Early menopause and hormone therapy as determinants for lung health outcomes: a secondary analysis using the PLCO trial.

RATIONALE: Early natural menopause (early-M; <45 years of age) increases the risk of lung morbidities and mortalities in smokers. However, it is largely unknown whether early-M due to surgery demonstrates similar effects and whether menopausal hormone therapy (MHT) is protective against lung diseases. OBJECTIVES: To assess the associations of early-M and MHT with lung morbidities and mortalities using the prospective Prostate, Lung, Colorectal and Ovarian (PLCO) trial. METHODS: We estimated the risk among 69 706 postmenopausal women in the PLCO trial, stratified by menopausal types and smoking status. RESULTS: Early-M was associated with an increased risk of most lung disease and mortality outcomes in ever smokers with the highest risk seen for respiratory mortality (HR 1.98, 95% CI 1.34 to 2.92) in those with bilateral oophorectomy (BO). Early-M was positively associated with chronic bronchitis, and all-cause, non-cancer and respiratory mortality in never smokers with natural menopause or BO, with the highest risk seen for BO- respiratory mortality (HR 1.91, 95% CI 1.16 to 3.12). Ever MHT was associated with reduced all-cause, non-cancer and cardiovascular mortality across menopause types regardless of smoking status and was additionally associated with reduced risk of non-ovarian cancer, lung cancer (LC) and respiratory mortality in ever smokers. Among smokers, ever MHT use was associated with a reduction in HR for all-cause, non-cancer and cardiovascular mortality in a duration-dependent manner. CONCLUSIONS: Smokers with early-M should be targeted for smoking cessation and LC screening regardless of menopause types. MHT users had a lower likelihood of dying from LC and respiratory diseases in ever smokers.

Multiplexed Live-Cell Imaging for Drug Responses in Patient-Derived Organoid Models of Cancer.

Patient-derived organoid (PDO) models of cancer are a multifunctional research system that better recapitulates human disease as compared to cancer cell lines. PDO models can be generated by culturing patient tumor cells in extracellular basement membrane extracts (BME) and plating them as three-dimensional domes. However, commercially available reagents that have been optimized for phenotypic assays in monolayer cultures often are not compatible with BME. Herein, we describe a method to plate PDO models and assess drug effects using an automated live-cell imaging system. In addition, we apply fluorescent dyes that are compatible with kinetic measurements to quantify cell health and apoptosis simultaneously. Image capture can be customized to occur at regular time intervals over several days. Users can analyze drug effects in individual Z-plane images or a Z Projection of serial images from multiple focal planes. Using masking, specific parameters of interest are calculated, such as PDO number, area, and fluorescence intensity. We provide proof-of-concept data demonstrating the effect of cytotoxic agents on cell health, apoptosis, and viability. This automated kinetic imaging platform can be expanded to other phenotypic readouts to understand diverse therapeutic effects in PDO models of cancer.

Multiplexed live-cell imaging for drug responses in patient-derived organoid models of cancer.

Patient-derived organoid (PDO) models of cancer are a multifunctional research system that better recapitulates human disease as compared to cancer cell lines. PDO models can be generated by culturing patient tumor cells in extracellular basement membrane extracts (BME) and plating as three-dimensional domes. However, commercially available reagents that have been optimized for phenotypic assays in monolayer cultures often are not compatible with BME. Herein we describe a method to plate PDO models and assess drug effects using an automated live-cell imaging system. In addition, we apply fluorescent dyes that are compatible with kinetic measurements to simultaneously quantitate cell health and apoptosis. Image capture can be customized to occur at regular time intervals over several days. Users can analyze drug effects in individual Z-plane images or a Z Projection of serial images from multiple focal planes. Using masking, specific parameters of interest are calculated, such as PDO number, area, and fluorescence intensity. We provide proof-of-concept data demonstrating the effect of cytotoxic agents on cell health, apoptosis and viability. This automated kinetic imaging platform can be expanded to other phenotypic readouts to understand diverse therapeutic effects in PDO models of cancer.

Global expression analysis of endometrial cancer cells in response to progesterone identifies new therapeutic targets.

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.

Microbial Communities in Gynecological Cancers and Their Association with Tumor Somatic Variation.

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.

Particles and Prejudice: Nanomedicine Approaches to Reducing Health Disparities in Endometrial Cancer.

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.

FGFR2 mutations promote endometrial cancer progression through dual engagement of EGFR and Notch signalling pathways.

BACKGROUND: Mutations 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. METHODS: Differential 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. RESULTS: We 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. CONCLUSIONS: These 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.

Using Genomic Variation to Distinguish Ovarian High-Grade Serous Carcinoma from Benign Fallopian Tubes.

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.

Enhancing progestin therapy via HDAC inhibitors in endometrial cancer.

Uterine endometrial cancer (EC) incidence and deaths are on the rise. Hormone therapy, a traditional treatment regimen for this disease, uses progesterone and its synthetic analogue, progestin, to induce cell differentiation, apoptosis, and inhibition of invasion. This therapy is highly effective for progesterone receptor (PR) positive tumors in the short term. However, responsiveness decreases over time due to loss of PR expression; acquired resistance leads to treatment failure and poor prognosis. Primary resistance occurs in advanced, PR-negative tumors. Regardless, progestin therapy can be effective if the PR downregulation mechanism is reversed and if functional PR expression is restored. Using histone deacetylase inhibitors (HDACi), we inhibited cell proliferation in three EC cell lines and restored functional PR expression at the mRNA and protein levels. Two HDACi were tested using an endometrial xenograft tumor model: entinostat, an oral drug, and romidepsin, an IV drug. In vitro and in vivo studies support that entinostat decreased EC tumor growth, induced differentiation, and increased expression of the PR-targeted gene, PAEP. These findings supported the approval of a new NIH NCTN clinical trial, NRG-GY011, which concluded that dual treatment of MPA and entinostat, decreased expression of the proliferation marker, Ki67, but did not increase PR expression relative to single treatment with MPA in this short-term study. Therefore, a more potent HDACi, romidepsin, was investigated. Romidepsin treatment inhibited tumor growth and enhanced progestin treatment efficacy. More importantly, PR, PAEP, and KIAA1324 expressions were upregulated. Using a chromatin immunoprecipitation assay, we verified that HDACi can reverse PR downregulation mechanisms in mice models. Other potential drug efficacy markers, such as CD52, DLK1, GALNT9, and GNG2, were identified by transcriptome analysis and verified by q-PCR. Many of the upregulated drug efficacy markers predict favorable patient outcomes, while downregulated genes predict worse survival. Here, our current data suggests that romidepsin is a more potent HDACi that has the potential to achieve more robust upregulation of PR expression and may be a more promising candidate for future clinical trials.

Integration of Genomic and Clinical Retrospective Data to Predict Endometrioid Endometrial Cancer Recurrence.

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.

Characterization of HCI-EC-23 a novel estrogen- and progesterone-responsive endometrial cancer cell line.

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.

Utilizing an Endogenous Progesterone Receptor Reporter Gene for Drug Screening and Mechanistic Study in Endometrial Cancer.

Expression of progesterone receptor (PR) is a favorable prognostic marker for multiple solid tumors. However, PR expression is reduced or lost in malignant tumors. Thus, monitoring and restoring functional PR expression is important in order to sensitize tumor cells to progesterone therapy in endometrial cancer. We developed stable PR reporter gene containing endometrial cancer cell lines monitoring the endogenous PR expression by inserting mCherry and hygromycin resistant gene at the endogenous PR gene locus by CRISPR/Cas9-mediated genome editing technique. This allows efficient, real-time monitoring of PR expression in its native epigenetic landscape. Reporter gene expression faithfully reflects and amplifies PR expression following treatment with drugs known to induce PR expression. Small molecular PR inducers have been identified from the FDA-approved 1018 drug library and tested for their ability to restore PR expression. Additionally, several candidate PR repressors have been identified by screening the genome-wide CRISPR knockout (GeCKO) library. This novel endogenous PR reporter gene system facilitates the discovery of a new treatment strategy to enhance PR expression and further sensitize progestin therapy in endometrial cancer. These tools provide a systematic, unbiased approach for monitoring target gene expression, allowing for novel drug discovery and mechanistic exploration.

Integrated Clinical and Genomic Models to Predict Optimal Cytoreduction in High-Grade Serous Ovarian Cancer.

Advanced high-grade serous (HGSC) ovarian cancer is treated with either primary surgery followed by chemotherapy or neoadjuvant chemotherapy followed by interval surgery. The decision to proceed with surgery primarily or after chemotherapy is based on a surgeon's clinical assessment and prediction of an optimal outcome. Optimal and complete cytoreductive surgery are correlated with improved overall survival. This clinical assessment results in an optimal surgery approximately 70% of the time. We hypothesize that this prediction can be improved by using biological tumor data to predict optimal cytoreduction. With access to a large biobank of ovarian cancer tumors, we obtained genomic data on 83 patients encompassing gene expression, exon expression, long non-coding RNA, micro RNA, single nucleotide variants, copy number variation, DNA methylation, and fusion transcripts. We then used statistical learning methods (lasso regression) to integrate these data with pre-operative clinical information to create predictive models to discriminate which patient would have an optimal or complete cytoreductive outcome. These models were then validated within The Cancer Genome Atlas (TCGA) HGSC database and using machine learning methods (TensorFlow). Of the 124 models created and validated for optimal cytoreduction, 21 performed at least equal to, if not better than, our historical clinical rate of optimal debulking in advanced-stage HGSC as a control. Of the 89 models created to predict complete cytoreduction, 37 have the potential to outperform clinical decision-making. Prospective validation of these models could result in improving our ability to objectively predict which patients will undergo optimal cytoreduction and, therefore, improve our ovarian cancer outcomes.

TP53 Sequencing and p53 Immunohistochemistry Predict Outcomes When Bevacizumab Is Added to Frontline Chemotherapy in Endometrial Cancer: An NRG Oncology/Gynecologic Oncology Group Study.

PURPOSE: The status of p53 in a tumor can be inferred by next-generation sequencing (NGS) or by immunohistochemistry (IHC). We examined the association between p53 IHC and sequence and whether p53 IHC alone, or integrated with TP53 NGS, predicts the outcome. METHODS: From GOG-86P, a randomized phase II study of chemotherapy combined with either bevacizumab or temsirolimus in advanced endometrial cancer, 213 cases had p53 protein expression data measured by IHC and TP53 NGS data. An analysis was designed to integrate p53 expression by IHC with the presence or absence of a TP53 mutation. These variables were further correlated with progression-free survival (PFS) and overall survival (OS) in the chemotherapy plus bevacizumab arms versus the chemotherapy plus temsirolimus arm. RESULTS: In the analysis of p53 IHC, the most striking treatment effect favoring bevacizumab was in cases where p53 was overexpressed (PFS hazard ratio [HR]: 0.46, 95% CI, 0.26 to 0.88; OS HR: 0.31, 95% CI, 0.16 to 0.62). On integrated analysis, patients with TP53 missense mutations and p53 protein overexpression had a similar treatment effect on PFS (HR: 0.41, 95% CI, 0.22 to 0.83) and OS (HR: 0.28, 95% CI, 0.14 to 0.59) favoring bevacizumab plus chemotherapy relative to temsirolimus plus chemotherapy. Concordance between TP53 NGS and p53 IHC was 88%. Concordance was 92% when cases with TP53 mutations and POLE mutations or mismatch repair deficiency were removed. CONCLUSION: IHC for p53 alone or when integrated with sequencing for TP53 identifies a specific, high-risk tumor genotype/phenotype for which bevacizumab is particularly beneficial in improving outcomes when combined with chemotherapy.

Blocking autophagy overcomes resistance to dual histone deacetylase and proteasome inhibition in gynecologic cancer.

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 Synthetic Curcumin Analog HO-3867 Rescues Suppression of PLAC1 Expression in Ovarian Cancer Cells.

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.

Advantages of Tyrosine Kinase Anti-Angiogenic Cediranib over Bevacizumab: Cell Cycle Abrogation and Synergy with Chemotherapy.

Angiogenesis plays a crucial role in tumor development and metastasis. Both bevacizumab and cediranib have demonstrated activity as single anti-angiogenic agents in endometrial cancer, though subsequent studies of bevacizumab combined with chemotherapy failed to improve outcomes compared to chemotherapy alone. Our objective was to compare the efficacy of cediranib and bevacizumab in endometrial cancer models. The cellular effects of bevacizumab and cediranib were examined in endometrial cancer cell lines using extracellular signal-related kinase (ERK) phosphorylation, ligand shedding, cell viability, and cell cycle progression as readouts. Cellular viability was also tested in eight patient-derived organoid models of endometrial cancer. Finally, we performed a phosphoproteomic array of 875 phosphoproteins to define the signaling changes related to bevacizumab versus cediranib. Cediranib but not bevacizumab blocked ligand-mediated ERK activation in endometrial cancer cells. In both cell lines and patient-derived organoids, neither bevacizumab nor cediranib alone had a notable effect on cell viability. Cediranib but not bevacizumab promoted marked cell death when combined with chemotherapy. Cell cycle analysis demonstrated an accumulation in mitosis after treatment with cediranib + chemotherapy, consistent with the abrogation of the G2/M checkpoint and subsequent mitotic catastrophe. Molecular analysis of key controllers of the G2/M cell cycle checkpoint confirmed its abrogation. Phosphoproteomic analysis revealed that bevacizumab and cediranib had both similar and unique effects on cell signaling that underlie their shared versus individual actions as anti-angiogenic agents. An anti-angiogenic tyrosine kinase inhibitor such as cediranib has the potential to be superior to bevacizumab in combination with chemotherapy.

Successful Patient-Derived Organoid Culture of Gynecologic Cancers for Disease Modeling and Drug Sensitivity Testing.

Developing reliable experimental models that can predict clinical response before treating the patient is a high priority in gynecologic cancer research, especially in advanced or recurrent endometrial and ovarian cancers. Patient-derived organoids (PDOs) represent such an opportunity. Herein, we describe our successful creation of 43 tumor organoid cultures and nine adjacent normal tissue organoid cultures derived from patients with endometrial or ovarian cancer. From an initial set of 45 tumor tissues and seven ascites fluid samples harvested at surgery, 83% grew as organoids. Drug sensitivity testing and organoid cell viability assays were performed in 19 PDOs, a process that was accomplished within seven days of obtaining the initial surgical tumor sample. Sufficient numbers of cells were obtained to facilitate testing of the most commonly used agents for ovarian and endometrial cancer. The models reflected a range of sensitivity to platinum-containing chemotherapy as well as other relevant agents. One PDO from a patient treated prior to surgery with neoadjuvant trastuzumab successfully predicted the patient's postoperative chemotherapy and trastuzumab resistance. In addition, the PDO drug sensitivity assay identified alternative treatment options that are currently used in the second-line setting. Our findings suggest that PDOs could be used as a preclinical platform for personalized cancer therapy for gynecologic cancer patients.

Team Science: American Heart Association's Hypertension Strategically Focused Research Network Experience.

In 2015, the American Heart Association awarded 4-year funding for a Strategically Focused Research Network focused on hypertension composed of 4 Centers: Cincinnati Children's Hospital, Medical College of Wisconsin, University of Alabama at Birmingham, and University of Iowa. Each center proposed 3 integrated (basic, clinical, and population science) projects around a single area of focus relevant to hypertension. Along with scientific progress, the American Heart Association put a significant emphasis on training of next-generation hypertension researchers by sponsoring 3 postdoctoral fellows per center over 4 years. With the center projects being spread across the continuum of basic, clinical, and population sciences, postdoctoral fellows were expected to garner experience in various types of research methodologies. The American Heart Association also provided a number of leadership development opportunities for fellows and investigators in these centers. In addition, collaboration was highly encouraged among the centers (both within and outside the network) with the American Heart Association providing multiple opportunities for meeting and expanding associations. The area of focus for the Cincinnati Children's Hospital Center was hypertension and target organ damage in children utilizing ambulatory blood pressure measurements. The Medical College of Wisconsin Center focused on epigenetic modifications and their role in pathogenesis of hypertension using human and animal studies. The University of Alabama at Birmingham Center's areas of research were diurnal blood pressure patterns and clock genes. The University of Iowa Center evaluated copeptin as a possible early biomarker for preeclampsia and vascular endothelial function during pregnancy. In this review, challenges faced and successes achieved by the investigators of each of the centers are presented.