Patients with endometrioid endometrial cancer are stratified as high risk and low risk for extrauterine disease by surgical staging. Since patients with low-grade, minimally invasive disease do not benefit from comprehensive staging, pre-surgery stratification into a risk category may prevent unnecessary surgical staging in low risk patients. Our objective was to develop a predictive model to identify risk levels using somatic mutations that could be used preoperatively.

Cancer-testis (CT) antigens are a large family of genes that are selectively expressed in human testis germ cells, overexpressed in a variety of tumors and predominantly located on the X chromosome. To date, all known CT antigens are protein-coding genes. Here, we identify miR-888 as the first miRNA with features characteristic of a CT antigen. In a panel of 21 normal human tissues, miR-888 expression was high in testes and minimal or absent in all other examined tissues. In situ hybridization localized miR-888 expression specifically to the early stages of sperm development within the testes. Using The Cancer Genome Atlas database, we discovered that miR-888 was predominately expressed in endometrial tumors, with a significant association to high-grade tumors and increased percent invasion. In a separate panel of endometrial tumor specimens, we validated overexpression of miR-888 by real-time polymerase chain reaction. In addition, miR-888 expression was highest in endometrial carcinosarcoma, a rare and aggressive type of endometrial tumor. Moreover, we identified the progesterone receptor (PR), a potent endometrial tumor suppressor, as a direct target of miR-888. These data define miR-888 as the first miRNA CT antigen and a potential mediator of an aggressive endometrial tumor phenotype through down-regulation of PR.

Mutations in the tumor suppressor TP53 occur in almost all advanced ovarian cancers and in many advanced serous endometrial cancers. Mutations in TP53 can alter the function of the p53 protein, and some mutations result in a mutated protein with oncogenic activity. Previously referred to as gain of function (GOF) p53 proteins, we now term these "oncomorphic" mutations to better describe their function as oncogenes. We reviewed the data from The Cancer Genome Atlas (TCGA) and demonstrate that of the patients diagnosed with endometrial cancer that harbor TP53 mutations, approximately 30% of these mutations are oncomorphic. In ovarian cancer, approximately 20% are oncomorphic. The wild type (WT) p53 protein transactivates genes and micro- RNAs (miRNAs) necessary in the response to cellular stress, which turn off growth and induce apoptosis. In addition to direct transcriptional activation, WT p53 also acts through protein:protein interactions with Drosha and the miRNA processing complex to mediate rapid, enhanced processing of a subset of anti-growth miRNAs. We validated the interaction of WT p53 with the Drosha complex in the cell line UCI-107. We observed that miRNAs that inhibit the expression of oncogenes were induced. Specifically, some miRNAs were induced very rapidly over minutes, consistent with enhanced processing, while others required hours, consistent with transcriptional activation. In contrast, the most common oncomorphic TP53 mutations failed to interact with the Drosha complex and lost the ability to rapidly induce the miRNAs which inhibit oncogene expression. These studies highlight one mechanism underlying the oncomorphic properties of specific TP53 mutations: loss of the enhanced processing of anti-proliferative miRNAs.

The utility of comprehensive surgical staging in patients with low risk disease has been questioned. Thus, a reliable means of determining risk would be quite useful. The aim of our study was to create the best performing prediction model to classify endometrioid endometrial cancer (EEC) patients into low or high risk using a combination of molecular and clinical-pathological variables. We then validated these models with publicly available datasets. Analyses between low and high risk EEC were performed using clinical and pathological data, gene and miRNA expression data, gene copy number variation and somatic mutation data. Variables were selected to be included in the prediction model of risk using cross-validation analysis; prediction models were then constructed using these variables. Model performance was assessed by area under the curve (AUC). Prediction models were validated using appropriate datasets in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A prediction model with only clinical variables performed at 88%. Integrating clinical and molecular data improved prediction performance up to 97%. The best prediction models included clinical, miRNA expression and/or somatic mutation data, and stratified pre-operative risk in EEC patients. Integrating molecular and clinical data improved the performance of prediction models to over 95%, resulting in potentially useful clinical tests.

Nearly one-third of patients with high-grade serous ovarian cancer (HGSC) do not respond to initial treatment with platinum-based therapy. Genomic and clinical characterization of these patients may lead to potential alternative therapies. Here, the objective is to classify non-responders into subsets using clinical and molecular features. Using patients from The Cancer Genome Atlas (TCGA) dataset with platinum-resistant or platinum-refractory HGSC, we performed a genome-wide unsupervised cluster analysis that integrated clinical data, gene copy number variations, gene somatic mutations, and DNA promoter methylation. Pathway enrichment analysis was performed for each cluster to identify the targetable processes. Following the unsupervised cluster analysis, three distinct clusters of non-responders emerged. Cluster 1 had overrepresentation of the stage IV disease and suboptimal debulking, under-expression of miRNAs and mRNAs, hypomethylated DNA, "loss of function" TP53 mutations, and the overexpression of genes in the PDGFR pathway. Cluster 2 had low miRNA expression, generalized hypermethylation, MUC17 mutations, and significant activation of the HIF-1 signaling pathway. Cluster 3 had more optimally cytoreduced stage III patients, overexpression of miRNAs, mixed methylation patterns, and "gain of function" TP53 mutations. However, the survival for all clusters was similar. Integration of genomic and clinical data from patients that do not respond to chemotherapy has identified different subgroups or clusters. Pathway analysis further identified the potential alternative therapeutic targets for each cluster.

The disruption of estrogen signaling is widely associated with the development of breast, endometrial and ovarian cancers. As a multifunctional mediator of carcinogenesis, metadherin (MTDH)/astrocyte elevated gene-1 (AEG-1) overexpression has been associated with numerous types of cancer, with reported roles in tumor initiation, proliferation, invasion, metastasis and chemoresistance. At the molecular level, MTDH has been shown to interact with proteins that drive tumorigenesis, including nuclear factor-κB (NF-κB), promyelocytic leukaemia zinc finger (PLZF), BRCA2- and CDKN1A (p21Cip1/Waf-1/mda-6)-interacting protein α (BCCIPα) and staphylococcal nuclease and tudor domain containing 1 (SND1). Through the analysis of the Cancer Genome Atlas (TCGA) datasets for estrogen receptor (ER)-positive endometrial and breast cancers, we found that over 25% of all gene expression correlated with MTDH. Using Affymetrix microarrays, we characterized the differences in gene expression between estrogen-treated parental and MTDH-deficient endometrial and breast cancer cells. We also explored a possible interaction between MTDH and ER by immunoprecipitation, and found that MTDH and ER associated in both breast and endometrial cancer cells in response to estrogen. Reciprocal co-immunoprecipitation analysis demonstrated that acute estrogen stimulation promoted the interaction of MTDH with ER in the nucleus. These data, to the best of our knowledge, provide the first evidence that MTDH and ERα interact in the nucleus with estrogen treatment to regulate gene expression.

Most endometrial cancers express the hormone receptor estrogen receptor alpha (ER) and are driven by excess estrogen signaling. However, evaluation of the estrogen response in endometrial cancer cells has been limited by the availability of hormonally responsive in vitro models, with one cell line, Ishikawa, being used in most studies. Here, we describe a novel, adherent endometrioid endometrial cancer (EEC) cell line model, HCI-EC-23. We show that HCI-EC-23 retains ER expression and that ER functionally responds to estrogen induction over a range of passages. We also demonstrate that this cell line retains paradoxical activation of ER by tamoxifen, which is also observed in Ishikawa and is consistent with clinical data. The mutational landscape shows that HCI-EC-23 is mutated at many of the commonly altered genes in EEC, has relatively few copy-number alterations, and is microsatellite instable high (MSI-high). In vitro proliferation of HCI-EC-23 is strongly reduced upon combination estrogen and progesterone treatment. HCI-EC-23 exhibits strong estrogen dependence for tumor growth in vivo and tumor size is reduced by combination estrogen and progesterone treatment. Molecular characterization of estrogen induction in HCI-EC-23 revealed hundreds of estrogen-responsive genes that significantly overlapped with those regulated in Ishikawa. Analysis of ER genome binding identified similar patterns in HCI-EC-23 and Ishikawa, although ER exhibited more bound sites in Ishikawa. This study demonstrates that HCI-EC-23 is an estrogen- and progesterone-responsive cell line model that can be used to study the hormonal aspects of endometrial cancer.

Mutations in the TP53 tumor suppressor gene are common in ovarian carcinoma (OC) but their impact on outcomes is controversial. We sought to define the relationship of TP53 mutations to cancer outcomes and their interactions with co-occurrent BRCA1 or BRCA2 (BRCA) mutations, comparing three different TP53 mutation classification schemes.

Placenta-specific protein 1 (PLAC1) is a small secreted protein expressed exclusively in trophoblast cells in the mammalian placenta. PLAC1 is expressed early in gestation and is maintained throughout. It is thought to function in trophoblast invasion of the uterine epithelium and, subsequently, to anchor the placenta to the epithelium. In recent years, evidence has accumulated that PLAC1 is also expressed in a variety of human solid tumors, notably in breast cancers. We demonstrate for the first time that PLAC1 is ubiquitously expressed in tumors originating in uterine epithelium. Further, we find that PLAC1 expression is significantly higher in the more advanced, more aggressive endometrial serous adenocarcinomas and carcinosarcomas relative to endometrioid adenocarcinomas by more than 6-fold and 16-fold, respectively. We also show that PLAC1 is simultaneously transcribed from two promoters but that, in all cases, the more distal P1 promoter dominates the more proximal P2 promoter. While the function of the two PLAC1 promoters and their regulation are as yet unknown, overall expression data suggest that PLAC1 may serve as a biomarker for endometrial cancer as well as a potential prognostic indicator.

Endometrial cancer can be diagnosed early and cured, yet cases that recur portend a very poor prognosis with over 10,000 women succumbing to the disease every year. In this study we addressed the question of how to recognize cases likely to recur early in the course of therapy using dysregulation of tumor microRNAs (miRNAs) as predictors.

Histone deacetylase (HDAC) inhibitors and proteasome inhibitors have been approved by the FDA for the treatment of multiple myeloma and lymphoma, respectively, but have not achieved similar activity as single agents in solid tumors. Preclinical studies have demonstrated the activity of the combination of an HDAC inhibitor and a proteasome inhibitor in a variety of tumor models. However, the mechanisms underlying sensitivity and resistance to this combination are not well-understood. This study explores the role of autophagy in adaptive resistance to dual HDAC and proteasome inhibition. Studies focus on ovarian and endometrial gynecologic cancers, two diseases with high mortality and a need for novel treatment approaches. We found that nanomolar concentrations of the proteasome inhibitor ixazomib and HDAC inhibitor romidepsin synergistically induce cell death in the majority of gynecologic cancer cells and patient-derived organoid (PDO) models created using endometrial and ovarian patient tumor tissue. However, some models were not sensitive to this combination, and mechanistic studies implicated autophagy as the main mediator of cell survival in the context of dual HDAC and proteasome inhibition. Whereas the combination of ixazomib and romidepsin reduces autophagy in sensitive gynecologic cancer models, autophagy is induced following drug treatment of resistant cells. Pharmacologic or genetic inhibition of autophagy in resistant cells reverses drug resistance as evidenced by an enhanced anti-tumor response both in vitro and in vivo. Taken together, our findings demonstrate a role for autophagic-mediated cell survival in proteasome inhibitor and HDAC inhibitor-resistant gynecologic cancer cells. These data reveal a new approach to overcome drug resistance by inhibiting the autophagy pathway.

Elevated expression of placenta-specific protein 1 (PLAC1) is associated with the increased proliferation and invasiveness of a variety of human cancers, including ovarian cancer. Recent studies have shown that the tumor suppressor p53 directly suppresses PLAC1 transcription. However, mutations in p53 lead to the loss of PLAC1 transcriptional suppression. Small molecules that structurally convert mutant p53 proteins to wild-type conformations are emerging. Our objective was to determine whether the restoration of the wild-type function of mutated p53 could rescue PLAC1 transcriptional suppression in tumors harboring certain TP53 mutations. Ovarian cancer cells OVCAR3 and ES-2, both harboring TP53 missense mutations, were treated with the p53 reactivator HO-3867. Treatment with HO-3867 successfully rescued PLAC1 transcriptional suppression. In addition, cell proliferation was inhibited and cell death through apoptosis was increased in both cell lines. We conclude that the use of HO-3867 as an adjuvant to conventional therapeutics in ovarian cancers harboring TP53 missense mutations could improve patient outcomes. Validation of this conclusion must, however, come from an appropriately designed clinical trial.

Ferroptosis is an iron-dependent, non-apoptotic form of regulated cell death driven by lipid hydroperoxides within biological membranes. Although therapy-resistant mesenchymal-high cancers are particularly vulnerable to ferroptosis inducers, especially phospholipid glutathione peroxidase 4 (GPx4) inhibitors, the underlying mechanism is yet to be deciphered. As such, the full application of GPx4 inhibitors in cancer therapy remains challenging. Here we demonstrate that metadherin (MTDH) confers a therapy-resistant mesenchymal-high cell state and enhanced sensitivity to inducers of ferroptosis. Mechanistically, MTDH inhibited GPx4, as well as the solute carrier family 3 member 2 (SLC3A2, a system Xc- heterodimerization partner), at both the messenger RNA and protein levels. Our metabolomic studies demonstrated that MTDH reduced intracellular cysteine, but increased glutamate levels, ultimately decreasing levels of glutathione and setting the stage for increased vulnerability to ferroptosis. Finally, we observed an enhanced antitumor effect when we combined various ferroptosis inducers both in vitro and in vivo; the level of MTDH correlated with the ferroptotic effect. We have demonstrated for the first time that MTDH enhances the vulnerability of cancer cells to ferroptosis and may serve as a therapeutic biomarker for future ferroptosis-centered cancer therapy.

The miR-503 miRNA cluster, located at Xq23.1, is composed of six miRNAs; miR-424, miR-503, miR-542, miR-450a-1, miR-450a-2 and miR-450b. Numerous studies have focused on the relationship of one or two members of the cluster and various human cancers. Here, we suggest that the entire cluster as a single coordinately expressed polycistron transcribed from a single promoter in endometrial endometrioid adenocarcinoma (EEA).

Progesterone, acting through its receptor, PR (progesterone receptor), is the natural inhibitor of uterine endometrial carcinogenesis by inducing differentiation. PR is downregulated in more advanced cases of endometrial cancer, thereby limiting the effectiveness of hormonal therapy. Our objective was to understand and reverse the mechanisms underlying loss of PR expression in order to improve therapeutic outcomes. Using endometrial cancer cell lines and data from The Cancer Genome Atlas, our findings demonstrate that PR expression is downregulated at four distinct levels. In well-differentiated cancers, ligand-induced receptor activation and downregulation are intact. miRNAs mediate fine tuning of PR levels. As differentiation is lost, PR silencing is primarily at the epigenetic level. Initially, recruitment of the polycomb repressor complex 2 to the PR promoter suppresses transcription. Subsequently, DNA methylation prevents PR expression. Appropriate epigenetic modulators reverse these mechanisms. These data provide a rationale for combining epigenetic modulators with progestins as a therapeutic strategy for endometrial cancer.

Endometrial cancer, the most common gynecologic malignancy, is a hormonally-regulated disease. Response to progestin therapy positively correlates with hormone receptor expression, in particular progesterone receptor (PR). However, many advanced tumors lose PR expression. We recently reported that the efficacy of progestin therapy can be significantly enhanced by combining progestin with epigenetic modulators, which we term "molecularly enhanced progestin therapy." What remained unclear was the mechanism of action and if estrogen receptor α (ERα), the principle inducer of PR, is necessary to restore functional expression of PR via molecularly enhanced progestin therapy. Therefore, we modeled advanced endometrial tumors that have lost both ERα and PR expression by generating ERα-null endometrial cancer cell lines. CRISPR-Cas9 technology was used to delete ERα at the genomic level. Our data demonstrate that treatment with a histone deacetylase inhibitor (HDACi) was sufficient to restore functional PR expression, even in cells devoid of ERα. Our studies also revealed that HDACi treatment results in marked downregulation of the oncogene Myc. We established that PR is a negative transcriptional regulator of Myc in endometrial cancer in the presence or absence of ERα, which is in contrast to studies in breast cancer cells. First, estrogen stimulation augmented PR expression and decreased Myc in endometrial cancer cell lines. Second, progesterone increased PR activity yet blunted Myc mRNA and protein expression. Finally, overexpression of PR by adenoviral transduction in ERα-null endometrial cancer cells significantly decreased expression of Myc and Myc-regulated genes. Analysis of the Cancer Genome Atlas (TCGA) database of endometrial tumors identified an inverse correlation between PR and Myc mRNA levels, with a corresponding inverse correlation between PR and Myc downstream transcriptional targets SRD5A1, CDK2 and CCNB1. Together, these data reveal a previously unanticipated inverse relationship between the tumor suppressor PR and the oncogene Myc in endometrial cancer.

Objectives: Endometrial cancer incidence and mortality are rising in the US. Disease recurrence has been shown to have a significant impact on mortality. However, to date, there are no accurate and validated prediction models that would discriminate which individual patients are likely to recur. Reliably predicting recurrence would be of benefit for treatment decisions following surgery. We present an integrated model constructed with comprehensive clinical, pathological and molecular features designed to discriminate risk of recurrence for patients with endometrioid endometrial adenocarcinoma. Subjects and methods: A cohort of endometrioid endometrial cancer patients treated at our institution was assembled. Clinical characteristics were extracted from patient charts. Primary tumors from these patients were obtained and total tissue RNA extracted for RNA sequencing. A prediction model was designed containing both clinical characteristics and molecular profiling of the tumors. The same analysis was carried out with data derived from The Cancer Genome Atlas for replication and external validation. Results: Prediction models derived from our institutional data predicted recurrence with high accuracy as evidenced by areas under the curve approaching 1. Similar trends were observed in the analysis of TCGA data. Further, a scoring system for risk of recurrence was devised that showed specificities as high as 81% and negative predictive value as high as 90%. Lastly, we identify specific molecular characteristics of patient tumors that may contribute to the process of disease recurrence. Conclusion: By constructing a comprehensive model, we are able to reliably predict recurrence in endometrioid endometrial cancer. We devised a clinically useful scoring system and thresholds to discriminate risk of recurrence. Finally, the data presented here open a window to understanding the mechanisms of recurrence in endometrial cancer.

The epigenome offers an additional facet of cancer that can help categorize patients into those at risk of disease, recurrence, or treatment failure. We conducted a retrospective, nested, case-control study of advanced and recurrent high-grade serous ovarian cancer (HGSOC) patients in which we assessed epigenome-wide association using Illumina methylationEPIC arrays to characterize DNA methylation status and RNAseq to evaluate gene expression. Comparing HGSOC tumors with normal fallopian tube tissues we observe global hypomethylation but with skewing towards hypermethylation when interrogating gene promoters. In total, 5,852 gene interrogating probes revealed significantly different methylation. Within HGSOC, 57 probes highlighting 17 genes displayed significant differential DNA methylation between primary and recurrent disease. Between optimal vs suboptimal surgical outcomes 99 probes displayed significantly different methylation but only 29 genes showed an inverse correlation between methylation status and gene expression. Overall, differentially methylated genes point to several pathways including RAS as well as hippo signaling in normal vs primary HGSOC; valine, leucine, and isoleucine degradation and endocytosis in primary vs recurrent HGSOC; and pathways containing immune driver genes in optimal vs suboptimal surgical outcomes. Thus, differential DNA methylation identified numerous genes that could serve as potential biomarkers and/or therapeutic targets in HGSOC.

Endometrial cancer (EC) incidence and mortality continues to rise. Molecular profiling of EC promises improvement of risk assessment and treatment selection. However, we still lack robust and accurate models to predict those at risk of failing treatment. The objective of this pilot study is to create models with clinical and genomic data that will discriminate patients with EC at risk of disease recurrence. We performed a pilot, retrospective, case−control study evaluating patients with EC, endometrioid type: 7 with recurrence of disease (cases), and 55 without (controls). RNA was extracted from frozen specimens and sequenced (RNAseq). Genomic features from RNAseq included transcriptome expression, genomic, and structural variation. Feature selection for variable reduction was performed with univariate ANOVA with cross-validation. Selected variables, informative for EC recurrence, were introduced in multivariate lasso regression models. Validation of models was performed in machine-learning platforms (ML) and independent datasets (TCGA). The best performing prediction models (out of >170) contained the same lncRNA features (AUC of 0.9, and 95% CI: 0.75, 1.0). Models were validated with excellent performance in ML platforms and good performance in an independent dataset. Prediction models of EC recurrence containing lncRNA features have better performance than models with clinical data alone.

Platinum compounds have been widely used as a primary treatment for many types of cancer. However, resistance is the major cause of therapeutic failure for patients with metastatic or recurrent disease, thus highlighting the need to identify novel factors driving resistance to Platinum compounds. Metadherin (MTDH, also known as AEG-1 and LYRIC), located in a frequently amplified region of chromosome 8, has been consistently associated with resistance to chemotherapeutic agents, though the precise mechanisms remain incompletely defined.