Journal Article
. 2017 Dec;12(12).
doi: 10.1371/journal.pone.0189750.

Evaluation of the EGFR polymorphism R497K in two cohorts of neoadjuvantly treated breast cancer patients

Marcelo Sobral-Leite 1 Esther H Lips 1 Hayra de Andrade Vieira-Monteiro 2 Letícia Carlos Giacomin 2 Daniely Regina Freitas-Alves 2 Sten Cornelissen 1 Lennart Mulder 1 Jelle Wesseling 1 Marjanka K Schmidt 1 Rosane Vianna-Jorge 2 
Affiliations
  • PMID: 29267323
  •     47 References
  •     3 citations

Abstract

Pathological response of breast cancer to neoadjuvant chemotherapy (NAC) presents great variability, and new prognostic biomarkers are needed. Our aim was to evaluate the association of the epidermal growth factor receptor gene (EGFR) polymorphism R497K (rs2227983) with prognostic features and clinical outcomes of breast cancer, including the pathological response to NAC and the recurrence-free survival (RFS). Tumoral complete response (tCR) was defined by no remaining invasive cancer in the excised breast, whereas pathological complete response (pCR) was defined by no remaining invasive cancer both in the excised breast and lymph nodes. Two independent cohorts were analyzed: one from Brazil (INCA, n = 288) and one from The Netherlands (NKI-AVL, n = 255). In the INCA cohort, the variant (Lys-containing) genotypes were significantly associated with lower proportion of tCR (ORadj = 0.92; 95%CI = 0.85-0.99), whereas in the NKI-AVL cohort they were associated with tumor grade 3 (p = 0.035) and with triple-negative subtype (p = 0.032), but not with clinical outcomes. Such distinct prognostic associations may have arisen due to different neoadjuvant protocols (p < 0.001), or to lower age at diagnosis (p < 0.001) and higher proportion of tumor grade 3 (p = 0.018) at the NKI-AVL cohort. Moreover, NKI-AVL patients achieved better proportion of pCR (21.2% vs 8.3%, p < 0.001) and better RFS (HRadj = 0.48; 95% adjCI = 0.26-0.86) than patients from INCA. In conclusion, large scale studies comprehending different populations are needed to evaluate the impact of genome variants on breast cancer outcomes.

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