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

被引:7
作者
Ali, Imran [1 ]
Dreij, Kristian [1 ]
Baker, Simon [2 ]
Hogberg, Johan [1 ]
Korhonen, Anna [2 ]
Stenius, Ulla [1 ]
机构
[1] Karolinska Inst, Inst Environm Med, Box 210, SE-17177 Stockholm, Sweden
[2] Univ Cambridge, Dept Theoret & Appl Linguist, Cambridge, England
基金
英国医学研究理事会; 瑞典研究理事会;
关键词
CELL-TRANSFORMATION ASSAY; LUNG-CANCER RISK; PROMOTING ACTIVITY; HALLMARKS; CARCINOGENS; CONTACT; XUANWEI; MODES;
D O I
10.1289/EHP6702
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
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页数:15
相关论文
共 48 条
[1]   Grouping chemicals for health risk assessment: A text mining-based case study of polychlorinated biphenyls (PCBs) [J].
Ali, Imran ;
Guo, Yufan ;
Silins, Ilona ;
Hogberg, Johan ;
Stenius, Ulla ;
Korhonen, Anna .
TOXICOLOGY LETTERS, 2016, 241 :32-37
[2]   Time to Say Goodbye to the 16 EPA PAHs? Toward an Up-to-Date Use of PACs for Environmental Purposes [J].
Andersson, Jan T. ;
Achten, Christine .
POLYCYCLIC AROMATIC COMPOUNDS, 2015, 35 (2-4) :330-354
[4]  
[Anonymous], 2014, P COLING 2014 25 INT
[5]  
[Anonymous], 2019, Off. J. Eur. Union L, V30, P112
[6]  
[Anonymous], 2000, Environ Sci Pollut Res, V3, P23
[7]  
[Anonymous], 2012, NTP BOARD SCI COUNS
[8]   Detection of initiating as well as promoting activity of chemicals by a novel cell transformation assay using v-Ha-ras-transfected BALB/c 3T3 cells (Bhas 42 cells) [J].
Asada, S ;
Sasaki, K ;
Tanaka, N ;
Takeda, K ;
Hayashi, M ;
Umeda, M .
MUTATION RESEARCH-GENETIC TOXICOLOGY AND ENVIRONMENTAL MUTAGENESIS, 2005, 588 (01) :7-21
[9]   Special Report: Policy A review of human carcinogens-Part F: Chemical agents and related occupations [J].
Baan, Robert ;
Grosse, Yann ;
Straif, Kurt ;
Secretan, Beatrice ;
El Ghissassi, Fatiha ;
Bouvard, Veronique ;
Benbrahim-Tallaa, Lamia ;
Guha, Neela ;
Freeman, Crystal ;
Galichet, Laurent ;
Cogliano, Vincent .
LANCET ONCOLOGY, 2009, 10 (12) :1143-1144
[10]   Cancer Hallmarks Analytics Tool (CHAT): a text mining approach to organize and evaluate scientific literature on cancer [J].
Baker, Simon ;
Ali, Imran ;
Silins, Ilona ;
Pyysalo, Sampo ;
Guo, Yufan ;
Hogberg, Johan ;
Stenius, Ulla ;
Korhonen, Anna .
BIOINFORMATICS, 2017, 33 (24) :3973-3981