In vitro cancer cell line classification using pattern recognition approach based on metabolite profiling

This study aims to evaluate the feasibility of metabolite profiling for the characterisation and discrimination volatile compounds using the pattern recognition from in vitro cancer cell lines, which are lung, breast and colon cancer together with the blank medium as a control group. This study impl...

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Main Authors:	Jeffree, Amanina Iymia, Omar, Mohammad Iqbal, Hashim, Yumi Zuhanis Has-Yun, Zakaria, Ammar, Thriumani, Reena, Md Shakaff, Ali Yeon
Format:	Article
Language:	English English
Published:	Universiti Teknikal Malaysia Melaka 2018
Subjects:	TP248.13 Biotechnology
Online Access:	http://irep.iium.edu.my/64762/ http://irep.iium.edu.my/64762/ http://irep.iium.edu.my/64762/1/64762_In%20Vitro%20Cancer%20Cell%20Line.pdf http://irep.iium.edu.my/64762/2/64762_In%20Vitro%20Cancer%20Cell%20Line_SCOPUS.pdf

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recordtype	eprints
spelling	iium-647622018-10-03T02:26:56Z http://irep.iium.edu.my/64762/ In vitro cancer cell line classification using pattern recognition approach based on metabolite profiling Jeffree, Amanina Iymia Omar, Mohammad Iqbal Hashim, Yumi Zuhanis Has-Yun Zakaria, Ammar Thriumani, Reena Md Shakaff, Ali Yeon TP248.13 Biotechnology This study aims to evaluate the feasibility of metabolite profiling for the characterisation and discrimination volatile compounds using the pattern recognition from in vitro cancer cell lines, which are lung, breast and colon cancer together with the blank medium as a control group. This study implemented the A549 (lung), MCF7 (breast) and HCT116 (colon). Cells were harvested and maintained until they grow as monolayer adherent and reach confluence 70-90% before sampling. The volatiles profile from the targeted cell line was established using headspace solid phase microextraction coupled to gas chromatography-mass spectrometry (HSSPME/GCMS). Multivariate data analysis employed principal component analysis (PCA) to better visualise the subtle similarities and the differences among these data sets. A total of 116 volatile organic compounds were detected focused on a limited range of retention time from 3rd until 17th minutes, and 33 compounds were recognized as targeted compounds (peak area>1%). According to both results, the score and the loading plot explained 83% of the total variance. The volatiles compound has shown to be significantly distinguished among cancerous and control group based on metabolite profiling using pattern recognition approach. Universiti Teknikal Malaysia Melaka 2018 Article PeerReviewed application/pdf en http://irep.iium.edu.my/64762/1/64762_In%20Vitro%20Cancer%20Cell%20Line.pdf application/pdf en http://irep.iium.edu.my/64762/2/64762_In%20Vitro%20Cancer%20Cell%20Line_SCOPUS.pdf Jeffree, Amanina Iymia and Omar, Mohammad Iqbal and Hashim, Yumi Zuhanis Has-Yun and Zakaria, Ammar and Thriumani, Reena and Md Shakaff, Ali Yeon (2018) In vitro cancer cell line classification using pattern recognition approach based on metabolite profiling. Journal of Telecommunication, Electronic and Computer Engineering, 10 (1-16). pp. 63-17. ISSN 2180-1843 E-ISSN 2289-8131 http://journal.utem.edu.my/index.php/jtec/article/view/4096
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TP248.13 Biotechnology
spellingShingle	TP248.13 Biotechnology Jeffree, Amanina Iymia Omar, Mohammad Iqbal Hashim, Yumi Zuhanis Has-Yun Zakaria, Ammar Thriumani, Reena Md Shakaff, Ali Yeon In vitro cancer cell line classification using pattern recognition approach based on metabolite profiling
description	This study aims to evaluate the feasibility of metabolite profiling for the characterisation and discrimination volatile compounds using the pattern recognition from in vitro cancer cell lines, which are lung, breast and colon cancer together with the blank medium as a control group. This study implemented the A549 (lung), MCF7 (breast) and HCT116 (colon). Cells were harvested and maintained until they grow as monolayer adherent and reach confluence 70-90% before sampling. The volatiles profile from the targeted cell line was established using headspace solid phase microextraction coupled to gas chromatography-mass spectrometry (HSSPME/GCMS). Multivariate data analysis employed principal component analysis (PCA) to better visualise the subtle similarities and the differences among these data sets. A total of 116 volatile organic compounds were detected focused on a limited range of retention time from 3rd until 17th minutes, and 33 compounds were recognized as targeted compounds (peak area>1%). According to both results, the score and the loading plot explained 83% of the total variance. The volatiles compound has shown to be significantly distinguished among cancerous and control group based on metabolite profiling using pattern recognition approach.
format	Article
author	Jeffree, Amanina Iymia Omar, Mohammad Iqbal Hashim, Yumi Zuhanis Has-Yun Zakaria, Ammar Thriumani, Reena Md Shakaff, Ali Yeon
author_facet	Jeffree, Amanina Iymia Omar, Mohammad Iqbal Hashim, Yumi Zuhanis Has-Yun Zakaria, Ammar Thriumani, Reena Md Shakaff, Ali Yeon
author_sort	Jeffree, Amanina Iymia
title	In vitro cancer cell line classification using pattern recognition approach based on metabolite profiling
title_short	In vitro cancer cell line classification using pattern recognition approach based on metabolite profiling
title_full	In vitro cancer cell line classification using pattern recognition approach based on metabolite profiling
title_fullStr	In vitro cancer cell line classification using pattern recognition approach based on metabolite profiling
title_full_unstemmed	In vitro cancer cell line classification using pattern recognition approach based on metabolite profiling
title_sort	in vitro cancer cell line classification using pattern recognition approach based on metabolite profiling
publisher	Universiti Teknikal Malaysia Melaka
publishDate	2018
url	http://irep.iium.edu.my/64762/ http://irep.iium.edu.my/64762/ http://irep.iium.edu.my/64762/1/64762_In%20Vitro%20Cancer%20Cell%20Line.pdf http://irep.iium.edu.my/64762/2/64762_In%20Vitro%20Cancer%20Cell%20Line_SCOPUS.pdf
first_indexed	2023-09-18T21:31:55Z
last_indexed	2023-09-18T21:31:55Z
_version_	1777412567416700928

In vitro cancer cell line classification using pattern recognition approach based on metabolite profiling

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