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pmid:28679371

CpG promoter methylation of the ALKBH3 alkylation repair gene in breast cancer.

Olafur Andri Stefansson · Stefan Hermanowicz · Jasper van der Horst · Holmfridur Hilmarsdottir · Zuzanna Staszczak · Jon Gunnlaugur Jonasson · Laufey Tryggvadottir · Thorkell Gudjonsson · Stefan Sigurdsson

BMC cancer · 2017 doi:10.1186/s12885-017-3453-8

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2026-11-01T15:40:27Z
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title
CpG promoter methylation of the ALKBH3 alkylation repair gene in breast cancer.
doi
10.1186/s12885-017-3453-8
pmid
28679371
authors array · 9 items
[0]
Olafur Andri Stefansson
[1]
Stefan Hermanowicz
[2]
Jasper van der Horst
[3]
Holmfridur Hilmarsdottir
[4]
Zuzanna Staszczak
[5]
Jon Gunnlaugur Jonasson
[6]
Laufey Tryggvadottir
[7]
Thorkell Gudjonsson
[8]
Stefan Sigurdsson
journal
BMC cancer
year
2017
abstract
BACKGROUND: DNA repair of alkylation damage is defective in various cancers. This occurs through somatically acquired inactivation of the MGMT gene in various cancer types, including breast cancers. In addition to MGMT, the two E. coli AlkB homologs ALKBH2 and ALKBH3 have also been linked to direct reversal of alkylation damage. However, it is currently unknown whether ALKBH2 or ALKBH3 are found inactivated in cancer. METHODS: Methylome datasets (GSE52865, GSE20713, GSE69914), available through Omnibus, were used to determine whether ALKBH2 or ALKBH3 are found inactivated by CpG promoter methylation. TCGA dataset enabled us to then assess the impact of CpG promoter methylation on mRNA expression for both ALKBH2 and ALKBH3. DNA methylation analysis for the ALKBH3 promoter region was carried out by pyrosequencing (PyroMark Q24) in 265 primary breast tumours and 30 proximal normal breast tissue samples along with 8 breast-derived cell lines. ALKBH3 mRNA and protein expression were analysed in cell lines using RT-PCR and Western blotting, respectively. DNA alkylation damage assay was carried out in cell lines based on immunofluorescence and confocal imaging. Data on clinical parameters and survival outcomes in patients were obtained and assessed in relation to ALKBH3 promoter methylation. RESULTS: The ALKBH3 gene, but not ALKBH2, undergoes CpG promoter methylation and transcriptional silencing in breast cancer. We developed a quantitative alkylation DNA damage assay based on immunofluorescence and confocal imaging revealing higher levels of alkylation damage in association with epigenetic inactivation of the ALKBH3 gene (P = 0.029). In our cohort of 265 primary breast cancer, we found 72 cases showing aberrantly high CpG promoter methylation over the ALKBH3 promoter (27%; 72 out of 265). We further show that increasingly higher degree of ALKBH3 promoter methylation is associated with reduced breast-cancer specific survival times in patients. In this analysis, ALKBH3 promoter methylation at >20% CpG methylation was found to be statistically significantly associated with reduced survival (HR = 2.3; P = 0.012). By thresholding at the clinically relevant CpG methylation level (>20%), we find the incidence of ALKBH3 promoter methylation to be 5% (13 out of 265). CONCLUSIONS: ALKBH3 is a novel addition to the catalogue of DNA repair genes found inactivated in breast cancer. Our results underscore a link between defective alkylation repair and breast cancer which, additionally, is found in association with poor disease outcome.
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The P-value shown was derived from Spearman’s correlation testing (Spearman’s rho = −0.577; P = 0.024)
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sections[13] "CpG promoter methylation and expression of the ALKBH3 gene in normal and primary breast tumor samples" paragraph 3
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The P-value shown was derived from Spearman’s correlation testing (Spearman’s rho = −0.577; P = 0.024)
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Methylome datasets used in this study: Stefansson et al. (GSE52865), Dedeurwaerder et al. (GSE20713) and Teschendorff et al. (GSE69914).
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Methylome datasets used in this study: Stefansson et al. (GSE52865), Dedeurwaerder et al. (GSE20713) and Teschendorff et al. (GSE69914).
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Using CpG promoter methylation analyses of Omnibus methylome datasets GSE52865, GSE20713, and GSE69914, complemented by TCGA expression data and pyrosequencing, the study found that ALKBH3—but not ALKBH2—undergoes promoter methylation and transcriptional silencing in breast cancer.
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Methylome datasets (GSE52865, GSE20713, GSE69914), available through Omnibus, were used to determine whether ALKBH2 or ALKBH3 are found inactivated by CpG promoter methylation.
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TCGA dataset enabled us to then assess the impact of CpG promoter methylation on mRNA expression for both ALKBH2 and ALKBH3.
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sections[0] "Abstract" paragraph 2
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DNA methylation analysis for the ALKBH3 promoter region was carried out by pyrosequencing (PyroMark Q24) in 265 primary breast tumours and 30 proximal normal breast tissue samples along with 8 breast-derived cell lines.
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The ALKBH3 gene, but not ALKBH2, undergoes CpG promoter methylation and transcriptional silencing in breast cancer.
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Using CpG promoter methylation analyses of Omnibus methylome datasets GSE52865, GSE20713, and GSE69914, complemented by TCGA expression data and pyrosequencing, the study found that ALKBH3—but not ALKBH2—undergoes promoter methylation and transcriptional silencing in breast cancer.
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sample_count
57
group_sizes
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13534
taxon
Homo sapiens
title
A DNA methylation definition of biologically distinct breast cancer subtypes
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
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[3] object · 15 fields
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data:geo:GSE69914
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note
Methylome datasets used in this study: Stefansson et al. (GSE52865), Dedeurwaerder et al. (GSE20713) and Teschendorff et al. (GSE69914).
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
Methylome datasets used in this study: Stefansson et al. (GSE52865), Dedeurwaerder et al. (GSE20713) and Teschendorff et al. (GSE69914).
access_statement_kind
data_availability_statement
sample_accessions array · 407 items
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[67]
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[68]
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[71]
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[73]
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[74]
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[75]
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[76]
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[77]
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[78]
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[79]
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[80]
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[83]
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[85]
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[86]
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[87]
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[88]
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[89]
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[90]
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[91]
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[92]
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[93]
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[94]
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[95]
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[96]
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[97]
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[98]
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[99]
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[100]
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[101]
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[102]
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[103]
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[104]
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[105]
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[106]
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[107]
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[108]
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[109]
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[110]
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[111]
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[112]
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[115]
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[118]
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[119]
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[120]
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[131]
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[132]
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[135]
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[198]
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[199]
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[200]
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[201]
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[202]
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[204]
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[240]
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[264]
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[265]
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[267]
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[268]
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[269]
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[270]
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[271]
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[272]
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[275]
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[280]
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[281]
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[282]
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[285]
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[286]
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[287]
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[288]
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[289]
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[290]
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[291]
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[292]
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[295]
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[296]
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[299]
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[317]
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[404]
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[405]
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[406]
GSM1712779
sample_count
407
group_sizes
null
group_sizes_basis
null
platform
16304
taxon
Homo sapiens
title
Genome wide DNA methylation profiling of normal breast, normal adjacent and breast cancer tissue
resolution_checked_at
2026-11-01T15:39:55Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[4] object · 16 fields
id
asset:table:pmid:28679371:1
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table
format
jats-table
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application/vnd.jats.table+json
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null
sha256
sha256:62b8549b3622148437326e4322dfa9a026fc4612396bc55557d7bf136f7d8ead
bytes
952
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open
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verified
reader
read_table
reader_status
available
identifier
section[14]/table-wrap[1]#Tab1
version
null
note
Clinical and pathological characteristics of the patient cohort
structure object · 5 fields
pmcid
PMC5498885
section_index
14
section_title
ALKBH3 promoter methylation with respect to clinical relevance
row_count
14
column_count
5
table object · 8 fields
label
Table 1
caption
Clinical and pathological characteristics of the patient cohort
rows array · 14 items
[0] array · 5 items
[0]
[1]
Positive
[2]
Negative
[3]
[4]
[1] array · 5 items
[0]
Estrogen-Receptor
[1]
175 (72%)
[2]
68 (28%)
[3]
[4]
[2] array · 5 items
[0]
Progestrone-Receptor
[1]
136 (56%)
[2]
108 (44%)
[3]
[4]
[3] array · 5 items
[0]
HER2-positive (over-expressed)
[1]
20 (14%)
[2]
121 (86%)
[3]
[4]
[4] array · 5 items
[0]
Ki67-positive (>14% positivity)
[1]
84 (60%)
[2]
55 (40%)
[3]
[4]
[5] array · 5 items
[0]
[1]
1986–1991
[2]
1991–1996
[3]
1996–2001
[4]
2001–2004
[6] array · 5 items
[0]
Year of Diagnosis
[1]
81 (30%)
[2]
121 (46%)
[3]
60 (23%)
[4]
3 (1%)
[7] array · 5 items
[0]
[1]
26–42
[2]
42–58
[3]
58–74
[4]
74–91
[8] array · 5 items
[0]
Age at Diagnosis
[1]
36 (14%)
[2]
104 (39%)
[3]
80 (30%)
[4]
45 (17%)
[9] array · 5 items
[0]
[1]
5–30
[2]
30–55
[3]
55–80
[4]
80–100
[10] array · 5 items
[0]
Tumour size (mm)
[1]
94 (77%)
[2]
24 (20%)
[3]
1 (1%)
[4]
3 (2%)
[11] array · 5 items
[0]
Nodal status
[1]
112 (64%)
[2]
63 (36%)
[3]
[4]
[12] array · 5 items
[0]
[1]
+
[2]
++
[3]
+++
[4]
[13] array · 5 items
[0]
Histological Grade
[1]
19 (13%)
[2]
62 (41%)
[3]
69 (46%)
[4]
locator
section[14]/table-wrap[1]#Tab1
gaps array · 6 items
[0]
asset:data:geo:GSE20713 not downloaded
[1]
asset:data:geo:GSE20713 licence not read
[2]
asset:data:geo:GSE52865 not downloaded
[3]
asset:data:geo:GSE52865 licence not read
[4]
asset:data:geo:GSE69914 not downloaded
[5]
asset:data:geo:GSE69914 licence not read
analysis object · 4 fields
state
partial
methods array · 2 items
[0] object · 10 fields
id
method-1
family
group_comparison
specific
wilcoxon
label
Group comparison
dsl_operations array · 0 items
missing_operations array · 1 item
[0]
group_comparison_wilcoxon
expressible
false
parameters object · 1 field
p_value
The P-value shown was derived from
data_shapes array · 1 item
[0]
two_or_more_groups_continuous
evidence object · 3 fields
score
0.8
band
high
quote
Wilcoxon
[1] object · 10 fields
id
method-2
family
null
specific
null
label
Spearman’s correlation testing
dsl_operations array · 0 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 0 items
evidence object · 3 fields
score
1
band
verbatim
quote
The P-value shown was derived from Spearman’s correlation testing (Spearman’s rho = −0.577; P = 0.024)
targets array · 0 items
gaps array · 2 items
[0]
method.reader_named_unmapped
[1]
method.group_comparison_wilcoxon
capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
molecular_docking
[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
state
complete
tier
R1
blocked_on
nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
false
required_operations array · 0 items
missing_operations array · 1 item
[0]
group_comparison_wilcoxon
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: wilcoxon.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
reachable
true
accessions array · 3 items
[0]
GSE52865
[1]
GSE20713
[2]
GSE69914
resolved_accessions array · 3 items
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Methylome datasets used in this study: Stefansson et al. (GSE52865), Dedeurwaerder et al. (GSE20713) and Teschendorff et al. (GSE69914).
basis
The paper names GSE52865, GSE20713, GSE69914 in Omnibus repository at NCBI’s website (www.ncbi.nlm.nih.gov/gds/) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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were analysed in cell lines using RT-PCR and Western blotting, respectively. DNA alkylation damage assay w
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assay was carried out in cell lines based on immunofluorescence and confocal imaging. Data on clinical param
[1]
itative alkylation DNA damage assay based on immunofluorescence and confocal imaging revealing higher levels
[2]
3 analysed with respect to 3-methyl-cytosine immunostaining. A) U2OS cells were transfected with a contr
[3]
(to gain access to single stranded DNA) and immunostained for 3-me-C and 5-me-C. As expected, decrease
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pect to 3-methyl-cytosine immunostaining. A) U2OS cells were transfected with a control (scram
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-cytosine immunostaining. A) U2OS cells were transfected with a control (scrambled siRNA) and ALKBH3
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s were transfected with a control (scrambled siRNA) and ALKBH3 siRNA for 72 h. After fixation c
[2]
with a control (scrambled siRNA) and ALKBH3 siRNA for 72 h. After fixation cells were denature
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ed as the average signal derived form ALKBH3 siRNA treated cells divided by the average signal
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:28679371", "kind": "science-record", "revision": 7, "content_hash": "sha256:4a053e3d9158ae745b9a0d657cc75d6279ce3a233f0985f44bfdd2d1aafaf72f", "created_at": "2026-11-01T15:40:27Z", "updated_at": "2026-11-01T21:59:26Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "CpG promoter methylation of the ALKBH3 alkylation repair gene in breast cancer.", "doi": "10.1186/s12885-017-3453-8", "pmid": "28679371", "authors": ["Olafur Andri Stefansson", "Stefan Hermanowicz", "Jasper van der Horst", "Holmfridur Hilmarsdottir", "Zuzanna Staszczak", "Jon Gunnlaugur Jonasson", "Laufey Tryggvadottir", "Thorkell Gudjonsson", "Stefan Sigurdsson"], "journal": "BMC cancer", "year": 2017, "abstract": "BACKGROUND: DNA repair of alkylation damage is defective in various cancers. This occurs through somatically acquired inactivation of the MGMT gene in various cancer types, including breast cancers. In addition to MGMT, the two E. coli AlkB homologs ALKBH2 and ALKBH3 have also been linked to direct reversal of alkylation damage. However, it is currently unknown whether ALKBH2 or ALKBH3 are found inactivated in cancer.\nMETHODS: Methylome datasets (GSE52865, GSE20713, GSE69914), available through Omnibus, were used to determine whether ALKBH2 or ALKBH3 are found inactivated by CpG promoter methylation. TCGA dataset enabled us to then assess the impact of CpG promoter methylation on mRNA expression for both ALKBH2 and ALKBH3. DNA methylation analysis for the ALKBH3 promoter region was carried out by pyrosequencing (PyroMark Q24) in 265 primary breast tumours and 30 proximal normal breast tissue samples along with 8 breast-derived cell lines. ALKBH3 mRNA and protein expression were analysed in cell lines using RT-PCR and Western blotting, respectively. DNA alkylation damage assay was carried out in cell lines based on immunofluorescence and confocal imaging. Data on clinical parameters and survival outcomes in patients were obtained and assessed in relation to ALKBH3 promoter methylation.\nRESULTS: The ALKBH3 gene, but not ALKBH2, undergoes CpG promoter methylation and transcriptional silencing in breast cancer. We developed a quantitative alkylation DNA damage assay based on immunofluorescence and confocal imaging revealing higher levels of alkylation damage in association with epigenetic inactivation of the ALKBH3 gene (P = 0.029). In our cohort of 265 primary breast cancer, we found 72 cases showing aberrantly high CpG promoter methylation over the ALKBH3 promoter (27%; 72 out of 265). We further show that increasingly higher degree of ALKBH3 promoter methylation is associated with reduced breast-cancer specific survival times in patients. In this analysis, ALKBH3 promoter methylation at >20% CpG methylation was found to be statistically significantly associated with reduced survival (HR = 2.3; P = 0.012). By thresholding at the clinically relevant CpG methylation level (>20%), we find the incidence of ALKBH3 promoter methylation to be 5% (13 out of 265).\nCONCLUSIONS: ALKBH3 is a novel addition to the catalogue of DNA repair genes found inactivated in breast cancer. Our results underscore a link between defective alkylation repair and breast cancer which, additionally, is found in association with poor disease outcome.", "claims": [{"id": "claim-method", "statement": "The P-value shown was derived from Spearman’s correlation testing (Spearman’s rho = −0.577; P = 0.024)", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:28679371", "locator": "sections[13] \"CpG promoter methylation and expression of the ALKBH3 gene in normal and primary breast tumor samples\" paragraph 3", "quote": "The P-value shown was derived from Spearman’s correlation testing (Spearman’s rho = −0.577; P = 0.024)"}], "state": "complete"}, {"id": "claim-data-access", "statement": "Methylome datasets used in this study: Stefansson et al. (GSE52865), Dedeurwaerder et al. (GSE20713) and Teschendorff et al. 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(GSE69914)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Using CpG promoter methylation analyses of Omnibus methylome datasets GSE52865, GSE20713, and GSE69914, complemented by TCGA expression data and pyrosequencing, the study found that ALKBH3—but not ALKBH2—undergoes promoter methylation and transcriptional silencing in breast cancer.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:28679371", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Methylome datasets (GSE52865, GSE20713, GSE69914), available through Omnibus, were used to determine whether ALKBH2 or ALKBH3 are found inactivated by CpG promoter methylation."}, {"asset": "source:pmid:28679371", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "TCGA dataset enabled us to then assess the impact of CpG promoter methylation on mRNA expression for both ALKBH2 and ALKBH3."}, {"asset": "source:pmid:28679371", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "DNA methylation analysis for the ALKBH3 promoter region was carried out by pyrosequencing (PyroMark Q24) in 265 primary breast tumours and 30 proximal normal breast tissue samples along with 8 breast-derived cell lines."}, {"asset": "source:pmid:28679371", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The ALKBH3 gene, but not ALKBH2, undergoes CpG promoter methylation and transcriptional silencing in breast cancer."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Using CpG promoter methylation analyses of Omnibus methylome datasets GSE52865, GSE20713, and GSE69914, complemented by TCGA expression data and pyrosequencing, the study found that ALKBH3—but not ALKBH2—undergoes promoter methylation and transcriptional silencing in breast cancer.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:28679371"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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