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 volat…

Class Decomposition for Gastric Cancer Detection from Breath

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 c…

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 f…

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/…

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 an…