Inhibition of protein arginine methyltransferase 6 activates interferon signaling and induces the apoptosis of endometrial cancer cells via histone modification.

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 multi­omics analysis, including an assay for chromatin immunoprecipitation sequencing (ChIP­seq) and RNA sequencing (RNA­seq). The expression of PRMT6 in EC was analyzed using reverse transcription­quantitative polymerase chain reaction (RT­qPCR) and immunohistochemistry (IHC). The prognostic impact of PRMT6 expression was evaluated using IHC. The effects of PRMT6­knockdown (KD) were investigated using cell viability and apoptosis assays, as well as its effects on the epigenome, using ChIP­seq of H3K27ac antibodies and RNA­seq. Finally, the downstream targets identified by multi­omics analysis were evaluated. PRMT6 was overexpressed in EC and associated with a poor prognosis. PRMT6­KD induced histone hypomethylation, while suppressing cell growth and apoptosis. ChIP­seq revealed that PRMT6 regulated genomic regions related to interferons and apoptosis through histone modifications. The RNA­seq data demonstrated altered interferon­related pathways and increased expression of tumor suppressor genes, including NK6 homeobox 1 and phosphoinositide­3­kinase regulatory subunit 1, following PRMT6­KD. RT­qPCR revealed that eight ERV genes which activated interferon signaling were upregulated by PRMT6­KD. 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.

Development of a deep learning method for improving diagnostic accuracy for uterine sarcoma cases.

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.

The Histone Methyltransferase SETD8 Regulates the Expression of Tumor Suppressor Genes via H4K20 Methylation and the p53 Signaling Pathway in Endometrial Cancer Cells.

The histone methyltransferase SET domain-containing protein 8 (SETD8), which methylates histone H4 lysine 20 (H4K20) and non-histone proteins such as p53, plays key roles in human carcinogenesis. Our aim was to determine the involvement of SETD8 in endometrial cancer and its therapeutic potential and identify the downstream genes regulated by SETD8 via H4K20 methylation and the p53 signaling pathway. We examined the expression profile of SETD8 and evaluated whether SETD8 plays a critical role in the proliferation of endometrial cancer cells using small interfering RNAs (siRNAs). We identified the prognostically important genes regulated by SETD8 via H4K20 methylation and p53 signaling using chromatin immunoprecipitation sequencing, RNA sequencing, and machine learning. We confirmed that SETD8 expression was elevated in endometrial cancer tissues. Our in vitro results suggest that the suppression of SETD8 using siRNA or a selective inhibitor attenuated cell proliferation and promoted the apoptosis of endometrial cancer cells. In these cells, SETD8 regulates genes via H4K20 methylation and the p53 signaling pathway. We also identified the prognostically important genes related to apoptosis, such as those encoding KIAA1324 and TP73, in endometrial cancer. SETD8 is an important gene for carcinogenesis and progression of endometrial cancer via H4K20 methylation.

Histone arginine methyltransferase CARM1 selective inhibitor TP-064 induces apoptosis in endometrial cancer.

Histone modification is the key epigenetic mechanism that regulates gene expression. Coactivator-associated arginine methyltransferase 1 (CARM1) is an arginine methyltransferase that catalyzes dimethylation of histone H3 (H3R17) at arginine 17. Lately, it has been suggested that CARM1 is associated with human carcinogenesis, and the CARM1-selective inhibitor, TP-064, has been shown to be a potential therapeutic agent for multiple myeloma. However, the physiological significance of CARM1 in endometrial cancer remains unclear. Therefore, we aimed to explore the role of CARM1 and the effect of TP-064 in endometrial cancer. To this end, we analyzed CARM1 expression in endometrial cancer using quantitative real-time polymerase chain reaction and examined the antitumor mechanism with CARM1 knockdown endometrial cancer cells. Moreover, we evaluated the therapeutic capability of TP-064 in endometrial cancer cells. CARM1 was remarkably overexpressed in 52 endometrial cancer tissues compared to normal endometrial tissues. The growth of CARM1 knockdown endometrial cancer cells was suppressed and CARM1 knockdown induced apoptosis. TP-064 also inhibited endometrial cancer cell growth and declined the number of endometrial cancer cell colonies. These data suggest that CARM1 may be a powerful therapeutic target for endometrial cancer.

A case of difficult-to-diagnose non-invasive papillary squamous cell carcinoma of the uterine cervix infected with human papilloma virus 6: A diagnostic pitfall.

We encountered HPV6-positive cervical papillary squamous cancer (PSCC) that was difficult to diagnose. The case was initially diagnosed and treated for condyloma. To the best of our knowledge, this is the first report of HPV6 infection in PSCC.

Targeting Epigenetic Regulators for Endometrial Cancer Therapy: Its Molecular Biology and Potential Clinical Applications.

Endometrial cancer is one of the most frequently diagnosed gynecological malignancies worldwide. However, its prognosis in advanced stages is poor, and there are only few available treatment options when it recurs. Epigenetic changes in gene function, such as DNA methylation, histone modification, and non-coding RNA, have been studied for the last two decades. Epigenetic dysregulation is often reported in the development and progression of various cancers. Recently, epigenetic changes in endometrial cancer have also been discussed. In this review, we give the main points of the role of DNA methylation and histone modification in endometrial cancer, the diagnostic tools to determine these modifications, and inhibitors targeting epigenetic regulators that are currently in preclinical studies and clinical trials.

Automated system for diagnosing endometrial cancer by adopting deep-learning technology in hysteroscopy.

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.

Epigenetic Modifier SETD8 as a Therapeutic Target for High-Grade Serous Ovarian Cancer.

The histone methyltransferase SETD8, which methylates the lysine 20 of histone H4 (H4K20), is reportedly involved in human carcinogenesis along with nonhistone proteins such as p53. However, its expression profiles and functions in the context of high-grade serous ovarian carcinoma (HGSOC) are still unknown. The purpose of this study was to investigate the role of SETD8 in HGSOC. We performed quantitative real-time PCR and immunohistochemistry to detect the expression of SETD8 in HGSOC samples and normal ovarian specimens. Then, we assessed the effect of the inhibition of SETD8 expression using small interfering RNA (siRNA) and a selective inhibitor (UNC0379) on cell proliferation and apoptosis in HGSOC cells. The expression of SETD8 was significantly upregulated in clinical ovarian cancer specimens compared to that in the corresponding normal ovary. In addition, suppression of SETD8 expression in HGSOC cells with either siRNA or UNC0379 resulted in reduced levels of H4K20 monomethylation, inhibition of cell proliferation, and induction of apoptosis. Furthermore, UNC0379 showed a long-term antitumor effect against HGSOC cells, as demonstrated by colony-formation assays. SETD8 thus constitutes a promising therapeutic target for HGSOC, warranting further functional studies.

Usefulness of biopsy by office hysteroscopy for endometrial cancer: A case report.

A diagnostic biopsy for endometrial cancer is performed via dilation and curettage (D&C). However, D&C may miss endometrial cancer lesions due to of its 'blind' approach. Hysteroscopy is a useful method that can be used to detect endometrial cancer lesions. In addition, office hysteroscopy is easy to be scheduled and does not require anesthesia. The patient was a 40-year-old woman with suspected endometrial cancer; however, it could not be diagnosed by D&C and biopsy using hysteroscopy during hospitalization. Office hysteroscopy during the proliferative phase indicated that the suspicious endometrial cancerous lesion was minimal at the isthmus of the uterus with atypical vessels and a white spot, for which biopsy was performed. Pathological diagnosis was endometrioid carcinoma with squamous differentiation, G1. Therefore, total laparoscopic hysterectomy, bilateral salpingo-oophorectomy and pelvic lymphadenectomy were performed. In this case, it was difficult to detect minimal lesion in the secretory phase because the endometrial thickness hid the endometrial cancer. It is easy to perform office hysteroscopy in the proliferative phase. This case indicated that office hysteroscopy is a useful method to diagnose and perform biopsy for minimal lesions.