Aflatoxins are fungal metabolites found in feeds and foods. When the ruminants eat feedstuffs containing Aflatoxin B1 (AFB1), this toxin is metabolized and Aflatoxin M1 (AFM1) is excreted in milk. International Agency for Research on Cancer (IARC) classified AFB1 and AFM1 as human carcinogens belonging to Group 1 and Group 2B, respectively, with the formation of DNA adducts. In the last years, some epidemiological studies were conducted on cancer patients aimed to evaluate the effects of AFB1 and AFM1 exposure on cancer cells in order to verify the correlation between toxin exposure and cancer cell proliferation and invasion. In this review, we summarize the activation pathways of AFB1 and AFM1 and the data already reported in literature about their correlation with cancer development and progression. Moreover, considering that few data are still reported about what genes/proteins/miRNAs can be used as damage markers due to AFB1 and AFM1 exposure, we performed a bioinformatic analysis based on interaction network and miRNA predictions to identify a panel of genes/proteins/miRNAs that can be used as targets in further studies for evaluating the effects of the damages induced by AFB1 and AFM1 and their capacity to induce cancer initiation.

Hepatoblastoma incidence has been associated with different environmental factors even if no data are reported about a correlation between aflatoxin exposure and hepatoblastoma initiation. Considering that hepatoblastoma develops in infants and children and aflatoxin M1 (AFM1), the aflatoxin B1 (AFB1) hydroxylated metabolite, can be present in mothers’ milk and in marketed milk products, in this study we decided to test the effects of AFM1 on a hepatoblastoma cell line (HepG2). Firstly, we evaluated the effects of AFM1 on the cell viability, apoptosis, cell cycle, and metabolomic and cytokinomic profile of HepG2 cells after treatment. AFM1 induced: (1) a decrease of HepG2 cell viability, reaching IC50 at 9 µM; (2) the blocking of the cell cycle in the G0/G1 phase; (3) the decrease of formiate levels and incremented level of some amino acids and metabolites in HepG2 cells after treatment; and (4) the increase of the concentration of three pro-inflammatory cytokines, IL-6, IL-8, and TNF-α, and the decrease of the anti-inflammatory interleukin, IL-4. Our results show that AFM1 inhibited the growth of HepG2 cells, inducing both a modulation of the lipidic, glycolytic, and amino acid metabolism and an increase of the inflammatory status of these cells.

Arsenic and arsenic-derivative compounds, named as arsenicals, represent a worldwide problem for their effect on the human health and, in particular, for their capability to increase the risk of developing cancer such as kidney, bladder and prostate cancer. The main source of arsenical exposure is drinking water. Nowadays, it is well known that the chronic exposure to arsenicals leads to a series of epigenetic alterations that have a role in arsenic-induced effects on human health including cancer. Based on these observations, the aim of our study was to select by network analysis the genes/proteins/miRNAs implicated in kidney, bladder and prostate cancer development upon arsenical exposure. From this analysis we identified: (i) the nodes linking the three molecular networks specific for kidney, bladder and prostate cancer; (ii) the relative HUB nodes (RXRA, MAP3K7, NR3C1, PABPC1, NDRG1, RELA and CTNNB1) that link the three cancer networks; (iii) the miRNAs able to target these HUB nodes. In conclusion, we highlighted a panel of potential molecules related to the molecular mechanisms of arsenical-induced cancerogenesis and suggest their utility as biomarkers or therapeutic targets.

In metastatic colorectal cancer (mCRC) patients (pts), treatment strategies integrating liver resection with more effective therapies offer better 5-year survival rates than palliative chemotherapy alone. However, resectability is established only on clinical-morphovolumetric criteria, liver resection is a complex and costly procedure and relapse occurs in almost 2/3 of pts after potentially curative resection. Therefore, prompt identification of pts at higher risk of recurrence is critical to avoid not-beneficial, expensive procedures. Aberrant metabolism is an emerging hallmark of cancer and recent observations suggest that specific metabolic changes can be used to stratify pts for prognosis and drug-response. We evaluated by 600MHz NMR spectroscopy the metabolomics profiling on sera from 30 mCRC pts, enrolled in the Obelics trial (NCT01718873), which investigated different schedules of bevacizumab in combination with oxaliplatin plus fluoropyrimidines regimens, and subdivided on the basis of outcome, in good (R) vs bad responders (NR) according to PFS: 12 months or longer (R, n = 12) and shorter than 12 months (NR, n = 18). We compared the samples of the two mCRC pts groups, collected at response evaluation when resectability was established in case of appropriate tumor reduction and PCA, sPLS-DA and loading plots evidenced metabolites with statistically different levels between the two sub-groups. ROC curves were performed to identify the cutoff levels of these significant metabolites to be correlated with patient survival. In this way we demonstrated that low levels of 3-hydroxybutyrate and of hydroxyproline as well as high levels of histidine correlated with both poor progression free survival (PFS) and overall survival (OS). Notably, either 3-hydroxybutyrate or histidine are better predictor of both PFS and OS compared to pathologic response on resected metatastases. Lipidomics analysis confirmed clear differences between R and NR pts indicating statistically significant increase of lipids in NR pts, with both higher triglycerides and phospholipids correlating with poor PFS and OS. This latter effects, may reflect, at least in part a non specific inflammatory response; indeed a significant increase of pro-inflammatory cytokines was also demonstrated in NR pts sera by cytokinomics using multiplex ELISA approach. Finally, basal serum metabolomics analysis in both NR and R pts demonstrated that on-treatment evaluation is more informative than pre-treatment evaluation to stratify patients for outcome. Overall, these data suggest that NMR-based metabolomics is a potent and affordable method that could play a role in the prediction of mCRC outcome. Citation Format: Alfredo Budillon, Susan Costantini, Angela Sorice, Francesca Capone, Silvia Marchese, Elena Di Gennaro, Carlo Vitagliano, Fabiana Tatangelo, Alfonso De Stefano, Franco Bianco, Paolo Delrio, Francesco Izzo, Antonio Avallone. Outcome prediction of metastatic colorectal cancer patients undergoing liver resection by analyzing serum metabolomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 5268.