Therapeutic approaches focused on the inflammatory microenvironment are currently gaining more support, as biomolecules involved in the inflammatory colorectal cancer (CRC) tumor microenvironment are being explored. We analyzed tumor and paired normal tissue samples from CRC patients (n = 22) whom underwent tumor resection surgery. We assessed 39 inflammation-involved biomolecules (multiplex magnetic bead-based immunoassay), CEA and CA19-9 (ELISA assay) and the tissue expression levels of occludin and also pErk, STAT1 and STAT3 transcriptional factors (western blot). Tumor staging has been established by histopathological evaluation of HE stained tumor tissue sections. We report 32 biomarkers displaying statistically significant differences in tumor vs. control. Additionally, positive statistical biomarker correlations were found between MMP2–IL8 and BAFF–IL8 (Pearson correlation coefficients > 0.751), while APRIL–MMP2, APRIL–BAFF and APRIL–IL8 were negatively correlated (correlation coefficients < − 0.650). While APRIL, BAFF, IL8 and MMP2 did not modulate with tumor stage, they were inversely related to the immune infiltrate level and CD163 tissue expression. We conclude that the significantly decreased APRIL and increased BAFF, IL8 and MMP2 expression were tumor-specific and deserve consideration in the development of new treatments. Also, the positive correlation between Chitinase 3-like 1 and IL8 (0.57) or MMP2 (0.50) suggest a role in tumor growth and metastasis pathways.

Background: Biomarker profiles should represent a coherent description of the colorectal cancer (CRC) stage and its predicted evolution. Methods: Using droplet digital PCR, we detected the allelic frequencies (AF) of KRAS, NRAS, BRAF, and EGFR mutations from 60 tumors. We employed a pair-wise association approach to estimate the risk involving AF mutations as outcome variables for clinical data and as predicting variables for tumor-staging. We evaluated correlations between mutations of AFs and also between the mutations and histopathology features (tumor staging, inflammation, differentiation, and invasiveness). Results: KRAS G12/G13 mutations were present in all patients. KRAS Q61 was significantly associated with poor differentiation, high desmoplastic reaction, invasiveness (ypT4), and metastasis (ypM1). NRAS and BRAF were associated with the right-side localization of tumors. Diabetic patients had a higher risk to exhibit NRAS G12/G13 mutations. BRAF and NRAS G12/G13 mutations co-existed in tumors with invasiveness limited to the submucosa. Conclusions: The associations we found and the mutational AF we reported may help to understand disease processes and may be considered as potential CCR biomarker candidates. In addition, we propose representative mutation panels associated with specific clinical and histopathological features of CRC, as a unique opportunity to refine the degree of personalization of CRC treatment.

The risk of mycotoxins co-occurrence in extrusion-produced dry foods increases due to their composition based on various grains and vegetables. This study aimed to validate a risk estimation for the association between ingredients and the ELISA-detected levels of DON, FUM, ZEA, AFs, T2, and OTA in 34 dry dog food products. The main ingredients were corn, beet, and oil of different origins (of equal frequency, 79.41%), rice (67.6%), and wheat (50%). DON and FUM had the strongest positive correlation (0.635, p = 0.001). The presence of corn in the sample composition increased the median DON and ZEA levels, respectively, by 99.45 μg/kg and 65.64 μg/kg, p = 0.011. In addition to DON and ZEA levels, integral corn presence increased the FUM median levels by 886.61 μg/kg, p = 0.005. For corn gluten flour-containing samples, DON, FUM, and ZEA median differences still existed, and OTA levels also differed by 1.99 μg/kg, p < 0.001. Corn gluten flour presence was strongly associated with DON levels >403.06 μg/kg (OR = 38.4, RR = 9.90, p = 0.002), FUM levels >1097.56 μg/kg (OR = 5.56, RR = 1.45, p = 0.048), ZEA levels >136.88 μg/kg (OR = 23.00, RR = 3.09, p = 0.002), and OTA levels >3.93 μg/kg (OR = 24.00, RR = 3.09, p = 0.002). Our results suggest that some ingredients or combinations should be avoided due to their risk of increasing mycotoxin levels.

No abstract