Multiwalled Carbon Nanotube-Induced Gene Signatures in the Mouse Lung: Potential Predictive Value for Human Lung Cancer Risk and Prognosis

Abstract

Concerns over the potential for multiwalled carbon nanotubes (MWCNT) to induce lung carcinogenesis have emerged. This study sought to (1) identify gene expression signatures in the mouse lungs following pharyngeal aspiration of well-dispersed MWCNT and (2) determine if these genes were associated with human lung cancer risk and progression. Genome-wide mRNA expression profiles were analyzed in mouse lungs (n = 160) exposed to 0, 10, 20, 40, or 80 μg of MWCNT by pharyngeal aspiration at 1, 7, 28, and 56 d postexposure. By using pairwise statistical analysis of microarray (SAM) and linear modeling, 24 genes were selected, which have significant changes in at least two time points, have a more than 1.5-fold change at all doses, and are significant in the linear model for the dose or the interaction of time and dose. Additionally, a 38-gene set was identified as related to cancer from 330 genes differentially expressed at d 56 postexposure in functional pathway analysis. Using the expression profiles of the cancer-related gene set in 8 mice at d 56 postexposure to 10 μg of MWCNT, a nearest centroid classification accurately predicts human lung cancer survival with a significant hazard ratio in training set (n = 256) and test set (n = 186). Furthermore, both gene signatures were associated with human lung cancer risk (n = 164) with significant odds ratios. These results may lead to development of a surveillance approach for early detection of lung cancer and prognosis associated with MWCNT in the workplace.

Acknowledgments

This study is supported by NIH/NLM R01LM009500 (PI: Guo) and NCRR P20RR16440 and Supplement (PD: Guo). The findings and conclusions in this report are those of the author(s) and do not necessarily represent the views of the National Institute for Occupational Safety and Health. Software license and training for Ingenuity Pathway Analysis and Pathway Studio is supported by NIH/NCRR P2016477.