Cancer Diagnoses From Exhaled Breath With Na-nose

Study Overview
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Brief Summary
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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 .

Detailed Description
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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.

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

Conditions
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Volatile Organic Compounds, Cancer, Diagnoses Disease

Intervention / Treatment
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* Diagnostic Test: Nanomaterial-based sensors


Participation Criteria
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Eligibility Criteria
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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

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 75 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| cancer<br>Patients with definitively diagnosed of solid tumors | Diagnostic Test: Nanomaterial-based sensors<br>* 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.<br>|
| Benign disease<br>Patients with definitively diagnosed of benign disease or precancerous lesion | Diagnostic Test: Nanomaterial-based sensors<br>* 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.<br>|
| Normal<br>Healthy volunteers | Diagnostic Test: Nanomaterial-based sensors<br>* 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.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 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 Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 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 | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Volatile organic chemicals, Cancer, Diagnose Disease, Na-nose, breath diagnoses