Dysregulated Immunological Functionome and Dysfunctional Metabolic Pathway Recognized for the Pathogenesis of Borderline Ovarian Tumors by Integrative Polygenic Analytics.

The pathogenesis and molecular mechanisms of ovarian low malignant potential (LMP) tumors or borderline ovarian tumors (BOTs) have not been fully elucidated to date. Surgery remains the cornerstone of treatment for this disease, and diagnosis is mainly made by histopathology to date. However, there is no integrated analysis investigating the tumorigenesis of BOTs with open experimental data. Therefore, we first utilized a functionome-based speculative model from the aggregated obtainable datasets to explore the expression profiling data among all BOTs and two major subtypes of BOTs, serous BOTs (SBOTs) and mucinous BOTs (MBOTs), by analyzing the functional regularity patterns and clustering the separate gene sets. We next prospected and assembled the association between these targeted biomolecular functions and their related genes. Our research found that BOTs can be accurately recognized by gene expression profiles by means of integrative polygenic analytics among all BOTs, SBOTs, and MBOTs; the results exhibited the top 41 common dysregulated biomolecular functions, which were sorted into four major categories: immune and inflammatory response-related functions, cell membrane- and transporter-related functions, cell cycle- and signaling-related functions, and cell metabolism-related functions, which were the key elements involved in its pathogenesis. In contrast to previous research, we identified 19 representative genes from the above classified categories (IL6, CCR2 for immune and inflammatory response-related functions; IFNG, ATP1B1, GAS6, and PSEN1 for cell membrane- and transporter-related functions; CTNNB1, GATA3, and IL1B for cell cycle- and signaling-related functions; and AKT1, SIRT1, IL4, PDGFB, MAPK3, SRC, TWIST1, TGFB1, ADIPOQ, and PPARGC1A for cell metabolism-related functions) that were relevant in the cause and development of BOTs. We also noticed that a dysfunctional pathway of galactose catabolism had taken place among all BOTs, SBOTs, and MBOTs from the analyzed gene set databases of canonical pathways. With the help of immunostaining, we verified significantly higher performance of interleukin 6 (IL6) and galactose-1-phosphate uridylyltransferase (GALT) among BOTs than the controls. In conclusion, a bioinformatic platform of gene-set integrative molecular functionomes and biophysiological pathways was constructed in this study to interpret the complicated pathogenic pathways of BOTs, and these important findings demonstrated the dysregulated immunological functionome and dysfunctional metabolic pathway as potential roles during the tumorigenesis of BOTs and may be helpful for the diagnosis and therapy of BOTs in the future.

The Potential Role of Complement System in the Progression of Ovarian Clear Cell Carcinoma Inferred from the Gene Ontology-Based Immunofunctionome Analysis.

Ovarian clear cell carcinoma (OCCC) is the second most common epithelial ovarian carcinoma (EOC). It is refractory to chemotherapy with a worse prognosis after the preliminary optimal debulking operation, such that the treatment of OCCC remains a challenge. OCCC is believed to evolve from endometriosis, a chronic immune/inflammation-related disease, so that immunotherapy may be a potential alternative treatment. Here, gene set-based analysis was used to investigate the immunofunctionomes of OCCC in early and advanced stages. Quantified biological functions defined by 5917 Gene Ontology (GO) terms downloaded from the Gene Expression Omnibus (GEO) database were used. DNA microarray gene expression profiles were used to convert 85 OCCCs and 136 normal controls into to the functionome. Relevant offspring were as extracted and the immunofunctionomes were rebuilt at different stages by machine learning. Several dysregulated pathogenic functions were found to coexist in the immunopathogenesis of early and advanced OCCC, wherein the complement-activation-alternative-pathway may be the headmost dysfunctional immunological pathway in duality for carcinogenesis at all OCCC stages. Several immunological genes involved in the complement system had dual influences on patients' survival, and immunohistochemistrical analysis implied the higher expression of C3a receptor (C3aR) and C5a receptor (C5aR) levels in OCCC than in controls.

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.

Key Immunological Functions Involved in the Progression of Epithelial Ovarian Serous Carcinoma Discovered by the Gene Ontology-Based Immunofunctionome Analysis.

Serous carcinoma (SC) is the most common and lethal subtype of epithelial ovarian carcinoma; immunotherapy is a potential treatment for SC, however, the global immunological functions of SC as well as their change during the progression of SC have not been investigated in detail till now. We conducted a genome-wide integrative analysis to investigate the immunofunctionomes of SC at four tumor stages by quantifying the immunological functions defined by the Gene Ontology gene sets. DNA microarray gene expression profiles of 1100 SCs and 136 normal ovarian tissue controls were downloaded from the Gene Expression Omnibus database and converted to the functionome. Then the immunofunctionomes were reconstructed by extracting the offspring from the functionome for the four SC staging groups. The key immunological functions extracted from immunofunctionomes with a series of filters revealed that the immunopathy of SC consisted of a group of deregulated functions with the core members including B cell activation and differentiation, regulation of leukocyte chemotaxis/cellular extravasation, antigen receptor mediated signaling pathway, T helper mediated immunity and macrophage activation; and the auxiliary elements included leukocyte mediated immunity, regulation of inflammatory response, T cell differentiation, mononuclear cell migration, megakaryocyte differentiation, complement activation and cytokine production. These deregulated immunological functions reveal the candidates to target in the immunotherapy.

Discovering the Deregulated Molecular Functions Involved in Malignant Transformation of Endometriosis to Endometriosis-Associated Ovarian Carcinoma Using a Data-Driven, Function-Based Analysis.

The clinical characteristics of clear cell carcinoma (CCC) and endometrioid carcinoma EC) are concomitant with endometriosis (ES), which leads to the postulation of malignant transformation of ES to endometriosis-associated ovarian carcinoma (EAOC). Different deregulated functional areas were proposed accounting for the pathogenesis of EAOC transformation, and there is still a lack of a data-driven analysis with the accumulated experimental data in publicly-available databases to incorporate the deregulated functions involved in the malignant transformation of EOAC. We used the microarray gene expression datasets of ES, CCC and EC downloaded from the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO) database. Then, we investigated the pathogenesis of EAOC by a data-driven, function-based analytic model with the quantified molecular functions defined by 1454 Gene Ontology (GO) term gene sets. This model converts the gene expression profiles to the functionome consisting of 1454 quantified GO functions, and then, the key functions involving the malignant transformation of EOAC can be extracted by a series of filters. Our results demonstrate that the deregulated oxidoreductase activity, metabolism, hormone activity, inflammatory response, innate immune response and cell-cell signaling play the key roles in the malignant transformation of EAOC. These results provide the evidence supporting the specific molecular pathways involved in the malignant transformation of EAOC.

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.

Gene Set-Based Functionome Analysis of Pathogenesis in Epithelial Ovarian Serous Carcinoma and the Molecular Features in Different FIGO Stages.

Serous carcinoma (SC) is the most common subtype of epithelial ovarian carcinoma and is divided into four stages by the Federation of Gynecologists and Obstetrics (FIGO) staging system. Currently, the molecular functions and biological processes of SC at different FIGO stages have not been quantified. Here, we conducted a whole-genome integrative analysis to investigate the functions of SC at different stages. The function, as defined by the GO term or canonical pathway gene set, was quantified by measuring the changes in the gene expressional order between cancerous and normal control states. The quantified function, i.e., the gene set regularity (GSR) index, was utilized to investigate the pathogenesis and functional regulation of SC at different FIGO stages. We showed that the informativeness of the GSR indices was sufficient for accurate pattern recognition and classification for machine learning. The function regularity presented by the GSR indices showed stepwise deterioration during SC progression from FIGO stage I to stage IV. The pathogenesis of SC was centered on cell cycle deregulation and accompanied with multiple functional aberrations as well as their interactions.

Gene Set-Based Integrative Analysis Revealing Two Distinct Functional Regulation Patterns in Four Common Subtypes of Epithelial Ovarian Cancer.

Clear cell (CCC), endometrioid (EC), mucinous (MC) and high-grade serous carcinoma (SC) are the four most common subtypes of epithelial ovarian carcinoma (EOC). The widely accepted dualistic model of ovarian carcinogenesis divided EOCs into type I and II categories based on the molecular features. However, this hypothesis has not been experimentally demonstrated. We carried out a gene set-based analysis by integrating the microarray gene expression profiles downloaded from the publicly available databases. These quantified biological functions of EOCs were defined by 1454 Gene Ontology (GO) term and 674 Reactome pathway gene sets. The pathogenesis of the four EOC subtypes was investigated by hierarchical clustering and exploratory factor analysis. The patterns of functional regulation among the four subtypes containing 1316 cases could be accurately classified by machine learning. The results revealed that the ERBB and PI3K-related pathways played important roles in the carcinogenesis of CCC, EC and MC; while deregulation of cell cycle was more predominant in SC. The study revealed that two different functional regulation patterns exist among the four EOC subtypes, which were compatible with the type I and II classifications proposed by the dualistic model of ovarian carcinogenesis.

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.

Prognostic factors and treatment outcomes for patients with surgically staged uterine clear cell carcinoma focusing on the early stage: A Taiwanese Gynecologic Oncology Group study.

OBJECTIVE: The aim of this study was to investigate the clinical and pathological characteristics of uterine clear cell carcinoma (UCCC) and the treatment of this disease in relation to patient outcomes. METHODS: The clinicopathological data for and the management of all patients with UCCC who presented between 1991 and 2010 at 11 member hospitals of the Taiwanese Gynecologic Oncology Group (TGOG) were retrospectively reviewed. RESULTS: There were no significant differences in 5-year overall survival (OS) rates between patients with pure UCCC (n=100) and non-pure UCCC (n=53) at the same surgical stage, with OS rates of 92.6%, and 87.7% for stage I; 83.3% and 83.3% for stage II; 64.0% and 67.8% for stage III; and 16.7% and 0% for stage IV (n=1), respectively. Tumor stage and age independently influenced the OS rate of UCCC. For the patients with early stage UCCC, the adjuvant therapy modality was the only significant prognostic factor for recurrence-free survival. The patients with early stage UCCC who received adjuvant therapy had excellent 5-year recurrence-free survival and OS rates compared to those who received radiotherapy (100% vs. 74%, p=0.01; 100% vs. 72%, p=0.03). CONCLUSIONS: The 5-year survival rates of patients with pure UCCC and non-pure UCCC were similar. The prognosis for surgical staging of patients with stage I/II UCCC was encouraging. Postoperative adjuvant platinum-based chemotherapy is recommended for patients with early stage UCCC who are at a high risk of recurrence.

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.

7,7''-Dimethoxyagastisflavone-induced apoptotic or autophagic cell death in different cancer cells.

7,7''-Dimethoxyagastisflavone (DMGF), a biflavonoid isolated from the needles of Taxus × media cv. Hicksii, was evaluated for its antiproliferative and antineoplastic effects in three human cancer cell lines. Interestingly, DMGF caused cell death via different pathways in different cancer cells. DMGF induced apoptosis, activated caspase-3 activity and changed the mitochondrial membrane potential in HT-29 human colon cancer cells. However, the apoptotic pathway is not the major pathway involved in DMGF-induced cell death in A549 human lung cancer cells and HepG2 human hepatoma cells. Treatment with 3-MA, an inhibitor of autophagy, significantly decreased DMGF-induced cell death in HepG2 and A549 cells, but did not affect DMGF-induced cell death in HT-29 cells. Following DMGF treatment, the HepG2 cells increased expression of LC3B-II, a marker used to monitor autophagy in cells. Thus, DMGF induced apoptotic cell death in HT-29 cells, triggered both apoptotic and autophagic death in A549 cells and induced autophagic cell death in HepG2 cells.

High-grade endometrial stromal sarcoma in cesarean section scar isthmocele - case report.

OBJECTIVE: Cesarean section scar defect isthmocele, the pouchlike defect in the anterior uterine wall of the prior cesarean site. No previous report of malignant neoplasm in the isthmocele have been published. We reported a case of High-grade endometrial stromal sarcoma in isthmocele. CASE REPORT: A 45-year-old patient with gravida 4, parity 2, two previous cesarean section presents of recurrent heavy vaginal bleeding. Curettage and hormone therapy were unsuccessful. She underwent hysteroscopic isthmoplasty. The pathology revealed high-grade sarcoma. Patient was referred to a tertiary medical center and she underwent total hysterectomy with bilateral salpingo-oophorectomy, aortic & pelvic LNs dissection. The final diagnosis was High-grade endometrial stromal sarcoma (HG-ESS) stage IA (pT1a N0) involving isthmocele. CONCLUSION: The presence of this rare tumor in the isthmocele is very interested. We stress the necessity for a high degree of suspicion to diagnose the malignancy in perimenopausal women with isthmocele and persisted abnormal uterine bleeding.

Weakly supervised deep learning for prediction of treatment effectiveness on ovarian cancer from histopathology images.

Despite the progress made during the last two decades in the surgery and chemotherapy of ovarian cancer, more than 70 % of advanced patients are with recurrent cancer and decease. Surgical debulking of tumors following chemotherapy is the conventional treatment for advanced carcinoma, but patients with such treatment remain at great risk for recurrence and developing drug resistance, and only about 30 % of the women affected will be cured. Bevacizumab is a humanized monoclonal antibody, which blocks VEGF signaling in cancer, inhibits angiogenesis and causes tumor shrinkage, and has been recently approved by FDA as a monotherapy for advanced ovarian cancer in combination with chemotherapy. Considering the cost, potential toxicity, and finding that only a portion of patients will benefit from these drugs, the identification of new predictive method for the treatment of ovarian cancer remains an urgent unmet medical need. In this study, we develop weakly supervised deep learning approaches to accurately predict therapeutic effect for bevacizumab of ovarian cancer patients from histopathological hematoxylin and eosin stained whole slide images, without any pathologist-provided locally annotated regions. To the authors' best knowledge, this is the first model demonstrated to be effective for prediction of the therapeutic effect of patients with epithelial ovarian cancer to bevacizumab. Quantitative evaluation of a whole section dataset shows that the proposed method achieves high accuracy, 0.882 ± 0.06; precision, 0.921 ± 0.04, recall, 0.912 ± 0.03; F-measure, 0.917 ± 0.07 using 5-fold cross validation and outperforms two state-of-the art deep learning approaches Coudray et al. (2018), Campanella et al. (2019). For an independent TMA testing set, the three proposed methods obtain promising results with high recall (sensitivity) 0.946, 0.893 and 0.964, respectively. The results suggest that the proposed method could be useful for guiding treatment by assisting in filtering out patients without positive therapeutic response to suffer from further treatments while keeping patients with positive response in the treatment process. Furthermore, according to the statistical analysis of the Cox Proportional Hazards Model, patients who were predicted to be invalid by the proposed model had a very high risk of cancer recurrence (hazard ratio = 13.727) than patients predicted to be effective with statistical signifcance (p < 0.05).

A Weakly Supervised Deep Learning Method for Guiding Ovarian Cancer Treatment and Identifying an Effective Biomarker.

Ovarian cancer is a common malignant gynecological disease. Molecular target therapy, i.e., antiangiogenesis with bevacizumab, was found to be effective in some patients of epithelial ovarian cancer (EOC). Although careful patient selection is essential, there are currently no biomarkers available for routine therapeutic usage. To the authors' best knowledge, this is the first automated precision oncology framework to effectively identify and select EOC and peritoneal serous papillary carcinoma (PSPC) patients with positive therapeutic effect. From March 2013 to January 2021, we have a database, containing four kinds of immunohistochemical tissue samples, including AIM2, c3, C5 and NLRP3, from patients diagnosed with EOC and PSPC and treated with bevacizumab in a hospital-based retrospective study. We developed a hybrid deep learning framework and weakly supervised deep learning models for each potential biomarker, and the experimental results show that the proposed model in combination with AIM2 achieves high accuracy 0.92, recall 0.97, F-measure 0.93 and AUC 0.97 for the first experiment (66% training and 34%testing) and high accuracy 0.86 ± 0.07, precision 0.9 ± 0.07, recall 0.85 ± 0.06, F-measure 0.87 ± 0.06 and AUC 0.91 ± 0.05 for the second experiment using five-fold cross validation, respectively. Both Kaplan-Meier PFS analysis and Cox proportional hazards model analysis further confirmed that the proposed AIM2-DL model is able to distinguish patients gaining positive therapeutic effects with low cancer recurrence from patients with disease progression after treatment (p < 0.005).

Histopathological whole slide image dataset for classification of treatment effectiveness to ovarian cancer.

Ovarian cancer is the leading cause of gynecologic cancer death among women. Regardless of the development made in the past two decades in the surgery and chemotherapy of ovarian cancer, most of the advanced-stage patients are with recurrent cancer and die. The conventional treatment for ovarian cancer is to remove cancerous tissues using surgery followed by chemotherapy, however, patients with such treatment remain at great risk for tumor recurrence and progressive resistance. Nowadays, new treatment with molecular-targeted agents have become accessible. Bevacizumab as a monotherapy in combination with chemotherapy has been recently approved by FDA for the treatment of epithelial ovarian cancer (EOC). Prediction of therapeutic effects and individualization of therapeutic strategies are critical, but to the authors' best knowledge, there are no effective biomarkers that can be used to predict patient response to bevacizumab treatment for EOC and peritoneal serous papillary carcinoma (PSPC). This dataset helps researchers to explore and develop methods to predict the therapeutic effect of patients with EOC and PSPC to bevacizumab.

Verification of HPV16 as a good prognostic factor for cervical adeno-adenosquamous carcinoma via an international collaborative study.

OBJECTIVE: This study (Asian Gynecologic Oncology Group [AGOG]13-001/Taiwanese Gynecologic Oncology Group [TGOG]1006) was to validate human papillomavirus (HPV)16 as an independent good prognostic factor and investigate the impact of treatment modalities to cervical adenocarcinoma and adenosquamous carcinoma (AD/ASC). MATERIALS AND METHODS: Patients receiving primary treatment at AGOG and TGOG member hospitals for cervical AD/ASC were retrospectively (1993-2014) and prospectively (since 2014) enrolled. DNA extraction from paraffin-embedded tissue (FFPE) specimens was used for HPV genotyping. Those with suspected endometrial origin were excluded for analysis. RESULTS: A total of 354 patients with valid HPV results were enrolled, 287 (81.1%) of which had HPV-positive tumors. The top-3 types were HPV 18 (50.8%), HPV16 (22.9%) and HPV45 (4.0%). The HPV16-negativity rates varied widely across hospitals. 322 patients were eligible for prognostic analyses. By multivariate analysis, advanced stage (HR5.8, 95% confidence interval [CI] 2.1-15.8; HR5.8, 95% CI 1.6-20.5), lymph node metastasis (HR4.6, 95% CI 2.7-7.9; HR7.3, 95% CI 3.8-14.0), and HPV16-positivity (HR0.3, 95% CI 0.1-0.6; HR0.3, 95% CI 0.1-0.9) were independent prognostic factors for progression-free survival (PFS) and overall survival (OS). Stage I patients with primary surgery had better 5-year PFS (82.8% vs 50.0% p = 0.020) and OS (89.3% vs 57.1%, p = 0.017) than those with non-primary surgery, while the propensity scores distribution were similar among the treatment groups. CONCLUSION: This study confirmed that HPV16-positivity was a good prognostic factor for PFS and OS in AD/ASC, and patients seemed to have better outcome with primary surgery than non-primary surgery.

The impact of COVID-19 in pregnancy: Part II. Vaccination to pregnant women.

Effective strategies are urgently needed to decrease the risk of untoward outcomes of pregnant women with severe acute respiratory syndrome coronavirus 2 (coronavirus disease 2019 [COVID-19]) infection. Pregnant women are a vulnerable population to infectious disease pandemics with dramatically increased infectious diseases-related serious complications, such as the need of hospitalizations, the need of admission to intensive care unit, and the final disease-related death compared with those nonpregnant counterparts or those pregnant women without infection. Several studies have shown that vaccinations in pregnancy are a safe and highly effective strategy, not only for pregnant women but also for fetus and/or newborn because of the passive transplacental transfer of antibodies to the offspring. Active and passive prevention of infectious diseases is approved as effective strategies for women who attempt to become pregnant or during pregnancy. Despite the large and proven scientific evidence, pregnant women still puzzle over whether they should get vaccinated. The question therefore arises: Why are pregnant women so reluctant to receive vaccination? The explanation is more likely in the way that the benefits of vaccination have been communicated "confusedly." In fact, like virtually all clinical trials, all the COVID-19 vaccine trials have excluded pregnant and lactating women from participating, contributing to uncertainty of safety and efficacy in COVID-19 vaccines that have been well prepared and available for the general adult population worldwide. Moreover, messenger RNA vaccine is a relatively brand-new vaccine, and experience with this type of vaccine is still scarce. It is hard to overcome this innovation deadlock. The knowledge and awareness of pregnant women who are at risk, and full information on the knowledge of vaccines and related preventable diseases in pregnant women may avoid hesitancy and increase vaccine acceptance. The current review is a part two addressing the impact of COVID-19 on pregnant women. We focus on the up-to-date information about the application of vaccination on pregnant women, especially during this COVID-19 pandemic.

The role of micronutrient and immunomodulation effect in the vaccine era of COVID-19.

Different dietary nutrients have distinct effects, including enhancing immune response activity and supporting mucous membrane integrity. These effects are critical in fighting against pathogenic agents, which cover coronavirus disease 2019 (COVID-19), the coronavirus disease that shuts down globally. Recent researches have shown that micronutrient deficiency is commonly associated with compromised immune responses, respiratory tract infections, or even susceptibility to COVID-19. The relationship between Vit A and infection is its role in mucosal epithelium integrity (skin and mucous membrane), the supplementation could be an option for assisted-treating the SARS-CoV-2 virus and a possible prevention of lung infection. Vit C/ascorbic acid stimulates oxygen radical scavenging activity of the skin and enhances epithelial barrier function. Ascorbic acid alone or with other natural compounds (baicalin and theaflavin) may inhibit the expression of angiotensin-converting enzyme II in human small alveolar epithelial cells and limited the entry of SARS-CoV-2. Vitamin D receptors can be expressed by immune cells, and different immune cells (macrophages, monocytes, dendritic cells, T cells, and B cells) can convert Vit D into its active form 1,25-(OH)2 D. Oral vitamin D intake can be a readily way to restrict the viral infection through downregulation of ACE2 receptor and to attenuate the disease severity by decreasing the frequency of cytokine storm and pulmonary pro-inflammatory response. Vit E supports T-cell mediated functions, optimization of Th1 response, and suppression of Th2 response. Vitamin E supplementation can lower the production of superoxides and may favors the antioxidants and benefit the progress of COVID-19 treatment. Zinc plays an essential role in both innate and adaptive immune systems and cytokine production, and Zinc-dependent viral enzymes to initiate the infectious process have proved the Zinc levels are directly associated with symptoms relieved of COVID-19. Iron is an essential component of enzymes involved in the activation of immune cells, lower iron levels predispose to severe symptoms of SARS-CoV-2, and monitoring the status can predict the disease severity and mortality. Selenium participates in the adaptive immune response by supporting antibody production and development. Deficiency can reduce antibody concentration, decreased cytotoxicity of NK cells, compromised cellular immunity, and an attenuated response to vaccination. The COVID-19 vaccines including three broad categories, protein-based vaccines, gene-based vaccines (mRNA vaccines and DNA vaccines), combination of gene and protein-based vaccines. Micronutrients are involved in immunity from the virus entering the human to innate immune response and adaptive immune response. Micronutrients are indispensable in immune response of vaccination.