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.

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.

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.

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.

Characterizing TP53 mutations in ovarian carcinomas with and without concurrent BRCA1 or BRCA2 mutations.

OBJECTIVES: 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. METHODS: We performed next generation sequencing on 393 cases of OC prospectively followed for survival. TP53 mutations were classified according to three schemes termed Structural, Functional, and Hotspot. Mutation distribution was compared between cases with and without BRCA mutations. In a subset of 281 cases of high grade serous carcinoma (HGSC), overall survival was compared using Kaplan-Meier curves, logrank testing, and multivariate Cox regression analysis, both stratified and adjusted for BRCA mutation status. Multivariate logistic regression was used to analyze the effects of TP53 mutation type on platinum resistance. RESULTS: TP53 mutations were identified in 76.8% of the total cohort (n = 302/393) and 87.9% of HGSC (n = 247/281). Cases with BRCA mutations demonstrated significantly higher TP53 mutation frequency overall (n = 84/91, 92.3% vs. n = 218/302, 72.2%, p < 0.001). TP53 mutations were not associated with overall survival, even when stratified by BRCA mutation. TP53 mutations were associated with platinum sensitivity, even after adjusting for BRCA mutation status (OR 0.41, p = 0.048). The choice of TP53 mutation classification scheme was not found to alter any significant outcome. CONCLUSIONS: BRCA mutations significantly co-occur with TP53 mutations. After adjusting for BRCA mutations, TP53 mutations are associated with platinum sensitivity, and this effect is not dependent on TP53 mutation type.

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.

Population Substructure Has Implications in Validating Next-Generation Cancer Genomics Studies with TCGA.

In the era of large genetic and genomic datasets, it has become crucially important to validate results of individual studies using data from publicly available sources, such as The Cancer Genome Atlas (TCGA). However, how generalizable are results from either an independent or a large public dataset to the remainder of the population? The study presented here aims to answer that question. Utilizing next generation sequencing data from endometrial and ovarian cancer patients from both the University of Iowa and TCGA, genomic admixture of each population was analyzed using STRUCTURE and ADMIXTURE software. In our independent data set, one subpopulation was identified, whereas in TCGA 4⁻6 subpopulations were identified. Data presented here demonstrate how different the genetic substructures of the TCGA and University of Iowa populations are. Validation of genomic studies between two different population samples must be aware of, account for and be corrected for background genetic substructure.

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.

Hepatitis C in Pregnancy in the Era of Direct-acting Antiviral Treatment: Potential Benefits of Universal Screening and Antepartum Therapy.

Hepatitis C in pregnancy is on the rise, and new direct-acting antiviral agents are available that cure the disease. Published recommendations need to be reviewed and clinically evaluated for the care of pregnant women who are at risk for or have chronic hepatitis C. Available evidence and some of the medical and ethical reasons to consider universal screening and antepartum therapy for hepatitis C during pregnancy are presented. Universal screening and proactive treatment during pregnancy is on the horizon, and these measures should be quickly evaluated for safety and implemented if appropriate.

Dysregulation of miR-181c expression influences recurrence of endometrial endometrioid adenocarcinoma by modulating NOTCH2 expression: An NRG Oncology/Gynecologic Oncology Group study.

OBJECTIVE: 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. METHODS: Using the tissue collection from Gynecologic Oncology Group Study-210, we selected and analyzed expression of miRNAs in 54 recurrent and non-recurrent cases. The three most common histologic types, endometrioid adenocarcinoma (EEA), serous adenocarcinoma (ESA) and carcinosarcoma (UCS), were analyzed as three independent sets and their miRNA expression profiles compared. RESULTS: Only one miRNA was statistically different between recurrent and non-recurrent cases, and in only one histologic type: significant down-regulation of miR-181c was observed in EEA recurrence. Using several well-known databases to assess miR-181c targets, one target of particular relevance to cancer, NOTCH2, was well supported. Using The Cancer Genome Atlas and our validation tumor panel from the GOG-210 cohort, we confirmed that NOTCH2 is significantly over-expressed in EEA. In the most relevant endometrial adenocarcinoma cell model, Ishikawa H, altering miR-181c expression produces significant changes in NOTCH2 expression, consistent with direct targeting. CONCLUSIONS: Our findings suggest that increased NOTCH2 via loss of miR-181c is a significant component of EEA recurrence. This presents an opportunity to develop miR-181c and NOTCH2 as markers for early identification of high risk cases and the use of NOTCH inhibitors in the prevention or treatment of recurrent disease.

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.

Tumor mutational analysis of GOG248, a phase II study of temsirolimus or temsirolimus and alternating megestrol acetate and tamoxifen for advanced endometrial cancer (EC): An NRG Oncology/Gynecologic Oncology Group study.

OBJECTIVE: Rapamycin analogs have reproducible but modest efficacy in endometrial cancer (EC). Identification of molecular biomarkers that predict benefit could guide clinical development. METHODS: Fixed primary tissue and whole blood were collected prospectively from patients enrolled on GOG 248. DNA was isolated from macro-dissected tumors and blood; next-generation sequence analysis was performed on a panel of cancer related genes. Associations between clinical outcomes [response rate (RR) 20%; progression-free survival (PFS) median 4.9months] and mutations (PTEN, PIK3CA, PIK3R1, KRAS, CTNNB1, AKT1, TSC1, TSC2, NF1, FBXW7) were explored. RESULTS: Sequencing data was obtained from tumors of 55 of the 73 enrolled pts. Mutation rates were consistent with published reports: mutations in PTEN (45%), PIK3CA (29%), PIK3R1 (24%), K-RAS (16%), CTNNB1 (18%) were common and mutations in AKT1 (4%), TSC1 (2%), TSC2 (2%), NF1 (9%) and FBXW7 (4%) were less common. Increased PFS (HR 0.16; 95% CI 0.01-0.78) and RR (response difference 0.83; 95% CI 0.03-0.99) were noted for AKT1 mutation. An increase in PFS (HR 0.46; 95% CI 0.20-0.97) but not RR (response difference 0.00, 95% CI -0.34-0.34) was identified for CTNNB1 mutation. Both patients with TSC mutations had an objective response. There were no statistically significant associations between mutations in PIK3CA, PTEN, PIK3R1, or KRAS and PFS or RR. CONCLUSIONS: Mutations in AKT1, TSC1 and TSC2 are rare, but may predict clinical benefit from temsirolimus. CTNNB1 mutations were associated with longer PFS on temsirolimus.

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.