Diagnostic Power Comparison Between VOCs and CTCs

NCT ID: NCT03958812

Last Updated: 2019-06-03

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

200 participants

Study Classification

OBSERVATIONAL

Study Start Date

2019-06-15

Study Completion Date

2020-12-31

Brief Summary

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Early diagnosis of malignant tumors is pivotal for improving their prognoses. Circulating tumor cells (CTC) in peripheral blood and Volatile organic compounds (VOCs) in exhaled breath are newly developed diagnosis method. Due to the low percentage of CTCs in peripheral blood of cancer patients and the surface structure of lymphocytes (especially megakaryocytes) is often confused with tumor cells, CTC has a high false positive and negative rate. In recent years, the detection of volatile organic compounds (VOCs) in exhaled breath as a simple and noninvasive method has shown broad application prospects in the diagnosis of various diseases. A series of studies of VOCs diagnosing solid tumors the investigators had conducted in the past decade show that VOCs can not only distinguish different types of tumors, but also can make a distinction between different stages. This study was to compare CTC and VOCs with clinical samples. Predictive models will be built employing discriminant factor analysis (DFA) pattern recognition method. Sensitivity and specificity will be determined using leave-one-out cross-validation or an independent blind test set.

Detailed Description

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200 patients with definitive diagnoses will be enrolled and the alveolar exhaled breath samples and peripheral venous blood will be collected. Two blood samples and two breath samples will be collected from each patient. One blood sample will be send to CTC tests for a blind test and the other will be used for headspace VOCs analyses. One breath sample was used for analysis with the Nano-sensors array, and the other was used for gas chromatography coupled with mass spectrometry (GC-MS) analysis. The VOCs samples were collected using sorbent tubes at a total flow through sorption trap of 200ml/min, then will be send to Israel Institute of Technology for further test.

Conditions

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Circulating Tumor Cell Volatile Organic Chemicals Breast Cancer Gastric Cancer Diagnoses Disease

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Gastric cancer

patients with definitive diagnosis of gastric cancer by pathology

Circulating tumor cells, Volatile organic compounds

Intervention Type DIAGNOSTIC_TEST

Alveolar exhaled breath samples and peripheral venous blood(10ml) will be collected from each patients

Breast cancer

patients with definitive diagnosis of breast cancer by pathology

Circulating tumor cells, Volatile organic compounds

Intervention Type DIAGNOSTIC_TEST

Alveolar exhaled breath samples and peripheral venous blood(10ml) will be collected from each patients

Benign gastric diseases

Gastritis or gastric ulcer

Circulating tumor cells, Volatile organic compounds

Intervention Type DIAGNOSTIC_TEST

Alveolar exhaled breath samples and peripheral venous blood(10ml) will be collected from each patients

Benign breast diseases

Hyperplasia of mammary glands or mastitis

Circulating tumor cells, Volatile organic compounds

Intervention Type DIAGNOSTIC_TEST

Alveolar exhaled breath samples and peripheral venous blood(10ml) will be collected from each patients

Normal

healthy volunteers

Circulating tumor cells, Volatile organic compounds

Intervention Type DIAGNOSTIC_TEST

Alveolar exhaled breath samples and peripheral venous blood(10ml) will be collected from each patients

Interventions

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Circulating tumor cells, Volatile organic compounds

Alveolar exhaled breath samples and peripheral venous blood(10ml) will be collected from each patients

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* 18-75 years
* Definitive diagnosis of gastric cancer, breast cancer,benign breast disease and gastric lesions
* ECOG(Eastern Cooperative Oncology Group) scores ≤ 2

Exclusion Criteria

* Other palliative chemotherapy and radiotherapy for this cancer
* Other cancer
* Diabetes, Fatty liver
* Autoimmune disease
* Pulmonary ventilation dysfunction
Minimum Eligible Age

18 Years

Maximum Eligible Age

75 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Technion, Israel Institute of Technology

OTHER

Sponsor Role collaborator

Anhui Medical University

OTHER

Sponsor Role lead

Responsible Party

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Hu Liu

Associate Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Hu Liu, MD

Role: PRINCIPAL_INVESTIGATOR

Anhui Provincial Cancer Hospital

Central Contacts

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Chuyang Bao, MD

Role: CONTACT

+86 18555039598

Hu Liu, MD

Role: CONTACT

+86 13866175691

References

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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.

Reference Type BACKGROUND
PMID: 26540569 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 25159530 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 28000444 (View on PubMed)

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. No abstract available.

Reference Type BACKGROUND
PMID: 23899275 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 24184568 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 22888249 (View on PubMed)

Other Identifiers

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DPCVC

Identifier Type: -

Identifier Source: org_study_id

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