An Exploratory Research On Expiratory Detection Of Gastric Cancer And Hepatocellular Cell Line

Background:Early diagnoses of gastric cancer and its differentiation from benignlesions,based on gastroendoscopyand biopsy withhistopathologic examination, isinvasive, costly, time-consuming, and highly reliant on the clinicians’expertise.Methods:We study the feasibility of a novel method in oncology based on breathanalysis for identifying gastric diseases. Alveolar exhaled breath samples collected from130volunteers and were analyzed using nanomaterial-based sensors.Predictive modelswere built employing discriminant factor analysis (DFA) pattern recognition.Classification success was determined using leave-one-out cross-validation. Thechemical composition of the breath samples was studied using gas chromatographycoupled with mass spectrometry (GC-MS).Findings:Excellent discrimination was achieved with the nanomaterial-based sensorsbetweenthe breath-prints of gastric cancer and non-malignant gastric conditions, andbetween their sub-categories.12substances in the breath were identified and could beassociated with gastric cancer, gastric ulcer and less severe gastric problems.Interpretation:The studied breathprints possess a new and promising possibility todiagnose gastric cancer and the related gastric diseases. In the future these technologies could provide a low-price high-scale screening tool. Objective: To investigate the in vitro feasibility for prediction of metastasis ofliver cancer with volatile biomarkers.Methods: Headspace gases collected from five hepatoma cells and one normalliver cell were analyzed using nanomaterial-based sensors. Predictive models werebuilt employing discriminant factor analysis (DFA) pattern recognition.Classification success was determined using leave-one-out cross-validation. Thechemical composition of the breath samples was studied using gas chromatographycoupled with mass spectrometry (GC-MS).Results: Excellent discrimination was achieved with the nanomaterial-basedsensors between the breath-prints of hepatoma cell lines and normal liver cells, andbetween high-and low-metastatic capacity hepatoma cells.9substances in thebreath were identified and could be associated with normal liver cell, low-andhigh-metastatic potential hepatoma cells.Conclusion: The studied breath-prints possess a new and promising possibility topredict the metastatic ability in vitro hepatocarcinoma cells. In the future thesetechnologies for forecasting the likelihood of metastasis, could lead toimprovement in cancer treatment, as well as new treatment for directly preventingmetastasis.