Proteomic profiling across breast cancer cell lines and models.

We performed quantitative proteomics on 60 human-derived breast cancer cell line models to a depth of ~13,000 proteins. The resulting high-throughput datasets were assessed for quality and reproducibility. We used the datasets to identify and characterize the subtypes of breast cancer and showed that they conform to known transcriptional subtypes, revealing that molecular subtypes are preserved even in under-sampled protein feature sets. All datasets are freely available as public resources on the LINCS portal. We anticipate that these datasets, either in isolation or in combination with complimentary measurements such as genomics, transcriptomics and phosphoproteomics, can be mined for the purpose of predicting drug response, informing cell line specific context in models of signalling pathways, and identifying markers of sensitivity or resistance to therapeutics.

Multiplexed and reproducible high content screening of live and fixed cells using Dye Drop.

High-throughput measurement of cells perturbed using libraries of small molecules, gene knockouts, or different microenvironmental factors is a key step in functional genomics and pre-clinical drug discovery. However, it remains difficult to perform accurate single-cell assays in 384-well plates, limiting many studies to well-average measurements (e.g., CellTiter-Glo®). Here we describe a public domain Dye Drop method that uses sequential density displacement and microscopy to perform multi-step assays on living cells. We use Dye Drop cell viability and DNA replication assays followed by immunofluorescence imaging to collect single-cell dose-response data for 67 investigational and clinical-grade small molecules in 58 breast cancer cell lines. By separating the cytostatic and cytotoxic effects of drugs computationally, we uncover unexpected relationships between the two. Dye Drop is rapid, reproducible, customizable, and compatible with manual or automated laboratory equipment. Dye Drop improves the tradeoff between data content and cost, enabling the collection of information-rich perturbagen-response datasets.

A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses.

The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods ( synapse.org/LINCS_MCF10A ). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes. Beyond these analyses, this dataset will serve as a resource for the broader scientific community to mine for biological insights, to compare signals carried across distinct molecular modalities, and to develop new computational methods for integrative data analysis.

Time-resolved phosphoproteomics reveals scaffolding and catalysis-responsive patterns of SHP2-dependent signaling.

SHP2 is a protein tyrosine phosphatase that normally potentiates intracellular signaling by growth factors, antigen receptors, and some cytokines, yet is frequently mutated in human cancer. Here, we examine the role of SHP2 in the responses of breast cancer cells to EGF by monitoring phosphoproteome dynamics when SHP2 is allosterically inhibited by SHP099. The dynamics of phosphotyrosine abundance at more than 400 tyrosine residues reveal six distinct response signatures following SHP099 treatment and washout. Remarkably, in addition to newly identified substrate sites on proteins such as occludin, ARHGAP35, and PLCγ2, another class of sites shows reduced phosphotyrosine abundance upon SHP2 inhibition. Sites of decreased phospho-abundance are enriched on proteins with two nearby phosphotyrosine residues, which can be directly protected from dephosphorylation by the paired SH2 domains of SHP2 itself. These findings highlight the distinct roles of the scaffolding and catalytic activities of SHP2 in effecting a transmembrane signaling response.

Chemical Biology Toolkit for DCLK1 Reveals Connection to RNA Processing.

Doublecortin-like kinase 1 (DCLK1) is critical for neurogenesis, but overexpression is also observed in multiple cancers and is associated with poor prognosis. Nevertheless, the function of DCLK1 in cancer, especially the context-dependent functions, are poorly understood. We present a "toolkit" that includes the DCLK1 inhibitor DCLK1-IN-1, a complementary DCLK1-IN-1-resistant mutation G532A, and kinase dead mutants D511N and D533N, which can be used to investigate signaling pathways regulated by DCLK1. Using a cancer cell line engineered to be DCLK1 dependent for growth and cell migration, we show that this toolkit can be used to discover associations between DCLK1 kinase activity and biological processes. In particular, we show an association between DCLK1 and RNA processing, including the identification of CDK11 as a potential substrate of DCLK1 using phosphoproteomics.

Inhibition of Haspin Kinase Promotes Cell-Intrinsic and Extrinsic Antitumor Activity.

Patients with melanoma resistant to RAF/MEK inhibitors (RMi) are frequently resistant to other therapies, such as immune checkpoint inhibitors (ICI), and individuals succumb to their disease. New drugs that control tumor growth and favorably modulate the immune environment are therefore needed. We report that the small-molecule CX-6258 has potent activity against both RMi-sensitive (RMS) and -resistant (RMR) melanoma cell lines. Haspin kinase (HASPIN) was identified as a target of CX-6258. HASPIN inhibition resulted in reduced proliferation, frequent formation of micronuclei, recruitment of cGAS, and activation of the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway. In murine models, CX-6258 induced a potent cGAS-dependent type-I IFN response in tumor cells, increased IFNγ-producing CD8+ T cells, and reduced Treg frequency in vivo. HASPIN was more strongly expressed in malignant compared with healthy tissue and its inhibition by CX-6258 had minimal toxicity in ex vivo-expanded human tumor-infiltrating lymphocytes (TIL), proliferating TILs, and in vitro differentiated neurons, suggesting a potential therapeutic index for anticancer therapy. Furthermore, the activity of CX-6258 was validated in several Ewing sarcoma and multiple myeloma cell lines. Thus, HASPIN inhibition may overcome drug resistance in melanoma, modulate the immune environment, and target a vulnerability in different cancer lineages. SIGNIFICANCE: HASPIN inhibition by CX-6258 is a novel and potent strategy for RAF/MEK inhibitor-resistant melanoma and potentially other tumor types. HASPIN inhibition has direct antitumor activity and induces a favorable immune microenvironment.

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

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.

Multiomics Profiling Establishes the Polypharmacology of FDA-Approved CDK4/6 Inhibitors and the Potential for Differential Clinical Activity.

The target profiles of many drugs are established early in their development and are not systematically revisited at the time of FDA approval. Thus, it is often unclear whether therapeutics with the same nominal targets but different chemical structures are functionally equivalent. In this paper we use five different phenotypic and biochemical assays to compare approved inhibitors of cyclin-dependent kinases 4/6-collectively regarded as breakthroughs in the treatment of hormone receptor-positive breast cancer. We find that transcriptional, proteomic, and phenotypic changes induced by palbociclib, ribociclib, and abemaciclib differ significantly; abemaciclib in particular has advantageous activities partially overlapping those of alvocidib, an older polyselective CDK inhibitor. In cells and mice, abemaciclib inhibits kinases other than CDK4/6 including CDK2/cyclin A/E-implicated in resistance to CDK4/6 inhibition-and CDK1/cyclin B. The multifaceted experimental and computational approaches described here therefore uncover underappreciated differences in CDK4/6 inhibitor activities with potential importance in treating human patients.

A multitargeted probe-based strategy to identify signaling vulnerabilities in cancers.

Most cancer cells are dependent on a network of deregulated signaling pathways for survival and are insensitive, or rapidly evolve resistance, to selective inhibitors aimed at a single target. For these reasons, drugs that target more than one protein (polypharmacology) can be clinically advantageous. The discovery of useful polypharmacology remains serendipitous and is challenging to characterize and validate. In this study, we developed a non-genetic strategy for the identification of pathways that drive cancer cell proliferation and represent exploitable signaling vulnerabilities. Our approach is based on using a multitargeted kinase inhibitor, SM1-71, as a tool compound to identify combinations of targets whose simultaneous inhibition elicits a potent cytotoxic effect. As a proof of concept, we applied this approach to a KRAS-dependent non-small cell lung cancer (NSCLC) cell line, H23-KRASG12C Using a combination of phenotypic screens, signaling analyses, and kinase inhibitors, we found that dual inhibition of MEK1/2 and insulin-like growth factor 1 receptor (IGF1R)/insulin receptor (INSR) is critical for blocking proliferation in cells. Our work supports the value of multitargeted tool compounds with well-validated polypharmacology and target space as tools to discover kinase dependences in cancer. We propose that the strategy described here is complementary to existing genetics-based approaches, generalizable to other systems, and enabling for future mechanistic and translational studies of polypharmacology in the context of signaling vulnerabilities in cancers.

A dynamic view of the proteomic landscape during differentiation of ReNcell VM cells, an immortalized human neural progenitor line.

The immortalized human ReNcell VM cell line represents a reproducible and easy-to-propagate cell culture system for studying the differentiation of neural progenitors. To better characterize the starting line and its subsequent differentiation, we assessed protein and phospho-protein levels and cell morphology over a 15-day period during which ReNcell progenitors differentiated into neurons, astrocytes and oligodendrocytes. Five of the resulting datasets measured protein levels or states of phosphorylation based on tandem-mass-tag (TMT) mass spectrometry and four datasets characterized cellular phenotypes using high-content microscopy. Proteomic analysis revealed reproducible changes in pathways responsible for cytoskeletal rearrangement, cell phase transitions, neuronal migration, glial differentiation, neurotrophic signalling and extracellular matrix regulation. Proteomic and imaging data revealed accelerated differentiation in cells treated with the poly-selective CDK and GSK3 inhibitor kenpaullone or the HMG-CoA reductase inhibitor mevastatin, both of which have previously been reported to promote neural differentiation. These data provide in-depth information on the ReNcell progenitor state and on neural differentiation in the presence and absence of drugs, setting the stage for functional studies.

From word models to executable models of signaling networks using automated assembly.

Word models (natural language descriptions of molecular mechanisms) are a common currency in spoken and written communication in biomedicine but are of limited use in predicting the behavior of complex biological networks. We present an approach to building computational models directly from natural language using automated assembly. Molecular mechanisms described in simple English are read by natural language processing algorithms, converted into an intermediate representation, and assembled into executable or network models. We have implemented this approach in the Integrated Network and Dynamical Reasoning Assembler (INDRA), which draws on existing natural language processing systems as well as pathway information in Pathway Commons and other online resources. We demonstrate the use of INDRA and natural language to model three biological processes of increasing scope: (i) p53 dynamics in response to DNA damage, (ii) adaptive drug resistance in BRAF-V600E-mutant melanomas, and (iii) the RAS signaling pathway. The use of natural language makes the task of developing a model more efficient and it increases model transparency, thereby promoting collaboration with the broader biology community.

Designing Drug-Response Experiments and Quantifying their Results.

We developed a Python package to help in performing drug-response experiments at medium and high throughput and evaluating sensitivity metrics from the resulting data. In this article, we describe the steps involved in (1) generating files necessary for treating cells with the HP D300 drug dispenser, by pin transfer or by manual pipetting; (2) merging the data generated by high-throughput slide scanners, such as the Perkin Elmer Operetta, with treatment annotations; and (3) analyzing the results to obtain data normalized to untreated controls and sensitivity metrics such as IC50 or GR50 . These modules are available on GitHub and provide an automated pipeline for the design and analysis of high-throughput drug response experiments, that helps to prevent errors that can arise from manually processing large data files. © 2017 by John Wiley & Sons, Inc.

Spatiotemporal Models of the Asymmetric Division Cycle of Caulobacter crescentus.

The spatial localization of proteins within the cytoplasm of bacteria is an underappreciated but critical aspect of cell cycle regulation for many prokaryotes. In Caulobacter crescentus-a model organism for the study of asymmetric cell reproduction in prokaryotes-heterogeneous localization of proteins has been identified as the underlying cause of asymmetry in cell morphology, DNA replication, and cell division. However, significant questions remain. Firstly, the mechanisms by which proteins localize in the organelle-free prokaryotic cytoplasm remain obscure. Furthermore, how variations in the spatial and temporal dynamics of cell fate determinants regulate signaling pathways and orchestrate the complex programs of asymmetric cell division and differentiation are subjects of ongoing research. In this chapter, we review current efforts in investigating these two questions. We describe how mathematical models of spatiotemporal protein dynamics are being used to generate and test competing hypotheses and provide complementary insight about the control mechanisms that regulate asymmetry in protein localization and cell division.

A stochastic spatiotemporal model of a response-regulator network in the Caulobacter crescentus cell cycle.

The asymmetric cell division cycle in Caulobacter crescentus is controlled by an elaborate molecular mechanism governing the production, activation and spatial localization of a host of interacting proteins. In previous work, we proposed a deterministic mathematical model for the spatiotemporal dynamics of six major regulatory proteins. In this paper, we study a stochastic version of the model, which takes into account molecular fluctuations of these regulatory proteins in space and time during early stages of the cell cycle of wild-type Caulobacter cells. We test the stochastic model with regard to experimental observations of increased variability of cycle time in cells depleted of the divJ gene product. The deterministic model predicts that overexpression of the divK gene blocks cell cycle progression in the stalked stage; however, stochastic simulations suggest that a small fraction of the mutants cells do complete the cell cycle normally.

Dynamical Localization of DivL and PleC in the Asymmetric Division Cycle of Caulobacter crescentus: A Theoretical Investigation of Alternative Models.

Cell-fate asymmetry in the predivisional cell of Caulobacter crescentus requires that the regulatory protein DivL localizes to the new pole of the cell where it up-regulates CckA kinase, resulting in a gradient of CtrA~P across the cell. In the preceding stage of the cell cycle (the "stalked" cell), DivL is localized uniformly along the cell membrane and maintained in an inactive form by DivK~P. It is unclear how DivL overcomes inhibition by DivK~P in the predivisional cell simply by changing its location to the new pole. It has been suggested that co-localization of DivL with PleC phosphatase at the new pole is essential to DivL's activity there. However, there are contrasting views on whether the bifunctional enzyme, PleC, acts as a kinase or phosphatase at the new pole. To explore these ambiguities, we formulated a mathematical model of the spatiotemporal distributions of DivL, PleC and associated proteins (DivJ, DivK, CckA, and CtrA) during the asymmetric division cycle of a Caulobacter cell. By varying localization profiles of DivL and PleC in our model, we show how the physiologically observed spatial distributions of these proteins are essential for the transition from a stalked cell to a predivisional cell. Our simulations suggest that PleC is a kinase in predivisional cells, and that, by sequestering DivK~P, the kinase form of PleC enables DivL to be reactivated at the new pole. Hence, co-localization of PleC kinase and DivL is essential to establishing cellular asymmetry. Our simulations reproduce the experimentally observed spatial distribution and phosphorylation status of CtrA in wild-type and mutant cells. Based on the model, we explore novel combinations of mutant alleles, making predictions that can be tested experimentally.

Spheroid culture for enhanced differentiation of human embryonic stem cells to hepatocyte-like cells.

Stem cell-derived hepatocyte-like cells hold great potential for the treatment of liver disease and for drug toxicity screening. The success of these applications hinges on the generation of differentiated cells with high liver specific activities. Many protocols have been developed to guide human embryonic stem cells (hESCs) to differentiate to the hepatic lineage. Here we report cultivation of hESCs as three-dimensional aggregates that enhances their differentiation to hepatocyte-like cells. Differentiation was first carried out in monolayer culture for 20 days. Subsequently cells were allowed to self-aggregate into spheroids. Significantly higher expression of liver-specific transcripts and proteins, including Albumin, phosphoenolpyruvate carboxykinase, and asialoglycoprotein receptor 1 was observed. The differentiated phenotype was sustained for more than 2 weeks in the three-dimensional spheroid culture system, significantly longer than in monolayer culture. Cells in spheroids exhibit morphological and ultrastructural characteristics of primary hepatocytes by scanning and transmission electron microscopy in addition to mature functions, such as biliary excretion of metabolic products and cytochrome P450 activities. This three-dimensional spheroid culture system may be appropriate for generating high quality, functional hepatocyte-like cells from ESCs.

Potential role of a bistable histidine kinase switch in the asymmetric division cycle of Caulobacter crescentus.

The free-living aquatic bacterium, Caulobacter crescentus, exhibits two different morphologies during its life cycle. The morphological change from swarmer cell to stalked cell is a result of changes of function of two bi-functional histidine kinases, PleC and CckA. Here, we describe a detailed molecular mechanism by which the function of PleC changes between phosphatase and kinase state. By mathematical modeling of our proposed molecular interactions, we derive conditions under which PleC, CckA and its response regulators exhibit bistable behavior, thus providing a scenario for robust switching between swarmer and stalked states. Our simulations are in reasonable agreement with in vitro and in vivo experimental observations of wild type and mutant phenotypes. According to our model, the kinase form of PleC is essential for the swarmer-to-stalked transition and to prevent premature development of the swarmer pole. Based on our results, we reconcile some published experimental observations and suggest novel mutants to test our predictions.

Enhanced differentiation of adult bone marrow-derived stem cells to liver lineage in aggregate culture.

Hepatocyte-like cells derived from stem cells hold great potential for clinical and pharmaceutical applications, including high-throughput drug toxicity screening. We report a three-dimensional aggregate culture system for the directed differentiation of adult rat bone marrow-derived stem cells, rat multipotent adult progenitor cells, to hepatocyte-like cells. Compared to adherent monolayer cultures, differentiation in the aggregate culture system resulted in significantly higher expression level of liver-specific transcripts, including an increased albumin mRNA level, and higher levels of albumin and urea secretion. This coincides with the presence of significantly more cells that express intracellular albumin at levels found in primary hepatocytes. The differentiated cell aggregates exhibited cytochrome P450-mediated ethoxyresorufin-O-dealkylation and pentoxyresorufin-O-dealkylation activity. Consistent with these increased mature functions, cells within the aggregates were shown to have many ultrastructural features of mature hepatocytes by transmission electron microscopy. With the scalability of the aggregate culture system and the enhanced differentiation capability, this system may facilitate translation of generating hepatocytes from stem cells to technology.

Human embryonic and rat adult stem cells with primitive endoderm-like phenotype can be fated to definitive endoderm, and finally hepatocyte-like cells.

Stem cell-derived hepatocytes may be an alternative cell source to treat liver diseases or to be used for pharmacological purposes. We developed a protocol that mimics mammalian liver development, to differentiate cells with pluripotent characteristics to hepatocyte-like cells. The protocol supports the stepwise differentiation of human embryonic stem cells (ESC) to cells with characteristics of primitive streak (PS)/mesendoderm (ME)/definitive endoderm (DE), hepatoblasts, and finally cells with phenotypic and functional characteristics of hepatocytes. Remarkably, the same protocol can also differentiate rat multipotent adult progenitor cells (rMAPCs) to hepatocyte-like cells, even though rMAPC are isolated clonally from cultured rat bone marrow (BM) and have characteristics of primitive endoderm cells. A fraction of rMAPCs can be fated to cells expressing genes consistent with a PS/ME/DE phenotype, preceding the acquisition of phenotypic and functional characteristics of hepatocytes. Although the hepatocyte-like progeny derived from both cell types is mixed, between 10-20% of cells are developmentally consistent with late fetal hepatocytes that have attained synthetic, storage and detoxifying functions near those of adult hepatocytes. This differentiation protocol will be useful for generating hepatocyte-like cells from rodent and human stem cells, and to gain insight into the early stages of liver development.