We introduce a novel statistical approach that quantifies, for the first time, the amount of colocalization of two fluorescent-labeled proteins in an image automatically, removing the bias of visual interpretation. This is done by estimating simultaneously the maximum threshold of intensity for each color below which pixels do not show any statistical correlation. The sensitivity of the method was illustrated on simulated data by statistically confirming the existence of true colocalization in images with as little as 3% colocalization. This method was then tested on a large three-dimensional set of fixed cells cotransfected with CFP/YFP pairs of proteins that either co-compartmentalized, interacted, or were just randomly localized in the nucleolus. In this test, the algorithm successfully distinguished random color overlap from colocalization due to either co-compartmentalization or interaction, and results were verified by fluorescence resonance energy transfer. The accuracy and consistency of our algorithm was further illustrated by measuring, for the first time in live cells, the dissociation rate (k(d)) of the HIV-1 Rev/CRM1 export complex induced by the cytotoxin leptomycin B. Rev/CRM1 colocalization in nucleoli dropped exponentially after addition of leptomycin B at a rate of 1.25 x 10(-3) s(-1). More generally, this algorithm can be used to answer a variety of biological questions involving protein-protein interactions or co-compartmentalization and can be generalized to colocalization of more than two colors.

Purpose Within heterogeneous tumors, subpopulations often labeled cancer stem cells (CSCs) have been identified that have enhanced tumorigenicity and chemoresistance in ex vivo models. However, whether these populations are more capable of surviving chemotherapy in de novo tumors is unknown. Experimental Design We examined 45 matched primary/recurrent tumor pairs of high grade ovarian adenocarcinomas for expression of CSC markers ALDH1A1, CD44 and CD133 using immunohistochemistry. Tumors collected immediately after completion of primary therapy were then laser-capture microdissected and subjected to a quantitative PCR array examining stem cell biology pathways (Hedgehog, Notch, TGF-β and Wnt). Select genes of interest were validated as important targets using siRNA-mediated downregulation. Results Primary samples were composed of low densities of ALDH1A1, CD44 and CD133. Tumors collected immediately after primary therapy were more densely composed of each marker, while samples collected at first recurrence, before initiating secondary therapy, were composed of similar percentages of each marker as their primary tumor. In tumors collected from recurrent platinum-resistant patients, only CD133 was significantly increased. Of stem cell pathway members examined, 14% were significantly overexpressed in recurrent compared to matched primary tumors. Knockdown of genes of interest, including endoglin/CD105 and the hedgehog mediators Gli1 and Gli2, led to decreased ovarian cancer cell viability, with Gli2 demonstrating a novel contribution to cisplatin resistance. Conclusions These data indicate that ovarian tumors are enriched with CSCs and stem cell pathway mediators, especially at the completion of primary therapy. This suggests that stem cell subpopulations contribute to tumor chemoresistance and ultimately recurrent disease.

A cornerstone of preclinical cancer research has been the use of clonal cell lines. However, this resource has underperformed in its ability to effectively identify novel therapeutics and evaluate the heterogeneity in a patient's tumor. The patient-derived xenograft (PDX) model retains the heterogeneity of patient tumors, allowing a means to not only examine efficacy of a therapy, but also basic tenets of cancer biology in response to treatment. Herein we describe the development and characterization of an ovarian-PDX model in order to study the development of chemoresistance. We demonstrate that PDX tumors are not simply composed of tumor-initiating cells, but recapitulate the original tumor's heterogeneity, oncogene expression profiles, and clinical response to chemotherapy. Combined carboplatin/paclitaxel treatment of PDX tumors enriches the cancer stem cell populations, but persistent tumors are not entirely composed of these populations. RNA-Seq analysis of six pair of treated PDX tumors compared to untreated tumors demonstrates a consistently contrasting genetic profile after therapy, suggesting similar, but few, pathways are mediating chemoresistance. Pathways and genes identified by this methodology represent novel approaches to targeting the chemoresistant population in ovarian cancer

Ovarian cancer is the fifth most common cause of death due to cancer in women despite being the tenth in incidence. Unfortunately, the five-year survival rate is only 45%, which has not improved much in the past 30 years. Even though the majority of women have successful initial therapy, the low rate of survival is due to the eventual recurrence and succumbing to their disease. With the recent release of the Cancer Genome Atlas for ovarian cancer, it was shown that the PI3K/AKT/mTOR pathway was one of the most frequently mutated or altered pathways in patients’ tumors. Researching how the PI3K/AKT/mTOR pathway affects the progression and tumorigensis of ovarian cancer will hopefully lead to new therapies that will increase survival for women. This review focuses on recent research on the PI3K/AKT/mTOR pathway and its role in the progression and tumorigensis of ovarian cancer.