Cancer Diagnoses From Exhaled Breath With Na-nose

Cancer Clinical Trial

Official title:

Diagnosing Cancers From Healthy From Human Exhaled Breath With Na-nose

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT03967652
• Other study ID #: NanoBreathDiag
• Status: Not yet recruiting
• Start date: July 1, 2019
• Est. completion date: December 31, 2022

Study information

• Verified date: May 2019
• Source: Anhui Medical University
• Contact: Bao Chuyang, MD
• Phone: +86 18555039598
• Email: des_mond[@]outlook.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Early diagnoses of malignant tumors are pivotal for improving their prognoses. The Exhaled Breath is made up of oxygen, carbon dioxide, nitrogen, water, inert gases and volatile organic compounds (VOCs). Theoretically, the concentration of VOCs in exhalation produced by metabolism in human body is only about nmol/L-pmol/L, which can significantly increase under certain pathological conditions. A series of studies of VOCs diagnosing solid tumors the investigators had been conducted in the past decade. It was found that VOCs in exhaled breath can not only distinguish different types of tumors, but also can make a clear distinction between different stages. Our long-term collaborator, Professor Hossam Haick (Israel Institute of Technology) has developed a nano sensor array, so called Na-nose, which can detect VOCs of the exhaled breath by binding gases to specific chemiresistors coated with gold nanomaterials. The Na-nose has the advantages of low cost, easy to use, good reproducibility and real-time detection for large scale clinical application. This study was to use large clinical samples to validate the diagnostic efficacy of the newly developed Nano-nose( Sniffphone and Breath Screener) for malignant tumors .

Description:

Israel Institute of Technology provides two type of Na-nose. One is Breath Screener used for large-scale sampling and feature VOCs extraction to establish database. The other is called Sniff Phone aim at clinical real-time VOCs detection assisted by software. About 10,000 patients will participate in the subject of Breath Screener in batches. First, 7000 patients will have a definitive diagnosis and exhaled breath collected. Feature VOCs of specific tumors will be extracted from these samples and employed to build predictive model by using discriminant factor analysis (DFA). After the predictive model had been completed, 3000 definitively diagnosed patients will participate in validating the specificity and sensitivity of the prediction model. With the assistance of Breath Screener clinical database and software services, Sniff Phone is more suitable for clinical real-time detection for its small and convenient design characteristics. At last, Breath Screener and Sniff Phone will continue enriching databases and improve diagnosis efficacy in their clinical applications.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 10000
• Est. completion date: December 31, 2022
• Est. primary completion date: December 31, 2020
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years to 75 Years

Eligibility

Inclusion Criteria:

• 18-75 years

• Cancer/benign disease having been diagnosed by pathology

• ECOG < 2

Exclusion Criteria:

• Concomitant malignancies other than one malignant tumor

• Diabetes, Fatty liver

• Autoimmune disease

• Ventilation and transaired function obstacle

Related Conditions & MeSH terms

• Cancer
• Diagnoses Disease
• Volatile Organic Compounds

Intervention

Diagnostic Test:
• Nanomaterial-based sensors
Chemical sensors based on Monolayer-Capped Metallic Nanoparticles (MCMNPs) can recognize and classify exhaled breath by special recognition algorithm, which achieves the purpose of disease diagnosis.

Locations

Country	Name	City	State
n/a

Sponsors (2)

Lead Sponsor	Collaborator
Anhui Medical University	Technion, Israel Institute of Technology

References & Publications (7)

Amal H, Ding L, Liu BB, Tisch U, Xu ZQ, Shi DY, Zhao Y, Chen J, Sun RX, Liu H, Ye SL, Tang ZY, Haick H. The scent fingerprint of hepatocarcinoma: in-vitro metastasis prediction with volatile organic compounds (VOCs). Int J Nanomedicine. 2012;7:4135-46. doi: 10.2147/IJN.S32680. Epub 2012 Jul 30. — View Citation

Amal H, Leja M, Broza YY, Tisch U, Funka K, Liepniece-Karele I, Skapars R, Xu ZQ, Liu H, Haick H. Geographical variation in the exhaled volatile organic compounds. J Breath Res. 2013 Dec;7(4):047102. doi: 10.1088/1752-7155/7/4/047102. Epub 2013 Nov 1. — View Citation

Amal H, Shi DY, Ionescu R, Zhang W, Hua QL, Pan YY, Tao L, Liu H, Haick H. Assessment of ovarian cancer conditions from exhaled breath. Int J Cancer. 2015 Mar 15;136(6):E614-22. doi: 10.1002/ijc.29166. Epub 2014 Sep 5. — View Citation

Barash O, Zhang W, Halpern JM, Hua QL, Pan YY, Kayal H, Khoury K, Liu H, Davies MP, Haick H. Differentiation between genetic mutations of breast cancer by breath volatolomics. Oncotarget. 2015 Dec 29;6(42):44864-76. doi: 10.18632/oncotarget.6269. — View Citation

Leja MA, Liu H, Haick H. Breath testing: the future for digestive cancer detection. Expert Rev Gastroenterol Hepatol. 2013 Jul;7(5):389-91. doi: 10.1586/17474124.2013.811033. — View Citation

Nakhleh MK, Amal H, Jeries R, Broza YY, Aboud M, Gharra A, Ivgi H, Khatib S, Badarneh S, Har-Shai L, Glass-Marmor L, Lejbkowicz I, Miller A, Badarny S, Winer R, Finberg J, Cohen-Kaminsky S, Perros F, Montani D, Girerd B, Garcia G, Simonneau G, Nakhoul F, Baram S, Salim R, Hakim M, Gruber M, Ronen O, Marshak T, Doweck I, Nativ O, Bahouth Z, Shi DY, Zhang W, Hua QL, Pan YY, Tao L, Liu H, Karban A, Koifman E, Rainis T, Skapars R, Sivins A, Ancans G, Liepniece-Karele I, Kikuste I, Lasina I, Tolmanis I, Johnson D, Millstone SZ, Fulton J, Wells JW, Wilf LH, Humbert M, Leja M, Peled N, Haick H. Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules. ACS Nano. 2017 Jan 24;11(1):112-125. doi: 10.1021/acsnano.6b04930. Epub 2016 Dec 21. — View Citation

Xu ZQ, Broza YY, Ionsecu R, Tisch U, Ding L, Liu H, Song Q, Pan YY, Xiong FX, Gu KS, Sun GP, Chen ZD, Leja M, Haick H. A nanomaterial-based breath test for distinguishing gastric cancer from benign gastric conditions. Br J Cancer. 2013 Mar 5;108(4):941-50. doi: 10.1038/bjc.2013.44. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Build predictive diagnosis database	First, feature VOCs of specific tumors will be extracted from part of collected samples and employed to build predictive model. After the predictive model had been completed, number of definitively diagnosed patients will participate in validating the specificity and sensitivity of the prediction model.	From July 01,2019 to December 31,2021
Secondary	Associated feature exhaled breath with differentially expressed genes	Integrate the correlation and relevance between the exhaled samples and the differentially expressed genes in the cancer group and the benign / normal control group to explore the mechanism of feature VOCs' production.	From Juan 01,2022 to December 31,2022