The dysregulation of transforming growth factor-β (TGF-β) signaling plays a crucial role in ovarian carcinogenesis and in maintaining cancer stem cell properties. Classified as a member of the ATP-binding cassette (ABC) family, ABCA1 was previously identified by methylated DNA immunoprecipitation microarray (mDIP-Chip) to be methylated in ovarian cancer cell lines, A2780 and CP70. By microarray, it was also found to be upregulated in immortalized ovarian surface epithelial (IOSE) cells following TGF-β treatment. Thus, we hypothesized that ABCA1 may be involved in ovarian cancer and its initiation. We first compared the expression level of ABCA1 in IOSE cells and a panel of ovarian cancer cell lines and found that ABCA1 was expressed in HeyC2, SKOV3, MCP3, and MCP2 ovarian cancer cell lines but downregulated in A2780 and CP70 ovarian cancer cell lines. The reduced expression of ABCA1 in A2780 and CP70 cells was associated with promoter hypermethylation, as demonstrated by bisulfite pyro-sequencing. We also found that knockdown of ABCA1 increased the cholesterol level and promoted cell growth in vitro and in vivo. Further analysis of ABCA1 methylation in 76 ovarian cancer patient samples demonstrated that patients with higher ABCA1 methylation are associated with high stage (P = 0.0131) and grade (P = 0.0137). Kaplan-Meier analysis also found that patients with higher levels of methylation of ABCA1 have shorter overall survival (P = 0.019). Furthermore, tissue microarray using 55 ovarian cancer patient samples revealed that patients with a lower level of ABCA1 expression are associated with shorter progress-free survival (P = 0.038). ABCA1 may be a tumor suppressor and is hypermethylated in a subset of ovarian cancer patients. Hypermethylation of ABCA1 is associated with poor prognosis in these patients.

Purpose: Endometrial cancer is a common gynecologic cancer whose incidence is increasing annually worldwide. Current methods to detect endometrial cancer are unreliable and biomarkers are unsatisfactory for screening. Cervical scrapings were reported as a potential source of material for molecular testing. DNA methylation is a promising cancer biomarker, but limited use for detecting endometrial cancer. Experimental Design: We analyzed two methylomics databases of endometrioid-type endometrial cancer. Using nonnegative matrix factorization algorithm clustered the methylation pattern and reduced the candidate genes. We verified in pools DNA from endometrial cancer tissues and cervical scrapings, and validated in 146 cervical scrapings from patients with endometrioid-type endometrial cancer (n = 50), uterine myoma (n = 40), and healthy controls (n = 56) using quantitative methylation–specific PCR (QMSP). The logistic regression was used to evaluate the performance of methylation signal and gene combination. Results: We filtered out 180 methylated genes, which constituted four consensus clusters. Serial testing of tissues and cervical scrapings detected 14 genes that are hypermethylated in endometrial cancer. Three genes, BHLHE22, CDO1, and CELF4, had the best performance. Individual genes were sensitivity of 83.7%–96.0% and specificity of 78.7%–96.0%. A panel comprising any two of the three hypermethylated genes reached a sensitivity of 91.8%, specificity of 95.5%, and odds ratio of 236.3 (95% confidence interval, 56.4–989.6). These markers were also applied to cervical scrapings of type II endometrial cancer patients, and detected in 13 of 14 patients. Conclusions: This study demonstrates the potential use of methylated BHLHE22/CDO1/CELF4 panel for endometrial cancer screening of cervical scrapings. Clin Cancer Res; 23(1); 263–72. ©2016 AACR.

Preclinical evaluation of a nanoformulated antihelminthic, niclosamide, in ovarian cancer

We aimed to determine whether PAX1/SOX1 methylation could be translated to clinical practice for cervical neoplasia detection when used alone and in combination with current cytology‐based Pap screening. We conducted a multicenter case–control study in 11 medical centers in Taiwan from December 2009 to November 2010. Six hundred seventy‐six patients were included in the analysis, including 330 in the training set and 346 in the testing set. Multiplex quantitative methylation‐specific polymerase chain reaction (PCR) was performed with a TaqMan probe system using a LightCycler 480 Real‐Time PCR System (Roche). The level of human papilloma virus (HPV) was analyzed using a Hybrid Capture 2 system (Digene). Receiver operating characteristic curves were generated to obtain the best cutoff values from the training data set. The sensitivities, specificities, and accuracies were validated in the testing set. The sensitivities for methylated (^m) PAX1^m and SOX1^m and HPV testing for detecting CIN3⁺ lesions were 0.64, 0.71, and 0.89, and the specificities were 0.91, 0.77, and 0.68, respectively. Combined parallel testing of PAX1^m/SOX1^m tests with Pap smearing showed superior specificity (0.84/0.71 vs. 0.66, respectively) and similar sensitivity (0.93/0.96 vs. 0.97) to the combination of Pap smear results and HPV testing. Thus, combined parallel testing using Pap smears and PAX1 or SOX1 methylation tests may provide better performance than a combination of Pap smears with HPV testing in detection for cervical neoplasia.

Using DNA methylation biomarkers in cancer detection is a potential direction in clinical testing. Some methylated genes have been proposed for cervical cancer detection; however, more reliable methylation markers are needed. To identify new hypermethylated genes in the discovery phase, we compared the methylome between a pool of DNA from normal cervical epithelium (n = 19) and a pool of DNA from cervical cancer tissues (n = 38) using a methylation bead array. We integrated the differentially methylated genes with public gene expression databases, which resulted in 91 candidate genes. Based on gene expression after demethylation treatment in cell lines, we confirmed 61 genes for further validation. In the validation phase, quantitative MSP and bisulfite pyrosequencing were used to examine their methylation level in an independent set of clinical samples. Fourteen genes, including ADRA1D, AJAP1, COL6A2, EDN3, EPO, HS3ST2, MAGI2, POU4F3, PTGDR, SOX8, SOX17, ST6GAL2, SYT9, and ZNF614, were significantly hypermethylated in CIN3+ lesions. The sensitivity, specificity, and accuracy of POU4F3 for detecting CIN3+ lesions were 0.88, 0.82, and 0.85, respectively. A bioinformatics function analysis revealed that AJAP1, EDN3, EPO, MAGI2, and SOX17 were potentially implicated in β‐catenin signaling, suggesting the epigenetic dysregulation of this signaling pathway during cervical cancer development. The concurrent methylation of multiple genes in cancers and in subsets of precancerous lesions suggests the presence of a driver of methylation phenotype in cervical carcinogenesis. Further validation of these new genes as biomarkers for cervical cancer screening in a larger population‐based study is warranted.

Background: Epithelial ovarian cancer is characterized by multiple genomic alterations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and can be broadly categorized into 4 main histotypes of clear cell, endometrioid, mucinous, and serous. To date, histotype-specific copy number alterations have been difficult to elucidate. The difficulty lies in having sufficient sample size in each histotype for statistical analyses. Methods: To dissect the heterogeneity of ovarian cancer and identify histotype-specific alterations, we used an in silico hypothesis-driven approach on multiple datasets of epithelial ovarian cancer. Results: In concordance with previous studies on global copy number alterations landscape, the study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here significant histotype-specific copy number alterations in ovarian cancer and showed that there is genomic diversity amongst the histotypes. 76 cancer genes were found to be significantly altered with several as potential copy number drivers, including ERBB2 in mucinous, and TPM3 in endometrioid histotypes. ERBB2 was found to have preferential alterations, where it was amplified in mucinous (28.6%) but deleted in serous tumors (15.1%). Validation of ERBB2 expression showed significant correlation with microarray data (p=0.007). There also appeared to be reciprocal relationship between KRAS mutation and copy number alterations. In mucinous tumors where KRAS mutation is common, the gene was not significantly altered. However, KRAS was significantly amplified in serous tumors where mutations are rare in high grade tumors. Conclusions: The study demonstrates that the copy number landscape is specific to the histotypes and identification of these alterations can pave the way for targeted drug therapy specific to the histotypes.