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Combined genetic mutations and DNA-methylated genes as biomarkers for endometrial cancer detection from cervical scrapings.

ABSTRACT: BACKGROUND:Endometrial cancer is a common gynecologic cancer. Noninvasive molecular biomarkers for triage of high-risk patients for invasive procedures are needed. Based on the success of cytological Pap smear screening, cervical scrapings are a good source of DNA for molecular testing. In addition to genetic lesions, DNA methylation is a promising biomarker. We assessed the usefulness of combining genetic and epigenetic biomarkers from cervical scrapings to detect endometrial carcinomas. METHODS:We performed a retrospective case-control study of 96 consecutive cervical scrapings from patients with abnormal uterine bleeding who underwent surgery for diagnostic evaluation. Thirty and 16 cases were diagnosed with type I and type II endometrial cancers, respectively. The remaining non-cancer cases included normal endometrium (n = 12), benign uterine lesions (n = 20), and endometrial hyperplasia (n = 18). Quantitative methylation-specific PCR and mass spectrometry were used for DNA methylation and genetic mutation analysis. Logistic regression was used to evaluate the clinical performance of these candidate biomarkers. RESULTS:We tested the effectiveness of the methylation status of four genes (BHLHE22, CDO1, TBX5, and HAND2) in endometrial cancer detection. The area under the receiver operating characteristic curves ranged from 0.703 to 0.878, and panels of hypermethylated BHLHE22/CDO1/HAND2 (87.0% sensitivity and 86.0% specificity) and BHLHE22/CDO1/TBX5 (89.1% sensitivity and 80.0% specificity) showed significant differences and could distinguish benign from malignant endometrial lesions. The sensitivity and specificity in endometrial cancer detection for BHLHE22/CDO1 were 84.8% and 88.0%, respectively. Both type I and II endometrial carcinomas could be detected using a BHLHE22/CDO1-based methylation profile, suggesting that they may have common epigenomes. Moreover, PTEN and TP53 mutations were found in 63.3% of type I and 93.6% of type II endometrial cancers. Unexpectedly, PTEN and TP53 mutations were commonly found in cervical scrapings of the normal endometrium (25% and 33.3%, respectively) and in cases with benign uterine lesions (10% and 50%, respectively). Finally, combinations of any one mutation of PTEN and TP53 mutations had a sensitivity of 91.3%, but a specificity of only 42.0%. CONCLUSIONS:Adding PTEN/TP53 mutation testing to BHLHE22/CDO1-based methylation testing did not improve the detection of endometrial cancer.

SUBMITTER: Liew PL

PROVIDER: S-EPMC6883641 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Combined genetic mutations and DNA-methylated genes as biomarkers for endometrial cancer detection from cervical scrapings.

Liew Phui-Ly PL Huang Rui-Lan RL Wu Tzu-I TI Liao Chi-Chun CC Chen Chien-Wen CW Su Po-Hsuan PH Wang Hui-Chen HC Weng Yu-Chun YC Lai Hung-Cheng HC

Clinical epigenetics 20191128 1

<h4>Background</h4>Endometrial cancer is a common gynecologic cancer. Noninvasive molecular biomarkers for triage of high-risk patients for invasive procedures are needed. Based on the success of cytological Pap smear screening, cervical scrapings are a good source of DNA for molecular testing. In addition to genetic lesions, DNA methylation is a promising biomarker. We assessed the usefulness of combining genetic and epigenetic biomarkers from cervical scrapings to detect endometrial carcinomas ...[more]

PMID: 31779688

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Project description:BACKGROUND:Ovarian cancer (OC) is the most lethal gynecological cancer, worldwide, largely due to its vague and nonspecific early stage symptoms, resulting in most tumors being found at advanced stages. Moreover, due to its relative rarity, there are currently no satisfactory methods for OC screening, which remains a controversial and cost-prohibitive issue. Here, we demonstrate that Papanicolaou test (Pap test) cervical scrapings, instead of blood, can reveal genetic/epigenetic information for OC detection, using specific and sensitive DNA methylation biomarkers. RESULTS:We analyzed the methylomes of tissues (50 OC tissues versus 6 normal ovarian epithelia) and cervical scrapings (5 OC patients versus 10 normal controls), and integrated public methylomic datasets, including 79 OC tissues and 6 normal tubal epithelia. Differentially methylated genes were further classified by unsupervised hierarchical clustering, and each candidate biomarker gene was verified in both OC tissues and cervical scrapings by either quantitative methylation-specific polymerase chain reaction (qMSP) or bisulfite pyrosequencing. A risk-score by logistic regression was generated for clinical application. One hundred fifty-one genes were classified into four clusters, and nine candidate hypermethylated genes from these four clusters were selected. Among these, four genes fulfilled our selection criteria and were validated in training and testing set, respectively. The OC detection accuracy was demonstrated by area under the receiver operating characteristic curves (AUCs) in 0.80-0.83 of AMPD3, 0.79-0.85 of AOX1, 0.78-0.88 of NRN1, and 0.82-0.85 of TBX15. From this, we found OC-risk score, equation generated by logistic regression in training set and validated an OC-associated panel comprising AMPD3, NRN1, and TBX15, reaching a sensitivity of 81%, specificity of 84%, and OC detection accuracy of 0.91 (95% CI, 0.82-1) in testing set. CONCLUSIONS:Ovarian cancer detection from cervical scrapings is feasible, using particularly promising epigenetic biomarkers such as AMPD3/NRN1/TBX15. Further validation is warranted.

Project description:DNA methylation can induce carcinogenesis by silencing key tumor suppressor genes. Analysis of aberrant methylation of tumor suppressor genes can be used as a prognostic and predictive biomarker for cancer. In this study, we propose a colorimetric method for the detection of DNA methylation of the paired box gene 1 (PAX1) gene in cervical scrapings obtained from 42 patients who underwent cervical colposcopic biopsy.A thiolated methylation-specific polymerase chain reaction (MSP) primer was used to generate MSP products labeled with the thiol group at one end. After bisulfite conversion and MSP amplification, the unmodified gold nanoparticles (AuNPs) were placed in a reaction tube and NaCl was added to induce aggregation of bare AuNPs without generating polymerase chain reaction products. After salt addition, the color of AuNPs remained red in the methylated PAX1 gene samples because of binding to the MSP-amplified products. By contrast, the color of the AuNP colloid solution changed from red to blue in the non-methylated PAX1 gene samples because of aggregation of AuNPs in the absence of the MSP-amplified products. Furthermore, PAX1 methylation was quantitatively detected in cervical scrapings of patients with varied pathological degrees of cervical cancer. Conventional quantitative MSP (qMSP) was also performed for comparison.The two methods showed a significant correlation of the methylation frequency of the PAX1 gene in cervical scrapings with severity of cervical cancer (n=42, P<0.05). The results of the proposed method showed that the areas under the receiver operating characteristic curve (AUCs) of PAX1 were 0.833, 0.742, and 0.739 for the detection of cervical intraepithelial neoplasms grade 2 and worse lesions (CIN2+), cervical intraepithelial neoplasms grade 3 and worse lesions (CIN3+), and squamous cell carcinoma, respectively. The sensitivity and specificity for detecting CIN2+ lesions were 0.941 and 0.600, respectively, with a cutoff value of 31.27%. The proposed method also showed superior sensitivity over qMSP methods for the detection of CIN2+ and CIN3+ (0.941 vs 0.824 and 1.000 vs 0.800, respectively). Furthermore, the novel method exhibited higher AUC (0.833) for the detection of CIN2+ than qMSP (0.807).The results of thiol-labeled AuNP method were clearly observed by the naked eyes without requiring any expensive equipment. Therefore, the thiol-labeled AuNP method could be a simple but efficient strategy for cervical cancer screening.

Project description:BackgroundAberrant DNA methylation is significantly associated with breast cancer.MethodsIn this study, we aimed to determine novel methylation biomarkers using a bioinformatics analysis approach that could have clinical value for breast cancer diagnosis and prognosis. Firstly, differentially methylated DNA patterns were detected in breast cancer samples by comparing publicly available datasets (GSE72245 and GSE88883). Methylation levels in 7 selected methylation biomarkers were also estimated using the online tool UALCAN. Next, we evaluated the diagnostic value of these selected biomarkers in two independent cohorts, as well as in two mixed cohorts, through ROC curve analysis. Finally, prognostic value of the selected methylation biomarkers was evaluated breast cancer by the Kaplan-Meier plot analysis.ResultsIn this study, a total of 23 significant differentially methylated sites, corresponding to 9 different genes, were identified in breast cancer datasets. Among the 9 identified genes, ADCY4, CPXM1, DNM3, GNG4, MAST1, mir129-2, PRDM14, and ZNF177 were hypermethylated. Importantly, individual value of each selected methylation gene was greater than 0.9, whereas predictive value for all genes combined was 0.9998. We also found the AUC for the combined signature of 7 genes (ADCY4, CPXM1, DNM3, GNG4, MAST1, PRDM14, ZNF177) was 0.9998 [95% CI 0.9994-1], and the AUC for the combined signature of 3 genes (MAST1, PRDM14, and ZNF177) was 0.9991 [95% CI 0.9976-1]. Results from additional validation analyses showed that MAST1, PRDM14, and ZNF177 had high sensitivity, specificity, and accuracy for breast cancer diagnosis. Lastly, patient survival analysis revealed that high expression of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 were significantly associated with better overall survival.ConclusionsMethylation pattern of MAST1, PRDM14, and ZNF177 may represent new diagnostic biomarkers for breast cancer, while methylation of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 may hold prognostic potential for breast cancer.

Dataset Information

Combined genetic mutations and DNA-methylated genes as biomarkers for endometrial cancer detection from cervical scrapings.

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Combined genetic mutations and DNA-methylated genes as biomarkers for endometrial cancer detection from cervical scrapings.

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