Yu Ping Liao

ALDH1-bright epithelial ovarian cancer cells are associated with CD44 expression, drug resistance, and poor clinical outcome.

The role of aldehyde dehydrogenase 1 (ALDH1) as an ovarian cancer stem cell marker and its clinical significance have rarely been explored. We used an Aldefluor assay to isolate ALDH1-bright (ALDH1(br)) cells from epithelial ovarian cancer cell lines and characterized the properties of the stem cells. ALDH1(br) cells were enriched in ES-2 (1.3%), TOV-21G (1.0%), and CP70 (1.2%) cells. Both ALDH1(br) and ALDH1(low) cells repopulated stem cell heterogeneity, formed spheroids, and grew into tumors in immunocompromised mice, although these processes were more efficient in ALDH1(br) cells. In the ES-2 and CP70 cells, ALDH1(br) cells conferred more chemoresistance, and were more enriched in CD44 (by 1.74-fold and 5.18-fold, respectively) than in CD133 (by 1.39-fold and 1.17-fold, respectively), compared with ALDH1(low) cells. Immunohistochemical staining for ALDH1 on a tissue microarray containing 84 epithelial ovarian cancer samples revealed that patients with higher ALDH1 expression (>50%) had poor overall survival, compared with those with lower ALDH1 (P = 0.004) and yielded an odds ratio of death of 2.43 (95% CI = 1.12 to 5.28) by multivariate analysis. The results did not support ALDH1 alone as an ovarian cancer stem cell marker, but demonstrated that ALDH1 is associated with CD44 expression, chemoresistance, and poor clinical outcome. The use of a combination of ALDH1 with other stem cell markers may help define ovarian cancer stem cells more stringently.

Quantitative DNA methylation analysis detects cervical intraepithelial neoplasms type 3 and worse

DNA methylation may be used a potential biomarker for detecting cervical cancer. The authors of this report used quantitative methylation analysis of 4 genes in a full spectrum of cervical lesions to test its potential clinical application.

Comprehensive methylome analysis of ovarian tumors reveals hedgehog signaling pathway regulators as prognostic DNA methylation biomarkers.

Women with advanced stage ovarian cancer (OC) have a five-year survival rate of less than 25%. OC progression is associated with accumulation of epigenetic alterations and aberrant DNA methylation in gene promoters acts as an inactivating “hit” during OC initiation and progression. Abnormal DNA methylation in OC has been used to predict disease outcome and therapy response. To globally examine DNA methylation in OC, we used next-generation sequencing technology, MethylCap-sequencing, to screen 75 malignant and 26 normal or benign ovarian tissues. Differential DNA methylation regions (DMRs) were identified, and the Kaplan–Meier method and Cox proportional hazard model were used to correlate methylation with clinical endpoints. Functional role of specific genes identified by MethylCap-sequencing was examined in in vitro assays. We identified 577 DMRs that distinguished (p < 0.001) malignant from non-malignant ovarian tissues; of these, 63 DMRs correlated (p < 0.001) with poor progression free survival (PFS). Concordant hypermethylation and corresponding gene silencing of sonic hedgehog pathway members ZIC1 and ZIC4 in OC tumors was confirmed in a panel of OC cell lines, and ZIC1 and ZIC4 repression correlated with increased proliferation, migration and invasion. ZIC1 promoter hypermethylation correlated (p < 0.01) with poor PFS. In summary, we identified functional DNA methylation biomarkers significantly associated with clinical outcome in OC and suggest our comprehensive methylome analysis has significant translational potential for guiding the design of future clinical investigations targeting the OC epigenome. Methylation of ZIC1, a putative tumor suppressor, may be a novel determinant of OC outcome.

Methylomics analysis identifies epigenetically silenced genes and implies an activation of β-catenin signaling in cervical cancer

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.

High methylation rate of LMX1A, NKX6-1, PAX1, PTPRR, SOX1, and ZNF582 genes in cervical adenocarcinoma

Objective This study aimed to investigate the status of DNA methylation of 6 genes, LMX1A, NKX6-1, PAX1, PTPRR, SOX1, and ZNF582, previously found from squamous cell carcinomas in adenocarcinomas (ACs) of the uterine cervix. Methods We assessed the methylation status of these genes in 40 ACs, cervical scrapings from 23 ACs, and 67 normal control cervices by real-time quantitative methylation-specific polymerase chain reaction. The results were validated by bisulfite pyrosequencing. Results The methylation levels of all the 6 genes in the ACs were significantly higher than those in normal cervical tissues, especially for PAX1, PTPRR, SOX1, and ZNF582. The odds ratios and 95% confidence intervals (CIs) of high methylation levels in PAX1, PTPRR, SOX1, and ZNF582 for the risk of developing an AC were 15.7 (95% CI, 7.0–40.6), 16.9 (95% CI, 7.6–43.0), 32.1 (95% CI, 12.1–124.3), and 25.4 (95% CI, 10.4–78.3), respectively (all P < 0.001). The methylation indices of PAX1, PTPRR, SOX1, and ZNF582 recovered from scrapings of ACs were significantly higher than in normal controls. The odds ratios of these indices for the risk of developing an AC in PAX1, PTPRR, SOX1, and ZNF582 were 6.2 (95% CI, 2.6–15.4), 12.1(95% CI, 3.8–46.4), 6.2 (95% CI, 2.6–15.8), and 20.6 (95% CI, 6.9–77.5), respectively (all P < 0.001). Conclusions Cervical ACs carry aberrantly high methylation rates of PAX1, PTPRR, SOX1, and ZNF582—commonly methylated in squamous cell carcinomas—which might help for AC screening.ObjectiveThis study aimed to investigate the status of DNA methylation of 6 genes, LMX1A, NKX6-1, PAX1, PTPRR, SOX1, and ZNF582, previously found from squamous cell carcinomas in adenocarcinomas (ACs) of the uterine cervix. MethodsWe assessed the methylation status of these genes in 40 ACs, cervical scrapings from 23 ACs, and 67 normal control cervices by real-time quantitative methylation-specific polymerase chain reaction. The results were validated by bisulfite pyrosequencing. ResultsThe methylation levels of all the 6 genes in the ACs were significantly higher than those in normal cervical tissues, especially for PAX1, PTPRR, SOX1, and ZNF582. The odds ratios and 95% confidence intervals (CIs) of high methylation levels in PAX1, PTPRR, SOX1, and ZNF582 for the risk of developing an AC were 15.7 (95% CI, 7.0–40.6), 16.9 (95% CI, 7.6–43.0), 32.1 (95% CI, 12.1–124.3), and 25.4 (95% CI, 10.4–78.3), respectively (all P < 0.001). The methylation indices of PAX1, PTPRR, SOX1, and ZNF582 recovered from scrapings of ACs were significantly higher than in normal controls. The odds ratios of these indices for the risk of developing an AC in PAX1, PTPRR, SOX1, and ZNF582 were 6.2 (95% CI, 2.6–15.4), 12.1(95% CI, 3.8–46.4), 6.2 (95% CI, 2.6–15.8), and 20.6 (95% CI, 6.9–77.5), respectively (all P < 0.001). ConclusionsCervical ACs carry aberrantly high methylation rates of PAX1, PTPRR, SOX1, and ZNF582—commonly methylated in squamous cell carcinomas—which might help for AC screening.

Hypomethylation Signature of Tumor-initiating Cells Predicts Poor Prognosis of Ovarian Cancer Patients

DNA methylation contributes to tumor formation, development and metastasis. Epigenetic dysregulation of stem cells is thought to predispose to malignant development. The clinical significance of DNA methylation in ovarian tumor-initiating cells (OTICs) remains unexplored. We analyzed the methylomic profiles of OTICs (CP70sps) and their derived progeny using a human methylation array. qRT-PCR, quantitative methylation-specific PCR (qMSP) and pyrosequencing were used to verify gene expression and DNA methylation in cancer cell lines. The methylation status of genes was validated quantitatively in cancer tissues and correlated with clinicopathological factors. ATG4A and HIST1H2BN were hypomethylated in OTICs. Methylation analysis of ATG4A and HIST1H2BN by qMSP in 168 tissue samples from patients with ovarian cancer showed that HIST1H2BN methylation was a significant and independent predictor of progression-free survival (PFS) and overall survival (OS). Multivariate Cox regression analysis showed that patients with a low level of HIST1H2BN methylation had poor PFS (hazard ratio (HR), 4.5; 95% confidence interval (CI), 1.4-14.8) and OS (HR, 4.3; 95% CI, 1.3-14.0). Hypomethylation of both ATG4A and HIST1H2BN predicted a poor PFS (HR, 1.8; 95% CI, 1.0-3.6; median, 21 months) and OS (HR, 1.7; 95% CI, 1.0-3.0; median, 40 months). In an independent cohort of ovarian tumors, hypomethylation predicted early disease recurrence (HR, 1.7; 95% CI, 1.1-2.5) and death (HR, 1.4; 95% CI, 1.0-1.9). The demonstration that expression of ATG4A in cells increased their stem properties provided an indication of its biological function. Hypomethylation of ATG4A and HIST1H2BN in OTICs predicts a poor prognosis for ovarian cancer patients.

LIM-homeobox transcription factor 1, alpha (LMX1A) inhibits tumourigenesis, epithelial–mesenchymal transition and stem-like properties of epithelial ovarian cancer

OBJECTIVE We reported recently the hypermethylation of LMX1A, a LIM-homeobox gene, as a prognostic biomarker in ovarian cancer; however, the function of LMX1A in ovarian cancer remains unknown. The present study aimed to evaluate the hypothesized tumour-suppressor functions of LMX1A in ovarian cancer. METHODS We analysed the function of LMX1A by examining cell lines, animal models and human ovarian cancer tissues. Overexpression of LMX1A in relation to chemotherapy was also analysed. RESULTS The expression of LMX1A inhibited cell proliferation, migration, invasion and colony formation in vitro, as well as tumourigenicity in a xenotransplantation mouse model. LMX1A also sensitized ovarian cancer cell lines to chemotherapeutics, and affected epithelial-mesenchymal transition (EMT). The restoration of LMX1A down-regulated stem cell markers and inhibited tumour spheroid formation in SKOV3 cells. Univariate analysis of immunohistochemical staining of tissue arrays (n=83) revealed that low LMX1A expression was significantly associated with advanced stages (p=0.001), poor differentiation (p<0.001), early recurrence (p=0.023) and poor overall survival (p=0.042) in ovarian cancer. CONCLUSIONS The present study demonstrated, for the first time, that LMX1A is a bona fide tumour suppressor of ovarian cancer. The prognostic values of LMX1A may provide a biomarker for personalized treatments of ovarian cancer patients. The mechanisms of LMX1A in EMT and stem-like properties in ovarian cancer warrant further investigation.

Concordance analysis of methylation biomarkers detection in self-collected and physician-collected samples in cervical neoplasm

BackgroundNon-attendance at gynecological clinics is a major limitation of cervical cancer screening and self-collection of samples may improve this situation. Although HPV testing of self-collected vaginal samples is acceptable, the specificity is inadequate. The current focus is increasing self-collection of vaginal samples to minimize clinic visits. In this study, we analyzed the concordance and clinical performance of DNA methylation biomarker (PAX1, SOX1, and ZNF582) detection in self-collected vaginal samples and physician-collected cervical samples for the identification of cervical neoplasm.MethodsWe enrolled 136 cases with paired methylation data identified from abnormal Pap smears (n = 126) and normal controls (n = 10) regardless of HPV status at gynecological clinics. The study group comprised 37 cervical intraepithelial neoplasm I (CIN1), 23 cervical intraepithelial neoplasm II (CIN2), 16 cervical intraepithelial neoplasm III (CIN3), 30 carcinoma in situ (CIS), 13 squamous cell carcinomas (SCCs) and seven adenocarcinomas (ACs)/adenosquamous carcinomas (ASCs). PAX1, SOX1 and ZNF582 methylation in study samples was assessed by real-time quantitative methylation-specific polymerase chain reaction analysis. We generated methylation index cutoff values for the detection of CIN3+ in physician-collected cervical samples for analysis of the self-collected group. Concordance between the physician-collected and self-collected groups was evaluated by Cohen’s Kappa. Sensitivity, specificity and area under curve (AUC) were calculated for detection of CIN3+ lesions. Finally, we produced an optimal cutoff value with the best sensitivity from the self-collected groups.ResultsWe generated a methylation index cutoff value from physician-collected samples for detection of CIN3+. There were no significant differences in sensitivity, specificity of PAX1, SOX1 and ZNF582 between the self-collected and physician-collected groups. The methylation status of all three genes in the normal control samples, and the CIN 1, CIN2, CIN3, CIS, ACs/ASCs and SCC samples showed reasonable to good concordance between the two groups (κ = 0.443, 0.427, and 0.609 for PAX1, SOX1, and ZNF582, respectively). In determining the optimal cutoff values from the self-collected group, ZNF582 showed the highest sensitivity (0.77; 95%CI, 0.65–0.87) using a cutoff value of 0.0204.ConclusionsMethylation biomarker analysis of the three genes for detection of CIN3+ lesions shows reasonable to good concordance between the self-collected and physician-collected samples. Therefore, self-collection of samples could be adopted to decrease non-attendance and improve cervical screening.

Integrated epigenomics analysis reveals a DNA methylation panel for endometrial cancer detection using cervical scrapings.

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.

Pyruvate kinase M2 is a poor prognostic marker of and a therapeutic target in ovarian cancer

Pyruvate kinase M2 (PKM2) regulates glycolysis and oxidative phosphorylation; however, the role of PKM2 in ovarian cancer remains largely unknown. We investigated whether ovarian cancer metabolism could provide insight into the development of therapeutic strategies. We performed immunohistochemical staining for PKM2 on a tissue microarray for multivariate analysis. It revealed that patients exhibiting higher PKM2 expression were significantly associated with malignancy groups (p < 0.001) and pathogenesis models (p < 0.001), had poor progression-free survival rates (p = 0.01) as compared with patients exhibiting lower PKM2 levels, and yielded a hazard ratio of death of 2.02 (95% confidence interval: 0.70–5.85). In cell lines, PKM2 inhibitor significantly inhibited the glycolytic rate according to cellular glucose consumption (p < 0.001). We also utilized Seahorse assays to assess metabolism-related cell-specific factors and the impact of PKM2 inhibitors. Energy shifts as per Seahorse analysis showed attenuation of the extracellular acidification rate (p < 0.05) and no significant difference in oxygen-consumption rate in SKOV3 cells. Treatment with PKM2 inhibitor suppressed ovarian cancer growth and cell migration in vitro and inhibited tumor growth without significant toxicity in a xenograft study. PKM2 inhibition disturbed Warburg effects and inhibited ovarian cancer cell growth. Targeting PKM2 may constitute a promising therapy for patients with ovarian cancer, and clinical trials involving shikonin are warranted.