Αρχειοθήκη ιστολογίου

Πέμπτη 6 Σεπτεμβρίου 2018

DNA methylation derived systemic inflammation indices are associated with head and neck cancer development and survival

Publication date: October 2018

Source: Oral Oncology, Volume 85

Author(s): Srikant Ambatipudi, Ryan Langdon, Rebecca C. Richmond, Matthew Suderman, Devin C. Koestler, Karl T. Kelsey, Nabila Kazmi, Christopher Penfold, Karen M. Ho, Wendy McArdle, Susan M. Ring, Miranda Pring, Tim Waterboer, Michael Pawlita, Tom R. Gaunt, George Davey Smith, Steve Thomas, Andy R. Ness, Caroline L. Relton

Abstract
Objectives

Head and neck squamous cell carcinoma (HNSCC) is often associated with chronic systemic inflammation (SI). In the present study, we assessed if DNA methylation-derived SI (mdSI) indices: Neutrophil-to-Lymphocyte ratio (mdNLR) and Lymphocyte-to-Monocyte ratio (mdLMR) are associated with the presence of HNSCC and overall survival (OS).

Materials and methods

We used two peripheral blood DNA methylation datasets: an HNSCC case-control dataset (n = 183) and an HNSCC survival dataset (n = 407) to estimate mdSI indices. We then performed multivariate regressions to test the association between mdSI indices, HNSCC development and OS.

Results

Multivariate logistic regression revealed that elevated mdNLR was associated with increased odds of being an HNSCC case (OR = 3.25, 95% CI = 2.14–5.34, P = 4 × 10−7) while the converse was observed for mdLMR (OR = 0.88, 95% CI = 0.81–0.90, P = 2 × 10−3).

In the HNSCC survival dataset, HPV16-E6 seropositive HNSCC cases had an elevated mdLMR (P = 9 × 10−5) and a lower mdNLR (P = 0.003) compared to seronegative patients. Multivariate Cox regression in the HNSCC survival dataset revealed that lower mdLMR (HR = 1.96, 95% CI = 1.30–2.95, P = 0.0013) but not lower mdNLR (HR = 0.68, 95% CI = 0.46–1.00, P = 0.0501) was associated with increased risk of death.

Conclusion

Our results indicate that mdSI estimated by DNA methylation data is associated with the presence of HNSCC and overall survival. The mdSI indices may be used as a valuable research tool to reliably estimate SI in the absence of cell-based estimates. Rigorous validation of our findings in large prospective studies is warranted in the future.



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