Three tyrosine kinase inhibitors cause cardiotoxicity by inducing endoplasmic reticulum stress and inflammation in cardiomyocytes.

BACKGROUND: Tyrosine kinase inhibitors (TKIs) are anti-cancer therapeutics often prescribed for long-term treatment. Many of these treatments cause cardiotoxicity with limited cure. We aim to clarify molecular mechanisms of TKI-induced cardiotoxicity so as to find potential targets for treating the adverse cardiac complications. METHODS: Eight TKIs with different levels of cardiotoxicity reported are selected. Phenotypic and transcriptomic responses of human cardiomyocytes to TKIs at varying doses and times are profiled and analyzed. Stress responses and signaling pathways that modulate cardiotoxicity induced by three TKIs are validated in cardiomyocytes and rat hearts. RESULTS: Toxicity rank of the eight TKIs determined by measuring their effects on cell viability, contractility, and respiration is largely consistent with that derived from database or literature, indicating that human cardiomyocytes are a good cellular model for studying cardiotoxicity. When transcriptomes are measured for selected TKI treatments with different levels of toxicity in human cardiomyocytes, the data are classified into 7 clusters with mainly single-drug clusters. Drug-specific effects on the transcriptome dominate over dose-, time- or toxicity-dependent effects. Two clusters with three TKIs (afatinib, ponatinib, and sorafenib) have the top enriched pathway as the endoplasmic reticulum stress (ERS). All three TKIs induce ERS in rat primary cardiomyocytes and ponatinib activates the IRE1α-XBP1s axis downstream of ERS in the hearts of rats underwent a 7-day course of drug treatment. To look for potential triggers of ERS, we find that the three TKIs induce transient reactive oxygen species followed by lipid peroxidation. Inhibiting either PERK or IRE1α downstream of ERS blocks TKI-induced cardiac damages, represented by the induction of cardiac fetal and pro-inflammatory genes without causing more cell death. CONCLUSIONS: Our data contain rich information about phenotypic and transcriptional responses of human cardiomyocytes to eight TKIs, uncovering potential molecular mechanisms in modulating cardiotoxicity. ER stress is activated by multiple TKIs and leads to cardiotoxicity through promoting expression of pro-inflammatory factors and cardiac fetal genes. ER stress-induced inflammation is a promising therapeutic target to mitigate ponatinib- and sorafenib-induced cardiotoxicity.

Continuous Monitoring of Tau-Induced Neurotoxicity in Patient-Derived iPSC-Neurons.

Tau aggregation within neurons is a critical feature of Alzheimer's disease (AD) and related tauopathies. It is believed that soluble pathologic tau species seed the formation of tau aggregates in a prion-like manner and propagate through connected neurons during the progression of disease. Both soluble and aggregated forms of tau are thought to have neurotoxic properties. In addition, different strains of misfolded tau may cause differential neurotoxicity. In this work, we present an accelerated human neuronal model of tau-induced neurotoxicity that incorporates both soluble tau species and tau aggregation. Using patient-derived induced pluripotent stem cell (iPSC) neurons expressing a tau aggregation biosensor, we develop a cell culture system that allows continuous assessment of both induced tau aggregation and neuronal viability at single-cell resolution for periods of >1 week. We show that exogenous tau "seed" uptake, as measured by tau repeat domain (TauRD) reporter aggregation, increases the risk for subsequent neuronal death in vitro These results are the first to directly visualize neuronal TauRD aggregation and subsequent cell death in single human iPSC neurons. Specific morphologic strains or patterns of TauRD aggregation are then identified and associated with differing neurotoxicity. Furthermore, we demonstrate that familial AD iPSC neurons expressing the PSEN1 L435F mutation exhibit accelerated TauRD aggregation kinetics and a tau strain propagation bias when compared with control iPSC neurons.SIGNIFICANCE STATEMENT Neuronal intracellular aggregation of the microtubule binding protein tau occurs in Alzheimer's disease and related neurodegenerative tauopathies. Tau aggregates are believed to spread from neuron to neuron via prion-like misfolded tau seeds. Our work develops a human neuronal live-imaging system to visualize seeded tau aggregation and tau-induced neurotoxicity within single neurons. Using an aggregation-sensing tau reporter, we find that neuronal uptake and propagation of tau seeds reduces subsequent survival. In addition, human induced pluripotent stem cell (iPSC) neurons carrying an Alzheimer's disease-causing mutation in presenilin-1 undergo tau seeding more rapidly than control iPSC neurons. However, they do not show subsequent differences in neuronal survival. Finally, specific morphologies of tau aggregates are associated with increased neurotoxicity.

Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs.

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-induced growth rate inhibition (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.

Analysis of growth factor signaling in genetically diverse breast cancer lines.

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 are 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 they differ 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 an "indirect negative regulation" by ErbB2. This analysis sets the stage for the development of a mechanistic and predictive model of growth factor 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/.

ß-Amyloid species production and tau phosphorylation in iPSC-neurons with reference to neuropathologically characterized matched donor brains.

A basic assumption underlying induced pluripotent stem cell (iPSC) models of neurodegeneration is that disease-relevant pathologies present in brain tissue are also represented in donor-matched cells differentiated from iPSCs. However, few studies have tested this hypothesis in matched iPSCs and neuropathologically characterized donated brain tissues. To address this, we assessed iPSC-neuron production of ß-amyloid (Aß) Aß40, Aß42, and Aß43 in 24 iPSC lines matched to donor brains with primary neuropathologic diagnoses of sporadic AD (sAD), familial AD (fAD), control, and other neurodegenerative disorders. Our results demonstrate a positive correlation between Aß43 production by fAD iPSC-neurons and Aß43 accumulation in matched brain tissues but do not reveal a substantial correlation in soluble Aß species between control or sAD iPSC-neurons and matched brains. However, we found that the ApoE4 genotype is associated with increased Aß production by AD iPSC-neurons. Pathologic tau phosphorylation was found to be increased in AD and fAD iPSC-neurons compared to controls and positively correlated with the relative abundance of longer-length Aß species produced by these cells. Taken together, our results demonstrate that sAD-predisposing genetic factors influence iPSC-neuron phenotypes and that these cells are capturing disease-relevant and patient-specific components of the amyloid cascade.

Discovery of bivalent small molecule degraders of cyclin-dependent kinase 7 (CDK7).

Cyclin-dependent kinase 7, along with cyclin H and MAT1, forms the CDK-activating complex (CAK), which directs cell cycle progression via T-loop phosphorylation of cell cycle CDKs. Pharmacological inhibition of CDK7 leads to selective anti-cancer effects in cellular and in vivo models, motivating several ongoing clinical investigations of this target. Current CDK7 inhibitors are either reversible or covalent inhibitors of its catalytic activity. We hypothesized that small molecule targeted protein degradation (TPD) might result in differentiated pharmacology due to the loss of scaffolding functions. Here, we report the design and characterization of a potent CDK7 degrader that is comprised of an ATP-competitive CDK7 binder linked to a CRL2VHL recruiter. JWZ-5-13 effectively degrades CDK7 in multiple cancer cells and leads to a potent inhibition of cell proliferation. Additionally, compound JWZ-5-13 displayed bioavailability in a pharmacokinetic study conducted in mice. Therefore, JWZ-5-13 is a useful chemical probe to investigate the pharmacological consequences of CDK7 degradation.

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.

Temporal and spatial topography of cell proliferation in cancer.

Proliferation is a fundamental trait of cancer cells, but its properties and spatial organization in tumours are poorly characterized. Here we use highly multiplexed tissue imaging to perform single-cell quantification of cell cycle regulators and then develop robust, multivariate, proliferation metrics. Across diverse cancers, proliferative architecture is organized at two spatial scales: large domains, and smaller niches enriched for specific immune lineages. Some tumour cells express cell cycle regulators in the (canonical) patterns expected of freely growing cells, a phenomenon we refer to as 'cell cycle coherence'. By contrast, the cell cycles of other tumour cell populations are skewed towards specific phases or exhibit non-canonical (incoherent) marker combinations. Coherence varies across space, with changes in oncogene activity and therapeutic intervention, and is associated with aggressive tumour behaviour. Thus, multivariate measures from high-plex tissue images capture clinically significant features of cancer proliferation, a fundamental step in enabling more precise use of anti-cancer therapies.

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.

The Alzheimer Disease-Causing Presenilin-1 L435F Mutation Causes Increased Production of Soluble Aß43 Species in Patient-Derived iPSC-Neurons, Closely Mimicking Matched Patient Brain Tissue.

Familial Alzheimer disease-causing mutations in Presenilin 1 (PSEN1) are generally thought to shift the processing of APP toward longer, more amyloidogenic Aß fragments. However, certain PSEN1 mutations cause severe reduction in gamma secretase function when expressed in the homozygous state, thus challenging the amyloid hypothesis. We sought to evaluate the effects of one such mutation, PSEN1 L435F, in more physiologic conditions and genetic contexts by using human induced pluripotent stem cell (iPSC)-derived neurons from an individual with familial AD (fAD) linked to the PSEN1 L435F mutation, and compared the biochemical phenotype of the iPS-derived neurons with brain tissue obtained at autopsy from the same patient. Our results demonstrate that in the endogenous heterozygous state, the PSEN1 L435F mutation causes a large increase in soluble Aß43 but does not change the overall levels of soluble Aß40 or Aß42 when compared with control iPSC-neurons. Increased pathologically phosphorylated tau species were also observed in PSEN1-mutant iPSC-neurons. Concordant changes in Aß species were present in autopsy brain tissue from the same patient. Finally, the feasibility of using Aß43 immunohistochemistry of brain tissue to identify fAD cases was evaluated in a limited autopsy case series with the finding that strong Aß43 staining occurred only in fAD cases.

Torin2 Exploits Replication and Checkpoint Vulnerabilities to Cause Death of PI3K-Activated Triple-Negative Breast Cancer Cells.

Frequent mutation of PI3K/AKT/mTOR signaling pathway genes in human cancers has stimulated large investments in targeted drugs but clinical successes are rare. As a result, many cancers with high PI3K pathway activity, such as triple-negative breast cancer (TNBC), are treated primarily with chemotherapy. By systematically analyzing responses of TNBC cells to a diverse collection of PI3K pathway inhibitors, we find that one drug, Torin2, is unusually effective because it inhibits both mTOR and other PI3K-like kinases (PIKKs). In contrast to mTOR-selective inhibitors, Torin2 exploits dependencies on several kinases for S-phase progression and cell-cycle checkpoints, thereby causing accumulation of single-stranded DNA and death by replication catastrophe or mitotic failure. Thus, Torin2 and its chemical analogs represent a mechanistically distinct class of PI3K pathway inhibitors that are uniquely cytotoxic to TNBC cells. This insight could be translated therapeutically by further developing Torin2 analogs or combinations of existing mTOR and PIKK inhibitors.

Development and Characterization of a Wee1 Kinase Degrader.

The G1/S cell cycle checkpoint is frequently dysregulated in cancer, leaving cancer cells reliant on a functional G2/M checkpoint to prevent excessive DNA damage. Wee1 regulates the G2/M checkpoint by phosphorylating CDK1 at Tyr15 to prevent mitotic entry. Previous drug development efforts targeting Wee1 resulted in the clinical-grade inhibitor, AZD1775. However, AZD1775 is burdened by dose-limiting adverse events, and has off-target PLK1 activity. In an attempt to overcome these limitations, we developed Wee1 degraders by conjugating AZD1775 to the cereblon (CRBN)-binding ligand, pomalidomide. The resulting lead compound, ZNL-02-096, degrades Wee1 while sparing PLK1, induces G2/M accumulation at 10-fold lower doses than AZD1775, and synergizes with Olaparib in ovarian cancer cells. We demonstrate that ZNL-02-096 has CRBN-dependent pharmacology that is distinct from AZD1775, which justifies further evaluation of selective Wee1 degraders.

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 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.

Measuring Cancer Drug Sensitivity and Resistance in Cultured Cells.

Measuring the potencies of small-molecule drugs in cell lines is a critical aspect of preclinical pharmacology. Such experiments are also prototypical of high-throughput experiments in multi-well plates. The procedure is simple in principle, but many unrecognized factors can affect the results, potentially making data unreliable. The procedures for measuring drug response described here were developed by the NIH LINCS program to improve reproducibility. Key features include maximizing uniform cell growth during the assay period, accounting for the effects of cell density on response, and correcting sensitivity measures for differences in proliferation rates. Two related protocols are described: one involves an endpoint measure well-suited to large-scale studies and the second is a time-dependent measurement that reveals changes in response over time. The methods can be adapted to other types of plate-based experiments. © 2017 by John Wiley & Sons, Inc.

Common and cell-type specific responses to anti-cancer drugs revealed by high throughput transcript profiling.

More effective use of targeted anti-cancer drugs depends on elucidating the connection between the molecular states induced by drug treatment and the cellular phenotypes controlled by these states, such as cytostasis and death. This is particularly true when mutation of a single gene is inadequate as a predictor of drug response. The current paper describes a data set of ~600 drug cell line pairs collected as part of the NIH LINCS Program ( http://www.lincsproject.org/ ) in which molecular data (reduced dimensionality transcript L1000 profiles) were recorded across dose and time in parallel with phenotypic data on cellular cytostasis and cytotoxicity. We report that transcriptional and phenotypic responses correlate with each other in general, but whereas inhibitors of chaperones and cell cycle kinases induce similar transcriptional changes across cell lines, changes induced by drugs that inhibit intra-cellular signaling kinases are cell-type specific. In some drug/cell line pairs significant changes in transcription are observed without a change in cell growth or survival; analysis of such pairs identifies drug equivalence classes and, in one case, synergistic drug interactions. In this case, synergy involves cell-type specific suppression of an adaptive drug response.

Transforming growth factor-beta promotes inactivation of extracellular thyroid hormones via transcriptional stimulation of type 3 iodothyronine deiodinase.

Thyroid hormone is a critical mediator of cellular metabolism and differentiation. Precise tissue-specific regulation of the concentration of the active ligand, T(3), is achieved by iodothyronine monodeiodination. Type 3 iodothyronine deiodinase (D3) is the major inactivating pathway, preventing activation of the prohormone T(4) and terminating the action of T(3). Using nontransformed human cells, we show that TGF-beta stimulates transcription of the hDio3 gene via a Smad-dependent pathway. Combinations of Smad2 or Smad3 with Smad4 stimulate hDio3 gene transcription only in cells that express endogenous D3 activity, indicating that Smads are necessary but not sufficient for D3 induction. TGF-beta induces endogenous D3 in diverse human cell types, including fetal and adult fibroblasts from several tissues, hemangioma cells, fetal epithelia, and skeletal muscle myoblasts. Maximum stimulation of D3 by TGF-beta also requires MAPK and is synergistic with phorbol ester and several mitogens known to signal through transmembrane receptor tyrosine kinases but not with estradiol. These data reveal a previously unrecognized interaction between two pluripotent systems, TGF-beta and thyroid hormone, both of which have major roles in the regulation of cell growth and differentiation.

Profiles of Basal and stimulated receptor signaling networks predict drug response in breast cancer lines.

Identifying factors responsible for variation in drug response is essential for the effective use of targeted therapeutics. We profiled signaling pathway activity in a collection of breast cancer cell lines before and after stimulation with physiologically relevant ligands, which revealed the variability in network activity among cells of known genotype and molecular subtype. Despite the receptor-based classification of breast cancer subtypes, we found that the abundance and activity of signaling proteins in unstimulated cells (basal profile), as well as the activity of proteins in stimulated cells (signaling profile), varied within each subtype. Using a partial least-squares regression approach, we constructed models that significantly predicted sensitivity to 23 targeted therapeutics. For example, one model showed that the response to the growth factor receptor ligand heregulin effectively predicted the sensitivity of cells to drugs targeting the cell survival pathway mediated by PI3K (phosphoinositide 3-kinase) and Akt, whereas the abundance of Akt or the mutational status of the enzymes in the pathway did not. Thus, basal and signaling protein profiles may yield new biomarkers of drug sensitivity and enable the identification of appropriate therapies in cancers characterized by similar functional dysregulation of signaling networks.

Mice with a targeted deletion of the type 2 deiodinase are insulin resistant and susceptible to diet induced obesity.

BACKGROUND: The type 2 iodothyronine deiodinase (D2) converts the pro-hormone thyroxine into T3 within target tissues. D2 is essential for a full thermogenic response of brown adipose tissue (BAT), and mice with a disrupted Dio2 gene (D2KO) have an impaired response to cold. BAT is also activated by overfeeding. METHODOLOGY/PRINCIPAL FINDINGS: After 6-weeks of HFD feeding D2KO mice gained 5.6% more body weight and had 28% more adipose tissue. Oxygen consumption (V0(2)) was not different between genotypes, but D2KO mice had an increased respiratory exchange ratio (RER), suggesting preferential use of carbohydrates. Consistent with this, serum free fatty acids and ß-hydroxybutyrate were lower in D2KO mice on a HFD, while hepatic triglycerides were increased and glycogen content decreased. Neither genotype showed glucose intolerance, but D2KO mice had significantly higher insulin levels during GTT independent of diet. Accordingly, during ITT testing D2KO mice had a significantly reduced glucose uptake, consistent with insulin resistance. Gene expression levels in liver, muscle, and brown and white adipose tissue showed no differences that could account for the increased weight gain in D2KO mice. However, D2KO mice have higher PEPCK mRNA in liver suggesting increased gluconeogenesis, which could also contribute to their apparent insulin resistance. CONCLUSIONS/SIGNIFICANCE: We conclude that the loss of the Dio2 gene has significant metabolic consequences. D2KO mice gain more weight on a HFD, suggesting a role for D2 in protection from diet-induced obesity. Further, D2KO mice appear to have a greater reliance on carbohydrates as a fuel source, and limited ability to mobilize and to burn fat. This results in increased fat storage in adipose tissue, hepatic steatosis, and depletion of liver glycogen in spite of increased gluconeogenesis. D2KO mice are also less responsive to insulin, independent of diet-induced obesity.