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2.  The Cancer Genome Atlas Pan-Cancer Analysis Project 
Nature genetics  2013;45(10):1113-1120.
Cancer can take hundreds of different forms depending on the location, cell of origin and spectrum of genomic alterations that promote oncogenesis and affect therapeutic response. Although many genomic events with direct phenotypic impact have been identified, much of the complex molecular landscape remains incompletely charted for most cancer lineages. For that reason, The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumours to discover molecular aberrations at the DNA, RNA, protein, and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences, and emergent themes across tumour lineages. The Pan-Cancer initiative compares the first twelve tumour types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumour types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile.
PMCID: PMC3919969  PMID: 24071849
3.  Resistance to BRAF inhibition in BRAF-mutant colon cancer can be overcome with PI3K inhibition or demethylating agents 
Vemurafenib, a selective inhibitor of BRAFV600 has shown significant activity in BRAFV600 melanoma, but not in the <10% of metastatic BRAFV600 colorectal cancers (CRC), suggesting that studies of the unique hypermethylated phenotype and concurrent oncogenic activation of BRAFmut CRC may provide combinatorial strategies
Experimental Design
We performed comparative proteomic analysis of BRAFV600E melanoma and CRC cell lines, followed by correlation of PI3K pathway activation and sensitivity to the vemurafenib-analog PLX-4720. Pharmacologic inhibitors and siRNA were used in combination with PLX4720 to inhibit PI3K and methyltrasnferase in cell lines and murine models.
Compared to melanoma, CRC lines demonstrate higher levels of PI3K/AKT pathway activation. CRC cell lines with mutations in PTEN or PIK3CA were less sensitive to growth inhibition by PLX4720 (P=0.03), and knockdown of PTEN expression in sensitive CRC cells reduced growth inhibition by the drug. Combined treatment of PLX4720 with PI3K inhibitors caused synergistic growth inhibition in BRAF-mutant CRC cells with both primary and secondary resistance. In addition, methyltransferase inhibition was synergistic with PLX4720 and decreased AKT activation. In vivo, PLX4720 combined with either inhibitors of AKT or methyltransferase demonstrated greater tumor growth inhibition than PLX4720 alone. Clones with acquired resistance to PLX4720 in vitro demonstrated PI3K/AKT activation with EGFR or KRAS amplification.
We demonstrate that activation of the PI3K/AKT pathway is a mechanism of both innate and acquired resistance to BRAF inhibitors in BRAFV600E CRC, and suggest combinatorial approaches to improve outcomes in this poor prognosis subset of patients.
PMCID: PMC3563727  PMID: 23251002
BRAF; colon cancer; resistance; PI3K; vemurafenib; PLX4720
4.  Agents that Stabilize Mutated von Hippel Lindau Protein Result in Differential Post-Translational Modification and Subcellular Localization 
Journal of biomolecular screening  2012;17(5):572-580.
von Hippel Lindau (VHL) disease is an autosomal dominant inherited disorder that results in multiple organ systems being affected. Treatment is mainly surgical, however, effective systemic therapies are needed. We developed and tested a cell-based screening tool to identify compounds that stabilize or upregulate full-length, point mutated VHL.
The 786-0 cell line was infected with full-length W117A mutated VHL linked to a C-terminal Venus fluorescent protein. This VHL-W117A-Venus line was used to screen the Prestwick drug library and was tested against the known proteasome inhibitors MG132 and bortezomib. Western blot validation and evaluation of downstream functional readouts, including HIF and GLUT1 levels, were performed.
Bortezomib, MG132, and the Prestwick compounds 8-azaguanine, thiostrepton and thioguanosine were found to reliably upregulate VHL-W117A-Venus in 786-0 cells. 8-azaguanine was found to downregulate HIF2α levels, and was augmented by the presence of VHL W117A. VHL p30 band intensities varied as a function of compound used, suggesting alternate post-translational processing. In addition, nuclear-cytoplasmic localization of pVHL varied amongst the different compounds.
786-0 cells containing VHL-W117A-Venus can be successfully used to identify compounds that upregulate VHL levels, and that have a differential effect on pVHL intracellular localization and posttranslational processing. Further screening efforts will broaden the number of pharmacophores available to develop therapeutic agents that will upregulate and refunctionalize mutated VHL.
PMCID: PMC3895461  PMID: 22357874
VHL upregulation; proteostasis; high-throughput screen; Prestwick
5.  Frequency of MET and PIK3CA copy number elevation and correlation with outcome in early stage breast cancer 
Cancer  2012;119(1):7-15.
To determine the frequency and association with relapse-free survival (RFS) of MET and PIK3CA copy number elevations in early stage breast cancer.
Tumor DNA was extracted from 971 formalin-fixed paraffin-embedded early breast cancers for molecular inversion probes arrays. Data was segmented using the SNP-FASST2 segmentation algorithm. Copy number gains were called when copy number of each segment was greater than 2.3 or 1.7 respectively. RFS was estimated by Kaplan-Meier. Cox proportional hazards models were fit to determine independent associations of copy number with RFS.
82 (8.44%) and 134 (13.8%) of tumors had MET or PIK3CA copy number elevation respectively, and 25.6% with MET copy number elevation had PIK3CA copy number elevation. Patients with either MET or PI3KCA high copy number tended to have poorer prognostic features (larger tumor size, higher grade, and hormone receptor negativity), Both, MET and PIK3CA high copy number were more likely to occur in triple negative disease (P=0.019 and <0.001, respectively). At a median follow-up of 7.4 years, there were 252 recurrences. Five-year RFS were 63.5%, and 83.1% for MET high copy number and MET normal/low copy number respectively, (P=0.06); and 73.1%, and 82.3% for PIK3CA high copy number and PIK3CA normal/low copy number respectively, (P=0.15). High copy number for either gene was not an independent predictor of RFS.
High copy number of MET or PIK3CA was associated with poorer prognostic features and triple negative disease. Co-amplification was frequent. Patients with high MET copy number tumors tended to have a worst RFS.
PMCID: PMC3461089  PMID: 22736407
MET; PIK3CA; gene copy number; breast cancer; prognosis
6.  High stearoyl-CoA desaturase 1 expression is associated with shorter survival in breast cancer patients 
Stearoyl-CoA desaturase 1 (SCD1) is an essential regulator of fatty acid synthesis. We have previously shown that overexpression of SCD1 increases the growth of breast cancer cell lines. The purpose of this study was to determine the relationship between SCD1 expression level and clinical-pathologic characteristics and survival of patients with breast cancer. Fine-needle aspirates were collected from the primary tumors of 250 patients with stage I–III breast cancer. Demographic and clinical characteristics including patient age, ethnicity, and menopausal status and tumor clinical stage, grade, and subtype were reviewed. SCD1 expression was analyzed using reverse-phase protein arrays. Samples were divided into high or low SCD1 expression levels based on a cut-off determined from martingale residual plots and regression tree analysis. SCD1 levels were significantly higher in tumors from patients >50 years old compared to patients ≤50 years old and were lower in triple-negative (estrogen/progesterone receptor-negative and human epidermal growth factor receptor-2-negative) breast cancers than other tumor subtypes. After adjusting for patient age, tumor subtype, tumor grade, and clinical stage, we found that patients with primary breast cancers expressing high SCD1 levels had significantly shorter relapse-free survival (RFS) (P = 0.014) and overall survival (OS) (P = 0.039) in multivariable analysis. We conclude that SCD1 expression varies by breast cancer subtype and that high levels of SCD1 expression are associated with significantly shorter RFS and OS in multivariable analysis. Future studies are needed to define the role of SCD1 in the malignant phenotype of breast cancer and to evaluate the potential for SCD1 as a therapeutic target.
PMCID: PMC3556743  PMID: 23208590
Breast neoplasms; Fatty acid metabolism; Stearoyl-CoA desaturase; Survival; Protein array analysis
8.  Rab25 in Cancer: A brief update 
Biochemical Society transactions  2012;40(6):1404-1408.
PMCID: PMC3804249  PMID: 23176489
9.  Inferring tumour purity and stromal and immune cell admixture from expression data 
Nature Communications  2013;4:2612.
Infiltrating stromal and immune cells form the major fraction of normal cells in tumour tissue and not only perturb the tumour signal in molecular studies but also have an important role in cancer biology. Here we describe ‘Estimation of STromal and Immune cells in MAlignant Tumours using Expression data’ (ESTIMATE)—a method that uses gene expression signatures to infer the fraction of stromal and immune cells in tumour samples. ESTIMATE scores correlate with DNA copy number-based tumour purity across samples from 11 different tumour types, profiled on Agilent, Affymetrix platforms or based on RNA sequencing and available through The Cancer Genome Atlas. The prediction accuracy is further corroborated using 3,809 transcriptional profiles available elsewhere in the public domain. The ESTIMATE method allows consideration of tumour-associated normal cells in genomic and transcriptomic studies. An R-library is available on
Tumour biopsies contain contaminating normal cells and these can influence the analysis of tumour samples. In this study, Yoshihara et al. develop an algorithm based on gene expression profiles from The Cancer Genome Atlas to estimate the number of contaminating normal cells in tumour samples.
PMCID: PMC3826632  PMID: 24113773
10.  Repurposing the Pap Smear: One Step Closer to Gynecologic Cancer Screening 
Science translational medicine  2013;5(167):10.1126/scitranslmed.3005411.
PMCID: PMC3824959  PMID: 23303602
11.  cMET and phospho-cMET protein levels in breast cancers and survival outcomes 
To evaluate cMET and phospho-cMET (p-cMET) levels in breast cancer subtypes and its impact on survival outcomes.
Experimental Design
We measured protein levels of cMET and p-cMET in 257 breast cancers using reverse phase protein array. Regression tree method and Martingale residual plots were applied to find best cutoff point for high and low levels. Kaplan-Meier survival curves were used to estimate relapse-free (RFS) and overall (OS) survival. Cox proportional hazards models were fit to determine associations of cMET/p-cMET with outcomes after adjustment for other characteristics.
Median age was 51years. There were 140 (54.5%) hormone receptor (HR)-positive, 53 (20.6%) HER2-positive and 64 (24.9%) triple-negative tumors. Using selected cutoffs, 181 (70.4%) and 123 (47.9%) cancers had high levels of cMET and p-cMET, respectively. There were no significant differences in mean expression of cMET (P<0.128) and p-cMET (P<0.088) by breast cancer subtype. Dichotomized cMET and p-cMET level was a significant prognostic factor for RFS (HR:2.44,95%CI:1.34-4.44,P=0.003 and HR:1.64,95%CI:1.04-2.60,P=0.033) and OS (HR:3.18,95%CI:1.43-7.11,P=0.003 and HR:1.92,95% CI:1.08-3.44,P=0.025). Within breast cancer subtypes, high cMET levels were associated with worse RFS (P=0.014) and OS (P=0.006) in HR-positive tumors, and high p-cMET levels were associated with worse RFS (P=0.019) and OS (P=0.014) in HER2-positive breast cancers. In multivariable analysis patients with high cMET had a significantly higher risk of recurrence (HR:2.06; 95%CI:1.08-3.94,P=0.028) and death (HR:2.81; 95%CI:1.19-6.64,P=0.019). High p-cMET level was associated with higher risk of recurrence (HR:1.79,95%CI 1.08-2.95.77,P=0.020).
High levels of cMET and p-cMET were seen in all breast cancer subtypes and correlated with poor prognosis.
PMCID: PMC3821167  PMID: 22374333
cMET; phospho-cMET; breast cancer prognosis; breast cancer subtype
12.  AMPK-Mediated Phosphorylation of Murine p27 at T197 Promotes Binding of 14-3-3 Proteins and Increases p27 Stability 
Molecular carcinogenesis  2010;49(5):10.1002/mc.20613.
The Tuberous Sclerosis Complex 2 (TSC2) gene product, tuberin, acts as a negative regulator of mTOR signaling, and loss of tuberin function leads to tumors of the brain, skin, kidney, heart and lungs. Previous studies have shown that loss of tuberin function affects the stability and subcellular localization of the cyclin-dependent kinase inhibitor (CKI) p27, although the mechanism(s) by which tuberin modulates p27 stability have not been elucidated. Previous studies have also shown that AMPK, which functions in an energy-sensing pathway in the cell, becomes activated in the absence of tuberin. Here we show that in Tsc2-null tumors and cell lines, AMPK activation correlates with an increase in p27 levels, and inhibition of AMPK signaling decreases p27 levels in these cells. In addition, activation of AMPK led to phosphorylation of p27 at the conserved terminal threonine residue of murine p27 (T197) in both in vitro kinase assays and in cells. Phosphorylation of p27 at T197 led to increased interaction between p27 and 14-3-3 proteins and increased the protein stability of p27. Furthermore, activation of AMPK signaling promoted the interaction between p27 and 14-3-3 proteins and increased the stability of the p27 protein in a manner that was dependent on T197. These data identify a conserved mechanism for regulation of p27 stability via phosphorylation at the terminal threonine (mT197/hT198), which when AMPK is activated, results in stabilization of the p27 protein.
PMCID: PMC3818129  PMID: 20146253
Tuberous sclerosis complex; TSC2; energy sensing
13.  Bayesian Inference of Signaling Network Topology in a Cancer Cell Line 
Bioinformatics  2012;28(21):2804-2810.
Motivation: Protein signaling networks play a key role in cellular function, and their dysregulation is central to many diseases, including cancer. To shed light on signaling network topology in specific contexts, such as cancer, requires interrogation of multiple proteins through time and statistical approaches to make inferences regarding network structure.
Results: In this study, we use dynamic Bayesian networks to make inferences regarding network structure and thereby generate testable hypotheses. We incorporate existing biology using informative network priors, weighted objectively by an empirical Bayes approach, and exploit a connection between variable selection and network inference to enable exact calculation of posterior probabilities of interest. The approach is computationally efficient and essentially free of user-set tuning parameters. Results on data where the true, underlying network is known place the approach favorably relative to existing approaches. We apply these methods to reverse-phase protein array time-course data from a breast cancer cell line (MDA-MB-468) to predict signaling links that we independently validate using targeted inhibition. The methods proposed offer a general approach by which to elucidate molecular networks specific to biological context, including, but not limited to, human cancers.
Availability: (code and data).
Supplementary information: Supplementary data are available at Bioinformatics online.
PMCID: PMC3476330  PMID: 22923301
14.  Mechanistic Basis for Overcoming Platinum Resistance Using Copper Chelating Agents 
Molecular cancer therapeutics  2012;11(11):2483-2494.
Platinum (Pt)-based antitumor agents are widely used in cancer chemotherapy. Drug resistance is a major obstacle to the successful use of these agents because once drug resistance develops, other effective treatment options are limited. Recently, we have conducted a clinical trial using a copper (Cu)-lowering agent to overcome Pt drug resistance in ovarian cancer patients and the preliminary results are encouraging. In supporting this clinical study, using three pairs of cisplatin (cDDP)-resistant cell lines and two ovarian cancer cell lines derived from patients who had failed in Pt-based chemotherapy, we demonstrated that cDDP resistance associated with reduced expression of the high affinity copper transporter (hCtr1) which is also a cDDP transporter, can be preferentially re-sensitized by copper-lowering agents due to enhanced hCtr1 expression, as compared with their drug-sensitive counterparts. Such a preferential induction of hCtr1 expression in cDDP-resistant variants by Cu chelation can be explained by the mammalian Cu homeostasis regulatory mechanism. Enhanced cell-killing efficacy by a Cu-lowering agent was also observed in animal xenografts bearing cDDP-resistant cells. Finally, by analyzing a public gene expression dataset, we found that ovarian cancer patients with elevated levels of hCtr1 in their tumors, but not ATP7A and ATP7B, had more favorable outcomes after Pt-drug treatment than those expressing low hCtr1 levels. This study reveals the mechanistic basis for using Cu chelation to overcome cDDP resistance in clinical investigations.
PMCID: PMC3496003  PMID: 22914438
Cisplatin; high-affinity copper transporter; Cu-lowering agents; drug-resistance
15.  CanDrA: Cancer-Specific Driver Missense Mutation Annotation with Optimized Features 
PLoS ONE  2013;8(10):e77945.
Driver mutations are somatic mutations that provide growth advantage to tumor cells, while passenger mutations are those not functionally related to oncogenesis. Distinguishing drivers from passengers is challenging because drivers occur much less frequently than passengers, they tend to have low prevalence, their functions are multifactorial and not intuitively obvious. Missense mutations are excellent candidates as drivers, as they occur more frequently and are potentially easier to identify than other types of mutations. Although several methods have been developed for predicting the functional impact of missense mutations, only a few have been specifically designed for identifying driver mutations. As more mutations are being discovered, more accurate predictive models can be developed using machine learning approaches that systematically characterize the commonality and peculiarity of missense mutations under the background of specific cancer types. Here, we present a cancer driver annotation (CanDrA) tool that predicts missense driver mutations based on a set of 95 structural and evolutionary features computed by over 10 functional prediction algorithms such as CHASM, SIFT, and MutationAssessor. Through feature optimization and supervised training, CanDrA outperforms existing tools in analyzing the glioblastoma multiforme and ovarian carcinoma data sets in The Cancer Genome Atlas and the Cancer Cell Line Encyclopedia project.
PMCID: PMC3813554  PMID: 24205039
16.  Biomarkers of Response to Akt Inhibitor MK-2206 in Breast Cancer 
We tested the hypothesis that allosteric Akt inhibitor MK-2206 inhibits tumor growth, and that PTEN/PIK3CA mutations confer MK-2206 sensitivity.
Experimental Design
MK-2206 effects on cell signaling were assessed in vitro and in vivo. Its antitumor efficacy was assessed in vitro in a panel of cancer cell lines with differing PIK3CA and PTEN status. Its in vivo efficacy was tested as a single agent and in combination with paclitaxel.
MK-2206 inhibited Akt signaling and cell-cycle progression, and increased apoptosis in a dose-dependent manner in breast cancer cell lines. Cell lines with PTEN or PIK3CA mutations were significantly more sensitive to MK-2206; however, several lines with PTEN/PIK3CA mutations were MK-2206 resistant. siRNA knockdown of PTEN in breast cancer cells increased Akt phosphorylation concordant with increased MK-2206 sensitivity. Stable transfection of PIK3CA E545K or H1047R mutant plasmids into normal-like MCF10A breast cells enhanced MK-2206 sensitivity. Cell lines that were less sensitive to MK-2206 had lower ratios of Akt1/Akt2 and had less growth inhibition with Akt siRNA knockdown. In PTEN-mutant ZR75-1 breast cancer xenografts, MK-2206 treatment inhibited Akt signaling, cell proliferation, and tumor growth. In vitro, MK-2206 showed a synergistic interaction with paclitaxel in MK-2206–sensitive cell lines, and this combination had significantly greater antitumor efficacy than either agent alone in vivo.
MK-2206 has antitumor activity alone and in combination with chemotherapy. This activity may be greater in tumors with PTEN loss or PIK3CA mutation, providing a strategy for patient enrichment in clinical trials.
PMCID: PMC3772348  PMID: 22932669
17.  Network inference using steady-state data and Goldbeter–koshland kinetics 
Bioinformatics  2012;28(18):2342-2348.
Motivation: Network inference approaches are widely used to shed light on regulatory interplay between molecular players such as genes and proteins. Biochemical processes underlying networks of interest (e.g. gene regulatory or protein signalling networks) are generally nonlinear. In many settings, knowledge is available concerning relevant chemical kinetics. However, existing network inference methods for continuous, steady-state data are typically rooted in statistical formulations, which do not exploit chemical kinetics to guide inference.
Results: Herein, we present an approach to network inference for steady-state data that is rooted in non-linear descriptions of biochemical mechanism. We use equilibrium analysis of chemical kinetics to obtain functional forms that are in turn used to infer networks using steady-state data. The approach we propose is directly applicable to conventional steady-state gene expression or proteomic data and does not require knowledge of either network topology or any kinetic parameters. We illustrate the approach in the context of protein phosphorylation networks, using data simulated from a recent mechanistic model and proteomic data from cancer cell lines. In the former, the true network is known and used for assessment, whereas in the latter, results are compared against known biochemistry. We find that the proposed methodology is more effective at estimating network topology than methods based on linear models.
Supplementary Information: Supplementary data are available at Bioinformatics online.
PMCID: PMC3436851  PMID: 22815361
18.  Detection Algorithm for the Validation of Human Cell Lines 
Cell lines are an important tool in understanding all aspects of cancer growth, development, metastasis, and tumor cell death. There has been a dramatic increase in the number of cell lines and diversity of the cancers they represent; however, misidentification and cross-contamination of cell lines can lead to erroneous conclusions. One method that has gained favor for authenticating cell lines is the use of short tandem repeats (STR) to generate a unique DNA profile. The challenge in validating cell lines is the requirement to compare the large number of existing STR profiles against cell lines of interest, particularly when considering that the profiles of many cell lines have drifted over time and original samples are not available. We report here methods that analyze the variations and the proportional changes extracted from tetra-nucleotide repeat regions in the STR analysis. This technique allows a paired match between a target cell line and a reference database of cell lines to find cell lines that match within a user designated percentage cut-off quality matrix. Our method accounts for DNA instability and can suggest whether the target cell lines are misidentified or unstable.
PMCID: PMC3772516  PMID: 22419365
Short Tandem Repeat (STR); Cell Line Validation
19.  Targeting the Hepatocyte Growth Factor–cMET Axis in Cancer Therapy 
Journal of Clinical Oncology  2012;30(26):3287-3296.
The hepatocyte growth factor (HGF) and its receptor, the transmembrane tyrosine kinase cMET, promote cell proliferation, survival, motility, and invasion as well as morphogenic changes that stimulate tissue repair and regeneration in normal cells but can be co-opted during tumor growth. MET overexpression, with or without gene amplification, has been reported in a variety of human cancers, including breast, lung, and GI malignancies. Furthermore, high levels of HGF and/or cMET correlate with poor prognosis in several tumor types, including breast, ovarian, cervical, gastric, head and neck, and non–small-cell lung cancers. Gene amplification and protein overexpression of cMET drive resistance to epidermal growth factor receptor family inhibitors, both in preclinical models and in patients. It is increasingly apparent that the HGF-cMET axis signaling network is complex, and rational combinatorial therapy is needed for optimal clinical efficacy. Better understanding of HGF-cMET axis signaling and the mechanism of action of HGF-cMET inhibitors, along with the identification of biomarkers of response and resistance, will lead to more effective targeting of this pathway for cancer therapy.
PMCID: PMC3434988  PMID: 22869872
20.  BSTA Promotes mTORC2-Mediated Phosphorylation of Akt1 to Suppress Expression of FoxC2 and Stimulate Adipocyte Differentiation 
Science signaling  2013;6(257):ra2.
Phosphorylation and activation of Akt1 is a crucial signaling event that promotes adipogenesis. However, neither the complex multistep process that leads to activation of Akt1 through phosphorylation at Thr308 and Ser473 nor the mechanism by which Akt1 stimulates adipogenesis is fully understood. We found that the BSD domain–containing signal transducer and Akt interactor (BSTA) promoted phosphorylation of Akt1 at Ser473 in various human and murine cells, and we uncovered a function for the BSD domain in BSTA-Akt1 complex formation. The mammalian target of rapamycin complex 2 (mTORC2) facilitated the phosphorylation of BSTA and its association with Akt1, and the BSTA-Akt1 interaction promoted the association of mTORC2 with Akt1 and phosphorylation of Akt1 at Ser473 in response to growth factor stimulation. Furthermore, analyses of bsta gene-trap murine embryonic stem cells revealed an essential function for BSTA and phosphorylation of Akt1 at Ser473 in promoting adipocyte differentiation, which required suppression of the expression of the gene encoding the transcription factor FoxC2. These findings indicate that BSTA is a molecular switch that promotes phosphorylation of Akt1 at Ser473 and reveal an mTORC2-BSTA-Akt1-FoxC2–mediated signaling mechanism that is critical for adipocyte differentiation.
PMCID: PMC3748614  PMID: 23300339
21.  Regulation of the Hippo-YAP pathway by G-protein coupled receptor signaling 
Cell  2012;150(4):780-791.
The Hippo pathway is crucial in organ size control and its dysregulation contributes to tumorigenesis. However, upstream signals that regulate the mammalian Hippo pathway have remained elusive. Here we report that the Hippo pathway is regulated by G-protein coupled receptor (GPCR) signaling. Serum-borne lysophosphatidic acid (LPA) and sphingosine 1-phosphophate (S1P) act through G12/13-coupled receptors to inhibit the Hippo pathway kinases Lats1/2 thereby activating YAP and TAZ transcription co-activators, which are oncoproteins repressed by Lats1/2. YAP and TAZ are involved in LPA-induced gene expression, cell migration, and proliferation. In contrast, stimulation of Gs-coupled receptors by glucagon or epinephrine activates Lats1/2 kinase activity, thereby inhibiting YAP function. Thus, GPCR signaling can either activate or inhibit the Hippo-YAP pathway depending on the coupled G-protein. Our study identifies extracellular diffusible signals that modulate the Hippo pathway and also establishes the Hippo-YAP pathway as a critical signaling branch downstream of GPCR.
PMCID: PMC3433174  PMID: 22863277
22.  Predicting time to ovarian carcinoma recurrence using protein markers 
The Journal of Clinical Investigation  2013;123(9):3740-3750.
Patients with ovarian cancer are at high risk of tumor recurrence. Prediction of therapy outcome may provide therapeutic avenues to improve patient outcomes. Using reverse-phase protein arrays, we generated ovarian carcinoma protein expression profiles on 412 cases from TCGA and constructed a PRotein-driven index of OVARian cancer (PROVAR). PROVAR significantly discriminated an independent cohort of 226 high-grade serous ovarian carcinomas into groups of high risk and low risk of tumor recurrence as well as short-term and long-term survivors. Comparison with gene expression–based outcome classification models showed a significantly improved capacity of the protein-based PROVAR to predict tumor progression. Identification of protein markers linked to disease recurrence may yield insights into tumor biology. When combined with features known to be associated with outcome, such as BRCA mutation, PROVAR may provide clinically useful predictions of time to tumor recurrence.
PMCID: PMC3754259  PMID: 23945238
23.  Genomic amplicons target vesicle recycling in breast cancer 
The Journal of Clinical Investigation  2009;119(8):2123-2127.
Aberrant endocytosis, vesicle targeting, and receptor recycling represent emerging hallmarks of cancer. In this issue of the JCI, Zhang and colleagues demonstrate that RAB-coupling protein (RCP; also known as RAB11FIP1) is a “driver” of the 8p11–12 amplicon in human breast cancer and mouse xenograft models of mammary carcinogenesis (see the related article beginning on page 2171). Their finding that RAB GTPase function enables genomic amplification to confer aggressiveness to mammary tumors adds significantly to the body of evidence supporting pivotal roles for receptor trafficking in the proliferation and metastasis of cancer.
PMCID: PMC2719927  PMID: 19620778
24.  Lysophosphatidic Acid Receptors Determine Tumorigenicity and Aggressiveness of Ovarian Cancer Cells 
Lysophosphatidic acid (LPA) acts through the cell surface G protein–coupled receptors, LPA1, LPA2, or LPA3, to elicit a wide range of cellular responses. It is present at high levels in intraperitoneal effusions of human ovarian cancer increasing cell survival, proliferation, and motility as well as stimulating production of neovascularizing factors. LPA2 and LPA3 and enzymes regulating the production and degradation of LPA are aberrantly expressed by ovarian cancer cells, but the consequences of these expression changes in ovarian cancer cells were unknown.
Expression of LPA1, LPA2, or LPA3 was inhibited or increased in ovarian cancer cells using small interfering RNAs (siRNAs) and lentivirus constructs, respectively. We measured the effects of changes in LPA receptor expression on cell proliferation (by crystal violet staining), cell motility and invasion (using Boyden chambers), and cytokines (interleukin 6 [IL-6], interleukin 8 [IL-8], and vascular endothelial growth factor [VEGF]) production by enzyme-linked immunosorbent assay. The role of LPA receptors in tumor growth, ascites formation, and cytokine production was assessed in a mouse xenograft model. All statistical tests were two-sided.
SKOV-3 cells with increased expression of LPA receptors showed increased invasiveness, whereas siRNA knockdown inhibited both migration (P < .001, Student t test) and invasion. Knockdown of the LPA2 or LPA3 receptors inhibited the production of IL-6, IL-8, and VEGF in SKOV-3 and OVCAR-3 cells. SKOV-3 xenografts expressing LPA receptors formed primary tumors of increased size and increased ascites volume. Invasive tumors in the peritoneal cavity occurred in 75% (n = 4) of mice injected with LPA1 expressing SKOV-3 and 80% (n = 5) of mice injected with LPA2 or LPA3 expressing SKOV-3 cells. Metastatic tumors expressing LPA1, LPA2, and LPA3 were identified in the liver, kidney, and pancreas; tumors expressing LPA2 and LPA3 were detected in skeletal muscle; and tumors expressing LPA2 were also found in the cervical lymph node and heart. The percent survival of mice with tumors expressing LPA2 or LPA3 was reduced in comparison with animals with tumors expressing β-galactosidase.
Expression of LPA2 or LPA3 during ovarian carcinogenesis contributes to ovarian cancer aggressiveness, suggesting that the targeting of LPA production and action may have potential for the treatment of ovarian cancer.
PMCID: PMC2720766  PMID: 19001604
25.  Correction: Systematic Identification of Combinatorial Drivers and Targets in Cancer Cell Lines 
PLoS ONE  2013;8(5):10.1371/annotation/85d86c29-4ba6-4bf0-94f6-2977b3e1c792.
PMCID: PMC3646664

Results 1-25 (156)