A study on volatile organic compounds emitted by in-vitro lung cancer cultured cells using gas sensor array and SPME-GCMS

被引:52
作者
Thriumani, Reena [1 ]
Zakaria, Ammar [1 ]
Hashim, Yumi Zuhanis Has-Yun [2 ,3 ]
Jeffree, Amanina Iymia [1 ]
Helmy, Khaled Mohamed [4 ]
Kamarudin, Latifah Munirah [1 ]
Omar, Mohammad Iqbal [1 ]
Shakaff, Ali Yeon Md [1 ]
Adom, Abdul Hamid [1 ]
Persaud, Krishna C. [5 ]
机构
[1] Univ Malaysia Perlis, Ctr Excellence Adv Sensor Technol, Arau, Perlis, Malaysia
[2] IIUM, Kulliyyah Engn, Dept Biotechnol Engn, CTEL, Kuala Lumpur, Malaysia
[3] IIUM, Int Inst Halal Res & Training INHART, Kuala Lumpur, Malaysia
[4] Hosp Tuanku Fauziah, Dept Resp, Kangar, Perlis, Malaysia
[5] Univ Manchester, Sch Chem Engn & Analyt Sci, Oxford Rd, Manchester, Lancs, England
关键词
E-nose; In-vitro; GCMS-SPME; Lung cancer; VOCs; SOLID-PHASE MICROEXTRACTION; K-NEAREST NEIGHBOR; EXHALED BREATH; BIOMARKERS; CLASSIFICATION; METABOLITES; RECOGNITION; PREDICTION; DIAGNOSIS;
D O I
10.1186/s12885-018-4235-7
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: Volatile organic compounds (VOCs) emitted from exhaled breath from human bodies have been proven to be a useful source of information for early lung cancer diagnosis. To date, there are still arguable information on the production and origin of significant VOCs of cancer cells. Thus, this study aims to conduct in-vitro experiments involving related cell lines to verify the capability of VOCs in providing information of the cells. Method: The performances of e-nose technology with different statistical methods to determine the best classifier were conducted and discussed. The gas sensor study has been complemented using solid phase micro-extractiongas chromatography mass spectrometry. For this purpose, the lung cancer cells (A549 and Calu-3) and control cell lines, breast cancer cell (MCF7) and non-cancerous lung cell (WI38VA13) were cultured in growth medium. Results: This study successfully provided a list of possible volatile organic compounds that can be specific biomarkers for lung cancer, even at the 24th hour of cell growth. Also, the Linear Discriminant Analysis-based One versus All-Support Vector Machine classifier, is able to produce high performance in distinguishing lung cancer from breast cancer cells and normal lung cells. Conclusion: The findings in this work conclude that the specific VOC released from the cancer cells can act as the odour signature and potentially to be used as non-invasive screening of lung cancer using gas array sensor devices.
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页数:17
相关论文
共 85 条
  • [1] Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening
    Aberle, Denise R.
    Adams, Amanda M.
    Berg, Christine D.
    Black, William C.
    Clapp, Jonathan D.
    Fagerstrom, Richard M.
    Gareen, Ilana F.
    Gatsonis, Constantine
    Marcus, Pamela M.
    Sicks, JoRean D.
    [J]. NEW ENGLAND JOURNAL OF MEDICINE, 2011, 365 (05) : 395 - 409
  • [3] Alberts B., 2002, MOL BIOL CELL, V4th
  • [4] Breath Analysis: The Approach Towards Clinical Applications
    Amann, Anton
    Spanel, Patrik
    Smith, David
    [J]. MINI-REVIEWS IN MEDICINAL CHEMISTRY, 2007, 7 (02) : 115 - 129
  • [5] [Anonymous], BR J CANC
  • [6] [Anonymous], LUNG CANC
  • [7] [Anonymous], CANC BIOMARKERS
  • [8] [Anonymous], WORD RECOGNITION IND
  • [9] [Anonymous], HAMDAN MED J
  • [10] [Anonymous], ELECT NOSE TECHNOLOG