Volatile organic compounds analysis optimization and biomarker discovery in urine of Non-Hodgkin lymphoma patients before and during chemotherapy

Development of a headspace-solid phase microextraction gas chromatography-high resolution mass spectrometry method for analyzing volatile organic compounds in urine: Application in breast cancer biomarker discovery

BACKGROUND AND AIM

Breast cancer (BC) is the leading cause of cancer-related death in females. The development of non-invasive methods for the early diagnosis of BC still remains challenge. Here, we aimed to discover the urinary volatile organic compounds (VOCs) pattern of BC patients and identify potential VOC biomarkers for BC diagnosis.

METHODS

Urine samples were analyzed by headspace-solid phase microextraction (HS-SPME) combined with gas chromatography-high resolution mass spectrometry (GC-HRMS). To assure reliable analysis, the factors influencing HS-SPME extraction efficiency were comprehensively investigated and optimized by combing the Plackett-Burman design (PBD) with the central composite design (CCD). The established HS-SPME/GC-HRMS method was validated and applied to analyze urine samples from BC patients (n = 80) and healthy controls (n = 88).

RESULTS

A total number of 134 VOCs belonging to distinct chemical classes were identified by GC-HRMS. BC patients demonstrated unique urinary VOCs pattern. Orthogonal partial least squares-discriminant analysis (OPLS-DA) showed a clear separation between BC patients and healthy controls. Eight potential VOC biomarkers were identified using multivariate and univariate statistical analysis. The predictive ability of candidate VOC biomarkers was further investigated by the random forest (RF) algorithm. The candidate VOC biomarkers yielded 76.3% sensitivity and 85.4% specificity on the training set, and achieved 76.0% sensitivity and 92.3% specificity on the validation set.

CONCLUSIONS

Overall, this work not only established a standardized HS-SPME/GC-HRMS approach for urinary VOCs analysis, but also highlighted the value of urinary VOCs for BC diagnosis. The knowledge gained from this study paves the way for early diagnosis of BC using urine in a non-invasive manner.

The untargeted urine volatilome for biomedical applications: methodology and volatilome database

Chemically diverse in compounds, urine can give us an insight into metabolic breakdown products from foods, drinks, drugs, environmental contaminants, endogenous waste metabolites, and bacterial by-products. Hundreds of them are volatile compounds; however, their composition has never been provided in detail, nor has the methodology used for urine volatilome untargeted analysis. Here, we summarize key elements for the untargeted analysis of urine volatilome from a comprehensive compilation of literature, including the latest reports published. Current achievements and limitations on each process step are discussed and compared. 34 studies were found retrieving all information from the urine treatment to the final results obtained. In this report, we provide the first specific urine volatilome database, consisting of 841 compounds from 80 different chemical classes.

Preparation of a Novel Solid Phase Microextraction Fiber for Headspace GC-MS Analysis of Hazardous Odorants in Landfill Leachate

The practice of odorant analysis can often be very challenging because odorants are usually composed of a host of volatile organic compounds (VOCs) at low concentrations. Preconcentration with solid phase microextraction (SPME) is a conventional technique for the enrichment of these volatile compounds before analysis by headspace gas chromatography-mass spectrometry (GC-MS). However, commercially available SPME products usually bear the defects of weak mechanical strength and high cost. In this work, novel SPME fibers were prepared by a one-pot synthesis procedure from divinylbenzene (DVB), porous carbon powder (Carbon) and polydimethylsiloxane (PDMS). Factors that influence the extraction efficiency, such as extraction temperature, extraction time, salting effects, pH, stirring rate, desorption temperature and time, were optimized. VOCs in landfills pose a great threat to human health and the environment. The new SPME fibers were successfully applied in the analysis of VOCs from the leachate of a cyanobacteria landfill. Quantification methods of major odor contributors were established, and a good linearity (r > 0.998) was obtained, with detection limits in the range of 0.30–0.50 ng/L. Compared to commercial SPME fibers, the new material has higher extraction efficacy and higher precision. Hence, it is suitable for the determination of hazardous odorants of various sources.

From Sampling to Analysis: How to Achieve the Best Sample Throughput via Sampling Optimization and Relevant Compound Analysis Using Sum of Ranking Differences Method?

The determination of an optimal volatile sampling procedure is always a key question in analytical chemistry. In this paper, we introduce the application of a novel non-parametric statistical method, the sum of ranking differences (SRD), for the quick and efficient determination of optimal sampling procedures. Different types of adsorbents (Porapak Q, HayeSep Q, and Carbotrap) and sampling times (1, 2, 4, and 6 h) were used for volatile collections of lettuce (Lactuca sativa) samples. SRD identified 6 h samplings as the optimal procedure. However, 1 or 4 h sampling with HayeSep Q and 2 h sampling with Carbotrap are still efficient enough if the aim is to reduce sampling time. Based on our results, SRD provides a novel way to not only highlight an optimal sampling procedure but also decrease evaluation time.