METHODS: Serum samples were digested with nitric acid and hydrochloric acid (ratio 1:1, v/v) and analysed by inductively coupled plasma-mass spectrometry (ICP-MS). Seronorm®, a human-derived serum control material was used as quality control samples.
RESULTS: The coefficient of variations for both intra- and inter-day precisions were consistently <15% for all elements. The validated method was later tested on 30 human serum samples to evaluate its applicability.
CONCLUSION: We have successfully developed and validated a precise and accurate analytical method for determining 25 trace elements requiring very low volume of human serum.
Methods: The systematic review searched through two databases of Medline and Cochrane up to 24th June 2017. The search strategy focused on Population, Intervention, Comparison, and Outcomes (PICO). We searched the role of trace elements in cancer and focusing on case-control studies in CRC to obtain an insight into the differences in trace element concentrations between those with and without cancer.
Results: The serum concentrations of Ca, Cu, Mg, Mn, Se, Si, and Zn were lower in CRC patients but for Co and S the levels were higher in CRC patients. The concentrations of Cd, Cr, Cu, Mg, Mn, Pb, and Zn were increased in patients with metastasis, but not in Se. As for colon tissue specimens, inconsistent levels were reported between studies, notably in Cu, Se, and Zn. No changes were reported for B and Ca levels. Most of the trace elements in the tissue specimens showed higher concentrations of Cr, Fe, K, Mg, P, Rb, S, and Si compared to Br.
Conclusion: With the growing interest to understand the link between trace elements in carcinogenesis and the possible interactions, multi assessment analysis of a larger cohort of samples is necessary.
METHODS: A systematic search of the Web of Science, PubMed, and Cochrane Library databases was conducted using PRISMA guidelines. Ten studies investigating serum metabolite biomarkers of CRC and polyps using different analytical platforms and study populations were included. QUADOMICS tool was used to analyse the quality of the included studies. All reported metabolites were then enriched into the pathways using MetaboAnalyst 5.0.
RESULTS: We found that several potential signature metabolites overlapped between studies, including tyrosine, lysine, cystine, arabinose, and lactate for CRC and lactate and glutamate for polyps. The most affected pathways related to CRC were the urea cycle, glutathione metabolism, purine metabolism, glutamate metabolism, and ammonia recycling. In contrast, those affected in the polyps were the urea cycle, glutamate metabolism, glutathione metabolism, arginine and proline metabolism, and carnitine synthesis.
CONCLUSIONS: This review has found commonly detected serum metabolites for polyps and CRC with huge potential to be used in clinical settings. However, the differences between altered pathways in polyps and CRC, other external factors, and their effects on the regulation level, sensitivity, and specificity of each identified metabolite remained unclear, which could benefit from a further extensive cohort study and well-defined analysis equipment.