Emerging evidence implicates alterations in the RAB small GTPases and their associated regulatory proteins and effectors in multiple human diseases including cancer. We have recently shown that RAB25, located at chromosome 1q22, is amplified at the DNA level and overexpressed at the RNA level in ovarian and breast cancer. These changes correlated with a worsened outcome in both diseases. In addition, enforced expression of RAB25 in both breast and ovarian cancer cells decreased apoptosis and increased proliferation and aggressiveness in vivo, potentially explaining the worsened prognosis. A better understanding of genetic alterations as well as the physiologic and pathophysiologic roles of RAB GTPases may open new opportunities for therapeutic intervention and better outcomes. (Cancer Res 2005; 65 (7): 2516-9) Molecular Profiling and Identification of Genetic Defect in CancersCancer is caused by abnormalities in DNA sequence, copy number, rearrangements, or expression. The accumulation of multiple changes in critical genes within a single cell is required to escape from normal controls on cell growth and proliferation, allowing development into a clinically evident tumor (1). Understanding the molecular basis of tumorigenesis is the key to better diagnosis, prognosis, and treatment for cancer. Large-scale profiling of gene expression and genomic alterations has revealed multiple differences between normal and malignant cells, specific genetic and cellular changes that occur at each stage of tumor progression, and aberrations that can distinguish cancers of different origins and metastatic potential. This genome-wide information will facilitate the identification of new diagnostic markers, prognostic and predictive information, and novel molecular targets. This, in turn, will lead to the development, validation, and implementation of new, less toxic, and more effective drugs.Array comparative genomic hybridization (2) provides a robust, sensitive, and high-resolution approach to the identification of regions of DNA copy number increase and decrease in tumors. These copy number aberrations are selected during tumorigenesis, contributing to the behavior of tumors, and indeed can be predictive of patient outcome (3). Multiple chromosomal amplifications implicated in the pathophysiology of ovarian and breast carcinomas have been detected (4, 5). The identification of the candidate genes driving the development of the DNA copy number aberrations in cancer has progressed at a slow rate. However, new technologies are likely to increase the pace. We, for example, have extensively characterized an amplicon present in ovarian cancer on chromosome 3q, finding that the PIK3CA gene expressing the catalytic a subunit of phosphoinositide-3-kinase is amplified in ovarian cancer and is a critical regulator of different functions in ovarian cancer (6). This, along with other developments, has contributed to the phosphoinositide-3-kinase pathway being identified as a prime candidate for the development of novel therapies. R...
Many dynamical processes can be represented as directed attributed graphs or Petri nets where relationships between various entities are explicitly expressed. Signaling networks modeled as Petri nets are one class of such graphical modeling and representations. These networks encode how different protein in specific compartments, interact to create new protein products. Initially, the proteins and rules governing their interactions are curated from literature and then refined with experimental data. Variation in these networks occurs in topological structure, size, and weights associated on edges. Collectively, these variations are quite significant for manual and interactive analysis. Furthermore, as new information is added to these networks, the emergence of new computational models becomes paramount. From this perspective, hierarchical spectral methods are proposed and applied for inferring similarities and dissimilarities from an ensemble of graphs that corresponds to reaction networks. The technique has been implemented and tested on curated signaling networks that are derived for breast cancer cell lines.
Our research efforts focus on the identification and detection of fundamental molecular differences between normal and tumor cells in breast, as well as differences among distinct breast cancer subtypes, especially in terms of signal transduction pathways that control cell cycle, apoptosis and cell growth. Cancer subtype specific molecular variations dramatically affect patient responses to already existing treatments. For example, the phosphorylation status of many proteins that are involved in signal transduction pathways perturbed in cancer cells is extremely important in determining whether these cells are susceptible to killing by available cancer therapeutics. Therefore, differentially phosphorylated protein isoforms can be a particularly useful prognostic biomarker of drug response in the clinic. However, accurate detection and quantitative analysis of cancer-related phosphoproteins in tumors is limited by current technologies.Using a novel, fully automated nanocapillary electrophoresis technology (FireFlyTM) designed to separate protein molecules based on their isoelectric point (pI), we are currently developing highly sensitive assays for reliable assessment of the phosphorylation status of cancer-related phosphoproteins in tumors, before and during drug treatment. We have already developed and optimized assays measuring AKT1, AKT2, AKT3, ERK1 and ERK2, and their respective phosphoisoforms. Using these assays, we were able to measure levels of activated ERK1/2 and AKT1/2/3 in a breast cancer cell line panel developed in our lab, using protein extracted from as few as 125 cells. Based on RNA expression data, cell lines in this panel have previously been categorized in two distinct subtypes (Basal and Luminal) and their molecular phenotypes closely resemble the respective profiles of tumors obtained from breast cancer patients (CITATION). This cell line panel is extensively used to measure cellular responses to breast cancer therapeutics, including drugs that target MEK, ERK, PI3K and AKT. Using FireFly assays, we are currently measuring changes in the phosphorylation states of these targets during drug treatment, in order to completely characterize pharmacodynamic changes in these cells during treatment, and develop molecular profiles that predict response in breast cancer tumors. Since this technology enables accurate detection and quantification of protein isoforms and post-translational modifications from only very small amounts of tumor samples or serum, it promises to propel cancer biomarker discovery and enable the development of clinically useful prognostic and diagnostic assays that predict responses to drugs targeting cancer-specific molecular networks. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 3172.
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