th International Conference on Software and Information Engineering, ICSIE 2019 ; Conference date: 09-04-2019 Through 12-04-2019",

year = "2019",

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day = "9",

doi = "10.1145/3328833.3328863",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

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Gameel, TA, Rady, S, ElBahnasy, KA & Kamal, SM 2019, Novel Biomarkers from genes in the apoptotic pathway for Prediction of HCC Progression using Association Rule Mining. in ICSIE 2019 - Proceedings of 2019 8th International Conference on Software and Information Engineering. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 217-221, 8th International Conference on Software and Information Engineering, ICSIE 2019, Cairo, Egypt, 9/04/19. https://doi.org/10.1145/3328833.3328863

Novel Biomarkers from genes in the apoptotic pathway for Prediction of HCC Progression using Association Rule Mining. / Gameel, Tasneem A.; Rady, Sherine; ElBahnasy, Khaled A. et al.
ICSIE 2019 - Proceedings of 2019 8th International Conference on Software and Information Engineering. Association for Computing Machinery, 2019. p. 217-221 (ACM International Conference Proceeding Series).

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

TY - GEN

T1 - Novel Biomarkers from genes in the apoptotic pathway for Prediction of HCC Progression using Association Rule Mining

AU - Gameel, Tasneem A.

AU - Rady, Sherine

AU - ElBahnasy, Khaled A.

AU - Kamal, Sanaa M.

PY - 2019/4/9

Y1 - 2019/4/9

N2 - Liver cancer, a main cause of death, is extremely difficult to be diagnosed at its early stages. On a positive side, predicting the disease development or progression by analyzing medical data can be helpful for the future early diagnosis and accordingly the increase of the patients' survival. Medical investigation and researchers raise that Single nucleotide polymorphisms in certain apoptosis-related genes are related to the cancer development. The objective of this paper is to find quantitative associations between apoptotic gene-related polymorphisms and the progression level of the liver cancer. To find these associations, Association rule mining is applied using the Frequent Pattern algorithm. An experimental study on an Egyptian cohort of 1246 patients with advanced cirrhosis and liver cancer resulted in associations which can serve as novel biomarkers. It has been found that CDKN2A and HLA-DP genes have relation to the HCC development with a confidence value 0.55, and CDKN1B and Il28b, are related to the liver cancer progression with a confidence value 0.54.

AB - Liver cancer, a main cause of death, is extremely difficult to be diagnosed at its early stages. On a positive side, predicting the disease development or progression by analyzing medical data can be helpful for the future early diagnosis and accordingly the increase of the patients' survival. Medical investigation and researchers raise that Single nucleotide polymorphisms in certain apoptosis-related genes are related to the cancer development. The objective of this paper is to find quantitative associations between apoptotic gene-related polymorphisms and the progression level of the liver cancer. To find these associations, Association rule mining is applied using the Frequent Pattern algorithm. An experimental study on an Egyptian cohort of 1246 patients with advanced cirrhosis and liver cancer resulted in associations which can serve as novel biomarkers. It has been found that CDKN2A and HLA-DP genes have relation to the HCC development with a confidence value 0.55, and CDKN1B and Il28b, are related to the liver cancer progression with a confidence value 0.54.

KW - Association rule mining

KW - CDKN1B

KW - CDKN2A

KW - FP growth

KW - HLA-DP

KW - Hepatocellular Carcinoma

KW - IL28b

KW - SNP

KW - Telomerase

UR - https://www.scopus.com/pages/publications/85068594060

U2 - 10.1145/3328833.3328863

DO - 10.1145/3328833.3328863

M3 - Conference contribution

AN - SCOPUS:85068594060

T3 - ACM International Conference Proceeding Series

SP - 217

EP - 221

BT - ICSIE 2019 - Proceedings of 2019 8th International Conference on Software and Information Engineering

PB - Association for Computing Machinery

T2 - 8th International Conference on Software and Information Engineering, ICSIE 2019

Y2 - 9 April 2019 through 12 April 2019

ER -

Gameel TA, Rady S, ElBahnasy KA, Kamal SM. Novel Biomarkers from genes in the apoptotic pathway for Prediction of HCC Progression using Association Rule Mining. In ICSIE 2019 - Proceedings of 2019 8th International Conference on Software and Information Engineering. Association for Computing Machinery. 2019. p. 217-221. (ACM International Conference Proceeding Series). doi: 10.1145/3328833.3328863

Novel Biomarkers from genes in the apoptotic pathway for Prediction of HCC Progression using Association Rule Mining

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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