RESUMO
Introduction: The progression of solid cancers is manifested at the systemic level as molecular changes in the metabolome of body fluids, an emerging source of cancer biomarkers. Methods: We analyzed quantitatively the serum metabolite profile using high-resolution mass spectrometry. Metabolic profiles were compared between breast cancer patients (n=112) and two groups of healthy women (from Poland and Norway; n=95 and n=112, respectively) with similar age distributions. Results: Despite differences between both cohorts of controls, a set of 43 metabolites and lipids uniformly discriminated against breast cancer patients and healthy women. Moreover, smaller groups of female patients with other types of solid cancers (colorectal, head and neck, and lung cancers) were analyzed, which revealed a set of 42 metabolites and lipids that uniformly differentiated all three cancer types from both cohorts of healthy women. A common part of both sets, which could be called a multi-cancer signature, contained 23 compounds, which included reduced levels of a few amino acids (alanine, aspartate, glutamine, histidine, phenylalanine, and leucine/isoleucine), lysophosphatidylcholines (exemplified by LPC(18:0)), and diglycerides. Interestingly, a reduced concentration of the most abundant cholesteryl ester (CE(18:2)) typical for other cancers was the least significant in the serum of breast cancer patients. Components present in a multi-cancer signature enabled the establishment of a well-performing breast cancer classifier, which predicted cancer with a very high precision in independent groups of women (AUC>0.95). Discussion: In conclusion, metabolites critical for discriminating breast cancer patients from controls included components of hypothetical multi-cancer signature, which indicated wider potential applicability of a general serum metabolome cancer biomarker.
RESUMO
Introduction: Magnetic resonance imgaing (MRI) targeted biopsy is the gold standard for prostate cancer (PCa) diagnosis. In this study, we examined the association between the operator's experience and the improvement in the precision of the MRI prostate biopsy procedure and the detection of PCa. Material and methods: We included consecutive patients who underwent prostate fusion biopsy. Data on biopsy duration, prostate-specific antigen (PSA) value, lesion size, number of samples taken, number of cores involved, and International Society of Urological Pathology (ISUP) grade were subjected to statistical analysis, with the study group divided into three consecutive time periods (tertiles). Results: There were statistically significant differences in biopsy duration between tertiles (p <0.001). The greatest difference in the involved/taken cores ratio occurred between the first and third tertile (p = 0.002). The difference between the first and second tertile was insignificant (p = 0.4), while the difference between the second and third tertile was statistically significant (p = 0.004). The differences between tertiles in Prostate Imaging and Reporting Data System v2.1 were also significant (p = 0.003). The PSA value (p = 0.036) was statistically significant, unlike prostate volume (p = 0.16), digital rectal examination (DRE) (p = 0.7), and ISUP grade (p = 0.7). There was no statistical difference between tested tertiles in the number of detected PCa ISUP ≥2 (Z = 0.191; p = 0.8). Conclusions: The abilities and precision of the operator increase with the increase in the number of procedures performed. The biopsy duration is shortened, and the detection of PCa during the procedure seems to improve with the operator's experience.