DNA methylation age in paired tumor and adjacent normal breast tissue in Chinese women with breast cancer.


Journal

Clinical epigenetics
ISSN: 1868-7083
Titre abrégé: Clin Epigenetics
Pays: Germany
ID NLM: 101516977

Informations de publication

Date de publication:
30 03 2023
Historique:
received: 19 08 2022
accepted: 13 03 2023
medline: 31 3 2023
entrez: 29 3 2023
pubmed: 30 3 2023
Statut: epublish

Résumé

Few studies have examined epigenetic age acceleration (AA), the difference between DNA methylation (DNAm) predicted age and chronological age, in relation to somatic genomic features in paired cancer and normal tissue, with less work done in non-European populations. In this study, we aimed to examine DNAm age and its associations with breast cancer risk factors, subtypes, somatic genomic profiles including mutation and copy number alterations and other aging markers in breast tissue of Chinese breast cancer (BC) patients from Hong Kong. We performed genome-wide DNA methylation profiling of 196 tumor and 188 paired adjacent normal tissue collected from Chinese BC patients in Hong Kong (HKBC) using Illumina MethylationEPIC array. The DNAm age was calculated using Horvath's pan-tissue clock model. Somatic genomic features were based on data from RNA sequencing (RNASeq), whole-exome sequencing (WES), and whole-genome sequencing (WGS). Pearson's correlation (r), Kruskal-Wallis test, and regression models were used to estimate associations of DNAm AA with somatic features and breast cancer risk factors. DNAm age showed a stronger correlation with chronological age in normal (Pearson r = 0.78, P < 2.2e-16) than in tumor tissue (Pearson r = 0.31, P = 7.8e-06). Although overall DNAm age or AA did not vary significantly by tissue within the same individual, luminal A tumors exhibited increased DNAm AA (P = 0.004) while HER2-enriched/basal-like tumors exhibited markedly lower DNAm AA (P = < .0001) compared with paired normal tissue. Consistent with the subtype association, tumor DNAm AA was positively correlated with ESR1 (Pearson r = 0.39, P = 6.3e-06) and PGR (Pearson r = 0.36, P = 2.4e-05) gene expression. In line with this, we found that increasing DNAm AA was associated with higher body mass index (P = 0.039) and earlier age at menarche (P = 0.035), factors that are related to cumulative exposure to estrogen. In contrast, variables indicating extensive genomic instability, such as TP53 somatic mutations, high tumor mutation/copy number alteration burden, and homologous repair deficiency were associated with lower DNAm AA. Our findings provide additional insights into the complexity of breast tissue aging that is associated with the interaction of hormonal, genomic, and epigenetic mechanisms in an East Asian population.

Sections du résumé

BACKGROUND
Few studies have examined epigenetic age acceleration (AA), the difference between DNA methylation (DNAm) predicted age and chronological age, in relation to somatic genomic features in paired cancer and normal tissue, with less work done in non-European populations. In this study, we aimed to examine DNAm age and its associations with breast cancer risk factors, subtypes, somatic genomic profiles including mutation and copy number alterations and other aging markers in breast tissue of Chinese breast cancer (BC) patients from Hong Kong.
METHODS
We performed genome-wide DNA methylation profiling of 196 tumor and 188 paired adjacent normal tissue collected from Chinese BC patients in Hong Kong (HKBC) using Illumina MethylationEPIC array. The DNAm age was calculated using Horvath's pan-tissue clock model. Somatic genomic features were based on data from RNA sequencing (RNASeq), whole-exome sequencing (WES), and whole-genome sequencing (WGS). Pearson's correlation (r), Kruskal-Wallis test, and regression models were used to estimate associations of DNAm AA with somatic features and breast cancer risk factors.
RESULTS
DNAm age showed a stronger correlation with chronological age in normal (Pearson r = 0.78, P < 2.2e-16) than in tumor tissue (Pearson r = 0.31, P = 7.8e-06). Although overall DNAm age or AA did not vary significantly by tissue within the same individual, luminal A tumors exhibited increased DNAm AA (P = 0.004) while HER2-enriched/basal-like tumors exhibited markedly lower DNAm AA (P = < .0001) compared with paired normal tissue. Consistent with the subtype association, tumor DNAm AA was positively correlated with ESR1 (Pearson r = 0.39, P = 6.3e-06) and PGR (Pearson r = 0.36, P = 2.4e-05) gene expression. In line with this, we found that increasing DNAm AA was associated with higher body mass index (P = 0.039) and earlier age at menarche (P = 0.035), factors that are related to cumulative exposure to estrogen. In contrast, variables indicating extensive genomic instability, such as TP53 somatic mutations, high tumor mutation/copy number alteration burden, and homologous repair deficiency were associated with lower DNAm AA.
CONCLUSIONS
Our findings provide additional insights into the complexity of breast tissue aging that is associated with the interaction of hormonal, genomic, and epigenetic mechanisms in an East Asian population.

Identifiants

pubmed: 36991516
doi: 10.1186/s13148-023-01465-1
pii: 10.1186/s13148-023-01465-1
pmc: PMC10062015
doi:

Types de publication

Journal Article Research Support, N.I.H., Intramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

55

Informations de copyright

© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.

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Auteurs

Hela Koka (H)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.

Clara Bodelon (C)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.

Steve Horvath (S)

Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
San Diego Institute of Science, Alto Labs, San Diego, CA, USA.

Priscilla Ming Yi Lee (PMY)

The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong., Prince of Wales Hospital, Sha Tin, N.T., Hong Kong SAR, China.

Difei Wang (D)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.
Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.

Lei Song (L)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.
Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.

Tongwu Zhang (T)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.

Amber N Hurson (AN)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.

Jennifer Lyn Guida (JL)

Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.

Bin Zhu (B)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.

Maeve Bailey-Whyte (M)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.
School of Medicine, University of Limerick, Limerick, Ireland.

Feng Wang (F)

The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong., Prince of Wales Hospital, Sha Tin, N.T., Hong Kong SAR, China.

Cherry Wu (C)

Department of Pathology, North District Hospital, Hong Kong, China.

Koon Ho Tsang (KH)

Department of Pathology, Yan Chai Hospital, Hong Kong, China.

Yee-Kei Tsoi (YK)

Department of Surgery, North District Hospital, Hong Kong, China.

W C Chan (WC)

Department of Surgery, North District Hospital, Hong Kong, China.

Sze Hong Law (SH)

Department of Surgery, North District Hospital, Hong Kong, China.

Ray Ka Wai Hung (RKW)

Department of Surgery, North District Hospital, Hong Kong, China.

Gary M Tse (GM)

Department of Anatomical and Cellular Pathology, The Chinese University of Hong Kong, Hong Kong, China.

Karen Ka-Wan Yuen (KK)

Department of Pathology, North District Hospital, Hong Kong, China.

Eric Karlins (E)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.
Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.

Kristine Jones (K)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.
Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.

Aurelie Vogt (A)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.
Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.

Bin Zhu (B)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.
Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.

Amy Hutchinson (A)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.
Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.

Belynda Hicks (B)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.
Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA.

Montserrat Garcia-Closas (M)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.

Stephen Chanock (S)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.

Jill Barnholtz-Sloan (J)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.
Center for Biomedical Informatics and Information Technology, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA.

Lap Ah Tse (LA)

The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong., Prince of Wales Hospital, Sha Tin, N.T., Hong Kong SAR, China. shelly@cuhk.edu.hk.

Xiaohong R Yang (XR)

Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, MD, USA. royang@mail.nih.gov.

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