Publications by authors named "James E Korkola"

47 Publications

Enzalutamide response in a panel of prostate cancer cell lines reveals a role for glucocorticoid receptor in enzalutamide resistant disease.

Sci Rep 2020 12 10;10(1):21750. Epub 2020 Dec 10.

Department of Biomedical Engineering, Oregon Health & Science University, 2730 SW Moody Ave CLSB Rm 3N018, Portland, OR, 97201, USA.

Representative in vitro model systems that accurately model response to therapy and allow the identification of new targets are important for improving our treatment of prostate cancer. Here we describe molecular characterization and drug testing in a panel of 20 prostate cancer cell lines. The cell lines cluster into distinct subsets based on RNA expression, which is largely driven by functional Androgen Receptor (AR) expression. KLK3, the AR-responsive gene that encodes prostate specific antigen, shows the greatest variability in expression across the cell line panel. Other common prostate cancer associated genes such as TMPRSS2 and ERG show similar expression patterns. Copy number analysis demonstrates that many of the most commonly gained (including regions containing TERC and MYC) and lost regions (including regions containing TP53 and PTEN) that were identified in patient samples by the TCGA are mirrored in the prostate cancer cell lines. Assessment of response to the anti-androgen enzalutamide shows a distinct separation of responders and non-responders, predominantly related to status of wild-type AR. Surprisingly, several AR-null lines responded to enzalutamide. These AR-null, enzalutamide-responsive cells were characterized by high levels of expression of glucocorticoid receptor (GR) encoded by NR3C1. Treatment of these cells with the anti-GR agent mifepristone showed that they were more sensitive to this drug than enzalutamide, as were several of the enzalutamide non-responsive lines. This is consistent with several recent reports that suggest that GR expression is an alternative signaling mechanism that can bypass AR blockade. This study reinforces the utility of large cell line panels for the study of cancer and identifies several cell lines that represent ideal models to study AR-null cells that have upregulated GR to sustain growth.
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http://dx.doi.org/10.1038/s41598-020-78798-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7729982PMC
December 2020

Cellular senescence in cancer: from mechanisms to detection.

Mol Oncol 2020 Sep 27. Epub 2020 Sep 27.

CRUK Cambridge Centre Early Detection Programme, Department of Oncology, Hutchison/MRC Research Centre, University of Cambridge, UK.

Senescence refers to a cellular state featuring a stable cell-cycle arrest triggered in response to stress. This response also involves other distinct morphological and intracellular changes including alterations in gene expression and epigenetic modifications, elevated macromolecular damage, metabolism deregulation and a complex pro-inflammatory secretory phenotype. The initial demonstration of oncogene-induced senescence in vitro established senescence as an important tumour-suppressive mechanism, in addition to apoptosis. Senescence not only halts the proliferation of premalignant cells but also facilitates the clearance of affected cells through immunosurveillance. Failure to clear senescent cells owing to deficient immunosurveillance may, however, lead to a state of chronic inflammation that nurtures a pro-tumorigenic microenvironment favouring cancer initiation, migration and metastasis. In addition, senescence is a response to post-therapy genotoxic stress. Therefore, tracking the emergence of senescent cells becomes pivotal to detect potential pro-tumorigenic events. Current protocols for the in vivo detection of senescence require the analysis of fixed or deep-frozen tissues, despite a significant clinical need for real-time bioimaging methods. Accuracy and efficiency of senescence detection are further hampered by a lack of universal and more specific senescence biomarkers. Recently, in an attempt to overcome these hurdles, an assortment of detection tools has been developed. These strategies all have significant potential for clinical utilisation and include flow cytometry combined with histo- or cytochemical approaches, nanoparticle-based targeted delivery of imaging contrast agents, OFF-ON fluorescent senoprobes, positron emission tomography senoprobes and analysis of circulating SASP factors, extracellular vesicles and cell-free nucleic acids isolated from plasma. Here, we highlight the occurrence of senescence in neoplasia and advanced tumours, assess the impact of senescence on tumorigenesis and discuss how the ongoing development of senescence detection tools might improve early detection of multiple cancers and response to therapy in the near future.
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http://dx.doi.org/10.1002/1878-0261.12807DOI Listing
September 2020

Transcriptional signatures in histologic structures within glioblastoma tumors may predict personalized drug sensitivity and survival.

Neurooncol Adv 2020 Jan-Dec;2(1):vdaa093. Epub 2020 Aug 3.

Department of Neurology, Blood-Brain Barrier Program, Oregon Health and Science University, Portland, Oregon, USA.

Background: Glioblastoma is a rapidly fatal brain cancer that exhibits extensive intra- and intertumoral heterogeneity. Improving survival will require the development of personalized treatment strategies that can stratify tumors into subtypes that differ in therapeutic vulnerability and outcomes. Glioblastoma stratification has been hampered by intratumoral heterogeneity, limiting our ability to compare tumors in a consistent manner. Here, we develop methods that mitigate the impact of intratumoral heterogeneity on transcriptomic-based patient stratification.

Methods: We accessed open-source transcriptional profiles of histological structures from 34 human glioblastomas from the Ivy Glioblastoma Atlas Project. Principal component and correlation network analyses were performed to assess sample inter-relationships. Gene set enrichment analysis was used to identify enriched biological processes and classify glioblastoma subtype. For survival models, Cox proportional hazards regression was utilized. Transcriptional profiles from 156 human glioblastomas were accessed from The Cancer Genome Atlas to externally validate the survival model.

Results: We showed that intratumoral histologic architecture influences tumor classification when assessing established subtyping and prognostic gene signatures, and that indiscriminate sampling can produce misleading results. We identified the cellular tumor as a glioblastoma structure that can be targeted for transcriptional analysis to more accurately stratify patients by subtype and prognosis. Based on expression from cellular tumor, we created an improved risk stratification gene signature.

Conclusions: Our results highlight that biomarker performance for diagnostics, prognostics, and prediction of therapeutic response can be improved by analyzing transcriptional profiles in pure cellular tumor, which is a critical step toward developing personalized treatment for glioblastoma.
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http://dx.doi.org/10.1093/noajnl/vdaa093DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7462280PMC
August 2020

Annot: a Django-based sample, reagent, and experiment metadata tracking system.

BMC Bioinformatics 2019 Nov 1;20(1):542. Epub 2019 Nov 1.

Department of Biomedical Engineering and OHSU Center for Spatial Systems Biomedicine, OHSU, Portland, OR, 97201, USA.

Background: In biological experiments, comprehensive experimental metadata tracking - which comprises experiment, reagent, and protocol annotation with controlled vocabulary from established ontologies - remains a challenge, especially when the experiment involves multiple laboratory scientists who execute different steps of the protocol. Here we describe Annot, a novel web application designed to provide a flexible solution for this task.

Results: Annot enforces the use of controlled vocabulary for sample and reagent annotation while enabling robust investigation, study, and protocol tracking. The cornerstone of Annot's implementation is a json syntax-compatible file format, which can capture detailed metadata for all aspects of complex biological experiments. Data stored in this json file format can easily be ported into spreadsheet or data frame files that can be loaded into R ( https://www.r-project.org/ ) or Pandas, Python's data analysis library ( https://pandas.pydata.org/ ). Annot is implemented in Python3 and utilizes the Django web framework, Postgresql, Nginx, and Debian. It is deployed via Docker and supports all major browsers.

Conclusions: Annot offers a robust solution to annotate samples, reagents, and experimental protocols for established assays where multiple laboratory scientists are involved. Further, it provides a framework to store and retrieve metadata for data analysis and integration, and therefore ensures that data generated in different experiments can be integrated and jointly analyzed. This type of solution to metadata tracking can enhance the utility of large-scale datasets, which we demonstrate here with a large-scale microenvironment microarray study.
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http://dx.doi.org/10.1186/s12859-019-3147-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6824123PMC
November 2019

A Multi-center Study on the Reproducibility of Drug-Response Assays in Mammalian Cell Lines.

Cell Syst 2019 07 10;9(1):35-48.e5. Epub 2019 Jul 10.

Laboratory of Systems Pharmacology, HMS LINCS Center, Harvard Medical School, Boston, MA 02115, USA. Electronic address:

Evidence that some high-impact biomedical results cannot be repeated has stimulated interest in practices that generate findable, accessible, interoperable, and reusable (FAIR) data. Multiple papers have identified specific examples of irreproducibility, but practical ways to make data more reproducible have not been widely studied. Here, five research centers in the NIH LINCS Program Consortium investigate the reproducibility of a prototypical perturbational assay: quantifying the responsiveness of cultured cells to anti-cancer drugs. Such assays are important for drug development, studying cellular networks, and patient stratification. While many experimental and computational factors impact intra- and inter-center reproducibility, the factors most difficult to identify and control are those with a strong dependency on biological context. These factors often vary in magnitude with the drug being analyzed and with growth conditions. We provide ways to identify such context-sensitive factors, thereby improving both the theory and practice of reproducible cell-based assays.
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http://dx.doi.org/10.1016/j.cels.2019.06.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6700527PMC
July 2019

Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer.

J Vis Exp 2019 05 21(147). Epub 2019 May 21.

Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health and Science University;

Understanding the impact of the microenvironment on the phenotype of cells is a difficult problem due to the complex mixture of both soluble growth factors and matrix-associated proteins in the microenvironment in vivo. Furthermore, readily available reagents for the modeling of microenvironments in vitro typically utilize complex mixtures of proteins that are incompletely defined and suffer from batch to batch variability. The microenvironment microarray (MEMA) platform allows for the assessment of thousands of simple combinations of microenvironment proteins for their impact on cellular phenotypes in a single assay. The MEMAs are prepared in well plates, which allows the addition of individual ligands to separate wells containing arrayed extracellular matrix (ECM) proteins. The combination of the soluble ligand with each printed ECM forms a unique combination. A typical MEMA assay contains greater than 2,500 unique combinatorial microenvironments that cells are exposed to in a single assay. As a test case, the breast cancer cell line MCF7 was plated on the MEMA platform. Analysis of this assay identified factors that both enhance and inhibit the growth and proliferation of these cells. The MEMA platform is highly flexible and can be extended for use with other biological questions beyond cancer research.
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http://dx.doi.org/10.3791/58957DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6736605PMC
May 2019

Maintenance of MYC expression promotes de novo resistance to BET bromodomain inhibition in castration-resistant prostate cancer.

Sci Rep 2019 03 7;9(1):3823. Epub 2019 Mar 7.

Knight Cancer Institute, Oregon Health & Science University, Portland, OR, 97201, USA.

The BET bromodomain protein BRD4 is a chromatin reader that regulates transcription, including in cancer. In prostate cancer, specifically, the anti-tumor activity of BET bromodomain inhibition has been principally linked to suppression of androgen receptor (AR) function. MYC is a well-described BRD4 target gene in multiple cancer types, and prior work demonstrates that MYC plays an important role in promoting prostate cancer cell survival. Importantly, several BET bromodomain clinical trials are ongoing, including in prostate cancer. However, there is limited information about pharmacodynamic markers of response or mediators of de novo resistance. Using a panel of prostate cancer cell lines, we demonstrated that MYC suppression-rather than AR suppression-is a key determinant of BET bromodomain inhibitor sensitivity. Importantly, we determined that BRD4 was dispensable for MYC expression in the most resistant cell lines and that MYC RNAi + BET bromodomain inhibition led to additive anti-tumor activity in the most resistant cell lines. Our findings demonstrate that MYC suppression is an important pharmacodynamic marker of BET bromodomain inhibitor response and suggest that targeting MYC may be a promising therapeutic strategy to overcome de novo BET bromodomain inhibitor resistance in prostate cancer.
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http://dx.doi.org/10.1038/s41598-019-40518-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6405739PMC
March 2019

Modeling Tumor Phenotypes In Vitro with Three-Dimensional Bioprinting.

Cell Rep 2019 01;26(3):608-623.e6

Department of Medical and Molecular Genetics, Oregon Health & Science University, Portland, OR 97201, USA; Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97201, USA. Electronic address:

The tumor microenvironment plays a critical role in tumor growth, progression, and therapeutic resistance, but interrogating the role of specific tumor-stromal interactions on tumorigenic phenotypes is challenging within in vivo tissues. Here, we tested whether three-dimensional (3D) bioprinting could improve in vitro models by incorporating multiple cell types into scaffold-free tumor tissues with defined architecture. We generated tumor tissues from distinct subtypes of breast or pancreatic cancer in relevant microenvironments and demonstrate that this technique can model patient-specific tumors by using primary patient tissue. We assess intrinsic, extrinsic, and spatial tumorigenic phenotypes in bioprinted tissues and find that cellular proliferation, extracellular matrix deposition, and cellular migration are altered in response to extrinsic signals or therapies. Together, this work demonstrates that multi-cell-type bioprinted tissues can recapitulate aspects of in vivo neoplastic tissues and provide a manipulable system for the interrogation of multiple tumorigenic endpoints in the context of distinct tumor microenvironments.
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http://dx.doi.org/10.1016/j.celrep.2018.12.090DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6366459PMC
January 2019

Kinome rewiring reveals AURKA limits PI3K-pathway inhibitor efficacy in breast cancer.

Nat Chem Biol 2018 08 25;14(8):768-777. Epub 2018 Jun 25.

Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA.

Dysregulation of the PI3K-AKT-mTOR signaling network is a prominent feature of breast cancers. However, clinical responses to drugs targeting this pathway have been modest, possibly because of dynamic changes in cellular signaling that drive resistance and limit drug efficacy. Using a quantitative chemoproteomics approach, we mapped kinome dynamics in response to inhibitors of this pathway and identified signaling changes that correlate with drug sensitivity. Maintenance of AURKA after drug treatment was associated with resistance in breast cancer models. Incomplete inhibition of AURKA was a common source of therapy failure, and combinations of PI3K, AKT or mTOR inhibitors with the AURKA inhibitor MLN8237 were highly synergistic and durably suppressed mTOR signaling, resulting in apoptosis and tumor regression in vivo. This signaling map identifies survival factors whose presence limits the efficacy of targeted therapies and reveals new drug combinations that may unlock the full potential of PI3K-AKT-mTOR pathway inhibitors in breast cancer.
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http://dx.doi.org/10.1038/s41589-018-0081-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6051919PMC
August 2018

Microenvironment-Mediated Mechanisms of Resistance to HER2 Inhibitors Differ between HER2+ Breast Cancer Subtypes.

Cell Syst 2018 Mar 14;6(3):329-342.e6. Epub 2018 Mar 14.

Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239, USA. Electronic address:

Extrinsic signals are implicated in breast cancer resistance to HER2-targeted tyrosine kinase inhibitors (TKIs). To examine how microenvironmental signals influence resistance, we monitored TKI-treated breast cancer cell lines grown on microenvironment microarrays composed of printed extracellular matrix proteins supplemented with soluble proteins. We tested ∼2,500 combinations of 56 soluble and 46 matrix microenvironmental proteins on basal-like HER2+ (HER2E) or luminal-like HER2+ (L-HER2+) cells treated with the TKIs lapatinib or neratinib. In HER2E cells, hepatocyte growth factor, a ligand for MET, induced resistance that could be reversed with crizotinib, an inhibitor of MET. In L-HER2+ cells, neuregulin1-β1 (NRG1β), a ligand for HER3, induced resistance that could be reversed with pertuzumab, an inhibitor of HER2-HER3 heterodimerization. The subtype-specific responses were also observed in 3D cultures and murine xenografts. These results, along with bioinformatic pathway analysis and siRNA knockdown experiments, suggest different mechanisms of resistance specific to each HER2+ subtype: MET signaling for HER2E and HER2-HER3 heterodimerization for L-HER2+ cells.
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http://dx.doi.org/10.1016/j.cels.2018.02.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5927625PMC
March 2018

CCR5 Governs DNA Damage Repair and Breast Cancer Stem Cell Expansion.

Cancer Res 2018 04 22;78(7):1657-1671. Epub 2018 Jan 22.

Pennsylvania Cancer and Regenerative Medicine Research Center, Baruch S. Blumberg Institute, Pennsylvania Biotechnology Center, Doylestown, Pennsylvania.

The functional significance of the chemokine receptor CCR5 in human breast cancer epithelial cells is poorly understood. Here, we report that CCR5 expression in human breast cancer correlates with poor outcome. CCR5 breast cancer epithelial cells formed mammospheres and initiated tumors with >60-fold greater efficiency in mice. Reintroduction of CCR5 expression into CCR5-negative breast cancer cells promoted tumor metastases and induced DNA repair gene expression and activity. CCR5 antagonists Maraviroc and Vicriviroc dramatically enhanced cell killing mediated by DNA-damaging chemotherapeutic agents. Single-cell analysis revealed CCR5 governs PI3K/Akt, ribosomal biogenesis, and cell survival signaling. As CCR5 augments DNA repair and is reexpressed selectively on cancerous, but not normal breast epithelial cells, CCR5 inhibitors may enhance the tumor-specific activities of DNA damage response-based treatments, allowing a dose reduction of standard chemotherapy and radiation. This study offers a preclinical rationale to reposition CCR5 inhibitors to improve the treatment of breast cancer, based on their ability to enhance the tumor-specific activities of DNA-damaging chemotherapies administered in that disease. .
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http://dx.doi.org/10.1158/0008-5472.CAN-17-0915DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6331183PMC
April 2018

The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations.

Cell Syst 2018 01 29;6(1):13-24. Epub 2017 Nov 29.

BD2K-LINCS DCIC, Department of Environmental Health, University of Cincinnati, Cincinnati, OH 45220, USA.

The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.
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http://dx.doi.org/10.1016/j.cels.2017.11.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5799026PMC
January 2018

Quantification of sensitivity and resistance of breast cancer cell lines to anti-cancer drugs using GR metrics.

Sci Data 2017 11 7;4:170166. Epub 2017 Nov 7.

HMS LINCS Center, Laboratory of Systems Pharmacology, Department of Systems Biology, Harvard Medical School, Boston, MA 02115 USA.

Traditional means for scoring the effects of anti-cancer drugs on the growth and survival of cell lines is based on relative cell number in drug-treated and control samples and is seriously confounded by unequal division rates arising from natural biological variation and differences in culture conditions. This problem can be overcome by computing drug sensitivity on a per-division basis. The normalized growth rate inhibition (GR) approach yields per-division metrics for drug potency (GR) and efficacy (GR) that are analogous to the more familiar IC and E values. In this work, we report GR-based, proliferation-corrected, drug sensitivity metrics for ~4,700 pairs of breast cancer cell lines and perturbagens. Such data are broadly useful in understanding the molecular basis of therapeutic response and resistance. Here, we use them to investigate the relationship between different measures of drug sensitivity and conclude that drug potency and efficacy exhibit high variation that is only weakly correlated. To facilitate further use of these data, computed GR curves and metrics can be browsed interactively at http://www.GRbrowser.org/.
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http://dx.doi.org/10.1038/sdata.2017.166DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5674849PMC
November 2017

Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling.

Cell Syst 2017 01 22;4(1):73-83.e10. Epub 2016 Dec 22.

Department of Molecular and Medical Genetics, Oregon Health and Science University, Portland, OR 97201, USA. Electronic address:

Signaling networks downstream of receptor tyrosine kinases are among the most extensively studied biological networks, but new approaches are needed to elucidate causal relationships between network components and understand how such relationships are influenced by biological context and disease. Here, we investigate the context specificity of signaling networks within a causal conceptual framework using reverse-phase protein array time-course assays and network analysis approaches. We focus on a well-defined set of signaling proteins profiled under inhibition with five kinase inhibitors in 32 contexts: four breast cancer cell lines (MCF7, UACC812, BT20, and BT549) under eight stimulus conditions. The data, spanning multiple pathways and comprising ∼70,000 phosphoprotein and ∼260,000 protein measurements, provide a wealth of testable, context-specific hypotheses, several of which we experimentally validate. Furthermore, the data provide a unique resource for computational methods development, permitting empirical assessment of causal network learning in a complex, mammalian setting.
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http://dx.doi.org/10.1016/j.cels.2016.11.013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5279869PMC
January 2017

Cellular androgen content influences enzalutamide agonism of F877L mutant androgen receptor.

Oncotarget 2016 Jun;7(26):40690-40703

OHSU Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, U.S.A.

Prostate cancer is the most commonly diagnosed and second-most lethal cancer among men in the United States. The vast majority of prostate cancer deaths are due to castration-resistant prostate cancer (CRPC) - the lethal form of the disease that has progressed despite therapies that interfere with activation of androgen receptor (AR) signaling. One emergent resistance mechanism to medical castration is synthesis of intratumoral androgens that activate the AR. This insight led to the development of the AR antagonist enzalutamide. However, resistance to enzalutamide invariably develops, and disease progression is nearly universal. One mechanism of resistance to enzalutamide is an F877L mutation in the AR ligand-binding domain that can convert enzalutamide to an agonist of AR activity. However, mechanisms that contribute to the agonist switch had not been fully clarified, and there were no therapies to block AR F877L. Using cell line models of castration-resistant prostate cancer (CRPC), we determined that cellular androgen content influences enzalutamide agonism of mutant F877L AR. Further, enzalutamide treatment of AR F877L-expressing cell lines recapitulated the effects of androgen activation of F877L AR or wild-type AR. Because the BET bromodomain inhibitor JQ-1 was previously shown to block androgen activation of wild-type AR, we tested JQ-1 in AR F877L-expressing CRPC models. We determined that JQ-1 suppressed androgen or enzalutamide activation of mutant F877L AR and suppressed growth of mutant F877L AR CRPC tumors in vivo, demonstrating a new strategy to treat tumors harboring this mutation.
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http://dx.doi.org/10.18632/oncotarget.9816DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5130036PMC
June 2016

Genome co-amplification upregulates a mitotic gene network activity that predicts outcome and response to mitotic protein inhibitors in breast cancer.

Breast Cancer Res 2016 07 1;18(1):70. Epub 2016 Jul 1.

Department of Biomedical Engineering, School of Medicine, Oregon Health & Science University, 3303 SW Bond Ave., CH13B, Portland, OR, 97239, USA.

Background: High mitotic activity is associated with the genesis and progression of many cancers. Small molecule inhibitors of mitotic apparatus proteins are now being developed and evaluated clinically as anticancer agents. With clinical trials of several of these experimental compounds underway, it is important to understand the molecular mechanisms that determine high mitotic activity, identify tumor subtypes that carry molecular aberrations that confer high mitotic activity, and to develop molecular markers that distinguish which tumors will be most responsive to mitotic apparatus inhibitors.

Methods: We identified a coordinately regulated mitotic apparatus network by analyzing gene expression profiles for 53 malignant and non-malignant human breast cancer cell lines and two separate primary breast tumor datasets. We defined the mitotic network activity index (MNAI) as the sum of the transcriptional levels of the 54 coordinately regulated mitotic apparatus genes. The effect of those genes on cell growth was evaluated by small interfering RNA (siRNA).

Results: High MNAI was enriched in basal-like breast tumors and was associated with reduced survival duration and preferential sensitivity to inhibitors of the mitotic apparatus proteins, polo-like kinase, centromere associated protein E and aurora kinase designated GSK462364, GSK923295 and GSK1070916, respectively. Co-amplification of regions of chromosomes 8q24, 10p15-p12, 12p13, and 17q24-q25 was associated with the transcriptional upregulation of this network of 54 mitotic apparatus genes, and we identify transcription factors that localize to these regions and putatively regulate mitotic activity. Knockdown of the mitotic network by siRNA identified 22 genes that might be considered as additional therapeutic targets for this clinically relevant patient subgroup.

Conclusions: We define a molecular signature which may guide therapeutic approaches for tumors with high mitotic network activity.
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http://dx.doi.org/10.1186/s13058-016-0728-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4930593PMC
July 2016

Mechanism and Role of SOX2 Repression in Seminoma: Relevance to Human Germline Specification.

Stem Cell Reports 2016 05 28;6(5):772-783. Epub 2016 Apr 28.

Cell Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA; Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA. Electronic address:

Human male germ cell tumors (GCTs) are derived from primordial germ cells (PGCs). The master pluripotency regulator and neuroectodermal lineage effector transcription factor SOX2 is repressed in PGCs and the seminoma (SEM) subset of GCTs. The mechanism of SOX2 repression and its significance to GC and GCT development currently are not understood. Here, we show that SOX2 repression in SEM-derived TCam-2 cells is mediated by the Polycomb repressive complex (PcG) and the repressive H3K27me3 chromatin mark that are enriched at its promoter. Furthermore, SOX2 repression in TCam-2 cells can be abrogated by recruitment of the constitutively expressed H3K27 demethylase UTX to the SOX2 promoter through retinoid signaling, leading to expression of neuronal and other lineage genes. SOX17 has been shown to initiate human PGC specification, with its target PRDM1 suppressing mesendodermal genes. Our results are consistent with a role for SOX2 repression in normal germline development by suppressing neuroectodermal genes.
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http://dx.doi.org/10.1016/j.stemcr.2016.04.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4939754PMC
May 2016

Development and Validation of a Gene-Based Model for Outcome Prediction in Germ Cell Tumors Using a Combined Genomic and Expression Profiling Approach.

PLoS One 2015 1;10(12):e0142846. Epub 2015 Dec 1.

Cell Biology Program, Sloan-Kettering Institute for Cancer Research, New York, New York, United States of America.

Germ Cell Tumors (GCT) have a high cure rate, but we currently lack the ability to accurately identify the small subset of patients who will die from their disease. We used a combined genomic and expression profiling approach to identify genomic regions and underlying genes that are predictive of outcome in GCT patients. We performed array-based comparative genomic hybridization (CGH) on 53 non-seminomatous GCTs (NSGCTs) treated with cisplatin based chemotherapy and defined altered genomic regions using Circular Binary Segmentation. We identified 14 regions associated with two year disease-free survival (2yDFS) and 16 regions associated with five year disease-specific survival (5yDSS). From corresponding expression data, we identified 101 probe sets that showed significant changes in expression. We built several models based on these differentially expressed genes, then tested them in an independent validation set of 54 NSGCTs. These predictive models correctly classified outcome in 64-79.6% of patients in the validation set, depending on the endpoint utilized. Survival analysis demonstrated a significant separation of patients with good versus poor predicted outcome when using a combined gene set model. Multivariate analysis using clinical risk classification with the combined gene model indicated that they were independent prognostic markers. This novel set of predictive genes from altered genomic regions is almost entirely independent of our previously identified set of predictive genes for patients with NSGCTs. These genes may aid in the identification of the small subset of patients who are at high risk of poor outcome.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0142846PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4666461PMC
June 2016

Exome Sequencing of Cell-Free DNA from Metastatic Cancer Patients Identifies Clinically Actionable Mutations Distinct from Primary Disease.

PLoS One 2015 28;10(8):e0136407. Epub 2015 Aug 28.

Knight Cancer Institute, Oregon Health and Sciences University, Portland, Oregon, United States of America.

The identification of the molecular drivers of cancer by sequencing is the backbone of precision medicine and the basis of personalized therapy; however, biopsies of primary tumors provide only a snapshot of the evolution of the disease and may miss potential therapeutic targets, especially in the metastatic setting. A liquid biopsy, in the form of cell-free DNA (cfDNA) sequencing, has the potential to capture the inter- and intra-tumoral heterogeneity present in metastatic disease, and, through serial blood draws, track the evolution of the tumor genome. In order to determine the clinical utility of cfDNA sequencing we performed whole-exome sequencing on cfDNA and tumor DNA from two patients with metastatic disease; only minor modifications to our sequencing and analysis pipelines were required for sequencing and mutation calling of cfDNA. The first patient had metastatic sarcoma and 47 of 48 mutations present in the primary tumor were also found in the cell-free DNA. The second patient had metastatic breast cancer and sequencing identified an ESR1 mutation in the cfDNA and metastatic site, but not in the primary tumor. This likely explains tumor progression on Anastrozole. Significant heterogeneity between the primary and metastatic tumors, with cfDNA reflecting the metastases, suggested separation from the primary lesion early in tumor evolution. This is best illustrated by an activating PIK3CA mutation (H1047R) which was clonal in the primary tumor, but completely absent from either the metastasis or cfDNA. Here we show that cfDNA sequencing supplies clinically actionable information with minimal risks compared to metastatic biopsies. This study demonstrates the utility of whole-exome sequencing of cell-free DNA from patients with metastatic disease. cfDNA sequencing identified an ESR1 mutation, potentially explaining a patient's resistance to aromatase inhibition, and gave insight into how metastatic lesions differ from the primary tumor.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0136407PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4552879PMC
May 2016

Decoupling of the PI3K Pathway via Mutation Necessitates Combinatorial Treatment in HER2+ Breast Cancer.

PLoS One 2015 16;10(7):e0133219. Epub 2015 Jul 16.

Oregon Health Sciences University, Department of Biomedical Engineering, Portland, Oregon, United States of America.

We report here on experimental and theoretical efforts to determine how best to combine drugs that inhibit HER2 and AKT in HER2(+) breast cancers. We accomplished this by measuring cellular and molecular responses to lapatinib and the AKT inhibitors (AKTi) GSK690693 and GSK2141795 in a panel of 22 HER2(+) breast cancer cell lines carrying wild type or mutant PIK3CA. We observed that combinations of lapatinib plus AKTi were synergistic in HER2(+)/PIK3CA(mut) cell lines but not in HER2(+)/PIK3CA(wt) cell lines. We measured changes in phospho-protein levels in 15 cell lines after treatment with lapatinib, AKTi or lapatinib + AKTi to shed light on the underlying signaling dynamics. This revealed that p-S6RP levels were less well attenuated by lapatinib in HER2(+)/PIK3CA(mut) cells compared to HER2(+)/PIK3CAwt cells and that lapatinib + AKTi reduced p-S6RP levels to those achieved in HER2(+)/PIK3CA(wt) cells with lapatinib alone. We also found that that compensatory up-regulation of p-HER3 and p-HER2 is blunted in PIK3CA(mut) cells following lapatinib + AKTi treatment. Responses of HER2(+) SKBR3 cells transfected with lentiviruses carrying control or PIK3CA(mut )sequences were similar to those observed in HER2(+)/PIK3CA(mut) cell lines but not in HER2(+)/PIK3CA(wt) cell lines. We used a nonlinear ordinary differential equation model to support the idea that PIK3CA mutations act as downstream activators of AKT that blunt lapatinib inhibition of downstream AKT signaling and that the effects of PIK3CA mutations can be countered by combining lapatinib with an AKTi. This combination does not confer substantial benefit beyond lapatinib in HER2+/PIK3CA(wt) cells.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0133219PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4504492PMC
April 2016

Erratum to: Modeling precision treatment of breast cancer.

Genome Biol 2015 May 12;16:95. Epub 2015 May 12.

Department of Cancer & DNA Damage Responses, Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.

During the type-setting of the final version of the article [1] some of the additional files were swapped. The correct files are republished in this Erratum.
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http://dx.doi.org/10.1186/s13059-015-0658-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4426644PMC
May 2015

Interrogation of a context-specific transcription factor network identifies novel regulators of pluripotency.

Stem Cells 2015 Feb;33(2):367-77

Cell Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York, USA.

The predominant view of pluripotency regulation proposes a stable ground state with coordinated expression of key transcription factors (TFs) that prohibit differentiation. Another perspective suggests a more complexly regulated state involving competition between multiple lineage-specifying TFs that define pluripotency. These contrasting views were developed from extensive analyses of TFs in pluripotent cells in vitro. An experimentally validated, genome-wide repertoire of the regulatory interactions that control pluripotency within the in vivo cellular contexts is yet to be developed. To address this limitation, we assembled a TF interactome of adult human male germ cell tumors (GCTs) using the Algorithm for the Accurate Reconstruction of Cellular Pathways (ARACNe) to analyze gene expression profiles of 141 tumors comprising pluripotent and differentiated subsets. The network (GCT(Net)) comprised 1,305 TFs, and its ingenuity pathway analysis identified pluripotency and embryonal development as the top functional pathways. We experimentally validated GCT(Net) by functional (silencing) and biochemical (ChIP-seq) analysis of the core pluripotency regulatory TFs POU5F1, NANOG, and SOX2 in relation to their targets predicted by ARACNe. To define the extent of the in vivo pluripotency network in this system, we ranked all TFs in the GCT(Net) according to sharing of ARACNe-predicted targets with those of POU5F1 and NANOG using an odds-ratio analysis method. To validate this network, we silenced the top 10 TFs in the network in H9 embryonic stem cells. Silencing of each led to downregulation of pluripotency and induction of lineage; 7 of the 10 TFs were identified as pluripotency regulators for the first time.
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http://dx.doi.org/10.1002/stem.1870DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4305010PMC
February 2015

Modeling precision treatment of breast cancer.

Genome Biol 2013 ;14(10):R110

Background: First-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets.

Results: We used least squares-support vector machines and random forest algorithms to identify molecular features associated with responses of a collection of 70 breast cancer cell lines to 90 experimental or approved therapeutic agents. The datasets analyzed included measurements of copy number aberrations, mutations, gene and isoform expression, promoter methylation and protein expression. Transcriptional subtype contributed strongly to response predictors for 25% of compounds, and adding other molecular data types improved prediction for 65%. No single molecular dataset consistently out-performed the others, suggesting that therapeutic response is mediated at multiple levels in the genome. Response predictors were developed and applied to TCGA data, and were found to be present in subsets of those patient samples.

Conclusions: These results suggest that matching patients to treatments based on transcriptional subtype will improve response rates, and inclusion of additional features from other profiling data types may provide additional benefit. Further, we suggest a systems biology strategy for guiding clinical trials so that patient cohorts most likely to respond to new therapies may be more efficiently identified.
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http://dx.doi.org/10.1186/gb-2013-14-10-r110DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3937590PMC
September 2014

Cross-platform pathway-based analysis identifies markers of response to the PARP inhibitor olaparib.

Breast Cancer Res Treat 2012 Sep 9;135(2):505-17. Epub 2012 Aug 9.

Laboratory Medicine, University of California San Francisco, 2340 Sutter Street Box 0808, San Francisco, CA 94115, USA.

Poly(ADP-ribose) polymerase (PARP) is an enzyme involved in DNA repair. PARP inhibitors can act as chemosensitizers, or operate on the principle of synthetic lethality when used as single agent. Clinical trials have shown drugs in this class to be promising for BRCA mutation carriers. We postulated that inability to demonstrate response in non-BRCA carriers in which BRCA is inactivated by other mechanisms or with deficiency in homologous recombination for DNA repair is due to lack of molecular markers that define a responding subpopulation. We identified candidate markers for this purpose for olaparib (AstraZeneca) by measuring inhibitory effects of nine concentrations of olaparib in 22 breast cancer cell lines and identifying features in transcriptional and genome copy number profiles that were significantly correlated with response. We emphasized in this discovery process genes involved in DNA repair. We found that the cell lines that were sensitive to olaparib had a significant lower copy number of BRCA1 compared to the resistant cell lines (p value 0.012). In addition, we discovered seven genes from DNA repair pathways whose transcriptional levels were associated with response. These included five genes (BRCA1, MRE11A, NBS1, TDG, and XPA) whose transcript levels were associated with resistance and two genes (CHEK2 and MK2) whose transcript levels were associated with sensitivity. We developed an algorithm to predict response using the seven-gene transcription levels and applied it to 1,846 invasive breast cancer samples from 8 U133A/plus 2 (Affymetrix) data sets and found that 8-21 % of patients would be predicted to be responsive to olaparib. A similar response frequency was predicted in 536 samples analyzed on an Agilent platform. Importantly, tumors predicted to respond were enriched in basal subtype tumors. Our studies support clinical evaluation of the utility of our seven-gene signature as a predictor of response to olaparib.
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http://dx.doi.org/10.1007/s10549-012-2188-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3429780PMC
September 2012

The transcription factor ZNF217 is a prognostic biomarker and therapeutic target during breast cancer progression.

Cancer Discov 2012 Jul 10;2(7):638-51. Epub 2012 May 10.

Department of Anatomy, University of California, San Francisco, CA 94143, USA.

Unlabelled: The transcription factor ZNF217 is a candidate oncogene in the amplicon on chromosome 20q13 that occurs in 20% to 30% of primary human breast cancers and that correlates with poor prognosis. We show that Znf217 overexpression drives aberrant differentiation and signaling events, promotes increased self-renewal capacity, mesenchymal marker expression, motility, and metastasis, and represses an adult tissue stem cell gene signature downregulated in cancers. By in silico screening, we identified candidate therapeutics that at low concentrations inhibit growth of cancer cells expressing high ZNF217. We show that the nucleoside analogue triciribine inhibits ZNF217-induced tumor growth and chemotherapy resistance and inhibits signaling events [e.g., phospho-AKT, phospho-mitogen-activated protein kinase (MAPK)] in vivo. Our data suggest that ZNF217 is a biomarker of poor prognosis and a therapeutic target in patients with breast cancer and that triciribine may be part of a personalized treatment strategy in patients overexpressing ZNF217. Because ZNF217 is amplified in numerous cancers, these results have implications for other cancers.

Significance: This study finds that ZNF217 is a poor prognostic indicator and therapeutic target in patients with breast cancer and may be a strong biomarker of triciribine treatment efficacy in patients. Because previous clinical trials for triciribine did not include biomarkers of treatment efficacy, this study provides a rationale for revisiting triciribine in the clinical setting as a therapy for patients with breast cancer who overexpress ZNF217.
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http://dx.doi.org/10.1158/2159-8290.CD-12-0093DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546490PMC
July 2012

A central role for RAF→MEK→ERK signaling in the genesis of pancreatic ductal adenocarcinoma.

Cancer Discov 2012 Aug 24;2(8):685-93. Epub 2012 May 24.

Department of Medicine, Division of Hematology and Oncology, University of California, San Francisco, California, USA.

Unlabelled: KRAS mutation is a hallmark of pancreatic ductal adenocarcinoma (PDA) but remains an intractable pharmacologic target. Consequently, defining RAS effector pathway(s) required for PDA initiation and maintenance is critical to improve treatment of this disease. Here, we show that expression of BRAF(V600E), but not PIK3CA(H1047R), in the mouse pancreas leads to pancreatic intraepithelial neoplasia (PanIN) lesions. Moreover, concomitant expression of BRAF(V600E) and TP53(R270H) result in lethal PDA. We tested pharmacologic inhibitors of RAS effectors against multiple human PDA cell lines. Mitogen-activated protein (MAP)/extracellular signal-regulated (ERK) kinase (MEK) inhibition was highly effective both in vivo and in vitro and was synergistic with AKT inhibition in most cell lines tested. We show that RAF→MEK→ERK signaling is central to the initiation and maintenance of PDA and to rational combination strategies in this disease. These results emphasize the value of leveraging multiple complementary experimental systems to prioritize pathways for effective intervention strategies in PDA.

Significance: PDA is diffi cult to treat, in large part, due to recurrent mutations in the KRAS gene. Here, we defi ne rational treatment approaches for the disease achievable today with existing drug combinations by thorough genetic and pharmacologic dissection of the major KRAS effector pathways, RAF→MEK→ERK and phosphoinositide 3′-kinase (PI3'K)→AKT.
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http://dx.doi.org/10.1158/2159-8290.CD-11-0347DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3425446PMC
August 2012

Subtype and pathway specific responses to anticancer compounds in breast cancer.

Proc Natl Acad Sci U S A 2012 Feb 14;109(8):2724-9. Epub 2011 Oct 14.

Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.

Breast cancers are comprised of molecularly distinct subtypes that may respond differently to pathway-targeted therapies now under development. Collections of breast cancer cell lines mirror many of the molecular subtypes and pathways found in tumors, suggesting that treatment of cell lines with candidate therapeutic compounds can guide identification of associations between molecular subtypes, pathways, and drug response. In a test of 77 therapeutic compounds, nearly all drugs showed differential responses across these cell lines, and approximately one third showed subtype-, pathway-, and/or genomic aberration-specific responses. These observations suggest mechanisms of response and resistance and may inform efforts to develop molecular assays that predict clinical response.
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http://dx.doi.org/10.1073/pnas.1018854108DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3286973PMC
February 2012

A genetic strategy for single and combinatorial analysis of miRNA function in mammalian hematopoietic stem cells.

Stem Cells 2010 Feb;28(2):287-96

Center for Cell Engineering Memorial Sloan-Kettering Cancer Center, New York, New York 10065, USA.

The regulatory role of micro-RNAs (miRNAs) in hematopoietic development is increasingly appreciated. Reverse genetics strategies based on the targeted disruption of miRNAs offer a powerful tool to study miRNA functions in mammalian hematopoiesis. The miR-144/451 cluster comprises two miRNAs coexpressed from a common precursor transcript in an erythroid-specific manner. To decipher the contribution of each miRNA of the cluster in mammalian erythropoiesis, we developed a strategy for stable in vivo individual and combinatorial miRNA inhibition. We developed decoy target sequences for each miRNA expressed by lentiviral vectors marked with distinct fluorescent proteins and used them to probe the functions of miR-144 and miR-451 in the murine hematopoietic system in a competitive repopulation setting. Murine hematopoietic chimeras expressing lentiviral-encoded inhibitory sequences specific for miR-144 or miR-451 exhibited markedly reduced Ter119(+) erythroblast counts, with the combined knockdown showing additive effect. These chimeras showed abnormal patterns of erythroid differentiation primarily affecting the proerythroblast to basophilic erythroblast transition, coinciding with the stage where expression of the miRNA cluster is dramatically induced and posttranscriptional gene regulation becomes prominent. These results reveal a role for the miR-144/451 locus in mammalian erythropoiesis and provide the first evidence of functional cooperativity between clustered miRNAs in the hematopoietic system. The strategy described herein will prove useful in functional miRNA studies in mammalian hematopoietic stem cells.
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http://dx.doi.org/10.1002/stem.257DOI Listing
February 2010
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