Data and literature gathering in chemical cancer risk assessment

Application of Text Mining in Risk Assessment of Chemical Mixtures: A Case Study of Polycyclic Aromatic Hydrocarbons (PAHs)

BACKGROUND

Cancer risk assessment of complex exposures, such as exposure to mixtures of polycyclic aromatic hydrocarbons (PAHs), is challenging due to the diverse biological activities of these compounds. With the help of text mining (TM), we have developed TM tools-the latest iteration of the Cancer Risk Assessment using Biomedical literature tool (CRAB3) and a Cancer Hallmarks Analytics Tool (CHAT)-that could be useful for automatic literature analyses in cancer risk assessment and research. Although CRAB3 analyses are based on carcinogenic modes of action (MOAs) and cover almost all the key characteristics of carcinogens, CHAT evaluates literature according to the hallmarks of cancer referring to the alterations in cellular behavior that characterize the cancer cell.

OBJECTIVES

The objective was to evaluate the usefulness of these tools to support cancer risk assessment by performing a case study of 22 European Union and U.S. Environmental Protection Agency priority PAHs and diesel exhaust and a case study of PAH interactions with silica.

METHODS

We analyzed PubMed literature, comprising 57,498 references concerning priority PAHs and complex PAH mixtures, using CRAB3 and CHAT.

RESULTS

CRAB3 analyses correctly identified similarities and differences in genotoxic and nongenotoxic MOAs of the 22 priority PAHs and grouped them according to their known carcinogenic potential. CHAT had the same capacity and complemented the CRAB output when comparing, for example, benzo[a]pyrene and dibenzo[a,l]pyrene. Both CRAB3 and CHAT analyses highlighted potentially interacting mechanisms within and across complex PAH mixtures and mechanisms of possible importance for interactions with silica.

CONCLUSION

These data suggest that our TM approach can be useful in the hazard identification of PAHs and mixtures including PAHs. The tools can assist in grouping chemicals and identifying similarities and differences in carcinogenic MOAs and their interactions. https://doi.org/10.1289/EHP6702.

Exocrine pancreatic carcinogenesis and autotaxin expression

Exocrine pancreatic cancer is an aggressive disease with an exceptionally high mortality rate. Genetic analysis suggests a causative role for environmental factors, but consistent epidemiological support is scarce and no biomarkers for monitoring the effects of chemical pancreatic carcinogens are available. With the objective to identify common traits for chemicals inducing pancreatic tumors we studied the National Toxicology Program (NTP) bioassay database. We found that male rats were affected more often than female rats and identified eight chemicals that induced exocrine pancreatic tumors in males only. For a hypothesis generating process we used a text mining tool to analyse published literature for suggested mode of actions (MOA). The resulting MOA analysis suggested inflammatory responses as common feature. In cell studies we found that all the chemicals increased protein levels of the inflammatory protein autotaxin (ATX) in Panc-1, MIA PaCa-2 or Capan-2 cells. Induction of MMP-9 and increased invasive migration were also frequent effects, consistent with ATX activation. Testosterone has previously been implicated in pancreatic carcinogenesis and we found that it increased ATX levels. Our data show that ATX is a target for chemicals inducing pancreatic tumors in rats. Several lines of evidence implicate ATX and its product lysophosphatidic acid in human pancreatic cancer. Mechanisms of action may include stimulated invasive growth and metastasis. ATX may interact with hormones or onco- or suppressor-genes often deregulated in exocrine pancreatic cancer. Our data suggest that ATX is a target for chemicals promoting pancreatic tumor development.