Objective-We investigated risk factors for Type II (n = 176) vs. Type I (n = 1,576) endometrial cancer (EC)

The projected increase of EC over next 16 years indicates the need for close monitoring of EC trends.

Obesity is a well recognized risk factor for several types of cancers, many of which occur solely or disproportionately in women. Adipose tissue is a rich source of adipose-derived stem cells (ASC), which have received attention for their role in cancer behavior. The purpose of this systematic review is to present the existing literature on the role of ASCs in the growth, development, progression, and metastasis of cancer, with an emphasis on malignancies that primarily affect women. To accomplish this goal, the bibliographic database PubMed was systematically searched for articles published between 2001 and 2014 that address ASCs' relationship to human cancer. Thirty-seven articles on ASCs' role in human cancer were reviewed. Literature suggests that ASCs exhibit cancer-promoting properties, influence/are influenced by the tumor microenvironment, promote angiogenesis, and may be associated with pathogenic processes through a variety of mechanisms, such as playing a role in hypoxic tumor microenvironment. ASCs appear to be important contributors to tumor behavior, but research in areas specific to women's cancers, specifically endometrial cancer, is scarce. Also, because obesity continues to be a major health concern, it is important to continue research in this area to improve understanding of the impact adiposity has on cancer incidence. Cancer Res; 75(7); 1161-8. Ó2015 AACR.

Squamous cell carcinoma of the head and neck (SCCHN) is an aggressive disease that has been linked to altered immune, inflammatory, and angiogenesis responses. A better understanding of these aberrant responses might improve early detection and prognosis of SCCHN and provide novel therapeutic targets. Previous studies examined the role of multiplexed serum biomarkers in small cohorts or SCCHN sera. We hypothesized that an expanded panel comprised of multiple cytokines, chemokines, growth factors, and other tumor markers, which individually may show some promising correlation with disease status, might provide higher diagnostic power if used in combination. Thus, we evaluated a novel multianalyte LabMAP profiling technology that allows simultaneous measurement of multiple serum biomarkers. Concentrations of 60 cytokines, growth factors, and tumor antigens were measured in the sera of 116 SCCHN patients before treatment (active disease group), 103 patients who were successfully treated (no evidence of disease group), and 117 smoker controls without evidence of cancer. The multimarker panel offering the highest diagnostic power was comprised of 25 biomarkers, including epidermal growth factor, epidermal growth factor receptor, interleukin (IL)-8, tissue plasminogen activator inhibitor-1, A-fetoprotein, matrix metalloproteinase-2, matrix metalloproteinase-3, IFN-A, IFN-;, IFN-inducible protein-10, regulated on activation, normal T-cell expressed and secreted (RANTES), macrophage inflammatory protein-1A, IL-7, IL-17, IL-1 receptor-A, IL-2 receptor, granulocyte colony-stimulating factor, mesothelin, insulin-like growth factor binding protein 1, E-selectin, cytokeratin-19, vascular cell adhesion molecule, and cancer antigen-125. Statistical analysis using an ADE algorithm resulted in a sensitivity of 84.5%, specificity of 98%, and 92% of patients in the active disease group correctly classified from a cross-validation serum set. The data presented show that simultaneous testing using a multiplexed panel of serum biomarkers may present a promising new approach for the early detection of head and neck cancer.

Background-In most studies, circulating biomarkers are usually assessed from a single sample, assuming that this single measurement represents the long-term biomarker status of the individual.Such an assumption is rarely tested although it may not be valid for all biomarkers. The objective of this study was to investigate the temporal reproducibility of a panel of cytokines and growth factors.Methods-Thirty-five postmenopausal women with two annual visits and 30 premenopausal women with three annual visits were randomly selected from the participants in an existing prospective cohort. A total of 23 serum cytokines, nine growth factors and C-reactive protein (CRP) were measured using the Luminex xMap™ technology. In addition, for eight biomarkers, regular and high sensitivity (hs) assays were compared.Results-The biomarkers with adequate (>60%) detection rates and acceptable (≥0.55) intra-class correlation coefficients (ICCs) were: hsIL-1β, IL-1RA, hsIL-2, hsIL-4, hsIL-5, hsIL-6, hsIL-10, IL-12p40, hsIL-12p70, hsTNF-α, TNF-R1, TNF-R2, CRP, HGF, NGF, and EGFR. The remaining biomarkers either had low temporal reproducibility or were undetectable in more than 40% of samples. Conclusions-The results suggest that 16 of the 41 biomarkers measured with Luminex technology showed sufficient sensitivity and temporal reproducibility in sera.

Findings of this study may form a foundation for the growing corpus of knowledge explaining the outcome differences in treatment of patients with metastatic breast cancer, potentially helping to create tailored counseling and personalized treatment approaches for this vulnerable group.

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Objective-Endometrial carcinoma is the most common gynecologic cancer. Although the prognosis for endometrial cancer is generally good, cancers identified at late stages are associated with high levels of morbidity and mortality. Therefore, prevention and early detection may further reduce the burden of this challenging disease.Methods-A panel of 64 serum biomarkers was analyzed in sera of patients with stages I-III endometrial cancer and age-matched healthy women, utilizing a multiplex xMAP ™ bead-based immunoassay. For multivariate analysis, four different statistical classification methods were used: logistic regression (LR), separating hyperplane (SHP), k nearest neighbors (KNN), and Classification Tree (CART). For each of these classifiers a diagnostic model was created, based on the crossvalidation set consisting of sera from 115 patients with endometrial cancer and 135 healthy women.Results-Our data have demonstrated that patients with endometrial cancer have significantly different expression patterns of several serum biomarkers as compared to healthy controls. Prolactin was the strongest discriminative biomarker for endometrial cancer providing 98.3% sensitivity and 98.0% specificity alone. Our results have revealed that serum concentration of cancer antigens, including CA 125, CA 15-3, and CEA are higher in patients with Stage III endometrial cancer as compared to those with Stage I. In addition, we have shown that the expression of CA 125, AFP and ACTH is elevated in women with tumor grade 3 vs. grade 1. Furthermore, 5-biomarker panel Requests for reprints: Anna Lokshin, University of Pittsburgh Cancer Institute, Hillman Cancer Center, 5117 Centre Ave., Pittsburgh, PA 15213. Phone: 412-623-7706; Fax: 412-623-1415; E-mail: lokshina@pitt.edu. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. (prolactin, GH, Eotaxin, E-selectin, and TSH) identified in this study, was able to discriminate endometrial cancer from ovarian and breast cancers with high sensitivity and specificity. NIH Public AccessConclusions-The ability of prolactin to accurately discriminate between cancer and control groups indicates that this biomarker could potentially be used for development of blood-based test for the early detection of endometrial cancer in high-risk populations. Combining the information on multiple serum markers using flexible statistical methods allows for achieving high cancer selectivity.