Cellular and clinical impact of protein phosphatase enzyme epigenetic silencing in multiple cancer tissues

Abstract

Background: Protein Phosphatase Enzymes (PPE) and protein kinases simultaneously control phosphorylation mechanisms that tightly regulate intracellular signalling pathways and stimulate cellular responses. In human malignancies, PPE and protein kinases are frequently mutated resulting in uncontrolled kinase activity and PPE suppression, leading to cell proliferation, migration and resistance to anti-cancer therapies. Cancer associated DNA hypermethylation at PPE promoters gives rise to transcriptional silencing (epimutations) and is a hallmark of cancer. Despite recent advances in sequencing technologies, data availability and computational capabilities, only a fraction of PPE have been reported as transcriptionally inactive as a consequence of epimutations.

Methods: In this study, we examined promoter-associated DNA methylation profiles in Protein Phosphatase Enzymes and their Interacting Proteins (PPEIP) in a cohort of 705 cancer patients in five tissues (Large intestine, Oesophagus, Lung, Pancreas and Stomach) in three cell models (primary tumours, cancer cell lines and 3D embedded cancer cell cultures). As a subset of PPEIP are known tumour suppressor genes, we analysed the impact of PPEIP promoter hypermethylation marks on gene expression, cellular networks and in a clinical setting.

Results: Here, we report epimutations in PPEIP are a frequent occurrence in the cancer genome and manifest independent of transcriptional activity. We observed that different tumours have varying susceptibility to epimutations and identify specific cellular signalling networks that are primarily affected by epimutations. Additionally, RNA-seq analysis showed the negative impact of epimutations on most (not all) Protein Tyrosine Phosphatase transcription. Finally, we detected novel clinical biomarkers that inform on patient mortality and anti-cancer treatment sensitivity.

Conclusions: We propose that DNA hypermethylation marks at PPEIP frequently contribute to the pathogenesis of malignancies and within the precision medicine space, hold promise as biomarkers to inform on clinical features such as patient survival and therapeutic response.

Keywords: Biomarker; Cancer; DNA methylation; Epigenetics; Gene-silencing; Hyper-methylation; Protein prosphatase enzymes; RNA-seq; Transcriptomics.

Fig. 1

Infinium Human Methylation 450K BeadChip (450K) probe distribution and promoter hyper-methylation analysis reveals cancer-associated epimutations occur with varying frequencies in multiple tissues. A. Distribution of 450K probes across all gene promoters (and CpG island-specific) and PPEIP promoters (also showing CpG island specific probes). B. % of promoter CpG genomic annotations. TSS1500 = CpG present within 1500 bp from transcription start site (TSS), TSS200 = within 200 bp of TSS, 5’UTR = CpG is found within the 5’ untranslated region of the PPEIP and 1stExon = CpG found in the first exon of the PPEIP gene. The annotation “others” refers to promoter CpG’s that annotate to other genomic regions (such as gene bodies or introns) of overlapping genes. C. Distribution of promoter probes per gene annotated to both CpG islands and non-CpG islands. D. Examples of hyper-methylated PPEIP promoters for both recurrent (observed in > 5% of the cancer population) and rare (< 1% % of the cancer population) epimutations. Red lines present individuals with outlier epimutations and grey lines, healthy controls. E. Bar graph showing the ten most epimutated PPEIP genes. Numbers on the y-axis (and above each bar) represent the % of total cancer individuals in all cancer tissues (ALL) as well as a breakdown of epimutations identified in individuals of specific cancer related tissue

Fig. 2

PPEIP genes with hypermethylated promoters are involved in several cancer-associated cellular pathways and mechanisms. (A) Biocarta pathway analysis for pathway gene enrichment. The shade of green presents the significance of the specific gene-set or term. (B) Enrichment of transcription factor (TF) binding associated with hyper-methylated PPEIP genes from ChIP-seq experiments of > 300 TFs from the ENCODE project. Bright green presents higher number of genes. C-D. Orthogonal cellular pathway analyses from two independent resources; Kyoto Encyclopedia of Genes and Genomes (KEGG) and Curated wiki. For Figures A-D, the brighter the tone of green, the more significant the term is. In all network images (B-D), the grey lines represent gene content similarity

Fig. 3

Cancer-associated epimutations are commonly observed in Protein Tyrosine (PTP) and Dual-Specificity Phosphatase (DUSP) gene promoters. A-B. Bar graph demonstrating the % of individuals in each cancer subtype that carry at least one cancer-specific epimutation in tyrosine (A, blue) and dual specificity (B, green) phosphatase gene promoters. C-D. Bar graph representing the most ubiquitous PTP (C) and DUSP (D) gene promoters that harbour cancer-specific hyper-methylated promoters. Numbers above each bar represents % of cancer individuals with epimutations in the genes highlighted on the x-axis. The genes represented in (C) and (D) were detected in at least 5 individuals

Fig. 4

Cancer-specific promoter DNA hypermethylation in Protein Tyrosine (PTP) and Dual-Specificity Phosphatase (DUSP) are associated with gene expression silencing. A-B. Boxplots representing the effect of hypermethylated promoters of PTP genes in primary tumours (A) and cancer cell lines (B). C-D. Boxplots representing the effect of epimutations discerned in promoters of DUSP genes from primary tumours (C) and cancer cell lines (C). Primary tumour and cancer cell line gene expression data was downloaded from The Cancer Genome Atlas (TCGA) and the Cancer Cell Line Encyclopedia (CCLE) projects. Gene expression values are presented as relative units (r.u) and are specific to each project (TCGA = FPKM and CCLE = TPM). Gene names shown at the top left-hand corner of each boxplot and blue dots presents individual (and cancer cell lines) expression values where DNA methylation profiles were also available. *P < 0.05; **P < 0.01; ***P < 0.001

Fig. 5

PTPRM reduced expression via epigenetic silencing is associated with poor survival and reduced sensitivity to JAK/STAT targeted anti-cancer therapy in pancreatic cancer patients. (A) Kaplan–Meier curve showing reduced expression of PTPRM in patients with pancreatic cancer was significantly associated with shorter overall survival, Log Rank P = < 0.05 (HR = 2; 95% CI = 0.757–4.336; P = < 0.05). Green line represents patients in the top 25-percentile of PTPRM expression and the red line, bottom 25-percentile PTPRM expression in the pancreatic primary tumour cohort. (B) Horizontal bar graph demonstrates the cellular pathways targeted by anti-cancer drugs from GDSC2 (Genomics of Drug Sensitivity in Cancer) project. Drugs targeting “other” category were excluded. (C) Scatter plot illustrating IC₅₀ concentration of JAK/STAT pathway targeting compounds is significantly proportional to DNA methylation of the PTPRM gene promoter in pancreatic cancer cell lines (rho = 0.3, P = < 0.005)