Investigation of volatile biomarkers in liver cancer blood using solid‐phase microextraction and gas chromatography/mass spectrometry

Abstract

Solid-phase microextraction (SPME) followed by gas chromatography/mass spectrometry (GC/MS) was used for the detection of liver cancer volatile biomarkers. Headspace SPME conditions (fiber coating, extraction temperature and extraction time) and desorption conditions were optimized and applied to the determination of volatiles in human blood. Between the liver cancer group (n = 19) and the normal group (n = 18), positive rates of 19 volatile compounds among the total of 47 detected were found to be different with statistical significance (p < 0.05, chi-squared test). We suggested hexanal, 1-octen-3-ol and octane, of the 19 compounds, as biomarkers of liver cancer with clinical diagnostic value. The sensitivity and specificity of 94.7% and 100% for hexanal, 84.2% and 100% for 1-octen-3-ol, and 89.5% and 100% for octane were obtained, respectively, after the cutoff values had been properly established. These results show that SPME-GC/MS is a simple, rapid and sensitive method for the investigation of volatile disease markers in human blood.

Solid phase microextraction, mass spectrometry and metabolomic approaches for detection of potential urinary cancer biomarkers—A powerful strategy for breast cancer diagnosis

“…Hexanal, which has also been identified in the samples, arises as a breakdown product of lipid peroxidation that is formed as a result of oxygen free radical (OFR) activity. The specificity of this marker for different cancers is under investigation [35]. Esters and higher alcohols were the chemical families with lowest contribution for the volatile metabolomic profile in breast cancer and healthy subjects.…”

Metabolomics Study of Stepwise Hepatocarcinogenesis From the Model Rats to Patients: Potential Biomarkers Effective for Small Hepatocellular Carcinoma Diagnosis

“…Metabolic fingerprinting and metabolite biomarkers have been studied for use in the discrimination or diagnosis of carcinoma (7,8), diabetes mellitus (9) and inborn errors (10). Nontarget metabolomics approaches have also been used to search for new biomarkers and to explore the mechanism of carcinogenesis in hepatic diseases (11)(12)(13)(14)(15)(16)(17)(18)(19)(20). According to these stud-ies, several circulation metabolites have been reported to be predictors for HCC, such as hexanal, 1-octen-3-ol, octane (18), and a combination of multimetabolites (21).…”

“…Nontarget metabolomics approaches have also been used to search for new biomarkers and to explore the mechanism of carcinogenesis in hepatic diseases (11)(12)(13)(14)(15)(16)(17)(18)(19)(20). According to these stud-ies, several circulation metabolites have been reported to be predictors for HCC, such as hexanal, 1-octen-3-ol, octane (18), and a combination of multimetabolites (21). Soga et al found that serum ␥-glutamyl dipeptides can be used as biomarkers for discriminating different liver diseases (22).…”

“…5B). Next, the HCC animals were discriminated from other non-HCC rats using LPC 22:5, 81.2% of the HCC (weeks 18,20), and 97.5% of the non-HCC (weeks 6 -15) rats were correctly discriminated, and the accuracy was 80 and 75% in the test group, respectively (cutoff value: 0.5, Fig. 5C).…”

“…B, Liver disease animal models (weeks 6 -20) versus control animals (weeks 6 -20). C, HCC (weeks 18,20) versus CLD (weeks 6 -14). The state in the border stage (week 16) was predicted using the above HCC and the CLD binary logistic regressions.…”