The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS2. The L1000CDS2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS2, we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS2 tool can be applied in many biological and biomedical settings, while improving the extraction of knowledge from the LINCS L1000 resource.
Various genetic mutations associated with cancer are known to alter cell signaling, but it is not clear whether they dysregulate signaling pathways by altering the abundance of pathway proteins. Using a combination of RNA sequencing and ultrasensitive targeted proteomics, we defined the primary components-16 core proteins and 10 feedback regulators-of the epidermal growth factor receptor (EGFR)-mitogen-activated protein kinase (MAPK) pathway in normal human mammary epithelial cells and then quantified their absolute abundance across a panel of normal and breast cancer cell lines as well as fibroblasts. We found that core pathway proteins were present at very similar concentrations across all cell types, with a variance similar to that of proteins previously shown to display conserved abundances across species. In contrast, EGFR and transcriptionally controlled feedback regulators were present at highly variable concentrations. The absolute abundance of most core proteins was between 50,000 and 70,000 copies per cell, but the adaptors SOS1, SOS2, and GAB1 were found at far lower amounts (2000 to 5000 copies per cell). MAPK signaling showed saturation in all cells between 3000 and 10,000 occupied EGFRs, consistent with the idea that adaptors limit signaling. Our results suggest that the relative stoichiometry of core MAPK pathway proteins is very similar across different cell types, with cell-specific differences mostly restricted to variable amounts of feedback regulators and receptors. The low abundance of adaptors relative to EGFR could be responsible for previous observations that only a fraction of total cell surface EGFR is capable of rapid endocytosis, high-affinity binding, and mitogenic signaling.
Drug sensitivity and resistance are conventionally quantified by IC50 or Emax values, but these metrics are highly sensitive to the number of divisions taking place over the course of a response assay. The dependency of IC50 and Emax on division rate creates artefactual correlations between genotype and drug sensitivity, while obscuring valuable biological insights and interfering with biomarker discovery. We derive alternative small molecule drug-response metrics that are insensitive to division number. These are based on estimation of the magnitude of drug-inducedgrowthrateinhibition (GR) using endpoint or time-course assays. We show that GR50 and GRmax are superior to conventional metrics for assessing the effects of small molecule drugs in dividing cells. Moreover, adopting GR metrics requires only modest changes in experimental protocols. We expect GR metrics to improve the study of cell signaling and growth using small molecules and biologics and to facilitate the discovery of drug-response biomarkers and the identification of drugs effective against specific patient-derived tumor cells.
Drugs that inhibit RAF/MEK signaling, such as vemurafenib, elicit profound but often temporary anti-tumor responses in patients with BRAF(V) (600E) melanoma. Adaptive responses to RAF/MEK inhibition occur on a timescale of hours to days, involve homeostatic responses that reactivate MAP kinase signaling and compensatory mitogenic pathways, and attenuate the anti-tumor effects of RAF/MEK inhibitors. We profile adaptive responses across a panel of melanoma cell lines using multiplex biochemical measurement, single-cell assays, and statistical modeling and show that adaptation involves at least six signaling cascades that act to reduce drug potency (IC50) and maximal effect (i.e., Emax ≪ 1). Among these cascades, we identify a role for JNK/c-Jun signaling in vemurafenib adaptation and show that RAF and JNK inhibitors synergize in cell killing. This arises because JNK inhibition prevents a subset of cells in a cycling population from becoming quiescent upon vemurafenib treatment, thereby reducing drug Emax. Our findings demonstrate the breadth and diversity of adaptive responses to RAF/MEK inhibition and a means to identify which steps in a signaling cascade are most predictive of phenotypic response.
BACKGROUND: Soluble growth factors present in the microenvironment play a major role in tumor development, invasion, metastasis, and responsiveness to targeted therapies. While the biochemistry of growth factor-dependent signal transduction has been studied extensively in individual cell types, relatively little systematic data is available across genetically diverse cell lines.RESULTS: We describe a quantitative and comparative dataset focused on immediate-early signaling that regulates the AKT (AKT1/2/3) and ERK (MAPK1/3) pathways in a canonical panel of well-characterized breast cancer lines; we also provide interactive web-based tools to facilitate follow-on analysis of the data. Our findings show that breast cancers are diverse with respect to ligand sensitivity and signaling biochemistry. Surprisingly, triple negative breast cancers (TNBCs; which express low levels of ErbB2, progesterone, and estrogen receptors) are the most broadly responsive to growth factors and HER2amp cancers (which overexpress ErbB2) the least. The ratio of ERK to AKT activation varies with ligand and subtype, with a systematic bias in favor of ERK in hormone receptor positive (HR+) cells. The factors that correlate with growth-factor responsiveness depend on whether fold-change or absolute activity is considered the key biological variable, and it differs between ERK and AKT pathways. CONCLUSIONS: Responses to growth factors are highly diverse across breast cancer cell lines, even within the same subtype. A simple four-part heuristic suggests that diversity arises from variation in receptor abundance, an ERK/AKT bias that depends on ligand identity, a set of factors common to all receptors that varies in abundance or activity with cell line, and "indirect negative regulation" by ErbB2. This analysis sets the stage for development of a mechanistic and predictive model of growth factors signaling in diverse cancer lines. Interactive tools for looking up these results and downloading raw data are available at http://lincs.hms.harvard.edu/niepel-bmcbiol-2014/.
For the Library of Integrated Network-based Cellular Signatures (LINCS) project many gene expression signatures using the L1000 technology have been produced. The L1000 technology is a cost-effective method to profile gene expression in large scale. LINCS Canvas Browser (LCB) is an interactive HTML5 web-based software application that facilitates querying, browsing and interrogating many of the currently available LINCS L1000 data. LCB implements two compacted layered canvases, one to visualize clustered L1000 expression data, and the other to display enrichment analysis results using 30 different gene set libraries. Clicking on an experimental condition highlights gene-sets enriched for the differentially expressed genes from the selected experiment. A search interface allows users to input gene lists and query them against over 100 000 conditions to find the top matching experiments. The tool integrates many resources for an unprecedented potential for new discoveries in systems biology and systems pharmacology. The LCB application is available at http://www.maayanlab.net/LINCS/LCB. Customized versions will be made part of the http://lincscloud.org and http://lincs.hms.harvard.edu websites.
mTOR is a highly conserved serine/threonine protein kinase that serves as a central regulator of cell growth, survival and autophagy. Deregulation of the PI3K/Akt/mTOR signaling pathway occurs commonly in cancer and numerous inhibitors targeting the ATP-binding site of these kinases are currently undergoing clinical evaluation. Here we report the characterization of Torin2, a second generation ATP-competitive inhibitor that is potent and selective for mTOR with a superior pharmacokinetic profile to previous inhibitors. Torin2 inhibited mTORC1-dependent T389 phosphorylation on S6K (RPS6KB1) with an EC50 of 250 pM with approximately 800-fold selectivity for cellular mTOR versus PI3K. Torin2 also exhibited potent biochemical and cellular activity against PIKK family kinases including ATM (EC50 28 nM), ATR (EC50 35 nM) and DNA-PK (EC50 118 nM) (PRKDC), the inhibition of which sensitized cells to Irradiation. Similar to the earlier generation compound Torin1 and in contrast to other reported mTOR inhibitors, Torin2 inhibited mTOR kinase and mTORC1 signaling activities in a sustained manner suggestive of a slow dissociation from the kinase. Cancer cell treatment with Torin2 for 24 hours resulted in a prolonged block in negative feedback and consequent T308 phosphorylation on Akt. These effects were associated with strong growth inhibition in vitro. Single agent treatment with Torin2 in vivo did not yield significant efficacy against KRAS-driven lung tumors, but the combination of Torin2 with MEK inhibitor AZD6244 yielded a significant growth inhibition. Taken together, our findings establish Torin2 as a strong candidate for clinical evaluation in a broad number of oncological settings where mTOR signaling has a pathogenic role.
MOTIVATION: Identifying the cellular wiring that connects genomic perturbations to transcriptional changes in cancer is essential to gain a mechanistic understanding of disease initiation, progression, and ultimately to predict drug response. We have developed a method called Tied Diffusion Through Interacting Events (TieDIE) that uses a network diffusion approach to connect genomic perturbations to gene expression changes characteristic of cancer subtypes. The method computes a sub-network of protein-protein interactions, predicted transcription factor-to-target connections, and curated interactions from literature that connects genomic and transcriptomic perturbations. RESULTS: Application of TieDIE to The Cancer Genome Atlas (TCGA) and a breast cancer cell line dataset identified key signaling pathways, with examples impinging on MYC activity. Interlinking genes are predicted to correspond to essential components of cancer signaling and may provide a mechanistic explanation of tumor character and suggest subtype-specific drug targets. AVAILABILITY: Software is available from the Stuart lab's wiki: https://sysbiowiki.soe.ucsc.edu/tiedie. CONTACT: email@example.com.
Protein kinases play critical roles in many biological and pathological processes, making them important targets for therapeutic drugs. Here, we desired to increase the throughput for kinome-wide profiling. A new workflow coupling ActivX ATP probe (AAP) affinity reagents with isotopic labeling to quantify the relative levels and modification states of kinases in cell lysates is described. We compared the new workflow to a classical proteomics approach in which fractionation was used to identify low-abundance kinases. We find that AAPs enriched approximately 90 kinases in a single analysis involving six cell lines or states in a single run, an 8-fold improvement in throughput relative to the classical approach. In general, AAPs cross-linked to both the active and inactive states of kinases but performing phosphopeptide enrichment made it possible to measure the phospho sites of regulatory residues lying in the kinase activation loops, providing information on activation state. When we compared the kinome across the six cell lines, representative of different breast cancer clinical subtypes, we observed that many kinases, particularly receptor tyrosine kinases, varied widely in abundance, perhaps explaining the differential sensitivities to kinase inhibitor drugs. The improved kinome profiling methods described here represent an effective means to perform systematic analysis of kinases involved in cell signaling and oncogenic transformation and for analyzing the effect of different inhibitory drugs.
The basket of the nuclear pore complex (NPC) is generally depicted as a discrete structure of eight protein filaments that protrude into the nucleoplasm and converge in a ring distal to the NPC. We show that the yeast proteins Mlp1p and Mlp2p are necessary components of the nuclear basket and that they also embed the NPC within a dynamic protein network, whose extended interactome includes the spindle organizer, silencing factors, the proteasome, and key components of messenger ribonucleoproteins (mRNPs). Ultrastructural observations indicate that the basket reduces chromatin crowding around the central transporter of the NPC and might function as a docking site for mRNP during nuclear export. In addition, we show that the Mlps contribute to NPC positioning, nuclear stability, and nuclear envelope morphology. Our results suggest that the Mlps are multifunctional proteins linking the nuclear transport channel to multiple macromolecular complexes involved in the regulation of gene expression and chromatin maintenance.
The mitogen-activated kinases JNK1/2/3 are key enzymes in signaling modules that transduce and integrate extracellular stimuli into coordinated cellular response. Here, we report the discovery of irreversible inhibitors of JNK1/2/3. We describe two JNK3 cocrystal structures at 2.60 and 2.97 Å resolution that show the compounds form covalent bonds with a conserved cysteine residue. JNK-IN-8 is a selective JNK inhibitor that inhibits phosphorylation of c-Jun, a direct substrate of JNK, in cells exposed to submicromolar drug in a manner that depends on covalent modification of the conserved cysteine residue. Extensive biochemical, cellular, and pathway-based profiling establish the selectivity of JNK-IN-8 for JNK and suggests that the compound will be broadly useful as a pharmacological probe of JNK-dependent signal transduction. Potential lead compounds have also been identified for kinases, including IRAK1, PIK3C3, PIP4K2C, and PIP5K3.
An intensive recent effort to develop ATP-competitive mTOR inhibitors has resulted in several potent and selective molecules such as Torin1, PP242, KU63794 and WYE354. These inhibitors are being widely used as pharmacological probes of mTOR-dependent biology. To determine the potency and specificity of these agents, we have undertaken a systematic, kinome-wide effort to profile their selectivity and potency using chemical proteomics, and assays for enzymatic activity, protein binding and disruption of cellular signaling. Enzymatic and cellular assays revealed that all four compounds are potent inhibitors of mTORC1 and mTORC2, with Torin1 exhibiting approximately 20-fold greater potency for inhibition of T389 phosphorylation on S6 kinases (EC50 = 2 nM) relative to other inhibitors. In vitro biochemical profiling at 10 μM revealed binding of PP242 to numerous kinases, while WYE354 and KU63794 bound only to p38 kinases and PI3K isoforms and Torin1 to ATR, ATM and DNA-PK. Analysis of these proteins targets in cellular assays did not reveal any off-target activities for Torin1, WYE354 and KU63794 at concentrations below 1 μM but did show that PP242 efficiently inhibited RET receptor (EC50: 42 nM) and JAK1/2/3 kinases (EC50: 780 nM). In addition, Torin1 displayed unusually slow kinetics for inhibition of the mTORC1/2 complex, a property likely to contribute to the pharmacology of this inhibitor. Our results demonstrated that with the exception of PP242, available ATP-competitive compounds are highly selective mTOR inhibitors when applied to cells at concentrations below 1 μM, and that the compounds may represent a starting point for medicinal chemistry efforts aimed at developing inhibitors of other PIKK-family kinases.
Centrosomes organize the bipolar mitotic spindle, and centrosomal defects cause chromosome instability. Protein phosphorylation modulates centrosome function, and we provide a comprehensive map of phosphorylation on intact yeast centrosomes (18 proteins). Mass spectrometry was used to identify 297 phosphorylation sites on centrosomes from different cell cycle stages. We observed different modes of phosphoregulation via specific protein kinases, phosphorylation site clustering, and conserved phosphorylated residues. Mutating all eight cyclin-dependent kinase (Cdk)–directed sites within the core component, Spc42, resulted in lethality and reduced centrosomal assembly. Alternatively, mutation of one conserved Cdk site within g-tubulin (Tub4-S360D) caused mitotic delay and aberrant anaphase spindle elongation. Our work establishes the extent and complexity of this prominent posttranslational modification in centrosome biology and provides specific examples of phosphorylation control in centrosome function.
Variability in patient responses to even the most potent and targeted therapeutics is now the primary challenge facing drug discovery and patient care, particularly in oncology and immune therapy. Variability with respect to mechanisms of induced resistance is observed both in drug-naive patients and among those who are initially responsive. Genomics has developed powerful tools for systematic interrogation of disease genotype and transcriptional states (particularly in cancer) and for correlation of these measures with parameters of disease such as histological diagnosis and outcome. In contrast, mechanistic preclinical studies remain relatively narrowly focused, leading to many apparent contradictions and poor understanding of the determinants of response. We describe the emergence of a systems pharmacology approach that is mechanistic, quantitative, probabilistic, and postgenomic and promises to do for mechanistic pharmacology what genomics is doing for correlative studies. We focus on studies in cell lines (which currently dominate mechanism-oriented analysis), but our arguments are equally valid for real tumors studied in short-term culture as xenografts and, perhaps some time in the future, in humans.
Although the nuclear pore complex (NPC) is best known for its primary function as the key regulator of molecular traffic between the cytoplasm and the nucleus, a growing body of experimental evidence suggests that this structure participates in a considerably broader range of cellular activities on both sides of the nuclear envelope. Indeed, the NPC is emerging as an important regulator of gene expression through its influence on the internal architectural organization of the nucleus and its apparently extensive involvement in coordinating the seamless delivery of genetic information to the cytoplasmic protein synthesis machinery.
The ErbB signaling pathways, which regulate diverse physiological responses such as cell survival, proliferation and motility, have been subjected to extensive molecular analysis. Nonetheless, it remains poorly understood how different ligands induce different responses and how this is affected by oncogenic mutations. To quantify signal flow through ErbB-activated pathways we have constructed, trained and analyzed a mass action model of immediate-early signaling involving ErbB1-4 receptors (EGFR, HER2/Neu2, ErbB3 and ErbB4), and the MAPK and PI3K/Akt cascades. We find that parameter sensitivity is strongly dependent on the feature (e.g. ERK or Akt activation) or condition (e.g. EGF or heregulin stimulation) under examination and that this context dependence is informative with respect to mechanisms of signal propagation. Modeling predicts log-linear amplification so that significant ERK and Akt activation is observed at ligand concentrations far below the K(d) for receptor binding. However, MAPK and Akt modules isolated from the ErbB model continue to exhibit switch-like responses. Thus, key system-wide features of ErbB signaling arise from nonlinear interaction among signaling elements, the properties of which appear quite different in context and in isolation.
Recent advances in single-cell assays have focused attention on the fact that even members of a genetically identical group of cells or organisms in identical environments can exhibit variability in drug sensitivity, cellular response, and phenotype. Underlying much of this variability is stochasticity in gene expression, which can produce unique proteomes even in genetically identical cells. Here we discuss the consequences of non-genetic cell-to-cell variability in the cellular response to drugs and its potential impact for the treatment of human disease.