DNA Methylation of Window of Implantation Genes in Cervical Secretions Predicts Ongoing Pregnancy in Infertility Treatment.

Window of implantation (WOI) genes have been comprehensively identified at the single cell level. DNA methylation changes in cervical secretions are associated with in vitro fertilization embryo transfer (IVF-ET) outcomes. Using a machine learning (ML) approach, we aimed to determine which methylation changes in WOI genes from cervical secretions best predict ongoing pregnancy during embryo transfer. A total of 2708 promoter probes were extracted from mid-secretory phase cervical secretion methylomic profiles for 158 WOI genes, and 152 differentially methylated probes (DMPs) were selected. Fifteen DMPs in 14 genes (BMP2, CTSA, DEFB1, GRN, MTF1, SERPINE1, SERPINE2, SFRP1, STAT3, TAGLN2, TCF4, THBS1, ZBTB20, ZNF292) were identified as the most relevant to ongoing pregnancy status. These 15 DMPs yielded accuracy rates of 83.53%, 85.26%, 85.78%, and 76.44%, and areas under the receiver operating characteristic curves (AUCs) of 0.90, 0.91, 0.89, and 0.86 for prediction by random forest (RF), naïve Bayes (NB), support vector machine (SVM), and k-nearest neighbors (KNN), respectively. SERPINE1, SERPINE2, and TAGLN2 maintained their methylation difference trends in an independent set of cervical secretion samples, resulting in accuracy rates of 71.46%, 80.06%, 80.72%, and 80.68%, and AUCs of 0.79, 0.84, 0.83, and 0.82 for prediction by RF, NB, SVM, and KNN, respectively. Our findings demonstrate that methylation changes in WOI genes detected noninvasively from cervical secretions are potential markers for predicting IVF-ET outcomes. Further studies of cervical secretion of DNA methylation markers may provide a novel approach for precision embryo transfer.

Cervical Secretion Methylation Is Associated with the Pregnancy Outcome of Frozen-Thawed Embryo Transfer.

The causes of implantation failure remain a black box in reproductive medicine. The exact mechanism behind the regulation of endometrial receptivity is still unknown. Epigenetic modifications influence gene expression patterns and may alter the receptivity of human endometrium. Cervical secretions contain endometrial genetic material, which can be used as an indicator of the endometrial condition. This study evaluates the association between the cervical secretion gene methylation profile and pregnancy outcome in a frozen-thawed embryonic transfer (FET) cycle. Cervical secretions were collected from women who entered the FET cycle with a blastocyst transfer (36 pregnant and 36 non-pregnant women). The DNA methylation profiles of six candidate genes selected from the literature review were measured by quantitative methylation-specific PCR (qMSP). Bioinformatic analysis of six selected candidate genes showed significant differences in DNA methylation between receptive and pre-receptive endometrium. All candidate genes showed different degrees of correlation with the pregnancy outcomes in the logistic regression model. A machine learning approach showed that the combination of candidate genes' DNA methylation profiles could differentiate pregnant from non-pregnant samples with an accuracy as high as 86.67% and an AUC of 0.81. This study demonstrated the association between cervical secretion methylation profiles and pregnancy outcomes in an FET cycle and provides a basis for potential clinical application as a non-invasive method for implantation prediction.

BHLHE22 Expression Is Associated with a Proinflammatory Immune Microenvironment and Confers a Favorable Prognosis in Endometrial Cancer.

Endometrial cancer (EC) rates are rising annually. Additional prediction markers need to be evaluated because only 10-20% of EC cases show an objective response to immune-checkpoint inhibitors (ICIs). Our previous methylomic study found that BHLHE22 is hypermethylated in EC tissues and can be detected using a Pap-smear sample. BHLHE22, a basic helix loop helix transcription factor family member, is known as a transcriptional repressor and is involved in cell differentiation. However, the role of BHLHE22 in EC remains poorly understood. Herein, we analyzed BHLHE22 expression in 54 paired cancer and normal endometrial tissue samples, and confirmed with databases (TCGA, GTEx, and human protein atlas). We found that BHLHE22 protein expression was significantly downregulated in EC compared with normal endometrium. High BHLHE22 expression was associated with microsatellite-instable subtype, endometrioid type, grade, and age. It showed a significant favorable survival. BHLHE22 overexpression inhibited the proliferation and migration of EC cells. Functional enrichment analysis showed that BHLHE22 was significantly associated with immune-related pathways. Furthermore, BHLHE22 was positively correlated with proinflammatory leukocyte infiltration and expression of chemokine genes in EC. In conclusion, BHLHE22 regulates immune-related pathways and modulates the immune microenvironment of EC.

Epigenomic Analysis Reveals the KCNK9 Potassium Channel as a Potential Therapeutic Target for Adenomyosis.

Adenomyosis is linked to dysmenorrhea and infertility. The pathogenesis of adenomyosis remains unclear, and little is known of the genetic and epigenetic changes in the eutopic endometrium in adenomyosis, which may predispose patients to the invasion and migration of endometrial tissues into the myometrium. Transcriptome studies have identified genes related to various cell behaviors but no targets for therapeutic intervention. The epigenetics of the eutopic endometrium in adenomyosis have rarely been investigated. Endometrial tissue was obtained from premenopausal women with (n = 32) or without adenomyosis (n = 17) who underwent hysterectomy aged 34-57 years at a tertiary hospital. The methylome and transcriptome were assessed by using a Methylation 450 K BeadChip array and Affymetrix expression microarray. Protein expression was examined by immunohistochemistry. Differential methylation analysis revealed 53 lowly methylated genes and 176 highly methylated genes with consistent gene expression in adenomyosis, including three genes encoding potassium ion channels. High expression of KCNK9 in the eutopic and ectopic endometria in patients with adenomyosis but not in normal controls was observed. Hormone-free, antibody-based KCNK9 targeting is a potential therapeutic strategy for adenomyosis-related dysmenorrhea, menorrhagia, and infertility.

Epigenomic Profiling of Epithelial Ovarian Cancer Stem-Cell Differentiation Reveals GPD1 Associated Immune Suppressive Microenvironment and Poor Prognosis.

Intraperitoneal metastasis is a challenging clinical scenario in epithelial ovarian cancer (EOC). As they are distinct from hematogenous metastasizing tumors, epithelial ovarian cancer cells primarily disseminate within the peritoneal cavity to form superficially invasive carcinomas. Unfavorable pharmacokinetics for peritoneal tumors and gut toxicity collectively lead to a narrow therapeutic window and therefore limit the opportunities for a favorable clinical outcome. New insights into tumor metastasis in the peritoneal microenvironment are keenly awaited to develop new therapeutic strategies. Epithelial ovarian cancer stem cell (OCSC) seeding is considered to be a critical component of the peritoneal spread. Using a unique and stepwise process of the OCSC differentiation model may provide insight into the intraperitoneal metastasis. The transcriptome and epigenome of OCSC differentiation were characterized by expression array and MethylCap-Seq. The TCGA, AOCS, and KM-Plotter databases were used to evaluate the association between survival outcomes and the methylation/expression levels of candidate genes in the EOC datasets. The STRING database was used to investigate the protein-protein interaction (PPI) for candidates and their associated genes. The infiltration level of immune cells in EOC patients and the association between clinical outcome and OCSCs differentiation genes were estimated using the TIDE and TIME2.0 algorithms. We established an EOC differentiation model using OCSCs. After an integrated transcriptomics and methylomics analysis of OCSCs differentiation, we revealed that the genes associated with earlier OCSC differentiation were better able to reflect the patient's outcome. The OCSC differentiation genes were involved in regulating metabolism shift and the suppressive immune microenvironment. High GPD1 expression with high pro-tumorigenic immune cells (M2 macrophage, and cancer associated fibroblast) had worst survival. Moreover, we developed a methylation signature, constituted by GNPDA1, GPD1, GRASP, HOXC11, and MSLN, that may be useful for prognostic prediction in EOC. Our results revealed a novel role of epigenetic plasticity OCSC differentiation and suggested metabolic and immune intervention as a new therapeutic strategy.

NKX6-1 mediates cancer stem-like properties and regulates sonic hedgehog signaling in leiomyosarcoma.

BACKGROUND: Leiomyosarcoma (LMS), the most common soft tissue sarcoma, exhibits heterogeneous and complex genetic karyotypes with severe chromosomal instability and rearrangement and poor prognosis. METHODS: Clinical variables associated with NKX6-1 were obtained from The Cancer Genome Atlas (TCGA). NKX6-1 mRNA expression was examined in 49 human uterine tissues. The in vitro effects of NXK6-1 in LMS cells were determined by reverse transcriptase PCR, western blotting, colony formation, spheroid formation, and cell viability assays. In vivo tumor growth was evaluated in nude mice. RESULTS: Using The Cancer Genome Atlas (TCGA) and human uterine tissue datasets, we observed that NKX6-1 expression was associated with poor prognosis and malignant potential in LMS. NKX6-1 enhanced in vitro tumor cell aggressiveness via upregulation of cell proliferation and anchorage-independent growth and promoted in vivo tumor growth. Moreover, overexpression and knockdown of NKX6-1 were associated with upregulation and downregulation, respectively, of stem cell transcription factors, including KLF8, MYC, and CD49F, and affected sphere formation, chemoresistance, NOTCH signaling and Sonic hedgehog (SHH) pathways in human sarcoma cells. Importantly, treatment with an SHH inhibitor (RU-SKI 43) but not a NOTCH inhibitor (DAPT) reduced cell survival in NKX6-1-expressing cancer cells, indicating that an SHH inhibitor could be useful in treating LMS. Finally, using the TCGA dataset, we demonstrated that LMS patients with high expression of NKX6-1 and HHAT, an SHH pathway acyltransferase, had poorer survival outcomes compared to those without. CONCLUSIONS: Our findings indicate that NKX6-1 and HHAT play critical roles in the pathogenesis of LMS and could be promising diagnostic and therapeutic targets for LMS patients.

TET1 reprograms the epithelial ovarian cancer epigenome and reveals casein kinase 2α as a therapeutic target.

Ten-eleven translocation methylcytosine dioxygenase-1, TET1, takes part in active DNA demethylation. However, our understanding of DNA demethylation in cancer biology and its clinical significance remain limited. This study showed that TET1 expression correlated with poor survival in advanced-stage epithelial ovarian carcinoma (EOC), and with cell migration, anchorage-independent growth, cancer stemness, and tumorigenicity. In particular, TET1 was highly expressed in serous tubal intraepithelial carcinoma (STIC), a currently accepted type II EOC precursor, and inversely correlated with TP53 mutations. Moreover, TET1 could demethylate the epigenome and activate multiple oncogenic pathways, including an immunomodulation network having casein kinase II subunit alpha (CK2α) as a hub. Patients with TET1high CK2αhigh EOCs had the worst outcomes, and TET1-expressing EOCs were more sensitive to a CK2 inhibitor, both in vitro and in vivo. Our findings uncover the oncogenic and poor prognostic roles of TET1 in EOC and suggest an unexplored role of epigenetic reprogramming in early ovarian carcinogenesis. Moreover, the immunomodulator CK2α represents a promising new therapeutic target, warranting clinical trials of the tolerable CK2 inhibitor, CX4945, for precision medicine against EOC. Copyright © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

GATA3 as a master regulator and therapeutic target in ovarian high-grade serous carcinoma stem cells.

Ovarian high-grade serous carcinoma (HGSC) is the most lethal gynecological malignancy. Prevailing evidences suggest that drug resistance and recurrence of ovarian HGSC are caused by the presence of cancer stem cells. Therefore, targeting cancer stems is appealing, however, all attempts to date, have failed. To circumvent this limit, we analyzed differential transcriptomes at early differentiation of ovarian HGSC stem cells and identified the developmental transcription factor GATA3 as highly expressed in stem, compared to progenitor cells. GATA3 expression associates with poor prognosis of ovarian HGSC patients, and was found to recruit the histone H3, lysine 27 (H3K27) demethylase, UTX, activate stemness markers, and promote stem-like phenotypes in ovarian HGSC cell lines. Targeting UTX by its inhibitor, GSKJ4, impeded GATA3-driven stemness phenotypes, and enhanced apoptosis of GATA3-expressing cancer cells. Combinations of gemcitabine or paclitaxel with GSKJ4, resulted in a synergistic cytotoxic effect. Our findings provide evidence for a new role for GATA3 in ovarian HGSC stemness, and demonstrate that GATA3 may serve as a biomarker for precision epigenetic therapy in the future.

Epigenetic loss of heparan sulfate 3-O-sulfation sensitizes ovarian carcinoma to oncogenic signals and predicts prognosis.

Precision medicine requires markers for therapeutic guidance. The purpose of this study was to determine whether epithelial ovarian cancer (EOC) epigenetics can lead to the identification of biomarkers for precision medicine. Through integrative methylomics, we discovered and validated the epigenetic signature of NEFH and HS3ST2 as an independent prognostic factor for type II EOC in our dataset (n = 84), and two independent methylomics datasets (total n = 467). Integrated transcriptomics dataset (n = 1147) and tissue microarrays (n = 54) of HS3ST2 also related to high-methylation statuses and the EOC prognosis. Mechanistic explorations of HS3ST2 have assessed responses to oncogenic stimulations such as IL-6, EGF, and FGF2 in cancer cells. The combination of HS3ST2 and various oncogenic ligands also confers the worse outcome. 3-O-sulfation of heparan sulfate by HS3ST2 makes ovarian cancer cells intrinsically sensitive to oncogenic signals, which sheds new light on the application of HS3ST2 as a companion diagnostic for targeted therapy using kinase inhibitors or therapeutic antibodies.

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.

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

BACKGROUND: Non-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. METHODS: We 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. RESULTS: We 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. CONCLUSIONS: Methylation 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.

Methylomics analysis identifies epigenetically silenced genes and implies an activation of ß-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 ß-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.

Active DNA Demethylase, TET1, Increases Oxidative Phosphorylation and Sensitizes Ovarian Cancer Stem Cells to Mitochondrial Complex I Inhibitor.

Ten-eleven translocation 1 (TET1) is a methylcytosine dioxygenase involved in active DNA demethylation. In our previous study, we demonstrated that TET1 reprogrammed the ovarian cancer epigenome, increased stem properties, and activated various regulatory networks, including metabolic networks. However, the role of TET1 in cancer metabolism remains poorly understood. Herein, we uncovered a demethylated metabolic gene network, especially oxidative phosphorylation (OXPHOS). Contrary to the concept of the Warburg effect in cancer cells, TET1 increased energy production mainly using OXPHOS rather than using glycolysis. Notably, TET1 increased the mitochondrial mass and DNA copy number. TET1 also activated mitochondrial biogenesis genes and adenosine triphosphate production. However, the reactive oxygen species levels were surprisingly decreased. In addition, TET1 increased the basal and maximal respiratory capacities. In an analysis of tricarboxylic acid cycle metabolites, TET1 increased the levels of α-ketoglutarate, which is a coenzyme of TET1 dioxygenase and may provide a positive feedback loop to modify the epigenomic landscape. TET1 also increased the mitochondrial complex I activity. Moreover, the mitochondrial complex I inhibitor, which had synergistic effects with the casein kinase 2 inhibitor, affected ovarian cancer growth. Altogether, TET1-reprogrammed ovarian cancer stem cells shifted the energy source to OXPHOS, which suggested that metabolic intervention might be a novel strategy for ovarian cancer treatment.

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.

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.

Genome-wide analysis of cervical secretions obtained during embryo transfer reveals the association between deoxyribonucleic acid methylation and pregnancy outcomes.

OBJECTIVE: To study whether the methylation status of cervical secretions can reflect the ability of the endometrium to allow embryo implantation. DESIGN: Case-control study. SETTING: In vitro fertilization centers. PATIENT(S): Women undergoing embryo transfer cycles, in which at least 1 good-quality embryo was transferred. INTERVENTION(S): Collection of cervical secretions during the procedure of embryo transfer. MAIN OUTCOME MEASURE(S): Methylation profiles of cervical secretions in relation to pregnancy outcomes. RESULT(S): Genome-wide methylation profiles differ between cervical secretions from pregnancy and nonpregnancy cycles. Clustering analysis on the basis of the top 2,000 differentially methylated probes of cervical secretions from 28 pregnancy and 29 nonpregnancy cycles correctly categorized 86.0% of the samples in terms of conceptional status, which was verified in selected genes by quantitative methylation-specific polymerase chain reaction and validated in another independent sample set. The combination of selected genes was estimated to predict pregnancy outcomes with a maximal area under the receiver operating characteristic curve of 0.83. CONCLUSION(S): The methylation profiles of cervical secretions were associated with pregnancy outcomes in embryo transfer cycles. Although not clinically useful at present, deoxyribonucleic acid methylation in cervical secretions may shed new light on the less invasive assessment of endometrial receptivity.

Endometrial Cancer Detection Using a Cervical DNA Methylation Assay (MPap) in Women with Abnormal Uterine Bleeding: A Multicenter Hospital-Based Validation Study.

BACKGROUND: We describe a DNA methylation assay, named MPap test, using cervical scraping as an alternative technique for endometrial cancer detection. METHODS: A multicenter hospital-based, two-stage validation study was conducted to validate the cancer detection performance of the MPap test. The MPap value was determined from the DNA methylation status of two genes (BHLHE22, CDO1) and combined with two other clinical variables (age, BMI). The cutoff threshold of the MPap value was established in stage 1 and validated in stage 2. A total of 592 women with abnormal uterine bleeding were enrolled from five medical centers throughout Taiwan. RESULTS: In stage 1, the sensitivity, specificity, and positive and negative predictive values of the MPap test for detecting endometrial cancer were 92.9%, 71.5%, 39.8%, and 98.0%, respectively. These values were validated in stage 2, being 92.5%, 73.8%, 40.2%, and 98.1%. Moreover, MPap outperformed transvaginal ultrasound in sensitivity and negative predictive values for detecting endometrial cancer. When we applied the algorithm for triage of endometrial cancer detection by MPap in the Taiwan National Health Insurance dataset, we found that it may reduce invasive procedures by 69~73%. CONCLUSIONS: MPap may provide a feasible alternative for endometrial cancer detection and can be considered as a triage test to reduce unnecessary invasive procedures.

Measuring outcomes in healthcare economics using Artificial Intelligence: With application to resource management.

The quality of service in healthcare is constantly challenged by outlier events such as pandemics (i.e., Covid-19) and natural disasters (such as hurricanes and earthquakes). In most cases, such events lead to critical uncertainties in decision-making, as well as in multiple medical and economic aspects at a hospital. External (geographic) or internal factors (medical and managerial) lead to shifts in planning and budgeting, but most importantly, reduce confidence in conventional processes. In some cases, support from other hospitals proves necessary, which exacerbates the planning aspect. This paper presents three data-driven methods that provide data-driven indicators to help healthcare managers organize their economics and identify the most optimum plan for resources allocation and sharing. Conventional decision-making methods fall short in recommending validated policies for managers. Using reinforcement learning, genetic algorithms, traveling salesman, and clustering, we experimented with different healthcare variables and presented tools and outcomes that could be applied at health institutes. Experiments are performed; the results are recorded, evaluated, and presented.

Characterization of LMX-1A as a metastasis suppressor in cervical cancer.

DNA methylation is important in cancer development and is a promising biomarker for cancer detection. An epigenomic approach used in our previous work showed that LMX-1A is methylation-silenced in cervical cancer. LMX-1A, a LIM-homeobox gene, is known to participate in developmental events; however, there are at present no data on the role of LMX-1A in cancers. In this study, we characterized the function of this transcription factor by examining cell lines, animal models and human cervical neoplastic tissues, and found that over-expression of LMX-1A does not affect cell proliferation or the cell cycle of cervical cancer cell lines but significantly inhibits colony formation and invasion in vitro. Analysis of changes in epithelial-mesenchymal transition (EMT) markers, such as CDH1, CDH2, VIMENTIN, SNAIL, SLUG and TWIST, revealed involvement of the EMT in LMX-1A-mediated cancer invasion; this result was validated in a stable transfectant over-expressing LMX-1A with RNA interference. Xenograft studies using immunocompromised mice confirmed the suppressor effects of LMX-1A on tumour formation and distant metastasis in cervical cancer cell lines. LMX-1A immunohistochemical staining of tissue arrays containing the full spectrum of cervical neoplasms, including normal cervix, low-grade cervical intra-epithelial neoplasia (CIN), high-grade CIN, locally invasive and distant metastatic cancers, demonstrated the critical role of LMX-1A in invasion and metastasis. Furthermore, we found by analysing TGFbeta-BMP signalling that BMP4 and BMP6 are down-regulated by LMX-1A. The results of this study suggest that LMX-1A suppresses cancer invasion and metastasis in cervical cancer through an incomplete EMT.

Current development in integrative therapy of traditional Chinese medicine for cancer treatment: A mini-review.

Cancer is a major public health problem worldwide, and there has been a sustained rise in its incidence in both developing and developed countries. Although there are currently numerous effective therapeutic options for cancer, they sometimes exhibit resistance and obvious side effects. Traditional Chinese medicine (TCM) currently plays a major role in cancer therapy by downregulating the growth of cancer cells through various pathways and by relieving side effects. Studies in cultured human malignant cell lines have demonstrated that Solanum nigrum can control cancer cell proliferation and cancer progression by inducing autophagic and apoptotic cell death. Case-control studies have indicated that TCM can relieve the side effects of cancer therapy. This review provides brief insights into the anticancer effects of TCM, the side effects relieved by TCM, and the role of TCM doctors in cancer treatment.