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Detection of differentially methylated CpGs between tumour and adjacent benign cells in diagnostic prostate cancer samples

  • Liesel M. FitzGerald
  • , Chol Hee Jung
  • , Ee Ming Wong
  • , Ji Hoon E. Joo
  • , Julie K. Bassett
  • , James G. Dowty
  • , Xiaoyu Wang
  • , James Y. Dai
  • , Janet L. Stanford
  • , Neil O’Callaghan
  • , Tim Nottle
  • , John Pedersen
  • , Graham G. Giles
  • , Melissa C. Southey

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Differentially methylated CpG sites (dmCpGs) that distinguish prostate tumour from adjacent benign tissue could aid in the diagnosis and prognosis of prostate cancer. Previously, the identification of such dmCpGs has only been undertaken in radical prostatectomy (RP) samples and not primary diagnostic tumour samples (needle biopsy or transurethral resection of the prostate). We interrogated an Australian dataset comprising 125 tumour and 43 adjacent histologically benign diagnostic tissue samples, including 41 paired samples, using the Infinium Human Methylation450 BeadChip. Regression analyses of paired tumour and adjacent benign samples identified 2,386 significant dmCpGs (Bonferroni p < 0.01; delta-β ≥ 40%), with LASSO regression selecting 16 dmCpGs that distinguished tumour samples in the full Australian diagnostic dataset (AUC = 0.99). Results were validated in independent North American (npaired = 19; AUC = 0.87) and The Cancer Genome Atlas (TCGA; npaired = 50; AUC = 0.94) RP datasets. Two of the 16 dmCpGs were in genes that were significantly down-regulated in Australian tumour samples (Bonferroni p < 0.01; GSTM2 and PRKCB). Ten additional dmCpGs distinguished low (n = 34) and high Gleason (n = 88) score tumours in the diagnostic Australian dataset (AUC = 0.95), but these performed poorly when applied to the RP datasets (North American: AUC = 0.66; TCGA: AUC = 0.62). The DNA methylation marks identified here could augment and improve current diagnostic tests and/or form the basis of future prognostic tests.

Original languageEnglish
Article number17877
Number of pages8
JournalScientific Reports
Volume14
Issue number1
DOIs
Publication statusPublished - 2 Aug 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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