Natalie C DuPré1, Yujing J Heng2, Benjamin A Raby3, Kimberly Glass4, Jaime E Hart5, Jen-Hwa Chu6, Catherine Askew7, A Heather Eliassen8, Susan E Hankinson9, Peter Kraft10, Francine Laden11, Rulla M Tamimi8. 1. Channing Division of Network Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Epidemiology and Population Health, University of Louisville School of Public Health and Information Sciences, Louisville, KY, USA. Electronic address: natalie.dupre@louisville.edu. 2. Department of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; Cancer Research Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA. 3. Channing Division of Network Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, USA; Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. 4. Channing Division of Network Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA. 5. Channing Division of Network Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 6. Section of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA. 7. Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA. 8. Channing Division of Network Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 9. Channing Division of Network Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA. 10. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02215, USA. 11. Channing Division of Network Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Abstract
BACKGROUND: Fine particulate matter (PM2.5) has been associated with breast cancer specific mortality, particularly for women with Stage I cancer. We examined the biological pathways that are perturbed by PM2.5 exposures by analyzing gene expression measurements from breast tissue specimens. METHODS: The Nurses' Health Studies (NHS and NHSII) are prospective cohorts with archival breast tissue specimens from breast cancer cases. Global gene expression data were ascertained with the Affymetrix Glue Human Transcriptome Array 3.0. PM2.5 was estimated using spatio-temporal models linked to participants' home addresses. All analyses were performed separately in tumor (n = 591) and adjacent-normal (n = 497) samples, and stratified by estrogen receptor (ER) status and stage. We used multivariable linear regression, gene-set enrichment analyses (GSEA), and the least squares kernel machine (LSKM) to assess whether 3-year cumulative average pre-diagnosis PM2.5 exposure was associated with breast-tissue gene expression pathways among predominately Stage I and II women (90.7%) and postmenopausal (81.2%) women. Replication samples (tumor, n = 245; adjacent-normal, n = 165) were measured on Affymetrix Human Transcriptome Array (HTA 2.0). RESULTS: Overall, no pathways in the tumor area were significantly associated with PM2.5 exposure. Among 272 adjacent-normal samples from Stage I ER-positive women, PM2.5 was associated with perturbations in the oxidative phosphorylation, protein secretion, and mTORC1 signaling pathways (GSEA and LSKM p-values <0.05); however, results were not replicated in a small set of replication samples (n = 80). CONCLUSIONS: PM2.5 was generally not associated with breast tissue gene expression though was suggested to perturb oxidative phosphorylation and regulation of proteins and cellular signaling in adjacent-normal breast tissue. More research is needed on the biological role of PM2.5 that influences breast tumor progression.
BACKGROUND: Fine particulate matter (PM2.5) has been associated with breast cancer specific mortality, particularly for women with Stage I cancer. We examined the biological pathways that are perturbed by PM2.5 exposures by analyzing gene expression measurements from breast tissue specimens. METHODS: The Nurses' Health Studies (NHS and NHSII) are prospective cohorts with archival breast tissue specimens from breast cancer cases. Global gene expression data were ascertained with the Affymetrix Glue Human Transcriptome Array 3.0. PM2.5 was estimated using spatio-temporal models linked to participants' home addresses. All analyses were performed separately in tumor (n = 591) and adjacent-normal (n = 497) samples, and stratified by estrogen receptor (ER) status and stage. We used multivariable linear regression, gene-set enrichment analyses (GSEA), and the least squares kernel machine (LSKM) to assess whether 3-year cumulative average pre-diagnosis PM2.5 exposure was associated with breast-tissue gene expression pathways among predominately Stage I and II women (90.7%) and postmenopausal (81.2%) women. Replication samples (tumor, n = 245; adjacent-normal, n = 165) were measured on Affymetrix Human Transcriptome Array (HTA 2.0). RESULTS: Overall, no pathways in the tumor area were significantly associated with PM2.5 exposure. Among 272 adjacent-normal samples from Stage I ER-positive women, PM2.5 was associated with perturbations in the oxidative phosphorylation, protein secretion, and mTORC1 signaling pathways (GSEA and LSKM p-values <0.05); however, results were not replicated in a small set of replication samples (n = 80). CONCLUSIONS: PM2.5 was generally not associated with breast tissue gene expression though was suggested to perturb oxidative phosphorylation and regulation of proteins and cellular signaling in adjacent-normal breast tissue. More research is needed on the biological role of PM2.5 that influences breast tumor progression.
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