Mutated p53 portends improvement in outcomes when bevacizumab is combined with chemotherapy in advanced/recurrent endometrial cancer: An NRG Oncology study.

BACKGROUND: Successfully combining targeted agents with chemotherapy is an important future goal for cancer therapy. However, an improvement in patient outcomes requires an enhanced understanding of the tumor biomarkers that predict for drug sensitivity. NRG Oncology/Gynecologic Oncology Group (GOG) Study GOG-86P was one of the first attempts to combine targeted agents (bevacizumab or temsirolimus) with chemotherapy in patients with advanced endometrial cancer. Herein we performed exploratory analyses to examine the relationship between mutations in TP53, the most commonly mutated gene in cancer, with outcomes on GOG-86P. METHODS: TP53 mutational status was determined and correlated with progression-free survival (PFS) and overall survival (OS) on GOG-86P. RESULTS: Mutations in TP53 were associated with improved PFS and OS for patients that received bevacizumab as compared to temsirolimus (PFS: HR 0.48, 95% CI 0.31, 0.75; OS: HR: 0.61, 95% CI 0.38, 0.98). By contrast, there was no statistically significant difference in PFS or OS between arms for cases with WT TP53. CONCLUSIONS: This exploratory study suggests that combining chemotherapy with bevacizumab, but not temsirolimus, may enhance PFS and OS for patients whose tumors harbor mutant p53. These data set the stage for larger clinical studies evaluating the potential of TP53 mutational status as a biomarker to guide choice of treatment for endometrial cancer patients. Clintrials.gov: NCT00977574.

Characterization of a TP53 Somatic Variant of Unknown Function From an Ovarian Cancer Patient Using Organoid Culture and Computational Modeling.

In our proof-of-concept study of 1 patient with stage IIIC carcinosarcoma of the ovary, we discovered a rare mutation in the tumor suppressor, TP53, that results in the deletion of N131. Immunofluorescence imaging of the organoid culture revealed hyperstaining of p53 protein. Computational modeling suggests this residue is important for maintaining protein conformation. Drug screening identified the combination of a proteasome inhibitor with a histone deacetylase inhibitor as the most effective treatment. These data provide evidence for the successful culture of a patient tumor and analysis of drug response ex vivo.

MTDH/AEG-1 downregulation using pristimerin-loaded nanoparticles inhibits Fanconi anemia proteins and increases sensitivity to platinum-based chemotherapy.

OBJECTIVE: 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. METHODS: The mRNA of FANCD2 and FANCI was pulled down by RNA-binding protein immunoprecipitation. Pristimerin-loaded nanoparticles were prepared using the nanoprecipitation method. Immunocompromised mice bearing patient-derived xenograft tumors were treated with pristimerin-loaded nanoparticles, cisplatin and a combination of the two. RESULTS: MTDH, through its recently discovered role as an RNA binding protein, regulates expression of FANCD2 and FANCI, two components of the Fanconi anemia complementation group (FA) that play critical roles in interstrand crosslink damage induced by platinum compounds. Pristimerin, a quinonemethide triterpenoid extract from members of the Celastraceae family used to treat inflammation in traditional Chinese medicine, significantly decreased MTDH, FANCD2 and FANCI levels in cancer cells, thereby restoring sensitivity to platinum-based chemotherapy. Using a patient-derived xenograft model of endometrial cancer, we discovered that treatment with pristimerin in a novel nanoparticle formulation markedly inhibited tumor growth when combined with cisplatin. CONCLUSIONS: MTDH is involved in post-transcriptional regulation of FANCD2 and FANCI. Pristimerin can increase sensitivity to platinum-based agents in tumors with MTDH overexpression by inhibiting the FA pathway.

Molecular Characterization of Non-responders to Chemotherapy in Serous Ovarian Cancer.

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.

A Prediction Model for Preoperative Risk Assessment in Endometrial Cancer Utilizing Clinical and Molecular Variables.

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.

High stathmin expression is a marker for poor clinical outcome in endometrial cancer: An NRG oncology group/gynecologic oncology group study.

OBJECTIVE: Gynecologic Oncology Group (GOG) 177 demonstrated that addition of paclitaxel to a backbone of adriamycin/cisplatin improves overall survival (OS) and progression-free survival (PFS) for patients with advanced or recurrent endometrial cancer. Using patient specimens from GOG-177, our objective was to identify potential mechanisms underlying the improved clinical response to taxanes. Stathmin (STMN1) is a recognized poor prognostic marker in endometrial cancer that functions as a microtubule depolymerizing protein, allowing cells to transit rapidly through mitosis. Therefore, we hypothesized that one possible mechanism underlying the beneficial effects of paclitaxel could be to counter the impact of stathmin. METHODS: We analyzed the expression of stathmin by immunohistochemistry (IHC) in 69 specimens from patients enrolled on GOG-177. We also determined the correlation between stathmin mRNA expression and clinical outcomes in The Cancer Genome Atlas (TCGA) dataset for endometrial cancer. RESULTS: We first established that stathmin expression was significantly associated with shorter PFS and OS for all analyzed cases in both GOG-177 and TCGA. However, subgroup analysis from GOG-177 revealed that high stathmin correlated with poor PFS and OS particularly in patients who received adriamycin/cisplatin only. In contrast, there was no statistically significant association between stathmin expression and OS or PFS in patients treated with paclitaxel/adriamycin/cisplatin. CONCLUSIONS: Our findings demonstrate that high stathmin expression is a poor prognostic marker in endometrial cancer. Paclitaxel may help to negate the impact of stathmin overexpression when treating high risk endometrial cancer cases.

Placenta-Specific Protein 1 Expression in Human Papillomavirus 16/18-Positive Cervical Cancers Is Associated With Tumor Histology.

OBJECTIVE: Expression of the trophoblast-specific gene placenta-specific protein 1 (PLAC1) has been detected in a wide variety of cancers. However, to date, PLAC1 expression has not been shown in cervical cancer. We have carried out a preliminary study that shows for the first time that PLAC1 is expressed in cervical cancers. METHODS: A total of 16 primary cervical tumors were obtained from patients shown to be human papillomavirus (HPV) 16/18 positive. Total cellular RNA, genomic DNA, and total protein were purified from each tumor. These materials were then used to determine PLAC1 expression, TP53 mutation status, and p53 expression. RESULTS: The PLAC1 expression was demonstrated in all 16 primary cervical tumors. The highest levels of expression were found in the more aggressive squamous and adenosquamous histologic types compared with adenocarcinomas. Moreover, the proportion of total PLAC1 message coming from the P1 promoter, also termed the distal or cancer promoter, was significantly greater in the more aggressive squamous and adenosquamous histologic types compared with adenocarcinomas. Finally, in spite of all 16 tumors being HPV-16/18 positive, 3 of 8 squamous cell cancers and 2 of 5 adenocarcinomas expressed wild-type p53 protein. Consistent with the recently shown suppression of the PLAC1P1 promoter by wild-type p53, these p53 positive tumors displayed among the lowest P1-specific PLAC1 expression levels. CONCLUSIONS: The PLAC1 expression has been demonstrated for the first time in cervical cancers. This preliminary study has further revealed a complex relationship between PLAC1 expression, cervical cancer histologic type, p53, and HPV type that requires further investigation.

Genetic Deficiency of Mtdh Gene in Mice Causes Male Infertility via Impaired Spermatogenesis and Alterations in the Expression of Small Non-coding RNAs.

Increased expression of metadherin (MTDH, also known as AEG-1 and 3D3/LYRIC) has been associated with drug resistance, metastasis, and angiogenesis in a variety of cancers. However, the specific mechanisms through which MTDH is involved in these processes remain unclear. To uncover these mechanisms, we generated Mtdh knock-out mice via a targeted disruption of exon 3. Homozygous Mtdh knock-out mice are viable, but males are infertile. The homozygous male mice present with massive loss of spermatozoa as a consequence of meiotic failure. Accumulation of γ-H2AX in spermatocytes of homozygous Mtdh knock-out mice confirms an increase in unrepaired DNA breaks. We also examined expression of the DNA repair protein Rad18, which is regulated by MTDH at the post-transcriptional level. In testes from Mtdh exon 3-deficient mice, Rad18 foci were increased in the lumina of the seminiferous tubules. The Piwi-interacting RNA (piRNA)-interacting protein Mili was expressed at high levels in testes from Mtdh knock-out mice. Accordingly, genome-wide small RNA deep sequencing demonstrated altered expression of piRNAs in the testes of Mtdh knock-out mice as compared with wild type mice. In addition, we observed significantly reduced expression of microRNAs (miRNAs) including miR-16 and miR-19b, which are known to be significantly reduced in the semen of infertile men. In sum, our observations indicate a crucial role for MTDH in male fertility and the DNA repair mechanisms required for normal spermatogenesis.

Prediction of chemo-response in serous ovarian cancer.

BACKGROUND: Nearly one-third of serous ovarian cancer (OVCA) patients will not respond to initial treatment with surgery and chemotherapy and die within one year of diagnosis. If patients who are unlikely to respond to current standard therapy can be identified up front, enhanced tumor analyses and treatment regimens could potentially be offered. Using the Cancer Genome Atlas (TCGA) serous OVCA database, we previously identified a robust molecular signature of 422-genes associated with chemo-response. Our objective was to test whether this signature is an accurate and sensitive predictor of chemo-response in serous OVCA. METHODS: We first constructed prediction models to predict chemo-response using our previously described 422-gene signature that was associated with response to treatment in serous OVCA. Performance of all prediction models were measured with area under the curves (AUCs, a measure of the model's accuracy) and their respective confidence intervals (CIs). To optimize the prediction process, we determined which elements of the signature most contributed to chemo-response prediction. All prediction models were replicated and validated using six publicly available independent gene expression datasets. RESULTS: The 422-gene signature prediction models predicted chemo-response with AUCs of ~70 %. Optimization of prediction models identified the 34 most important genes in chemo-response prediction. These 34-gene models had improved performance, with AUCs approaching 80 %. Both 422-gene and 34-gene prediction models were replicated and validated in six independent datasets. CONCLUSIONS: These prediction models serve as the foundation for the future development and implementation of a diagnostic tool to predict response to chemotherapy for serous OVCA patients.

Stratification of endometrioid endometrial cancer patients into risk levels using somatic mutations.

OBJECTIVE: 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. METHODS: We classified endometrioid endometrial cancer patients in The Cancer Genome Atlas (TCGA) dataset into high risk and low risk categories: high risk patients presented with stage II, III or IV disease or stage I with high-intermediate risk features, whereas low risk patients consisted of the remaining stage I patients with either no myometrial invasion or low-intermediate risk features. Three strategies were used to build the prediction model: 1) mutational status for each gene; 2) number of somatic mutations for each gene; and 3) variant allele frequencies for each somatic mutation for each gene. RESULTS: Each prediction strategy had a good performance, with an area under the curve (or AUC) between 61% and 80%. Analysis of variant allele frequency produced a superior prediction model for risk levels of endometrial cancer as compared to the other two strategies, with an AUC=91%. Lasso and Ridge methods identified 53 mutations that together had the highest predictability for high risk endometrioid endometrial cancer. CONCLUSIONS: This prediction model will assist future retrospective and prospective studies to categorize endometrial cancer patients into high risk and low risk in the preoperative setting.

Downregulation of FOXO1 mRNA levels predicts treatment failure in patients with endometrial pathology conservatively managed with progestin-containing intrauterine devices.

OBJECTIVE: To examine hormone receptor expression levels and downstream gene activation in pre-treatment and post-treatment biopsies in a cohort of patients with endometrial pathology who were being conservatively managed with a progestin-containing intrauterine device (IUD). A molecular signature of treatment failure is proposed. METHODS: A retrospective analysis of pre- and post-treatment biopsy specimens from 10 women treated with progestin-containing IUD for complex atypical hyperplasia (CAH) or grade 1 endometrioid adenocarcinoma was performed. Expression of estrogen receptor (ER), progesterone receptor (PR) and PR target genes was examined by immunohistochemistry (IHC) and quantitative RT-PCR. RESULTS: The mean treatment duration was 14.3 months. Four CAH patients had stable disease or regressed after treatment, and four progressed to endometrioid adenocarcinoma. Both patients with an initial diagnosis of endometrioid adenocarcinoma regressed to CAH or no disease. In general, hormone receptor levels diminished post-treatment compared to pre-treatment biopsies; however, we noted unexpected higher expression of the B isoform of PR (PRB) as well as ER in those patients who progressed to frank cancer. There was a trend towards a non-nuclear cytoplasmic location of PRB in these patients. Importantly, the differentiating impact of PR signaling, as determined by the expression of the progestin-controlled tumor suppressor FOXO1, was lost in individuals who progressed on therapy. CONCLUSIONS: FOXO1 mRNA levels may serve as a biomarker for response to therapy and an indicator of PR function in patients being conservatively managed with a progestin-containing IUD.

NEDD4 ubiquitin ligase is a putative oncogene in endometrial cancer that activates IGF-1R/PI3K/Akt signaling.

OBJECTIVE: The PI3K/Akt pathway is frequently dysregulated in endometrial cancer, the most common gynecologic malignancy. Emerging evidence identifies the ubiquitin ligase NEDD4 as a key regulator of the PI3K/Akt pathway via activation of insulin-like growth factor-1 receptor (IGF-1R). Our objective was to understand the role of NEDD4 in endometrial cancer. METHODS: NEDD4 expression was assessed by immunohistochemistry in a tissue microarray with 77 endometrial lesions ranging from normal benign endometrium to tumor specimens of varying stage and grade. Studies were extended to a panel of eight endometrial cancer cell lines phenotypically representing the most common endometrial patient tumors. RESULTS: Immunohistochemistry demonstrated robust staining of NEDD4 in endometrial tumor specimens, with greater NEDD4 expression in the most aggressive tumors. Expression of NEDD4 was detected in a majority of endometrial cancer cell lines surveyed. Exogenous overexpression of murine Nedd4 in endometrial cancer cell lines with modest endogenous NEDD4 expression resulted in a significant increase in the rate of proliferation. Nedd4 overexpression also promoted an increase in cell surface localization of IGF-1R and activation of Akt. Inhibition of PI3K/Akt signaling reversed the enhanced cell growth in Nedd4-overexpressing endometrial cancer cells. In addition, the expression of NEDD4 in endometrial tumors positively correlated with the Akt downstream effector FoxM1. CONCLUSIONS: This study identifies NEDD4 as a putative oncogene in endometrial cancer that may augment activation of the IGF-1R/PI3K/Akt signaling pathway.

Delivery of chemo-sensitizing siRNAs to HER2+-breast cancer cells using RNA aptamers.

Human epidermal growth factor receptor 2 (HER2) expression in breast cancer is associated with an aggressive phenotype and poor prognosis, making it an appealing therapeutic target. Trastuzumab, an HER2 antibody-based inhibitor, is currently the leading targeted treatment for HER2(+)-breast cancers. Unfortunately, many patients inevitably develop resistance to the therapy, highlighting the need for alternative targeted therapeutic options. In this study, we used a novel, cell-based selection approach for isolating 'cell-type specific', 'cell-internalizing RNA ligands (aptamers)' capable of delivering therapeutic small interfering RNAs (siRNAs) to HER2-expressing breast cancer cells. RNA aptamers with the greatest specificity and internalization potential were covalently linked to siRNAs targeting the anti-apoptotic gene, Bcl-2. We demonstrate that, when applied to cells, the HER2 aptamer-Bcl-2 siRNA conjugates selectively internalize into HER2(+)-cells and silence Bcl-2 gene expression. Importantly, Bcl-2 silencing sensitizes these cells to chemotherapy (cisplatin) suggesting a potential new therapeutic approach for treating breast cancers with HER2(+)-status. In summary, we describe a novel cell-based selection methodology that enables the identification of cell-internalizing RNA aptamers for targeting therapeutic siRNAs to HER2-expressing breast cancer cells. The future refinement of this technology may promote the widespread use of RNA-based reagents for targeted therapeutic applications.

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.

The epidermal growth factor receptor and its ligands in cardiovascular disease.

The epidermal growth factor receptor (EGFR) family and its ligands serve as a switchboard for the regulation of multiple cellular processes. While it is clear that EGFR activity is essential for normal cardiac development, its function in the vasculature and its role in cardiovascular disease are only beginning to be elucidated. In the blood vessel, endothelial cells and smooth muscle cells are both a source and a target of EGF-like ligands. Activation of EGFR has been implicated in blood pressure regulation, endothelial dysfunction, neointimal hyperplasia, atherogenesis, and cardiac remodeling. Furthermore, increased circulating EGF-like ligands may mediate accelerated vascular disease associated with chronic inflammation. Although EGFR inhibitors are currently being used clinically for the treatment of cancer, additional studies are necessary to determine whether abrogation of EGFR signaling is a potential strategy for the treatment of cardiovascular disease.

The consequence of oncomorphic TP53 mutations in ovarian cancer.

Ovarian cancer is the most lethal gynecological malignancy, with an alarmingly poor prognosis attributed to late detection and chemoresistance. Initially, most tumors respond to chemotherapy but eventually relapse due to the development of drug resistance. Currently, there are no biological markers that can be used to predict patient response to chemotherapy. However, it is clear that mutations in the tumor suppressor gene TP53, which occur in 96% of serous ovarian tumors, alter the core molecular pathways involved in drug response. One subtype of TP53 mutations, widely termed gain-of-function (GOF) mutations, surprisingly converts this protein from a tumor suppressor to an oncogene. We term the resulting change an oncomorphism. In this review, we discuss particular TP53 mutations, including known oncomorphic properties of the resulting mutant p53 proteins. For example, several different oncomorphic mutations have been reported, but each mutation acts in a distinct manner and has a different effect on tumor progression and chemoresistance. An understanding of the pathological pathways altered by each mutation is necessary in order to design appropriate drug interventions for patients suffering from this deadly disease.

AptamerRunner: An accessible aptamer structure prediction and clustering algorithm for visualization of selected aptamers.

Aptamers are short single-stranded DNA or RNA molecules with high affinity and specificity for targets and are generated using the iterative Systematic Evolution of Ligands by EXponential enrichment (SELEX) process. Next-generation sequencing (NGS) revolutionized aptamer selections by allowing a more comprehensive analysis of SELEX-enriched aptamers as compared to Sanger sequencing. The current challenge with aptamer NGS datasets is identifying a diverse cohort of candidate aptamers with the highest likelihood of successful experimental validation. Herein we present AptamerRunner, an aptamer clustering algorithm that generates visual networks of aptamers that are related by sequence and/or structure. These networks can then be overlayed with ranking data, such as fold enrichment or data from scoring algorithms. The ability to visually integrate data using AptamerRunner represents a significant advancement over existing clustering tools by providing a natural context to depict groups of aptamers from which ranked or scored candidates can be chosen for experimental validation. The inherent flexibility, user-friendly design, and prospects for future enhancements with AptamerRunner has broad-reaching implications for aptamer researchers across a wide range of disciplines.

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.

An exploratory study of the variables impacting preterm birth rates in New Mexico.

BACKGROUND: Preterm birth (PTB) is a substantial health problem that accounts for significant infant morbidity and mortality and poses an economic burden to both individuals and the state of residence. The goal of this study was to identify maternal risk factors for PTB in New Mexico, a poor state with a unique ethnic background, in order to identify populations at increased risk that would benefit from intervention. METHODS: This was a cross-sectional retrospective exploratory analysis of 377,770 singleton live births in the state of New Mexico from 1991-2005. Gestational age of less than 37 weeks was defined as PTB. The Kotelchuck Index was used as a measure for level of prenatal care described as inadequate, intermediate, adequate, and intensive. RESULTS: Of the live births analyzed, 28,036 of these were preterm (7.4%). Overall the PTB rate rose at a rate of 0.18% per year from 1991-2005. Among patients with medical risk factors, the absence of prenatal care was associated with higher odds for PTB as compared to adequate prenatal care. Other risk factors were unmarried status, education less than high school, tobacco/alcohol use, black, Asian, and white Hispanic ethnicity, and the presence of one or more medical risk factors. Statistically significant protective factors for PTB were age 25-29, education surpassing high school, and Native American race. CONCLUSIONS: This study identified several factors that correlate with increased PTB in New Mexico, in particular ethnicity and level of prenatal care. The finding that Native American patients have a lower PTB rate compared to other groups, even though this group is traditionally one of low socioeconomic status in New Mexico, signifies that other factors yet to be identified affect PTB.