scholarly journals DNA Methylation Status of RETN and ADIPOQ Genes in Sporadic Colon Cancer

2021 ◽  
Author(s):  
Rowyda Al-Harithy ◽  
Eman Al abdulsalam
Keyword(s):  
Dna Methylation ◽  
Colon Cancer ◽  
Cancer Progression ◽  
Mrna Level ◽  
Methylation Status ◽  
Colon Tissue ◽  
Cancerous Tissue ◽  
Cpg Sites ◽  
Cancer Pathogenesis ◽  
Sporadic Colon Cancer

Abstract Background: Colon cancer develops through a complex process that involves epigenetic alterations. Compelling evidence has been achieved that adipocytokines link obesity with colon cancer progression Therefore, understanding the epigenetic modifications in adipokine genes might help in clarifying their role in colon cancer pathogenesis. The aim of the present project was to study the DNA methylation status of RETN and ADIPOQ genes in sporadic colon cancer patients. Methods: 70 cancerous colon tissue and adjacent paired non-cancerous tissue was used to determine the DNA methylation status using methylation-specific polymerase chain reaction (MS-PCR) assay. Quantitative real-time PCR (qRT-PCR) was used to determine the expression level of RETN and ADIPOQ genes. Results: In colon cancer tissues, the CpG sites in the three selected promoter regions of ADIPOQ and RETN were hypermethylated in all samples. DNA methylation level at the CpG sites in exon one of the RETN gene exhibited a lower level in the non-cancerous tissue compared to the cancerous tissue and paired blood samples. The RETN mRNA was upregulated. Conclusion: We postulate that DNA methylation status at the CpG sites in exon one of the RETN gene might help uncover cancer signatures in sporadic colon cancer and may be used as a biomarker. The upregulation of the RETN mRNA level might play a role in sporadic colon cancer tumorigenesis.

Genomic DNA methylation analysis revealed that BLNK is a key potential gene in the regulation of autophagy-related thyroid cancer progression

Genome ◽  
2021 ◽  
Author(s):  
Shengchi Zhang ◽  
Yongzhe Zheng ◽  
Guimin Zhang ◽  
Peng Lin ◽  
Wei Wang
Keyword(s):  
Dna Methylation ◽  
Thyroid Cancer ◽  
Cancer Progression ◽  
Protein Interactions ◽  
Methylation Status ◽  
Expression Change ◽  
Prognostic Analysis ◽  
Key Genes ◽  
New Perspective ◽  
The Relationship

The purpose of this study was to explore the relationship between autophagy and DNA methylation, and to identify key genes for autophagy-regulated thyroid cancer progression. We divided patients with thyroid cancer into high-autophagy score (AS) group and low-AS group based on their AS values. The results found that AS was associated with the distant metastasis of thyroid cancer, and adversely affected prognosis. Then, we screened 359 differently expressed genes (DEGs) with DNA methylation status consistent with gene expression change. Functional classification analysis demonstrated that the 359 DEGs consistent with DNA methylation status were significantly involved in adhesion, migration and differentiation of immune cells. To further screen the key genes in the autophagy-related thyroid cancer progression, we constructed a protein-protein interactions (PPI) network and performed prognostic analysis. B cell linker (BLNK) was identified as the key potential gene affecting autophagy-related thyroid cancer progression. Finally, we verified that BLNK promoted the proliferation of thyroid cancer cells, and BLNK expression was regulated by DNA methylation. Our research provides a new perspective for exploring the relationship between autophagy and DNA methylation during the progression of thyroid cancer, and provides a new target for the treatment of metastatic thyroid cancer.

scholarly journals The Expression Level of mRNA, Protein, and DNA Methylation Status of FOSL2 of Uyghur in XinJiang in Type 2 Diabetes

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Jun Li ◽  
Siyuan Li ◽  
Ying Hu ◽  
Guolei Cao ◽  
Siyao Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Type 2 Diabetes ◽  
Dna Methylation ◽  
Methylation Status ◽  
Methylation Data ◽  
Biochemical Indicators ◽  
Expression Levels ◽  
Protein Levels ◽  
Cpg Sites

Objective. We investigated the expression levels of both FOSL2 mRNA and protein as well as evaluating DNA methylation in the blood of type 2 diabetes mellitus (T2DM) Uyghur patients from Xinjiang. This study also evaluated whether FOSL2 gene expression had demonstrated any associations with clinical and biochemical indicators of T2DM. Methods. One hundred Uyghur subjects where divided into two groups, T2DM and nonimpaired glucose tolerance (NGT) groups. DNA methylation of FOSL2 was also analyzed by MassARRAY Spectrometry and methylation data of individual units were generated by the EpiTyper v1.0.5 software. The expression levels of FOS-like antigen 2 (FOSL2) and the protein expression levels were analyzed. Results. Significant differences were observed in mRNA and protein levels when compared with the NGT group, while methylation rates of eight CpG units within the FOSL2 gene were higher in the T2DM group. Methylation of CpG sites was found to inversely correlate with expression of other markers. Conclusions. Results show that a correlation between mRNA, protein, and DNA methylation of FOSL2 gene exists among T2DM patients from Uyghur. FOSL2 protein and mRNA were downregulated and the DNA became hypermethylated, all of which may be involved in T2DM pathogenesis in this population.

scholarly journals Role of miRNAs in Sigmoid Colon Cancer: A Search for Potential Biomarkers

Cancers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3311
Author(s):  
Diego Marques ◽  
Layse Raynara Ferreira-Costa ◽  
Lorenna Larissa Ferreira-Costa ◽  
Ana Beatriz Bezerra-Oliveira ◽  
Romualdo da Silva Correa ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Sigmoid Colon ◽  
Cancer Progression ◽  
Target Genes ◽  
Mirna Gene ◽  
Differentially Expressed ◽  
Sigmoid Colon Cancer ◽  
Colon Tissue ◽  
Aberrant Expression ◽  
Differentially Expressed Mirnas

The aberrant expression of microRNAs in known to play a crucial role in carcinogenesis. Here, we evaluated the miRNA expression profile of sigmoid colon cancer (SCC) compared to adjacent-to-tumor (ADJ) and sigmoid colon healthy (SCH) tissues obtained from colon biopsy extracted from Brazilian patients. Comparisons were performed between each group separately, considering as significant p-values < 0.05 and |Log2(Fold-Change)| > 2. We found 20 differentially expressed miRNAs (DEmiRNAs) in all comparisons, two of which were shared between SCC vs. ADJ and SCC vs. SCH. We used miRTarBase, and miRTargetLink to identify target-genes of the differentially expressed miRNAs, and DAVID and REACTOME databases for gene enrichment analysis. We also used TCGA and GTEx databases to build miRNA-gene regulatory networks and check for the reproducibility in our results. As findings, in addition to previously known miRNAs associated with colorectal cancer, we identified three potential novel biomarkers. We showed that the three types of colon tissue could be clearly distinguished using a panel composed by the 20 DEmiRNAs. Additionally, we found enriched pathways related to the carcinogenic process in which miRNA could be involved, indicating that adjacent-to-tumor tissues may be already altered and cannot be considered as healthy tissues. Overall, we expect that these findings may help in the search for biomarkers to prevent cancer progression or, at least, allow its early detection, however, more studies are needed to confirm our results.

Azacytidine as a Maintenance Therapy in Elderly AML Progressively Demethylates CpG Sites within the p16 Gene

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 4466-4466
Author(s):  
Margaret Dellett ◽  
Michelle Lazenby ◽  
Alan K Burnett ◽  
Ken I Mills
Keyword(s):  
Dna Methylation ◽  
Maintenance Therapy ◽  
Peripheral Blood ◽  
Age Of Onset ◽  
Methylation Status ◽  
Global Methylation ◽  
Cpg Sites ◽  
Number Of Patients ◽  
Elderly Aml ◽  
Diagnostic Samples

Abstract Acute myeloid leukemia (AML) accounts for ~30% of adult leukaemia cases and is expected to increase as the population ages, due to median age of onset at ~60 years old. Recent evidence suggests that DNA methylation is actively involved in AML and myelodysplastic syndrome (MDS). Tumor suppressor genes, such as p16, have been shown to be silenced by methylation in AML. However, epigenetic events such as DNA methylation are reversible and therefore targets for chemotherapeutic intervention. It has been reported that ~30% of MDS patients with an abnormal karyotype show normalization of their methylation status after receiving a demethylating drug during early stages of their therapy. The UK NCRI AML16 programme for elderly patients (&gt;60 years old at diagnosis) with AML and high risk MDS has several therapeutic questions for patients considered fit for intensive treatment, one of which is to compare the use of azacytidine demethylation maintenance treatment with no maintenance therapy. Samples were obtained from patients entered into the AML16 trial, at diagnosis and from patients entered into the intensive arm of the trial who were randomized to receive azacytidine maintenance therapy were analyzed for the alterations for genomic methylation. Pyrosequencing was used to determine methylation within 17 CpG sites within p16, MLH1, and MGMT whilst LINE1 was used as a measure of global methylation. To date, approximately 714 patients have been entered into AML16. Of these 195 diagnostic samples have been analyzed, of which 103 were in the intensive arm of the trial. At the second randomization stage, 34 patient samples were analyzed and a further 26 samples were obtained following 3, 6 or 9 courses of azacytidine therapy. Statistical comparison of the methylation levels at each individual CpG or for the averaged CpG in each gene studies indicated that there was no difference whether the sample was derived from bone marrow or peripheral blood. This allowed the direct comparison of peripheral blood samples obtained at 2nd randomization and during azacytidine maintenance courses. Differential levels of methylation at individual CpG within the gene were seen at diagnosis. Higher levels of average p16 methylation were observed in the AML patients when compared to a small cohort of “well elderly” individuals. No difference was noted in the individual or averaged CpG methylation status for MGMT or LINE1 during the maintenance course of azacytidine. However, the methylation status of the CpG sites within the p16 and MLH1 genes reduced during maintenance by a median of 19% and 25% respectively. However, the number of patients completing three courses of azacytidine was only about 20% of those entering the intensive arm of AML16, however sequential samples from the same individual also showed demethylation of the CpG sites in p16 and MLH1. This study shows that azacytidine maintenance therapy in elderly AML patients does reduce the methylation status of some genes whilst others genes show no response. This is being investigated further using arrays containing 12,000 CpG sites which will be correlated with gene expression microarrays on the diagnostic samples from AML16.

DNA Demethylation By Activation-Induced Cytidine Deaminase in B Cell Lymphoma

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 3549-3549
Author(s):  
Yang Xi ◽  
Velizar Shivarov ◽  
Gur Yaari ◽  
Steven Kleinstein ◽  
Matthew P. Strout
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Dna Repair ◽  
B Cell ◽  
Somatic Hypermutation ◽  
Methylation Status ◽  
B Cell Lymphoma ◽  
Dna Demethylation ◽  
Cpg Sites ◽  
Average Beta

Abstract DNA methylation and demethylation at cytosine residues are epigenetic modifications that regulate gene expression associated with early cell development, somatic cell differentiation, cellular reprogramming and malignant transformation. While the process of DNA methylation and maintenance by DNA methyltransferases is well described, the nature of DNA demethylation remains poorly understood. The current model of DNA demethylation proposes modification of 5-methylcytosine followed by DNA repair-dependent cytosine substitution. Although there is debate on the extent of its involvement in DNA demethylation, activation-induced cytidine deaminase (AID) has recently emerged as an enzyme that is capable of deaminating 5-methylcytosine to thymine, creating a T:G mismatch which can be repaired back to cytosine through DNA repair pathways. AID is expressed at low levels in many tissue types but is most highly expressed in germinal center B cells where it deaminates cytidine to uracil during somatic hypermutation and class switch recombination of the immunoglobulin genes. In addition to this critical role in immune diversification, aberrant targeting of AID contributes to oncogenic point mutations and chromosome translocations associated with B cell malignancies. Thus, to explore a role for AID in DNA demethylation in B cell lymphoma, we performed genome-wide methylation profiling in BL2 and AID-deficient (AID-/-) BL2 cell lines (Burkitt lymphoma that can be induced to express high levels of AID). Using Illumina’s Infinium II DNA Methylation assay combined with the Infinium Human Methylation 450 Bead Chip, we analyzed over 450,000 methylation (CpG) sites at single nucleotide resolution in each line. BL2 AID-/- cells had a median average beta value (ratio of the methylated probe intensity to overall intensity) of 0.76 compared with 0.73 in AID-expressing BL2 cells (P < 0.00001), indicating a significant reduction in global methylation in the presence of AID. Using a delta average beta value of ≥ 0.3 (high stringency cut-off whereby a difference of 0.3 or more defines a CpG site as hypomethylated), we identified 5883 CpG sites in 3347 genes that were hypomethylated in BL2 versus BL2 AID-/- cells. Using the Illumina HumanHT-12 v4 Expression BeadChip and Genome Studio software, we then integrated gene expression and methylation profiles from both lines to generate a list of genes that met the following criteria: 1) contained at least 4 methylation sites within the first 1500 bases downstream of the primary transcriptional start site (TSS 1500; AID is most active in this region during somatic hypermutation); 2) average beta value increased by >0.1 in the TSS 1500 region in BL2 compared with BL2 AID-/- cells; and 3) down-regulated by >50% in BL2 compared with BL2 AID-/- cells. This analysis identified 31 candidate genes targeted for AID-dependent demethylation with consequent changes in gene expression. Interestingly, 15 of these genes have been reported to be bound by AID in association with stalled RNA polymerase II in activated mouse B cells. After validating methylation status in a subset of genes (APOBEC3B, BIN1, DEM1, GRN, GNPDA1) through bisulfite sequencing, we selected DEM1 for further analysis. DEM1 encodes an exonuclease involved in DNA repair and contains 16 CpG sites within its TSS1500, with only one site >50% methylated in BL2 cells compared with 8 of 16 in BL2 AID-/- cells. To assess a direct role for AID in DEM1 methylation status, a retroviral construct (AIDΔL189-L198ER) driving tamoxifen-inducible expression of a C-terminal deletion mutant of AID (increases time spent in the nucleus) was introduced into BL2 AID-/- cells. BL2, BL2 AID-/-, and BL2 AIDΔL189-L198ER cells were cultured continuously for 21 days in the presence of tamoxifen, 100 nM. Bisulfite sequencing of DEM1 TSS 1500 did not demonstrate any significant changes in methylation at day 7. However, at day 21, 13 of the 16 DEM1 TSS 1500 methylation sites in BL2 AIDΔL189-L198ER cells were found to have an increase in the ratio of unmethylated to methylated clones ~10-25% above that of BL2 AID-/- cells. By qPCR, this correlated with a 1.75-fold increase in DEM1 gene expression to levels that were equivalent to that seen in BL2 cells (P = 0.003). Although further investigations are needed, this data supports the notion that AID is able to regulate target gene expression in B cell malignancy through active DNA demethylation. Disclosures No relevant conflicts of interest to declare.

A smoothed EM-algorithm for DNA methylation profiles from sequencing-based methods in cell lines or for a single cell type

2017 ◽  
Vol 16 (5-6) ◽  
Author(s):  
Lajmi Lakhal-Chaieb ◽  
Celia M.T. Greenwood ◽  
Mohamed Ouhourane ◽  
Kaiqiong Zhao ◽  
Belkacem Abdous ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Em Algorithm ◽  
Single Cell ◽  
Cell Lines ◽  
Methylation Status ◽  
Embryonic Stem ◽  
Cell Type ◽  
Data Set ◽  
Cpg Sites ◽  
Single Cell Type

AbstractWe consider the assessment of DNA methylation profiles for sequencing-derived data from a single cell type or from cell lines. We derive a kernel smoothed EM-algorithm, capable of analyzing an entire chromosome at once, and to simultaneously correct for experimental errors arising from either the pre-treatment steps or from the sequencing stage and to take into account spatial correlations between DNA methylation profiles at neighbouring CpG sites. The outcomes of our algorithm are then used to (i) call the true methylation status at each CpG site, (ii) provide accurate smoothed estimates of DNA methylation levels, and (iii) detect differentially methylated regions. Simulations show that the proposed methodology outperforms existing analysis methods that either ignore the correlation between DNA methylation profiles at neighbouring CpG sites or do not correct for errors. The use of the proposed inference procedure is illustrated through the analysis of a publicly available data set from a cell line of induced pluripotent H9 human embryonic stem cells and also a data set where methylation measures were obtained for a small genomic region in three different immune cell types separated from whole blood.

scholarly journals A DNA methylation-based classifier for accurate molecular diagnosis of bone sarcomas.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 11034-11034
Author(s):  
Shengyang Wu ◽  
Benjamin Thomas Cooper ◽  
Fang Bu ◽  
Christopher Bowman ◽  
Keith Killian ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Synovial Sarcoma ◽  
Ewing’S Sarcoma ◽  
Ewing's Sarcoma ◽  
Clinical Sample ◽  
Methylation Status ◽  
Accurate Diagnosis ◽  
Cpg Sites ◽  
Bone Sarcomas ◽  
Methylation Profiling

11034 Background: Bone sarcomas present a unique diagnostic challenge because of the considerable morphologic overlap between different entities. The choice of optimal treatment, however, is dependent upon accurate diagnosis. Genome-wide DNA methylation profiling has emerged as a new approach to aid in the diagnosis of brain tumors, with diagnostic accuracy exceeding standard histopathology. In this work we developed and validated a methylation based classifier to differentiate between osteosarcoma, Ewing’s sarcoma, and synovial sarcoma. Methods: DNA methylation status of 482,421 CpG sites in 15 osteosarcoma, 10 Ewing’s sarcoma, and 11 synovial sarcoma samples were measured using the Illumina HumanMethylation450 array. From this training set of 36 samples we developed a random forest classifier using the 400 most differentially methylated CpG sites (FDR q value < 0.001). This classifier was then validated on 10 synovial sarcoma samples from TCGA, 86 osteosarcoma samples from TARGET-OS, and 15 Ewing’s sarcoma from a recently published series (Huertas-Martinez et al., Cancer Letters 2016). Results: Methylation profiling revealed three distinct molecular clusters, each enriched with a single sarcoma subtype. Within the validation cohorts, all samples from TCGA were correctly classified as synovial sarcoma (10/10, sensitivity and specificity 100%). All but one sample from TARGET-OS were classified as osteosarcoma (85/86, sensitivity 98%, specificity 100%) and all but one sample from the Ewing’s sarcoma series was classified as Ewing’s sarcoma (14/15, sensitivity 93%, specificity 100%). The single misclassified osteosarcoma sample was classified as Ewing’s sarcoma, and was later determined to be a misdiagnosed Ewing’s sarcoma based on RNA-Seq demonstrating high EWRS1 and ETV1 expression. An additional clinical sample that was misdiagnosed as a synovial sarcoma by initial histolopathology, was accurately recognized as osteosarcoma by the methylation classifier. Conclusions: Osteosarcoma, Ewing’s sarcoma and synovial sarcoma have distinct epigenetic profiles. Our validated methylation-based classifier can be used to provide an accurate diagnosis when histological and standard techniques are inconclusive.

scholarly journals SUN-115 Distinct DNA Methylation Signature in Neuroendocrine Tumors of Different Primary Sites and Hereditary Predisposition

2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Amit Tirosh ◽  
Jonathan Keith Killian ◽  
Petersen David ◽  
Yuelin Jack Zhu ◽  
Jenny Blau ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Neuroendocrine Tumors ◽  
Methylation Status ◽  
Principal Component ◽  
Circulating Tumor Dna ◽  
Adenomatous Polyposis Coli Gene ◽  
Unknown Primary ◽  
Cpg Sites ◽  
Genome Wide ◽  
Cpg Hypermethylation

Abstract Objective There is scant data of the genome-wide methylome alterations in neuroendocrine tumors (NET). Thus, the goal of this study was to compare the DNA methylation signature of NETs with respect to various primary sites and inherited genetic predisposition syndromes including von Hippel-Lindau (VHL) and multiple endocrine neoplasia type 1 (MEN1). Methods Genome-wide DNA methylation analysis of 96 NETs (primary and metastatic) was performed by using the Illumina Infinium EPIC Array. Principal component analysis (PCA) and unsupervised clustering analyses were performed to identify distinct methylome signatures. The methylation status of genetic drivers such as APC were assessed by primary site. Results A total of 835,424 CpGs methylation sites were quantified. Hypermethylated CpG sites were detected more frequently in sporadic vs. MEN1-related vs. VHL-related NETs, respectively (p &lt; 0.001 for all comparisons), while hypomethylated CpGs sites were more common in VHL-related NETs vs. sporadic and MEN1-related NETs (p&lt;0.001 for both comparisons). Small-intestinal NETs (SINETs) had the most differences at CpGs with the highest number of hyper- and hypomethylated CpG sites, followed by duodenal NETs (DNETs) and pancreatic NETs (PNETs, p&lt;0.001 for all comparisons). PCA showed distinct clustering of SINETs and three NETs of unknown primary. Sporadic, VHL-related and MEN1-related PNETs formed distinct groups on PCA. VHL-related NETs clustered separately showing pronounced CpG hypomethylation, while sporadic and MEN1-related NETs clustered together showing relative CpG hypermethylation. In a subgroup analysis, MEN1-related SINETs, DNETs and gastric NETs had distinct methylome signatures, respectively, with complete separation by PCA and unsupervised hierarchical clustering. Furthermore, we found CpG hypermethylation in the APC (adenomatous polyposis coli) gene, specifically in the 1A promoter, with higher methylation levels in gastric- and DNETs vs. SINETs, PNETs and NETs of unknown primary (p &lt; 0.001 for all comparisons). Conclusion Various primary NET sites and genetically predisposed MEN1-related NETs have distinct DNA CpG methylation signatures. The methylome signatures identified in this study may be useful for non-invasive molecular characterization of NETs, through DNA methylation profiling of biopsy samples or circulating tumor DNA.

scholarly journals Early Pregnancy Peripheral Blood DNA Methylation and Risk of Gestational Diabetes Mellitus: A Nested Case-Control Study

2021 ◽  
Author(s):  
Xiaolei Wang ◽  
Jin Huang ◽  
Sisi Long ◽  
Huijun Lin ◽  
Na Zhang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Dna Methylation ◽  
Peripheral Blood ◽  
Case Control Study ◽  
Methylation Status ◽  
First Trimester ◽  
Case Control ◽  
Cpg Sites ◽  
Nested Case Control ◽  
Control Study

Abstract Introduction: Genome-wide DNA methylation profiling has been used to identify CpG sites relevant to gestational diabetes mellitus (GDM). However, these sites have not been verified in larger samples. Here, our aim was to evaluate the changes in target CpG sites in the peripheral blood of pregnant women with GDM in their first trimester. Research Design and Methods: This nested case-control study examined a large cohort of women with GDM in early pregnancy (10–15 weeks; n = 80). Target CpG sites were extracted from related published literature and bioinformatics analysis. The DNA methylation levels at 337 CpG sites located in 27 target genes were determined using MethylTarget™ sequencing. The best cut-off levels for methylation of CpG sites were determined using the generated ROC curve. The independent effect of CpG site methylation status on GDM was analyzed using conditional logistic regression. Results Methylation levels at 6 CpG sites were significantly higher in the GDM group than in controls, whereas those at 7 CpG sites were significantly lower (P < 0.05). The area under the ROC curve at each methylation level of the significant CpG sites ranged between 0.593 and 0.650 for GDM prediction. After adjusting for possible confounders, the hypermethylation status of candidate sites cg68167324 (OR = 3.168, 1.038–9.666) and cg24837915 (OR = 5.232, 1.659–16.506) was identified as more strongly associated with GDM; conversely, the hypermethylation of sites cg157130156 (OR = 0.361, 0.135–0.966) and cg89438648 (OR = 0.206, 0.065–0.655) might indicate lower risk of GDM. Conclusions The methylation status of target CpG sites in the peripheral blood of pregnant women during the first trimester is associated with GDM pathogenesis, and has potential as a predictor of GDM.

DNA methylation signature predictive of benefit from neoadjuvant chemotherapy in esophageal adenocarcinoma: Results from the MRC OEO2 phase III trial.

2019 ◽  
Vol 37 (4_suppl) ◽  
pp. 43-43
Author(s):  
Raghav Sundar ◽  
Alvin Ng ◽  
Hermioni Zouridis ◽  
Taotao Sheng ◽  
Shenli Zhang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Neoadjuvant Chemotherapy ◽  
Univariate Analysis ◽  
Methylation Status ◽  
Predictive Biomarkers ◽  
Predictive Biomarker ◽  
Phase Iii ◽  
Cpg Sites ◽  
Poor Risk ◽  
Good Risk

43 Background: Platinum and 5-Fluorouracil (5FU) neoadjuvant chemotherapy followed by surgery is one of the standard approaches for patients with resectable EAC. To date, there are no predictive biomarkers of chemotherapy benefit. We hypothesize that DNA methylation of genes in key biologic and oncogenic pathways predict for chemotherapy benefit in EAC. Methods: In the OE02 trial, 802 patients with resectable esophageal carcinoma were randomised to surgery alone (S) versus two cycles of cisplatin and 5FU chemotherapy followed by surgery (CS). DNA was extracted from 213 EAC resection specimens (110 from the (CS) arm, 103 from the (S) arm). DNA methylation was analyzed at 1505 CpG sites within 807 genes using the Illumina GoldenGate platform. Cox proportional hazard analysis was performed to identify predictive markers of survival in (CS) arm; non-negative matrix factorization (NMF) was used to delineate methylation signatures. Results: Methylation status of 1505 CpG sites had no statistical difference between the (CS) and (S) arms. In the (CS) arm, 87 (5.7%) CpG sites were initially identified as promising candidates in univariate analysis (p < 0.05 cutoff). NMF generated a 4 CpG site signature which divided patients into poor risk and good risk. Genes involved in the signature include RUNX1T1, CCND2, MST1R and MMP14. Survival was significantly different between poor risk and good risk in (CS) arm (HR 0.32, 95% CI: 0.21 to 0.52, p < 0.0001). No difference in survival was detected in the surgery arm (HR 1.12, 95% CI: 0.76 to 1.80, p = 0.48), suggesting the signature served as a predictive and not prognostic biomarker. Methylation signature remained an independent predictor of survival in multivariate analysis with clinicopathologic factors (along with age and vascular invasion). Conclusions: Chemotherapy does not appear to change methylation status of EAC. Hypermethylation of RUNX1T1, CCND2 and hypomethylation of MST1R and MMP14 leads to significantly decreased benefit from chemotherapy in EA. We describe an epigenetic signature which may serve as a predictive biomarker for chemotherapy benefit using data form the largest bank of DNA methylation in EA reported to date.

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