Evidence map›Paper›PMID 29609557›Full record

ArticleBMC cancer2018

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

Reena Thriumani, Ammar Zakaria, Yumi Zuhanis Has-Yun Hashim, Amanina Iymia Jeffree, Khaled Mohamed Helmy, Latifah Munirah Kamarudin, Mohammad Iqbal Omar, Ali Yeon Md Shakaff, Abdul Hamid Adom, Krishna C Persaud

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
3.4field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed, 83 citations in OpenAlex.

  1. Review
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  3. Metabolomics and Biomarker Discovery.Advances in experimental medicine and biology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 2 countries.

Reena ThriumaniCentre of Excellence for Advanced Sensor Technology, Universiti Malaysia Perlis, Arau, Perlis, Malaysia. thriumanireena@yahoo.com.ORCID 0000-0002-6983-5933
Ammar ZakariaCentre of Excellence for Advanced Sensor Technology, Universiti Malaysia Perlis, Arau, Perlis, Malaysia. ammarzakaria@unimap.edu.my.
Yumi Zuhanis Has-Yun HashimCell and Tissue Engineering Lab (CTEL), Department of Biotechnology Engineering, Kulliyyah of Engineering, International Islamic University Malaysia (IIUM), Kuala Lumpur, Malaysia.
Amanina Iymia JeffreeCentre of Excellence for Advanced Sensor Technology, Universiti Malaysia Perlis, Arau, Perlis, Malaysia.
Khaled Mohamed HelmyDepartment of Respiratory, Hospital Tuanku Fauziah, Jalan Kolam, Kangar, Perlis, Malaysia.
Latifah Munirah KamarudinCentre of Excellence for Advanced Sensor Technology, Universiti Malaysia Perlis, Arau, Perlis, Malaysia.
Mohammad Iqbal OmarCentre of Excellence for Advanced Sensor Technology, Universiti Malaysia Perlis, Arau, Perlis, Malaysia.
Ali Yeon Md ShakaffCentre of Excellence for Advanced Sensor Technology, Universiti Malaysia Perlis, Arau, Perlis, Malaysia.
Abdul Hamid AdomCentre of Excellence for Advanced Sensor Technology, Universiti Malaysia Perlis, Arau, Perlis, Malaysia.
Krishna C PersaudSchool of Chemical Engineering and Analytical Science, University of Manchester, Oxford Road, Manchester, United Kingdom.
Universiti Malaysia Perlis · MYInternational Islamic University Malaysia · MYUniversity of Manchester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVolatile 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.

methodThe 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-extraction-gas 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.

resultsThis 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.

conclusionThe 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.

Indexed as

Gas Chromatography-Mass SpectrometrySolid Phase MicroextractionAlgorithmsBiomarkersBiosensing TechniquesCell Line, TumorCells, CulturedHumansLung NeoplasmsReproducibility of ResultsSupport Vector MachineVolatile Organic CompoundsBiomarkersVolatile Organic CompoundsE-noseGCMS-SPMEIn-vitroLung cancerVOCs

Identifiers

PMID29609557
PMCPMC5879746
OpenAlexW2803689993

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.