Biomarkers of genetic susceptibility to cancer: applications to epidemiological studies

The application of statistical methods using VOCs to identify patients with lung cancer

In this work, an attempt was made to determine a group of lung cancer biomarkers. For this study, breath samples collected from 137 patients with confirmed lung cancer were analyzed by the SPME-GC/MS method. As a reference group, exhaled air from 143 healthy volunteers with different smoking habits (active smokers, passive smokers and nonsmokers) was applied. Statistical methods such as discriminant analysis (DA) and the CHAID model tree were used for data processing and evaluation. In the breath of patients with lung cancer, increased concentration of ethanol, acetone, butane, dimethyl sulfide, isoprene, propanal, 1-propanol, 2-pentanone, furan, o-xylene and ethylbenzene was observed in comparison to healthy nonsmokers. Furthermore, pentanal, hexanal and nonane were identified only in the breath of people who suffered from cancer. DA confirmed the importance of these compounds and allowed us to identify patients with lung cancer from healthy volunteers. In the exhaled air of healthy smokers (passive and active), a higher concentration of acetonitrile, benzene and furan derivatives was observed than in nonsmokers. DA revealed that in order to recognize healthy volunteers with different smoking habits by breath analysis, butyrolactone, carbon disulfide and dimethyl sulfide have to be considered.

Investigation of lung cancer biomarkers by hyphenated separation techniques and chemometrics

BACKGROUND

Volatile organic compounds (VOCs) present in breath of lung cancer patients and released by lung cancer cells were determined. As a reference sample breath collected from healthy volunteers and lung segments of cells with proper morphology were used.

METHODS

Solid phase microextraction and gas chromato-graphy mass spectrometry (SPME-GC/MS) method was applied for VOC analysis. Statistical methods have been developed to find similarities between patterns of investigated compounds within three populations of samples: exhaled air samples from patients with lung cancer, headspace of lung tissues with healthy and cancer cells.

RESULTS

Quantitative analysis of VOCs in the headspace of lung tissues revealed that cancer cells released higher concentrations of ethanol, acetone, carbon disulfide, dimethyl sulfide, 1-propanol, 2-propanol, 2-butanone and 2-pentanone than healthy tissues. The increase of concentration of the same compounds was observed in the breath of patients with lung cancer in comparison to breath from healthy non-smoking volunteers.

CONCLUSIONS

Detection of lung cancer is possible by volatile biomarkers analysis in breath.

Lung cancer susceptibility: are we on our way to identifying a high-risk group?

Many studies have investigated lung cancer susceptibility based on the presence of low-penetrance, high-frequency single nucleotide polymorphisms. Identifying such susceptibility polymorphisms may lead to the development of tests that allow a more focused follow-up of a high-risk group. Genetic polymorphisms of xenobiotic metabolism, DNA repair, cell-cycle control, immunity, addiction and nutritional status have been described as promising candidates. Genetic polymorphisms in both metabolic activation (Phase I) and detoxification (Phase II) enzymes influence DNA damage. The DNA repair system is a critical cellular response that counteracts the carcinogenic effects of DNA. Thus, genetically determined susceptibility to carcinogens depends on the balance between metabolic and DNA repair enzymes. This review evaluates whether or not a specific polymorphism or a combination of such polymorphisms can effectively predict high-risk groups.