Personalized PDAC chip with functional endothelial barrier for tumour biomarker detection: A platform for precision medicine applications.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer characterised by poor survival rates and an increasing global incidence. Advances in the staging and categorization of pancreatic tumours, along with the discovery of functional mutations, have made precision treatments possible, which may lead to better clinical results. To further improve customized treatment approaches, in vitro models that can be used for functional drug sensitivity testing and precisely mimic the disease at the organ level are required. In this study, we present a workflow for creating a personalized PDAC chip utilising primary tumour-derived human pancreatic organoids (hPOs) and Human Umbilical Vein Endothelial Cells (HUVECs) to simulate the vascular barrier and tumour interactions within a PDMS-free organ-on-a-chip system. The patient PDAC tissue, expanded as tumour hPOs, could be cultured as adherent cells on the chip for more than 50 days, allowing continuous monitoring of cell viability through outflows from tumour and endothelial channels. Our findings demonstrate a gradual increase in cell density and cell turnover in the pancreatic tumor channel. Tumour-specific biomarkers, including CA-19.9, TIMP-1, Osteopontin, MIC-1, ICAM-1 and sAXL were consistently detected in the PDAC chip outflows. Comparative analyses between tissue culture plates and microfluidic conditions revealed significant differences in biomarker secretion patterns, highlighting the advantages of the microfluidics approach. This PDAC chip provides a stable, reproducible tumour model system with a functional endothelial cell barrier, suitable for drug sensitivity and secretory biomarker studies, thus serving as a platform for functional precision medicine application and multi-organ chip development.

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.

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.

Breath Volatile Organic Compounds in Surveillance of Gastric Cancer Patients following Radical Surgical Management.

As of today, there is a lack of a perfect non-invasive test for the surveillance of patients for potential relapse following curative treatment. Breath volatile organic compounds (VOCs) have been demonstrated to be an accurate diagnostic tool for gastric cancer (GC) detection; here, we aimed to prove the yield of the markers in surveillance, i.e., following curative surgical management. Patients were sampled in regular intervals before and within 3 years following curative surgery for GC; gas chromatography-mass spectrometry (GC-MS) and nanosensor technologies were used for the VOC assessment. GC-MS measurements revealed a single VOC (14b-Pregnane) that significantly decreased at 12 months, and three VOCs (Isochiapin B, Dotriacontane, Threitol, 2-O-octyl-) that decreased at 18 months following surgery. The nanomaterial-based sensors S9 and S14 revealed changes in the breath VOC content 9 months after surgery. Our study results confirm the cancer origin of the particular VOCs, as well as suggest the value of breath VOC testing for cancer patient surveillance, either during the treatment phase or thereafter, for potential relapse.

The Association of Circulating L-Carnitine, γ-Butyrobetaine and Trimethylamine N-Oxide Levels with Gastric Cancer.

Our study aimed to evaluate the association between gastric cancer (GC) and higher concentrations of the metabolites L-carnitine, γ-butyrobetaine (GBB) and gut microbiota-mediated trimethylamine N-oxide (TMAO) in the circulation. There is evidence suggesting that higher levels of TMAO and its precursors in blood can be indicative of either a higher risk of malignancy or indeed its presence; however, GC has not been studied in this regard until now. Our study included 83 controls without high-risk stomach lesions and 105 GC cases. Blood serum L-carnitine, GBB and TMAO levels were measured by ultra-high-performance liquid chromatography-mass spectrometry (UPLC/MS/MS). Although there were no significant differences between female control and GC groups, we found a significant difference in circulating levels of metabolites between the male control group and the male GC group, with median levels of L-carnitine reaching 30.22 (25.78-37.57) nmol/mL vs. 37.38 (32.73-42.61) nmol/mL (p < 0.001), GBB-0.79 (0.73-0.97) nmol/mL vs. 0.97 (0.78-1.16) nmol/mL (p < 0.05) and TMAO-2.49 (2.00-2.97) nmol/mL vs. 3.12 (2.08-5.83) nmol/mL (p < 0.05). Thus, our study demonstrated the association between higher blood levels of L-carnitine, GBB, TMAO and GC in males, but not in females. Furthermore, correlations of any two investigated metabolites were stronger in the GC groups of both genders in comparison to the control groups. Our findings reveal the potential role of L-carnitine, GBB and TMAO in GC and suggest metabolic differences between genders. In addition, the logistic regression analysis revealed that the only significant factor in terms of predicting whether the patient belonged to the control or to the GC group was the blood level of L-carnitine in males only. Hence, carnitine might be important as a biomarker or a risk factor for GC, especially in males.