Publications by authors named "Laura M Heiser"

54 Publications

Integrating Mathematical Modeling with High-Throughput Imaging Explains How Polyploid Populations Behave in Nutrient-Sparse Environments.

Cancer Res 2020 11 16;80(22):5109-5120. Epub 2020 Sep 16.

Department of Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, Florida.

Breast cancer progresses in a multistep process from primary tumor growth and stroma invasion to metastasis. Nutrient-limiting environments promote chemotaxis with aggressive morphologies characteristic of invasion. It is unknown how coexisting cells differ in their response to nutrient limitations and how this impacts invasion of the metapopulation as a whole. In this study, we integrate mathematical modeling with microenvironmental perturbation data to investigate invasion in nutrient-limiting environments inhabited by one or two cancer cell subpopulations. Subpopulations were defined by their energy efficiency and chemotactic ability. Invasion distance traveled by a homogeneous population was estimated. For heterogeneous populations, results suggest that an imbalance between nutrient efficacy and chemotactic superiority accelerates invasion. Such imbalance will spatially segregate the two populations and only one type will dominate at the invasion front. Only if these two phenotypes are balanced, the two subpopulations compete for the same space, which decelerates invasion. We investigate ploidy as a candidate biomarker of this phenotypic heterogeneity and discuss its potential to inform the dose of mTOR inhibitors (mTOR-I) that can inhibit chemotaxis just enough to facilitate such competition. SIGNIFICANCE: This study identifies the double-edged sword of high ploidy as a prerequisite to personalize combination therapies with cytotoxic drugs and inhibitors of signal transduction pathways such as mTOR-Is. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/22/5109/F1.large.jpg.
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http://dx.doi.org/10.1158/0008-5472.CAN-20-1231DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671819PMC
November 2020

Systems biology approaches to measure and model phenotypic heterogeneity in cancer.

Curr Opin Syst Biol 2019 Oct 11;17:35-40. Epub 2019 Sep 11.

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

The recent wide-spread adoption of single cell profiling technologies has revealed that individual cancers are not homogenous collections of deregulated cells, but instead are comprised of multiple genetically and phenotypically distinct cell subpopulations that exhibit a wide range of responses to extracellular signals and therapeutic insult. Such observations point to the urgent need to understand cancer as a complex, adaptive system. Cancer systems biology studies seek to develop the experimental and theoretical methods required to understand how biological components work together to determine how cancer cells function. Ultimately, such approaches will lead to improvements in how cancer is managed and treated. In this review, we discuss recent advances in cancer systems biology approaches to quantify, model, and elucidate mechanisms of heterogeneity.
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http://dx.doi.org/10.1016/j.coisb.2019.09.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7449235PMC
October 2019

How Machine Learning Will Transform Biomedicine.

Cell 2020 04;181(1):92-101

Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA.

This Perspective explores the application of machine learning toward improved diagnosis and treatment. We outline a vision for how machine learning can transform three broad areas of biomedicine: clinical diagnostics, precision treatments, and health monitoring, where the goal is to maintain health through a range of diseases and the normal aging process. For each area, early instances of successful machine learning applications are discussed, as well as opportunities and challenges for machine learning. When these challenges are met, machine learning promises a future of rigorous, outcomes-based medicine with detection, diagnosis, and treatment strategies that are continuously adapted to individual and environmental differences.
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http://dx.doi.org/10.1016/j.cell.2020.03.022DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141410PMC
April 2020

Individual Cells Can Resolve Variations in Stimulus Intensity along the IGF-PI3K-AKT Signaling Axis.

Cell Syst 2019 12 11;9(6):580-588.e4. Epub 2019 Dec 11.

Department of Biomedical Engineering, OHSU Center for Spatial Systems Biomedicine, Knight Cancer Institute, Oregon Health & Sciences University, Portland OR, USA. Electronic address:

Cells sense and respond to signals in their local environment by activating signaling cascades that lead to phenotypic changes. Differences in these signals can be discriminated at the population level; however, single cells have been thought to be limited in their capacity to distinguish ligand doses due to signaling noise. We describe here the rational development of a genetically encoded FoxO1 sensor, which serves as a down-stream readout of insulin growth factor-phosphatidylinositol 3-kinase IGF-PI3K-AKT signaling pathway activity. With this reporter, we tracked individual cell responses to multiple IGF-I doses, pathway inhibitors, and repeated treatments. We observed that individual cells can discriminate multiple IGF-I doses, and these responses are sustained over time, are reproducible at the single-cell level, and display cell-to-cell heterogeneity. These studies imply that cell-to-cell variation in signaling responses is biologically meaningful and support the endeavor to elucidate mechanisms of cell signaling at the level of the individual cell.
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http://dx.doi.org/10.1016/j.cels.2019.11.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7081831PMC
December 2019

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

The tracking of lipopolysaccharide through the feto-maternal compartment and the involvement of maternal TLR4 in inflammation-induced fetal brain injury.

Am J Reprod Immunol 2019 12 30;82(6):e13189. Epub 2019 Sep 30.

Department of Obstetrics and Gynecology, Maternal and Child Health Research Center, Center for Research on Reproduction and Women's Health, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.

Problem: Exposure to intrauterine inflammation (IUI) has been shown to induce fetal brain injury and increase the risk of acquiring a neurobehavioral disorder. The trafficking of the inflammatory mediator, lipopolysaccharide (LPS), in the pregnant female reproductive tract in the setting of IUI and the precise mechanisms by which inflammation induces fetal brain injury are not fully understood.

Method Of Study: FITC-labeled LPS was utilized to induce IUI on E15, tissues were collected, and fluorescence was visualized via the Spectrum IVIS. Embryo transfer was utilized to create divergent maternal and fetal genotypes. Wild-type (WT) embryos were transferred into TLR4-/- pseudopregnant dams (TLR4-/- /WT ). On E15, TLR4-/- /WT dams or their WT controls (WT /WT ) received an intrauterine injection of LPS or phosphate-buffered saline (PBS). Endotoxin and IL-6 levels were assessed in amniotic fluid, and cytokine expression was measured via QPCR.

Results: Lipopolysaccharide trafficked to the uterus, fetal membranes, placenta, and the fetus and was undetectable in other tissues. Endotoxin was present in the amniotic fluid of all animals exposed to LPS. However, the immune response was blunted in TLR4-/- /WT compared with WT controls.

Conclusion: Intrauterine administered LPS is capable of accessing the entire feto-placental unit with or without a functional maternal TLR4. Thus, bacteria or bacterial byproducts in the uterus may negatively impact fetal development regardless of the maternal genotype or endotoxin response. Despite the blunted immune response in the TLR4-deficient dams, an inflammatory response is still ignited in the amniotic cavity and may negatively impact the fetus.
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http://dx.doi.org/10.1111/aji.13189DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6899932PMC
December 2019

Targeting the Mevalonate Pathway to Overcome Acquired Anti-HER2 Treatment Resistance in Breast Cancer.

Mol Cancer Res 2019 11 16;17(11):2318-2330. Epub 2019 Aug 16.

Lester & Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas.

Despite effective strategies, resistance in HER2 breast cancer remains a challenge. While the mevalonate pathway (MVA) is suggested to promote cell growth and survival, including in HER2 models, its potential role in resistance to HER2-targeted therapy is unknown. Parental HER2 breast cancer cells and their lapatinib-resistant and lapatinib + trastuzumab-resistant derivatives were used for this study. MVA activity was found to be increased in lapatinib-resistant and lapatinib + trastuzumab-resistant cells. Specific blockade of this pathway with lipophilic but not hydrophilic statins and with the N-bisphosphonate zoledronic acid led to apoptosis and substantial growth inhibition of R cells. Inhibition was rescued by mevalonate or the intermediate metabolites farnesyl pyrophosphate or geranylgeranyl pyrophosphate, but not cholesterol. Activated Yes-associated protein (YAP)/transcriptional coactivator with PDZ-binding motif (TAZ) and mTORC1 signaling, and their downstream target gene product Survivin, were inhibited by MVA blockade, especially in the lapatinib-resistant/lapatinib + trastuzumab-resistant models. Overexpression of constitutively active YAP rescued Survivin and phosphorylated-S6 levels, despite blockade of the MVA. These results suggest that the MVA provides alternative signaling leading to cell survival and resistance by activating YAP/TAZ-mTORC1-Survivin signaling when HER2 is blocked, suggesting novel therapeutic targets. MVA inhibitors including lipophilic statins and N-bisphosphonates may circumvent resistance to anti-HER2 therapy warranting further clinical investigation. IMPLICATIONS: The MVA was found to constitute an escape mechanism of survival and growth in HER2 breast cancer models resistant to anti-HER2 therapies. MVA inhibitors such as simvastatin and zoledronic acid are potential therapeutic agents to resensitize the tumors that depend on the MVA to progress on anti-HER2 therapies.
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http://dx.doi.org/10.1158/1541-7786.MCR-19-0756DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6825570PMC
November 2019

Variational Autoencoding Tissue Response to Microenvironment Perturbation.

Proc SPIE Int Soc Opt Eng 2019 Feb 15;10949. Epub 2019 Mar 15.

Dept. of Biomedical Engineering, Center for Spatial Systems Biomedicine, Oregon Health & Science University, Portland, OR, USA.

This work applies deep variational autoencoder learning architecture to study multi-cellular growth characteristics of human mammary epithelial cells in response to diverse microenvironment perturbations. Our approach introduces a novel method of visualizing learned feature spaces of trained variational autoencoding models that enables visualization of principal features in two dimensions. We find that unsupervised learned features more closely associate with expert annotation of cell colony organization than biologically-inspired hand-crafted features, demonstrating the utility of deep learning systems to meaningfully characterize features of multi-cellular growth characteristics in a fully unsupervised and data-driven manner.
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http://dx.doi.org/10.1117/12.2512660DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6677277PMC
February 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

BET bromodomain inhibition blocks the function of a critical AR-independent master regulator network in lethal prostate cancer.

Oncogene 2019 07 17;38(28):5658-5669. Epub 2019 Apr 17.

Knight Cancer Institute, Oregon Health & Science University, Portland, OR, 97239, USA.

BET bromodomain inhibitors block prostate cancer cell growth at least in part through c-Myc and androgen receptor (AR) suppression. However, little is known about other transcriptional regulators whose suppression contributes to BET bromodomain inhibitor anti-tumor activity. Moreover, the anti-tumor activity of BET bromodomain inhibition in AR-independent castration-resistant prostate cancers (CRPC), whose frequency is increasing, is also unknown. Herein, we demonstrate that BET bromodomain inhibition blocks growth of a diverse set of CRPC cell models, including those that are AR-independent or in which c-Myc is not suppressed. To identify transcriptional regulators whose suppression accounts for these effects, we treated multiple CRPC cell lines with the BET bromodomain inhibitor JQ1 and then performed RNA-sequencing followed by Master Regulator computational analysis. This approach identified several previously unappreciated transcriptional regulators that are highly expressed in CRPC and whose suppression, via both transcriptional or post-translational mechanisms, contributes to the anti-tumor activity of BET bromodomain inhibitors.
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http://dx.doi.org/10.1038/s41388-019-0815-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6677126PMC
July 2019

Therapeutic Clues from an Integrated Omic Assessment of East Asian Triple Negative Breast Cancers.

Cancer Cell 2019 03;35(3):341-343

Center for Spatial Systems Biomedicine, Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR 97201, USA. Electronic address:

In this issue of Cancer Cell, Jiang et al. report a genomic and transcriptional analysis of triple negative breast cancers (TNBCs) from an East Asian population. Their study shows minor differences with published studies of European and North American populations and suggests a therapeutic decision tree for treatment of TNBC.
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http://dx.doi.org/10.1016/j.ccell.2019.02.012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499473PMC
March 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

LSD1 activates a lethal prostate cancer gene network independently of its demethylase function.

Proc Natl Acad Sci U S A 2018 05 26;115(18):E4179-E4188. Epub 2018 Mar 26.

Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239;

Medical castration that interferes with androgen receptor (AR) function is the principal treatment for advanced prostate cancer. However, clinical progression is universal, and tumors with AR-independent resistance mechanisms appear to be increasing in frequency. Consequently, there is an urgent need to develop new treatments targeting molecular pathways enriched in lethal prostate cancer. Lysine-specific demethylase 1 (LSD1) is a histone demethylase and an important regulator of gene expression. Here, we show that LSD1 promotes the survival of prostate cancer cells, including those that are castration-resistant, independently of its demethylase function and of the AR. Importantly, this effect is explained in part by activation of a lethal prostate cancer gene network in collaboration with LSD1's binding protein, ZNF217. Finally, that a small-molecule LSD1 inhibitor-SP-2509-blocks important demethylase-independent functions and suppresses castration-resistant prostate cancer cell viability demonstrates the potential of LSD1 inhibition in this disease.
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http://dx.doi.org/10.1073/pnas.1719168115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5939079PMC
May 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

Publisher Correction: Combating subclonal evolution of resistant cancer phenotypes.

Nat Commun 2018 02 5;9(1):572. Epub 2018 Feb 5.

Department of Pharmacology and Toxicology, College of Pharmacy, University of Utah, 30 South 2000 East, Salt Lake City, UT, 84112, USA.

The originally published version of this Article contained an error in Figure 4. In panel a, grey boxes surrounding the subclones associated with patients #2 and #4 obscured adjacent portions of the heatmap. This error has now been corrected in both the PDF and HTML versions of the Article.
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http://dx.doi.org/10.1038/s41467-017-02383-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5799176PMC
February 2018

Integrative molecular network analysis identifies emergent enzalutamide resistance mechanisms in prostate cancer.

Oncotarget 2017 Dec 20;8(67):111084-111095. Epub 2017 Nov 20.

Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA.

Recent work demonstrates that castration-resistant prostate cancer (CRPC) tumors harbor countless genomic aberrations that control many hallmarks of cancer. While some specific mutations in CRPC may be actionable, many others are not. We hypothesized that genomic aberrations in cancer may operate in concert to promote drug resistance and tumor progression, and that organization of these genomic aberrations into therapeutically targetable pathways may improve our ability to treat CRPC. To identify the molecular underpinnings of enzalutamide-resistant CRPC, we performed transcriptional and copy number profiling studies using paired enzalutamide-sensitive and resistant LNCaP prostate cancer cell lines. Gene networks associated with enzalutamide resistance were revealed by performing an integrative genomic analysis with the PAthway Representation and Analysis by Direct Reference on Graphical Models (PARADIGM) tool. Amongst the pathways enriched in the enzalutamide-resistant cells were those associated with MEK, EGFR, RAS, and NFKB. Functional validation studies of 64 genes identified 10 candidate genes whose suppression led to greater effects on cell viability in enzalutamide-resistant cells as compared to sensitive parental cells. Examination of a patient cohort demonstrated that several of our functionally-validated gene hits are deregulated in metastatic CRPC tumor samples, suggesting that they may be clinically relevant therapeutic targets for patients with enzalutamide-resistant CRPC. Altogether, our approach demonstrates the potential of integrative genomic analyses to clarify determinants of drug resistance and rational co-targeting strategies to overcome resistance.
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http://dx.doi.org/10.18632/oncotarget.22560DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5762307PMC
December 2017

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

Authors:
Alexandra B Keenan Sherry L Jenkins Kathleen M Jagodnik Simon Koplev Edward He Denis Torre Zichen Wang Anders B Dohlman Moshe C Silverstein Alexander Lachmann Maxim V Kuleshov Avi Ma'ayan Vasileios Stathias Raymond Terryn Daniel Cooper Michele Forlin Amar Koleti Dusica Vidovic Caty Chung Stephan C Schürer Jouzas Vasiliauskas Marcin Pilarczyk Behrouz Shamsaei Mehdi Fazel Yan Ren Wen Niu Nicholas A Clark Shana White Naim Mahi Lixia Zhang Michal Kouril John F Reichard Siva Sivaganesan Mario Medvedovic Jaroslaw Meller Rick J Koch Marc R Birtwistle Ravi Iyengar Eric A Sobie Evren U Azeloglu Julia Kaye Jeannette Osterloh Kelly Haston Jaslin Kalra Steve Finkbiener Jonathan Li Pamela Milani Miriam Adam Renan Escalante-Chong Karen Sachs Alex Lenail Divya Ramamoorthy Ernest Fraenkel Gavin Daigle Uzma Hussain Alyssa Coye Jeffrey Rothstein Dhruv Sareen Loren Ornelas Maria Banuelos Berhan Mandefro Ritchie Ho Clive N Svendsen Ryan G Lim Jennifer Stocksdale Malcolm S Casale Terri G Thompson Jie Wu Leslie M Thompson Victoria Dardov Vidya Venkatraman Andrea Matlock Jennifer E Van Eyk Jacob D Jaffe Malvina Papanastasiou Aravind Subramanian Todd R Golub Sean D Erickson Mohammad Fallahi-Sichani Marc Hafner Nathanael S Gray Jia-Ren Lin Caitlin E Mills Jeremy L Muhlich Mario Niepel Caroline E Shamu Elizabeth H Williams David Wrobel Peter K Sorger Laura M Heiser Joe W Gray James E Korkola Gordon B Mills Mark LaBarge Heidi S Feiler Mark A Dane Elmar Bucher Michel Nederlof Damir Sudar Sean Gross David F Kilburn Rebecca Smith Kaylyn Devlin Ron Margolis Leslie Derr Albert Lee Ajay Pillai

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

NIH, Bethesda, MD 20892, 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

MYC regulates ductal-neuroendocrine lineage plasticity in pancreatic ductal adenocarcinoma associated with poor outcome and chemoresistance.

Nat Commun 2017 11 23;8(1):1728. Epub 2017 Nov 23.

Department of Molecular and Medical Genetics, Oregon Health and Science University, 3181 S.W. Sam Jackson Park Road, Portland, OR, 97239, USA.

Intratumoral phenotypic heterogeneity has been described in many tumor types, where it can contribute to drug resistance and disease recurrence. We analyzed ductal and neuroendocrine markers in pancreatic ductal adenocarcinoma, revealing heterogeneous expression of the neuroendocrine marker Synaptophysin within ductal lesions. Higher percentages of Cytokeratin-Synaptophysin dual positive tumor cells correlate with shortened disease-free survival. We observe similar lineage marker heterogeneity in mouse models of pancreatic ductal adenocarcinoma, where lineage tracing indicates that Cytokeratin-Synaptophysin dual positive cells arise from the exocrine compartment. Mechanistically, MYC binding is enriched at neuroendocrine genes in mouse tumor cells and loss of MYC reduces ductal-neuroendocrine lineage heterogeneity, while deregulated MYC expression in KRAS mutant mice increases this phenotype. Neuroendocrine marker expression is associated with chemoresistance and reducing MYC levels decreases gemcitabine-induced neuroendocrine marker expression and increases chemosensitivity. Altogether, we demonstrate that MYC facilitates ductal-neuroendocrine lineage plasticity in pancreatic ductal adenocarcinoma, contributing to poor survival and chemoresistance.
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http://dx.doi.org/10.1038/s41467-017-01967-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5701042PMC
November 2017

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

Combating subclonal evolution of resistant cancer phenotypes.

Nat Commun 2017 11 1;8(1):1231. Epub 2017 Nov 1.

Department of Pharmacology and Toxicology, College of Pharmacy, University of Utah, 30 South 2000 East, Salt Lake City, UT, 84112, USA.

Metastatic breast cancer remains challenging to treat, and most patients ultimately progress on therapy. This acquired drug resistance is largely due to drug-refractory sub-populations (subclones) within heterogeneous tumors. Here, we track the genetic and phenotypic subclonal evolution of four breast cancers through years of treatment to better understand how breast cancers become drug-resistant. Recurrently appearing post-chemotherapy mutations are rare. However, bulk and single-cell RNA sequencing reveal acquisition of malignant phenotypes after treatment, including enhanced mesenchymal and growth factor signaling, which may promote drug resistance, and decreased antigen presentation and TNF-α signaling, which may enable immune system avoidance. Some of these phenotypes pre-exist in pre-treatment subclones that become dominant after chemotherapy, indicating selection for resistance phenotypes. Post-chemotherapy cancer cells are effectively treated with drugs targeting acquired phenotypes. These findings highlight cancer's ability to evolve phenotypically and suggest a phenotype-targeted treatment strategy that adapts to cancer as it evolves.
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http://dx.doi.org/10.1038/s41467-017-01174-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5666005PMC
November 2017

Pathway-Enriched Gene Signature Associated with 53BP1 Response to PARP Inhibition in Triple-Negative Breast Cancer.

Mol Cancer Ther 2017 Dec 27;16(12):2892-2901. Epub 2017 Sep 27.

Department of Biomedical Engineering, OHSU Center for Spatial Systems Biomedicine, Oregon Health and Science University, Portland, Oregon.

Effective treatment of patients with triple-negative (ER-negative, PR-negative, HER2-negative) breast cancer remains a challenge. Although PARP inhibitors are being evaluated in clinical trials, biomarkers are needed to identify patients who will most benefit from anti-PARP therapy. We determined the responses of three PARP inhibitors (veliparib, olaparib, and talazoparib) in a panel of eight triple-negative breast cancer cell lines. Therapeutic responses and cellular phenotypes were elucidated using high-content imaging and quantitative immunofluorescence to assess markers of DNA damage (53BP1) and apoptosis (cleaved PARP). We determined the pharmacodynamic changes as percentage of cells positive for 53BP1, mean number of 53BP1 foci per cell, and percentage of cells positive for cleaved PARP. Inspired by traditional dose-response measures of cell viability, an EC value was calculated for each cellular phenotype and each PARP inhibitor. The EC values for both 53BP1 metrics strongly correlated with IC values for each PARP inhibitor. Pathway enrichment analysis identified a set of DNA repair and cell cycle-associated genes that were associated with 53BP1 response following PARP inhibition. The overall accuracy of our 63 gene set in predicting response to olaparib in seven breast cancer patient-derived xenograft tumors was 86%. In triple-negative breast cancer patients who had not received anti-PARP therapy, the predicted response rate of our gene signature was 45%. These results indicate that 53BP1 is a biomarker of response to anti-PARP therapy in the laboratory, and our DNA damage response gene signature may be used to identify patients who are most likely to respond to PARP inhibition. .
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http://dx.doi.org/10.1158/1535-7163.MCT-17-0170DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5765867PMC
December 2017

HER2 Reactivation through Acquisition of the HER2 L755S Mutation as a Mechanism of Acquired Resistance to HER2-targeted Therapy in HER2 Breast Cancer.

Clin Cancer Res 2017 Sep 9;23(17):5123-5134. Epub 2017 May 9.

Lester & Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas.

Resistance to anti-HER2 therapies in HER2 breast cancer can occur through activation of alternative survival pathways or reactivation of the HER signaling network. Here we employed BT474 parental and treatment-resistant cell line models to investigate a mechanism by which HER2 breast cancer can reactivate the HER network under potent HER2-targeted therapies. Resistant derivatives to lapatinib (L), trastuzumab (T), or the combination (LR/TR/LTR) were developed independently from two independent estrogen receptor ER/HER2 BT474 cell lines (AZ/ATCC). Two derivatives resistant to the lapatinib-containing regimens (BT474/AZ-LR and BT474/ATCC-LTR lines) that showed HER2 reactivation at the time of resistance were subjected to massive parallel sequencing and compared with parental lines. Ectopic expression and mutant-specific siRNA interference were applied to analyze the mutation functionally. and experiments were performed to test alternative therapies for mutant HER2 inhibition. Genomic analyses revealed that the L755S mutation was the only common somatic mutation gained in the BT474/AZ-LR and BT474/ATCC-LTR lines. Ectopic expression of L755S induced acquired lapatinib resistance in the BT474/AZ, SK-BR-3, and AU565 parental cell lines. L755S-specific siRNA knockdown reversed the resistance in BT474/AZ-LR and BT474/ATCC-LTR lines. The HER1/2-irreversible inhibitors afatinib and neratinib substantially inhibited both resistant cell growth and the HER2 and downstream AKT/MAPK signaling driven by L755S and HER2 reactivation through acquisition of the L755S mutation was identified as a mechanism of acquired resistance to lapatinib-containing HER2-targeted therapy in preclinical HER2-amplified breast cancer models, which can be overcome by irreversible HER1/2 inhibitors. .
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http://dx.doi.org/10.1158/1078-0432.CCR-16-2191DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5762201PMC
September 2017

Activity of distinct growth factor receptor network components in breast tumors uncovers two biologically relevant subtypes.

Genome Med 2017 04 26;9(1):40. Epub 2017 Apr 26.

Department of Pharmacology and Toxicology, University of Utah, 30 S 2000 E, Salt Lake City, UT, 84108, USA.

Background: The growth factor receptor network (GFRN) plays a significant role in driving key oncogenic processes. However, assessment of global GFRN activity is challenging due to complex crosstalk among GFRN components, or pathways, and the inability to study complex signaling networks in patient tumors. Here, pathway-specific genomic signatures were used to interrogate GFRN activity in breast tumors and the consequent phenotypic impact of GRFN activity patterns.

Methods: Novel pathway signatures were generated in human primary mammary epithelial cells by overexpressing key genes from GFRN pathways (HER2, IGF1R, AKT1, EGFR, KRAS (G12V), RAF1, BAD). The pathway analysis toolkit Adaptive Signature Selection and InteGratioN (ASSIGN) was used to estimate pathway activity for GFRN components in 1119 breast tumors from The Cancer Genome Atlas (TCGA) and across 55 breast cancer cell lines from the Integrative Cancer Biology Program (ICBP43). These signatures were investigated for their relationship to pro- and anti-apoptotic protein expression and drug response in breast cancer cell lines.

Results: Application of these signatures to breast tumor gene expression data identified two novel discrete phenotypes characterized by concordant, aberrant activation of either the HER2, IGF1R, and AKT pathways ("the survival phenotype") or the EGFR, KRAS (G12V), RAF1, and BAD pathways ("the growth phenotype"). These phenotypes described a significant amount of the variability in the total expression data across breast cancer tumors and characterized distinctive patterns in apoptosis evasion and drug response. The growth phenotype expressed lower levels of BIM and higher levels of MCL-1 proteins. Further, the growth phenotype was more sensitive to common chemotherapies and targeted therapies directed at EGFR and MEK. Alternatively, the survival phenotype was more sensitive to drugs inhibiting HER2, PI3K, AKT, and mTOR, but more resistant to chemotherapies.

Conclusions: Gene expression profiling revealed a bifurcation pattern in GFRN activity represented by two discrete phenotypes. These phenotypes correlate to unique mechanisms of apoptosis and drug response and have the potential of pinpointing targetable aberration(s) for more effective breast cancer treatments.
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http://dx.doi.org/10.1186/s13073-017-0429-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5406893PMC
April 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

FOXA1 overexpression mediates endocrine resistance by altering the ER transcriptome and IL-8 expression in ER-positive breast cancer.

Proc Natl Acad Sci U S A 2016 10 6;113(43):E6600-E6609. Epub 2016 Oct 6.

Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030; Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX 77030; Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030; Department of Medicine, Baylor College of Medicine, Houston, TX 77030;

Forkhead box protein A1 (FOXA1) is a pioneer factor of estrogen receptor α (ER)-chromatin binding and function, yet its aberration in endocrine-resistant (Endo-R) breast cancer is unknown. Here, we report preclinical evidence for a role of FOXA1 in Endo-R breast cancer as well as evidence for its clinical significance. FOXA1 is gene-amplified and/or overexpressed in Endo-R derivatives of several breast cancer cell line models. Induced FOXA1 triggers oncogenic gene signatures and proteomic profiles highly associated with endocrine resistance. Integrated omics data reveal IL8 as one of the most perturbed genes regulated by FOXA1 and ER transcriptional reprogramming in Endo-R cells. IL-8 knockdown inhibits tamoxifen-resistant cell growth and invasion and partially attenuates the effect of overexpressed FOXA1. Our study highlights a role of FOXA1 via IL-8 signaling as a potential therapeutic target in FOXA1-overexpressing ER-positive tumors.
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http://dx.doi.org/10.1073/pnas.1612835113DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5087040PMC
October 2016

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

PEG-lipid micelles enable cholesterol efflux in Niemann-Pick Type C1 disease-based lysosomal storage disorder.

Sci Rep 2016 08 30;6:31750. Epub 2016 Aug 30.

Department of Pharmaceutical Sciences, College of Pharmacy, Collaborative Life Science Building, Oregon State University, Portland OR, USA.

2-Hydroxy-propyl-β-cyclodextrin (HPβCD), a cholesterol scavenger, is currently undergoing Phase 2b/3 clinical trial for treatment of Niemann Pick Type C-1 (NPC1), a fatal neurodegenerative disorder that stems from abnormal cholesterol accumulation in the endo/lysosomes. Unfortunately, the extremely high doses of HPβCD required to prevent progressive neurodegeneration exacerbates ototoxicity, pulmonary toxicity and autophagy-based cellular defects. We present unexpected evidence that a poly (ethylene glycol) (PEG)-lipid conjugate enables cholesterol clearance from endo/lysosomes of Npc1 mutant (Npc1(-/-)) cells. Herein, we show that distearyl-phosphatidylethanolamine-PEG (DSPE-PEG), which forms 12-nm micelles above the critical micelle concentration, accumulates heavily inside cholesterol-rich late endosomes in Npc1(-/-) cells. This potentially results in cholesterol solubilization and leakage from lysosomes. High-throughput screening revealed that DSPE-PEG, in combination with HPβCD, acts synergistically to efflux cholesterol without significantly aggravating autophagy defects. These well-known excipients can be used as admixtures to treat NPC1 disorder. Increasing PEG chain lengths from 350 Da-30 kDa in DSPE-PEG micelles, or increasing DSPE-PEG content in an array of liposomes packaged with HPβCD, improved cholesterol egress, while Pluronic block copolymers capable of micelle formation showed slight effects at high concentrations. We postulate that PEG-lipid based nanocarriers can serve as bioactive drug delivery systems for effective treatment of lysosomal storage disorders.
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http://dx.doi.org/10.1038/srep31750DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5004151PMC
August 2016

Inferring causal molecular networks: empirical assessment through a community-based effort.

Nat Methods 2016 Apr 22;13(4):310-8. Epub 2016 Feb 22.

MRC Biostatistics Unit, Cambridge Institute of Public Health, Cambridge, UK.

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense.
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http://dx.doi.org/10.1038/nmeth.3773DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4854847PMC
April 2016

A Network-Based Model of Oncogenic Collaboration for Prediction of Drug Sensitivity.

Front Genet 2015 23;6:341. Epub 2015 Dec 23.

Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health & Science University, Portland OR, USA.

Tumorigenesis is a multi-step process, involving the acquisition of multiple oncogenic mutations that transform cells, resulting in systemic dysregulation that enables proliferation, invasion, and other cancer hallmarks. The goal of precision medicine is to identify therapeutically-actionable mutations from large-scale omic datasets. However, the multiplicity of oncogenes required for transformation, known as oncogenic collaboration, makes assigning effective treatments difficult. Motivated by this observation, we propose a new type of oncogenic collaboration where mutations in genes that interact with an oncogene may contribute to the oncogene's deleterious potential, a new genomic feature that we term "surrogate oncogenes." Surrogate oncogenes are representatives of these mutated subnetworks that interact with oncogenes. By mapping mutations to a protein-protein interaction network, we determine the significance of the observed distribution using permutation-based methods. For a panel of 38 breast cancer cell lines, we identified a significant number of surrogate oncogenes in known oncogenes such as BRCA1 and ESR1, lending credence to this approach. In addition, using Random Forest Classifiers, we show that these significant surrogate oncogenes predict drug sensitivity for 74 drugs in the breast cancer cell lines with a mean error rate of 30.9%. Additionally, we show that surrogate oncogenes are predictive of survival in patients. The surrogate oncogene framework incorporates unique or rare mutations from a single sample, and therefore has the potential to integrate patient-unique mutations into drug sensitivity predictions, suggesting a new direction in precision medicine and drug development. Additionally, we show the prevalence of significant surrogate oncogenes in multiple cancers from The Cancer Genome Atlas, suggesting that surrogate oncogenes may be a useful genomic feature for guiding pancancer analyses and assigning therapies across many tissue types.
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http://dx.doi.org/10.3389/fgene.2015.00341DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4688377PMC
January 2016