A genome-wide cell-free DNA methylation analysis identifies an episignature associated with metastatic luminal B breast cancer

Abstract

Breast cancers of the luminal B subtype are frequent tumors with high proliferation and poor prognosis. Epigenetic alterations have been found in breast tumors and in biological fluids. We aimed to profile the cell-free DNA (cfDNA) methylome of metastatic luminal B breast cancer (LBBC) patients using an epigenomic approach to discover potential noninvasive biomarkers. Plasma cfDNA was analyzed using the Infinium MethylationEpic array in a cohort of 14 women, including metastatic LBBC patients and nontumor controls. The methylation levels of cfDNA and tissue samples were validated with droplet digital PCR. The methylation and gene expression data of 582 primary luminal breast tumors and 79 nontumor tissues were obtained from The Cancer Genome Atlas (TCGA). We found an episignature of 1,467 differentially methylated CpGs that clearly identified patients with LBBC. Among the genes identified, the promoter hypermethylation of WNT1 was validated in cfDNA, showing an area under the ROC curve (AUC) of 0.86 for the noninvasive detection of metastatic LBBC. Both paired cfDNA and primary/metastatic breast tumor samples showed hypermethylation of WNT1. TCGA analysis revealed significant WNT1 hypermethylation in the primary tumors of luminal breast cancer patients, with a negative association between WNT1 methylation and gene expression. In this proof-of-principle study, we discovered an episignature associated with metastatic LBBC using a genome-wide cfDNA methylation approach. We also identified the promoter hypermethylation of WNT1 in cfDNA as a potential noninvasive biomarker for luminal breast cancer. Our results support the use of EPIC arrays to identify new epigenetic noninvasive biomarkers in breast cancer.

Methods in DNA methylation array dataset analysis: A review

“…These modules frequently correspond to biologically relevant pathways or processes, containing related hub genes within the module. Another study done by Rodriguez et al, 2022, used Hierarchical linear models (HLM) coupled with the Mann-Whitney U test to measure the accurate estimates of the methylation differences in the expression data between different tumour and non-tumour groups of breast cancer patients, to account for promoter hypermethylation of WNT1 [106] . Over time, Hierarchical Linear Model (HLM) is preferred for its robust handling of large amounts of missing data and its ability to estimate individual changes over time with fewer assumptions [107] .…”

“… (i) Receiver operating characteristic (ROC) curve depicts the diagnostic behavior of genes. (i) 28,799 differentially methylated CpGs [106] 2 Univariate and multivariate Cox regression analysis 560 patients’ samples of breast cancer (raw IDAT files) (i) This method screens the prognostic CpGs and survival analysis of patients. (i) Methylation prognostic model deriving methylation-based gene prognostic signature (i) Favourable prognosis: 66 and 49 CpG loci poor prognosis: 17 CpG loci.…”

Omics Technologies Improving Breast Cancer Research and Diagnostics

“…In other studies, extensive hypermethylation was identified in the TWIST , RASSF1A , CCND2 and HIN1 genes in breast carcinoma samples [ 89 , 90 ]. New targets are being uncovered, including the hypermethylation of the WNT1 promoter in patients with metastatic tumors and RASGRF1, CPXM1 , HOXA10 and DACH1 in TBNC [ 91 , 92 ]. CDH13 and GSTP1 hypermethylation are also more common in triple-negative and lymph-node-positive BC patients, respectively [ 93 ].…”

Liquid Biopsy in Clinical Oncology

“…Было показано, что пациенты со злокачественными опухолями имеют более высокое содержание циркулирующей ДНК, чем здоровые люди, -это обусловлено дополнительным поступлением в кровь фрагментов ДНК из опухолевых клеток. Позднее обнаружилось, что всевозможные аберрации, присущие «материнской» опухоли, могут быть достоверно детектированы в циркулирующих фрагментах ДНК: мутации в онкогенах и опухолевых супрессорах [23]; микросателлитная нестабильность [24]; транслокации, делеции и амплификации [25][26][27][28]; нарушения метилирования [29,30] Исследования последних лет подтверждают высокую репрезентативность цоДНК по отношению к злокачественному заболеванию в целом, что в сочетании с доступностью этого материала обеспечивает его исключительную ценность и перспективность для молекулярной диагностики. Принимая во внимание гетерогенность опухолевой ткани, можно ожидать, что жидкостная биопсия во многих случаях может оказаться даже предпочтительней, чем традиционная биопсия опухолевых очагов [31][32][33][34].…”