Literature DB >> 25159530

Assessment of ovarian cancer conditions from exhaled breath.

Haitham Amal1, Da-You Shi, Radu Ionescu, Wei Zhang, Qing-Ling Hua, Yue-Yin Pan, Li Tao, Hu Liu, Hossam Haick.   

Abstract

We present a pilot study that aims to examine the possibility to easily and noninvasively detect and discriminate females with ovarian cancer (OC) from females that have no tumor(s) and from females that have benign genital tract neoplasia, using exhaled breath samples. The study is based on clinical samples and data from 182 females, as follows: 48 females with OC, 48 tumor-free controls and 86 females with benign gynecological neoplasia. Analysis of the breath samples with gas chromatography linked with mass spectrometry shows that decanal, nonanal, styrene, 2-butanone and hexadecane could serve as potential volatile markers for OC. Analysis of the same samples with tailor-made nanoarrays shows good discrimination between females with OC and females that have either no tumor or benign genital tract neoplasia (71% for accuracy, sensitivity and specificity). Conversely, the nanoarray output shows excellent discrimination between the OC patients and the tumor-free controls (79% sensitivity, 100% specificity and 89% accuracy). These results suggest that the nanoarray approach might be useful to avoid unnecessary complicated or expensive tests for tumor-free females in case of a negative result. In the case of positive result, the test will indicate with high probability the presence of OC.
© 2014 UICC.

Entities:  

Keywords:  breath; diagnosis; ovarian cancer; sensor; volatile organic compound

Mesh:

Substances:

Year:  2014        PMID: 25159530     DOI: 10.1002/ijc.29166

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  21 in total

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3.  Diagnostic Performance of Electronic Noses in Cancer Diagnoses Using Exhaled Breath: A Systematic Review and Meta-analysis.

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4.  Accuracy and Methodologic Challenges of Volatile Organic Compound-Based Exhaled Breath Tests for Cancer Diagnosis: A Systematic Review and Meta-analysis.

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6.  Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules.

Authors:  Morad K Nakhleh; Haitham Amal; Raneen Jeries; Yoav Y Broza; Manal Aboud; Alaa Gharra; Hodaya Ivgi; Salam Khatib; Shifaa Badarneh; Lior Har-Shai; Lea Glass-Marmor; Izabella Lejbkowicz; Ariel Miller; Samih Badarny; Raz Winer; John Finberg; Sylvia Cohen-Kaminsky; Frédéric Perros; David Montani; Barbara Girerd; Gilles Garcia; Gérald Simonneau; Farid Nakhoul; Shira Baram; Raed Salim; Marwan Hakim; Maayan Gruber; Ohad Ronen; Tal Marshak; Ilana Doweck; Ofer Nativ; Zaher Bahouth; Da-You Shi; Wei Zhang; Qing-Ling Hua; Yue-Yin Pan; Li Tao; Hu Liu; Amir Karban; Eduard Koifman; Tova Rainis; Roberts Skapars; Armands Sivins; Guntis Ancans; Inta Liepniece-Karele; Ilze Kikuste; Ieva Lasina; Ivars Tolmanis; Douglas Johnson; Stuart Z Millstone; Jennifer Fulton; John W Wells; Larry H Wilf; Marc Humbert; Marcis Leja; Nir Peled; Hossam Haick
Journal:  ACS Nano       Date:  2016-12-21       Impact factor: 15.881

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Review 8.  Detection of cancer through exhaled breath: a systematic review.

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Journal:  Oncotarget       Date:  2015-11-17

9.  Differentiation between genetic mutations of breast cancer by breath volatolomics.

Authors:  Orna Barash; Wei Zhang; Jeffrey M Halpern; Qing-Ling Hua; Yue-Yin Pan; Haneen Kayal; Kayan Khoury; Hu Liu; Michael P A Davies; Hossam Haick
Journal:  Oncotarget       Date:  2015-12-29

Review 10.  Electronic Noses for Well-Being: Breath Analysis and Energy Expenditure.

Authors:  Julian W Gardner; Timothy A Vincent
Journal:  Sensors (Basel)       Date:  2016-06-23       Impact factor: 3.576

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