DNA methylation patterns associated with breast cancer prognosis that are specific to tumor subtype and menopausal status

Do Hyun Kim; Alexandra M Binder; Hua Zhou; Su Yon Jung

doi:10.3389/fgene.2023.1133443

DNA methylation patterns associated with breast cancer prognosis that are specific to tumor subtype and menopausal status

Front Genet. 2023 Mar 2:14:1133443. doi: 10.3389/fgene.2023.1133443. eCollection 2023.

Authors

Do Hyun Kim¹, Alexandra M Binder^{2

3}, Hua Zhou^{1

4}, Su Yon Jung^{5

6}

Affiliations

¹ Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States.
² Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, United States.
³ Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States.
⁴ Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, United States.
⁵ Translational Sciences Section, School of Nursing, University of California, Los Angeles, Los Angeles, CA, United States.
⁶ Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, United States.

Abstract

Tumor subtype and menopausal status are strong predictors of breast cancer (BC) prognosis. We aimed to find and validate subtype- or menopausal-status-specific changes in tumor DNA methylation (DNAm) associated with all-cause mortality or BC progression. Associations between site-specific tumor DNAm and BC prognosis were estimated among The Cancer Genome Atlas participants (n = 692) with Illumina Infinium HumanMethylation450 BeadChip array data. All-cause mortality and BC progression were modeled using Cox proportional hazards models stratified by tumor subtypes, adjusting for age, race, stage, menopausal status, tumor purity, and cell type proportion. Effect measure modification by subtype and menopausal status were evaluated by incorporating a product term with DNAm. Site-specific inference was used to identify subtype- or menopausal-status-specific differentially methylated regions (DMRs) and functional pathways. The validation of the results was carried out on an independent dataset (GSE72308; n = 180). We identified a total of fifteen unique CpG probes that were significantly associated ( $(P \leq 1 \times 10^{- 7})$ with survival outcomes in subtype- or menopausal-status-specific manner. Seven probes were associated with overall survival (OS) or progression-free interval (PFI) for women with luminal A subtype, and four probes were associated with PFI for women with luminal B subtype. Five probes were associated with PFI for post-menopausal women. A majority of significant probes showed a lower risk of OS or BC progression with higher DNAm. We identified subtype- or menopausal-status-specific DMRs and functional pathways of which top associated pathways differed across subtypes or menopausal status. None of significant probes from site-specific analyses met genome-wide significant level in validation analyses while directions and magnitudes of coefficients showed consistent pattern. We have identified subtype- or menopausal-status-specific DNAm biomarkers, DMRs and functional pathways associated with all-cause mortality or BC progression, albeit with limited validation. Future studies with larger independent cohort of non-post-menopausal women with non-luminal A subtypes are warranted for identifying subtype- and menopausal-status-specific DNAm biomarkers for BC prognosis.

Keywords: DNA methylation signatures; breast cancer; menopause; subtypes; survival and prognosis.

Abstract

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