Quantitative DNA methylation and recurrence of breast cancer: A study of 30 candidate genes

Kim, Dae Cheol; Thorat, Mangesh A.; Lee, Mi Ri; Cho, Se Heon; Vasiljević, Nataša; Scibior‐Bentkowska, Dorota; Wu, Keqiang; Ahmad, Amar; Duffy, Stephen W.; Cuzick, Jack; Lörincz, Attila T.

doi:10.3233/cbm-2012-0266

Cited by 15 publications

(10 citation statements)

References 38 publications

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“…In our data set, SUM149, which is a classic TN breast cancer, has a very low level transcript expression of PTEN (0.8), compared to SUM190 (6.1). Interestingly, another tumor suppressor, SERPINB5 (Serpin B5), has been reported to be negatively correlated with both ER and PGR genes in a quantitative DNA analysis 51 , was only observed in SUM149 (proteomics and trancriptomics), which is the only TN cell line in the study. Likewise, amplification of S100A2 (Protein S100-A2) was observed in both proteomics and transcriptomics experiments.…”

Section: Resultsmentioning

confidence: 89%

Genome Wide Proteomics of ERBB2 and EGFR and Other Oncogenic Pathways in Inflammatory Breast Cancer

et al. 2013

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In this study we selected three breast cancer cell lines (SKBR3, SUM149 and SUM190) with different oncogene expression levels involved in ERBB2 and EGFR signaling pathways as a model system for the evaluation of selective integration of subsets of transcriptomic and proteomic data. We assessed the oncogene status with RPKM values (Reads Per Kilobase per Million mapped reads1) for ERBB2 (14.4, 400 and 300 for SUM149, SUM 190 and SKBR3 respectively and for EGFR 60.1, not detected and 1.4 for the same 3 cell lines. We then used RNA-Seq data to identify those oncogenes with significant transcript levels in these cell lines (total 31) and interrogated the corresponding proteomics data sets for proteins with significant interaction values with these oncogenes. The number of observed interactors for each oncogene showed a significant range, e.g. 4.2% (JAK1) to 27.3% (MYC). The percentage is measured as a fraction of the total protein interactions in a given data set vs. total interactors for that oncogene in STRING (Search Tool for the Retrieval of Interacting Genes/Proteins, version 9.0) and I2D (Interologous Interaction Database, version 1.95). This approach allowed us to focus on 4 main oncogenes, ERBB2, EGFR, MYC, and GRB2, for pathway analysis. We used the following bioinformatics sites, GeneGo, PathwayCommons and NCI receptor signaling networks to identify pathways which contained the four main oncogenes, had good coverage in the transcriptomic and proteomic data sets as well as significant number of oncogene interactors. The four pathways identified were ERBB signaling, EGFR1 signaling, integrin outside-in signaling, and validated targets of C-MYC transcriptional activation. The greater dynamic range of the RNA-Seq values allowed the use of transcript ratios to correlate observed protein values with the relative levels of the ERBB2 and EGFR transcripts in each of the four pathways. This provided us with potential proteomic signatures for the SUM149 and 190 cell lines, growth factor receptor-bound protein 7 (GRB7), Crk-like protein (CRKL) and Catenin delta-1 (CTNND1) for ERBB signaling, caveolin 1 (CAV1), plectin (PLEC) for EGFR signaling; filamin A (FLNA) and actinin alpha1 (ACTN1) (associated with high levels of EGFR transcript) for integrin signalings: branched chain amino-acid transaminase 1 (BCAT1), carbamoyl-phosphate synthetase (CAD), nucleolin (NCL) (high levels of EGFR transcript); transferrin receptor (TFRC), metadherin (MTDH) (high levels of ERBB2 transcript) for MYC signaling; S100-A2 protein (S100A2), caveolin 1 (CAV1), Serpin B5 (SERPINB5), stratifin (SFN), PYD and CARD domain containing (PYCARD), and EPH receptor A2 (EPHA2) for PI3K signaling, p53 sub-pathway. Future studies of inflammatory breast cancer (IBC), from which the cell lines were derived, will be used to explore the significance of these observations.

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Section: Resultsmentioning

confidence: 89%

Genome Wide Proteomics of ERBB2 and EGFR and Other Oncogenic Pathways in Inflammatory Breast Cancer

et al. 2013

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“…Although there is a large body of literature and the PubMeth online database (www.pubmeth.org) reporting tumor suppressor gene methylation frequency in breast cancer, methylation research of breast cancer in the Korean patients is still lacking, except for a few reports [5, 19, 20]. Several techniques exist to study aberrant methylation, i.e., methyl-specific PCR, bisulfite-dependent sequencing, and methyl-sensitive restriction enzyme-based assays.…”

Section: Discussionmentioning

confidence: 99%

“…However, in a recent study based on the Korean ethnicity, the methylation frequency of ductal carcinoma in situ was 89% by using MethyLight PCR analysis, which was determined as positive when the percentage of methylated reference was >4 [19]. Therefore, the method and cut-offs of positivity of methylation analyses are very important to reduce false positives due to inadequate conversion of non-methylated cytosine to uracil and mis-priming when high numbers of PCR cycles or nested primers are used [5, 6]. Optimal cut-off determination can result in over-fitting and false-discovery.…”

Section: Discussionmentioning

confidence: 99%

Comparison of Methylation Profiling in Cancerous and Their Corresponding Normal Tissues from Korean Patients with Breast Cancer

et al. 2013

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BackgroundAberrant DNA hypermethylation plays a pivotal role in carcinogenesis and disease progression; therefore, accurate measurement of differential gene methylation patterns among many genes is likely to reveal biomarkers for improved risk assessment. We evaluated the gene hypermethylation profiles of primary breast tumors and their corresponding normal tissues and investigated the association between major clinicopathological features and gene hypermethylation.MethodsA single reaction using methylation-specific multiplex ligation-dependent probe amplification was used to analyze the DNA methylation status of 24 tumor suppressor genes in 60 cancerous tissues and their corresponding normal tissues from patients with primary breast cancer.ResultsIn cancerous breast tissues, 21 of 24 genes displayed promoter methylation in one or more samples. The most frequently methylated genes included RASSF1 (43.3%), APC (31.7%), CDKN2B (25.0%), CDH13 (23.3%), GSTP1 (16.7%), and BRCA1 (10%). APC was associated with lymph node metastasis, and BRCA1 was associated with negative estrogen receptor and negative progesterone receptor expression. In normal breast tissues, 8 of 24 tumor suppressor genes displayed promoter hypermethylation; CDKN2B (28.3%) and RASSF1 (8.3%) hypermethylation were most frequently observed.ConclusionsRASSF1 and CDKN2B hypermethylation in Korean breast cancer patients were the most frequent in cancerous tissue and corresponding normal tissue, respectively. Our data indicates that methylation of specific genes is a frequent event in morphologically normal breast tissues adjacent to breast tumors as well as the corresponding breast cancers. This study also suggests that gene methylation is linked to various pathological features of breast cancer; however, this requires confirmation in a larger study.

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“…It is well established that widespread changes of DNA methylation occur during carcinogenesis and tumor progression (10). Distinct from other biomarkers in BC which are typically based on gene expression, DNA methylation has been identified to have independent prognostic values that can be used in tailoring treatment to patients who are receiving uniform therapy regimens (11). …”

Section: Introductionmentioning

confidence: 99%

Aberrant promoter methylation of cancer-related genes in human breast cancer

Shen²,

Peng

et al. 2016

Oncology Letters

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The clinical relevance of aberrant DNA methylation is being increasingly recognized in breast cancer. The present study aimed to evaluate the promoter methylation status of seven candidate genes and to explore their potential use as a biomarker for the diagnosis of breast cancer. A total of 70 Chinese patients with breast cancer were recruited, and matched with 20 patients with benign breast disease (BBD). Methylation-specific polymerase chain reaction was performed to measure the methylation status of selected genes. The protein expression of candidate genes was determined by immunohistochemistry. Hypermethylation of Breast cancer 1, early onset; DNA repair associated (BRCA1), glutathione S-transferase pi 1 (GSTP1), cyclin dependent kinase inhibitor 2A, O-6-methylguanine-DNA methyltransferase, phosphatase and tensin homolog, retinoic acid receptor beta 2 and cyclin D2 was observed to be more common in cancerous tissues (24.3, 31.4, 40.0, 27.1, 48.6, 55.7 and 67.1%, respectively) as compared with BBD controls (0.0, 0.0, 20.0, 25.0, 40.0, 40.0 and 45.0%, respectively). Immunohistochemical analysis demonstrated a correlation between the methylation of the target gene and downregulation of protein expression. When BRCA1 and GSTP1 were combined as the biomarker, the area under the receiver operating characteristic curve reached 0.721 (95% confidence interval, 0.616–0.827). The present findings indicated that promoter methylation of cancer-related genes was frequently observed in patients with breast cancer and was associated with various clinical features. Hypermethylation of BRCA1 and GSTP1 may be used as promising biomarkers for breast cancer.

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Quantitative DNA methylation and recurrence of breast cancer: A study of 30 candidate genes

Cited by 15 publications

References 38 publications

Genome Wide Proteomics of ERBB2 and EGFR and Other Oncogenic Pathways in Inflammatory Breast Cancer

Genome Wide Proteomics of ERBB2 and EGFR and Other Oncogenic Pathways in Inflammatory Breast Cancer

Comparison of Methylation Profiling in Cancerous and Their Corresponding Normal Tissues from Korean Patients with Breast Cancer

Aberrant promoter methylation of cancer-related genes in human breast cancer

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