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.

Integrating multi-omics data reveals function and therapeutic potential of deubiquitinating enzymes.

Deubiquitinating enzymes (DUBs), ~100 of which are found in human cells, are proteases that remove ubiquitin conjugates from proteins, thereby regulating protein turnover. They are involved in a wide range of cellular activities and are emerging therapeutic targets for cancer and other diseases. Drugs targeting USP1 and USP30 are in clinical development for cancer and kidney disease respectively. However, the majority of substrates and pathways regulated by DUBs remain unknown, impeding efforts to prioritize specific enzymes for research and drug development. To assemble a knowledgebase of DUB activities, co-dependent genes, and substrates, we combined targeted experiments using CRISPR libraries and inhibitors with systematic mining of functional genomic databases. Analysis of the Dependency Map, Connectivity Map, Cancer Cell Line Encyclopedia, and multiple protein-protein interaction databases yielded specific hypotheses about DUB function, a subset of which were confirmed in follow-on experiments. The data in this paper are browsable online in a newly developed DUB Portal and promise to improve understanding of DUBs as a family as well as the activities of incompletely characterized DUBs (e.g. USPL1 and USP32) and those already targeted with investigational cancer therapeutics (e.g. USP14, UCHL5, and USP7).

A Semi-Quantitative Isothermal Diagnostic Assay Utilizing Competitive Amplification.

Quantitative diagnostics that are rapid, inexpensive, sensitive, robust, and field-deployable are needed to contain the spread of infectious diseases and inform treatment strategies. While current gold-standard techniques are highly sensitive and quantitative, they are slow and require expensive equipment. Conversely, current rapid field-deployable assays available provide essentially binary information about the presence of the target analyte, not a quantitative measure of concentration. Here, we report the development of a molecular diagnostic test [quantitative recombinase polymerase amplification (qRPA)] that utilizes competitive amplification during a recombinase polymerase amplification (RPA) assay to provide semi-quantitative information on a target nucleic acid. We demonstrate that qRPA can quantify DNA, RNA, and viral titers in HIV and COVID-19 patient samples and that it is more robust to environmental perturbations than traditional RPA. These features make qRPA potentially useful for at-home testing to monitor the progress of viral infections or other diseases.

Accessioning and automation compatible anterior nares swab design.

The COVID-19 pandemic has resulted in an unparalleled need for viral testing capacity across the world and is a critical requirement for successful re-opening of economies. The logistical barriers to near-universal testing are considerable. We have designed an injection molded polypropylene anterior nares swab, the Rhinostic, with a screw cap integrated into the swab handle that is compatible with fully automated sample accessioning and processing. The ability to collect and release both human and viral material is comparable to that of several commonly used swabs on the market. SARS-CoV-2 is stable on dry Rhinostic swabs for at least 3 days, even at 42 °C, and elution can be achieved with small volumes. To test the performance of the Rhinostic in patients, 119 samples were collected with Rhinostic and the positive and negative determinations were 100 % concordant with samples collected using Clinical Laboratory Improvement Amendments (CLIA) use approved nasal swabs at a clinical lab. The Rhinostic swab and barcoded tube set can be produced, sterilized, and packaged cost effectively and is designed to be adopted by clinical laboratories using automation to increase throughput and dramatically reduce the cost of a standard SARS-CoV-2 detection pipeline.

Targeting immunosuppressive macrophages overcomes PARP inhibitor resistance in BRCA1-associated triple-negative breast cancer.

Despite objective responses to PARP inhibition and improvements in progression-free survival compared to standard chemotherapy in patients with BRCA-associated triple-negative breast cancer (TNBC), benefits are transitory. Using high dimensional single-cell profiling of human TNBC, here we demonstrate that macrophages are the predominant infiltrating immune cell type in BRCA-associated TNBC. Through multi-omics profiling we show that PARP inhibitors enhance both anti- and pro-tumor features of macrophages through glucose and lipid metabolic reprogramming driven by the sterol regulatory element-binding protein 1 (SREBP-1) pathway. Combined PARP inhibitor therapy with CSF-1R blocking antibodies significantly enhanced innate and adaptive anti-tumor immunity and extends survival in BRCA-deficient tumors in vivo and is mediated by CD8+ T-cells. Collectively, our results uncover macrophage-mediated immune suppression as a liability of PARP inhibitor treatment and demonstrate combined PARP inhibition and macrophage targeting therapy induces a durable reprogramming of the tumor microenvironment, thus constituting a promising therapeutic strategy for TNBC.

Machine learning identifies candidates for drug repurposing in Alzheimer's disease.

Clinical trials of novel therapeutics for Alzheimer's Disease (AD) have consumed a large amount of time and resources with largely negative results. Repurposing drugs already approved by the Food and Drug Administration (FDA) for another indication is a more rapid and less expensive option. We present DRIAD (Drug Repurposing In AD), a machine learning framework that quantifies potential associations between the pathology of AD severity (the Braak stage) and molecular mechanisms as encoded in lists of gene names. DRIAD is applied to lists of genes arising from perturbations in differentiated human neural cell cultures by 80 FDA-approved and clinically tested drugs, producing a ranked list of possible repurposing candidates. Top-scoring drugs are inspected for common trends among their targets. We propose that the DRIAD method can be used to nominate drugs that, after additional validation and identification of relevant pharmacodynamic biomarker(s), could be readily evaluated in a clinical trial.

An enhanced isothermal amplification assay for viral detection.

Rapid, inexpensive, robust diagnostics are essential to control the spread of infectious diseases. Current state of the art diagnostics are highly sensitive and specific, but slow, and require expensive equipment. Here we report the development of a molecular diagnostic test for SARS-CoV-2 based on an enhanced recombinase polymerase amplification (eRPA) reaction. eRPA has a detection limit on patient samples down to 5 viral copies, requires minimal instrumentation, and is highly scalable and inexpensive. eRPA does not cross-react with other common coronaviruses, does not require RNA purification, and takes ~45 min from sample collection to results. eRPA represents a first step toward at-home SARS-CoV-2 detection and can be adapted to future viruses within days of genomic sequence availability.

An enhanced isothermal amplification assay for viral detection.

Rapid, inexpensive, robust diagnostics are essential to control the spread of infectious diseases. Current state of the art diagnostics are highly sensitive and specific, but slow, and require expensive equipment. We developed a molecular diagnostic test for SARS-CoV-2, FIND (Fast Isothermal Nucleic acid Detection), based on an enhanced isothermal recombinase polymerase amplification reaction. FIND has a detection limit on patient samples close to that of RT-qPCR, requires minimal instrumentation, and is highly scalable and cheap. It can be performed in high throughput, does not cross-react with other common coronaviruses, avoids bottlenecks caused by the current worldwide shortage of RNA isolation kits, and takes ~45 minutes from sample collection to results. FIND can be adapted to future novel viruses in days once sequence is available. ONE SENTENCE SUMMARY: Sensitive, specific, rapid, scalable, enhanced isothermal amplification method for detecting SARS-CoV-2 from patient samples.

Barcoded microbial system for high-resolution object provenance.

Determining where an object has been is a fundamental challenge for human health, commerce, and food safety. Location-specific microbes in principle offer a cheap and sensitive way to determine object provenance. We created a synthetic, scalable microbial spore system that identifies object provenance in under 1 hour at meter-scale resolution and near single-spore sensitivity and can be safely introduced into and recovered from the environment. This system solves the key challenges in object provenance: persistence in the environment, scalability, rapid and facile decoding, and biocontainment. Our system is compatible with SHERLOCK, a Cas13a RNA-guided nucleic acid detection assay, facilitating its implementation in a wide range of applications.

Selective USP7 inhibition elicits cancer cell killing through a p53-dependent mechanism.

Ubiquitin specific peptidase 7 (USP7) is a deubiquitinating enzyme (DUB) that removes ubiquitin tags from specific protein substrates in order to alter their degradation rate and sub-cellular localization. USP7 has been proposed as a therapeutic target in several cancers because it has many reported substrates with a role in cancer progression, including FOXO4, MDM2, N-Myc, and PTEN. The multi-substrate nature of USP7, combined with the modest potency and selectivity of early generation USP7 inhibitors, has presented a challenge in defining predictors of response to USP7 and potential patient populations that would benefit most from USP7-targeted drugs. Here, we describe the structure-guided development of XL177A, which irreversibly inhibits USP7 with sub-nM potency and selectivity across the human proteome. Evaluation of the cellular effects of XL177A reveals that selective USP7 inhibition suppresses cancer cell growth predominantly through a p53-dependent mechanism: XL177A specifically upregulates p53 transcriptional targets transcriptome-wide, hotspot mutations in TP53 but not any other genes predict response to XL177A across a panel of ~500 cancer cell lines, and TP53 knockout rescues XL177A-mediated growth suppression of TP53 wild-type (WT) cells. Together, these findings suggest TP53 mutational status as a biomarker for response to USP7 inhibition. We find that Ewing sarcoma and malignant rhabdoid tumor (MRT), two pediatric cancers that are sensitive to other p53-dependent cytotoxic drugs, also display increased sensitivity to XL177A.

Multi omics analysis of fibrotic kidneys in two mouse models.

Kidney fibrosis represents an urgent unmet clinical need due to the lack of effective therapies and an inadequate understanding of the molecular pathogenesis. We have generated a comprehensive and combined multi-omics dataset (proteomics, mRNA and small RNA transcriptomics) of fibrotic kidneys that is searchable through a user-friendly web application: http://hbcreports.med.harvard.edu/fmm/ . Two commonly used mouse models were utilized: a reversible chemical-induced injury model (folic acid (FA) induced nephropathy) and an irreversible surgically-induced fibrosis model (unilateral ureteral obstruction (UUO)). mRNA and small RNA sequencing, as well as 10-plex tandem mass tag (TMT) proteomics were performed with kidney samples from different time points over the course of fibrosis development. The bioinformatics workflow used to process, technically validate, and combine the single omics data will be described. In summary, we present temporal multi-omics data from fibrotic mouse kidneys that are accessible through an interrogation tool (Mouse Kidney Fibromics browser) to provide a searchable transcriptome and proteome for kidney fibrosis researchers.

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.

Adaptation of Human iPSC-Derived Cardiomyocytes to Tyrosine Kinase Inhibitors Reduces Acute Cardiotoxicity via Metabolic Reprogramming.

Tyrosine kinase inhibitors (TKIs) are widely used to treat solid tumors but can be cardiotoxic. The molecular basis for this toxicity and its relationship to therapeutic mechanisms remain unclear; we therefore undertook a systems-level analysis of human cardiomyocytes (CMs) exposed to four TKIs. CMs differentiated from human induced pluripotent stem cells (hiPSCs) were exposed to sunitinib, sorafenib, lapatinib, or erlotinib, and responses were assessed by functional assays, microscopy, RNA sequencing, and mass spectrometry (GEO: GSE114686; PRIDE: PXD012043). TKIs have diverse effects on hiPSC-CMs distinct from inhibition of tyrosine-kinase-mediated signal transduction; cardiac metabolism is particularly sensitive. Following sorafenib treatment, oxidative phosphorylation is downregulated, resulting in a profound defect in mitochondrial energetics. Cells adapt by upregulating aerobic glycolysis. Adaptation makes cells less acutely sensitive to sorafenib but may have long-term negative consequences. Thus, CMs exhibit adaptive responses to anti-cancer drugs conceptually similar to those previously shown in tumors to mediate drug resistance.

Tubulin mRNA stability is sensitive to change in microtubule dynamics caused by multiple physiological and toxic cues.

The localization, mass, and dynamics of microtubules are important in many processes. Cells may actively monitor the state of their microtubules and respond to perturbation, but how this occurs outside mitosis is poorly understood. We used gene-expression analysis in quiescent cells to analyze responses to subtle and strong perturbation of microtubules. Genes encoding α-, ß, and γ-tubulins (TUBAs, TUBBs, and TUBGs), but not δ- or ε-tubulins (TUBDs or TUBEs), exhibited the strongest differential expression response to microtubule-stabilizing versus destabilizing drugs. Quantitative PCR of exon versus intron sequences confirmed that these changes were caused by regulation of tubulin mRNA stability and not transcription. Using tubulin mRNA stability as a signature to query the Gene Expression Omnibus (GEO) database, we find that tubulin genes respond to toxins known to damage microtubules. Importantly, we find many other experimental perturbations, including multiple signaling and metabolic inputs that trigger tubulin differential expression, suggesting their novel, to our knowledge, role in the regulation of the microtubule cytoskeleton. Mechanistic follow-up confirms that one important physiological signal, phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K) activity, indeed regulates tubulin mRNA stability via changes in microtubule dynamics. We propose that tubulin gene expression is regulated as part of many coordinated biological responses, with wide implications in physiology and toxicology. Furthermore, we present a new way to discover microtubule regulation using transcriptomics.

A High-Throughput Screen Identifies DYRK1A Inhibitor ID-8 that Stimulates Human Kidney Tubular Epithelial Cell Proliferation.

BACKGROUND: The death of epithelial cells in the proximal tubules is thought to be the primary cause of AKI, but epithelial cells that survive kidney injury have a remarkable ability to proliferate. Because proximal tubular epithelial cells play a predominant role in kidney regeneration after damage, a potential approach to treat AKI is to discover regenerative therapeutics capable of stimulating proliferation of these cells. METHODS: We conducted a high-throughput phenotypic screen using 1902 biologically active compounds to identify new molecules that promote proliferation of primary human proximal tubular epithelial cells in vitro. RESULTS: The primary screen identified 129 compounds that stimulated tubular epithelial cell proliferation. A secondary screen against these compounds over a range of four doses confirmed that eight resulted in a significant increase in cell number and incorporation of the modified thymidine analog EdU (indicating actively proliferating cells), compared with control conditions. These eight compounds also stimulated tubular cell proliferation in vitro after damage induced by hypoxia, cadmium chloride, cyclosporin A, or polymyxin B. ID-8, an inhibitor of dual-specificity tyrosine-phosphorylation-regulated kinase 1A (DYRK1A), was the top candidate identified as having a robust proproliferative effect in two-dimensional culture models as well as a microphysiologic, three-dimensional cell culture system. Target engagement and genetic knockdown studies and RNA sequencing confirmed binding of ID-8 to DYRK1A and upregulation of cyclins and other cell cycle regulators, leading to epithelial cell proliferation. CONCLUSIONS: We have identified a potential first-in-class compound that stimulates human kidney tubular epithelial cell proliferation after acute damage in vitro.

Total RNA-seq to identify pharmacological effects on specific stages of mRNA synthesis.

Pharmacological perturbation is a powerful tool for understanding mRNA synthesis, but identification of the specific steps of this multi-step process that are targeted by small molecules remains challenging. Here we applied strand-specific total RNA sequencing (RNA-seq) to identify and distinguish specific pharmacological effects on transcription and pre-mRNA processing in human cells. We found unexpectedly that the natural product isoginkgetin, previously described as a splicing inhibitor, inhibits transcription elongation. Compared to well-characterized elongation inhibitors that target CDK9, isoginkgetin caused RNA polymerase accumulation within a broader promoter-proximal band, indicating that elongation inhibition by isoginkgetin occurs after release from promoter-proximal pause. RNA-seq distinguished isoginkgetin and CDK9 inhibitors from topoisomerase I inhibition, which alters elongation across gene bodies. We were able to detect these and other specific defects in mRNA synthesis at low sequencing depth using simple metagene-based metrics. These metrics now enable total-RNA-seq-based screening for high-throughput identification of pharmacological effects on individual stages of mRNA synthesis.

Adaptive resistance of melanoma cells to RAF inhibition via reversible induction of a slowly dividing de-differentiated state.

Treatment of BRAF-mutant melanomas with MAP kinase pathway inhibitors is paradigmatic of the promise of precision cancer therapy but also highlights problems with drug resistance that limit patient benefit. We use live-cell imaging, single-cell analysis, and molecular profiling to show that exposure of tumor cells to RAF/MEK inhibitors elicits a heterogeneous response in which some cells die, some arrest, and the remainder adapt to drug. Drug-adapted cells up-regulate markers of the neural crest (e.g., NGFR), a melanocyte precursor, and grow slowly. This phenotype is transiently stable, reverting to the drug-naïve state within 9 days of drug withdrawal. Transcriptional profiling of cell lines and human tumors implicates a c-Jun/ECM/FAK/Src cascade in de-differentiation in about one-third of cell lines studied; drug-induced changes in c-Jun and NGFR levels are also observed in xenograft and human tumors. Drugs targeting the c-Jun/ECM/FAK/Src cascade as well as BET bromodomain inhibitors increase the maximum effect (Emax) of RAF/MEK kinase inhibitors by promoting cell killing. Thus, analysis of reversible drug resistance at a single-cell level identifies signaling pathways and inhibitory drugs missed by assays that focus on cell populations.

Abundance-based classifier for the prediction of mass spectrometric peptide detectability upon enrichment (PPA).

The function of a large percentage of proteins is modulated by post-translational modifications (PTMs). Currently, mass spectrometry (MS) is the only proteome-wide technology that can identify PTMs. Unfortunately, the inability to detect a PTM by MS is not proof that the modification is not present. The detectability of peptides varies significantly making MS potentially blind to a large fraction of peptides. Learning from published algorithms that generally focus on predicting the most detectable peptides we developed a tool that incorporates protein abundance into the peptide prediction algorithm with the aim to determine the detectability of every peptide within a protein. We tested our tool, "Peptide Prediction with Abundance" (PPA), on in-house acquired as well as published data sets from other groups acquired on different instrument platforms. Incorporation of protein abundance into the prediction allows us to assess not only the detectability of all peptides but also whether a peptide of interest is likely to become detectable upon enrichment. We validated the ability of our tool to predict changes in protein detectability with a dilution series of 31 purified proteins at several different concentrations. PPA predicted the concentration dependent peptide detectability in 78% of the cases correctly, demonstrating its utility for predicting the protein enrichment needed to observe a peptide of interest in targeted experiments. This is especially important in the analysis of PTMs. PPA is available as a web-based or executable package that can work with generally applicable defaults or retrained from a pilot MS data set.