Objective: Obesity is a major risk factor for endometrial cancer. In addition to hormone therapy with progestins, glucagon like peptide-1 receptor (GLP-1R) agonists such as semaglutide may be helpful to achieve weight loss during conservative treatment of endometrial hyperplasia or cancer. Methods: We theorized that the combination of semaglutide and the progestin levonorgestrel would be useful as a novel treatment or prevention regimen and tested this hypothesis using endometrial cancer cell lines and patient-derived organoids (PDOs). Results: Hec50, KLE, and Ishikawa endometrial cancer cells express GLP-1R, as determined by both qPCR and Western blotting, and GLP-1R agonist treatment induces GLP-1R mRNA transcription through positive feedback mechanisms in cell models. PDOs from six individuals with grade 1 endometrial carcinomas were treated with progesterone, levonorgestrel, semaglutide, or levonorgestrel + semaglutide. Multiple models demonstrated a significant reduction in viability in response to combinatorial treatment, and the effect was noted in models from both PR high- and PR low-expressing tumors. Most interesting was the induction not only of the membrane GLP-1R with treatment, but also the significant upregulation of nuclear and membrane progesterone receptors—PR and PGRMC1/2, respectively—indicating a potential positive feedback loop between semaglutide and progestins such as levonorgestrel. Conclusion: In summary, we identify synergistic molecular cross-talk between the GLP-1R and steroid hormone receptor pathways, with the potential to enhance the anticancer activity of levonorgestrel when combined with semaglutide.

Ovarian and endometrial cancers frequently harbor a mutation in the tumor suppressor gene TP53, which occurs in over 90 % of ovarian cancers and in the most aggressive endometrial cancers. The normal tumor suppressive functions of p53 are disrupted, resulting in unregulated cell growth and therapeutic resistance to standard treatments including chemotherapy and PARP inhibitors. Hence, a novel therapeutic strategy is urgently needed for p53 mutant gynecologic cancers, and we propose that converting mutant p53 to a wild type conformation and restoring its tumor suppressive functions has the potential to greatly improve treatment. In this study, we investigated the effects of two purported p53 reactivators, HO-3867 and APR-246, on cell proliferation via half-maximal inhibitory concentration (IC50) analyses using CyQUANT DNA measurements, tumor growth in vivo and gene expression by bulk RNA sequencing in gynecologic cancer cell lines that harbor oncogenic mutations in p53. We also tested these compounds in combination with the PARP inhibitor olaparib. We found that HO-3867 was very effective in inhibiting growth, with IC50 values in the low micromolar range. Importantly, HO-3867 was synergistic with olaparib treatment in five cell lines studied in vitro as well as in vivo in a xenograft model of high grade serous ovarian cancer. RNA sequencing data suggest that HO-3867 is acting through both p53-independent and p53-dependent pathways resulting in inhibition of DNA repair pathways including homologous recombination in p53 mutant cancer cells. Significance: The development of resistance to PARP inhibitors is a major problem and a cause of treatment failures in advanced gynecologic cancers, and we show that adding a p53 reactivator such as HO-3867 enhances the efficacy of PARP inhibitors in p53-mutant cancer models.

High-grade serous ovarian cancer (HGSC) is a heterogeneous disease. RNA sequencing (RNAseq) of bulk solid tissue is of limited use in these populations due to heterogeneity. Single-cell RNA-seq (scRNA-seq) allows for the identification of diverse genetic compositions of heterogeneous cell populations. New computational methodologies are now available that use scRNAseq results to estimate cell type proportions in bulk RNAseq data. We performed bulk RNA-seq gene expression analysis on 112 HGSC specimens and 12 benign fallopian tube (FT) controls. We identified several publicly available scRNAseq datasets for use as annotation and reference datasets. Deconvolution was performed with MUlti-Subject SIngle Cell Deconvolution (MuSiC) to estimate cell type proportions in the bulk RNA-seq data. Datasets from the Cancer Genome Atlas (TCGA). HGSC repositories were also evaluated. Clinical variables and percentages of cell types were compared for differences in clinical outcomes and treatment results. Pathway enrichment analysis was also performed. Different annotations for referenced scRNA-seq datasets used for deconvolution of bulk RNA-seq data revealed different cellular proportions that were significantly associated with clinical outcomes; for example, higher proportions of macrophages were associated with a better response to primary chemotherapy. Our deconvolution study of bulk RNAseq HGSC samples identified cell populations within the tumor that may be associated with some of the observed clinical outcomes.

Endometrial cancer is the most common gynecological malignancy worldwide and unfortunately has a much higher mortality rate in Black women compared with White women. Many potential factors contribute to these mortality rates, including the underlying effects of systemic and interpersonal racism. Furthermore, other trends in medicine have potential links to these rates including participation in clinical trials, hormone therapy, and pre-existing health conditions. Addressing the high incidence and disparate mortality rates in endometrial cancer requires novel methods, such as nanoparticle-based therapeutics. These therapeutics have been growing in increasing prevalence in pre-clinical development and have far-reaching implications in cancer therapy. The rigor of pre-clinical studies is enhanced by the likeness of the model to the human body. In systems for 3D cell culture, for example, the extracellular matrix mimics the tumor more closely. The increasing emphasis on precision medicine can be applied to cancer using nanoparticle-based methods and applied to pre-clinical models by using patient-derived model data. This review highlights the intersections of nanomedicine, precision medicine, and racial disparities within endometrial cancer and provides insights into reducing health disparities using recent scientific advances on the nanoscale.

Abstract Obesity is a major risk factor for endometrial cancer (EC), and glucagon like peptide-1 receptor (GLP-1R) agonists such as semaglutide may be helpful to achieve weight loss during conservative treatment or for EC prevention. Progestins such as levonorgestrel are effective in preventing or treating early-stage EC. However, better and more durable response rates could be achieved using combinatorial therapeutic regimens of well tolerated agents with the potential to enhance progestin effectiveness. We theorized that the combination of semaglutide and levonorgestrel would be useful as a novel treatment or prevention regimen and tested this hypothesis using EC cell lines, patient-derived organoids, and RNA-sequencing from patient samples. From the molecular perspective, EC cell lines, organoids, and tissues express GLP-1R as determined by both qPCR and Western blotting, and GLP-1R agonist treatment induces GLP-1R mRNA transcription through positive feedback mechanisms in EC cell models. Preclinical studies in 6 patient-derived organoid models of EC demonstrated the promising therapeutic effects of the combination of semaglutide and levonorgestrel on endometrial cell viability. Specifically, patient-derived organoids from grade 1 endometrial carcinomas were treated with progesterone, levonorgestrel, semaglutide, or levonorgestrel + semaglutide at drug concentrations of 100 nM for 72 hours. Multiple models demonstrated a significant reduction in viability in response to combinatorial treatment. Most interesting was the induction of not only the membrane GLP-1 receptor with treatment, but also the significant upregulation of nuclear and membrane progesterone receptors, PR and PGRMC1/2, respectively, indicating a positive feedback loop between semaglutide and progestins such as levonorgestrel. In addition, other steroid hormone receptor mRNAs such as the estrogen, androgen and mineralocorticoid receptors (ER, AR, and MR) were similarly upregulated. In these studies, we identify synergistic molecular crosstalk between the GLP-1R and steroid hormone receptor pathways with the potential to enhance the anti-cancer activity of semaglutide and levonorgestrel when combined. Future studies are aimed at testing this regimen in patients conservatively managed for atypical endometrial hyperplasia or low-grade endometrial cancers. Citation Format: Kimberly K. Leslie, Andrea Hagemann, Kristina Thiel, Ian Hagemann, David Mutch, Eric Devor, Paige Malmrose. The combination of the glucagon like peptide-1 receptor agonist semaglutide and the progestin levonorgestrel is highly effective in preclinical studies of endometrial cancer [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr PR003.

Psychiatric and obstetric diseases are growing threats to public health and share high rates of co-morbidity. G protein-coupled receptor signaling (e.g., vasopressin, serotonin) may be a convergent psycho-obstetric risk mechanism. Regulator of G Protein Signaling 2 (RGS2) mutations increase risk for both the gestational disease preeclampsia and for depression. We previously found preeclampsia-like, anti-angiogenic obstetric phenotypes with reduced placental Rgs2 expression in mice. Here, we extend this to test whether conserved cerebrovascular and serotonergic mechanisms are also associated with risk for neurobiological phenotypes in the Rgs2 KO mouse. Rgs2 KO exhibited anxiety-, depression-, and hedonic-like behaviors. Cortical vascular density and vessel length decreased in Rgs2 KO; cortical and white matter thickness and cell densities were unchanged. In Rgs2 KO, serotonergic gene expression was sex-specifically changed (e.g., cortical Htr2a, Maoa increased in females but all serotonin targets unchanged or decreased in males); redox-related expression increased in paraventricular nucleus and aorta; and angiogenic gene expression was changed in male but not female cortex. Whole-cell recordings from dorsal raphe serotonin neurons revealed altered 5-HT1A receptor-dependent inhibitory postsynaptic currents (5-HT1A-IPSCs) in female but not male KO neurons. Additionally, serotonin transporter blockade by the SSRI sertraline increased the amplitude and time-to-peak of 5-HT1A-IPSCs in KO neurons to a greater extent than in WT neurons in females only. These results demonstrate behavioral, cerebrovascular, and sertraline hypersensitivity phenotypes in Rgs2 KOs, some of which are sex-specific. Disruptions may be driven by vascular and cell stress mechanisms linking the shared pathogenesis of psychiatric and obstetric disease to reveal future targets.

Abstract Serous endometrial and ovarian cancers represent significant morbidity and mortality for gynecologic cancers due to the high rate of resistance to chemotherapy and recurrence after treatment. Among the many reasons for poor outcomes is a lack of preclinical models that reflect the complex heterogeneity across patients. Our objective was to create patient-derived organoid (PDO) models of serous endometrial and ovarian cancer and examine how genomic profiles evolve in response to standard therapy. This study was performed in four PDO models of serous gynecologic cancer, including serous endometrial, high grade and low grade serous ovarian, and high grade serous fallopian tube. We first compared genomic alterations in the primary tumors and PDOs using a 484-gene NGS panel (NovoPM 2.0, Novogene). A large overlap in single nucleotide variants (SNVs), copy number variations (CNVs) and indels was observed between primary tumor tissue and the corresponding PDO model. For example, there was an average of 175 shared SNVs between each primary tumor and PDO model and <20 unique variants in the PDO that were not present in primary tumor specimen. For the patient with serous fallopian tube cancer, we were further able to generate PDO models from tumor tissue acquired from three different sites: ovary, omentum, and ascites fluid. We found that 217 SNVs were shared among the PDOs from the three sites, with only 2-11 variants unique to each location. Interestingly, eight unique CNVs were detected in the ovary and ascites PDOs but not in the metastatic (omentum) PDO. We next exposed each PDO to a short 3-day pulse of carboplatin+paclitaxel to create chemoexposed models. The rationale for this duration of exposure is that clinical response in patients has been shown to correlate with drug response at 72 hrs in PDO models of ovarian cancer. As expected, all chemoexposed PDOs were more resistant to chemotherapy as compared to treatment-naïve counterparts. Genomic analysis of the treatment-naïve vs. chemoexposed PDOs revealed acquisition of new variants, such as a p53 mutation in the serous endometrial model after the pulse of chemotherapy. Finally, we compared drug sensitivity of the treatment-naïve vs. chemoexposed PDOs to agents used in the adjuvant and recurrent settings. The chemoexposed models yielded different drug profiles, with some showing increased sensitivity and others increased resistance. Taken together, these data substantiate that PDO models retain tumor heterogeneity, exhibited by the different genomic profiles and varying chemosensitivity. In addition, PDO models can be used to model the genomic and drug response profiles that arise in response to chemotherapy. Citation Format: Andreea Newtson, Emily Symons, Paige Malmrose, Eric Devor, Samantha Parks, Craig Rush, Jessica Andrew-Udoh, Haley Losh, Jay Gertz, Kristina Thiel, Kimberly Leslie. Use of patient-derived organoids to model tumor evolution in response to chemotherapy [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr B032.

The vast majority of ovarian cancers have a TP53 mutation. Among these, a substantial proportion also have a BRCA1 and/or a BRCA2 mutation. Given a rising interest in the therapeutic use of p53 reactivating agents, we assessed the effect that such BRCA mutants would have on the action of a p53 reactivator. As an initial tool to examine the effect of a BRCA mutation on the action of a p53 reactivator we chose to utilize a naturally occurring experimental model. The high grade serous ovarian cancer cell lines PEO1 and PEO4 were established from the same patient. Both cell lines have a missense TP53 mutation, G244D. However, PEO1 cells also have a nonsense BRCA2 mutation, Y1655ter, which is cancelled out by a second mutation, Y1655Y, that renders PEO4 cells BRCA2 wild-type. This makes these cell lines an ideal experimental platform to begin to assess the effect of a BRCA mutation on the action of a p53 reactivator. Both PEO1 and PEO4 cells were treated with a p53 reactivator, the synthetic curcumin analog HO-3867. The effect of treatment was assessed through quantitative PCR (qPCR) assays of fourteen known p53 target loci, including p53 itself. In all cases there was a definite difference between treated and untreated cells relative to their BRCA2 status. While these results are preliminary, the fact that BRCA2 status influences the effect of a p53 reactivator on numerous target loci suggests that this relationship should be further investigated and that, in future, the BRCA status of ovarian tumors containing missense TP53 mutations should be considered when opting for the therapeutic use of a p53 reactivator.

BackgroundMutations in the receptor tyrosine kinase gene fibroblast growth factor receptor 2 (FGFR2) occur at a high frequency in endometrial cancer (EC) and have been linked to advanced and recurrent disease. However, little is known about how these mutations drive carcinogenesis. MethodsDifferential transcriptomic analysis and two-step quantitative real-time PCR (qRT-PCR) assays were applied to identify genes differentially expressed in two cohorts of EC patients carrying mutations in the FGFR2 gene as well as in EC cells harbouring mutations in the FGFR2. Candidate genes and target signalling pathways were investigated by qRT-PCR assays, immunohistochemistry and bioinformatics analysis. The functional roles of differently regulated genes were analysed using in vitro and in vivo experiments, including 3D-orthotypic co-culture systems, cell proliferation and migration protocols, as well as colony and focus formation assays together with murine xenograft tumour models. The molecular mechanisms were examined using CRISPR/Cas9-based loss-of-function and pharmacological approaches as well as luciferase reporter techniques, cell-based ectodomain shedding assays and bioinformatics analysis. ResultsWe show that common FGFR2 mutations significantly enhance the sensitivity to FGF7-mediated activation of a disintegrin and metalloprotease (ADAM)17 and subsequent transactivation of the epidermal growth factor receptor (EGFR). We further show that FGFR2 mutants trigger the activation of ADAM10-mediated Notch signalling in an ADAM17-dependent manner, highlighting for the first time an intimate cooperation between EGFR and Notch pathways in EC. Differential transcriptomic analysis in EC cells in a cohort of patients carrying mutations in the FGFR2 gene identified a strong association between FGFR2 mutations and increased expression of members of the Notch pathway and ErbB receptor family. Notably, FGFR2 mutants are not constitutively active but require FGF7 stimulation to reprogram Notch and EGFR pathway components, resulting in ADAM17-dependent oncogenic growth. ConclusionsThese findings highlight a pivotal role of ADAM17 in the pathogenesis of EC and provide a compelling rationale for targeting ADAM17 protease activity in FGFR2-driven cancers.

There are strong correlations between the microbiome and human disease, including cancer. However, very little is known about potential mechanisms associated with malignant transformation in microbiome-associated gynecological cancer, except for HPV-induced cervical cancer. Our hypothesis is that differences in bacterial communities in upper genital tract epithelium may lead to selection of specific genomic variation at the cellular level of these tissues that may predispose to their malignant transformation. We first assessed differences in the taxonomic composition of microbial communities and genomic variation between gynecologic cancers and normal samples. Then, we performed a correlation analysis to assess whether differences in microbial communities selected for specific single nucleotide variation (SNV) between normal and gynecological cancers. We validated these results in independent datasets. This is a retrospective nested case-control study that used clinical and genomic information to perform all analyses. Our present study confirms a changing landscape in microbial communities as we progress into the upper genital tract, with more diversity in lower levels of the tract. Some of the different genomic variations between cancer and controls strongly correlated with the changing microbial communities. Pathway analyses including these correlated genes may help understand the basis for how changing bacterial landscapes may lead to these cancers. However, one of the most important implications of our findings is the possibility of cancer prevention in women at risk by detecting altered bacterial communities in the upper genital tract epithelium.

Progesterone prevents development of endometrial cancers through its receptor (PR) although the molecular mechanisms have yet to be fully characterized. In this study, we performed a global analysis of gene regulation by progesterone using human endometrial cancer cells that expressed PR endogenously or exogenously. We found progesterone strongly inhibits multiple components of the platelet derived growth factor receptor (PDGFR), Janus kinase (JAK), signal transducer and activator of transcription (STAT) pathway through PR. The PDGFR/JAK/STAT pathway signals to control numerous downstream targets including AP-1 transcription factors Fos and Jun. Treatment with inhibitors of the PDGFR/JAK/STAT pathway significantly blocked proliferation in multiple novel patient-derived organoid models of endometrial cancer, and activation of this pathway was found to be a poor prognostic signal for the survival of patients with endometrial cancer from The Cancer Genome Atlas. Our study identifies this pathway as central to the growth-limiting effects of progesterone in endometrial cancer and suggests that inhibitors of PDGFR/JAK/STAT should be considered for future therapeutic interventions.

Bulk tissue RNA sequencing (RNAseq) measures average gene expression in specimens but cannot account for the expression of different cell types in the tissues. Single-cell RNA-seq (scRNAseq) identifies specific cell populations for sequencing, allowing for the identification of diverse genetic populations. However, scRNAseq is costly and not well-suited to characterizing cell types in solid tissues. Newer computational methods have been developed that can use scRNAseq to estimate cell type proportions in bulk RNA-seq data.

Early detection of ovarian cancer remains elusive. Recently there have been some reports indicating the possibility of using genetic variation in the detection of several malignancies, including using variation from mitochondrial DNA (mtDNA). The objective of this pilot study was to assess if a genetic variation of mtDNA can identify high-grade serous ovarian cancer (HGSC). Additionally, we assessed the effect of significant variants on gene expression.

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.

The preoperative diagnosis of pelvic masses has been elusive to date. Methods for characterization such as CA-125 have had limited specificity. We hypothesize that genomic variation can be used to create prediction models which accurately distinguish high grade serous ovarian cancer (HGSC) from benign tissue. Methods: In this retrospective, pilot study, we extracted DNA and RNA from HGSC specimens and from benign fallopian tubes. Then, we performed whole exome sequencing and RNA sequencing, and identified single nucleotide variants (SNV), copy number variants (CNV) and structural variants (SV). We used these variants to create prediction models to distinguish cancer from benign tissue. The models were then validated in independent datasets and with a machine learning platform. Results: The prediction model with SNV had an AUC of 1.00 (95% CI 1.00–1.00). The models with CNV and SV had AUC of 0.87 and 0.73, respectively. Validated models also had excellent performances. Conclusions: Genomic variation of HGSC can be used to create prediction models which accurately discriminate cancer from benign tissue. Further refining of these models (early-stage samples, other tumor types) has the potential to lead to detection of ovarian cancer in blood with cell free DNA, even in early stage.

Pregnancy Predictors of Health, University of Iowa Obstetrics and Gynecology Postgraduate Virtual Conference, November 5, 2021Poster Presentations