Volatilomic signatures of different strains of Helicobacter pylori.

BACKGROUND: Helicobacter pylori (H. pylori) infection is the most extensively studied risk factor for gastric cancer. As with any bacteria, H. pylori will release distinctive odors that result from an emission of volatile metabolic byproducts in unique combinations and proportions. Effectively capturing and identifying these volatiles can pave the way for the development of innovative and non-invasive diagnostic methods for determining infection. Here we characterize the H. pylori volatilomic signature, pinpoint potential biomarkers of its presence, and evaluate the variability of volatilomic signatures between different H. pylori isolates. MATERIALS AND METHODS: Using needle trap extraction, volatiles in the headspace above H. pylori cultures were collected and, following thermal desorption at 290°C in a splitless mode, were analyzed using gas chromatography-mass spectrometry. The resulting volatilomic signatures of H. pylori cultures were compared to those obtained from an analysis of the volatiles in the headspace above the cultivating medium only. RESULTS: Amongst the volatiles detected, 21 showed consistent differences between the bacteria cultures and the cultivation medium, with 11 compounds being elevated and 10 showing decreased levels in the culture's headspace. The 11 elevated volatiles are four ketones (2-pentanone, 5-methyl-3-heptanone, 2-heptanone, and 2-nonanone), three alcohols (2-methyl-1-propanol, 3-methyl-1-butanol, and 1 butanol), one aromatic (styrene), one aldehyde (2-ethyl-hexanal), one hydrocarbon (n-octane), and one sulfur compound (dimethyl disulfide). The 10 volatiles with lower levels in the headspace of the cultures are four aldehydes (2-methylpropanal, benzaldehyde, 3-methylbutanal, and butanal), two heterocyclic compounds (2-ethylfuran and 2-pentylfuran), one ketone (2-butanone), one aromatic (benzene), one alcohol (2-butanol) and bromodichloromethane. Of the volatile species showing increased levels, the highest emissions are found to be for 3-methyl-1-butanol, 1-butanol and dimethyl disulfide. Qualitative variations in their emissions from the different isolates was observed. CONCLUSIONS: The volatiles emitted by H. pylori provide a characteristic volatilome signature that has the potential of being developed as a tool for monitoring infections caused by this pathogen. Furthermore, using the volatilome signature, we are able to differentiate different isolates of H. pylori. However, the volatiles also represent potential confounders for the recognition of gastric cancer volatile markers.

Volatilomic profiles of gastric juice in gastric cancer patients.

Volatilomics is a powerful tool capable of providing novel biomarkers for the diagnosis of gastric cancer. The main objective of this study was to characterize the volatilomic signatures of gastric juice in order to identify potential alterations induced by gastric cancer. Gas chromatography with mass spectrometric detection, coupled with headspace solid phase microextraction as the pre-concentration technique, was used to identify volatile organic compounds (VOCs) released by gastric juice samples collected from 78 gastric cancer patients and two cohorts of controls (80 and 96 subjects) from four different locations (Latvia, Ukraine, Brazil, and Colombia). 1440 distinct compounds were identified in samples obtained from patients and 1422 in samples provided by controls. However, only 6% of the VOCs exhibited an incidence higher than 20%. Amongst the volatiles emitted, 18 showed differences in their headspace concentrations above gastric juice of cancer patients and controls. Ten of these (1-propanol, 2,3-butanedione, 2-pentanone, benzeneacetaldehyde, 3-methylbutanal, butylated hydroxytoluene, 2-pentyl-furan, 2-ethylhexanal, 2-methylpropanal and phenol) appeared at significantly higher levels in the headspace of the gastric juice samples obtained from patients; whereas, eight species showed lower abundance in patients than found in controls. Given that the difference in the volatilomic signatures can be explained by cancer-related changes in the activity of certain enzymes or pathways, the former set can be considered potential biomarkers for gastric cancer, which may assist in developing non-invasive breath tests for the diagnosis of this disease. Further studies are required to elucidate further the mechanisms that underlie the changes in the volatilomic profile as a result of gastric cancer.

Breath Fingerprint of Colorectal Cancer Patients Based on the Gas Chromatography-Mass Spectrometry Analysis.

The human body emits a multitude of volatile organic compounds (VOCs) via tissues and various bodily fluids or exhaled breath. These compounds collectively create a distinctive chemical profile, which can potentially be employed to identify changes in human metabolism associated with colorectal cancer (CRC) and, consequently, facilitate the diagnosis of this disease. The main goal of this study was to investigate and characterize the VOCs' chemical patterns associated with the breath of CRC patients and controls and identify potential expiratory markers of this disease. For this purpose, gas chromatography-mass spectrometry was applied. Collectively, 1656 distinct compounds were identified in the breath samples provided by 152 subjects. Twenty-two statistically significant VOCs (p-xylene; hexanal; 2-methyl-1,3-dioxolane; 2,2,4-trimethyl-1,3-pentanediol diisobutyrate; hexadecane; nonane; ethylbenzene; cyclohexanone; diethyl phthalate; 6-methyl-5-hepten-2-one; tetrahydro-2H-pyran-2-one; 2-butanone; benzaldehyde; dodecanal; benzothiazole; tetradecane; 1-dodecanol; 1-benzene; 3-methylcyclopentyl acetate; 1-nonene; toluene) were observed at higher concentrations in the exhaled breath of the CRC group. The elevated levels of these VOCs in CRC patients' breath suggest the potential for these compounds to serve as biomarkers for CRC.

The Detection of Colorectal Cancer through Machine Learning-Based Breath Sensor Analysis.

Colorectal cancer (CRC) is the third most common malignancy and the second most common cause of cancer-related deaths worldwide. While CRC screening is already part of organized programs in many countries, there remains a need for improved screening tools. In recent years, a potential approach for cancer diagnosis has emerged via the analysis of volatile organic compounds (VOCs) using sensor technologies. The main goal of this study was to demonstrate and evaluate the diagnostic potential of a table-top breath analyzer for detecting CRC. Breath sampling was conducted and CRC vs. non-cancer groups (105 patients with CRC, 186 non-cancer subjects) were included in analysis. The obtained data were analyzed using supervised machine learning methods (i.e., Random Forest, C4.5, Artificial Neural Network, and Naïve Bayes). Superior accuracy was achieved using Random Forest and Evolutionary Search for Features (79.3%, sensitivity 53.3%, specificity 93.0%, AUC ROC 0.734), and Artificial Neural Networks and Greedy Search for Features (78.2%, sensitivity 43.3%, specificity 96.5%, AUC ROC 0.735). Our results confirm the potential of the developed breath analyzer as a promising tool for identifying and categorizing CRC within a point-of-care clinical context. The combination of MOX sensors provided promising results in distinguishing healthy vs. diseased breath samples. Its capacity for rapid, non-invasive, and targeted CRC detection suggests encouraging prospects for future clinical screening applications.

Age-Based Comparative Analysis of Colorectal Cancer Colonoscopy Screening Findings.

Background and Objectives: Colorectal cancer (CRC) incidence is rapidly emerging among individuals <50 years, termed as early-onset colorectal cancer (EOCRC). This study aimed to probe variations in tumorigenic pathology and relevant manifestations (polyp and adenoma incidence) between suspected cases of EOCRC and late-onset CRC (LOCRC; ≥50 years of age). Materials and Methods: Between September 2022 and February 2023, colonoscopy-based screening data from 1653 patients were included in this study. All eligible participants were divided into two groups, depending upon patient age, where Group 1 consisted of 1021 patients aged <50 years while Group 2 consisted of 632 patients aged ≥ 50 years. Polyp samples were collected when identified peri-procedurally and characterized according to World Health Organization criteria. Results: Polyp detection rate was 42% for the <50-year age group, while this was 76% for the ≥50-year age group. Additionally, the <50-year age group predominated in hyperplastic polyp manifestation, particularly within the rectum and sigmoid colon. In addition, the ≥50-year age group had increased prevalence of serrated polyps and differing adenoma manifestations. Conclusions: This investigation served to highlight the importance of age stratification for CRC colonoscopy-based screening effectiveness, with particular reference to evaluations that are based on polyp localization within differing colon regions.

Identification of Volatile Markers of Colorectal Cancer from Tumor Tissues Using Volatilomic Approach.

The human body releases numerous volatile organic compounds (VOCs) through tissues and various body fluids, including breath. These compounds form a specific chemical profile that may be used to detect the colorectal cancer CRC-related changes in human metabolism and thereby diagnose this type of cancer. The main goal of this study was to investigate the volatile signatures formed by VOCs released from the CRC tissue. For this purpose, headspace solid-phase microextraction gas chromatography-mass spectrometry was applied. In total, 163 compounds were detected. Both cancerous and non-cancerous tissues emitted 138 common VOCs. Ten volatiles (2-butanone; dodecane; benzaldehyde; pyridine; octane; 2-pentanone; toluene; p-xylene; n-pentane; 2-methyl-2-propanol) occurred in at least 90% of both types of samples; 1-propanol in cancer tissue (86% in normal one), acetone in normal tissue (82% in cancer one). Four compounds (1-propanol, pyridine, isoprene, methyl thiolacetate) were found to have increased emissions from cancer tissue, whereas eleven showed reduced release from this type of tissue (2-butanone; 2-pentanone; 2-methyl-2-propanol; ethyl acetate; 3-methyl-1-butanol; d-limonene; tetradecane; dodecanal; tridecane; 2-ethyl-1-hexanol; cyclohexanone). The outcomes of this study provide evidence that the VOCs signature of the CRC tissue is altered by the CRC. The volatile constituents of this distinct signature can be emitted through exhalation and serve as potential biomarkers for identifying the presence of CRC. Reliable identification of the VOCs associated with CRC is essential to guide and tune the development of advanced sensor technologies that can effectively and sensitively detect and quantify these markers.

Volatile Markers for Cancer in Exhaled Breath-Could They Be the Signature of the Gut Microbiota?

It has been shown that the gut microbiota plays a central role in human health and disease. A wide range of volatile metabolites present in exhaled breath have been linked with gut microbiota and proposed as a non-invasive marker for monitoring pathological conditions. The aim of this study was to examine the possible correlation between volatile organic compounds (VOCs) in exhaled breath and the fecal microbiome by multivariate statistical analysis in gastric cancer patients (n = 16) and healthy controls (n = 33). Shotgun metagenomic sequencing was used to characterize the fecal microbiota. Breath-VOC profiles in the same participants were identified by an untargeted gas chromatography-mass spectrometry (GC-MS) technique. A multivariate statistical approach involving a canonical correlation analysis (CCA) and sparse principal component analysis identified the significant relationship between the breath VOCs and fecal microbiota. This relation was found to differ between gastric cancer patients and healthy controls. In 16 cancer cases, 14 distinct metabolites identified from the breath belonging to hydrocarbons, alcohols, aromatics, ketones, ethers, and organosulfur compounds were highly correlated with 33 fecal bacterial taxa (correlation of 0.891, p-value 0.045), whereas in 33 healthy controls, 7 volatile metabolites belonging to alcohols, aldehydes, esters, phenols, and benzamide derivatives correlated with 17 bacterial taxa (correlation of 0.871, p-value 0.0007). This study suggested that the correlation between fecal microbiota and breath VOCs was effective in identifying exhaled volatile metabolites and the functional effects of microbiome, thus helping to understand cancer-related changes and improving the survival and life expectancy in gastric cancer patients.

The Role of an Artificial Intelligence Method of Improving the Diagnosis of Neoplasms by Colonoscopy.

BACKGROUND: Colorectal cancer (CRC) is the third most common cancer worldwide. Colonoscopy is the gold standard examination that reduces the morbidity and mortality of CRC. Artificial intelligence (AI) could be useful in reducing the errors of the specialist and in drawing attention to the suspicious area. METHODS: A prospective single-center randomized controlled study was conducted in an outpatient endoscopy unit with the aim of evaluating the usefulness of AI-assisted colonoscopy in PDR and ADR during the day time. It is important to understand how already available CADe systems improve the detection of polyps and adenomas in order to make a decision about their routine use in practice. In the period from October 2021 to February 2022, 400 examinations (patients) were included in the study. One hundred and ninety-four patients were examined using the ENDO-AID CADe artificial intelligence device (study group), and 206 patients were examined without the artificial intelligence (control group). RESULTS: None of the analyzed indicators (PDR and ADR during morning and afternoon colonoscopies) showed differences between the study and control groups. There was an increase in PDR during afternoon colonoscopies, as well as ADR during morning and afternoon colonoscopies. CONCLUSIONS: Based on our results, the use of AI systems in colonoscopies is recommended, especially in circumstances of an increase of examinations. Additional studies with larger groups of patients at night are needed to confirm the already available data.

Identification of Key Volatile Organic Compounds Released by Gastric Tissues as Potential Non-Invasive Biomarkers for Gastric Cancer.

BACKGROUND: Volatilomics is a powerful tool capable of providing novel biomarkers for medical diagnosis and therapy monitoring. The objective of this study is to identify potential volatile biomarkers of gastric cancer. METHODS: The volatilomic signatures of gastric tissues obtained from two distinct populations were investigated using gas chromatography with mass spectrometric detection. RESULTS: Amongst the volatiles emitted, nineteen showed differences in their headspace concentrations above the normal and cancer tissues in at least one population of patients. Headspace levels of seven compounds (hexanal, nonanal, cyclohexanone, 2-nonanone, pyrrole, pyridine, and phenol) were significantly higher above the cancer tissue, whereas eleven volatiles (ethyl acetate, acetoin, 2,3-butanedione, 3-methyl-1-butanol, 2-pentanone, γ-butyrolactone, DL-limonene, benzaldehyde, 2-methyl-1-propanol, benzonitrile, and 3-methyl-butanal) were higher above the non-cancerous tissue. One compound, isoprene, exhibited contradictory alterations in both cohorts. Five compounds, pyridine, ethyl acetate, acetoin, 2,3-butanedione, and 3-methyl-1-butanol, showed consistent cancer-related changes in both populations. CONCLUSIONS: Pyridine is found to be the most promising biomarker candidate for detecting gastric cancer. The difference in the volatilomic signatures can be explained by cancer-related changes in the activity of certain enzymes, or pathways. The results of this study confirm that the chemical fingerprint formed by volatiles in gastric tissue is altered by gastric cancer.

Volatilomic Signatures of AGS and SNU-1 Gastric Cancer Cell Lines.

In vitro studies can help reveal the biochemical pathways underlying the origin of volatile indicators of numerous diseases. The key objective of this study is to identify the potential biomarkers of gastric cancer. For this purpose, the volatilomic signatures of two human gastric cancer cell lines, AGS (human gastric adenocarcinoma) and SNU-1 (human gastric carcinoma), and one normal gastric mucosa cell line (GES-1) were investigated. More specifically, gas chromatography mass spectrometry has been applied to pinpoint changes in cell metabolism triggered by cancer. In total, ten volatiles were found to be metabolized, and thirty-five were produced by cells under study. The volatiles consumed were mainly six aldehydes and two heterocyclics, whereas the volatiles released embraced twelve ketones, eight alcohols, six hydrocarbons, three esters, three ethers, and three aromatic compounds. The SNU-1 cell line was found to have significantly altered metabolism in comparison to normal GES-1 cells. This was manifested by the decreased production of alcohols and ketones and the upregulated emission of esters. The AGS cells exhibited the increased production of methyl ketones containing an odd number of carbons, namely 2-tridecanone, 2-pentadecanone, and 2-heptadecanone. This study provides evidence that the cancer state modifies the volatilome of human cells.

Modular Point-of-Care Breath Analyzer and Shape Taxonomy-Based Machine Learning for Gastric Cancer Detection.

BACKGROUND: Gastric cancer is one of the deadliest malignant diseases, and the non-invasive screening and diagnostics options for it are limited. In this article, we present a multi-modular device for breath analysis coupled with a machine learning approach for the detection of cancer-specific breath from the shapes of sensor response curves (taxonomies of clusters). METHODS: We analyzed the breaths of 54 gastric cancer patients and 85 control group participants. The analysis was carried out using a breath analyzer with gold nanoparticle and metal oxide sensors. The response of the sensors was analyzed on the basis of the curve shapes and other features commonly used for comparison. These features were then used to train machine learning models using Naïve Bayes classifiers, Support Vector Machines and Random Forests. RESULTS: The accuracy of the trained models reached 77.8% (sensitivity: up to 66.54%; specificity: up to 92.39%). The use of the proposed shape-based features improved the accuracy in most cases, especially the overall accuracy and sensitivity. CONCLUSIONS: The results show that this point-of-care breath analyzer and data analysis approach constitute a promising combination for the detection of gastric cancer-specific breath. The cluster taxonomy-based sensor reaction curve representation improved the results, and could be used in other similar applications.

High-risk individuals for gastric cancer would be missed for surveillance without subtyping of intestinal metaplasia.

The use of Operative Link on Gastritis Assessment (OLGA) and Operative Link on Gastritis Assessment based on Intestinal Metaplasia (OLGIM) staging system is recommended for identifying subjects at risk for developing gastric cancer; usually high-risk lesions are considered only as stages III and IV. Accumulating evidence suggests that incomplete intestinal metaplasia (IM) is important in the development of gastric cancer. Our aim has been to identify the prevalence of incomplete IM in patients with low-risk OLGA/OLGIM stages among a high-risk general population. Healthy adult volunteers aged 40-64 years were invited to undergo upper endoscopy within a regional GISTAR pilot study in Kazakhstan (n = 166). Gastric lesions were staged according to OLGA/OLGIM staging system. High iron diamine-alcian blue (HID-AB) was used for subtyping IM. IM prevalence overall was 45.8%. Incomplete IM was present in 52.6% (type II in 30.3% and type III in 22.3%), whereas complete IM was found in 47.4% individuals. The prevalence of OLGIM I and II stage were 39.8 and 4.8%, respectively, whereas OLGIM III was observed in 1.2%. The prevalence of incomplete IM in patients stratified to OLGIM I was 54.5% (type II in 31.8% and type III in 22.7%). High prevalence of incomplete IM was detected not only in subjects with extensive IM, but in those stratified as at the OLGIM I stage. Without IM subtyping, patients with high risk of gastric cancer development would be missed for surveillance.

Sensing gastric cancer via point-of-care sensor breath analyzer.

BACKGROUND: Detection of disease by means of volatile organic compounds from breath samples using sensors is an attractive approach to fast, noninvasive and inexpensive diagnostics. However, these techniques are still limited to applications within the laboratory settings. Here, we report on the development and use of a fast, portable, and IoT-connected point-of-care device (so-called, SniffPhone) to detect and classify gastric cancer to potentially provide new qualitative solutions for cancer screening. METHODS: A validation study of patients with gastric cancer, patients with high-risk precancerous gastric lesions, and controls was conducted with 2 SniffPhone devices. Linear discriminant analysis (LDA) was used as a classifying model of the sensing signals obatined from the examined groups. For the testing step, an additional device was added. The study group included 274 patients: 94 with gastric cancer, 67 who were in the high-risk group, and 113 controls. RESULTS: The results of the test set showed a clear discrimination between patients with gastric cancer and controls using the 2-device LDA model (area under the curve, 93.8%; sensitivity, 100%; specificity, 87.5%; overall accuracy, 91.1%), and acceptable results were also achieved for patients with high-risk lesions (the corresponding values for dysplasia were 84.9%, 45.2%, 87.5%, and 65.9%, respectively). The test-phase analysis showed lower accuracies, though still clinically useful. CONCLUSION: Our results demonstrate that a portable breath sensor device could be useful in point-of-care settings. It shows a promise for detection of gastric cancer as well as for other types of disease. LAY SUMMARY: A portable sensor-based breath analyzer for detection of gastric cancer can be used in point-of-care settings. The results are transferrable between devices via advanced IoT technology. Both the hardware and software of the reported breath analyzer could be easily modified to enable detection and monitirng of other disease states.

Prevalence and Potential Risk Factors of Helicobacter pylori Infection among Asymptomatic Individuals in Kazakhstan.

BACKGROUND: Helicobacter pylori (H. pylori) infection is associated with several risk factors such as demographic, socioeconomic status and personal habits, which vary in different populations. This is the most up-to-date data on H. pylori prevalence and potential risk factors for H. pylori infection among asymptomatic middle-aged individuals in Kazakhstan. METHODS: Apparently healthy individuals aged 40 to 64, who took part in the health control in the outpatient clinic, were invited to participate in the study; answered a questionnaire, donated a blood sample. The antibodies to H. pylori were analysed by latex agglutination method. The baseline characteristics of study subjects with or without H. pylori infection were compared using the Chi-square test. Odds ratio (OR) and 95% confidence intervals (CI) for the association between H. pylori infection and potential risk factors were estimated using multivariable logistic regression models. RESULTS: Altogether 166 subjects (59% male; the median age - 51 years old) were included; 104 (62.7%) were H. pylori positive. There were no statistically significant differences between H. pylori positive and H. pylori negative groups in respect to the gender, anthropometric measurements, socioeconomic factors and personal habits. The multiple variable analysis showed that age (OR, 1.99; 95% CI, 1.03 - 3.86; P=0.04) and increased salt intake (OR, 2.21; 95% CI, 1.12 - 4.35; P=0.02) were associated with H. pylori infection. CONCLUSIONS: More than half of the study subjects were infected with H. pylori in Kazakhstan. The prevalence of H. pylori infection was independently associated with older age and regular high salt consumption.

Review: Epidemiology of Helicobacter pylori.

This review summarizes the recent knowledge on the epidemiology of Helicobacter pylori and the potential modes of transmission. In addition to English language publications, the authors have included original full-text publications from Russia and Latin America published in the original languages. High H pylori prevalence has been reported in Russia, Jordan, Iran, China, and Latin American countries as well as in Arctic populations in Canada. Indigenous inhabitants in the Arctic were found to be infected substantially more frequently than non-indigenous inhabitants. In Amsterdam, the Netherlands, the ethnic minority groups were at a significantly higher risk of being H pylori seropositive compared to the Dutch population. For the first time, data on the prevalence from Armenia have been published indicating 41.5% H pylori prevalence. Convincing evidence on the decline of H pylori prevalence in Southeast Hungary and Taiwan was published. A study from Chile suggested high infection rates in newborns during the first month after birth. Two meta-analyses covered the potential correlation between H pylori and periodontal diseases, therefore addressing the potential oro-oral transmission rates. Periodontal disease was found to be more prevalent in H pylori-infected subjects. Other studies addressed the potential role of drinking water and food products as well as socioeconomic factors in transmitting the infection. Several studies in Asia addressed annual reinfection rates of H pylori, ranging from 1.5% in China to 3.1% in Korea. Finally, a review was published on the current evidence and future perspective of analysing H pylori in ancient human remains by a metagenomic approach.

The Volatilomic Footprints of Human HGC-27 and CLS-145 Gastric Cancer Cell Lines.

The presence of certain volatile biomarkers in the breath of patients with gastric cancer has been reported by several studies; however, the origin of these compounds remains controversial. In vitro studies, involving gastric cancer cells may address this problem and aid in revealing the biochemical pathways underlying the production and metabolism of gastric cancer volatile indicators. Gas chromatography with mass spectrometric detection, coupled with headspace needle trap extraction as the pre-concentration technique, has been applied to map the volatilomic footprints of human HGC-27 and CLS-145 gastric cancer cell lines and normal Human Stomach Epithelial Cells (HSEC). In total, 27 volatile compounds are found to be associated with metabolism occurring in HGC-27, CLS-145, and HSEC. Amongst these, the headspace concentrations of 12 volatiles were found to be reduced compared to those above just the cultivating medium, namely there was an observed uptake of eight aldehydes (2-methylpropanal, 2-methyl-2-propenal, 2-methylbutanal, 3-methylbutanal, hexanal, heptanal, nonanal, and benzaldehyde), three heterocyclic compounds (2-methyl-furan, 2-ethyl-furan, and 2-pentyl-furan), and one sulfur-containing compound (dimethyl disulphide). For the other 15 volatiles, the headspace concentrations above the healthy and cancerous cells were found to be higher than those found above the cultivating medium, namely the cells were found to release three esters (ethyl acetate, ethyl propanoate, and ethyl 2-methylbutyrate), seven ketones (2-pentanone, 2-heptanone, 2-nonanone, 2-undecanone, 2-tridecanone, 2-pentadecanone, and 2-heptadecanone), three alcohols (2-methyl-1-butanol, 3-methyl-1-butanol, and 2-ethyl-1-hexanol), one aromatic compound (toluene), and one sulfur containing compound [2-methyl-5-(methylthio) furan]. In comparison to HSEC, HGC-27 cancer cell lines were found to have significantly altered metabolism, manifested by an increased production of methyl ketones containing an odd number of carbons. Amongst these species, three volatiles were found exclusively to be produced by this cell line, namely 2-undecanone, 2-tridecanone, and 2-heptadecanone. Another interesting feature of the HGC-27 footprint is the lowered level of alcohols and esters. The CLS-145 cells exhibited less pronounced changes in their volatilomic pattern compared to HSEC. Their footprint was characterized by the upregulated production of esters and 2-ethyl-hexanol and downregulated production of other alcohols. We have therefore demonstrated that it is possible to differentiate between cancerous and healthy gastric cells using biochemical volatile signatures.

Prevalence of Atrophic Gastritis in Kazakhstan and the Accuracy of Pepsinogen Tests to Detect Gastric Mucosal Atrophy.

BACKGROUND: Atrophic gastritis is considered precursor condition for gastric cancer. There is so far limited evidence on the performance of pepsinogens for atrophy detection in Central Asia. The aim of our study was to detect the prevalence of atrophic gastritis in the asymptomatic adult population in Kazakhstan as well as address the accuracy of pepsinogen testing in atrophy detection. METHODS: Healthy individuals aged 40-64 were included. Upper endoscopy and pepsinogens (PG) evaluation were performed. PG were analysed in plasma by latex agglutination. Cut off values were used to define decreased PG values (PGR ≤ 3 and PG I ≤ 70 ng/mL); severely decreased PG values (PGR ≤ 2 and PG I ≤ 30 ng/mL). Biopsies were analyzed and obtained according to the updated Sydney System. PG test sensitivity, specificity and overall accuracy were assessed using the histological diagnosis as the "gold standard". RESULTS: Altogether 157 individuals - female 40,1% and male 59,9% were included. Histologically, moderate to severe corpus atrophy, was present only in 1,3% cases. From all study subjects, 26,8% had decreased plasma PG values with cut-off values PGR ≤ 3 and PG I ≤ 70 ng/mL. The sensitivity of the PG test with this cut-off values was 50,0%, specificity 73,5%, overall accuracy 73,2% for detection of moderate to severe atrophy in the corpus. The sensitivity of PG test with cut-off values PGR ≤ 2 and PG I ≤30 ng/mL was 50,0%, specificity 90,9% and overall accuracy 90,4%. CONCLUSIONS: The prevalence of gastric mucosal atrophy was low in the Kazakh population. Serological PG test screening nevertheless can play an important role in the diagnosis of gastric precancerous lesions. However, the diagnostic accuracy of the PG test is mainly dependent on the cut-off values for positive results.