Current applications of chromatographic methods for diagnosis and identification of potential biomarkers in cancer

GC-MS and multivariate analysis reveal partial serum metabolome restoration by bevacizumab in a colon cancer rat model: An untargeted metabolomics investigation

Bevacizumab is an anti-angiogenic therapeutic agent that targets vascular endothelial growth factor (VEGF) and has been approved for the treatment of several types of cancer, including colon cancer. Herein, a GC-MS based metabolomics approach was employed to investigate the impact of bevacizumab on the serum metabolome of colon cancer rats. Multivariate chemometric analysis models such as PCA and PLS-DA showed a clear separation between the control, cancer and bevacizumab-treated groups, suggesting that bevacizumab administration induced significant metabolic alterations. Furthermore, pairwise comparisons between the studied groups using the OPLS-DA model in addition to univariate analysis identified several discriminatory metabolites belonged to various chemical classes including amino acids, organic acids and fatty acids that were perturbed between the studied groups. Interestingly, bevacizumab treatment was able to partially restore some of the cancer-induced metabolic disturbances, indicating its potential therapeutic efficacy via improving the tumor vasculature and nutrient delivery. Besides, pathway analysis of the differential metabolites identified key metabolic pathways affected by bevacizumab, which included valine, leucine and isoleucine metabolism, pyruvate metabolism and butanoate metabolism. However, little effects were observed on lipid metabolites such as palmitic acid and stearic acid and consequently their related metabolic pathways such as fatty acid biosynthesis metabolism suggesting that bevacizumab has more prominent effect on energy and amino acid metabolisms as compared to fatty acid metabolism in colon cancer rats. Overall, our study provided novel insights into the metabolic mechanisms underlying the therapeutic effects of bevacizumab in colon cancer rats via the use of a comprehensive GC-MS metabolomics approach.

Aptamers and New Bioreceptors for the Electrochemical Detection of Biomarkers Expressed in Hepatocellular Carcinoma

Hepatocellular carcinoma is a malignancy associated with high mortality and increasing incidence. Early detection of this disease could help increase survival and overall patient benefit. Non-invasive strategies for the diagnosis of this medical condition are of utmost importance. In this scope, the detection of hepatocellular carcinoma biomarkers could provide a useful diagnostic tool. Aptamers represent as short, single-stranded DNAs or RNAs that can specifically bind selected analytes, and also as pseudo-biorecognition elements that can be employed for electrode functionalization. Also, other types of DNA sequences can be used for the construction of DNA-based biosensors applied for the quantification of hepatocellular carcinoma biomarkers. Herein, we will be analyzing recent examples of aptasensors and DNA biosensors for the detection of hepatocellular carcinoma biomarkers like micro-RNAs, long non-coding RNAs, exosomes, circulating tumor cells and proteins. The literature data is discussed comparatively in a critical manner highlighting the advantages of using electrochemical biosensors in diagnosis, as well as the use of nanomaterials and biocomponents in the functionalization of electrodes for improved sensitivity and selectivity.

Induced volatolomics of pathologies

Volatolomics allows us to elucidate cell metabolic processes in real time. In particular, a volatile organic compound (VOC) excreted from our bodies may be specific for a certain disease, such that measuring this VOC may afford a simple, fast, accessible and safe diagnostic approach. Yet, finding the optimal endogenous volatile marker specific to a pathology is non-trivial because of interlaboratory disparities in sample preparation and analysis, as well as high interindividual variability. These limit the sensitivity and specificity of volatolomics and its applications in biological and clinical fields but have motivated the development of induced volatolomics. This approach aims to overcome issues by measuring VOCs that result not from an endogenous metabolite but, rather, from the pathogen-specific or metabolic-specific enzymatic metabolism of an exogenous biological or chemical probe. In this Review, we introduce volatile-compound-based probes and discuss how they can be exploited to detect and discriminate pathogenic infections, to assess organ function and to diagnose and monitor cancers in real time. We focus on cases in which labelled probes have informed us about metabolic processes and consider the potential and drawbacks of the probes for clinical trials. Beyond diagnostics, VOC-based probes may also be effective tools to explore biological processes more generally.

A sensitive and selective magnetic graphene composite-modified polycrystalline-silicon nanowire field-effect transistor for bladder cancer diagnosis

In this study, we describe the urinary quantification of apolipoprotein A II protein (APOA2 protein), a biomarker for the diagnosis of bladder cancer, using an n-type polycrystalline silicon nanowire field-effect transistor (poly-SiNW-FET). The modification of poly-SiNW-FET by magnetic graphene with long-chain acid groups (MGLA) synthesized via Friedel-Crafts acylation was compared with that obtained using short-chain acid groups (MGSA). Compared with MGSA, the MGLA showed a higher immobilization degree and bioactivity to the anti-APOA2 antibody (Ab) due to its lower steric hindrance. In addition, the magnetic properties enabled rapid separation and purification during Ab immobilization, ultimately preserving its bioactivity. The Ab-MGLA/poly-SiNW-FET exhibited a linear dependence of relative response to the logarithmical concentration in a range between 19.5pgmL(-1) and 1.95µgmL(-1), with a limit of detection (LOD) of 6.7pgmL(-1). An additional washing step before measurement aimed at excluding the interfering biocomponents ensured the reliability of the assay. We conclude that our biosensor efficiently distinguishes mean values of urinary APOA2 protein concentrations between patients with bladder cancer (29-344ngmL(-1)) and those with hernia (0.425-9.47ngmL(-1)).