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The objective of the present study was to investigate whether deep learning could be applied successfully to the classification of images from colposcopy. For this purpose, a total of 158 patients who underwent conization were enrolled, and medical records and data from the gynecological oncology database were retrospectively reviewed. Deep learning was performed with the Keras neural network and TensorFlow libraries. Using preoperative images from colposcopy as the input data and deep learning technology, the patients were classified into three groups [severe dysplasia, carcinoma in situ (CIS) and invasive cancer (IC)]. A total of 485 images were obtained for the analysis, of which 142 images were of severe dysplasia (2.9 images/patient), 257 were of CIS (3.3 images/patient), and 86 were of IC (4.1 images/patient). Of these, 233 images were captured with a green filter, and the remaining 252 were captured without a green filter. Following the application of L2 regularization, L1 regularization, dropout and data augmentation, the accuracy of the validation dataset was ~50%. Although the present study is preliminary, the results indicated that deep learning may be applied to classify colposcopy images.

Endometrial cancer is a ubiquitous gynecological disease with increasing global incidence. Therefore, despite the lack of an established screening technique to date, early diagnosis of endometrial cancer assumes critical importance. This paper presents an artificial-intelligence-based system to detect the regions affected by endometrial cancer automatically from hysteroscopic images. In this study, 177 patients (60 with normal endometrium, 21 with uterine myoma, 60 with endometrial polyp, 15 with atypical endometrial hyperplasia, and 21 with endometrial cancer) with a history of hysteroscopy were recruited. Machine-learning techniques based on three popular deep neural network models were employed, and a continuity-analysis method was developed to enhance the accuracy of cancer diagnosis. Finally, we investigated if the accuracy could be improved by combining all the trained models. The results reveal that the diagnosis accuracy was approximately 80% (78.91–80.93%) when using the standard method, and it increased to 89% (83.94–89.13%) and exceeded 90% (i.e., 90.29%) when employing the proposed continuity analysis and combining the three neural networks, respectively. The corresponding sensitivity and specificity equaled 91.66% and 89.36%, respectively. These findings demonstrate the proposed method to be sufficient to facilitate timely diagnosis of endometrial cancer in the near future.

Background Resveratrol is a natural polyphenolic compound known for its beneficial effects on energy homeostasis, and it also has multiple properties, including anti-oxidant, anti-inflammatory, and anti-tumor activities. Recently, silent information regulator genes (Sirtuins) have been identified as targets of resveratrol. Sirtuin 1 (SIRT1), originally found as an NAD + -dependent histone deacetylase, is a principal modulator of pathways downstream of calorie restriction, and the activation of SIRT1 ameliorates glucose homeostasis and insulin sensitivity. To date, the presence and physiological role of SIRT1 in the ovary are not known. Here we found that SIRT1 was localized in granulosa cells of the human ovary. Methods The physiological roles of resveratrol and SIRT1 in the ovary were analyzed. Immunohistochemistry was performed to localize the SIRT1 expression. SIRT1 protein expression of cultured cells and luteinized human granulosa cells was investigated by Western blot. Rat granulosa cells were obtained from diethylstilbestrol treated rats. The cells were treated with increasing doses of resveratrol, and subsequently harvested to determine mRNA levels and protein levels. Cell viability was tested by MTS assay. Cellular apoptosis was analyzed by caspase 3/7 activity test and Hoechst 33342 staining. Results SIRT1 protein was expressed in the human ovarian tissues and human luteinized granulosa cells. We demonstrated that resveratrol exhibited a potent concentration-dependent inhibition of rat granulosa cells viability. However, resveratrol-induced inhibition of rat granulosa cells viability is independent of apoptosis signal. Resveratrol increased mRNA levels of SIRT1, LH receptor, StAR, and P450 aromatase, while mRNA levels of FSH receptor remained unchanged. Western blot analysis was consistent with the results of quantitative real-time RT-PCR assay. In addition, progesterone secretion was induced by the treatment of resveratrol. Conclusions These results suggest a novel mechanism that resveratrol could enhance progesterone secretion and expression of luteinization-related genes in the ovary, and thus provide important implications to understand the mechanism of luteal phase deficiency.

BackgroundThe albumin-to-globulin ratio reflects both the nutrition and inflammation and predicts prognosis in patients with various malignancies. However, in cervical cancer patients who undergo surgery, its significance has yet to be established.MethodsA total of 247 cervical cancer patients who received surgical treatment at our institution between 2005 and 2017 were enrolled in this study. Preoperative data, such as the levels of serum albumin and serum globulin as well as the albumin-to-globulin ratio along with the other clinicopathological characteristics were retrospectively assessed, and their association with the overall survival was analyzed.ResultsOverall, 49 cases of recurrence and 26 deaths were observed during the median follow-up time of 58.6 months. A low albumin-to-globulin ratio (< 1.345) as well as low albumin (< 3.25 g/dL) and high globulin levels (≥ 3.25 g/dL) were significantly associated with poor prognosis. According to the multivariate analysis, a low albumin-to-globulin ratio was an independent prognostic factor for overall survival (HR = 2.59, 95% CI 1.12–5.96, P = 0.026); however, low albumin or high globulin levels was not associated with the overall survival. Among the clinicopathological characteristics, older age, diabetes mellitus, hypertension, larger tumor size, and parametrial invasion were associated with a low albumin-to-globulin ratio.ConclusionA low albumin-to-globulin ratio was associated with a poor prognosis in patients with surgically treated invasive cervical cancer. Therefore, the albumin-to-globulin ratio may serve as a prognostic marker, which predicts a worse prognosis.

Background Uterine leiomyosarcoma (uLMS) has a poor prognosis owing to its resistance to chemotherapy. Therefore, novel therapeutic targets for uLMS should be identified. Suppressor license of variegation 3–9 homolog 2 (SUV39H2) is a histone methyltransferase that promotes the repair of double-strand DNA breaks by recruiting phosphorylated H2AX (γH2AX). In this study, we investigated the potential therapeutic targets of SUV39H2 in uLMS and the mechanism of synthetic lethality between PARP inhibitors and the SUV39H2 inhibitor OTS186935. Methods First, we analyzed the mRNA and protein expression of SUV39H2 in the clinical tissues of uLMS, normal myometrium, and leiomyomas using real-time polymerase chain reaction and immunohistochemistry, respectively. Next, we conducted drug sensitivity assays for OTS186935 alone and in combination with olaparib, a poly (ADP-ribose) polymerase inhibitor, using the uLMS cell lines SK-LMS-1 and SK-UT-1. We performed western blotting, immunofluorescence, and chromatin immunoprecipitation sequencing (ChIP-seq) to investigate γH2AX following OTS186935 treatment in addition to in vivo experiments using nude mice with subcutaneously implanted uLMS. Results SUV39H2 expression in uLMS was significantly higher than that in the normal myometrium and leiomyomas. OTS186935 decreased the viability of both cell lines, and its combination with olaparib resulted in synthetic lethality in SK-UT-1 cells (combination index = 0.88). After treatment with OTS186935, γH2AX accumulation decreased. ChIP-seq also showed downregulation of γH2AX following OTS186935 treatment. Notably, the combination of OTS186935 and a PARP inhibitor was significantly more effective in vivo. Conclusion OTS186935 inhibited double-strand DNA break repair, as evidenced by γH2AX downregulation by ChIP-seq and other assays. Combining OTS186935 with olaparib demonstrated activity resembling synthetic lethality; however, further validation is required before clinical translation.

Background Age-associated infertility is a problem worldwide, and management of oxidative stress is known to be essential. Nuclear factor-E2-related factor 2 (Nrf2)/Kelch-like ECH-associated protein 1 (Keap1)-antioxidant response element (ARE) signaling pathway works as an essential defense mechanism against oxidative stress, and an oral drug Dimethylfumarate (DMF) is known to activate the pathway. Methods We tested the hypothesis that oral DMF could alleviate oxidative stress in the ovary, resulting in salvation of age-associated infertility in a mouse model of reproductive age, and we examined the effects of DMF administration. 20 mg/kg DMF was administrated to female mice from 32 to 48 weeks, and Nrf2 levels, antioxidant levels, ovarian reserve, DNA damage, and oxidative stress were examined. Results DMF administration resulted in elevated mRNA and protein levels of Nrf2, antioxidants, and telomere, and serum levels of Nrf2 and anti-mullerian hormone were also elevated. Results of TUNEL assay and Immunohistochemistry of mice ovarian tissues showed that DNA damage and oxidative stress were decreased by DMF administration, and significantly more oocytes were collected along with preservation of 60% more primordial follicles. Conclusions Our data suggest that DMF administration activates the Nrf2/Keap1 pathway, elevate levels of antioxidants, and decrease DNA damage and oxidative stress, resulting in improved ovarian reserve in the mouse ovary.

Uterine sarcomas have very poor prognoses and are sometimes difficult to distinguish from uterine leiomyomas on preoperative examinations. Herein, we investigated whether deep neural network (DNN) models can improve the accuracy of preoperative MRI-based diagnosis in patients with uterine sarcomas. Fifteen sequences of MRI for patients (uterine sarcoma group: n = 63; uterine leiomyoma: n = 200) were used to train the models. Six radiologists (three specialists, three practitioners) interpreted the same images for validation. The most important individual sequences for diagnosis were axial T2-weighted imaging (T2WI), sagittal T2WI, and diffusion-weighted imaging. These sequences also represented the most accurate combination (accuracy: 91.3%), achieving diagnostic ability comparable to that of specialists (accuracy: 88.3%) and superior to that of practitioners (accuracy: 80.1%). Moreover, radiologists’ diagnostic accuracy improved when provided with DNN results (specialists: 89.6%; practitioners: 92.3%). Our DNN models are valuable to improve diagnostic accuracy, especially in filling the gap of clinical skills between interpreters. This method can be a universal model for the use of deep learning in the diagnostic imaging of rare tumors.

Treatment of recurrent or advanced cervical cancer is still limited, and new therapeutic choices are needed for improving prognosis and quality of life of patients. Because human papilloma virus (HPV) infection is critical in cervical carcinogenesis, with the E6 and E7 oncogenes of HPV degrading tumor suppressor proteins through the ubiquitin proteasome system, the inhibition of the ubiquitin proteasome system appears to be an ideal target to suppress the growth of cervical tumors. Herein, we focused on the ubiquitin proteasome inhibitor MG132 (carbobenzoxy‐Leu‐Leu‐leucinal) as an anticancer agent against cervical cancer cells, and physically incorporated it into micellar nanomedicines for achieving selective delivery to solid tumors and improving its in vivo efficacy. These MG132‐loaded polymeric micelles (MG132/m) showed strong tumor inhibitory in vivo effect against HPV‐positive tumors from HeLa and CaSki cells, and even in HPV‐negative tumors from C33A cells. Repeated injection of MG132/m showed no significant toxicity to mice under analysis by weight change or histopathology. Moreover, the tumors treated with MG132/m showed higher levels of tumor suppressing proteins, hScrib and p53, as well as apoptotic degree, than tumors treated with free MG132. This enhanced efficacy of MG132/m was attributed to their prolonged circulation in the bloodstream, which allowed their gradual extravasation and penetration within the tumor tissue, as determined by intravital microscopy. These results support the use of MG132 incorporated into polymeric micelles as a safe and effective therapeutic strategy against cervical tumors. We focused on the ubiquitin proteasome inhibitor MG132 as the anticancer agent against cervical cancer cells, and physically incorporated it into micellar nanomedicines for achieving selective delivery to solid tumors and improving its in vivo efficacy. These MG132‐loaded polymeric micelles (MG132/m) showed strong tumor inhibitory in vivo effect against HPV‐positive tumors from HeLa and CaSki cells, and even in HPV‐negative tumors from C33A cells.

Histone modification, a major epigenetic mechanism regulating gene expression through chromatin remodeling, introduces dynamic changes in chromatin architecture. Protein arginine methyltransferase 6 (PRMT6) is overexpressed in various types of cancer, including prostate, lung and endometrial cancer (EC). Epigenome regulates the expression of endogenous retrovirus (ERV), which activates interferon signaling related to cancer. The antitumor effects of PRMT6 inhibition and the role of PRMT6 in EC were investigated, using epigenome multi-omics analysis, including an assay for chromatin immunoprecipitation sequencing (ChIP-seq) and RNA sequencing (RNA-seq). The expression of PRMT6 in EC was analyzed using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC). The prognostic impact of PRMT6 expression was evaluated using IHC. The effects of PRMT6-knockdown (KD) were investigated using cell viability and apoptosis assays, as well as its effects on the epigenome, using ChIP-seq of H3K27ac antibodies and RNA-seq. Finally, the downstream targets identified by multi-omics analysis were evaluated. PRMT6 was overexpressed in EC and associated with a poor prognosis. PRMT6-KD induced histone hypomethylation, while suppressing cell growth and apoptosis. ChIP-seq revealed that PRMT6 regulated genomic regions related to interferons and apoptosis through histone modifications. The RNA-seq data demonstrated altered interferon-related pathways and increased expression of tumor suppressor genes, including NK6 homeobox 1 and phosphoinositide-3-kinase regulatory subunit 1, following PRMT6-KD. RT-qPCR revealed that eight ERV genes which activated interferon signaling were upregulated by PRMT6-KD. The data of the present study suggested that PRMT6 inhibition induced apoptosis through interferon signaling activated by ERV. PRMT6 regulated tumor suppressor genes and may be a novel therapeutic target, to the best of our knowledge, in EC.

Homologous recombination (HR) is a major repair pathway of DNA double-strand breaks and is closely related to carcinogenesis. HR deficiency has been established as a therapeutic target. The aim of this study was to elucidate the functions of a novel HR factor, Mediator complex subunit 1 (MED1), and its association with BRCA1. Formation of the MED1/BRCA1 complex was examined by immunoprecipitation and GST-pull down assays. The transcription cofactor role of BRCA1 was evaluated using luciferase assays. The roles of MED1 on DNA damage response and HR were analyzed by immunofluorescence and HR assays. R-loop accumulation was analyzed using immunofluorescence. R-loop-induced DNA damage was analyzed by comet assays. Immunoprecipitation and GST-pull down assays demonstrated that MED1 is a novel binding partner of BRCA1 and binds to the BRCT domain. Luciferase assays showed that MED1 potentiated the transcription ability of BRCT by two-fold. In MED1-depleted cells, recruitment of HR genes, such as RPA and γH2AX, to DNA damage sites was severely impaired. HR assays showed that MED1 knockdown significantly decreased HR activity. R-loop nuclear accumulation and R-loop-induced comet tails were observed in MED1-depleted cells. We conclude that the transcription factor MED1 contributes to the regulation of the HR pathway and R-loop processing.