Clinical trial NCT03228095: Volatiles in Breath and Headspace Analysis - Diagnostic Markers
Official title: Volatile Organic Compounds in Breath and Headspace Analysis - Diagnostic and Monitoring Markers for Diseases
Study type: OBSERVATIONAL
Overall status: ENROLLING_BY_INVITATION
Conditions: Tuberculosis
Gastric Cancer
Peptic Ulcer
Atrophic Gastritis
Intestinal Metaplasia
Gastric Dysplasia
Colorectal Cancer
Colorectal Polyp
Colorectal Adenoma
Pancreatic Cancer
Pancreatitis, Chronic
Liver Cancer
Liver Cirrhosis
Flu, Human
Other Infectious Diseases
Inflammatory Bowel Diseases
Keywords: Volatile Organic Compounds
Tuberculosis
Nano-sensors
Electronic nose
Digestive cancers
Lead sponsor: University of Latvia
Sponsor class: OTHER
Collaborators: name: Technion, Israel Institute of Technology
name: Riga East University Hospital
name: JLM Innovation GmbH
First posted: 2017-07-24
Enrollment: 3000
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Patients being referred for diagnostic testing and treatment Healthy individuals from general population

Brief summary: Detection of Volatile Organic Compounds (VOC) directly from tissue by headspace analysis (skin, surgery material, other tissue) and exhaled breath is feasible using affordable user-friendly novel nano-chemo sensors that can accurately be used for screening and monitoring purpose

Detailed description: Study propose to explore a novel approach for the diagnosis and monitoring of diseases. The approach is based on the detection of volatile organic compounds (VOCs) that are emitted from the cells and detected directly from tissue, such as skin, surgery material, blood as well as from exhaled breath.

In the literature there are several reports on VOCs which can be detected by Gas Chromatography - Mass Spectrometry (GC-MS) means directly from: (i) the headspace of TB cells (i.e., the mixture of volatile biomarkers trapped above the TB cells in a sealed vessel); (ii) the exhaled breath or (iii) from urine. Excellent results in detection of the tuberculosis disease by using nanosensor array were shown by Nakhleh et al achieved 90% sensitivity, 93% specificity and 92% accuracy in discrimination between healthy and diseased patients using electronic nose devices with a single sensor. None of the reported studies identified the tentative recognition of the tuberculosis-related VOCs and quantified the concentration differences between samples from ill and healthy controls. Further investigation of the exhaled breath tuberculosis-related VOC by GC-MS means will improve the knowledge and simultaneously will help to improve the nanosensor array design.

Several studies have shown that disease-rated VOC patterns can be transmitted through the skin, and, therefore, skin can be used as a source for disease detection and identification. The principle of this detection approach is that disease-related changes are reflected in measurable changes in the skin through exchange via the blood. In addition, several studies have suggested that the VOC levels are elevated even in early stages of the disease, because they reflect a change in the human's body chemistry (as a result of the development of disease condition), rather than the amount of infected cells. Complementary studies have shown that VOCs can be emitted to the skin within minutes after they have emerged in the infected part of the human's body. What is particularly significant about this approach is that each type of (infectious) disease has its own unique pattern of VOCs, and, therefore, the presence of one (infectious) disease would not screen other disease types. Nevertheless, to the best of our knowledge, the detection of tuberculosis VOCs through skin has not been examined yet. Additionally, all studies targeting skin VOCs have been carried out by means of spectrometry and spectroscopy techniques. In few cases, electronic nose devices were used. These techniques are powerful tools for detecting VOCs. However, to date, the use of these techniques has been impeded by the need for moderately to highly expensive equipment's, the high levels of expertise required to operate such instruments, the speed required for sampling and analysis, and the need for preconcentration techniques. For VOC skin testing and breath testing of tuberculosis to become widely used in clinical practice, several advances in the knowledge of tuberculosis specific VOCs and sensor development need to occur. Nanoparticles containing flexible sensors, based on organic films, are more likely to become a clinical diagnostic tool, because they are significantly smaller, easier-to-use, and significantly less expensive.

In recent years comprehensive studies have shown excellent data for using VOCs from exhaled breath as tool for diagnosing gastric cancer. In one of the biggest studies carried out by Chinese and Latvian centers, malignancy could be identified with 89% sensitivity and 90% specificity after cross-validation, irrespective of important confounding factors in gastric patients such as tobacco or alcohol consumption and H. pylori infection. A breath test for GC staging could also be demonstrated by distinguishing stage I\&II cancers from stage III\&IV cancers with 89% sensitivity and 94% specificity. These studies used both - mass spectometry and nano-sensors technologies. Most recent study published in ASC Nano journal in January 2017 reported on more extended use of nanoarry sensors in breath analysis, blind experiments showed that 86% accuracy could be achieved with the artificially intelligent nanoarray, allowing both detection and discrimination between the different disease conditions examined (chronic kidney failure, idiopathic Parkinson's disease, atypical Parkinsonism , multiple sclerosis, Crohn's disease, ulcerative colitis, irritable bowel syndrome, pulmonary arterial hypertension, pre-eclampsia in pregnant women, head and neck cancer, lung cancer, colorectal cancer, bladder cancer, kidney cancer, prostate cancer, gastric cancer, and ovarian cancer. Analysis of the artificially intelligent nanoarray also showed that each disease has its own unique breathprint, and that the presence of one disease would not screen out others.

Therefore, this study is aimed to test VOCs detecting technologies as diagnostic and monitoring tools for digestive tract and infectious diseases.

Eligibility criteria: Inclusion Criteria:

* Informed Consent signed
* Individual with targeted disease/lesion (tuberculosis, gastric cancer, gastric dysplasia, high/ normal/ low risk gastric lesions, colorectal cancer, high-risk colorectal lesions, low-risk colorectal adenoma, pancreatic cancer, chronic pancreatitis, liver cancer, chronic liver disease, other infectious diseases, oncological diseases of other location)

Exclusion Criteria:

* Informed Consent not signed
* Other active cancer at the time of inclusion for particular study group

Primary outcomes:
measure: Specific VOC detected
timeFrame: 2 years
measure: Performance of nanoarray sensor testing to detect target lesions and diseases
timeFrame: At the time of breath sampling
Secondary outcomes:
measure: Specific VOC patterns for target disease or lesion and risk groups
timeFrame: At the time of breath sampling
measure: VOC pattern changes following treatment
timeFrame: At baseline, 3 and/or 6 months after treatment (other time frame according to study group)
measure: VOC pattern changes in relapse of disease for early recognition and treatment
timeFrame: At baseline, 3 and/or 6 months after treatment (other time frame according to study group)
measure: Groups of gastrointestinal microbiota correlating to VOCs
timeFrame: At the time of sampling
Other outcomes:
Locations:
city: Riga
country: Latvia
facility: University of Latvia
Study officials:
affiliation: University of Latvia
name: Mārcis Leja, PhD, MD
role: STUDY_DIRECTOR
affiliation: University of Latvia
name: Lelde Lauka, MD
role: PRINCIPAL_INVESTIGATOR
affiliation: Riga East University Hospital
name: Andra Cīrule, MD
role: PRINCIPAL_INVESTIGATOR
References:
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.
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.
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.